Research progress on the mechanism of common inflammatory pathways in the pathogenesis and development of lymphoma

In recent years, the incidence and mortality rates of lymphoma have gradually increased worldwide. Tumorigenesis and drug resistance are closely related to intracellular inflammatory pathways in lymphoma. Therefore, understanding the biological role of inflammatory pathways and their abnormal activation in relation to the development of lymphoma and their selective modulation may open new avenues for targeted therapy of lymphoma. The biological functions of inflammatory pathways are extensive, and they are central hubs for regulating inflammatory responses, immune responses, and the tumour immune microenvironment. However, limited studies have investigated the role of inflammatory pathways in lymphoma development. This review summarizes the relationship between abnormal activation of common inflammatory pathways and lymphoma development to identify precise and efficient targeted therapeutic options for patients with advanced, drug-resistant lymphoma.

A novel method for quantifying the short-range order in non-crystalline starch by Raman spectroscopy

A quantitative method was developed to characterize the short-range order in non-crystalline starch by Raman spectroscopy. The Raman spectra of three forms of non-crystalline starches (just-gelatinized starch, which was heated to the point of having just lost its long-range order but still retaining essentially all of its short-range order, gelatinized starch and amorphous starch) were resolved into subspectra to calculate the short-range ordered phases. By deducting the spectra of amorphous starch using a subtraction technique, the areas of subspectra for short-range ordered phases in just-gelatinized and gelatinized starches were obtained. The ratio of the area for short-range ordered phases in gelatinized starch relative to that in just-gelatinized starch was negatively correlated with water content for gelatinization. Based on this, we propose that this ratio of areas provides a quantitative measure for assessing the short-range order in non-crystalline starch. This study provides an alternative and simpler method to an X-ray diffraction protocol proposed previously.

Integrated network pharmacological analysis revealed that Smilax glabra Roxb. alleviates IMQ-induced psoriatic skin inflammation through regulating T cell immune response

ETHNOPHARMACOLOGICAL RELEVANCE

Psoriasis is an autoimmune disease characterized by dysfunctional T cells and dysregulated immune responses. Smilax glabra Roxb. (SGR) is a formulation used in Traditional Chinese Medicine for the treatment of inflammatory skin disorders, including psoriasis. This study explores the scientific basis for its use by examining the effects of SGR on T cell differentiation and insulin receptor signaling, relevant pathways implicated in the pathophysiology of psoriasis.

AIM OF THE STUDY

This study investigates the therapeutic potential of SGR (a Chinese medicine) in psoriasis and its impact on T cell differentiation.

MATERIALS AND METHODS

An integrated network pharmacology and bioinformatics approach was employed to elucidate the mechanisms of SGR in regulating T cell differentiation. A psoriasis mouse model was utilized to evaluate the effects of SGR on T cell subsets. Immunohistochemistry and gene expression analyses were conducted to investigate the modulation of insulin receptor signaling pathways by SGR.

RESULTS

SGR treatment effectively reset the expression of various T cell subsets in the psoriasis mouse model, suggesting its ability to regulate T cell differentiation and immune function. Furthermore, SGR treatment inhibited insulin receptor signaling and downstream pathways, including PI3K/AKT and ERK, in psoriatic skin lesions. This indicates that SGR may exert its therapeutic effects through modulation of the insulin receptor signaling pathway.

CONCLUSIONS

This study provides novel insights into the therapeutic potential of SGR in psoriasis. By modulating T cell differentiation and targeting the insulin receptor signaling pathway, SGR holds promise as a potential treatment option for psoriasis.

One-step and label-free ratiometric fluorescence assay for the detection of plasma exosome towards cancer diagnosis

Exosomes are closely associated with tumor development and are regarded as viable biomarkers for cancer. Here, a ratiometric fluorescence method was proposed for the one-step and label-free detection of plasma exosomes. A bicolor streptavidin magnetic beads were specifically created with an immobilized Cy5-labeled hairpin aptamer for CD63 (Cy5-Apt) on its surface to identify exosome, and a green color SYBR Green I (SGI) embedded in the stem of Cy5-Apt to respond to exosomes. After exosome capture, the Cy5-Apt could undergo a conformational shift and release the encapsulated SGI, allowing exosome measurement based on the fluorescence ratio of Cy5 and SGI. The enrichment, separation and detection of exosomes in proposed method could be completed in one step (30 min), which is a significant improvement over previous method. Furthermore, the use of ratiometric fluorescence and magnetic separation allows for exosome enrichment and interference elimination from complex matrices, improving accuracy and sensitivity. Particularly, the assay could detect exosomes in plasma and has potential to distinguish lung cancer patients from healthy volunteers with an area under the receiver operator characteristic curve of 0.85. Besides, the study provided an efficient method for analyzing the various divisions of exosomes by merely modifying the aptamer, which holds great promise for point-of-care applications.

Reducing the risk of tooth injury in anterior maxillary interdental osteotomy for cleft lip and palate patients using a surgical navigation technique

The aim of this study was to investigate the clinical feasibility of preventing tooth injury from anterior maxillary interdental osteotomy by using a surgical navigation technique. A retrospective review was conducted on cleft lip and palate patients treated with anterior maxillary osteotomy followed by distraction osteogenesis between August 2019 and May 2022. Patients operated on through image guidance were enrolled in the navigation group, while those who were operated on freehand were enrolled in the freehand group. Tooth injuries were identified on postoperative images. Linear and angular deviations of the osteotomy line were measured. Twelve patients were enrolled in the study, seven in the navigation group and five in the freehand group. Altogether, 24 osteotomy lines and 53 adjacent teeth were evaluated. The dental injury rate was 3% in the navigation group and 27% in the freehand group (P = 0.016). The average linear deviations (mean ± standard deviation) were 0.67 ± 0.30 mm and 2.05 ± 1.33 mm, respectively (P < 0.001), while the average angular deviations were 1.67 ± 0.68° and 11.41 ± 7.46°, respectively (P < 0.001). The results suggest that navigation was able to reduce the tooth injury risk compared with freehand interdental osteotomies in crowded dental arches.

Cardiac MRI feature-tracking-derived torsion mechanics in systolic and diastolic dysfunction in systemic light-chain cardiac amyloidosis

AIM

To describe the myocardial torsion mechanics in cardiac amyloidosis (CA), and evaluate the correlations between left ventricle (LV) torsion mechanics and conventional parameters using cardiac magnetic resonance imaging feature tracking (CMR-FT).

MATERIALS AND METHODS

One hundred and thirty-nine patients with light-chain CA (AL-CA) were divided into three groups: group 1 with preserved systolic function (LV ejection fraction [LVEF] ≥50%, n=55), group 2 with mildly reduced systolic function (40% ≤ LVEF <50%, n=51), and group 3 with reduced systolic function (LVEF <40%, n=33), and compared with age- and gender-matched healthy controls (n=26). All patients underwent cine imaging and late gadolinium-enhancement (LGE). Cine images were analysed offline using CMR-FT to estimate torsion parameters.

RESULTS

Global torsion, base-mid torsion, and peak diastolic torsion rate (diasTR) were significantly impaired in patients with preserved systolic function (p<0.05 for all), whereas mid-apex torsion and peak systolic torsion rate (sysTR) were preserved (p>0.05 for both) compared with healthy controls. In patients with mildly reduced systolic function, global torsion and base-mid torsion were lower compared to those with preserved systolic function (p<0.05 for both), while mid-apex torsion, sysTR, and diasTR were preserved (p>0.05 for all). In patients with reduced systolic function, only sysTR was significantly worse compared with mildly reduced systolic function (p<0.05). At multivariable analysis, right ventricle (RV) end-systolic volume RVESV index and NYHA class were independently related to global torsion, whereas LVEF was independently related to sysTR. RV ejection fraction (RVEF) was independently related to diasTR. LV global torsion performed well (AUC 0.71; 95% confidence interval [CI]: 0.61, 0.77) in discriminating transmural from non-transmural LGE in AL-CA patients.

CONCLUSION

LV torsion mechanics derived by CMR-FT could help to monitor LV systolic and diastolic function in AL-CA patients and function as a new imaging marker for LV dysfunction and LGE transmurality.

CD58 alterations govern antitumor immune responses by inducing PD-L1 and IDO in diffuse large B-cell lymphoma

Recurrent abnormalities in immune surveillance-related genes affect the progression of diffuse large B-cell lymphoma (DLBCL) and modulate the response to therapeutic interventions. CD58 interacts with the CD2 receptor on T cells and natural killer (NK) cells and is recurrently mutated and deleted in DLBCL, suggesting it may play a role in regulating antitumor immunity. Herein, we comprehensively analyzed the genomic characteristics of CD58 through targeted next-generation sequencing, RNA-sequencing, whole-exome sequencing, and single-cell RNA-sequencing in patients with newly diagnosed DLBCL. The CD58 mutation rate was 9.1%, and the copy number loss rate was 44.7% among all enrolled DLBCL patients. Notably, CD58 genetic alterations, along with low CD58 expression, significantly correlated with reduced rates of response to R-CHOP therapy and inferior progression-free and overall survival. Single-cell RNA sequencing revealed that CD58 expression in tumor cells was negatively correlated with CD8+ T cell exhaustion/dysfunction status. Insufficient T-cell activation resulting from CD58 alterations could not be attributed solely to CD2 signaling. CD58 inhibited the activity of the JAK2/STAT1 pathway by activating the Lyn/CD22/SHP1 axis, thereby limiting PD-L1 and IDO expression. Elevated PD-L1 and IDO expression in CD58 deficient DLBCL cells led to immune evasion and tumor-intrinsic resistance to CAR T-cell therapy. Direct activation of CD58-CD2 costimulatory signaling in combination with anti-PD-L1 blockade or IDO inhibitor sensitized CD58-deficient DLBCL to CAR T-cell therapy. Collectively, this work identified the multiple roles of CD58 in regulating antitumor immune responses in DLBCL.

Dimensions of family stress and repetitive nonsuicidal self-injury in adolescence: Examining the interactive effects of impulsivity and emotion dysregulation

BACKGROUND

Repetitive non-suicidal self-injury (R-NSSI) in adolescence represents a significant risk factor for suicide. Although exposure to family stress is robustly associated with the risk of non-suicidal self-injury (NSSI), studies have not examined the potential mechanisms linking different forms of family stress and R-NSSI.

OBJECTIVE

This study examined how unique dimensions of family stress (threat and deprivation) relate to R-NSSI via interactions between impulsivity and emotion dysregulation.

PARTICIPANTS AND SETTING

The current sample included 3801 middle-school adolescents (42.2 % girls, Mage = 13.21 years).

METHODS

We conducted a two-wave study with 6-month intervals. Participants completed self-report measures assessing family stress, impulsivity, emotion dysregulation, and NSSI.

RESULTS

Moderate mediation analyses showed that threat was indirectly associated with NSSI frequency through the interaction of impulsivity and emotion dysregulation in the R-NSSI group and indirectly through impulsivity in the occasional NSSI (O-NSSI) group. Deprivation did not predict subsequent NSSI frequency in either group.

CONCLUSIONS

These findings lend empirical support to dimensional models of adversity and suggest that adolescents who experience threat-related family stress may have greater impulsivity and are more likely to report R-NSSI in the context of emotion dysregulation.

Optimizing cell voltage dependence on size of carbon nanotube-based electrodes in Na-ion and K-ion batteries

Sodium-ion batteries (NIBs) and potassium-ion batteries (KIBs) are gaining extensive attention as promising alternatives to lithium-ion batteries owing to their superior energy density and cost-effectiveness. However, the larger ionic radius of Na+ and K+ ions in comparison to Li+ ions poses a challenge in designing anode materials characterized by enduring structures and elevated voltage to facilitate the efficacy of high-performance NIBs and KIBs. Carbon nanomaterials, particularly carbon nanotubes (CNTs), have emerged as a potential candidate in anode materials. Herein, we used density functional theory calculations to study the cell voltage of CNTs in relation to Na-ion and K-ion storage as a function of CNT size. The adsorption energy profiles of both Na+@CNT and K+@CNT systems exhibit a descending trend concomitant with the increase in the CNT diameter, where Na+/K+ ion primarily prefers to adsorb in the interior wall of CNT. Conversely, the cell voltage for the Na and K system gradually increases with the increasing diameter of CNT, which can be attributed to the stronger electrostatic interaction validated by energy decomposition calculation. The voltage of Na-ion adsorbed on the inter wall of (10,10) CNT attains 1.29 V, close to the previously theoretical voltage of Li-ion on the same CNT (1.35 V), while the much lower voltage pertaining to K-ion adsorption on the inter wall of (10,10) CNT just stands at 0.59 V, suggesting the viability of CNT-based electrode for NIBs but not for KIBs. These findings lay a solid foundation for delineating the interrelationship between the voltage properties of CNT as prospective anode material and their structural characteristics, thereby expanding the application of CNT-based optoelectronic devices.

Reduced myelin content in bipolar disorder: A study of inhomogeneous magnetization transfer

BACKGROUND

Previous neuroimaging and pathological studies have found myelin-related abnormalities in bipolar disorder (BD), which prompted the use of magnetic resonance (MR) imaging technology sensitive to neuropathological changes to explore its neuropathological basis. We holistically investigated alterations in myelin within BD patients by inhomogeneous magnetization transfer (ihMT), which is sensitive and specific to myelin content.

METHODS

Thirty-one BD and 42 healthy controls (HC) were involved. Four MR metrics, i.e., ihMT ratio (ihMTR), pseudo-quantitative ihMT (qihMT), magnetization transfer ratio and pseudo-quantitative magnetization transfer (qMT), were compared between groups using analysis methods based on whole-brain voxel-level and white matter regions of interest (ROI), respectively.

RESULTS

The voxel-wise analysis showed significantly inter-group differences of ihMTR and qihMT in the corpus callosum. The ROI-wise analysis showed that ihMTR, qihMT, and qMT values in BD group were significantly lower than that in HC group in the genu and body of corpus callosum, left anterior limb of the internal capsule, left anterior corona radiate, and bilateral cingulum (p < 0.001). And the qihMT in genu of corpus callosum and right cingulum were negatively correlated with depressive symptoms in BD group.

LIMITATIONS

This study is based on cross-sectional data and the sample size is limited.

CONCLUSION

These findings suggest the reduced myelin content of anterior midline structure in the bipolar patients, which might be a critical pathophysiological feature of BD.

Triplet Rydberg States of Aluminum Monofluoride

Aluminum monofluoride (AlF) is a suitable molecule for laser cooling and trapping. Such experiments require extensive spectroscopic characterization of the electronic structure. Two of the theoretically predicted higher-lying triplet states of AlF, the counterparts of the well-characterized D1Δ and E1Π states, had not been experimentally identified yet. We here report on the characterization of the d3Π (v = 0-6) and e3Δ (v = 0-2) states, confirming the predicted energetic ordering of these states (J. Chem. Phys. 1988, 88, 5715-5725), as well as of the f3Σ+ (v = 0-2) state. The transition intensity of the d3Π, v = 3 - a3Π, v = 3 band is negligibly small. This band gets its weak, unexpected rotational structure via intensity borrowing from the nearby e3Δ, v = 2 - a3Π, v = 3 band, made possible via spin-orbit and spin-rotation interaction between the d3Π and e3Δ states. This interaction affects the equilibrium rotational constants in both states; their deperturbed values yield equilibrium internuclear distances that are consistent with the observations. We determined the ionization potential of AlF to be 78,492(1) cm-1 by ionization from the d3Π state.

Kuntai capsule for the treatment of diminished ovarian reserve: A systematic review and meta-analysis of randomized controlled trials

ETHNOPHARMACOLOGICAL RELEVANCE

Diminished ovarian reserve (DOR) results in reduced fertility. Kuntai capsule, a Chinese patent medicine, which can nourish the heart and kidneys, has shown promising efficacy in its treatment. However, there is no enough clinical evidence to confirm the efficacy and safety of Kuntai capsule.

AIM OF THE STUDY

This review aims to evaluate Kuntai capsule's potential benefits and detriments for diminished ovarian reserve.

MATERIALS AND METHODS

Databases namely China National Knowledge Infrastructure, WANFANG Database, Chinese Science and Technology Journal Database, Chinese Biomedical Literature Database, PubMed, Cochrane Library, and Embase were searched from their inception to July 2023. We included randomized controlled trials (RCTs) comparing Kuntai capsule to hormone therapy (HT) and Kuntai capsule in combination with HT to HT alone for DOR treatment. The risk of bias was evaluated using RoB 1.0. A Meta-analysis was performed using RevMan 5.4 software. The primary outcomes were antral follicle count (AFC) and serum anti-Müllerian hormone (AMH), secondary outcomes were follicle-stimulating hormone (FSH) and adverse reactions.

RESULTS

A Meta-analysis of 12 randomized controlled trials (RCTs), encompassing a total of 905 DOR patients was conducted. The results indicated that the combination of Kuntai capsule with HT exhibited superior efficacy in enhancing AFC (MD = 1.34, 95% CI [0.96,1.72]) and AMH levels (MD = 1.09 (ng/mL) 95% CI[0.80,1.38]), Kuntai capsule demonstrated improvements in AFC (MD = 0.65, 95% CI [0.48,0.83]) in DOR patients compared to HT alone.

CONCLUSIONS

Based on the available results, the combination of Kuntai capsule with HT appears to improve the AFC, AMH and FSH levels of DOR patients. Kuntai capsule alone appears to improve the AFC and FSH levels of DOR patients. However, included trials had methodological quality issues, further standardized research is required.

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.

Blocking senescence and tolerogenic function of dendritic cells induced by γδ Treg cells enhances tumor-specific immunity for cancer immunotherapy

BACKGROUND

Regulatory T (Treg) cells are a key component in maintaining the suppressive tumor microenvironment and immune suppression in different types of cancers. A precise understanding of the molecular mechanisms used by Treg cells for immune suppression is critical for the development of effective strategies for cancer immunotherapy.

METHODS

Senescence development and tolerogenic functions of dendritic cells (DCs) induced by breast cancer tumor-derived γδ Treg cells were fully characterized using real-time PCR, flow cytometry, western blot, and functional assays. Loss-of-function strategies with pharmacological inhibitor and/or neutralizing antibody were used to identify the potential molecule(s) and pathway(s) involved in DC senescence and dysfunction induced by Treg cells. Impaired tumor antigen HER2-specific recognition and immune response of senescent DCs induced by γδ Treg cells were explored in vitro and in vivo in humanized mouse models. In addition, the DC-based HER2 tumor vaccine immunotherapy in breast cancer models was performed to explore the enhanced antitumor immunity via prevention of DC senescence through blockages of STAT3 and programmed death-ligand 1 (PD-L1) signaling.

RESULTS

We showed that tumor-derived γδ Treg cells promote the development of senescence in DCs with tolerogenic functions in breast cancer. Senescent DCs induced by γδ Treg cells suppress Th1 and Th17 cell differentiation but promote the development of Treg cells. In addition, we demonstrated that PD-L1 and STAT3 signaling pathways are critical and involved in senescence induction in DCs mediated by tumor-derived γδ Treg cells. Importantly, our complementary in vivo studies further demonstrated that blockages of PD-L1 and/or STAT3 signaling can prevent γδ Treg-induced senescence and reverse tolerogenic functions in DCs, resulting in enhanced HER2 tumor-specific immune responses and immunotherapy efficacy in human breast cancer models.

CONCLUSIONS

These studies not only dissect the suppressive mechanism mediated by tumor-derived γδ Treg cells on DCs in the tumor microenvironment but also provide novel strategies to prevent senescence and dysfunction in DCs and enhance antitumor efficacy mediated by tumor-specific T cells for cancer immunotherapy.

Liver kinase B-1 modulates the activity of dopamine neurons in the ventral tegmental area and regulates social memory formation

Social memory is the ability to discriminate between familiar and unknown conspecifics. It is an important component of social cognition and is therefore essential for the establishment of social relationships. Although the neural circuit mechanisms underlying social memory encoding have been well investigated, little focus has been placed on the regulatory mechanisms of social memory processing. The dopaminergic system, originating from the midbrain ventral tegmental area (VTA), is a key modulator of cognitive function. This study aimed to illustrate its role in modulating social memory and explore the possible molecular mechanisms. Here, we show that the activation of VTA dopamine (DA) neurons is required for the formation, but not the retrieval, of social memory. Inhibition of VTA DA neurons before social interaction, but not 24 h after social interaction, significantly impaired social discrimination the following day. In addition, we showed that the activation of VTA DA neurons was regulated by the serine/threonine protein kinase liver kinase B1 (Lkb1). Deletion of Lkb1 in VTA DA neurons reduced the frequency of burst firing of dopaminergic neurons. Furthermore, Lkb1 plays an important role in regulating social behaviors. Both genetic and virus-mediated deletions of Lkb1 in the VTA of adult mice impaired social memory and subsequently attenuated social familiarization. Altogether, our results provide direct evidence linking social memory formation to the activation of VTA DA neurons in mice and illustrate the crucial role of Lkb1 in regulating VTA DA neuron function.

Rosai-Dorfman disease manifesting as a solitary mass with fat in the thymus a case report

BACKGROUND

Sinus histiocytosis with massive lymphadenopathy, also known as Rosai-Dorfman disease, is a rare, self-limiting disease that predominantly affects children and young adults. Moreover, the disease is characterized by painless bilateral cervical lymphadenopathy in 95% of the patients. However, few reports are available on the Rosai-Dorfman disease of the thymus.

CASE PRESENTATION

We report a rare case of thymic Rosai-Dorfman disease detected using computed tomography. During a medical examination, a 50-year-old man underwent a chest computed tomography scan, which revealed an anterior mediastinal single mass with fat in the thymus. A thymectomy was performed to completely remove the tumor using a thoracoscopic technique due to a clinical suspicion of thymoma. Furthermore, Rosai-Dorfman disease was confirmed using histological and immunohistochemical analyses.

CONCLUSIONS

To the best of our knowledge, this is the sixth case of thymus-affecting solitary Rosai-Dorfman disease with histological and immunohistochemical evidence. Fat in the thymus, as was present in this case, has never been described in Rosai-Dorfman disease previously. Our results highlight the challenge of diagnosing this uncommon tumor before surgery, and more cases need to be reported to help with the preoperative diagnosis of such a rare tumor.

Inhibition of p70 Ribosomal S6 Kinase (S6K1) Reduces Cortical Blood Flow in a Rat Model of Autism-Tuberous Sclerosis

The manifestations of tuberous sclerosis complex (TSC) in humans include epilepsy, autism spectrum disorders (ASD) and intellectual disability. Previous studies suggested the linkage of TSC to altered cerebral blood flow and metabolic dysfunction. We previously reported a significant elevation in cerebral blood flow in an animal model of TSC and autism of young Eker rats. Inhibition of the mammalian target of rapamycin (mTOR) by rapamycin could restore normal oxygen consumption and cerebral blood flow. In this study, we investigated whether inhibiting a component of the mTOR signaling pathway, p70 ribosomal S6 kinase (S6K1), would yield comparable effects. Control Long Evans and Eker rats were divided into vehicle and PF-4708671 (S6K1 inhibitor, 75 mg/kg for 1 h) treated groups. Cerebral regional blood flow (14C-iodoantipyrine) was determined in isoflurane anesthetized rats. We found significantly increased basal cortical (+ 32%) and hippocampal (+ 15%) blood flow in the Eker rats. PF-4708671 significantly lowered regional blood flow in the cortex and hippocampus of the Eker rats. PF-4708671 did not significantly lower blood flow in these regions in the control Long Evans rats. Phosphorylation of S6-Ser240/244 and Akt-Ser473 was moderately decreased in Eker rats but only the latter reached statistical significance upon PF-4708671 treatment. Our findings suggest that moderate inhibition of S6K1 with PF-4708671 helps to restore normal cortical blood flow in Eker rats and that this information might have therapeutic potential in tuberous sclerosis complex and autism.

Determinants of depressive symptoms at individual, school and province levels: a national survey of 398,520 Chinese children and adolescents

OBJECTIVES

The aims of this study were to describe the national distribution of depressive symptoms in Chinese children and adolescents, to examine the determinants of depressive symptoms at individual, school and province levels and to assess the gender and age differences in the effect of school factors on depressive symptoms.

STUDY DESIGN

This was a national cross-sectional study.

METHODS

A school-based online survey was conducted in mainland China from between December 1, 2021, and January 1, 2022. A total of 398,520 eligible participants were included in the analysis. School-level data were drawn from students, headteachers and Baidu Maps, and province-level data were obtained from the national human development report. The Patient Health Questionnaire-2 was used to measure depressive symptoms.

RESULTS

Areas with the highest mean scores for depressive symptoms were in the northeastern, inner central and southwestern regions of China. At the individual level, younger age, male sex, being an only child, Han ethnicity, lower body mass index, more days of exercise, less drinking and smoking behaviours, higher subjective family socio-economic status (SES) and popularity in school were related to fewer depressive symptoms; however, objective family SES and maternal education were not related to fewer depressive symptoms. The school-level variables of public status, psychological activities and psychological courses and province-level variable of higher Human Development Index were associated with fewer depressive symptoms. The effect of psychological courses and activities on depressive symptoms was greater in females.

CONCLUSIONS

The results showed multilevel factors related to depressive symptoms and emphasised the importance of implementing school-based psychological activities to ameliorate depressive symptoms in Chinese children and adolescents across age and gender.

Construction and validation of a novel tumor necrosis factor-related apoptosis-inducing ligand mutant MuR5S4-TR

AIM

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) can selectively kill tumor cells but has no significant effect on normal cells. However, the use of TRAIL is limited for resistance by more than 50% of the tumor cell lines. It's very important to develop a more efficient form of TRAIL for cancer treatment.

METHODS

The N-terminal in soluble fragments (114-281aa) of TRAIL was redesigned to construct a novel TRAIL mutant-MuR5S4-TR. The Cell Counting Kit-8 method to explore the antitumor effects. The potential mechanisms were also explored.

RESULTS

Novel TRAIL mutant with cell-penetrating peptides (CPP) like and Second mitochondria-derived activator of caspases (Smac) like structure-MuR5S4-TR was successfully constructed. The prokaryotic expression system was successfully built, and the MuR5S4-TR was purified and reconfirmed by western blot. MuR5S4-TR could enhance the antitumor effects of TRAIL in most of the cancer cell lines significantly, NCI-H460 lung cancer cell line, for instance. After MuR5S4-TR treatment, the expressions of death receptor 4 (DR4), DR5, Caspase-8, and cleaved Caspase-3 were remarkably increased, however, there was no significant difference in X-linked inhibitor of apoptosis expression.

CONCLUSION

We constructed a novel TRAIL mutant with CPP-like and Smac-like structure-MuR5S4-TR. The MuR5S4-TR showed significantly stronger antitumor effects than TRAIL in many tumor cell lines. The MuR5S4-TR showed strong antitumor effects both in vitro and in vivo. This preliminary study implies that MuR5S4-TR may be a more efficient form of TRAIL for cancer therapy.

Predictive value of crossover sign for outcome of ultrasound-guided vacuum aspiration in women with Cesarean scar pregnancy

OBJECTIVE

To examine the value of the crossover sign (COS) in predicting treatment outcome in women with a Cesarean scar pregnancy (CSP) who were treated with ultrasound-guided vacuum aspiration.

METHODS

This was a retrospective cohort study of women with CSP who underwent ultrasound-guided vacuum aspiration. Based on the relationship between the gestational sac, Cesarean scar and anterior wall of the uterus, CSPs were classified by COS type. Analysis was conducted to investigate the association between COS type (COS-1, COS-2) and treatment outcome. The incidence of treatment failure, retained pregnancy tissue, secondary therapy and bleeding ≥ 200 mL were analyzed.

RESULTS

In total, 181 eligible patients with CSP, including 90 (49.7%) women with COS-1 and 91 (50.3%) women with COS-2, were analyzed. COS-1 patients had a higher incidence of treatment failure compared with COS-2 patients (25.6% vs 8.8%; P = 0.003), as well as higher rates of retained pregnancy tissue (18.9% vs 6.6%; P = 0.013), secondary therapy (20.0% vs 6.6%; P = 0.002) and bleeding of ≥ 200 mL (13.3% vs 4.4%; P = 0.034). COS-1 and a large gestational sac (30.1-50.0 mm or >50.0 mm in diameter) were associated independently with increased risk of treatment failure (odds ratio, 4.57 (95% CI, 1.66-12.56); P = 0.003, 4.34 (95% CI, 1.35-13.94); P = 0.014 and 10.50 (95% CI, 2.54-43.46); P = 0.001, respectively).

CONCLUSIONS

Ultrasound evaluation of the relationship between the gestational sac and the endometrial line (COS classification) in women with CSP may help to predict treatment outcome among those undergoing vacuum aspiration. Among COS-1 patients, especially those with a gestational sac diameter of >30.0 mm, vacuum aspiration may be discouraged. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Construct validation of machine learning for accurately predicting the risk of postoperative surgical site infection following spine surgery

BACKGROUND

This study aimed to evaluate the risk factors for machine learning (ML) algorithms in predicting postoperative surgical site infection (SSI) following spine surgery.

METHODS

This prospective cohort study included 986 patients who underwent spine surgery at Taizhou People's Hospital Affiliated to Nanjing Medical University from January 2015 to October 2022. Supervised ML algorithms included support vector machine, logistic regression, random forest, XGboost, decision tree, k-nearest neighbour, and naïve Bayes (NB), which were tested and trained to develop a predicting model. The ML model performance was evaluated from the test dataset. We gradually analysed their accuracy, sensitivity, and specificity, as well as the positive predictive value, negative predictive value, and area under the curve.

RESULTS

The rate of SSI was 9.33%. Using a backward stepwise approach, we identified that the remarkable risk factors predicting SSI in the multi-variate Cox regression analysis were age, body mass index, smoking, cerebrospinal fluid leakage, drain duration and pre-operative albumin level. Compared with other ML algorithms, the NB model had the highest performance in seven ML models, with an average area under the curve of 0.95, sensitivity of 0.78, specificity of 0.88, and accuracy of 0.87.

CONCLUSIONS

The NB model in the ML algorithm had excellent calibration and accurately predicted the risk of SSI compared with the existing models, and might serve as an important tool for the early detection and treatment of SSI following spinal infection.

Cellulose nanofibers embedded chitosan/tannin hydrogel with high antibacterial activity and hemostatic ability for drug-resistant bacterial infected wound healing

Millions of patients annually suffer life-threatening illnesses caused by bacterial infections of skin wounds. However, the treatment of wounds infected with bacteria is a thorny issue in clinical medicine, especially with drug-resistant bacteria infections. Therefore, there is an increasing interest in developing wound dressings that can efficiently fight against drug-resistant bacterial infections and promote wound healing. In this work, an anti-drug-resistant bacterial chitosan/cellulose nanofiber/tannic acid (CS/CNF/TA) hydrogel with excellent wound management ability was developed by electrospinning and fiber breakage-recombination. The hydrogel exhibited an outstanding antibacterial property exceeding 99.9 %, even for drug-resistant bacteria. This hydrogel could adhere to the tissue surface due to its abundant catechol groups, which avoided the shedding of hydrogel during the movement. Besides, it exhibited extraordinary hemostatic ability during the bleeding phase of the wound and then regulated the wound microenvironment by absorbing water and moisturizing. Moreover, the CS/CNF/TA also promoted the regrowth of vessels and follicles, accelerating the healing of infected wound tissue, with a healing rate exceeding 95 % within a 14-day timeframe. Therefore, the CS/CNF/TA hydrogel opens a new approach for the healing of drug-resistant bacterial infected wounds.

Effect of Regional Brain Activity Following Repeat Transcranial Magnetic Stimulation in SCA3: A Secondary Analysis of a Randomized Clinical Trial

Repetitive transcranial magnetic stimulation (rTMS), a noninvasive neuroregulatory technique used to treat neurodegenerative diseases, holds promise for spinocerebellar ataxia type 3 (SCA3) treatment, although its efficacy and mechanisms remain unclear. This study aims to observe the short-term impact of cerebellar rTMS on motor function in SCA3 patients and utilize resting-state functional magnetic resonance imaging (RS-fMRI) to assess potential therapeutic mechanisms. Twenty-two SCA3 patients were randomly assigned to receive actual rTMS (AC group, n = 11, three men and eight women; age 32-55 years) or sham rTMS (SH group, n = 11, three men and eight women; age 26-58 years). Both groups underwent cerebellar rTMS or sham rTMS daily for 15 days. The primary outcome measured was the ICARS scores and parameters for regional brain activity. Compared to baseline, ICARS scores decreased more significantly in the AC group than in the SH group after the 15-day intervention. Imaging indicators revealed increased Amplitude of Low Frequency Fluctuation (ALFF) values in the posterior cerebellar lobe and cerebellar tonsil following AC stimulation. This study suggests that rTMS enhances motor functions in SCA3 patients by modulating the excitability of specific brain regions and associated pathways, reinforcing the potential clinical utility of rTMS in SCA3 treatment. The Chinese Clinical Trial Registry identifier is ChiCTR1800020133.

A fluorogenic nitric oxide donor induced by yellow LED light for cells proliferation inhibition and imaging

Nitric oxide (NO), as a vital cellular signalling molecule in physiological processes, has been found to play an important role in various biological functions. In this study, we rationally designed three NO donors by tethering nitrobenzene derivatives to three fluorescent chromophores. NX-NO was found to release NO and exhibit a high fluorescence turn-on signal ratio upon exposure to LED yellow light. Additionally, it had excellent photo-stability and good inhibitory activity against cancer cell proliferation, and was successfully applied to cell imaging. Moreover, we detected the release of NO and fluorescence response in the blood of a mouse, suggesting its potential therapeutic application in living organisms.

Sensitivity to reward and punishment in adolescents with repetitive non-suicidal self-injury: The role of inhibitory control

Background

Repetitive Nonsuicidal Self-Injury (R-NSSI) is complex and prevalent in adolescents. Although the reward system is a promising mechanism to explain R-NSSI, the specific processes of reward and punishment related to R-NSSI remain unclear. This study examined whether adolescents with R-NSSI displayed difficulties in both reward and punishment contexts, and further explored the role of inhibitory control in processing monetary reward and punishment.

Methods

Within a cohort from two middle schools (N = 3,475, 48.6 % female, Mage = 12.95), a total of 187 adolescents completed three novel behavioral tasks. Specifically, in Study 1, 36 adolescents with R-NSSI and 28 without NSSI completed adapted incentive-delay tasks to evaluate sensitivity to reward and punishment. In Study 2, 27 adolescents with R-NSSI and 21 without NSSI were given novel incentive delay-two choice oddball task to evaluate the interaction between reward and inhibitory control. In Study 3, 38 adolescents with R-NSSI and 35 without NSSI completed similar task to assess the interaction between punishment and inhibitory control.

Results

Adolescents with R-NSSI were characterized by higher levels of behavioral reward and punishment sensitivity than adolescents without NSSI. More importantly, the difference between reward and punishment in inhibitory control of R-NSSI was found. Compared to adolescents without NSSI, adolescents with R-NSSI showed lower levels of inhibitory control in response to cues depicting punishment content but not to those depicting reward content.

Conclusions

This study provides novel experimental evidence that heightened behavioral sensitivity to both reward and punishment may be relevant trait marker in R-NSSI among adolescents, and emphasizes that punishment not reward interact with inhibitory control in the R-NSSI.

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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Study of High-Transverse-Momentum Higgs Boson Production in Association with a Vector Boson in the qqbb Final State with the ATLAS Detector

This Letter presents the first study of Higgs boson production in association with a vector boson (V=W or Z) in the fully hadronic qqbb final state using data recorded by the ATLAS detector at the LHC in proton-proton collisions at sqrt[s]=13  TeV and corresponding to an integrated luminosity of 137  fb^{-1}. The vector bosons and Higgs bosons are each reconstructed as large-radius jets and tagged using jet substructure techniques. Dedicated tagging algorithms exploiting b-tagging properties are used to identify jets consistent with Higgs bosons decaying into bb[over ¯]. Dominant backgrounds from multijet production are determined directly from the data, and a likelihood fit to the jet mass distribution of Higgs boson candidates is used to extract the number of signal events. The VH production cross section is measured inclusively and differentially in several ranges of Higgs boson transverse momentum: 250-450, 450-650, and greater than 650 GeV. The inclusive signal yield relative to the standard model expectation is observed to be μ=1.4_{-0.9}^{+1.0} and the corresponding cross section is 3.1±1.3(stat)_{-1.4}^{+1.8}(syst)  pb.

Paediatric meningitis in the conjugate vaccine era and a novel clinical decision model to predict bacterial aetiology

OBJECTIVES

The aims of this study were to assess aetiology and clinical characteristics in childhood meningitis, and develop clinical decision rules to distinguish bacterial meningitis from other similar clinical syndromes.

METHODS

Children aged <16 years hospitalised with suspected meningitis/encephalitis were included, and prospectively recruited at 31 UK hospitals. Meningitis was defined as identification of bacteria/viruses from cerebrospinal fluid (CSF) and/or a raised CSF white blood cell count. New clinical decision rules were developed to distinguish bacterial from viral meningitis and those of alternative aetiology.

RESULTS

The cohort included 3002 children (median age 2·4 months); 1101/3002 (36·7%) had meningitis, including 180 bacterial, 423 viral and 280 with no pathogen identified. Enterovirus was the most common pathogen in those aged <6 months and 10-16 years, with Neisseria meningitidis and/or Streptococcus pneumoniae commonest at age 6 months to 9 years. The Bacterial Meningitis Score had a negative predictive value of 95·3%. We developed two clinical decision rules, that could be used either before (sensitivity 82%, specificity 71%) or after lumbar puncture (sensitivity 84%, specificity 93%), to determine risk of bacterial meningitis.

CONCLUSIONS

Bacterial meningitis comprised 6% of children with suspected meningitis/encephalitis. Our clinical decision rules provide potential novel approaches to assist with identifying children with bacterial meningitis.

FUNDING

This study was funded by the Meningitis Research Foundation, Pfizer and the NIHR Programme Grants for Applied Research.

Mechanical Field Guiding Structure Design Strategy for Meta-Fiber Reinforced Hydrogel Composites by Deep Learning

Fiber-reinforced hydrogel composites are widely employed in many engineering applications, such as drug release, and flexible electronics, with more flexible mechanical properties than pure hydrogel materials. Comparing to the hydrogel strengthened by continuous fiber, the meta-fiber reinforced hydrogel provides stronger individualized design ability of deformation patterns and tunable stiffness, especially for the elaborate applications in joint, cartilage, and organ. In this paper, a novel structure design strategy based on deep learning algorithm is proposed for hydrogel reinforced by meta-fiber to achieve targeted mechanical properties, such as stress and displacement fields. A solid mechanic model for meta-fiber reinforced hydrogel is first developed to construct the dataset of fiber distribution and the corresponding mechanical properties of the composite. Generative adversarial network (GAN) is then trained to characterize the relationship between stress or displacement field, and meta-fiber distribution. The well-trained GAN is implemented to design meta-fiber reinforced hydrogel composite structure under specific operation conditions. The results show that the deep learning method may efficiently predict the structure of the hydrogel composite with satisfied confidence, and has great potential for applications in drug delivery and flexible electronics.

Effect of Traditional Chinese Medicine Characteristic Nursing on Perioperative Nursing of Children with Trichiasis Correction Under General Anesthesia

Objective

To study the nursing impact of traditional Chinese medicine on children undergoing trichiasis correction surgery with general anesthesia.

Methods

A total of 104 children with trichiasis admitted to the hospital for correction under general anesthesia from February 2020 to July 2023 were selected as the research objects. They were randomly divided into a comparison group (52 cases) and an observation group (52 cases). The comparison group was given routine nursing after surgery, and the observation group was given special nursing after surgery. Hamilton Anxiety Scale (HAMA) scores and Wong-Baker Smiley face scale scores of the two groups of children before and after nursing were observed, and the nursing satisfaction of family members of the two groups was evaluated.

Results

The anesthesia waking time, operation time, eating time and drinking time of the two groups in the observation group were lower than those in the comparison group, and the differences were statistically significant (P < .05). After nursing, the HAMA and HAMD scores of the two groups decreased, and the HAMA and HAMD scores of the two groups in the observation group were lower than those in the comparison group (P < .05). After nursing, the pain scores of the two groups were decreased, and the pain scores of the observation group were lower than those of the control group (P < .05). The visual acuity of the observation group was significantly better than that of the comparison group, and the difference was statistically significant (P < .05). The total satisfaction rate of the observation group was 94.23%, and that of the comparison group was 80.77%, and the total satisfaction rate of the observation group was higher than that of the comparison group (P < .05). The compliance of the observation group was 96.15%, and that of the comparison group was 84.62%, and the compliance of the observation group was higher than that of the comparison group (P < .05). Within 24h after the operation, the incidence of hunger, thirst, abdominal distension, fever, and irritable crying in the observation group was significantly lower than in the control group, and the difference was statistically significant (P < .05).

Conclusion

The application of traditional Chinese medicine-based nursing interventions can effectively alleviate negative emotions, alleviate pain, and enhance the satisfaction of family members towards nursing care for children undergoing trichiasis correction surgery under general anesthesia.

Research Status and Progress of Studies on Optic Disc Structures in Non-arteritic Anterior Ischemic Optic Neuropathy

Objective

Non-arteritic anterior ischemic optic neuropathy (NAION) is a prevalent acute optic neuropathy. This article provides a comprehensive overview of the research advancements in regional optic disc structural changes and local risk factors among NAION patients, aiming to establish a foundation for clinical diagnosis, treatment, and future follow-up investigations.

Methods

One English database and two Chinese databases were utilized for the purpose of conducting a comprehensive literature search, followed by meticulous analysis. The investigation encompassed an in-depth exploration of the optic disc's structural composition, as well as a thorough examination of the distinctive characteristics exhibited by NAION optic discs. Furthermore, this study aimed to elucidate the intricate relationship between NAION and ODD (Optic Disc Drusen) alongside PHOMS (Peripapillary Hyperreflective Ovoid Mass-like Structures).

Results

A total of 44 English articles were retrieved from Pubmed, including case reports, clinical trials, and reviews. Keywords retrieved included NAION, optic disc, optic disc drusen, PHOMS.

Conclusion

The risk factors of NAION include systemic factors such as hypertension, diabetes, and nocturnal hypotension and local factors such as small optic cup, crowded optic discs, ODD and PHOMS. Among them, ODD and PHOMS are the local anatomical changes of the optic disc, and their relationship with the occurrence of NAION has received more and more attention in recent years. NAION is more likely to occur in eyes with ODD and PHOMS, and NAION patients with ODD and PHOMS have a high prevalence. In recent years, optical coherence tomography (OCT) and optical coherence tomography angiography(OCTA) can provide accurate anatomical imaging and microvascular imaging. Help us better observe the local structural changes and local-related risk factors. Although ODD and PHOMS are closely associated with the occurrence and progression of NAION, research on their relationship is still in its nascent stages. Specifically, further investigation is needed to determine whether the presence of ODD and PHOMS affects the prognosis of NAION patients, including potential influences on lateral eye involvement.This article summarizes the changes in optic disc structure and local risk factors in NAION patients in order to clinical decision making in NIAON patients and provide a basis for further Research on the relationship between the occurrence of NIAON and optic disc structure.

Antibody level comparison after porcine epidemic diarrhea vaccination via different immunization routes

Porcine epidemic diarrhea (PED) is a disease extremely harmful to pig health. Intramuscular and Houhai acupoint injections are the main immunization routes to prevent and control PED. This study aimed to evaluate the efficacy of these two routes in pregnant sows based on serum IgG, IgA, and neutralizing antibody levels. PED virus (PEDV) immunoprophylaxis with live-attenuated and inactivated vaccines was administered. The vaccinations for the intramuscular injections elevated IgG and neutralizing antibody levels more than Houhai acupoint injections at most timepoints after immunization. However, the anti-PEDV IgA antibodies induced by vaccination with the two immunization routes did not differ significantly. In conclusion, intramuscular injections are better than Houhai acupoint injections for PEDV vaccination of pregnant sows.

Modulating the d-Band Center of Palladium via Ethylene Glycol Modification: Accelerating Had Desorption for Enhanced Formate Electrooxidation

This study addresses the critical challenge in alkaline direct formate fuel cells (DFFCs) of slow formate oxidation reaction (FOR) kinetics as a result of strong hydrogen intermediate (Had) adsorption on Pd catalysts. We developed WO3-supported Pd nanoparticles (EG-Pd/WO3) via an organic reduction method using ethylene glycol (EG), aiming to modulate the d-band center of Pd and alter Had adsorption dynamics. Cyclic voltammetry demonstrated significantly improved Had desorption kinetics in EG-Pd/WO3 catalysts. Density functional theory (DFT) calculations revealed that the presence of EG reduces the d-band center of Pd, leading to weaker Pd-H bonds and enhanced Had desorption during the FOR. This research provides a new approach to optimize catalyst efficiency in DFFCs, highlighting the potential for more effective and sustainable energy solutions through advanced material engineering.

Effects of second language acquisition on brain functional networks at different developmental stages

Previous studies have shown that language acquisition influences both the structure and function of the brain. However, whether the acquisition of a second language at different periods of life alters functional network organization in different ways remains unclear. Here, functional magnetic resonance imaging data from 27 English-speaking monolingual controls and 52 Spanish-English bilingual individuals, including 22 early bilinguals who began learning a second language before the age of ten and 30 late bilinguals who started learning a second language at age fourteen or later, were collected from the OpenNeuro database. Topological metrics of resting-state functional networks, including small-world attributes, network efficiency, and rich- and diverse-club regions, that characterize functional integration and segregation of the networks were computed via a graph theoretical approach. The results showed obvious increases in network efficiency in early bilinguals and late bilinguals relative to the monolingual controls; for example, the global efficiency of late bilinguals and early bilinguals was improved relative to that of monolingual controls, and the local efficiency of early bilinguals occupied an intermediate position between that of late bilinguals and monolingual controls. Obvious increases in rich-club and diverse-club functional connectivity were observed in the bilinguals relative to the monolingual controls. Three network metrics were positively correlated with Spanish proficiency test scores. These findings demonstrated that early and late acquisition of a second language had different impacts on the functional networks of the brain.

Electronic structure modulation of iron sites with fluorine coordination enables ultra-effective H2O2 activation

Electronic structure modulation of active sites is critical important in Fenton catalysis as it offers a promising strategy for boosting H2O2 activation. However, efficient generation of hydroxyl radicals (•OH) is often limited to the unoptimized coordination environment of active sites. Herein, we report the rational design and synthesis of iron oxyfluoride (FeOF), whose iron sites strongly coordinate with the most electronegative fluorine atoms in a characteristic moiety of F-(Fe(III)O3)-F, for effective H2O2 activation with potent •OH generation. Results demonstrate that the fluorine coordination plays a pivotal role in lowering the local electron density and optimizing the electronic structures of iron sites, thus facilitating the rate-limiting H2O2 adsorption and subsequent peroxyl bond cleavage reactions. Consequently, FeOF exhibits a significant and pH-adaptive •OH yield (~450 µM) with high selectivity, which is 1 ~ 3 orders of magnitude higher than the state-of-the-art iron-based catalysts, leading to excellent degradation activities against various organic pollutants at neutral condition. This work provides fundamental insights into the function of fluorine coordination in boosting Fenton catalysis at atomic level, which may inspire the design of efficient active sites for sustainable environmental remediation.

[Research status of glucagon-like peptide-1 receptor agonists on obstructive sleep apnea]

Obstructive sleep apnea (OSA) is the most common sleep-disordered breathing disease. Continuous positive airway pressure (CPAP) is the gold standard for treatment, but compliance is suboptimal. Therefore, new therapeutic strategies need to be explored. OSA is often associated with multiple comorbidities, particularly type 2 diabetes and obesity. Effective weight loss is known to be crucial in reversing OSA and its associated comorbidities. However, sustained weight loss is difficult to achieve with lifestyle changes alone. Medications that have both hypoglycemic and weight-loss effects are one way to achieve this goal. This article discussed the therapeutic effect of glucagon-like peptide-1 receptor agonists on this disease.

Enhancing gestational diabetes mellitus risk assessment and treatment through GDMPredictor: a machine learning approach

BACKGROUND

Gestational diabetes mellitus (GDM) is a serious health concern that affects pregnant women worldwide and can lead to adverse pregnancy outcomes. Early detection of high-risk individuals and the implementation of appropriate treatment can enhance these outcomes.

METHODS

We conducted a study on a cohort of 3467 pregnant women during their pregnancy, with a total of 5649 clinical and biochemical records collected. We utilized this dataset as our training dataset to develop a web server called GDMPredictor. The GDMPredictor utilizes advanced machine learning techniques to predict the risk of GDM in pregnant women. We also personalize treatment recommendations based on essential biochemical indicators, such as A1MG, BMG, CysC, CO2, TBA, FPG, and CREA. Our assessment of GDMPredictor's effectiveness involved training it on the dataset of 3467 pregnant women and measuring its ability to predict GDM risk using an AUC and auPRC.

RESULTS

GDMPredictor demonstrated an impressive level of precision by achieving an AUC score of 0.967. To tailor our treatment recommendations, we use the GDM risk level to identify higher risk candidates who require more intensive care. The GDMPredictor can accept biochemical indicators for predicting the risk of GDM at any period from 1 to 24 weeks, providing healthcare professionals with an intuitive interface to identify high-risk patients and give optimal treatment recommendations.

CONCLUSIONS

The GDMPredictor presents a valuable asset for clinical practice, with the potential to change the management of GDM in pregnant women. Its high accuracy and efficiency make it a reliable tool for doctors to improve patient outcomes. Early identification of high-risk individuals and tailored treatment can improve maternal and fetal health outcomes http://www.bioinfogenetics.info/GDM/ .

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.

Measurement of the Centrality Dependence of the Dijet Yield in p+Pb Collisions at sqrt[s_{NN}]=8.16 TeV with the ATLAS Detector

ATLAS measured the centrality dependence of the dijet yield using 165  nb^{-1} of p+Pb data collected at sqrt[s_{NN}]=8.16  TeV in 2016. The event centrality, which reflects the p+Pb impact parameter, is characterized by the total transverse energy registered in the Pb-going side of the forward calorimeter. The central-to-peripheral ratio of the scaled dijet yields, R_{CP}, is evaluated, and the results are presented as a function of variables that reflect the kinematics of the initial hard parton scattering process. The R_{CP} shows a scaling with the Bjorken x of the parton originating from the proton, x_{p}, while no such trend is observed as a function of x_{Pb}. This analysis provides unique input to understanding the role of small proton spatial configurations in p+Pb collisions by covering parton momentum fractions from the valence region down to x_{p}∼10^{-3} and x_{Pb}∼4×10^{-4}.

S100A9+CD14+ monocytes contribute to anti-PD-1 immunotherapy resistance in advanced hepatocellular carcinoma by attenuating T cell-mediated antitumor function

BACKGROUND

The paucity of reliable biomarkers for predicting immunotherapy efficacy in patients with advanced hepatocellular carcinoma (HCC) has emerged as a burgeoning concern with the expanding use of immunotherapy. This study endeavors to delve into the potential peripheral biomarkers capable of prognosticating efficacy in HCC patients who are poised to receive anti-PD-1 monotherapy within the phase III clinical trial, KEYNOTE394. Additionally, we sought to elucidate the underlying molecular mechanisms for resistance to immune checkpoint blockade (ICB) and propose innovative combination immunotherapy strategies for future clinical application.

METHODS

Patient blood samples were collected for single-cell RNA sequencing to evaluate the immune cell signature before receiving ICB therapy. Subsequently, in vitro assays and in vivo murine model experiments were conducted to validate the mechanism that S100A9+CD14+ monocytes play a role in ICB resistance.

RESULTS

Our study demonstrates a notable enrichment of S100A9+CD14+ monocytes in the peripheral blood of patients exhibiting suboptimal responses to anti-PD-1 therapy. Moreover, we identified the Mono_S100A9 signature as a predictive biomarker, indicative of reduced efficacy in immunotherapy and decreased survival benefits across various tumor types. Mechanistically, S100A9 activates PD-L1 transcription by directly binding to the CD274 (PD-L1) gene promoter, thereby suppressing T-cell proliferation and cytotoxicity via the PD-1/PD-L1 axis, consequently diminishing the therapeutic effectiveness of subsequent anti-PD-1 treatments. Furthermore, our in vivo studies revealed that inhibiting S100A9 can synergistically enhance the efficacy of anti-PD-1 drugs in the eradication of hepatocellular carcinoma.

CONCLUSIONS

Our study underscores the significance of S100A9+CD14+ monocytes in predicting inadequate response to ICB treatment and provides insights into the monocyte cell-intrinsic mechanisms of resistance to ICB therapy. We also propose a combined therapeutic approach to enhance ICB efficacy by targeting S100A9.

Epidemiological features and prognosis for primary gastrointestinal follicular lymphoma

Primary gastrointestinal follicular lymphoma (PGI-FL) is a rare extra-nodal lymphoma. Its epidemiology and prognosis remain unclear. We performed a retrospective analysis of eligible patients with 1648 PGI-FL and 34 892 nodal FL (N-FL) in the Surveillance, Epidemiology and End Results (SEER) database. The age-adjusted average annual incidence of PGI-FL was 0.111/100000. The median overall survival (OS) for PGI-FL and N-FL patients was 207 and 165 months respectively. The 5-year diffuse large B-cell lymphoma (DLBCL) transformation rates were 2.1% and 2.6% respectively. Age, sex, grade, Ann Arbor stage, primary site and radiation were independent prognostic factors (p < 0.05). Nomograms were constructed to predict 1-, 5- and 10-year OS and disease-specific survival (DSS). The receiver operating characteristic curves and calibration plots showed the established nomograms had robust and accurate performance. Patients were classified into three risk groups according to nomogram score. In conclusion, the incidence of PGI-FL has increased over the past 40 years, and PGI-FL has a better prognosis and a lower DLBCL transformation rate than N-FL. The nomograms were developed and validated as an individualized tool to predict survival. Patients were divided into three risk groups to assist clinicians in identifying high-risk patients and choosing the optimal individualized treatments.

Confining the Growth of AgNPs onto Epigallocatechin Gallate-Decorated Zein Nanoparticles for Constructing Potent Protein-Based Antibacterial Nanocomposites

Sliver nanoparticles (AgNPs) have attracted tremendous interest as an alternative to commercially available antibiotics due to their low microbial resistance and broad-spectrum antimicrobial activity. However, AgNPs are highly reactive and unstable and are susceptible to fast oxidation. Synthesizing stable and efficient AgNPs using green chemistry principles remains a major challenge. To address this issue, we establish a facile route to form AgNP-doped zein nanoparticle core-satellite superstructures with ultralow minimum bactericidal concentration (MBC). In brief, polyphenol surface-functionalization of zein nanoparticles was performed, and the epigallocatechin gallate (EGCG) layer on zein nanoparticles served as a reducing-cum-stabilizing agent. We used EGCG-decorated zein nanoparticles (ZE) as a template to direct the nucleation and growth of AgNPs to develop metallized hybrid nanoparticles (ZE-Ag). The highly monodispersed core-satellite nanoparticles (∼150 nm) decorated with ∼4.9 nm AgNPs were synthesized successfully. The spatial restriction of EGCG by zein nanoparticles confined the nucleation and growth of AgNPs only on the surface of the particles, which prevented the formation of entangled clusters of polyphenols and AgNPs and concomitantly inhibited the coalescence and oxidation of AgNPs. Thus, this strategy improved the effective specific surface area of AgNPs, and as a result, ZE-Ag efficiently killed the indicator bacteria, Escherichia coli (E. coli) and Methicillin-resistant Staphylococcus aureus(MRSA) after 20 min of incubation, with MBCs of 2 and 4 μg/mL, respectively. This situation indicated that as-prepared core-satellite nanoparticles possessed potent short-term sterilization capability. Moreover, the simulated wound infection model also confirmed the promising application of ZE-Ag as an efficient antimicrobial composite. This work provides new insights into the synthesis and emerging application of AgNPs in food preservation, packaging, biomedicine, and catalysis.

IL-6-Driven Autocrine Lactate Promotes Immune Escape of Uveal Melanoma

Purpose

Early metastasis, in which immune escape plays a crucial role, is the leading cause of death in patients with uveal melanoma (UM); however, the molecular mechanism underlying UM immune escape remains unclear, which greatly limits the clinical application of immunotherapy for metastatic UM.

Methods

Transcriptome profiles were revealed by RNA-seq analysis. TALL-104 and NK-92MI-mediated cell killing assays were used to examine the immune resistance of UM cells. The glycolysis rate was measured by extracellular acidification analysis. Protein stability was evaluated by CHX-chase assay. Immunofluorescence histochemistry was performed to detect protein levels in clinical UM specimens.

Results

Continuous exposure to IL-6 induced the expression of both PD-L1 and HLA-E in UM cells, which promoted UM immune escape. Transcriptome analysis revealed that the expression of most metabolic enzymes in the glycolysis pathway, especially the rate-limiting enzymes, PFKP and PKM, was upregulated, whereas enzymes involved in the acetyl-CoA synthesis pathway were downregulated after exposure to IL-6. Blocking the glycolytic pathway and lactate production by knocking down PKM and LDHA decreased PD-L1 and HLA-E protein, but not mRNA, levels in UM cells treated with IL-6. Notably, lactate secreted by IL-6-treated UM cells was crucial in influencing PD-L1 and HLA-E stability via the GPR81-cAMP-PKA signaling pathway.

Conclusions

Our data reveal a novel mechanism by which UM cells acquire an immune-escape phenotype by metabolic reprogramming and reinforce the importance of the link between inflammation and immune escape.

Ultralong afterglow of heavy-atom-free carbon dots with a phosphorescence lifetime of up to 3.7 s for encryption and fingerprinting description

Metal-free room-temperature phosphorescent (RTP) materials with changeable colors have attracted great attention in anti-counterfeiting information encryption. Most ultralong-lifetime RTP (URTP) luminophores are traditionally obtained through heavy atom effects via enhancing the spin-orbit coupling efficiency. Here, we report the self-assembly of URTP carbon dots (CDs) using diphenylaminourea as the precursor through a thermal-evaporation assisted covalent-binding approach in the presence of boric acid (BA). The BA-functionalized diphenylaminourea-derived CDs (denoted as D-CDs1.5/BA composites) show a rigid network structure with B-C linkages connected to the surface of the CDs, which can effectively suppress the free vibration of CDs to promote intersystem crossover, finally resulting in an excellent URTP afterglow performance. They feature a low singlet-triplet energy gap and reduced nonradiative attenuation properties. As a result, the D-CDs1.5/BA composites exhibit a bifunctional fluorescence/phosphorescence performance with a high phosphorescence quantum efficiency (12.67%) and an ultra-long green afterglow phosphorescence lifetime of up to 3.66 s. A high-level information encryption and fingerprinting description based on the URTP D-CDs1.5/BA composites were then investigated. This work contributes to the feasible design and preparation of novel URTP CD materials with both ultra-long afterglow and a high phosphorescence efficiency, making them promising candidates for advanced anti-counterfeiting applications.

Impact of combined propranolol and oxytocin on the process and outcomes of labor: a meta-analysis of randomized controlled trials

PURPOSE

To systematically review the impact of propranolol combined with oxytocin on the process and outcomes of labor.

METHODS

A comprehensive literature search was performed across multiple databases, including China National Knowledge Infrastructure (CNKI), VIP, Wanfang, China Biomedical Literature Database, PubMed, Embase, and the Cochrane Library. All publicly published randomized controlled trials (RCTs) of propranolol combined with oxytocin compared to the use of oxytocin alone in labor were collected. After screening the literature and extracting data, the Cochrane Handbook for Systematic Reviews of Interventions 5.1.0 recommended bias risk assessment tool was used to assess the quality of the included studies. A meta-analysis was conducted using RevMan 5.3 software, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system was used to rate the quality of evidence for outcome measures.

RESULTS

Meta-analysis results showed that the group receiving propranolol combined with oxytocin was more capable of reducing the cesarean section rate (eight studies, 815 women, RR = 0.67, 95% CI (0.53, 0.86), P = 0.001) and shortening the duration of the latent phase (two studies, 206 women, MD =  - 1.20, 95% CI (- 1.97, - 0.43), P = 0.002) and the duration of the active phase on day 1 (two studies, 296 women, MD =  - 0.69, 95% CI (- 0.83, - 0.54), P < 0.00001), compared to the oxytocin monotherapy group. No significant difference was found between the two groups in terms of the 5-min Apgar score (five studies, 609 women, MD =  - 0.05, 95% CI (- 0.14, 0.04), P = 0.32) and the rate of admissions to the Neonatal Intensive Care Unit (NICU) (three studies, 359 women, RR = 0.82, 95% CI (0.38, 1.79), P = 0.62).

CONCLUSION

The combined use of propranolol and oxytocin can significantly reduce the cesarean section rate, shorten the duration of the latent phase and the duration of the active phase on day 1, and is safe. However, due to the limitations, the conclusions of this article still need to be verified by large-sample, multicenter, rigorously designed high-quality clinical RCTs.

TRIAL REGISTRATION

Registration number is INPLASY202390107.

Phosphorylated CPI-17 and MLC2 as Biomarkers of Coronary Artery Spasm-Induced Sudden Cardiac Death

Coronary artery spasm (CAS) plays an important role in the pathogeneses of various ischemic heart diseases and has gradually become a common cause of life-threatening arrhythmia. The specific molecular mechanism of CAS has not been fully elucidated, nor are there any specific diagnostic markers for the condition. Therefore, this study aimed to examine the specific molecular mechanism underlying CAS, and screen for potential diagnostic markers. To this end, we successfully constructed a rat CAS model and achieved in vitro culture of a human coronary-artery smooth-muscle cell (hCASMC) contraction model. Possible molecular mechanisms by which protein kinase C (PKC) regulated CAS through the C kinase-potentiated protein phosphatase 1 inhibitor of 17 kDa (CPI-17)/myosin II regulatory light chain (MLC2) pathway were studied in vivo and in vitro to screen for potential molecular markers of CAS. We performed hematoxylin and eosin staining, myocardial zymogram, and transmission electron microscopy to determine myocardial and coronary artery injury in CAS rats. Then, using immunohistochemical staining, immunofluorescence staining, and Western blotting, we further demonstrated a potential molecular mechanism by which PKC regulated CAS via the CPI-17/MLC2 pathway. The results showed that membrane translocation of PKCα occurred in the coronary arteries of CAS rats. CPI-17/MLC2 signaling was observably activated in coronary arteries undergoing CAS. In addition, in vitro treatment of hCASMCs with angiotensin II (Ang II) increased PKCα membrane translocation while consistently activating CPI-17/MLC2 signaling. Conversely, GF-109203X and calphostin C, specific inhibitors of PKC, inactivated CPI-17/MLC2 signaling. We also collected the coronary artery tissues from deceased subjects suspected to have died of CAS and measured their levels of phosphorylated CPI-17 (p-CPI-17) and MLC2 (p-MLC2). Immunohistochemical staining was positive for p-CPI-17 and p-MLC2 in the tissues of these subjects. These findings suggest that PKCα induced CAS through the CPI-17/MLC2 pathway; therefore, p-CPI-17 and p-MLC2 could be used as potential markers for CAS. Our data provide novel evidence that therapeutic strategies against PKC or CPI-17/MLC2 signaling might be promising in the treatment of CAS.

Two new 2-(2-phenylethyl)chromone derivatives and two sesquiterpenes from agarwood of Aquilaria sinensis with anti-inflammatory activity

Two new 2-(2-phenylethyl)chromones (1-2), two new sesquiterpenes (12-13), and twelve known compounds (3-11, 14-16) were isolated from agarwood of Aquilaria sinensis. These structures were confirmed by HRESIMS, 1D and 2D NMR spectra. The absolute configurations of two new sesquiterpenes were determined by comparing the experimental and calculated ECD spectra. Among them, 7,8-dihydroxy-2-[2-(4'-methoxyphenyl)ethyl]chromone (2) was the first time found that the hydroxyl groups at both C-7/C-8 in agarwood. And Aseudesm B (13), the aldehyded methyl group at C-5 of eucalyptane sesquiterpenes was first discovered in natural products. In the bioassays, all compounds were evaluated for their inhibitory activity against lipopolysaccharide-activated nitric oxide (NO) production in RAW264.7 cells. Compounds 2-5, 7, 9-10, and 13-14 revealed notable inhibitory effects against NO production with IC50 values ranging from 4.0 to 13.0 μM.

Upregulation of tumor suppressor PIAS3 by Honokiol promotes tumor cell apoptosis via selective inhibition of STAT3 tyrosine 705 phosphorylation

The natural product Honokiol exhibits robust antitumor activity against a range of cancers, and it has also received approval to undergo phase I clinical trial testing. We confrmed that honokiol can promote the apoptotic death of tumor cells through cell experiments. Then siRNA constructs specific for PIAS3, PIAS3 overexpression plasmid and the mutation of the STAT3 Tyr705 residue were used to confirm the mechanism of Honokiol-induced apoptosis. Finally, we confrmed that honokiol can promote PIAS3 upregulation, in turn suppressing STAT3 Tyr705 phosphorylation through the in vivo and in vitro experiments. Honokiol was ultimately found to reduce tumor cell viability by promoting apoptosis through a mechanism dependent on the ability of Honokiol to promote PIAS3 upregulation and the selective inhibition of p-STAT3 (Tyr705) without affecting p-STAT3 (Ser727) or p-STAT1 (Tyr701) levels. PIAS3 knockdown and overexpression in tumor cells altered STAT3 activation and associated DNA binding activity through the control of Tyr705 phosphorylation via PIAS3-STAT3 complex formation, ultimately shaping Honokiol-induced tumor cell apoptosis. Honokiol was also confirmed to significantly prolong the survival of mice bearing xenograft tumors in a PIAS3-dependent fashion. Together, these findings highlight a novel pathway through which Honokiol can promote PIAS3 upregulation, in turn suppressing STAT3 Tyr705 phosphorylation and promoting the apoptotic death of tumor cells.

Unconventional luminescent CS-PEC-based composite hemostasis sponge with antibacterial activity and visual monitoring for wound healing

Multifunctional wound dressings are promising medical materials for various applications. Among them, dressings with antimicrobial activity, high biosafety, and real-time monitoring have attracted considerable research interest. Herein, a biodegradable hemostatic sponge comprising a chitosan skeleton and polyelectrolyte-surfactant complex (CS-PEC) was developed as a versatile wound dressing for wound pH monitoring and inhibition of bacterial infection. CS-PEC sponge with high porosity exhibited satisfactory fluid absorption capacity and biocompatibility, along with antibacterial properties against E. coli and S. aureus. In vivo experiments in rat liver trauma model revealed that wounds treated with the CS-PEC sponge recorded less blood loss (97.1 mg) and shorter hemostasis time (27.2 s) than those treated with commercial gelatin sponge (309.1 mg and 163.5 s, respectively). Furthermore, PECs based on unconventional luminescent molecules (L-C16-Hyp) were used as pH fluorescent indicators, which endowed the sponge with fluorescence-responsive behavior to wound pH changes in the range of 5.0-8.5. Visual images can be captured using a smartphone and converted to RGB color mode values for on-site assessment of wound status. This study sheds light on the design and application of unconventional luminescent materials in wound dressing and provides a smart and effective solution for wound management.