Co-assisted strategy of sacrificial salt-template and nitrogen-doping to promote lithium storage performance of NiO-Ni/N-C frameworks

Tailoring the omnidirectional conductivity networks in nickel oxide-based electrodes is important for ensuring their long lifespan, stability, high capacity, and high-rate capability. In this study, nickel metal nanoparticles and a three-dimensional nitrogen-doped carbon matrix were used to embellish the nickel oxide composite NiO-Ni/N-C via simplified hard templating. When a porous nitrogen-doped carbon matrix is present, a rapid pathway would be established for charging and discharging the electrons and lithium ions in a lithium-ion battery, thereby alleviating the volumetric expansion of the NiO nanoparticles during the operation of the battery. Moreover, the Ni0 ions added to serve as active sites to improve the capacity of the NiO-based electrodes and strengthen their conductivities. The multielement-effects of the optimal NiO-Ni/N-C electrode leads it to exhibit a capacity of 1310.8 mAh g-1 at 0.1 A g-1 for 120 loops and a rate capability of 441.5 mAh g-1 at 20.0 A g-1. Kinetic analysis of the prepared electrodes proved their ultrafast ionic and electronic conductivities. This strategy of hard templating reduces the number of routes required for preparing different types of electrodes, including NiO-based electrodes, and improves their electrochemical performance to enable their use in energy storage applications.

Low-intensity alternating ventilation achieves effective humification during food waste composting by enhancing the intensity of microbial interaction and carbon metabolism

Vertical static composting is an efficient and convenient technology for the treatment of food waste. Exploring the impact of oxygen concentration levels on microbial community structure and functional stability is crucial for optimizing ventilation technology. This study set three experimental groups with varying ventilation intensities based on self-made alternating ventilation composting reactor (AL2: 0.2 L kg-1 DM·min-1; AL4: 0.4 L kg-1 DM·min-1; AL6: 0.6 L kg-1 DM·min-1) to explore the optimal alternating ventilation rate. The results showed that the cumulative ammonia emission of AL2 group reduced by 25.13% and 12.59% compared to the AL4 and AL6 groups. The humification degree of the product was 1.18 times and 1.25 times higher than the other two groups. AL2 increased the relative abundance of the core species Saccharomonospora, thereby strengthening microbial interaction. Low-intensity alternating ventilation increased the carbon metabolism levels, especially aerobic_chemoheterotrophy, carbohydrate and lipid metabolism. However, it simultaneously reduced nitrogen metabolism. Structural equation model analysis demonstrated that alternating low-intensity ventilation effectively regulated both microbial diversity (0.81, p < 0.001) and metabolism (0.81, p < 0.001) by shaping the composting environment. This study optimized the intensity of alternating ventilation and revealed the regulatory mechanism of community structure and metabolism. This study provides guidance for achieving efficient and low-consumption composting.

[Methylthioadenosine phosphorylase and p16 as surrogate diagnostic markers for CDKN2A homozygous deletion in brain tumors]

Objective: To examine whether immunohistochemistry of methylthioadenosine phosphorylase (MTAP) and p16 could be used to predict the CDKN2A status in various brain tumors. Methods: A total of 118 cases of IDH-mutant astrocytomas, 16 IDH-wildtype glioblastoma, 17 polymorphic xanthoastrocytoma (PXA) and 20 meningiomas diagnosed at Xuanwu Hospital, Capital Medical University, Beijing, China from November 2017 to October 2023 were collected and analyzed. The CDKN2A status was detected by using fluorescence in situ hybridization or next-generation sequencing. Expression of MTAP and p16 proteins was detected with immunohistochemistry. The association of loss of MTAP/p16 expression with CDKN2A homozygous/heterozygous deletion was examined. Results: Among the 118 cases of IDH-mutant astrocytoma, 13 cases showed homozygous deletion of CDKN2A. All of them had no expression of MTAP while 9 cases had no expression of p16. Among the 16 cases of IDH wild-type glioblastoma, 6 cases showed homozygous deletion of CDKN2A. All 6 cases had no expression of MTAP, while 3 of these cases had no expression of p16 expression. Among the 17 PXA cases, 4 cases showed homozygous deletion of CDKN2A, and the expression of MTAP and p16 was also absent in these 4 cases. Among the 20 cases of meningiomas, 4 cases showed homozygous deletion of CDKN2A. Their expression of MTAP and p16 was also absent. Among the four types of brain tumors, MTAP was significantly correlated with CDKN2A homozygous deletion (P<0.05), with a sensitivity of 100%. However, it was only significantly correlated with the loss of heterozygosity (LOH) of CDKN2A in astrocytomas (P<0.001). P16 was associated with CDKN2A homozygous deletion in IDH-mutant astrocytoma and PXA (P<0.001), but not with the LOH of CDKN2A. Its sensitivity and specificity were lower than that of MTAP. Conclusions: MTAP could serve as a predictive surrogate for CDKN2A homozygous deletion in adult IDH-mutant astrocytoma, PXA, adult IDH-wildtype glioblastoma and meningioma. However, p16 could only be used in the first two tumor types, and its specificity and sensitivity are lower than that of MTAP.

[Analysis of the application effect and safety of transnasal humidified rapid insufflation ventilatory exchange technique in hysteroscopic diagnostic and therapeutic surgery]

Objective: To investigate the effect and safety of transnasal humidified rapid insufflation ventilatory exchange (THRIVE) technique in hysteroscopic diagnostic and therapeutic surgery. Methods: This study was a randomized controlled trial. A total of 100 female patients undergoing hysteroscopy surgery at Beijing Tongren Hospital from September to December 2023 were selected and randomly divided into two groups by the random number table method: the THRIVE group and the mask oxygen group, with 50 patients in each group. Patients in both groups were given total intravenous anesthesia with propofol combined with remifentanil and preserved spontaneous respiration. The THRIVE group was given oxygen by the THRIVE device with an oxygen flow rate of 50 L/min, while the mask oxygen group was given oxygen by the mask with an oxygen flow rate of 5 L/min; the oxygen concentration of both groups was set at 100%. The general condition of the patients, vital signs during the operation, the amount of anesthesia drugs used and the operation time were recorded. The primary observation index was the incidence of hypoxic events in the two groups; the secondary observation indexes were the incidence and time of intraoperative apnea as well as the corresponding oxygenation interventions and the incidence of non-hypoxic adverse events. Results: The age of the THRIVE group was (42±14) years, and the age of the mask oxygen group was (43±15) years. The duration of surgery in the THRIVE group was (15.9±3.4) min, which was statistically lower than that of the mask oxygen group (16.3±4.5) min (P=0.041), and there were no differences observed in the duration of awakening time and anesthesia time (both P>0.05). There was no significant difference in the dosage of propofol, remifentanil, and intraoperative vasoactive drugs between the two groups (all P>0.05). The SpO2 of the patients in the THRIVE group at the end of the operation was (99.7±1.1) %, which was higher than that of the mask-oxygen group (99.1±1.1) % (P<0.05). There was no difference in SpO2 of the two groups at the other time points (all P>0.05). There were no differences in HR and MAP of two group patients at each time point (all P>0.05). The incidence of hypoxic events in the THRIVE group was 12.0% (6/50), which was lower than that of 28.0% (14/50) in the mask oxygen group (P=0.045). The difference in the incidence and duration of apnea between the two groups was not statistically significant (all P>0.05). There were no cases of temporary need for laryngeal mask or tracheal intubation during surgery in both groups. There was no statistically significant difference in the incidence of intraoperative body movement, dizziness, nausea and vomiting between the two groups (all P>0.05), and no cardiac, cerebral, renal or other important organ insufficiency occurred in the two weeks after surgery. Conclusion: THRIVE technology can provide effective oxygenation for patients undergoing hysteroscopic diagnosis and treatment, maintain patients' circulatory stability, and improve the safety and efficiency of surgery.

Label-free Raman spectroscopy reveals tumor microenvironmental changes induced by intermittent fasting for the prevention of breast cancer in animal model

The development of tools that can provide a holistic picture of the evolution of the tumor microenvironment in response to intermittent fasting on the prevention of breast cancer is highly desirable. Here, we show, for the first time, the use of label-free Raman spectroscopy to reveal biomolecular alterations induced by intermittent fasting in the tumor microenvironment of breast cancer using a dimethyl-benzanthracene induced rat model. To quantify biomolecular alterations in the tumor microenvironment, chemometric analysis of Raman spectra obtained from untreated and treated tumors was performed using multivariate curve resolution-alternative least squares and support vector machines. Raman measurements revealed remarkable and robust differences in lipid, protein, and glycogen content prior to morphological manifestations in a dynamically changing tumor microenvironment, consistent with the proteomic changes observed by quantitative mass spectrometry. Taken together with its non-invasive nature, this research provides prospective evidence for the clinical translation of Raman spectroscopy to identify biomolecular variations in the microenvironment induced by intermittent fasting for the prevention of breast cancer, providing new perspectives on the specific molecular effects in the tumorigenesis of breast cancer.

[HBeAg-positive patients hepatic tissue inflammatory activity and influencing factors during normal ALT and indeterminate phases]

Objective: To analyze the hepatic tissue inflammatory activity and influencing factors in HBeAg-positive patients during normal alanine aminotransferase (ALT) and indeterminate phases so as to provide a basis for evaluating the disease condition. Methods: Patients with HBeAg-positive with normal ALT and HBV DNA levels below 2 × 10(7) IU/ml from January 2017 to December 2021 were selected as the study subjects. A histopathologic liver test was performed on these patients. Age, gender, time of HBV infection, liver function, HBsAg level, HBV DNA load, genotype, portal vein inner diameter, splenic vein inner diameter, splenic thickness, and others of the patients were collected. Significant influencing factors of inflammation were analyzed in patients using logistic regression analysis, and its effectiveness was evaluated using receiver operating characteristic (ROC) curves. Results: Of the 178 cases, there were 0 cases of inflammation in G0, 52 cases in G1, 101 cases in G2, 24 cases in G3, and one case in G4. 126 cases (70.8%) had inflammatory activity ≥ G2. Infection time (Z=-7.138, P<0.001), γ-glutamyltransferase (t =-2.940, P=0.004), aspartate aminotransferase (t =-2.749, P=0.007), ALT (t =-2.153, P=0.033), HBV DNA level (t =-4.771, P=0.010) and portal vein inner diameter (t =-4.771, P<0.001) between the ≥G2 group and < G2 group were statistically significantly different. A logistic regression analysis showed that significant inflammation in liver tissue was independently correlated with infection time [odds ratio (OR)=1.437, 95% confidence interval (CI): 1.267-1.630; P<0.001)] and portal vein inner diameter (OR=2.738, 95% CI: 1.641, 4.570; P<0.001). The area under the curve (AUROC), specificity, and sensitivity for infection time and portal vein inner diameter were 0.84, 0.71, 0.87, 0.72, 0.40, and 0.95, respectively. Conclusion: A considerable proportion of HBeAg-positive patients have inflammation grade ≥G2 during normal ALT and indeterminate phases, pointing to the need for antiviral therapy. Additionally, inflammatory activity has a close association with the time of infection and portal vein inner diameter.

Observation of Structures in the Processes e^{+}e^{-}→ωχ_{c1} and ωχ_{c2}

We present measurements of the Born cross sections for the processes e^{+}e^{-}→ωχ_{c1} and ωχ_{c2} at center-of-mass energies sqrt[s] from 4.308 to 4.951 GeV. The measurements are performed with data samples corresponding to an integrated luminosity of 11.0  fb^{-1} collected with the BESIII detector operating at the Beijing Electron Positron Collider storage ring. Assuming the e^{+}e^{-}→ωχ_{c2} signals come from a single resonance, the mass and width are determined to be M=(4413.6±9.0±0.8)  MeV/c^{2} and Γ=(110.5±15.0±2.9)  MeV, respectively, which is consistent with the parameters of the well-established resonance ψ(4415). In addition, we also use one single resonance to describe the e^{+}e^{-}→ωχ_{c1} line shape and determine the mass and width to be M=(4544.2±18.7±1.7)  MeV/c^{2} and Γ=(116.1±33.5±1.7)  MeV, respectively. The structure of this line shape, observed for the first time, requires further understanding.

[The mechanical ventilation guided by electrical impedance tomography in acute respiratory distress syndrome]

Acute respiratory distress syndrome (ARDS) is a common and critical clinical condition characterized by diffuse damage to the lung interstitium, alveoli, and increased permeability of pulmonary blood vessels. CT can be used to assess the imaging features, severity, and prediction of ARDS, but it requires patient transportation to the CT room and is only a static examination. Electrical impedance tomography (EIT) is an increasingly widely used monitoring tool in clinical applications in recent years. It enables continuous real-time assessment of lung ventilation distribution at the bedside and has high clinical value in optimizing mechanical ventilation parameters for critically ill patients. This article introduces the basic principles of EIT and how to better utilize EIT technology to guide mechanical ventilation treatment for ARDS patients.

[New 2023 global definition of acute respiratory distress syndrome: progress and limitation]

Acute respiratory distress syndrome (ARDS) presents a challenge in clinical diagnosis as it lacks a definitive gold standard. Over the past 55 years, there have been several revisions to the definition of ARDS. With the progress of clinical practice and scientific research, the limitations of the "Berlin definition" have become increasingly evident. In response to these changes, the 2023 global definition of ARDS aims to address these issues by expanding the diagnostic targets, chest imaging, and methods for assessing hypoxia. Additionally, the new definition increases the diagnostic criteria to accommodate resource-constrained settings. The expansion facilitates early identification and treatment interventions for ARDS, thereby advancing epidemiological and clinically related research. Nevertheless, the broad nature of this revision may include patients who do not actually have ARDS, thus raising the risk of false-positive diagnoses. Therefore, additional verification is crucial to ascertain the validity and accuracy of the 2023 global definition of ARDS.

Effects of moxibustion with wheat-grain size cone at "Zusanli" (ST 36) on vascular injury and oxidative stress in high-fat diet rats through mTOR/HIF-1α/VEGF signaling pathway

OBJECTIVES

To explore the effect mechanism of moxibustion with wheat-grain size cone at "Zusanli" (ST 36) on vascular injury and oxidative stress in hyperlipidemia through mammalian target of rapamycin (mTOR)/hypoxia inducible factor-1α (HIF-1α)/vascular endothelial growth factor (VEGF) signaling pathway.

METHODS

Forty healthy male SD rats with SPF grade were randomly divided into a normal group, a model group, a moxibustion group, and an inhibitor group, with 10 rats in each one. The hyperlipidemia model was established by feeding a high-fat diet for 8 weeks in rats of the model group, the moxibustion group and the inhibitor group. The moxibustion with wheat-grain size cone was delivered at bilateral "Zusanli" (ST 36) of each rat in the moxibustion group and the inhibitor group, with 3 cones on each acupoint in each intervention, once daily for 4 weeks. In the inhibitor group, before each intervention with moxibustion, rapamycin solution was injected intraperitoneally, 2.0 mg/kg. After modeling and intervention, using ELISA, the levels of total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) in the serum of rats were determined. After intervention, with HE staining and oil red O staining adopted, the abdominal aortic morphology and peripheral lipid deposition were observed. Separately, using WST-1, TBA and micro-plate method, the superoxide dismutase (SOD) activity and the levels of malondialdehyde (MDA) and nitric oxide (NO) in the serum were detected. The protein expression of mTOR, HIF-1α and VEGF in abdominal aorta were measured by Western blot method.

RESULTS

Compared with those in the normal group, the levels of TC, TG and LDL-C increased (P<0.01) and HDL-C decreased (P<0.01) in the serum of the rats in the model group, the moxibustion group and the inhibitor group after model establishment. When compared with the normal group after intervention, in the model group, the serum levels of TC, TG, LDL-C and MDA increased (P<0.01), HDL-C level, SOD activity and NO level were reduced (P<0.01); the cell structure of the abdominal arota was abnormal, the peripheral lipids deposited seriously; and the protein expression of mTOR, HIF-1α and VEGF of abdominal aorta was elevated (P<0.01, P<0.05). In comparison with the model group, the levels of TC, TG, LDL-C and MDA were reduced (P<0.01), HDL-C levels, SOD activities and NO levels elevated (P<0.01, P<0.05), as well as the protein expression of mTOR, HIF-1α and VEGF of abdominal aorta (P<0.01, P<0.05) in the moxibustion group and the inhibitor group; besides, the vascular structure was ameliorated and the lipid deposition reduced in the moxibustion group, while, the vascular structure was still abnormal and the lipid deposition declined in the inhibitor group. When compared with the inhibitor group, the serum SOD activity and NO level increased (P<0.05) and MDA decreased (P<0.05); and the protein expression of mTOR, HIF-1α and VEGF of abdominal aorta was elevated (P<0.01, P<0.05) in the moxibustion group.

CONCLUSIONS

The vascular injury due to hyperlipidemia is repaired by moxibustion with wheat-grain size cone at "Zusanli" (ST 36) through ameliorating oxidative stress, which is associated potentially with the modulation of mTOR/HIF-1α/VEGF signaling pathway.

Coupled-Channel Analysis of the χ_{c1}(3872) Line Shape with BESIII Data

We perform a study of the χ_{c1}(3872) line shape using the data samples of e^{+}e^{-}→γχ_{c1}(3872), χ_{c1}(3872)→D^{0}D[over ¯]^{0}π^{0}, and π^{+}π^{-}J/ψ collected with the BESIII detector. The effects of the coupled channels and the off-shell D^{*0} are included in the parametrization of the line shape. The line shape mass parameter is obtained to be M_{X}=(3871.63±0.13_{-0.05}^{+0.06})  MeV. Two poles are found on the first and second Riemann sheets corresponding to the D^{*0}D[over ¯]^{0} branch cut. The pole location on the first sheet is much closer to the D^{*0}D[over ¯]^{0} threshold than the other, and is determined to be 7.04±0.15_{-0.08}^{+0.07}  MeV above the D^{0}D[over ¯]^{0}π^{0} threshold with an imaginary part -0.19±0.08_{-0.19}^{+0.14}  MeV.

Observation of the Anomalous Shape of X(1840) in J/ψ→γ3(π^{+}π^{-}) Indicating a Second Resonance Near pp[over ¯] Threshold

Using a sample of (10087±44)×10^{6}  J/ψ events, which is about 45 times larger than that was previously analyzed, a further investigation on the J/ψ→γ3(π^{+}π^{-}) decay is performed. A significant distortion at 1.84  GeV/c^{2} in the line shape of the 3(π^{+}π^{-}) invariant mass spectrum is observed for the first time, which could be resolved by two overlapping resonant structures, X(1840) and X(1880). The new state X(1880) is observed with a statistical significance larger than 10σ. The mass and width of X(1880) are determined to be 1882.1±1.7±0.7  MeV/c^{2} and 30.7±5.5±2.4  MeV, respectively, which indicates the existence of a pp[over ¯] bound state.

Temporal patterns of organ dysfunction in COVID-19 patients hospitalized in the intensive care unit: A group-based multitrajectory modeling analysis

BACKGROUND

The course of organ dysfunction (OD) in Corona Virus Disease 2019 (COVID-19) patients is unknown. Herein, we analyze the temporal patterns of OD in intensive care unit-admitted COVID-19 patients.

METHODS

Sequential organ failure assessment scores were evaluated daily within 2 weeks of admission to determine the temporal trajectory of OD using group-based multitrajectory modeling (GBMTM).

RESULTS

A total of 392 patients were enrolled with a 28-day mortality rate of 53.6%. GBMTM identified four distinct trajectories. Group 1 (mild OD, n = 64), with a median APACHE II score of 13 (IQR 9-21), had an early resolution of OD and a low mortality rate. Group 2 (moderate OD, n = 140), with a median APACHE II score of 18 (IQR 13-22), had a 28-day mortality rate of 30.0%. Group 3 (severe OD, n = 117), with a median APACHR II score of 20 (IQR 13-27), had a deterioration trend of respiratory dysfunction and a 28-day mortality rate of 69.2%. Group 4 (extremely severe OD, n = 71), with a median APACHE II score of 20 (IQR 17-27), had a significant and sustained OD affecting all organ systems and a 28-day mortality rate of 97.2%.

CONCLUSIONS

Four distinct trajectories of OD were identified, and respiratory dysfunction trajectory could predict nonpulmonary OD trajectories and patient prognosis.

Study of the f_{0}(980) and f_{0}(500) Scalar Mesons through the Decay D_{s}^{+}→π^{+}π^{-}e^{+}ν_{e}

Using e^{+}e^{-} collision data corresponding to an integrated luminosity of 7.33  fb^{-1} recorded by the BESIII detector at center-of-mass energies between 4.128 and 4.226 GeV, we present an analysis of the decay D_{s}^{+}→π^{+}π^{-}e^{+}ν_{e}, where the D_{s}^{+} is produced via the process e^{+}e^{-}→D_{s}^{*±}D_{s}^{∓}. We observe the f_{0}(980) in the π^{+}π^{-} system and the branching fraction of the decay D_{s}^{+}→f_{0}(980)e^{+}ν_{e} with f_{0}(980)→π^{+}π^{-} measured to be (1.72±0.13_{stat}±0.10_{syst})×10^{-3}, where the uncertainties are statistical and systematic, respectively. The dynamics of the D_{s}^{+}→f_{0}(980)e^{+}ν_{e} decay are studied with the simple pole parametrization of the hadronic form factor and the Flatté formula describing the f_{0}(980) in the differential decay rate, and the product of the form factor f_{+}^{f_{0}}(0) and the c→s Cabibbo-Kobayashi-Maskawa matrix element |V_{cs}| is determined for the first time to be f_{+}^{f_{0}}(0)|V_{cs}|=0.504±0.017_{stat}±0.035_{syst}. Furthermore, the decay D_{s}^{+}→f_{0}(500)e^{+}ν_{e} is searched for the first time but no signal is found. The upper limit on the branching fraction of D_{s}^{+}→f_{0}(500)e^{+}ν_{e}, f_{0}(500)→π^{+}π^{-} decay is set to be 3.3×10^{-4} at 90% confidence level.

Repetitive transcranial magnetic stimulation ameliorates cognitive deficits in mice with radiation-induced brain injury by attenuating microglial pyroptosis and promoting neurogenesis via BDNF pathway

BACKGROUND

Radiation-induced brain injury (RIBI) is a common and severe complication during radiotherapy for head and neck tumor. Repetitive transcranial magnetic stimulation (rTMS) is a novel and non-invasive method of brain stimulation, which has been applied in various neurological diseases. rTMS has been proved to be effective for treatment of RIBI, while its mechanisms have not been well understood.

METHODS

RIBI mouse model was established by cranial irradiation, K252a was daily injected intraperitoneally to block BDNF pathway. Immunofluorescence staining, immunohistochemistry and western blotting were performed to examine the microglial pyroptosis and hippocampal neurogenesis. Behavioral tests were used to assess the cognitive function and emotionality of mice. Golgi staining was applied to observe the structure of dendritic spine in hippocampus.

RESULTS

rTMS significantly promoted hippocampal neurogenesis and mitigated neuroinflammation, with ameliorating pyroptosis in microglia, as well as downregulation of the protein expression level of NLRP3 inflammasome and key pyroptosis factor Gasdermin D (GSDMD). BDNF signaling pathway might be involved in it. After blocking BDNF pathway by K252a, a specific BDNF pathway inhibitor, the neuroprotective effect of rTMS was markedly reversed. Evaluated by behavioral tests, the cognitive dysfunction and anxiety-like behavior were found aggravated with the comparison of mice in rTMS intervention group. Moreover, the level of hippocampal neurogenesis was found to be attenuated, the pyroptosis of microglia as well as the levels of GSDMD, NLRP3 inflammasome and IL-1β were upregulated.

CONCLUSION

Our study indicated that rTMS notably ameliorated RIBI-induced cognitive disorders, by mitigating pyroptosis in microglia and promoting hippocampal neurogenesis via mediating BDNF pathway.

[Comparison of the microbiota diversity between autogenous and anautogenous Culex pipiens pallens]

OBJECTIVE

To investigate the microbiota composition and diversity between autogenous and anautogenous Culex pipiens pallens, so as to provide insights into unraveling the pathogenesis of autogeny in Cx. pipiens pallens.

METHODS

Autogenous and anautogenous adult Cx. pipiens pallens samples were collected at 25 ℃, and the hypervariable regions of the microbial 16S ribosomal RNA (16S rRNA) gene was sequenced on the Illumina NovaSeq 6000 sequencing platform. The microbiota abundance and diversity were evaluated using the alpha diversity index, and the difference in the microbiota structure was examined using the beta diversity index. The microbiota with significant differences in the abundance between autogenous and anautogenous adult Cx. pipiens pallens samples was identified using the linear discriminant analysis effect size (LEfSe).

RESULTS

The microbiota in autogenous and anautogenous Cx. pipiens pallens samples belonged to 18 phyla, 28 classes, 70 orders, 113 families, and 170 genera, and the dominant phyla included Proteobacteria, Bacteroidetes, and so on. At the genus level, Wolbachia was a common dominant genus, and the relative abundance was (77.6 ± 11.3)% in autogenous Cx. pipiens pallens samples and (47.5 ± 8.5)% in anautogenous mosquito samples, while Faecalibaculum (0.4% ± 0.1%), Dubosiella (0.5% ± 0.0%) and Massilia (0.5% ± 0.1%) were specific species in autogenous Cx. pipiens pallens samples. Alpha diversity analysis showed that higher Chao1 index and ACE index in autogenous Cx. pipiens pallens samples than in anautogenous samples (both P values > 0.05), and lower Shannon index (P > 0.05) and Simpson index (P < 0.05) in autogenous Cx. pipiens pallens samples than in anautogenous samples. LEfSe analysis showed a total of 48 significantly different taxa between autogenous and anautogenous Cx. pipiens pallens samples (all P values < 0.05).

CONCLUSIONS

There is a significant difference in the microbiota diversity between autogenous and anautogenous Cx. pipiens pallens.

Role of Surface Terminations for Charge Storage of Ti3C2Tx MXene Electrodes in Aqueous Acidic Electrolyte

In this study, we used 2-Dimmensionnal Ti3C2 MXene as model materials to understand how the surface groups affect their electrochemical performance. By adjusting the nature of the surface terminations (Cl-, N/O-, and O-) of Ti3C2 MXene through a molten salt approach, we could change the spacing between MXene layers and the level of water confinement, resulting in significant modifications of the electrochemical performance in acidic electrolyte. Using a combination of techniques including in-operando X-ray diffraction and electrochemical quartz crystal microbalance (EQCM) techniques, we found that the presence of confined water results in a drastic transition from an almost electrochemically inactive behavior for Cl-terminated Ti3C2 to an ideally fast pseudocapacitive signature for N,O-terminated Ti3C2 MXene. This experimental work not only demonstrates the strong connection between surface terminations and confined water but also reveals the importance of confined water on the charge storage mechanism and the reaction kinetics in MXene.

Clinicopathological features and prognostic factors of salivary gland myoepithelial carcinoma: institutional experience of 42 cases

Myoepithelial carcinoma (MECA) is a rare type of carcinoma for which the clinicopathological features and prognostic factors have not yet been fully clarified. A retrospective study of 42 patients diagnosed with salivary gland MECA was performed, focusing on the clinicopathological features and prognostic factors. Of the 42 patients, 20 died of cancer, 20 lived without tumour, one lived with distant metastasis, and one was lost to follow-up. Overall, 69.0% had tumour recurrence, 16.7% had cervical nodal metastasis, and 21.4% had distant metastasis. The 5-year overall survival rate was 70.2%. Kaplan-Meier analysis revealed that patients with pathological positive lymph nodes (pN+), multiple recurrences of tumour, and higher histological grade had worse overall survival. Multivariate Cox analysis indicated pN+ and higher histological grade to be independent predictors of decreased survival. The 5-year overall survival rate in the pN0 group was 87.5%, while that in the pN+ group was 28.6%. In conclusion, myoepithelial carcinoma can be defined as a tumour with a high incidence of recurrence and poor prognosis, especially in pN+ patients. Pathological positive lymph nodes and histological grade may serve as predictors of survival.

Observation of D^{+}→K_{S}^{0}a_{0}(980)^{+} in the Amplitude Analysis of D^{+}→K_{S}^{0}π^{+}η

We perform for the first time an amplitude analysis of the decay D^{+}→K_{S}^{0}π^{+}η and report the observation of the decay D^{+}→K_{S}^{0}a_{0}(980)^{+} using 2.93  fb^{-1} of e^{+}e^{-} collision data taken at a center-of-mass energy of 3.773 GeV with the BESIII detector. As the only W-annihilation-free decay among D to a_{0}(980) pseudoscalar, D^{+}→K_{S}^{0}a_{0}(980)^{+} is the ideal decay in extracting the contributions of the W-emission amplitudes involving a_{0}(980) and to study the final-state interactions. The absolute branching fraction of D^{+}→K_{S}^{0}π^{+}η is measured to be (1.27±0.04_{stat}±0.03_{syst})%. The branching fractions of intermediate processes D^{+}→K_{S}^{0}a_{0}(980)^{+} with a_{0}(980)^{+}→π^{+}η and D^{+}→π^{+}K[over ¯]_{0}^{*}(1430)^{0} with K[over ¯]_{0}^{*}(1430)^{0}→K_{S}^{0}η are measured to be (1.33±0.05_{stat}±0.04_{syst})% and (0.14±0.03_{stat}±0.01_{syst})%, respectively.

Observation of Significant Flavor-SU(3) Breaking in the Kaon Wave Function at 12<Q^{2}<25 GeV^{2} and Discovery of the Charmless Decay ψ(3770)→K_{S}^{0}K_{L}^{0}

We present cross sections for the reaction e^{+}e^{-}→K_{S}^{0}K_{L}^{0} at center-of-mass energies ranging from 3.51 to 4.95 GeV using data samples collected in the BESIII experiment, corresponding to a total integrated luminosity of 26.5  fb^{-1}. The ratio of neutral-to-charged kaon form factors at large momentum transfers (12 Collapse

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Affiliation(s)

M Ablikim Institute of High Energy Physics, Beijing 100049, People's Republic of China
M N Achasov Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
P Adlarson Uppsala University, Box 516, SE-75120 Uppsala, Sweden
X C Ai Zhengzhou University, Zhengzhou 450001, People's Republic of China
R Aliberti Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
A Amoroso University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
M R An Liaoning Normal University, Dalian 116029, People's Republic of China
Q An State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y Bai Southeast University, Nanjing 211100, People's Republic of China
O Bakina Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
I Balossino INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
Y Ban Peking University, Beijing 100871, People's Republic of China
H-R Bao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
V Batozskaya Institute of High Energy Physics, Beijing 100049, People's Republic of China National Centre for Nuclear Research, Warsaw 02-093, Poland
K Begzsuren Institute of Physics and Technology, Peace Avenue 54B, Ulaanbaatar 13330, Mongolia
N Berger Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
M Berlowski National Centre for Nuclear Research, Warsaw 02-093, Poland
M Bertani INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
D Bettoni INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
F Bianchi University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
E Bianco University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
A Bortone University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
I Boyko Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
R A Briere Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
A Brueggemann University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
H Cai Wuhan University, Wuhan 430072, People's Republic of China
X Cai Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
A Calcaterra INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
G F Cao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
N Cao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S A Cetin Turkish Accelerator Center Particle Factory Group, Istinye University, 34010 Istanbul, Turkey
J F Chang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
T T Chang Xinyang Normal University, Xinyang 464000, People's Republic of China
W L Chang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
G R Che Nankai University, Tianjin 300071, People's Republic of China
G Chelkov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
C Chen Nankai University, Tianjin 300071, People's Republic of China
Chao Chen Soochow University, Suzhou 215006, People's Republic of China
G Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China
H S Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
M L Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S J Chen Nanjing University, Nanjing 210093, People's Republic of China
S L Chen North China Electric Power University, Beijing 102206, People's Republic of China
S M Chen Tsinghua University, Beijing 100084, People's Republic of China
T Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X R Chen Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X T Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y B Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y Q Chen Jilin University, Changchun 130012, People's Republic of China
Z J Chen Hunan University, Changsha 410082, People's Republic of China
S K Choi Chung-Ang University, Seoul, 06974, Republic of Korea
X Chu Nankai University, Tianjin 300071, People's Republic of China
G Cibinetto INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
S C Coen Bochum Ruhr-University, D-44780 Bochum, Germany
F Cossio INFN, I-10125, Turin, Italy
J J Cui Shandong University, Jinan 250100, People's Republic of China
H L Dai Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J P Dai Yunnan University, Kunming 650500, People's Republic of China
A Dbeyssi Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
R E de Boer Bochum Ruhr-University, D-44780 Bochum, Germany
D Dedovich Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
Z Y Deng Institute of High Energy Physics, Beijing 100049, People's Republic of China
A Denig Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
I Denysenko Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
M Destefanis University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
F De Mori University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
B Ding Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Jinan, Jinan 250022, People's Republic of China
X X Ding Peking University, Beijing 100871, People's Republic of China
Y Ding Liaoning University, Shenyang 110036, People's Republic of China
Y Ding Jilin University, Changchun 130012, People's Republic of China
J Dong Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
L Y Dong Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
M Y Dong Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Dong Wuhan University, Wuhan 430072, People's Republic of China
M C Du Institute of High Energy Physics, Beijing 100049, People's Republic of China
S X Du Zhengzhou University, Zhengzhou 450001, People's Republic of China
Z H Duan Nanjing University, Nanjing 210093, People's Republic of China
P Egorov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
Y H Fan North China Electric Power University, Beijing 102206, People's Republic of China
J Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
S S Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
W X Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Q Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
R Farinelli INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
L Fava University of Eastern Piedmont, I-15121 Alessandria, Italy INFN, I-10125, Turin, Italy
F Feldbauer Bochum Ruhr-University, D-44780 Bochum, Germany
G Felici INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
C Q Feng State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J H Feng Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
K Fischer University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
M Fritsch Bochum Ruhr-University, D-44780 Bochum, Germany
C D Fu Institute of High Energy Physics, Beijing 100049, People's Republic of China
J L Fu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y W Fu Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Gao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y N Gao Peking University, Beijing 100871, People's Republic of China
Yang Gao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
S Garbolino INFN, I-10125, Turin, Italy
I Garzia INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy University of Ferrara, I-44122 Ferrara, Italy
P T Ge Wuhan University, Wuhan 430072, People's Republic of China
Z W Ge Nanjing University, Nanjing 210093, People's Republic of China
C Geng Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
E M Gersabeck University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
A Gilman University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
K Goetzen GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
L Gong Liaoning University, Shenyang 110036, People's Republic of China
W X Gong Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
W Gradl Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
S Gramigna INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy University of Ferrara, I-44122 Ferrara, Italy
M Greco University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
M H Gu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y T Gu Guangxi University, Nanning 530004, People's Republic of China
C Y Guan Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z L Guan Henan University of Technology, Zhengzhou 450001, People's Republic of China
A Q Guo Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L B Guo Nanjing Normal University, Nanjing 210023, People's Republic of China
M J Guo Shandong University, Jinan 250100, People's Republic of China
R P Guo Shandong Normal University, Jinan 250014, People's Republic of China
Y P Guo Fudan University, Shanghai 200433, People's Republic of China
A Guskov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
J Gutierrez Indiana University, Bloomington, Indiana 47405, USA
T T Han Institute of High Energy Physics, Beijing 100049, People's Republic of China
W Y Han Liaoning Normal University, Dalian 116029, People's Republic of China
X Q Hao Henan Normal University, Xinxiang 453007, People's Republic of China
F A Harris University of Hawaii, Honolulu, Hawaii 96822, USA
K K He Soochow University, Suzhou 215006, People's Republic of China
K L He Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
F H H Heinsius Bochum Ruhr-University, D-44780 Bochum, Germany
C H Heinz Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
Y K Heng Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C Herold Suranaree University of Technology, University Avenue 111, Nakhon Ratchasima 30000, Thailand
T Holtmann Bochum Ruhr-University, D-44780 Bochum, Germany
P C Hong Fudan University, Shanghai 200433, People's Republic of China
G Y Hou Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X T Hou Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y R Hou University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z L Hou Institute of High Energy Physics, Beijing 100049, People's Republic of China
B Y Hu Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H M Hu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J F Hu South China Normal University, Guangzhou 510006, People's Republic of China
T Hu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y Hu Institute of High Energy Physics, Beijing 100049, People's Republic of China
G S Huang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
K X Huang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
L Q Huang Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X T Huang Shandong University, Jinan 250100, People's Republic of China
Y P Huang Institute of High Energy Physics, Beijing 100049, People's Republic of China
T Hussain University of the Punjab, Lahore-54590, Pakistan
N Hüsken Indiana University, Bloomington, Indiana 47405, USA Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
N In der Wiesche University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
M Irshad State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J Jackson Indiana University, Bloomington, Indiana 47405, USA
S Jaeger Bochum Ruhr-University, D-44780 Bochum, Germany
S Janchiv Institute of Physics and Technology, Peace Avenue 54B, Ulaanbaatar 13330, Mongolia
J H Jeong Chung-Ang University, Seoul, 06974, Republic of Korea
Q Ji Institute of High Energy Physics, Beijing 100049, People's Republic of China
Q P Ji Henan Normal University, Xinxiang 453007, People's Republic of China
X B Ji Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X L Ji Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y Y Ji Shandong University, Jinan 250100, People's Republic of China
X Q Jia Shandong University, Jinan 250100, People's Republic of China
Z K Jia State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H J Jiang Wuhan University, Wuhan 430072, People's Republic of China
P C Jiang Peking University, Beijing 100871, People's Republic of China
S S Jiang Liaoning Normal University, Dalian 116029, People's Republic of China
T J Jiang Hangzhou Normal University, Hangzhou 310036, People's Republic of China
X S Jiang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y Jiang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J B Jiao Shandong University, Jinan 250100, People's Republic of China
Z Jiao Huangshan College, Huangshan 245000, People's Republic of China
S Jin Nanjing University, Nanjing 210093, People's Republic of China
Y Jin University of Jinan, Jinan 250022, People's Republic of China
M Q Jing Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X M Jing University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T Johansson Uppsala University, Box 516, SE-75120 Uppsala, Sweden
X Kui Institute of High Energy Physics, Beijing 100049, People's Republic of China
S Kabana Instituto de Alta Investigación, Universidad de Tarapacá, Casilla 7D, Arica 1000000, Chile
N Kalantar-Nayestanaki University of Groningen, NL-9747 AA Groningen, The Netherlands
X L Kang China University of Geosciences, Wuhan 430074, People's Republic of China
X S Kang Liaoning University, Shenyang 110036, People's Republic of China
M Kavatsyuk University of Groningen, NL-9747 AA Groningen, The Netherlands
B C Ke Zhengzhou University, Zhengzhou 450001, People's Republic of China
V Khachatryan Indiana University, Bloomington, Indiana 47405, USA
A Khoukaz University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
R Kiuchi Institute of High Energy Physics, Beijing 100049, People's Republic of China
R Kliemt GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
O B Kolcu Turkish Accelerator Center Particle Factory Group, Istinye University, 34010 Istanbul, Turkey
B Kopf Bochum Ruhr-University, D-44780 Bochum, Germany
M Kuessner Bochum Ruhr-University, D-44780 Bochum, Germany
A Kupsc National Centre for Nuclear Research, Warsaw 02-093, Poland Uppsala University, Box 516, SE-75120 Uppsala, Sweden
W Kühn Justus-Liebig-Universitaet Giessen, II. Physikalisches Institut, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
J J Lane University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
P Larin Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
A Lavania Indian Institute of Technology Madras, Chennai 600036, India
L Lavezzi University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
T T Lei State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Z H Lei State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H Leithoff Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
M Lellmann Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
T Lenz Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
C Li Qufu Normal University, Qufu 273165, People's Republic of China
C Li Nankai University, Tianjin 300071, People's Republic of China
C H Li Liaoning Normal University, Dalian 116029, People's Republic of China
Cheng Li State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
D M Li Zhengzhou University, Zhengzhou 450001, People's Republic of China
F Li Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
G Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Li State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H B Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H J Li Henan Normal University, Xinxiang 453007, People's Republic of China
H N Li South China Normal University, Guangzhou 510006, People's Republic of China
Hui Li Nankai University, Tianjin 300071, People's Republic of China
J R Li Tsinghua University, Beijing 100084, People's Republic of China
J S Li Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
J W Li Shandong University, Jinan 250100, People's Republic of China
Ke Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
L J Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L K Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
Lei Li Renmin University of China, Beijing 100872, People's Republic of China
M H Li Nankai University, Tianjin 300071, People's Republic of China
P R Li Lanzhou University, Lanzhou 730000, People's Republic of China
Q X Li Shandong University, Jinan 250100, People's Republic of China
S X Li Fudan University, Shanghai 200433, People's Republic of China
T Li Shandong University, Jinan 250100, People's Republic of China
W D Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
W G Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
X H Li State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X L Li Shandong University, Jinan 250100, People's Republic of China
Xiaoyu Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y G Li Peking University, Beijing 100871, People's Republic of China
Z J Li Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Z X Li Guangxi University, Nanning 530004, People's Republic of China
C Liang Nanjing University, Nanjing 210093, People's Republic of China
H Liang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H Liang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y F Liang Sichuan University, Chengdu 610064, People's Republic of China
Y T Liang Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
G R Liao Guangxi Normal University, Guilin 541004, People's Republic of China
L Z Liao Shandong University, Jinan 250100, People's Republic of China
Y P Liao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J Libby Indian Institute of Technology Madras, Chennai 600036, India
A Limphirat Suranaree University of Technology, University Avenue 111, Nakhon Ratchasima 30000, Thailand
D X Lin Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T Lin Institute of High Energy Physics, Beijing 100049, People's Republic of China
B J Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
B X Liu Wuhan University, Wuhan 430072, People's Republic of China
C Liu Jilin University, Changchun 130012, People's Republic of China
C X Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
F H Liu Shanxi University, Taiyuan 030006, People's Republic of China
Fang Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Feng Liu Central China Normal University, Wuhan 430079, People's Republic of China
G M Liu South China Normal University, Guangzhou 510006, People's Republic of China
H Liu Lanzhou University, Lanzhou 730000, People's Republic of China
H B Liu Guangxi University, Nanning 530004, People's Republic of China
H M Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Huanhuan Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Huihui Liu Henan University of Science and Technology, Luoyang 471003, People's Republic of China
J B Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J Y Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
K Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
K Y Liu Liaoning University, Shenyang 110036, People's Republic of China
Ke Liu Henan University of Technology, Zhengzhou 450001, People's Republic of China
L Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
L C Liu Nankai University, Tianjin 300071, People's Republic of China
Lu Liu Nankai University, Tianjin 300071, People's Republic of China
M H Liu Fudan University, Shanghai 200433, People's Republic of China
P L Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Q Liu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S B Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
T Liu Fudan University, Shanghai 200433, People's Republic of China
W K Liu Nankai University, Tianjin 300071, People's Republic of China
W M Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X Liu Lanzhou University, Lanzhou 730000, People's Republic of China
Y Liu Lanzhou University, Lanzhou 730000, People's Republic of China
Y Liu Zhengzhou University, Zhengzhou 450001, People's Republic of China
Y B Liu Nankai University, Tianjin 300071, People's Republic of China
Z A Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z Q Liu Shandong University, Jinan 250100, People's Republic of China
X C Lou Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
F X Lu Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H J Lu Huangshan College, Huangshan 245000, People's Republic of China
J G Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
X L Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Lu Central South University, Changsha 410083, People's Republic of China
Y P Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Z H Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C L Luo Nanjing Normal University, Nanjing 210023, People's Republic of China
M X Luo Zhejiang University, Hangzhou 310027, People's Republic of China
T Luo Fudan University, Shanghai 200433, People's Republic of China
X L Luo Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
X R Lyu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y F Lyu Nankai University, Tianjin 300071, People's Republic of China
F C Ma Liaoning University, Shenyang 110036, People's Republic of China
H Ma Yunnan University, Kunming 650500, People's Republic of China
H L Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China
J L Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L L Ma Shandong University, Jinan 250100, People's Republic of China
M M Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Q M Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China
R Q Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Y Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y Ma Peking University, Beijing 100871, People's Republic of China
Y M Ma Institute of Modern Physics, Lanzhou 730000, People's Republic of China
F E Maas Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
M Maggiora University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
S Malde University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
Q A Malik University of the Punjab, Lahore-54590, Pakistan
A Mangoni INFN Sezione di Perugia, I-06100 Perugia, Italy
Y J Mao Peking University, Beijing 100871, People's Republic of China
Z P Mao Institute of High Energy Physics, Beijing 100049, People's Republic of China
S Marcello University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
Z X Meng University of Jinan, Jinan 250022, People's Republic of China
J G Messchendorp GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany University of Groningen, NL-9747 AA Groningen, The Netherlands
G Mezzadri INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
H Miao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T J Min Nanjing University, Nanjing 210093, People's Republic of China
R E Mitchell Indiana University, Bloomington, Indiana 47405, USA
X H Mo Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B Moses Indiana University, Bloomington, Indiana 47405, USA
N Yu Muchnoi Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
J Muskalla Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
Y Nefedov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
F Nerling Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
I B Nikolaev Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
Z Ning Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
S Nisar COMSATS University Islamabad, Lahore Campus, Defence Road, Off Raiwind Road, 54000 Lahore, Pakistan
Q L Niu Lanzhou University, Lanzhou 730000, People's Republic of China
W D Niu Soochow University, Suzhou 215006, People's Republic of China
Y Niu Shandong University, Jinan 250100, People's Republic of China
S L Olsen University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Q Ouyang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S Pacetti INFN Sezione di Perugia, I-06100 Perugia, Italy University of Perugia, I-06100 Perugia, Italy
X Pan Soochow University, Suzhou 215006, People's Republic of China
Y Pan Southeast University, Nanjing 211100, People's Republic of China
A Pathak Jilin University, Changchun 130012, People's Republic of China
P Patteri INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
Y P Pei State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
M Pelizaeus Bochum Ruhr-University, D-44780 Bochum, Germany
H P Peng State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y Y Peng Lanzhou University, Lanzhou 730000, People's Republic of China
K Peters GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
J L Ping Nanjing Normal University, Nanjing 210023, People's Republic of China
R G Ping Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S Plura Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
V Prasad Instituto de Alta Investigación, Universidad de Tarapacá, Casilla 7D, Arica 1000000, Chile
F Z Qi Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Qi State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H R Qi Tsinghua University, Beijing 100084, People's Republic of China
M Qi Nanjing University, Nanjing 210093, People's Republic of China
T Y Qi Fudan University, Shanghai 200433, People's Republic of China
S Qian Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
W B Qian University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C F Qiao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J J Qin University of South China, Hengyang 421001, People's Republic of China
L Q Qin Guangxi Normal University, Guilin 541004, People's Republic of China
X S Qin Shandong University, Jinan 250100, People's Republic of China
Z H Qin Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J F Qiu Institute of High Energy Physics, Beijing 100049, People's Republic of China
S Q Qu Tsinghua University, Beijing 100084, People's Republic of China
C F Redmer Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
K J Ren Liaoning Normal University, Dalian 116029, People's Republic of China
A Rivetti INFN, I-10125, Turin, Italy
M Rolo INFN, I-10125, Turin, Italy
G Rong Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Ch Rosner Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
S N Ruan Nankai University, Tianjin 300071, People's Republic of China
N Salone National Centre for Nuclear Research, Warsaw 02-093, Poland
A Sarantsev Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
Y Schelhaas Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
K Schoenning Uppsala University, Box 516, SE-75120 Uppsala, Sweden
M Scodeggio INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy University of Ferrara, I-44122 Ferrara, Italy
K Y Shan Fudan University, Shanghai 200433, People's Republic of China
W Shan Hunan Normal University, Changsha 410081, People's Republic of China
X Y Shan State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J F Shangguan Soochow University, Suzhou 215006, People's Republic of China
L G Shao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
M Shao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
C P Shen Fudan University, Shanghai 200433, People's Republic of China
H F Shen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
W H Shen University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Y Shen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B A Shi University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H C Shi State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J L Shi Fudan University, Shanghai 200433, People's Republic of China
J Y Shi Institute of High Energy Physics, Beijing 100049, People's Republic of China
Q Q Shi Soochow University, Suzhou 215006, People's Republic of China
R S Shi Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Shi Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J J Song Henan Normal University, Xinxiang 453007, People's Republic of China
T Z Song Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
W M Song Institute of High Energy Physics, Beijing 100049, People's Republic of China Jilin University, Changchun 130012, People's Republic of China
Y J Song Fudan University, Shanghai 200433, People's Republic of China
Y X Song Peking University, Beijing 100871, People's Republic of China
S Sosio University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
S Spataro University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
F Stieler Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
Y J Su University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
G B Sun Wuhan University, Wuhan 430072, People's Republic of China
G X Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Sun University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H K Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China
J F Sun Henan Normal University, Xinxiang 453007, People's Republic of China
K Sun Tsinghua University, Beijing 100084, People's Republic of China
L Sun Wuhan University, Wuhan 430072, People's Republic of China
S S Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T Sun Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China
W Y Sun Jilin University, Changchun 130012, People's Republic of China
Y Sun China University of Geosciences, Wuhan 430074, People's Republic of China
Y J Sun State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y Z Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z T Sun Shandong University, Jinan 250100, People's Republic of China
Y X Tan State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
C J Tang Sichuan University, Chengdu 610064, People's Republic of China
G Y Tang Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Tang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Y A Tang Wuhan University, Wuhan 430072, People's Republic of China
L Y Tao University of South China, Hengyang 421001, People's Republic of China
Q T Tao Hunan University, Changsha 410082, People's Republic of China
M Tat University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
J X Teng State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
V Thoren Uppsala University, Box 516, SE-75120 Uppsala, Sweden
W H Tian Shanxi Normal University, Linfen 041004, People's Republic of China
W H Tian Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Y Tian Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z F Tian Wuhan University, Wuhan 430072, People's Republic of China
I Uman Near East University, Nicosia, North Cyprus, 99138, Mersin 10, Turkey
Y Wan Soochow University, Suzhou 215006, People's Republic of China
S J Wang Shandong University, Jinan 250100, People's Republic of China
B Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China
B L Wang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Bo Wang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
C W Wang Nanjing University, Nanjing 210093, People's Republic of China
D Y Wang Peking University, Beijing 100871, People's Republic of China
F Wang University of South China, Hengyang 421001, People's Republic of China
H J Wang Lanzhou University, Lanzhou 730000, People's Republic of China
J P Wang Shandong University, Jinan 250100, People's Republic of China
K Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
L L Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China
M Wang Shandong University, Jinan 250100, People's Republic of China
Meng Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
N Y Wang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S Wang Fudan University, Shanghai 200433, People's Republic of China
S Wang Lanzhou University, Lanzhou 730000, People's Republic of China
T Wang Fudan University, Shanghai 200433, People's Republic of China
T J Wang Nankai University, Tianjin 300071, People's Republic of China
W Wang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
W Wang University of South China, Hengyang 421001, People's Republic of China
W P Wang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X Wang Peking University, Beijing 100871, People's Republic of China
X F Wang Lanzhou University, Lanzhou 730000, People's Republic of China
X J Wang Liaoning Normal University, Dalian 116029, People's Republic of China
X L Wang Fudan University, Shanghai 200433, People's Republic of China
Y Wang Tsinghua University, Beijing 100084, People's Republic of China
Y D Wang North China Electric Power University, Beijing 102206, People's Republic of China
Y F Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y L Wang Henan Normal University, Xinxiang 453007, People's Republic of China
Y N Wang North China Electric Power University, Beijing 102206, People's Republic of China
Y Q Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Yaqian Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China Hebei University, Baoding 071002, People's Republic of China
Yi Wang Tsinghua University, Beijing 100084, People's Republic of China
Z Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Z L Wang University of South China, Hengyang 421001, People's Republic of China
Z Y Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Ziyi Wang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
D Wei University of Science and Technology Liaoning, Anshan 114051, People's Republic of China
D H Wei Guangxi Normal University, Guilin 541004, People's Republic of China
F Weidner University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
S P Wen Institute of High Energy Physics, Beijing 100049, People's Republic of China
C W Wenzel Bochum Ruhr-University, D-44780 Bochum, Germany
U Wiedner Bochum Ruhr-University, D-44780 Bochum, Germany
G Wilkinson University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
M Wolke Uppsala University, Box 516, SE-75120 Uppsala, Sweden
L Wollenberg Bochum Ruhr-University, D-44780 Bochum, Germany
C Wu Liaoning Normal University, Dalian 116029, People's Republic of China
J F Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China China Center of Advanced Science and Technology, Beijing 100190, People's Republic of China
L H Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China
L J Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Wu Fudan University, Shanghai 200433, People's Republic of China
X H Wu Jilin University, Changchun 130012, People's Republic of China
Y Wu University of Science and Technology of China, Hefei 230026, People's Republic of China
Y H Wu Soochow University, Suzhou 215006, People's Republic of China
Y J Wu Institute of Modern Physics, Lanzhou 730000, People's Republic of China
Z Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
L Xia State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X M Xian Liaoning Normal University, Dalian 116029, People's Republic of China
T Xiang Peking University, Beijing 100871, People's Republic of China
D Xiao Lanzhou University, Lanzhou 730000, People's Republic of China
G Y Xiao Nanjing University, Nanjing 210093, People's Republic of China
S Y Xiao Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y L Xiao Fudan University, Shanghai 200433, People's Republic of China
Z J Xiao Nanjing Normal University, Nanjing 210023, People's Republic of China
C Xie Nanjing University, Nanjing 210093, People's Republic of China
X H Xie Peking University, Beijing 100871, People's Republic of China
Y Xie Shandong University, Jinan 250100, People's Republic of China
Y G Xie Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y H Xie Central China Normal University, Wuhan 430079, People's Republic of China
Z P Xie State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
T Y Xing Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C F Xu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C J Xu Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
G F Xu Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Y Xu University of Jinan, Jinan 250022, People's Republic of China
Q J Xu Hangzhou Normal University, Hangzhou 310036, People's Republic of China
Q N Xu Inner Mongolia University, Hohhot 010021, People's Republic of China
W Xu Institute of High Energy Physics, Beijing 100049, People's Republic of China
W L Xu University of Jinan, Jinan 250022, People's Republic of China
X P Xu Soochow University, Suzhou 215006, People's Republic of China
Y C Xu Yantai University, Yantai 264005, People's Republic of China
Z P Xu Nanjing University, Nanjing 210093, People's Republic of China
Z S Xu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
F Yan Fudan University, Shanghai 200433, People's Republic of China
L Yan Fudan University, Shanghai 200433, People's Republic of China
W B Yan State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
W C Yan Zhengzhou University, Zhengzhou 450001, People's Republic of China
X Q Yan Institute of High Energy Physics, Beijing 100049, People's Republic of China
H J Yang Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China
H L Yang Jilin University, Changchun 130012, People's Republic of China
H X Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Tao Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Yang Fudan University, Shanghai 200433, People's Republic of China
Y F Yang Nankai University, Tianjin 300071, People's Republic of China
Y X Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Yifan Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z W Yang Lanzhou University, Lanzhou 730000, People's Republic of China
Z P Yao Shandong University, Jinan 250100, People's Republic of China
M Ye Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
M H Ye China Center of Advanced Science and Technology, Beijing 100190, People's Republic of China
J H Yin Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z Y You Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
B X Yu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C X Yu Nankai University, Tianjin 300071, People's Republic of China
G Yu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J S Yu Hunan University, Changsha 410082, People's Republic of China
T Yu University of South China, Hengyang 421001, People's Republic of China
X D Yu Peking University, Beijing 100871, People's Republic of China
C Z Yuan Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L Yuan Beihang University, Beijing 100191, People's Republic of China
S C Yuan Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Yuan Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z Y Yuan Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
C X Yue Liaoning Normal University, Dalian 116029, People's Republic of China
A A Zafar University of the Punjab, Lahore-54590, Pakistan
F R Zeng Shandong University, Jinan 250100, People's Republic of China
S H Zeng University of South China, Hengyang 421001, People's Republic of China
X Zeng Fudan University, Shanghai 200433, People's Republic of China
Y Zeng Hunan University, Changsha 410082, People's Republic of China
Y J Zeng Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Y Zhai Jilin University, Changchun 130012, People's Republic of China
Y C Zhai Shandong University, Jinan 250100, People's Republic of China
Y H Zhan Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
A Q Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B L Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B X Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
D H Zhang Nankai University, Tianjin 300071, People's Republic of China
G Y Zhang Henan Normal University, Xinxiang 453007, People's Republic of China
H Zhang University of Science and Technology of China, Hefei 230026, People's Republic of China
H C Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H H Zhang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H H Zhang Jilin University, Changchun 130012, People's Republic of China
H Q Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H Y Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J Zhang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
J Zhang Zhengzhou University, Zhengzhou 450001, People's Republic of China
J J Zhang Shanxi Normal University, Linfen 041004, People's Republic of China
J L Zhang Henan University, Kaifeng 475004, People's Republic of China
J Q Zhang Nanjing Normal University, Nanjing 210023, People's Republic of China
J W Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J X Zhang Lanzhou University, Lanzhou 730000, People's Republic of China
J Y Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Z Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Jianyu Zhang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L M Zhang Tsinghua University, Beijing 100084, People's Republic of China
L Q Zhang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Lei Zhang Nanjing University, Nanjing 210093, People's Republic of China
P Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Q Y Zhang Liaoning Normal University, Dalian 116029, People's Republic of China Zhengzhou University, Zhengzhou 450001, People's Republic of China
Shuihan Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Shulei Zhang Hunan University, Changsha 410082, People's Republic of China
X D Zhang North China Electric Power University, Beijing 102206, People's Republic of China
X M Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
X Y Zhang Shandong University, Jinan 250100, People's Republic of China
Y Zhang University of South China, Hengyang 421001, People's Republic of China
Y Zhang University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
Y T Zhang Zhengzhou University, Zhengzhou 450001, People's Republic of China
Y H Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Yan Zhang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Yao Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z D Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z H Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z L Zhang Jilin University, Changchun 130012, People's Republic of China
Z Y Zhang Nankai University, Tianjin 300071, People's Republic of China
Z Y Zhang Wuhan University, Wuhan 430072, People's Republic of China
G Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Y Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J Z Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Lei Zhao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Ling Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China
M G Zhao Nankai University, Tianjin 300071, People's Republic of China
R P Zhao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S J Zhao Zhengzhou University, Zhengzhou 450001, People's Republic of China
Y B Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y X Zhao Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z G Zhao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
A Zhemchugov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
B Zheng University of South China, Hengyang 421001, People's Republic of China
J P Zheng Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
W J Zheng Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y H Zheng University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B Zhong Nanjing Normal University, Nanjing 210023, People's Republic of China
X Zhong Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H Zhou Shandong University, Jinan 250100, People's Republic of China
L P Zhou Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Zhou Wuhan University, Wuhan 430072, People's Republic of China
X K Zhou Central China Normal University, Wuhan 430079, People's Republic of China
X R Zhou State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X Y Zhou Liaoning Normal University, Dalian 116029, People's Republic of China
Y Z Zhou Fudan University, Shanghai 200433, People's Republic of China
J Zhu Nankai University, Tianjin 300071, People's Republic of China
K Zhu Institute of High Energy Physics, Beijing 100049, People's Republic of China
K J Zhu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L Zhu Jilin University, Changchun 130012, People's Republic of China
L X Zhu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S H Zhu University of Science and Technology Liaoning, Anshan 114051, People's Republic of China
S Q Zhu Nanjing University, Nanjing 210093, People's Republic of China
T J Zhu Fudan University, Shanghai 200433, People's Republic of China
W J Zhu Fudan University, Shanghai 200433, People's Republic of China
Y C Zhu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Z A Zhu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J H Zou Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Zu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China

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Heavy metal pollution near an abandoned mercury-bearing waste recovery enterprise in southwestern China: Spatial distribution and its sources in soil and plants

The contribution of smelting of nonferrous metals to heavy metals in surface soil have become increasingly important over the past decade. In this study, the distribution of heavy metals around an abandoned mercury-bearing waste recovery enterprise were investigated. Soil (14) and plant (18) samples were collected in the surrounding area. The total concentration of heavy metals and methyl mercury content were measured by ICP-MS and HPLC-ICP-MS. The results show that the average contents of Cd, Cr, Pb, Hg and As in all soil samples are higher than the second-level values of Soil environmental quality-Risk control standard for soil contamination of development land (GB 36600-2018). Hg in the leaves ranged from 0.003 to 0.174 mg kg-1. Besides, the Pearson correlation analysis results indicate that Hg has a different environmental behavior compared to the other heavy metal under certain environmental or geographical conditions. But the mantel test statistical analysis results show that the Cr (P < 0.01), Cu, Pb, and Fe (P < 0.05) in the soil may have similar pollution sources with carbonate-bound mercury and iron-manganese oxide-bound mercury. The Hg concentrations show no correlation among plant leaves and soil, but significantly influenced by the distance and wind direction. These findings suggest that Hg in plant leaves may be derived from the deposition of atmospheric mercury from secondary mercury plant. The results will supplement those for relevant policy making for mercury-bearing waste recovery enterprises to improve urban environmental quality and human health.

Investigation of the ΔI=1/2 Rule and Test of CP Symmetry through the Measurement of Decay Asymmetry Parameters in Ξ^{-} Decays

Using (10087±44)×10^{6}  J/ψ events collected with the BESIII detector, numerous Ξ^{-} and Λ decay asymmetry parameters are simultaneously determined from the process J/ψ→Ξ^{-}Ξ[over ¯]^{+}→Λ(pπ^{-})π^{-}Λ[over ¯](n[over ¯]π^{0})π^{+} and its charge-conjugate channel. The precisions of α_{Λ0} for Λ→nπ^{0} and α[over ¯]_{Λ0} for Λ[over ¯]→n[over ¯]π^{0} compared to world averages are improved by factors of 4 and 1.7, respectively. The ratio of decay asymmetry parameters of Λ→nπ^{0} to that of Λ→pπ^{-}, ⟨α_{Λ0}⟩/⟨α_{Λ-}⟩, is determined to be 0.873±0.012_{-0.010}^{+0.011}, where the first and the second uncertainties are statistical and systematic, respectively. The ratio is smaller than unity more than 5σ, which signifies the existence of the ΔI=3/2 transition in Λ for the first time. Besides, we test for CP symmetry in Ξ^{-}→Λπ^{-} and in Λ→nπ^{0} with the best precision to date.

Temperature-Dependent Electrochemical Performance of Ta-Substituted SrCoO3 Perovskite for Supercapacitors

Developing new electrode materials with good temperature-dependent electrochemical performance has become a great issue for the deployment of hybrid supercapacitors with wide temperature tolerance. In this work, a series of Ta-substituted SrCo1-x Tax O3-δ (x=0.05, 0.10, 0.15, 0.20) perovskites have been studied as positive electrodes for hybrid supercapacitors in terms of their structures, elemental valence states and electrochemical performances. Incorporating Ta into SrCoO3-δ perovskite not only stabilizes the crystallite structure but also notably improves electrochemical activities. The SrCo0.95 Ta0.05 O3-δ @CC delivers the highest specific capacity (Qsp ) of 227.91 C g-1 at 1 A g-1 , which is attributed to the highest oxygen vacancy content and the fastest oxygen diffusion kinetics. The hybrid supercapacitor SrCo0.95 Ta0.05 O3-δ @CC//AC@CC exhibits a high energy density of 22.82 Wh kg-1 @775.09 W kg-1 and a stable long-term cycle life (5000 cycles) with 90.7 % capacity retention. As temperature increases from 25 to 85 °C, the capacitance properties are improved at elevated temperatures for both electrode and device due to the increased electrolyte conductivity. The outstanding electrochemical results present that SrCo1-x Tax O3-δ perovskite holds good prospects for hybrid supercapacitors with wide temperature tolerance.

Efficacy and safety of rifampicin-based triple therapy for non-puerperal mastitis: A single-arm, open-label, prospective clinical trial

OBJECTIVES

To assess the efficacy and safety of rifampicin-based triple therapy (rifampicin, isoniazid, and ethambutol) for treating NPM.

METHODS

This single-center, single-arm, prospective clinical trial was conducted at the Second Hospital of Shandong University (Jinan, China). Patients with pathologically diagnosed granulomatous lobular mastitis and periductal mastitis received triple drugs, i.e., rifampicin (450 mg/day), isoniazid (300 mg/day), and ethambutol (15 mg/kg/day), until complete response or the investigator decided to discontinue treatment. The primary endpoint was the complete response rate (CRR) assessed by the investigator. The secondary endpoints included the overall remission rate (ORR), recurrence rate (RR), and safety.

RESULTS

A total of 218 patients were enrolled in the study between January 1, 2013 and October 31, 2020. With a median follow-up time of 48 months, the CRR and the ORR were 78.44% and 94.04%, respectively. While 13 patients (5.96%) demonstrated no response and 19 relapsed (8.72%). Adverse events (AEs) were not common. The most common AEs during treatment were liver dysfunction (1.83%), gastrointestinal reactions (1.83%), fatigue (1.83%), erythema (1.38%), and menstrual disorders (0.92%).

CONCLUSION

Rifampicin, isoniazid, and ethambutol demonstrated promising response rates with acceptable safety profiles in patients with NPM. Further confirmatory trial is warranted in the future.

TRIAL REGISTRATION

The study was approved by the Ethics Committee of the Second Hospital of Shandong University and retrospectively registered at the China Clinical Trial Registration Center (registration number: ChiCTR2100049591).

Observation of D_{s}^{+}→η^{'}μ^{+}ν_{μ}, Precision Test of Lepton Flavor Universality with D_{s}^{+}→η^{(')}l^{+}ν_{l}, and First Measurements of D_{s}^{+}→η^{(')}μ^{+}ν_{μ} Decay Dynamics

By analyzing 7.33  fb^{-1} of e^{+}e^{-} annihilation data collected at center-of-mass energies between 4.128 and 4.226 GeV with the BESIII detector, we report the observation of the semileptonic decay D_{s}^{+}→η^{'}μ^{+}ν_{μ}, with a statistical significance larger than 10σ, and the measurements of the D_{s}^{+}→ημ^{+}ν_{μ} and D_{s}^{+}→η^{'}μ^{+}ν_{μ} decay dynamics for the first time. The branching fractions of D_{s}^{+}→ημ^{+}ν_{μ} and D_{s}^{+}→η^{'}μ^{+}ν_{μ} are determined to be (2.235±0.051_{stat}±0.052_{syst})% and (0.801±0.055_{stat}±0.028_{syst})%, respectively, with precision improved by factors of 6.0 and 6.6 compared to the previous best measurements. Combined with the results for the decays D_{s}^{+}→ηe^{+}ν_{e} and D_{s}^{+}→η^{'}e^{+}ν_{e}, the ratios of the decay widths are examined both inclusively and in several ℓ^{+}ν_{ℓ} four-momentum transfer ranges. No evidence for lepton flavor universality violation is found within the current statistics. The products of the hadronic form factors f_{+,0}^{η^{(')}}(0) and the c→s Cabibbo-Kobayashi-Maskawa matrix element |V_{cs}| are determined. The results based on the two-parameter series expansion are f_{+,0}^{η}(0)|V_{cs}|=0.452±0.010_{stat}±0.007_{syst} and f_{+,0}^{η^{'}}(0)|V_{cs}|=0.504±0.037_{stat}±0.012_{syst}, which help to constrain present models on f_{+,0}^{η^{(')}}(0). The forward-backward asymmetries are determined to be ⟨A_{FB}^{η}⟩=-0.059±0.031_{stat}±0.005_{syst} and ⟨A_{FB}^{η^{'}}⟩=-0.064±0.079_{stat}±0.006_{syst} for the first time, which are consistent with the theoretical calculation.

The mechanism by which cannabidiol (CBD) suppresses TNF-α secretion involves inappropriate localization of TNF-α converting enzyme (TACE)

Cannabidiol (CBD) is a phytocannabinoid derived from Cannabis sativa that exerts anti-inflammatory mechanisms. CBD is being examined for its putative effects on the neuroinflammatory disease, multiple sclerosis (MS). One of the major immune mediators that propagates MS and its mouse model experimental autoimmune encephalomyelitis (EAE) are macrophages. Macrophages can polarize into an inflammatory phenotype (M1) or an anti-inflammatory phenotype (M2a). Therefore, elucidating the impact on macrophage polarization with CBD pre-treatment is necessary to understand its anti-inflammatory mechanisms. To study this effect, murine macrophages (RAW 264.7) were pre-treated with CBD (10 µM) or vehicle (ethanol 0.1 %) and were either left untreated (naive; cell media only), or stimulated under M1 (IFN-γ + lipopolysaccharide, LPS) or M2a (IL-4) conditions for 24 hr. Cells were analyzed for macrophage polarization markers, and supernatants were analyzed for cytokines and chemokines. Immunofluorescence staining was performed on M1-polarized cells for the metalloprotease, tumor necrosis factor-α-converting enzyme (TACE), as this enzyme is responsible for the secretion of TNF-α. Overall results showed that CBD decreased several markers associated with the M1 phenotype while exhibiting less effects on the M2a phenotype. Significantly, under M1 conditions, CBD increased the percentage of intracellular and surface TNF-α but decreased secreted TNF-α. This phenomenon might be mediated by TACE as staining showed that CBD sequestered TACE intracellularly. CBD also prevented RelA nuclear translocation. These results suggest that CBD may exert its anti-inflammatory effects by reducing M1 polarization and decreasing TNF-α secretion via inappropriate localization of TACE and RelA.

Three dimensional analysis of the exhalation flow in the proximity of the mouth

The human exhalation flow is characterized in this work from the three-dimensional velocimetry results obtained by using the stereo particle image velocimetry (SPIV) measurement technique on the flow emitted from a realistic airway model. For this purpose, the transient exhalation flow through the mouth of a person performing two different breaths corresponding to two metabolic rates, standing relaxed (SR) and walking active (WA), is emulated and studied. To reproduce the flow realistically, a detailed three-dimensional model obtained from computed tomography measurements on real subjects is used. To cope with the variability of the experimental data, a subsequent analysis of the results is performed using the TR-PIV (time resolved particle image velocimetry) technique. Exhalation produces a transient jet that becomes a puff when flow emission ends. Three-dimensional vector fields of the jet velocity are obtained in five equally spaced transverse planes up to a distance of Image 1 from the mouth at equally spaced time instants Image 2 which will be referred to as phases (φ), from the beginning to the end of exhalation. The time evolution during exhalation of the jet area of influence, the velocity field and the jet air entrainment have been characterized for each of the jet cross sections. The importance of the use of realistic airway models for the study of this type of flow and the influence of the metabolic rate on its development are also analyzed. The results obtained contribute to the characterization of the human exhalation as a pathway of the transmission of pathogens such as SARS-CoV-2 virus.

An advanced machine learning method for simultaneous breast cancer risk prediction and risk ranking in Chinese population: A prospective cohort and modeling study

BACKGROUND

Breast cancer (BC) risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking. We aimed to develop risk-stratification models to predict long- and short-term BC risk among Chinese women and to simultaneously rank potential non-experimental risk factors.

METHODS

The Breast Cancer Cohort Study in Chinese Women, a large ongoing prospective dynamic cohort study, includes 122,058 women aged 25-70 years from the eastern part of China. We developed multiple machine-learning risk prediction models using parametric models (penalized logistic regression, bootstrap, and ensemble learning), which were the short-term ensemble penalized logistic regression (EPLR) risk prediction model and the ensemble penalized long-term (EPLT) risk prediction model to estimate BC risk. The models were assessed based on calibration and discrimination, and following this assessment, they were externally validated in new study participants from 2017 to 2020.

RESULTS

The AUC values of the short-term EPLR risk prediction model were 0.800 for the internal validation and 0.751 for the external validation set. For the long-term EPLT risk prediction model, the area under the receiver operating characteristic curve was 0.692 and 0.760 in internal and external validations, respectively. The net reclassification improvement index of the EPLT relative to the Gail and the Han Chinese Breast Cancer Prediction Model (HCBCP) models for external validation was 0.193 and 0.233, respectively, indicating that the EPLT model has higher classification accuracy.

CONCLUSIONS

We developed the EPLR and EPLT models to screen populations with a high risk of developing BC. These can serve as useful tools to aid in risk-stratified screening and BC prevention.

Determination of the Σ^{+} Timelike Electromagnetic Form Factors

Based on data samples collected with the BESIII detector at the BEPCII collider, the process e^{+}e^{-}→Σ^{+}Σ[over ¯]^{-} is studied at center-of-mass energies sqrt[s]=2.3960, 2.6454, and 2.9000 GeV. Using a fully differential angular description of the final state particles, both the relative magnitude and phase information of the Σ^{+} electromagnetic form factors in the timelike region are extracted. The relative phase between the electric and magnetic form factors is determined to be sinΔΦ=-0.67±0.29(stat)±0.18(syst) at sqrt[s]=2.3960  GeV, ΔΦ=55°±19°(stat)±14°(syst) at sqrt[s]=2.6454  GeV, and 78°±22°(stat)±9°(syst) at sqrt[s]=2.9000  GeV. For the first time, the phase of the hyperon electromagnetic form factors is explored in a wide range of four-momentum transfer. The evolution of the phase along with four-momentum transfer is an important input for understanding its asymptotic behavior and the dynamics of baryons.

Long-term prognostic value of thyroid hormones in left ventricular noncompaction

PURPOSE

Thyroid function is closely related to the prognosis of cardiovascular diseases. This study aimed to explore the predictive value of thyroid hormones for adverse cardiovascular outcomes in left ventricular noncompaction (LVNC).

METHODS

This longitudinal cohort study enrolled 388 consecutive LVNC patients with complete thyroid function profiles and comprehensive cardiovascular assessment. Potential predictors for adverse outcomes were thoroughly evaluated.

RESULTS

Over a median follow-up of 5.22 years, primary outcome (the combination of cardiovascular mortality and heart transplantation) occurred in 98 (25.3%) patients. For secondary outcomes, 75 (19.3%) patients died and 130 (33.5%) patients experienced major adverse cardiovascular events (MACE). Multivariable Cox analysis identified that free triiodothyronine (FT3) was independently associated with both primary (HR 0.455, 95%CI 0.313-0.664) and secondary (HR 0.547, 95%CI 0.349-0.858; HR 0.663, 95%CI 0.475-0.925) outcomes. Restricted cubic spline analysis illustrated that the risk for adverse outcomes increased significantly with the decline of serum FT3. The LVNC cohort was further stratified according to tertiles of FT3 levels. Individuals with lower FT3 levels in the tertile 1 group suffered from severe cardiac dysfunction and remodeling, resulting in higher incidence of mortality and MACE (Log-rank P < 0.001). Subgroup analysis revealed that lower concentration of FT3 was linked to worse prognosis, particularly for patients with left atrial diameter ≥ 40 mm or left ventricular ejection fraction ≤ 35%. Adding FT3 to the pre-existing risk score for MACE in LVNC improved its predictive performance.

CONCLUSION

Through the long-term investigation on a large LVNC cohort, we demonstrated that low FT3 level was an independent predictor for adverse cardiovascular outcomes.

[Clinical study of the efficacies of ruxolitinib plus low-dose PTCY for acute GVHD prevention after haploidentical transplantation in malignant hematological diseases]

Objective: To investigate and verify a novel acute graft versus host disease (aGVHD) prevention protocol in the context of haploidentical hematopoietic stem cell transplantation (haplo-HSCT) . Methods: Patients who underwent haplo-HSCT in our center between January 2022 and December 2022 were included. All patients received reduced doses of cyclophosphamide, Rabbit anti-human tymoglobulin, ruxolitinib, methotrexate, cyclosporine, and MMF to prevent aGVHD. The transplantation outcomes, complications, and survival rate of all patients were investigated. Results: A total of 52 patients with haplo-HSCT were enrolled, 29 (55.8%) male and 23 (44.2%) female, with a median age of 28 (5-59) years. There were 25 cases of acute myeloid leukemia, 17 cases of acute lymphocyte leukemia, 6 cases of myelodysplastic syndrome, 2 cases of chronic myeloid leukemia and 2 cases of myeloproliferative neoplasms. 98.1% of patients had successful engraftment. The incidence of Ⅱ-Ⅳ aGVHD and Ⅲ-Ⅳ aGVHD was 19.2% (95% CI 8.2% -30.3% ) and 7.7% (95% CI 0.2% -15.2% ), respectively. No patients experienced severe gastrointestinal mucositis. The Epstein-Barr virus and CMV reactivation rates were 40.4% and 21.3%, respectively. 9.6% of patients relapsed during followup, with 1-year overall survival, progression-free survival, and non-relapse mortality rates of 86.5% (95% CI 76.9% -96.1% ), 78.8% (95% CI 67.4% -90.3% ) and 11.5% (95% CI 2.6% -20.5% ), respectively. Conclusion: Ruxolitinib combined with a low dose of PTCY is a safe and effective first-line aGVHD prevention strategy.

[Association between waist circumference and ischemic stroke: a prospective study in adults from Qingdao]

Objective: To analyze the association between waist circumference (WC) and ischemic stroke (IS). Methods: The data for the present study were from the prospective cohort study of China Kadoorie Biobank in Qingdao. Using baseline information and IS events of the participants, the Cox proportional hazard regression model and restricted cubic spline (RCS) were used to analyze the association between WC and IS. Results: A total of 33 355 participants were included in the study, with 302 008.88 person-years of follow-up. A total of 1 093 new cases of IS were observed. Multivariate Cox proportional hazard regression model analysis showed that compared to the respondents with normal WC (male <85.0 cm, female <80.0 cm), respondents with excessive WC (male ≥85.0 cm, female ≥80.0 cm) had a 78% higher risk of IS incidence [hazard ratio(HR)=1.78, 95%CI: 1.51-2.10], and the risk increased by 72% (HR=1.72, 95%CI: 1.40-2.12) and 83% (HR=1.83, 95%CI: 1.40-2.39) in men and women. According to the RCS, the increase in WC and the risk of IS showed an "S" trend of nonlinear dose-response relationship. Conclusions: The risk of IS would increase with the WC. Keeping a normal WC is important for preventing IS.

Copy Number Alterations Predict Development of OSCC from Oral Leukoplakia

Oral leukoplakia (OLK) is a common type of potentially malignant disorder. Early identification of the malignancy potential leads to a better management of OLK and prediction of development of oral squamous cell carcinoma (OSCC). However, there has been no effective biomarker to assess the risk of malignancy in OLK. Genomic copy number alteration (CNA) is a complex chromosomal structural variation in the genome and has been identified as a potential biomarker in multiple cancers. This study aimed to develop a predictive model for the malignant transformation risk of OLK by copy number analysis. A total of 431 OLK samples with long-term follow-up (median follow-up of 67 mo) from multiple academic centers were analyzed for CNAs. CNA events increased with the severity of hyperplasia, mild dysplasia, moderate dysplasia, and severe dysplasia. More CNA events were present in patients with OLK who later developed OSCC than in those with OLK who did not. By multivariate Cox regression analysis, the OLK of the CNA scorehigh group showed an increased risk of malignant transformation than the CNA scorelow group (P < 0.001). A CNA score model was developed to accurately predict the prognosis (area under the receiver operating characteristic curve [AUC] = 0.879; 95% confidence interval [CI], 0.799-0.959) and was validated using data from 2 external centers (AUC = 0.836, 95% CI, 0.683-0.989; AUC = 0.876, 95% CI, 0.682-1.000), and all of them showed better prediction performances than histopathological grade in assessing the transformation risk of OLK. Furthermore, we performed CNA models among 4 subgroups of OLK with hyperplasia, mild dysplasia, moderate dysplasia, and severe dysplasia and found that CNA score can accurately predict malignant transformation of different subgroups. CNA score may be a useful biomarker to predict malignant transformation of OLK. Subtyping of OLK by the CNA score could contribute to better management of OLK and predicting development of OSCC.

The impact of air pollutants on spontaneous abortion: a case-control study in Tongchuan City

OBJECTIVES

Studies related to air pollutants and spontaneous abortion in urban northwestern China are scarce, and the main exposure windows of pollutants acting on pregnant women are unclear.

STUDY DESIGN

Case-control study.

METHODS

Data were collected from pregnant women in Tongchuan City from 2018 to 2019. A total of 289 cases of spontaneous abortion and 1156 cases of full-term labor were included and analyzed using a case-control study. Logistic regression models were developed to explore the relationship between air pollutants and spontaneous abortion after Chi square analysis and Air pollutant description.

RESULTS

O3 (odds ratio [OR] = 1.028) is a risk factor for spontaneous abortion throughout pregnancy. PM2.5 (OR = 1.015), PM10 (OR = 1.010), SO2 (OR = 1.026), and NO2 (OR = 1.028) are risk factors for spontaneous abortion in the 30 days before the last menstrual period. PM2.5 (OR = 1.015), PM10 (OR = 1.013), SO2 (OR = 1.036), and NO2 (OR = 1.033) are risk factors for spontaneous abortion in the 30-60 days before the last menstrual period. PM2.5 (OR = 1.028), PM10 (OR = 1.013), SO2 (OR = 1.035), and NO2 (OR = 1.059) are risk factors for spontaneous abortion in the 60-90 days before the last menstrual period.

CONCLUSION

Exposure to high levels of air pollutants may be a cause of increased risk of spontaneous abortion, especially in the first trimester of the last menstrual period.

Restricted growth of molybdenum carbide nanoparticles in hierarchically porous nitrogen-doped carbon matrix for boosting electromagnetic wave absorption performance

With the development of electronic science and technology, electromagnetic pollution is becoming increasingly serious, which urgent people to develop wave-absorbing materials with the features of "thin, light, strong and wide". In this paper, restricted growth of molybdenum carbide nanoparticles in hierarchically porous nitrogen-doped carbon matrix (Mo2C/NC) was designed and prepared via a salt-assisted template route and carbonization process, whose morphology and the wave-absorbing properties are regulated by changing the content of Mo2C/NC nanoparticles. The honeycomb porous Mo2C/NC composites with large specific surface area and smooth surface can optimize the impedance matching and allow the entrance, multiple reflections and scattering of incident electromagnetic waves (EMW), which effective enhance the electromagnetic wave consumption. Meanwhile, the honeycomb cross-linked carbon matrix facilitates the construction of the conductive network and enhances its conductive loss. Furthermore, numerous Mo2C/NC nanoparticles dispersed restricted growth in carbon matrix induces interfacial polarization. In addition, the heteroatom nitrogen doping acts as dipole centers to induce dipole polarization under electromagnetic field. The uniquely designed Mo2C/NC absorbers show satisfactory EMW absorption behaviors of a minimum reflection loss (RLmin) of -61.53 dB at 1.5 mm and an effective absorption bandwidth (EAB) of 9.6 GHz at 3.5 mm. This work enriches the variety of EMW absorbers and offers the route to promote the EMW absorption performance, especially large effective absorption bandwidth.

Comparison of clinical data between the proximal femoral bionic nail (PFBN) and hip replacement for the treatment of femoral intertrochanteric fracture

OBJECTIVE

The aim of this study was to compare the difference between proximal femoral bionic nail (PFBN) and hip replacement (HR) for femoral intertrochanteric fracture.

MATERIALS AND METHODS

A retrospective analysis of the differences in operative time, length of stay, postoperative Harris score, and postoperative mortality between patients with femoral intertrochanteric fracture treated by PFBN and HR admitted to Jinzhai County People's Hospital from October 2020 to September 2022 was performed.

RESULTS

A total of 56 patients with femoral intertrochanteric fracture, 26 with PFBN and 30 with HR, were included in the study. There were no differences in the length of surgery, pre- and post-operative hemoglobin, or post-operative Harris score at 3 months between the two groups. Compared to the HR group, the PFBN group had a lower total cost, shorter hospital stays, and lower mortality but a longer ambulation time, with a difference of 3.36 weeks.

CONCLUSIONS

PFBN may be a promising new treatment for femoral intertrochanteric fracture.

Toripalimab plus axitinib versus sunitinib as first-line treatment for advanced renal cell carcinoma: RENOTORCH, a randomized, open-label, phase III study

BACKGROUND

Immune checkpoint inhibitors in combination with tyrosine kinase inhibitors are standard treatments for advanced clear cell renal cell carcinoma (RCC). This phase III RENOTORCH study compared the efficacy and safety of toripalimab plus axitinib versus sunitinib for the first-line treatment of patients with intermediate-/poor-risk advanced RCC.

PATIENTS AND METHODS

Patients with intermediate-/poor-risk unresectable or metastatic RCC were randomized in a ratio of 1 : 1 to receive toripalimab (240 mg intravenously once every 3 weeks) plus axitinib (5 mg orally twice daily) or sunitinib [50 mg orally once daily for 4 weeks (6-week cycle) or 2 weeks (3-week cycle)]. The primary endpoint was progression-free survival (PFS) assessed by an independent review committee (IRC). The secondary endpoints were investigator-assessed PFS, overall response rate (ORR), overall survival (OS), and safety.

RESULTS

A total of 421 patients were randomized to receive toripalimab plus axitinib (n = 210) or sunitinib (n = 211). With a median follow-up of 14.6 months, toripalimab plus axitinib significantly reduced the risk of disease progression or death by 35% compared with sunitinib as assessed by an IRC [hazard ratio (HR) 0.65, 95% confidence interval (CI) 0.49-0.86; P = 0.0028]. The median PFS was 18.0 months in the toripalimab-axitinib group, whereas it was 9.8 months in the sunitinib group. The IRC-assessed ORR was significantly higher in the toripalimab-axitinib group compared with the sunitinib group (56.7% versus 30.8%; P < 0.0001). An OS trend favoring toripalimab plus axitinib was also observed (HR 0.61, 95% CI 0.40-0.92). Treatment-related grade ≥3 adverse events occurred in 61.5% of patients in the toripalimab-axitinib group and 58.6% of patients in the sunitinib group.

CONCLUSION

In patients with previously untreated intermediate-/poor-risk advanced RCC, toripalimab plus axitinib provided significantly longer PFS and higher ORR than sunitinib and had a manageable safety profile TRIAL REGISTRATION: ClinicalTrials.gov NCT04394975.

[Analysis of the incidence and symptomatology of low anterior resection syndrome after laparoscopic anterior resection for rectal cancer]

Objective: This study aims to explore the temporal trend of Low Anterior Resection Syndrome (LARS) and its symptoms after laparoscopic anterior resection for rectal cancer. Methods: A retrospective cohort study design was employed. The study included primary rectal (adenocarcinoma) cancer patients who underwent laparoscopic anterior resection at Tongji Hospital, Huazhong University of Science and Technology, between January 1, 2010, and December 31, 2020. Complete medical records and follow-up data at 3, 6, 9, 12, and 18 months postoperatively were available for all patients. A total of 1454 patients were included, of whom 1094 (75.2%) were aged ≤65 years, and 597 (41.1%) were females. Among them, 1040 cases (71.5%) had an anastomosis-to-anus distance of 0-5cm, and 86 cases (5.9%) received neoadjuvant treatment. All patients completed the Chinese version of the LARS questionnaire and their LARS occurrence and specific symptom information were recorded at 3, 6, 9, 12, and 18 months postoperatively. Considering past literature and clinical experience, further subgroup analyses were performed to explore the potential impact factors on severe LARS, including anastomosis level, preoperative neoadjuvant therapy, postoperative adjuvant therapy, and the presence of preventive stoma. Results: The occurrence rates of LARS at 3, 6, 9, 12, and 18 months postoperatively were 78.5% (1142/1454), 71.4% (1038/1454), 55.0% (799/1454), 45.7% (664/1454), and 45.7% (664/1454), respectively (χ2=546.180, P<0.001). No statistically significant difference was observed between the 12-month and 18-month time points (P>0.05). When compared with the symptoms at 3 months, the occurrence rates of gas incontinence [1.7% (24/1454) vs. 33.9% (493/1454)], liquid stool incontinence [3.9% (56/1454) vs. 41.9% (609/1454)], increased stool frequency [79.6% (1158/1454) vs. 95.9% (1395/1454)], stool clustering [74.3% (1081/1454) vs. 92.9% (1351/1454)], and stool urgency [46.5% (676/1454) vs. 78.7% (1144/1454)] in the LARS symptom spectrum were significantly alleviated at 12 months (all P<0.05) and remained stable beyond 12 months (all P>0.05). With the extension of postoperative time, the incidence rates of severe LARS exhibited a decreasing trend in different subgroups, of anastomosis level, preoperative neoadjuvant therapy, postoperative adjuvant therapy, and the presence of preventive stoma, and reached stability at 12 months postoperatively (all P>0.05). Conclusion: LARS and its specific symptom profile showed a trend of gradual improvement over time up to 1 year postoperatively, and stabilized after more than 1 year. Increased stool frequency and stool clustering are the most common features of abnormal bowel dys function, which improve slowly after surgery.

First Measurement of the Decay Asymmetry in the Pure W-Boson-Exchange Decay Λ_{c}^{+}→Ξ^{0}K^{+}

Based on 4.4  fb^{-1} of e^{+}e^{-} annihilation data collected at the center-of-mass energies between 4.60 and 4.70 GeV with the BESIII detector at the BEPCII collider, the pure W-boson-exchange decay Λ_{c}^{+}→Ξ^{0}K^{+} is studied with a full angular analysis. The corresponding decay asymmetry is measured for the first time to be α_{Ξ^{0}K^{+}}=0.01±0.16(stat)±0.03(syst). This result reflects the noninterference effect between the S- and P-wave amplitudes. The phase shift between S- and P-wave amplitudes has two solutions, which are δ_{p}-δ_{s}=-1.55±0.25(stat)±0.05(syst)  rad or 1.59±0.25(stat)±0.05(syst)  rad.

[Safety and efficacy of donor-derived chimeric antigen receptor T-cell therapy in patients with relapsed B-cell acute lymphoblastic leukemia after allogeneic hematopoietic stem cell transplantation]

Objective: To investigated the safety and efficacy of donor-derived CD19+ or sequential CD19+ CD22+ chimeric antigen receptor T-cell (CAR-T) therapy in patients with B-cell acute lymphoblastic leukemia (B-ALL) after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Methods: The data of 22 patients with B-ALL who relapsed after allo-HSCT and who underwent donor-derived CAR-T therapy at the Zhujiang Hospital of Southern Medical University and the 920th Hospital of Joint Logistics Support Force of the People's Liberation Army of China from September 2015 to December 2022 were retrospectively analyzed. The primary endpoint was overall survival (OS), and the secondary endpoints were event-free survival (EFS), complete remission (CR) rate, and Grade 3-4 adverse events. Results: A total of 81.82% (n=18) of the 22 patients achieved minimal residual disease-negative CR after CAR-T infusion. The median follow-up time was 1037 (95% CI 546-1509) days, and the median OS and EFS were 287 (95% CI 132-441) days and 212 (95% CI 120-303) days, respectively. The 6-month OS and EFS rates were 67.90% (95% CI 48.30%-84.50%) and 58.70% (95% CI 37.92%-79.48%), respectively, and the 1-year OS and EFS rates were 41.10% (95% CI 19.15%-63.05%) and 34.30% (95% CI 13.92%-54.68%), respectively. Grade 1-2 cytokine release syndrome occurred in 36.36% (n=8) of the patients, and grade 3-4 occurred in 13.64% of the patients (n=3). Grade 2 and 4 graft-versus-host disease occurred in two patients. Conclusion: Donor-derived CAR-T therapy is safe and effective in patients with relapsed B-ALL after allo-HSCT.

Genomic and transcriptomic analysis of breast cancer identifies novel signatures associated with response to neoadjuvant chemotherapy

BACKGROUND

Neoadjuvant chemotherapy (NAC) has become a standard treatment strategy for breast cancer (BC). However, owing to the high heterogeneity of these tumors, it is unclear which patient population most likely benefit from NAC. Multi-omics offer an improved approach to uncovering genomic and transcriptomic changes before and after NAC in BC and to identifying molecular features associated with NAC sensitivity.

METHODS

We performed whole-exome and RNA sequencing on 233 samples (including matched pre- and post-treatment tumors) from 50 BC patients with rigorously defined responses to NAC and analyzed changes in the multi-omics landscape. Molecular features associated with NAC response were identified and validated in a larger internal, and two external validation cohorts, as well as in vitro experiments.

RESULTS

The most frequently altered genes were TP53, TTN, and MUC16 in both pre- and post-treatment tumors. In comparison with pre-treatment tumors, there was a significant decrease in C > A transversion mutations in post-treatment tumors (P = 0.020). NAC significantly decreased the mutation rate (P = 0.006) of the DNA repair pathway and gene expression levels (FDR = 0.007) in this pathway. NAC also significantly changed the expression level of immune checkpoint genes and the abundance of tumor-infiltrating immune and stroma cells, including B cells, activated dendritic cells, γδT cells, M2 macrophages and endothelial cells. Furthermore, there was a higher rate of C > T substitutions in NAC nonresponsive tumors than responsive ones, especially when the substitution site was flanked by C and G. Importantly, there was a unique amplified region at 8p11.23 (containing ADGRA2 and ADRB3) and a deleted region at 3p13 (harboring FOXP1) in NAC nonresponsive and responsive tumors, respectively. Particularly, the CDKAL1 missense variant P409L (p.Pro409Leu, c.1226C > T) decreased BC cell sensitivity to docetaxel, and ADGRA2 or ADRB3 gene amplifications were associated with worse NAC response and poor prognosis in BC patients.

CONCLUSIONS

Our study has revealed genomic and transcriptomic landscape changes following NAC in BC, and identified novel biomarkers (CDKAL1P409L, ADGRA2 and ADRB3) underlying chemotherapy resistance and poor prognosis, which could guide the development of personalized treatments for BC.

Dual-Stage Surficial Microstructure to Enhance the Sensitivity of MXene Pressure Sensors for Human Physiological Signal Acquisition

Accompanying the rapid growth of wearable electronics, flexible pressure sensors have received great interest due to their promising application in health monitoring, human-machine interfaces, and intelligent robotics. The high sensitivity over a wide responsive range, integrated with excellent repeatability, is a crucial requirement for the fabrication of reliable pressure sensors for various wearable scenes. In this work, we developed a highly sensitive and long-life flexible pressure sensor by constructing surficial microarrayed architecture polydimethylsiloxane (PDMS) film as a substrate and Ti3C2TX MXene/bacterial cellulose (BC) hybrid as an active sensing layer. The specific surficial morphology of PDMS couples with nanointercalated structure of Ti3C2Tx MXene/BC can effectively improve the sensitivity through controlling the stress distribution and layer spacing under different levels of pressure loading. In addition, abundant spontaneous hydrogen bonds between BC and Ti3C2Tx MXene nanosheets endow the MXene coating with highly adhesive strength on the PDMS surface; hence, the cyclic stability of the pressure sensor is greatly boosted. As a result, the obtained MXene/BC/PDMS (MBP) pressure sensor delivers high sensitivity (528.87 kPa-1), fast response/recovery time (45 ms/29 ms), low detection limit (0.6 Pa), and outstanding repeatability of up to 8000 cycles. Those excellent sensing properties of the MBP sensor allow it to serve as a reliable wearable device to monitor full-range human physiological motions, and it is expected to be applied in next-generation portable electronics, such as E-skins, smart healthcare, and the Internet of Things technology.

[Analysis of gene characteristics and core genome characteristics of carbapenem-resistant Enterobacter cloacae in rural residents of Weifang City, Shandong Province]

Objective: To investigate the drug-resistant gene characteristics and core genome characteristics of carbapenem-resistant Enterobacter cloacae (CR-ECL) in rural residents of Weifang City, Shandong Province. Methods: Fecal samples were collected from rural community residents in Weifang City, Shandong Province in 2017. Drug-resistant strains were screened using a carbapenem-resistant enterobacter chromogenic medium. CR-ECL positive strains were acquired via Matrix Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry(MALDI-TOFMS) analysis. The antibiotic resistance phenotype of CR-ECL was determined using a microbroth dilution assay. Whole genome sequencing (WGS) and analysis were conducted, along with an examination of the immediate vicinity of the blaNDM gene and phylogenetic analysis of the strains. Results: A total of 628 fecal samples were collected and tested, of which 6 were CR-ECL positive (detection rate 0.96%), all exhibiting multiple drug resistance (MDR) phenotypes. Six CR-ECL strains had four MLST genotypes (ST), all of which carried multiple drug resistance genes (blaNDM-1, blaNDM-5, etc.) and virulence genes (acrA, acrB, entB, fepC, etc.). There were mobile genetic elements ISAba125, TN3-IS3000, TN3 and IS5 in the genetic environment surrounding the blaNDM gene. The phylogenetic tree showed that the multi-locus sequence typing of the core genome (cgMLST) was consistent with the single nucleotide polymorphism (SNPs) results. The cgMLST results showed that the allele differences between strains 2BC0101B and 2BC0251B, 2BG0561B and 2BI0221B were 2 and 1, respectively. The SNPs results showed that the above two pairs of bacteria also clustered together. It was found that the strains of chicken fecal samples in the National Center for Biotechnology Information (NCBI) database were located in the center of the evolutionary tree, and the local sequences could be traced back to American human sequences. Conclusion: Multidrug-resistant CR-ECL is detected in rural community residents in Weifang City, Shandong Province.

Effects of empagliflozin on progression of chronic kidney disease: a prespecified secondary analysis from the empa-kidney trial

BACKGROUND

Sodium-glucose co-transporter-2 (SGLT2) inhibitors reduce progression of chronic kidney disease and the risk of cardiovascular morbidity and mortality in a wide range of patients. However, their effects on kidney disease progression in some patients with chronic kidney disease are unclear because few clinical kidney outcomes occurred among such patients in the completed trials. In particular, some guidelines stratify their level of recommendation about who should be treated with SGLT2 inhibitors based on diabetes status and albuminuria. We aimed to assess the effects of empagliflozin on progression of chronic kidney disease both overall and among specific types of participants in the EMPA-KIDNEY trial.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA), and included individuals aged 18 years or older with an estimated glomerular filtration rate (eGFR) of 20 to less than 45 mL/min per 1·73 m2, or with an eGFR of 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher. We explored the effects of 10 mg oral empagliflozin once daily versus placebo on the annualised rate of change in estimated glomerular filtration rate (eGFR slope), a tertiary outcome. We studied the acute slope (from randomisation to 2 months) and chronic slope (from 2 months onwards) separately, using shared parameter models to estimate the latter. Analyses were done in all randomly assigned participants by intention to treat. EMPA-KIDNEY is registered at ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and then followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroups of eGFR included 2282 (34·5%) participants with an eGFR of less than 30 mL/min per 1·73 m2, 2928 (44·3%) with an eGFR of 30 to less than 45 mL/min per 1·73 m2, and 1399 (21·2%) with an eGFR 45 mL/min per 1·73 m2 or higher. Prespecified subgroups of uACR included 1328 (20·1%) with a uACR of less than 30 mg/g, 1864 (28·2%) with a uACR of 30 to 300 mg/g, and 3417 (51·7%) with a uACR of more than 300 mg/g. Overall, allocation to empagliflozin caused an acute 2·12 mL/min per 1·73 m2 (95% CI 1·83-2·41) reduction in eGFR, equivalent to a 6% (5-6) dip in the first 2 months. After this, it halved the chronic slope from -2·75 to -1·37 mL/min per 1·73 m2 per year (relative difference 50%, 95% CI 42-58). The absolute and relative benefits of empagliflozin on the magnitude of the chronic slope varied significantly depending on diabetes status and baseline levels of eGFR and uACR. In particular, the absolute difference in chronic slopes was lower in patients with lower baseline uACR, but because this group progressed more slowly than those with higher uACR, this translated to a larger relative difference in chronic slopes in this group (86% [36-136] reduction in the chronic slope among those with baseline uACR <30 mg/g compared with a 29% [19-38] reduction for those with baseline uACR ≥2000 mg/g; ptrend<0·0001).

INTERPRETATION

Empagliflozin slowed the rate of progression of chronic kidney disease among all types of participant in the EMPA-KIDNEY trial, including those with little albuminuria. Albuminuria alone should not be used to determine whether to treat with an SGLT2 inhibitor.

FUNDING

Boehringer Ingelheim and Eli Lilly.

Asthma and clinical outcomes of COVID-19 in a community setting

OBJECTIVES

The association between asthma and COVID-19 mortality remains inconclusive. We examined the association between asthma and clinical outcomes of patients with COVID-19.

STUDY DESIGN

A case-control study based on a surveillance cohort in Harris County, Texas.

METHODS

Using the data of 21,765 patients who reported having at least one chronic health condition, we investigated the association between asthma and COVID-19 severity, characterized primarily by hospitalization and death. Unconditional logistic regression models were used to estimate the multivariable odds ratio (mOR) and its 95 % confidence interval (CI) of COVID-19 severity associated with asthma and other chronic lung diseases, adjusting for demographic and other comorbidities. A P-value < 0.005 was considered statistically significant after correcting multiple testing.

RESULTS

In total, 3034 patients (13.9 %) had asthma, and 774 (3.56 %) had other chronic lung diseases. The case death rate among patients with asthma and other chronic lung diseases was 0.75 % and 19.0 %, respectively. Compared to patients without the respective conditions, patients with asthma had lower odds of death (mOR = 0.44, 95 % CI: 0.27-0.69), while patients with other chronic lung diseases had higher odds of hospitalization (mOR = 2.02, 95 % CI: 1.68-2.42) and death (mOR = 1.95, 95 % CI: 1.52-2.49) (P-values < 0.005). Risk factors for COVID-19 mortality included older age, male gender, diabetes, obesity, hypertension, cardiovascular disease, active cancer, and chronic kidney disease.

CONCLUSIONS

The public health surveillance data suggested that preexisting asthma was inversely associated with COVID-19 mortality.

Loneliness prevention and the role of the Public Health system

AIMS

To evaluate evidence on loneliness interventions that have been assessed and found effective, both for remediation and addressing fundamental causes of loneliness; to consider why population-level primary prevention strategies targeting fundamental causes are necessary, and determine areas for future research; and to outline an integrated approach to prevention considering roles for the Public Health system.

METHOD

We conducted a review of systematic reviews to identify effective loneliness interventions and classified them in our Population-Prevention Matrix according to public health impact, amount of individual effort required, and level of prevention. We also highlighted emerging interventions that have yet to be formally evaluated.

RESULTS

We identified a range of preventive or therapeutic approaches, and a dearth of population-level primary prevention interventions targeting fundamental causes of loneliness. Filling this gap will be essential in addressing the loneliness epidemic, and we provided emerging examples of population-level primary prevention interventions that may inform future efforts.

CONCLUSION

Based on evidence to date, we suggest an integrated approach to prevention with significant roles for the US Public Health system, including its function as Chief Health Strategist to lead and guide multisystem approaches to loneliness prevention, with a particular focus on population-level primary prevention strategies.

Novel Ameloblastin Variants, Contrasting Amelogenesis Imperfecta Phenotypes

Amelogenesis imperfecta (AI) comprises a group of rare, inherited disorders with abnormal enamel formation. Ameloblastin (AMBN), the second most abundant enamel matrix protein (EMP), plays a critical role in amelogenesis. Pathogenic biallelic loss-of-function AMBN variants are known to cause recessive hypoplastic AI. A report of a family with dominant hypoplastic AI attributed to AMBN missense change p.Pro357Ser, together with data from animal models, suggests that the consequences of AMBN variants in human AI remain incompletely characterized. Here we describe 5 new pathogenic AMBN variants in 11 individuals with AI. These fall within 3 groups by phenotype. Group 1, consisting of 6 families biallelic for combinations of 4 different variants, have yellow hypoplastic AI with poor-quality enamel, consistent with previous reports. Group 2, with 2 families, appears monoallelic for a variant shared with group 1 and has hypomaturation AI of near-normal enamel volume with pitting. Group 3 includes 3 families, all monoallelic for a fifth variant, which are affected by white hypoplastic AI with a thin intact enamel layer. Three variants, c.209C>G; p.(Ser70*) (groups 1 and 2), c.295T>C; p.(Tyr99His) (group 1), and c.76G>A; p.(Ala26Thr) (group 3) were identified in multiple families. Long-read AMBN locus sequencing revealed these variants are on the same conserved haplotype, implying they originate from a common ancestor. Data presented therefore provide further support for possible dominant as well as recessive inheritance for AMBN-related AI and for multiple contrasting phenotypes. In conclusion, our findings suggest pathogenic AMBN variants have a more complex impact on human AI than previously reported.

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

BACKGROUND

The EMPA-KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62-0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16-1·59), representing a 50% (42-58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1).

INTERPRETATION

In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease.

FUNDING

Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council.

Prenatal diagnosis of polycystic renal diseases: diagnostic yield, novel disease-causing variants, and genotype-phenotype correlations

BACKGROUND

Polycystic renal disease is a frequent congenital anomaly of the kidneys, but research using chromosomal microarray analysis and exome sequencing in fetuses with polycystic renal disease remains sparse, with most studies focusing on the multisystem or genitourinary system.

OBJECTIVE

This study aimed to assess the detection rate of detectable genetic causes of fetal polycystic renal disease at different levels, novel disease-causing variants, and genotype-phenotype correlations.

STUDY DESIGN

This study included 220 fetal polycystic renal disease cases from January 2014 to June 2022. Cases were divided into the following 3 groups: isolated multicystic dysplastic kidneys, nonisolated multicystic dysplastic kidneys, and suspected polycystic kidney disease group. We reviewed data on maternal demographics, ultrasonographic results, chromosomal microarray analysis/exome sequencing results, and pregnancy outcomes.

RESULTS

In our cohort, chromosomal microarray analysis identified 19 (8.6%) fetuses carrying chromosomal abnormalities, and the most common copy number variation was 17q12 microdeletion (7/220; 3.2%). Furthermore, 94 families chose to perform trio-exome sequencing testing, and 21 fetuses (22.3%) were found to harbor pathogenic/likely pathogenic variants. There was a significant difference in the live birth rate among the 3 groups (91/130 vs 46/80 vs 1/10; P<.001). Among 138 live birth cases, 106 (78.5%) underwent postnatal ultrasound review, of which 95 (89.6%) had a consistent prenatal-postnatal ultrasound diagnosis.

CONCLUSION

For both isolated and nonisolated polycystic renal disease, our data showed high detection efficiency with both testing tools. The detection of novel pathogenic variants expands the known disease spectrum of polycystic renal disease-associated genes while enriching our understanding of the genotype-phenotype correlation. Therefore, we consider it feasible to perform chromosomal microarray analysis+exome sequencing testing in fetal polycystic renal disease. Moreover, prenatal-postnatal ultrasound concordance was greater, the live birth rate was higher, and prognosis was better when known genetic disorders were excluded, indicating that genetic testing results significantly influenced pregnancy decisions.