Global stability for age-infection-structured human immunodeficiency virus model with heterogeneous transmission

In this paper, we analyze the global asymptotic behaviors of a mathematical susceptible-infected(SI) age-infection-structured human immunodeficiency virus(HIV) model with heterogeneous transmission. Mathematical analysis shows that the local and global dynamics are completely determined by the basic reproductive number R 0 . If R 0 < 1 , disease-free equilibrium is globally asymptotically stable. If R 0 > 1 , it shows that disease-free equilibrium is unstable and the unique endemic equilibrium is globally asymptotically stable. The proofs of global stability utilize Lyapunov functions. Besides, the numerical simulations are illustrated to support these theoretical results and sensitivity analysis of each parameter for R 0 is performed by the method of partial rank correlation coefficient(PRCC).

Predictive value of peripheral blood leukocytes-based methylation of Long non-coding RNA MALAT1 and H19 in the chemotherapy effect and prognosis of gastric cancer

BACKGROUND

The predictive value of the methylation of Long non-coding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) and H19 promoters in peripheral blood leukocytes as a non-invasive biomarker for the chemotherapy effect and prognosis gastric cancer (GC) is unclear.

METHODS

The DNA methylation of H19 and MALAT1 between chemotherapy-sensitive and non-sensitive groups and between groups with better and worse survival of GC was compared using regression analyses. Several predictive nomograms were constructed. The genetic alteration of MALAT1 and H19 and the association between gene expression and immune status in GC were also investigated using bioinformatics analysis.

RESULTS

Higher genetic methylations in peripheral blood were noticed in GC groups with poorer survival. The constructed nomograms presented strong predictive values for the chemotherapy effect and 3-year survival of disease-free survival, progression-free survival, and overall survival, with the area under the curve as 0.838, 0.838, 0.912, and 0.925, respectively. Significant correlations between MALAT1 or H19 expression and marker genes of immune checkpoints and immune pathways were noticed. The high infiltration of macrophages in H19-high and low infiltration of CD8+ T cells in MALAT1-high groups were associated with worse survival of GC.

CONCLUSIONS

MALAT1 and H19 have the potential to predict the chemotherapy response and clinical outcomes of GC.

Prenatal exposure to poly/perfluoroalkyl substances and risk for congenital heart disease in offspring

Congenital heart disease (CHD) is the most prevalent congenital malformation worldwide, and the association between per- and polyfluoroalkyl substances (PFASs) exposure and CHD in population has only received limited study. Therefore, we conducted a multicenter case-control study to explore the associations between prenatal exposure to individual PFASs, and also a PFAS mixture, and CHD risk, including 185 CHDs and 247 controls in China from 2016 to 2021. Thirteen PFASs in maternal plasma were quantified using liquid chromatography-tandem mass spectrometry. Logistic regression and two multipollutant models (Bayesian kernel machine regression [BKMR] and quantile g-computation [qgcomp]) were used to assess the potential associations between any individual PFAS, and also a PFAS mixture, and CHD risk. After adjusting for potential confounders, logistic regression indicated significant associations between elevated levels of perfluorononanoic acid (odds ratio [OR]= 1.30, 95% confidence intervals [CI]: 1.07-1.58), perfluorodecanoic acid (OR=2.07, 95%CI: 1.32-3.26), and perfluoroundecanoic acid (OR=2.86, 95%CI:1.45-5.65) and CHD risk. The BKMR model and qgcomp approach identified that a significant positive association between the PFAS mixture and risk for CHD. These findings provide essential evidence that there is indeed a health crisis associated with PFASs and that it is linked to CHD.

Preparation of core-shell structure Ag@TiO2 plasma photocatalysts and reduction of Cr(VI): Size dependent and LSPR effect

The poor light absorption and low carrier separation efficiency of Titanium dioxide (TiO2) limit its further application. The introduction of plasma metal Ag have the potential to solve these drawbacks owing to its plasma resonance effect. Thus core-shell structure Ag@TiO2 plasma photocatalysts was prepared by using facile reduction method in this work. More specifically, Ag@TiO2 composite catalysts with different Ag loading amounts were prepared in the presence of surfactant PVP. Ag@TiO2 demonstrates excellent light absorption performance and photoelectric separation efficiency compared with pure TiO2. As a result, it displays excellent performance of Cr(VI) reduction under visible light. The optimal composite catalysts Ag@TiO2-5P achieves exceptional visible-light-driven photocatalytic Cr(VI) reduction efficiency of 0.01416 min-1 that is 2.29 times greater than pure TiO2. To investigate the role of PVP, we also synthesized Ag@TiO2-5 without PVP. The experimental results show that although Ag@TiO2-5 Cr(VI) reduction performance is superior to pure TiO2, it significantly decreases compared with Ag@TiO2-5P. The results of TEM and optoelectronic testing show that agglomeration of Ag particles leads to a decrease in the photoelectric separation efficiency of Ag@TiO2-5. The smaller Ag particles provide more active sites and demonstrating a stronger overall local surface plasmon resonance (LSPR) effect. DMPO spin-trapping ESR spectra testing indicates that ∙O2- and ∙OH are the main reactive species. This research provides a potential strategy to prepare Ag-based plasma photocatalysts for environment protection.

Polysaccharide from Boletus aereus ameliorates DSS-induced colitis in mice by regulating the MANF/MUC2 signaling and gut microbiota

Inflammatory bowel diseases (IBD) are chronic inflammatory conditions characterized by disruptions in the colonic mucus barrier and gut microbiota. In this study, a novel soluble polysaccharide obtained from Boletus aereus (BAP) through water extraction was examined for its structure. The protective effects of BAP on colitis were investigated using a DSS-induced mice model. BAP was found to promote the expression of intestinal mucosal and tight junction proteins, restore the compromised mucus barrier, and suppress the activation of inflammatory signaling. Moreover, BAP reshape the gut microbiota and had a positive impact on the composition of the gut microbiota by reducing inflammation-related microbes. Additionally, BAP decreased cytokine levels through the MANF-BATF2 signaling pathway. Correlation analysis revealed that MANF was negatively correlated with the DAI and the level of cytokines. Furthermore, the depletion of gut microbiota using antibiotic partially inhabited the effect of BAP on the activation of MANF and Muc2, indicating the role of gut microbiota in its protective effect against colitis. In conclusion, BAP had an obvious activation on MANF under gut inflammation. This provides new insights into the prospective use of BAP as a functional food to enhance intestinal health.

Aptamer-Based Nongenetic Reprogramming of CARs Enables Flexible Modulation of T Cell-Mediated Tumor Immunotherapy

Innovating the design of chimeric antigen receptors (CARs) beyond conventional structures would be necessary to address the challenges of efficacy, safety, and applicability in T cell-based cancer therapy, whereas excessive genetic modification might complicate CAR design and manufacturing, and increase gene editing risks. In this work, we used aptamers as the antigen-recognition unit to develop a nongenetic CAR engineering strategy for programming the antitumor activity and specificity of CAR T cells. Our results demonstrated that aptamer-functionalized CAR (Apt-CAR) T cells could be directly activated by recognizing target antigens on cancer cells, and then impart a cytotoxic effect for cancer elimination in vitro and in vivo. The designable antigen recognition capability of Apt-CAR T cells allows for easy modulation of their efficacy and specificity. Additionally, multiple features, e.g., tunable antigen-binding avidity and the tumor microenvironment responsiveness, could be readily integrated into Apt-CAR design without T cell re-engineering, offering a new paradigm for developing adaptable immunotherapeutics.

The relationship between anxiety symptoms and disturbances in biological rhythms in patients with depression

BACKGROUND

Biological rhythms denote the cyclical patterns of life activities anchored to a 24-hour cycle. Research shows that depression exhibits disturbances in biological rhythms. Yet, the relationship between these biological rhythms and concomitant anxiety symptoms is insufficiently investigated in structured clinical assessments.

METHODS

This multicenter study, carried out in four Chinese hospitals, comprehensively examined the relationship between anxiety and disruptions in biological rhythms among patients with depression. The study encompassed 218 patients diagnosed with depression and 205 matched healthy controls. The Chinese version of the Biological Rhythms Interview of Assessment in Neuropsychiatry was utilized to evaluate the participants' biological rhythms, focusing on four dimensions: sleep, activity, social, and diet.

RESULTS

In patients with depression, there is a significant positive correlation between the severity of anxiety symptoms and the disturbances in biological rhythms. The severity of anxiety and depression, along with the quality of life, are independently associated with disruptions in biological rhythms. The mediation model reveals that anxiety symptoms mediate the relationship between depressive symptoms and biological rhythms.

CONCLUSION

This research highlights the role of anxiety within the spectrum of depressive disorders and the associated disturbances in biological rhythms. Our findings shed light on potential pathways towards more targeted preventive strategies and therapeutic interventions for individuals battling depression and anxiety.

Flexible free-standing Fe-CoP-NAs/CC nanoarrays for high-performance full lithium-ion batteries

In this study, a flexible, free-standing Fe-doped CoP nanoarrays electrode for superior lithium-ion storage has been successfully fabricated. The electrode combines the advantages of a Fe-doping and a flexible carbon cloth (CC) support, resulting in a high specific capacity (1356 mAh/g at 0.2 A/g) and excellent cycling stability (1138 mAh/g after 100 cycles). The cyclic voltammetry (CV) curves at different scan rates investigate the outstanding lithium storage behavior of Fe-CoP-NAs/CC which indicates a combined influence of diffusion behavior and capacitance behavior on the electrochemical process. The galvanostatic intermittent titration technique (GITT) analyzes the diffusion kinetics of Li+ which indicates the fast diffusion kinetics in the Fe-CoP/NAs/CC anode. The assembled Fe-CoP-NAs/CC//LiFePO4 battery exhibits a remarkable capacity of 325.2 mAh/g even at 5 A/g. And the battery also has good cycle stability, and still provides 498.1 mAh/g specific capacity after 200 cycles. Moreover, the Fe-CoP-NAs/CC//LiFePO4 soft-pack battery can continuously power the LEDs when it is bent at various angles which demonstrates its potential for use in wearable devices.

Investigating the association between inflammation mediated by mushroom consumption and mild cognitive impairment in Chinese older adults

Background: Chronic inflammatory stimulation is a major risk factor for mild cognitive impairment. Mushroom consumption and inflammatory factors may play an important role in the pathogenesis of mild cognitive impairment. Additionally, consuming mushrooms can reduce the levels of inflammatory cytokines and preserve cognitive function. Therefore, this study aimed to investigate the relationship between mushroom consumption and serum inflammatory cytokines and mild cognitive impairment (MCI). Methods: Binary logistic regression was used to determine the relationship between mushroom consumption and MCI in 550 participants. Subsequently, mediation analysis was used to analyze the relationship between mushroom consumption, inflammatory factors, and the Montreal Cognitive assessment (MoCA) score in 248 participants. Results: Mushroom consumption was associated with MCI (odds ratio = 0.623, 95% confidence interval = 0.542-0.715, P < 0.001). The association between mushroom intake and MCI was mediated by interleukin-6 (IL-6) and hypersensitive C-reactive protein (hs-CRP), and the MoCA score was 12.76% and 47.59%, respectively. Conclusion: A high intake of mushrooms was associated with a low risk of MCI. Serum inflammatory factors including IL-6 and hs-CRP play a partial mediating role between mushroom intake and the MoCA score, and the underlying mechanism needs to be further explored.

Inadvertent antibiotic exposure during pregnancy may increase the risk for neural tube defects in offspring

BACKGROUND

As emerging environmental contaminants, antibiotics pose potential threats to human health, in particular to pregnant women and infants. However, the potential harm of inadvertent antibiotic exposure (IAE) is often disregarded in light of the focus on intentional antibiotic use during pregnancy. Currently, little is known about the effects of IAE during pregnancy on fetal neural tube development.

METHODS

In this case-control study, we used questionnaire data from 855 subjects to investigate the effects of intentional antibiotic use in early pregnancy on neural tube defects (NTDs). Then we tested for placental antibiotics in mothers who had not intentionally used antibiotics, and the compounds were detected in 379 subjects; these were considered IAE cases. We assessed the association between IAE during pregnancy and fetal NTDs using both multivariable logistic and multi-pollutant exposure models. We also analyzed the correlation between maternal dietary habits and placental antibiotics to explore possible sources of IAE.

RESULTS

Only 50 of 855 participants (5.8%) intentionally used antibiotics and such use showed no significant association with NTD risk (odds ratio [OR] = 1.92, confidence interval [95%CI] = [0.66, 5.59]). However, 14 of 15 placental antibiotics were detected in 378 of 379 subjects (99.7%) and multivariable logistic analysis indicated that high levels of placental macrolides were significantly associated with increased NTD risk (4.42 [2.01-10.45]). Multi-pollutant exposure analysis suggested an increase in NTD risk with an increase in exposure to a mixture of placental antibiotics, among which macrolides were the most important contributor. In addition, the level of placental macrolides was positively correlated with the intake frequency of milk. Finally, mothers who drank river, well, or pond water had higher levels of placental macrolides than those who drank only tap water.

CONCLUSIONS

Intentional antibiotic use during early pregnancy may not be associated with NTDs, while IAE during pregnancy is associated with higher NTD risk in offspring. Macrolides are crucial risk factors. Milk, and river, well, or pond water may be important sources of IAE.

Effect of Regulation of Chemerin/Chemokine-like Receptor 1/Stimulator of Interferon Genes Pathway on Astrocyte Recruitment to Aβ Plaques

Recruitment and accumulation of reactive astrocytes around senile plaques are common pathological features of Alzheimer's disease (AD), with unclear mechanisms. Chemerin, an adipokine implicated in neuroinflammation, acts through its receptor, chemokine-like receptor 1 (CMKLR1), which also functions as a receptor for amyloid β (Aβ). The impact of the chemerin/CMKLR1 axis on astrocyte migration towards Aβ plaques is unknown. Here we investigated the effect of CMKLR1 on astrocyte migration around Aβ deposition in APP/PS1 mice with Cmklr1 knockout (APP/PS1-Cmklr1-/-). CMKLR1-expressed astrocytes were upregulated in the cortices and hippocampi of 9-month-old APP/PS1 mice. Chemerin mainly co-localized with neurons, and its expression was reduced in the brains of APP/PS1 mice, compared to WT mice. CMKLR1 deficiency decreased astrocyte colocalization with Aβ plaques in APP/PS1-Cmklr1-/- mice, compared to APP/PS1 mice. Activation of the chemerin/CMKLR1 axis promoted the migration of primary cultured astrocytes and U251 cells, and reduced astrocyte clustering induced by Aβ42. Mechanistic studies revealed that chemerin/CMKLR1 activation induced STING phosphorylation. Deletion of STING attenuated the promotion of the chemerin/CMKLR1 axis relative to astrocyte migration and abolished the inhibitory effect of chemerin on Aβ42-induced astrocyte clustering. These findings suggest the involvement of the chemerin/CMKLR1/STING pathway in the regulation of astrocyte migration and recruitment to Aβ plaques/Aβ42.

Detection method for unrecognized spatial disorientation based on optical flow stimuli

BACKGROUND

Flight accidents caused by spatial disorientation (SD) greatly affect flight safety.

OBJECTIVE

Few studies have been devoted to the evaluation of SD.

METHODS

10 pilots and 10 non-pilots were recruited for the experimental induction of SD. Videos for giving optical flow stimuli were played at two different flow speeds to induce SD. Subjective judgment and center of foot pressure (CoP) data were collected from the tests. The data were combined to determine the occurrence of SD and analyze the SD types.

RESULTS

The number of self-reported SD events was slightly smaller in the pilots than in the non-pilots. The average upper bound of the confidence interval for the standard deviation of CoP was 0.32 ± 0.09 cm and 0.38 ± 0.12 cm in the pilots and non-pilots, respectively. This indicator was significantly lower in the pilots than in the non-pilots (P= 0.03). The success rate of the experimental induction of unrecognized SD was 26.7% and 45.0% in the pilots and non-pilots, respectively.

CONCLUSION

The method offered a new to analyze unrecognized SD. We could determine the occurrence unrecognized SD. This is an essential means of reducing flight accidents caused by unrecognized SD.

IGFBP1a is a nutrient deficient response factor that can inhibit fish reproduction through the hypothalamus-pituitary-ovary axis†

Reproduction is a high energy consuming process, so long-term malnutrition can significantly inhibit gonadal development. However, little is known about the molecular mechanism by which fasting inhibits reproduction. Our present study found that fasting could dramatically induce insulin-like growth factor binding protein 1 (IGFBP1) expression in the liver, hypothalamus, pituitary and ovaries of grass carp. In addition, IGFBP1a in the hypothalamus-pituitary-gonad axis could inhibit the development of gonads. These results indicated that fasting may participate in the regulation of fish gonadal development through the mediation of IGFBP1a. Further studies found that IGFBP1a could markedly inhibit gonadotropin-releasing hormone 3 expressions in hypothalamus cells. At the pituitary level, IGFBP1a could significantly reduce the gonadotropin hormones (LH and FSH) expression by blocking the action of pituitary insulin-like growth factor 1. Interestingly, IGFBP1a could also directly inhibit the expression of lhr, fshr, and sex steroid hormone synthase genes (cyp11a, cyp17a, and cyp19a1) in the ovary. These results indicated that IGFBP1a should be a nutrient deficient response factor that could inhibit fish reproduction through the hypothalamus-pituitary-ovary axis.

Prenatal chromosomal microarray analysis and karyotyping in fetuses with isolated choroid plexus cyst: A retrospective case-control study

OBJECTIVES

To evaluate the the diagnostic yield of chromosomal microarray analysis (CMA) in fetuses with isolated CPC (iCPC).

METHODS

A total of 315 fetuses with iCPC (iCPC group) and 364 fetuses without abnormal ultrasound findings (control group) were recruited between July 2014 to March 2018.

RESULTS

The overall diagnostic yield of chromosomal abnormalities by CMA and karyotyping in iCPC group was up to 4.1 %, higher than 1.4 % in the control group, p < 0.05. The detection rate of pathogenic or likely pathogenic copy number variants (CNVs) with clinical significance by CMA in iCPC group (1.3 %) was higher than in control group (0 %), p < 0.05. According to the type of chromosome abnormalities, the missed diagnosis rate of non-invasive prenatal testing (NIPT) was 1.6 % in our study.

CONCLUSIONS

The presence of iCPC on ultrasound examination suggests a potential indication for genetic counseling. Karyotyping and chromosomal microarray analysis may be considered for fetuses with iCPC. It is important to be aware of the limitations of non-invasive prenatal testing, as there is a possibility of residual risk.

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.

Nanomaterials Regulate Bacterial Quorum Sensing: Applications, Mechanisms, and Optimization Strategies

Anti-virulence therapy that interferes with bacterial communication, known as "quorum sensing (QS)", is a promising strategy for circumventing bacterial resistance. Using nanomaterials to regulate bacterial QS in anti-virulence therapy has attracted much attention, which is mainly attributed to unique physicochemical properties and excellent designability of nanomaterials. However, bacterial QS is a dynamic and multistep process, and there are significant differences in the specific regulatory mechanisms and related influencing factors of nanomaterials in different steps of the QS process. An in-depth understanding of the specific regulatory mechanisms and related influencing factors of nanomaterials in each step can significantly optimize QS regulatory activity and enhance the development of novel nanomaterials with better comprehensive performance. Therefore, this review focuses on the mechanisms by which nanomaterials regulate bacterial QS in the signal supply (including signal synthesis, secretion, and accumulation) and signal transduction cascade (including signal perception and response) processes. Moreover, based on the two key influencing factors (i.e., the nanomaterial itself and the environment), optimization strategies to enhance the QS regulatory activity are comprehensively summarized. Collectively, applying nanomaterials to regulate bacterial QS is a promising strategy for anti-virulence therapy. This review provides reference and inspiration for further research on the anti-virulence application of nanomaterials.

Recyclable fabrication of hollow N-doped amorphous carbon nanospindles with abundant short-range curved carbon fragments as bifunctional anode for lithium/sodium ion storage

A recyclable hard-template method is proposed to exploit spindle-shaped hollow nitrogen-doped amorphous carbon (h-NAC) with a large number of short-range curved carbon fragments as anodes for lithium/sodium ion batteries (LIBs/SIBs). Besides providing adsorption sites due to the high existence of oxygen-containing functional groups (CO and COOH), the heavily exposed edge regions also provide a favorable storage environment with high adsorption energy for Li+/Na+ due to their short-range curved structure. Importantly, the etching solution of hard templates can be recycled to generate the FeOOH nanospindles as a precursor through a simple chemical titration, which supplies a new idea for the green preparation of hollow materials. The h-NAC electrode is proven to be bifunctional for storing lithium and sodium ions, displaying favorable rate capability (255 mAh g-1 and 106 mAh g-1 at 5 A g-1 for LIBs and SIBs, respectively). After 1000 cycles at 1 A g-1, the reproducible capacities of the LIBs and SIBs kept 496 mAh g-1 and 181 mAh g-1, respectively.

Effect of glycolysis on water holding capacity during postmortem aging of Jersey cattle-yak meat

BACKGROUND

Postmortem muscle moisture loss leads to a decrease in carcass weight and can adversely impact overall meat quality. Therefore, it is critical to investigate water holding capacity (WHC) to enhance meat quality. Current research has primarily focused on examining the correlation between signaling molecules and meat quality in relation to the glycolysis effect on muscle WHC. But there exists a significant knowledge gap regarding the mechanism of WHC in Jersey cattle-yak meat.

RESULTS

Jersey cattle-yak meat pH decreased and then increased during postmortem aging. Lactate content, cooking loss, pressing loss, drip loss and centrifuging loss of Jersey cattle-yak meat increased and then decreased during postmortem aging. The glycogen content of Jersey cattle-yak meat was significantly higher than that of yak meat at 6-120 h, being 8.40% higher than that of yak meat at 120 h. The activity of key glycolytic enzymes hexokinase (HK), pyruvate kinase (PK), phosphofructokinase (PFK) and lactate dehydrogenase (LDH) in Jersey cattle-yak meat was lower than that in yak meat. Correlation analysis showed that Jersey cattle-yak meat WHC was positively correlated with the activity of HK, PK, PFK and LDH.

CONCLUSIONS

The WHC of Jersey cattle-yak meat was higher than that of Gannan yak meat, and it was significantly positively correlated with the activity of key enzymes of the glycolytic signaling pathway. Therefore, the glycolysis rate can be reduced by inhibiting enzyme activity to improve Jersey cattle-yak meat WHC and meat quality. © 2023 Society of Chemical Industry.

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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The mechanism of Shenlong Jianji treatment of idiopathic pulmonary fibrosis inhibits fibroblast-to-myofibroblast transformation via the TGF-β1/smads signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Shenlong Jianji (SLJJ) is a Chinese herbal compound composed of traditional medicines for supplementing Qi, nourishing Yin, promoting blood circulation, and removing obstruction in channels. It is widely used to treat idiopathic pulmonary fibrosis (IPF) in China. However, the underlying mechanism of SLJJ remains unclear.

AIM OF THIS STUDY

To elucidate the efficacy and mechanisms of SLJJ in the treatment of IPF through in vivo and in vitro experiments.

MATERIAL AND METHODS

84 Wistar rats were randomly and equally divided into 7 groups: the control group (CTRL), the sham operation group (SHAM), the model group (IPF), the low dose of SLJJ group (L-SLJJ), the middle dose of SLJJ group (M-SLJJ), the high dose of SLJJ group (H-SLJJ), and the pirfenidone group (PFD). The rats in the CTRL, SHAM, and IPF groups were given normal saline each time for 28 days; the SLJJ groups were given Shenlong Jianji (9 g kg-1·d-1, 18 g kg-1·d-1, 36 g kg-1·d-1), and pirfenidone was administered as a sequential dose. After 28 days, the general condition of the rats was evaluated, and samples were collected. The lung coefficient was measured. The pathological changes of lung in each group were observed by H&E staining and Masson staining. α-SMA, collagen 1, and E-cadherin proteins were detected by immunohistochemistry. α-SMA, collagen 1, vimentin, E-cadherin, N-cadherin, TGF-β1, smad2, and smad3 proteins were detected by WB in vivo.In vitro, A scratch test was used to assess the ratio of cell migration. α-SMA, vimentin, E-cadherin, and N-cadherin protein levels were evaluated by a cellular immunofluorescence assay. TGF-β1/smads signaling pathway was detected by WB. HPLC-Q-TOF/MS analysis was used to identify the active compounds in the SLJJ. Molecular docking determined the free binding energy of the compound with the TGF-β1 protein.

RESULTS

SLJJ significantly improved the respiratory symptoms, heart rate, mental state, and food intake of IPF group rats and decreased the lung coefficient. In the IPF group, inflammatory cells were infiltrated, and the thickened alveoli wall and alveoli collapse were shown, while significantly alleviating pathological changes in the SLJJ and PFD groups. Masson staining showed that SLJJ and PFD decreased the collagen expression. Immunohistochemical results showed that the expressions of α-SMA, collagen 1, and N-cadherin decreased in the SLJJ and PFD groups, while E-cadherin increased significantly compared with the IPF group. SLJJ regulates TGF-β1/smads signaling pathway proteins in vivo. SLJJ decreased the ratio of migration in HFL-1 cells; SLJJ reduced the fluorescence intensity of α-SMA, vimentin, and N-cadherin and increased the fluorescence intensity of E-cadherin in primary rat lung (PRL) fibroblast cells and HFL-1 cells. WB results showed that SLJJ significantly down-regulated α-SMA, Vimentin, N-cadherin, TGF-β1, smad2, and p-smad2/3 proteins expression and up-regulated E-cadherin protein expression in vitro, whereas SRI-011381 (a TGF-β1 agonist) antagonized the effects of SLJJ.

CONCLUSION

SLJJ inhibits idiopathic pulmonary fibrosis. The TGF- β1/Smads signaling pathway can be the target of SLJJ, which inhibits fibroblast-to-myofibroblast transformation and is expected to be a new drug for the treatment of IPF.

Altering optical zone diameter, reverse curve width, and compression factor: impacts on visual performance and axial elongation in orthokeratology

PURPOSE

To investigate the effects of modifications in back optical zone diameter (BOZD), reverse curve width (RCW), and compression factor (CF) on refractive error changes and axial elongation in myopic children undergoing orthokeratology (ortho-k) over a 12-month period.

METHOD

In this retrospective study, data from 126 myopic children undergoing ortho-k fitting were analyzed. Subjects were categorized into four distinct groups based on lens design parameters: Group A (BOZD 6.0 mm, RCW 0.6 mm, CF 0.75 D); Group B (BOZD 6.0 mm, RCW 0.6 mm, CF 1.25 D); Group C (BOZD 5.4 mm, RCW 0.9 mm, CF 1.25 D); and Group D (BOZD 5.0 mm, RCW 1.1 mm, CF 1.25 D). The study evaluated uncorrected visual acuity (UCVA), corneal topography, and axial length (AL) at intervals, using Linear Mixed Models (LMMs) for time-based changes, and ANOVA or Kruskal-Wallis tests for group differences in AL elongation. A multivariable regression analysis identified factors independently associated with AL elongation.

RESULTS

Within the first day and week, all four groups displayed significant improvements in UCVA and alterations in corneal curvature, which subsequently stabilized. Although UCVA variations between groups were subtle, Group D had less corneal curvature change than Groups A and B initially and exhibited significantly less AL elongation after one year. No significant difference in corneal curvature change or AL elongation was observed between Group C and the other groups. Multiple regression analysis indicated that older baseline age, greater baseline spherical equivalent refractive error, and smaller BOZD were associated with less AL elongation.

CONCLUSION

The study reveals a positive correlation between BOZD and axial length growth over the 12-month period. A pure 0.5 D CF increment demonstrates a nonsignificant impact. This study provides new ideas into optimizing the parameters of ortho-k lenses.

Spontaneous uterine rupture with amniotic sac protrusion during the third trimester of a unicornuate uterus pregnancy: A rate case report

RATIONALE

Uterine rupture is an obstetrical emergency associated with severe maternal and fetal mortality. It is rare in the unscarred uterus of a primipara.

PATIENT CONCERNS

A 25-year-old woman in her 38th week of gestation presented with slight abdominal pain of sudden onset 10 hours before. An emergency cesarean section was done. After surgery, the patient and the infant survived.

DIAGNOSES

With slight abdominal pain of clinical signs, ultrasound examination showed that the amniotic sac was found in the peritoneal cavity with a rupture of the uterine fundus.

INTERVENTIONS

Uterine repair and right salpingectomy.

OUTCOMES

After surgery, the patient and the infant survived. The newborn weighed 2600 g and had an Apgar score of 10 points per minute. Forty-two days after delivery, the uterus recovered well.

LESSONS

Spontaneous uterine rupture should be considered in patients even without acute pain, regardless of gestational age, and pregnancy with abdominal cystic mass should consider the possibility of uterine rupture.

Estimating the methane flux of the Dajiuhu subalpine peatland using machine learning algorithms and the maximal information coefficient technique

The eddy covariance (EC) technique has emerged as the most widely used method for long-term continuous methane flux (FCH4) observations. However, the completeness of the FCH4 time series is limited by instrumental failures and data quality issues, resulting in missing data gaps ranging from 20 % to 90 %. In this situation, the excellent performance of machine learning (ML) algorithms in filling missing FCH4 data has provided a foundation for developing regional-scale FCH4 models. In this study, we established estimation models for FCH4 utilizing random forest (RF), support vector machine (SVM), back propagation (BP) and nonlinear multiple regression (MLR) algorithms. The maximal information coefficient (MIC) technique was employed to identify and rank the environmental factors that were correlated with FCH4. Our findings revealed that soil temperature (Ts), soil water content (SWC) and air temperature (Ta) were the primary environmental factors influencing FCH4. Among the four algorithms, from perspectives of model accuracy and relatively small number of driving factors, the RF models exhibited the best performance, followed by BP and SVM, whereas MLR demonstrated the lowest performance. Among the 144 RF models established using nine datasets, RF model with 8 driving factors in all-year (RFall-year8) could capture seasonal variations. Ultimately, we recommend (RFall-year8 as the optimal model for estimating FCH4 in the Dajiuhu subalpine peatland.

Mutually enhanced multi-view information learning for segmentation of lung tumor in CT images

Objective.The accurate automatic segmentation of tumors from computed tomography (CT) volumes facilitates early diagnosis and treatment of patients. A significant challenge in tumor segmentation is the integration of the spatial correlations among multiple parts of a CT volume and the context relationship across multiple channels.Approach.We proposed a mutually enhanced multi-view information model (MEMI) to propagate and fuse the spatial correlations and the context relationship and then apply it to lung tumor CT segmentation. First, a feature map was obtained from segmentation backbone encoder, which contained many image region nodes. An attention mechanism from the region node perspective was presented to determine the impact of all the other nodes on a specific node and enhance the node attribute embedding. A gated convolution-based strategy was also designed to integrate the enhanced attributes and the original node features. Second, transformer across multiple channels was constructed to integrate the channel context relationship. Finally, since the encoded node attributes from the gated convolution view and those from the channel transformer view were complementary, an interaction attention mechanism was proposed to propagate the mutual information among the multiple views.Main results.The segmentation performance was evaluated on both public lung tumor dataset and private dataset collected from a hospital. The experimental results demonstrated that MEMI was superior to other compared segmentation methods. Ablation studies showed the contributions of node correlation learning, channel context relationship learning, and mutual information interaction across multiple views to the improved segmentation performance. Utilizing MEMI on multiple segmentation backbones also demonstrated MEMI's generalization ability.Significance.Our model improved the lung tumor segmentation performance by learning the correlations among multiple region nodes, integrating the channel context relationship, and mutual information enhancement from multiple views.

BNIP3 and DAPK1 methylation in peripheral blood leucocytes are noninvasive biomarkers for gastric cancer

OBJECTIVE

The objective of this study is to comprehensively investigate the potential value of BNIP3 and DAPK1 methylation in peripheral blood leukocytes as a non-invasive biomarker for the detection of gastric cancer (GC), prediction of chemotherapy efficacy, and prognosis assessment.

PATIENTS AND METHODS

Initially, multiple bioinformatic analyses were employed to explore the genetic landscape and biological effects of BNIP3 and DAPK1 in GC tissues. Subsequently, case-control and prospective follow-up studies were conducted to compare the differences in BNIP3 and DAPK1 methylation levels in peripheral blood leukocytes among GC patients and healthy controls, as well as between patients exhibiting sensitivity and resistance to platinum plus fluorouracil treatment, and between patients with varying survival outcomes of GC. Additionally, several predictive nomograms were constructed based on the identified CpG sites and relevant clinical parameters to forecast the occurrence of GC, chemotherapy efficacy, and prognosis.

RESULTS

The upregulation of BNIP3 and DAPK1 was found to be associated with the development and poorer survival outcomes of GC. Furthermore, the expression of BNIP3/DAPK1 exhibited an inverse relationship with their DNA methylation levels and demonstrated a positive correlation with immune cell infiltration, as well as the IC50 values of 5-Fluorouracil and Cisplatin in GC tissues. Increased infiltration of macrophages in the high-expression groups was observed to be linked to unfavorable GC survival. In the case-control and follow-up studies, lower methylation levels of BNIP3 and DAPK1 were identified in the peripheral leukocytes of GC patients compared to healthy controls. Hypomethylation was also associated with more aggressive subtypes, diminished chemotherapy efficacy, and poorer survival outcomes in GC.

CONCLUSION

The DNA methylation of BNIP3 and DAPK1 in peripheral blood leukocytes holds promise as a novel non-invasive biomarker for predicting the occurrence of GC, chemotherapy efficacy, and prognosis assessment.

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.

Prolyl isomerase Pin1 sculpts the immune microenvironment of colorectal cancer

Pin1, a peptide prolyl cis-trans isomerase, is overexpressed and/or overactivated in many human malignancies. However, whether Pin1 regulates the immunosuppressive TME has not been well defined. In this study, we detected the effect of Pin1 on immune cells and immune checkpoint PD-L1 in the TME of CRC and explored the anti-tumor efficacy of Pin1 inhibitor ATRA combined with PD-1 antibody. We found that Pin1 facilitated the immunosuppressive TME by raising the proportion of myeloid-derived suppressor cells (MDSCs) and declining the percentage of CD8+ T cells and CD4+ T cells. Pin1 restrained PD-L1 protein expression in CRC cells and the effect was tempered by endoplasmic reticulum (ER) stress inducers. Mechanically, Pin1 overexpression decreased the stability of PD-L1 and promoted its degradation by mitigating ER stress. Silencing or inhibiting Pin1 promoted PD-L1 protein expression by inducing ER stress. Hence, Pin1 inhibitor ATRA enhanced the anti-tumor efficacy of PD-1 antibody in the CRC allograft by upregulating PD-L1. Our results reveal the critical and pleiotropic effects of Pin1 on managing the immune cells and immune checkpoint PD-L1 in the TME of CRC, providing a new promising candidate for combination with immunotherapy.

Engineered macrophage-derived cellular vesicles for NIR-II fluorescence imaging-guided precise cancer photo-immunotherapy

Significant progress has been made in cancer immunotherapy; however, challenges such as interpatient variability, limited treatment response, and severe side effects persist. Although nanoimmunotherapy has emerged as a promising approach, the construction of precise and efficient nanosystems remain formidable challenges. Herein, a multifunctional nanoplatform was developed using macrophage-derived cellular vesicles (MCVs) for NIR-II imaging-guided precise cancer photo-immunotherapy. MCVs exhibited excellent tumor targeting and TAMs re-education effects, serving as both delivery carriers and therapeutic agents. Through amide bond, indocyanine green (ICG) was conjugated to the surface of MCVs, enabling in vivo tracking of MCVs distribution. Notably, ICG exhibited dual functionality as a NIR-II fluorescent agent and possessed photodynamic and photothermal effects, enabling the conversion of light energy into chemical or heat energy to eliminate tumor cells. This precision phototherapy triggered immunogenic cell death (ICD) of tumor, thereby activating the anti-tumor immune response. Additionally, MCVs loaded with R848, a toll-like receptor agonist, augmented the ICD-induced anti-tumor immunity. Animal experiments confirmed that MCVs-mediated photoimmunotherapy promoted T cell infiltration, inhibited tumor growth, and improved survival rates. In conclusion, we have developed a promising precision immunotherapy strategy capable of enhancing the immune response while mitigating off-target effects. These findings offer encouraging prospects for clinical translation.

Characterization of fermented pomegranate juice: ACE inhibitory activity under in vitro digestion, antioxidant capacity, phenolics composition, chemical properties and sensory evaluation

Consuming pomegranate juice (PJ) is beneficial for hypertensive regulation because of the phenolic compounds in PJ and their inhibitory activity on angiotensin-I-converting enzyme (ACE). To better utilize bioactive function of food, microorganism fermentation has been adopted to alter phenolic metabolism. This study confirms that even under in vitro digestion, fermented PJ (FPJ) maintains higher ACE inhibitory activity than that of PJ. The main phenolic compounds in PJ were compared either under fermentation or in vitro digestion. This study finds that fermentation promotes antioxidant capacity of PJ. The chemical properties of FPJ are evaluated and the corresponding relationship with bioactivities is analyzed. A sensory evaluation comparison is conducted between FPJ and PJ, furnishing interesting information for consumers. This study highlights the relationship between ACE inhibitory activity of PJ and phenolic composition under fermentation and in vitro digestion, providing novel insights for diet regulation of phenolic-rich FPJ in ACE inhibition therapy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10068-023-01388-w.

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.

Clinical and neuroimaging association between neuropsychiatric symptoms and nutritional status across the Alzheimer's disease continuum: a longitudinal cohort study

OBJECTIVES

To investigate the association between neuropsychiatric symptoms (NPS) and nutritional status, and explore their shared regulatory brain regions on the Alzheimer's disease (AD) continuum.

DESIGN

A longitudinal, observational cohort study.

SETTING

Data were collected from the Chinese Imaging, Biomarkers, and Lifestyle study between June 1, 2021 and December 31, 2022.

PARTICIPANTS

Overall, 432 patients on the AD continuum, including amnestic mild cognitive impairment and AD dementia, were assessed at baseline, and only 165 patients completed the (10.37 ± 6.08) months' follow-up.

MEASUREMENTS

The Mini-Nutritional Assessment (MNA) and Neuropsychiatric Inventory (NPI) were used to evaluate nutritional status and NPS, respectively. The corrected cerebral blood flow (cCBF) measured by pseudo-continuous arterial spin labeling of the dietary nutrition-related brain regions was analyzed. The association between the NPS at baseline and subsequent change in nutritional status and the association between the changes in the severity of NPS and nutritional status were examined using generalized linear mixed models.

RESULTS

Increased cCBF in the left putamen was associated with malnutrition, general NPS, affective symptoms, and hyperactivity (P < 0.05). The presence of general NPS (β = -1.317, P = 0.003), affective symptoms (β = -1.887, P < 0.001), and appetite/eating disorders (β = -1.714, P < 0.001) at baseline were associated with a decline in the MNA scores during follow-up. The higher scores of general NPI (β = -0.048), affective symptoms (β = -0.181), and appetite/eating disorders (β = -0.416; all P < 0.001) were longitudinally associated with lower MNA scores after adjusting for confounding factors.

CONCLUSIONS

We found that baseline NPS were predictors of a decline in nutritional status on the AD continuum. The worse the severity of affective symptoms and appetite/eating disorders, the poorer the nutritional status. Furthermore, abnormal perfusion of the putamen may regulate the association between malnutrition and NPS, which suggests their potentially common neural regulatory basis.

Artificial DNA Framework Channel Modulates Antiapoptotic Behavior in Ischemia-Stressed Cells via Destabilizing Promoter G-Quadruplex

Regulating folding/unfolding of gene promoter G-quadruplexes (G4s) is important for understanding the topological changes in genomic DNAs and the biological effects of such changes on important cellular events. Although many G4-stabilizing ligands have been screened out, effective G4-destabilizing ligands are extremely rare, posing a great challenge for illustrating how G4 destabilization affects gene function in living cells under stress, a long-standing question in neuroscience. Herein, we report a distinct methodology able to destabilize gene promoter G4s in ischemia-stressed neural cells by mitigating the ischemia-induced accumulation of intracellular K+ with an artificial membrane-spanning DNA framework channel (DFC). We also show that ischemia-triggered K+ influx is positively correlated to anomalous stabilization of promoter G4s and downregulation of Bcl-2, an antiapoptotic gene with neuroprotective effects against ischemic injury. Intriguingly, the DFC enables rapid transmembrane transport of excessive K+ mediated by the internal G4 filter, leading to the destabilization of endogenous promoter G4 in Bcl-2 and subsequent turnover of gene expression at both transcription and translation levels under ischemia. Consequently, this work enriches our understanding of the biological roles of endogenous G4s and may offer important clues to study the cellular behaviors in response to stress.

Efficacy and safety of thoracic radiotherapy in extensive-stage small-cell lung cancer patients receiving first-line immunotherapy plus chemotherapy: a propensity score matched multicentre retrospective analysis

BACKGROUND

Platinum-etoposide chemotherapy combined with immune checkpoint inhibitors (ICIs) has been recommended as the first-line standard treatment for extensive-stage small-cell lung cancer (ES-SCLC). However, the effect of thoracic radiotherapy (TRT) on these patients is still unknown. This study aimed to evaluate the efficacy and safety of TRT for ES-SCLC patients who responded to first-line ICIs and chemotherapy (CHT).

METHODS

Patients who received 4 to 6 cycles of ICIs and CHT as first-line therapy at three hospitals between 2018 and 2022 were included in the analysis. All patients were divided into two groups based on whether they received TRT as first-line treatment, and propensity score matching (PSM) was performed to ensure that the characteristics of two groups were well-balanced. The primary endpoints were overall survival (OS) and progression-free survival (PFS), and the secondary endpoint was toxic effects.

RESULTS

A total of 276 patients were included, and the median follow-up time was 22.3 (range, 4.0-53.73) months. After PSM, 197 patients were further analysed, and 99 of whom received TRT. The baseline characteristics were well-balanced between patients in the TRT and non-TRT groups. There were significant differences in PFS between the TRT and non-TRT groups, with the median PFS of 10.76 and 7.63 months, respectively (P = 0.014). Significantly improved OS was observed in the TRT group (21.67 vs. 16.6 months, P = 0.009). In addition, the use of TRT was an independent prognostic factor for PFS and OS of ES-SCLC patients receiving ICIs plus CHT. In terms of safety, no significant increase of any grades adverse event (AE) (P = 0.874) and G3-4 AE (P = 0.909) was observed for patients receiving TRT. Radiation esophagitis, gastrointestinal and hematologic toxicities were the most common AEs in TRT group, which were tolerable. And high-dose radiotherapy was associated with higher incidence of pneumonitis.

CONCLUSION

Addition of TRT showed significant survival benefits and well tolerability in ES-SCLC patients receiving platinum-etoposide CHT and ICIs, which could be a feasible first-line treatment strategy for ES-SCLC patients.

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.

From pixels to patient care: deep learning-enabled pathomics signature offers precise outcome predictions for immunotherapy in esophageal squamous cell cancer

BACKGROUND

Immunotherapy has significantly improved survival of esophageal squamous cell cancer (ESCC) patients, however the clinical benefit was limited to only a small portion of patients. This study aimed to perform a deep learning signature based on H&E-stained pathological specimens to accurately predict the clinical benefit of PD-1 inhibitors in ESCC patients.

METHODS

ESCC patients receiving PD-1 inhibitors from Shandong Cancer Hospital were included. WSI images of H&E-stained histological specimens of included patients were collected, and randomly divided into training (70%) and validation (30%) sets. The labels of images were defined by the progression-free survival (PFS) with the interval of 4 months. The pretrained ViT model was used for patch-level model training, and all patches were projected into probabilities after linear classifier. Then the most predictive patches were passed to RNN for final patient-level prediction to construct ESCC-pathomics signature (ESCC-PS). Accuracy rate and survival analysis were performed to evaluate the performance of ViT-RNN survival model in validation cohort.

RESULTS

163 ESCC patients receiving PD-1 inhibitors were included for model training. There were 486,188 patches of 1024*1024 pixels from 324 WSI images of H&E-stained histological specimens after image pre-processing. There were 120 patients with 227 images in training cohort and 43 patients with 97 images in validation cohort, with balanced baseline characteristics between two groups. The ESCC-PS achieved an accuracy of 84.5% in the validation cohort, and could distinguish patients into three risk groups with the median PFS of 2.6, 4.5 and 12.9 months (P < 0.001). The multivariate cox analysis revealed ESCC-PS could act as an independent predictor of survival from PD-1 inhibitors (P < 0.001). A combined signature incorporating ESCC-PS and expression of PD-L1 shows significantly improved accuracy in outcome prediction of PD-1 inhibitors compared to ESCC-PS and PD-L1 anlone, with the area under curve value of 0.904, 0.924, 0.610 for 6-month PFS and C-index of 0.814, 0.806, 0.601, respectively.

CONCLUSIONS

The outcome supervised pathomics signature based on deep learning has the potential to enable superior prognostic stratification of ESCC patients receiving PD-1 inhibitors, which convert the images pixels to an effective and labour-saving tool to optimize clinical management of ESCC patients.

Comparing Strain Assessment in Compressed Sensing and Conventional Cine MRI

The aim of this study is to assess the feasibility of compressed sensing (CS) acceleration methods compared to conventional segmented cine (Seg) cardiac magnetic resonance (CMR) for evaluating left ventricular (LV) function and strain by feature tracking (FT). In this prospective study, 45 healthy volunteers underwent CMR imaging used Seg, threefold (CS3), fourfold (CS4), and eightfold (CS8) CS acceleration. Cine images were scored for quality (1-5 scale). LV volumetric and functional parameters and global longitudinal (GLS), circumferential (GCS), and radial strains (GRS) were quantified. LV volumetric and functional parameters exhibited no differences between Seg and all CS cines (all P > 0.05). The strains were similar for Seg, CS3, and CS4 (all P > 0.05). Similarly, no significant differences were observed in GRS and GCS between Seg and CS8 (all P > 0.05), but the global longitudinal strain was significantly lower for CS8 versus Seg (P < 0.001). Image quality declined with CS acceleration, especially in long-axis views with CS8. CS cine MRI at acceleration factor 4 maintained good image quality and accurate measurements of LV function and strain, although there was a slight reduction in the quality of long-axis images and GLS with CS8. CS acceleration up to a factor of 4 enabled fast CMR evaluations, making it suitable for clinical use.

Critical roles of PAI-1 in lipopolysaccharide-induced acute lung injury

PURPOSE

Plasminogen activator inhibitor-1 (PAI-1) is the main inhibitor of fibrinolytic systems. The effect of PAI-1 on inflammatory response is still inconsistent. Our study was conducted to investigate its effects on inflammation to clarify the role of PAI-1 in acute lung injury (ALI) induced by lipopolysaccharide (LPS).

MATERIAL AND METHODS

ALI models were established in wild-type (WT) and PAI-1 knockout (KO) mice by LPS intervention for 48 ​h. Lung histopathology, wet-dry ratio, total cell count and TNF-α concentration in bronchoalveolar lavage fluid (BALF), and inflammation related proteins were detected. Flow cytometry was used to sort neutrophils, macrophages, regulatory T cells (Treg) and T helper cell 17 (Th17). RNA sequencing was performed to find differentially expressed genes. Masson staining and immunohistochemistry were used to analyze pulmonary fiber deposition and proliferation.

RESULTS

Compared with ALI (WT) group, the wet-dry ratio, the total number of BALF cells, the concentration of TNF-α in BALF, and the expression of pp65 in the lung tissue was increased in ALI (PAI-1 KO) group, with increased proportion of neutrophils, decreased proportion of macrophages and decreased proportion of Treg/Th17 in the lung tissue. Collagen fiber deposition and PCNA expression were lighter in ALI (PAI-1 KO) group than ALI (WT) group. PPI analysis showed that PAI-1 was closely related to TNF, IL-6, IL-1β, Smad2/3 and mainly concentrated in the complement and coagulation system, TNF-α and IL-17 signaling pathways.

CONCLUSIONS

PAI-1 KO could aggravate ALI induced by LPS at 48 ​h. PAI-1 may be an important target to improve the prognosis of ALI.

A novel method of identifying estuary high-nutrient zones for water quality management

Coastal shallow waters are highly vulnerable to pollution, often leading to the development of intricate eutrophication zones. However, accurately determining these areas poses a significant challenge due to the complex interplay of estuarine hydrodynamics and nutrient transformation. To address such issue, a novel method was proposed to identify high-nutrient zones through calculating the continuous zonation of released tracers when their instantaneous concentrations declined to 1/e of their initial values. The method was well tested using idealized estuary models with varying shape parameters, water depths and river discharges. The results consistently revealed that the boundaries of high-nutrient zones fell within the mixed zone, characterized by salinity levels of 10- 20 psu. In Shenzhen Bay, a typical shallow bay, distinct differences were observed in the concentrations of dissolved inorganic nitrogen (DIN) and PO43-. Both the 20 psu isohaline and the proposed method effectively identified the partition boundary of high DIN and PO43- in 2001-2010, but only the newly proposed method demonstrated accuracy in delineating the actual high-nutrient zone during the continuous nutrient reduction period from 2010 to 2020. This study provides a practical and feasible approach that can serve as an auxiliary decision-making tool for managing estuarine water environments, and it has potential to facilitate the implementation of timely and effective measures for pollution control.

Ezrin inhibition alleviates oxidative stress and pyroptosis via regulating TRPML1-calcineurin axis mediated enhancement of autophagy in spinal cord injury

Spinal cord injury (SCI) presents profound ramifications for patients, leading to diminished motor and sensory capabilities distal to the lesion site. Once SCI occurs, it not only causes great physical and psychological problems for patients but also imposes a heavy economic burden. Ezrin is involved in various cellular processes, including signal transduction, cell death, inflammation, chemotherapy resistance and the stress response. However, whether Ezrin regulates functional repair after SCI and its underlying mechanism has not been elucidated. Here, our results showed that there is a marked augmentation of Ezrin levels within neurons and Ezrin inhibition markedly diminished glial scarring and bolstered functional recuperation after SCI. RNA sequencing indicated the potential involvement of pyroptosis, oxidative stress and autophagy in the enhancement of functional recovery upon reduced Ezrin expression. Moreover, the inhibition of Ezrin expression curtailed pyroptosis and oxidative stress by amplifying autophagy. Our studies further demonstrated that Ezrin inhibition promoted autophagy by increasing TFEB activity via the Akt-TRPML1-calcineurin pathway. Finally, we concluded that inhibiting Ezrin expression alleviates pyroptosis and oxidative stress by enhancing TFEB-driven autophagy, thereby promoting functional recovery after SCI, which may be a promising therapeutic target for SCI treatment.

Model construction and drug therapy of primary ovarian insufficiency by ultrasound-guided injection

BACKGROUND

Clinically, hormone replacement therapy (HRT) is the main treatment for primary ovarian insufficiency (POI). However, HRT may increase the risk of both breast cancer and cardiovascular disease. Exosomes derived from human umbilical cord mesenchymal stem cell (hUC-MSC) have been gradually applied to the therapy of a variety of diseases through inflammation inhibition, immune regulation, and tissue repair functions. However, the application and study of hUC-MSC exosomes in POI remain limited.

METHODS

Here, we first constructed four rat animal models: the POI-C model (the "cyclophosphamide-induced" POI model via intraperitoneal injection), the POI-B model (the "busulfan-induced" POI model), the POI-U model (the "cyclophosphamide-induced" POI model under ultrasonic guidance), and MS model (the "maternal separation model"). Second, we compared the body weight, ovarian index, status, Rat Grimace Scale, complications, and mortality rate of different POI rat models. Finally, a transabdominal ultrasound-guided injection of hUC-MSC exosomes was performed, and its therapeuticy effects on the POI animal models were evaluated, including changes in hormone levels, oestrous cycles, ovarian apoptosis levels, and fertility. In addition, we performed RNA-seq to explore the possible mechanism of hUC-MSC exosomes function.

RESULTS

Compared with the POI-C, POI-B, and MS animal models, the POI-U model showed less fluctuation in weight, a lower ovarian index, fewer complications, a lower mortality rate, and a higher model success rate. Second, we successfully identified hUC-MSCs and their exosomes, and performed ultrasound-guided intraovarian hUC-MSCs exosomes injection. Finally, we confirmed that the ultrasound-guided exosome injection (termed POI-e) effectively improved ovarian hormone levels, the oestrous cycle, ovarian function, and fertility. Mechanically, hUC-MSCs may play a therapeutic role by regulating ovarian immune and metabolic functions.

CONCLUSIONS

In our study, we innovatively constructed an ultrasound-guided ovarian drug injection method to construct POI-U animal models and hUC-MSC exosomes injection. And we confirmed the therapeutic efficacy of hUC-MSC exosomes on the POI-U animal models. Our study will offer a better choice for new animal models of POI in the future and provides certain guidance for the hUC-MSCs exosome therapy in POI patients.

Effects of Muscle Type and Aging on Glycolysis and Physicochemical Quality Properties of Bactrian camel (Camelus bactrianus) Meat

Poor tenderness of camel meat has seriously hampered the development of the camel meat industry. This study investigated the effects of muscle fiber composition and ageing time on meat quality, glycolytic potential, and glycolysis-related enzyme activities. Muscle samples of the longissimus thoracis (LT), psoas major (PM), and semitendinosus (ST) were collected from eight 8-10 year old Sonid Bactrian camels (females). Muscle fiber composition was examined by ATPase staining and immunohistochemistry. Meat quality indexes, glycolytic potential, and activities of major glycolytic enzymes were examined at 4 °C aging for 1, 6, 24, 72, and 120 h. The results showed that LT was mainly composed of type IIb muscle fibers, whereas PM and ST were mainly composed of type I muscle fibers. The PCR results of the myosin heavy chain (MyHC) were consistent with the ATPase staining results. During aging, the shear force of LT muscle was always greater than that of PM and ST, and its glycolysis was the strongest; type IIa, IIb, and IIx muscle fibers were positively correlated with muscle shear force and glycolysis rate, and type I muscle fibers were significantly and negatively correlated with the activities of the key enzymes of glycolysis within 6 h. The results showed that the muscle fibers of LT muscle had the greatest glycolysis capacity. These results suggest that an excessive type IIb muscle fiber number percentage and area in camel meat accelerated the glycolysis process, but seriously affected the sensory profile of the camel meat. The results of this study provide directions for the camel industry when addressing the poor tenderness of camel meat.

Topological Single-stranded DNA Encoding and Programmable Assembly of Molecular Nanostructures for NIR-II Cancer Theranostics

Molecular nanotechnology promises to offer privileged access to developing NIR-II materials with precise structural and functional manipulation for transformable theranostic applications. However, the lack of an affordable, yet general, method makes this goal currently inaccessible. By virtue of the intriguing nucleic acid chemistry, here we present an artificial base-directed topological single-strand DNA encoding design that enables one-step synthesis of valence-controlled NIR-II molecular nanostructures and spatial assembly of these nanostructures to modulate their behaviors in living systems. As proof-of-concept studies, we construct ultrasmall Ag2 S quantum dots and pH-responsive, size-tunable CuS assemblies for in vivo NIR-II fluorescence imaging and deep tumor photothermal therapy. This work paves a new way for creating functionally diversified architectures and broadens the scope of DNA-encoded material engineering.

Dynamics of the Gut Microbiota and Faecal and Serum Metabolomes during Pregnancy-A Longitudinal Study

Normal pregnancy involves numerous physiological changes, including changes in hormone levels, immune responses, and metabolism. Although several studies have shown that the gut microbiota may have an important role in the progression of pregnancy, these findings have been inconsistent, and the relationship between the gut microbiota and metabolites that change dynamically during and after pregnancy remains to be clarified. In this longitudinal study, we comprehensively profiled the temporal dynamics of the gut microbiota, Bifidobacterium communities, and serum and faecal metabolomes of 31 women during their pregnancies and postpartum periods. The microbial composition changed as gestation progressed, with the pregnancy and postpartum periods exhibiting distinct bacterial community characteristics, including significant alterations in the genera of the Lachnospiraceae or Ruminococcaceae families, especially the Lachnospiraceae FCS020 group and Ruminococcaceae UCG-003. Metabolic dynamics, characterised by changes in nutrients important for fetal growth (e.g., docosatrienoic acid), anti-inflammatory metabolites (e.g., trans-3-indoleacrylic acid), and steroid hormones (e.g., progesterone), were observed in both serum and faecal samples during pregnancy. Moreover, a complex correlation was identified between the pregnancy-related microbiota and metabolites, with Ruminococcus1 and Ruminococcaceae UCG-013 making important contributions to changes in faecal and serum metabolites, respectively. Overall, a highly coordinated microbiota-metabolite regulatory network may underlie the pregnancy process. These findings provide a foundation for enhancing our understanding of the molecular processes occurring during the progression of pregnancy, thereby contributing to nutrition and health management during this period.

East Asian patients who received immunotherapy-based therapy associated with improved survival benefit in advanced non-small cell lung cancer: An updated meta-analysis

BACKGROUND

Immune checkpoint inhibitors (ICIs) combined with chemotherapy have been recommended as the standard treatment for advanced NSCLC patients without driver-gene mutations. However, there are different genetic characteristics and biological traits of tumors between non-East Asian (nEA) and East Asian (EA) patients with NSCLC, which may contribute to differences in the efficacy of ICIs in different ethnic populations. Previous findings regarding differences in the efficacy of ICIs among ethnic groups have been inconsistent. Therefore, we performed a meta-analysis by collecting published data to investigate the clinical outcomes of ICIs for EA NSCLC patients compared to nEA patients.

METHODS

Overall survival (OS) and progression-free survival (PFS) were used to access the difference in survival outcomes between the two populations. Subgroup analyses were performed based on the line of ICIs, the use of ICIs alone or in combination, and the type of ICIs.

RESULTS

A total of 9826 NSCLC patients from 21 randomized controlled trials (RCTs) with 4064 EAs were included, which involved PD-1, PD-L1, and CTLA-4 inhibitors. EA NSCLC patients who received ICIs-based therapy were associated with significantly improved survival benefits in OS (p = 0.02) compared with nEA patients. Subgroup analysis indicated that EA patients receiving first-line ICIs showed significantly superior OS compared with nEA patients (p = 0.007). Chemo-ICIs treatment showed significant advantages in terms of OS (p = 0.002) and PFS (p = 0.02) among EA patients compared to nEA patients. In addition, PD-1 inhibitors were associated with improved OS among both EA patients and nEA patients compared with PD-L1 inhibitors.

CONCLUSION

EA NSCLC patients who received ICIs-based therapy were associated with significantly improved survival benefits compared with nEA NSCLC patients. Earlier intervention with ICIs and combination treatment was more recommended for EA NSCLC patients. Moreover, PD-1 inhibitors are associated with prolonged survival among both EA and nEA patients.

Genetic insights into associations of multisite chronic pain with common diseases and biomarkers using data from the UK Biobank

BACKGROUND

Chronic pain is a common, complex, and challenging condition, for which specialised healthcare is required. We investigated the relationship between multisite chronic pain (MCP) and different disease traits identify safe biomarker interventions that can prevent MCP.

METHODS

Univariable and multivariable Mendelian randomisation (MR) analysis were conducted to investigate associations between MCP and 36 common diseases in the UK Biobank. Subsequently, we estimated the potential effect of expression of 4774 proteins on MCP utilising existing plasma protein quantitative trait locus data. For the significant biomarkers, we performed phenome-wide MR (Phe-MR) with 1658 outcomes to predict potential safety profiles linked to biomarker intervention.

RESULTS

Multisite chronic pain had a substantial impact on psychiatric and neurodevelopmental traits (major depression and attention deficit hyperactivity disorder), cardiovascular diseases (myocardial infarction, coronary artery disease, and heart failure), respiratory outcomes (asthma, chronic obstructive pulmonary disease, and sleep apnoea), arthropathies, type 2 diabetes mellitus, and cholelithiasis. Higher genetically predicted levels of S100A6, DOCK9, ferritin, and ferritin light chain were associated with a risk of MCP, whereas PTN9 and NEUG were linked to decreased MCP risk. Phe-MR results suggested that genetic inhibition of DOCK9 increased the risk of 21 types of disease, whereas the other biomarker interventions were relatively safe.

CONCLUSIONS

We established that MCP has an effect on health conditions covering various physiological systems and identified six novel biomarkers for intervention. In particular, S100A6, PTN9, NEUG, and ferritin light chain represent promising targets for MCP prevention, as no significant side-effects were predicted in our study.

Hydrolysis of Solid Buffer Enables High-Performance Aqueous Zinc Ion Battery

Aqueous zinc (Zn) ion batteries (AZIBs) have not yet fulfilled their talent of high safety and low cost since the anode/electrolyte interface (AEI) has long been impeded by hydrogen evolution, surface corrosion, dendritic growth, and by-product accumulation. Here, the hydrolysis of solid buffers is elaborately proposed to comprehensively and enduringly handle these issues. Take 2D layered black phosphorus (BP) as a hydrolytic subject. It is reported that the phosphoric acid generated by hydrolysis in an aqueous electrolyte produces a zinc phosphate (ZPO) rich solid electrolyte interphase (SEI) layer, which largely inhibits the dendrite growth, surface corrosion, and hydrogen evolution. Meanwhile, the hydrolytic phosphoric acid stabilizes the pH value near AEI, avoiding the accumulation of alkaline by-products. Notably, compared with the disposable ZPO engineerings of anodic SEI pre-construction and electrolyte additive, the hydrolysis strategy of BP can realize a dramatically prolonged protective effect. As a result, these multiple merits endow BP modified separator to achieve improved stripping/plating stability toward Zn anode with more than ten times lifespan enhancement in Zn||Zn symmetrical cell. More encouragingly, when coupled with a V2 O5 ·nH2 O cathode with ultra-high loadings (34.1 and 28.7 mg cm-2 ), the cumulative capacities are remarkably promoted for both coin and pouch cells.

Subgroups of sleep quality and associated risk factors in patients with cancer undergoing radiotherapy: A cross-sectional study based on latent profile analysis

PURPOSE

To identify latent classes of sleep quality among patients with cancer undergoing radiotherapy, and to examine the predictors of different latent classes.

METHODS

This cross-sectional study included 238 cancer patients. The assessment instrument included the Pittsburgh Sleep Quality Index, the sleep hygiene awareness and practice scale, the MD Anderson Symptom Inventory, the Distress Thermometer and the Fear of Cancer Recurrence Questionnaire. Latent profile analysis was used to identify different sleep quality subgroups.

RESULTS

Three latent classes with distinct sleep characteristics were identified: good sleep quality (class 1, 66.8%), moderate sleep disturbance with high hypnotics use (class 2, 9.2%), and high sleep disturbance with low hypnotics use (class 3, 24.0%) classes. Patients who were young (P = 0.022) and diagnosed with cancer stage Ⅲ (P = 0.021) were significantly more likely to be in Class 3 than in Class 1. Patients with a senior middle school were less likely to fall into Class 2, but more likely to fall into Class 1 (P = 0.026). Those with higher sleep hygiene practice scores (P = 0.022; P < 0.001), symptom severity (P < 0.001; P < 0.001), and psychological distress (P = 0.040; P < 0.001) had a significantly higher probability of being classified in Class 2 or Class 3 than in Class 1.

CONCLUSIONS

Our study revealed the heterogeneity of sleep quality in patients with cancer undergoing radiotherapy; moreover, through our findings, targeted interventions may be developed to promote the sleep quality of these patients.