DCES-PA: Deformation-controllable elastic shape model for 3D bone proliferation analysis using hand HR-pQCT images

Bone proliferation is an important pathological feature of inflammatory rheumatic diseases. Although recent advance in high-resolution peripheral quantitative computed tomography (HR-pQCT) enables physicians to study microarchitectures, physicians' annotation of proliferation suffers from slice inconsistency and subjective variations. Also, there are only few effective automatic or semi-automatic tools for proliferation detection. In this study, by integrating pathological knowledge of proliferation formation with the advancement of statistical shape analysis theory, we present an unsupervised method, named Deformation-Controllable Elastic Shape model, for 3D bone Proliferation Analysis (DCES-PA). Unlike previous shape analysis methods that directly regularize the smoothness of the displacement field, DCES-PA regularizes the first and second-order derivative of the displacement field and decomposes these vector fields according to different deformations. For the first-order elastic metric, DCES-PA orthogonally decomposes the first-order derivative of the displacement field by shearing, scaling and bending deformation, and then penalize deformations triggering proliferation formation. For the second-order elastic metric, DCES-PA encodes both intrinsic and extrinsic surface curvatures into the second-order derivative of the displacement field to control the generation of high-curvature regions. By integrating the elastic shape metric with the varifold distances, DCES-PA achieves correspondence-free shape analysis. Extensive experiments on both simulated and real clinical datasets demonstrate that DCES-PA not only shows an improved accuracy than other state-of-the-art shape-based methods applied to proliferation analysis but also produces highly sensitive proliferation annotations to assist physicians in proliferation analysis.

[Multi-omics prediction of lymph node metastasis status in breast cancer]

Lymph node metastasis status stands as a pivotal prognostic indicator in forecasting the outlook for breast cancer patients. Consequently, precise evaluation of this status holds paramount importance in the staging, treatment, and prognosis of breast cancer. The utilization of radiomics, genomics, proteomics, transcriptomics, and histopathology methodologies has notably enhanced the precision of lymph node metastasis status prediction in breast cancer. This review provides an overview of recent advancements in omics-based lymph node metastasis prediction for breast cancer, elucidating the significance of various omics prediction models and integrated multi-omics models in this predictive endeavor. The overarching goal is to augment the accuracy of preoperative lymph node metastasis status prediction in breast cancer, thereby aiding clinicians in the selection of efficacious personalized treatment strategies, while concurrently averting undertreatment of patients with a heightened risk of metastasis.

[Prognostic value of skeletal muscle measured by CT at the T4 level in advanced EGFR-positive non-small cell lung cancer patients treated with ecotinib]

Objective: To investigate the prognostic value of skeletal muscle measured by CT at the level of the fourth thoracic vertebra (T4) in advanced epidermal growth factor receptor (EGFR)-positive non-small cell lung cancer (NSCLC) patients treated with ecotinib. Methods: The study retrospectively reviewed clinical and pathological characteristics of 176 patients with advanced EGFR-positive NSCLC who received ecotinib and underwent chest CT scans at Wuhan Union Hospital between January 2017 and October 2020. Among them, 70 were male and 106 were female, with ages ranging from 27 to 80 (58.6±10.6) years. As of August 21, 2021, the median follow-up duration was 19.2 months (95%CI: 15.3 to 23.7 months). The optimal cut-off value of skeletal muscle density (T4-SMD) on CT images at the T4 level were determined using X-tile software. Kaplan-Meier analysis and log-rank test were used to plot progression-free survival curves. Cox proportional hazards regression models were employed to analyze factors influencing 1-year progression-free survival (PFS), and a nomogram prognostic model was constructed accordingly. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were utilized to evaluate the predictive value of the nomogram. Results: The T4-SMD [M (Q1,Q3)] of 176 patients was 42.56 (37.05, 45.93) HU. Patients were divided into low T4-SMD group (n=122) and high T4-SMD group (n=54) based on the cut-off value (The values for males and females were 49.44 and 41.41 HU, respectively) of T4-SMD. The median PFS time and 1-year PFS rate in the low T4-SMD group were significantly lower than those in the high T4-SMD group [10.4 (95%CI: 9.3-11.8) vs 13.7 (95%CI: 11.1-18.5) months, 36.1% vs 59.3%, respectively, P=0.034]. Eastern Cooperative Oncology Group performance status (HR=3.308, 95%CI: 1.183-9.247, P=0.023), lactate dehydrogenase level (HR=1.852, 95%CI: 1.037-3.307, P=0.037), systemic immune-inflammation index (HR=1.772, 95%CI: 1.019-3.080, P=0.043), and T4-SMD (HR=0.563, 95%CI: 0.325-0.974, P=0.040) were prognostic factors for 1-year PFS in advanced EGFR-positive NSCLC patients treated with ecotinib. A nomogram for predicting 1-year PFS of advanced EGFR-positive NSCLC patients treated with ecotinib was constructed based on the four indicators selected by multivariate Cox regression analysis. The area under the ROC curve of the nomogram was 0.775 (95%CI: 0.676-0.874). The calibration curve showed good consistency between the predicted and actual 1-year PFS. DCA demonstrated good clinical prediction effectiveness of the nomogram. Conclusion: Low T4-SMD is a prognostic risk factor for patients with advanced EGFR-positive NSCLC receiving icotinib therapy.

[Opportunities and challenges in accurate early diagnosis and treatment of lung cancer/pulmonary nodules]

Lung cancer remains the most prevalent and lethal malignancy in our country. Early diagnosis and treatment are crucial for improving patient prognosis in lung cancer/pulmonary nodules. Recent advancements in non-invasive/minimally invasive liquid biopsy, multi-omics, and artificial intelligence technologies have significantly enhanced the accuracy of early lung cancer/pulmonary nodule diagnosis. However, an early diagnostic method with both high sensitivity and specificity is yet to be established. Furthermore, addressing the methods and extent of early precision surgery, local precision therapy, perioperative combined treatment, and postoperative recurrence and metastasis monitoring are urgent challenges in the early management of lung cancer/pulmonary nodules. Integrating the advantages of various treatment strategies and formulating personalized and precise treatment plans is key to further improving patient survival. In the future, while exploring new therapeutic strategies, it is necessary to continuously search for biomarkers to identify the population that will benefit from the treatment effectively. Additionally, large-sample randomized controlled clinical studies should be conducted to investigate the benefits of long-term patient survival under a diverse range of treatment strategies.

[Theory and practice of mesenchymal condensation directing tooth development and regeneration]

Mesenchymal stem cells, under spatiotemporal regulation of genes and microenvironment, are capable of spontaneously aggregating into dense regions, a phenomenon known as mesenchymal condensation. Mesenchymal condensation is an evolutionarily conserved developmental event that is critical in initiating morphogenesis of teeth and systemic organs. Mesenchymal stem cells hold the intrinsic ability to self-assemble in culture, and the generation of stem cell aggregates based on this property that mimics developmental mesenchymal condensation has become a potent and promising approach in regenerative medicine. This review discusses the mesenchymal condensation principles and its role as well as mechanism in tooth morphogenesis, as well as the engineering strategies for constructing mesenchymal stem cell aggregates and their application experience in tooth regeneration. It aims to start from the perspective of "development-inspired regeneration" and provide insights into understanding stem cell developmental biology and establishing new organ regenerative strategies.

[Study on liver tissue derived-extracellular vesicles regulating the osteogenic differentiation ability of mesenchymal stem cells and promoting the healing of jaw bone defects]

Objective: To explore the biological process of liver tissue-derived extracellular vesicle (LT-EV) in promoting osteogenic differentiation of mesenchymal stem cells and healing of jaw defects to provide a feasible treatment method for the clinical treatment of jaw bone defects. Methods: Enzymatic hydrolysis and differential centrifugation were used to extract LT-EV, scanning electron microscopy, Western blotting, and nanoparticle tracking analyzers were used to identify and characterize LT-EV, and further to explore the biological functions of LT-EV through proteomics and Kyoto Encyclopedia of Genes and Genomes. Flow cytometry was used to detect LT-EV plasma concentration and to calculate the plasma half-life of LT-EV. Small animal in vivo imaging system was used to detect the biological distribution of LT-EV 24 hours after injection. Six C57BL/6 mice were divided into control group and LT-EV group (3 mice in each group) by simple random sampling method. All mice underwent jaw bone defect surgery and tail vein injection every 7 days (the control group was injected with phosphoric buffer saline, LT-EV group was injected with LT-EV), micro-CT was used to evaluate the degree of mouse jaw bone healing 28 days after surgery, HE staining was used to analyze the multi-organ biosafety of LT-EV, and immunofluorescence staining was used to detect the jaw bone expression of osteogenic marker proteins in the defect area. Human jaw bone mesenchymal stem cells (hJBMSC) induced by osteogenic differentiation were treated with LT-EV (obtained from orthognathic surgery patients provided by the Department of Traumatology and Orthognathic Surgery of School of Stomatology of The Fourth Military Medical University resected normal jaw bone fragments), and the difference in osteogenic differentiation ability between the hJBMSC group and the control group (phosphate buffer saline treatment) was compared, and the in vitro bone differentiation promoting effect of LT-EV was verified through alkaline phosphatase (ALP) staining and real-time fluorescence quantitative PCR. Results: The yield of LT-EV was high, and proteomics and Kyoto Encyclopedia of Genes and Genomes showed that LT-EV contained a series of proteins that regulated cell biological functions. LT-EV injected into the tail vein could reach the mouse jaw bone defect area and promote the regeneration and repair of the jaw bone defect [the bone volume fractions of the LT-EV group and the control group were (36.06±4.20)% and (18.58±5.61)%, respectively; t=4.32, P=0.013], and had good biosafety. LT-EV could promote osteogenic differentiation of hJBMSC in vitro. Compared to the control group, ALP staining and osteogenic gene expression levels were significantly enhanced after osteogenic differentiation of hJBMSC (P<0.05). Conclusions: LT-EV exhibits a high yield, ease of acquisition, high biological safety, and excellent bone-promoting effects. It holds promise as a novel cell-free therapy strategy for regenerating craniofacial bone defects.

[Construction of a model based on multipoint full-layer puncture biopsy for predicting pathological complete response after neoadjuvant therapy for locally advanced rectal cancer]

Objective: To investigate the value of transanal multipoint full-layer puncture biopsy (TMFP) in predicting pathological complete response (pCR) after neoadjuvant radiotherapy and chemotherapy (nCRT) in patients with locally advanced rectal cancer (LARC) and to establish a predictive model for providing clinical guidance regarding the treatment of LARC. Methods: In this multicenter, prospective, cohort study, we collected data on 110 LARC patients from four hospitals between April 2020 and March 2023: Beijing Chaoyang Hospital of Capital Medical University (50 patients), Beijing Friendship Hospital of Capital Medical University (41 patients), Qilu Hospital of Shandong University (16 patients), and Zhongnan Hospital of Wuhan University (three patients). The patients had all received TMFP after completing standard nCRT. The variables studied included (1) clinicopathological characteristics; (2) clinical complete remission (cCR) and efficacy of TMFP in determining pCR after NCRT in LARC patients; and (3) hospital attended, sex, age, clinical T- and N-stages, distance between the lower margin of the tumor and the anal verge, baseline and post-radiotherapy serum carcinoembryonic antigen (CEA) and carbohydrate antigen (CA)19-9 concentrations, chemotherapy regimen, use of immunosuppressants with or without radiotherapy, radiation therapy dosage, interval between surgery and radiotherapy, surgical procedure, clinical T/N stage after radiotherapy, cCR, pathological results of TMFP, puncture method (endoscopic or percutaneous), and number and timing of punctures. Single-factor and multifactorial logistic regression analysis were used to determine the factors affecting pCR after NCRT in LARC patients. A prediction model was constructed based on the results of multivariat analysis and the performance of this model evaluated by analyzing subject work characteristics (ROC), calibration, and clinical decision-making (DCA) curves. pCR was defined as complete absence of tumor cells on microscopic examination of the surgical specimens of rectal cancer (including lymph node dissection) after NCRT, that is, ypT0+N0. cCR was defined according to the Chinese Neoadjuvant Rectal Cancer Waiting Watch Database Study Collaborative Group criteria after treatment, which specify an absence of ulceration and nodules on endoscopy; negative rectal palpation; no tumor signals on rectal MRI T2 and DWI sequences; normal serum CEA concentrations, and no evidence of recurrence on pelvic computed tomography/magnetic resonance imaging. Results: Of the 110 patients, 45 (40.9%) achieved pCR after nCRT, which was combined with immune checkpoint inhibitors in 34 (30.9%). cCR was diagnosed before puncture in 38 (34.5%) patients, 43 (39.1%) of the punctures being endoscopic. There were no complications of puncture such as enterocutaneous fistulae, vaginal injury, prostatic injury, or presacral bleeding . Only one (2.3%) patient had a small amount of blood in the stools, which was relieved by anal pressure. cCR had a sensitivity of 57.8% (26/45) for determining pCR, specificity of 81.5% (53/65), accuracy of 71.8% (79/110), positive predictive value 68.4% (26/38), and negative predictive value of 73.6% (53/72). In contrast, the sensitivity of TMFP pathology in determining pCR was 100% (45/45), specificity 66.2% (43/65), accuracy 80.0% (88/110), positive predictive value 67.2% (45/67), and negative predictive value 100.0% (43/43). In this study, the sensitivity of TMFP for pCR (100.0% vs. 57.8%, χ2=24.09, P<0.001) was significantly higher than that for cCR. However, the accuracy of pCR did not differ significantly (80.0% vs. 71.8%, χ2=2.01, P=0.156). Univariate and multivariate logistic regression analyses showed that a ≥4 cm distance between the lower edge of the tumor and the anal verge (OR=7.84, 95%CI: 1.48-41.45, P=0.015), non-cCR (OR=4.81, 95%CI: 1.39-16.69, P=0.013), and pathological diagnosis by TMFP (OR=114.29, the 95%CI: 11.07-1180.28, P<0.001) were risk factors for pCR after NCRT in LARC patients. Additionally, endoscopic puncture (OR=0.02, 95%CI: 0.05-0.77, P=0.020) was a protective factor for pCR after NCRT in LARC patients. The area under the ROC curve of the established prediction model was 0.934 (95%CI: 0.892-0.977), suggesting that the model has good discrimination. The calibration curve was relatively close to the ideal 45° reference line, indicating that the predicted values of the model were in good agreement with the actual values. A decision-making curve showed that the model had a good net clinical benefit. Conclusion: Our predictive model, which incorporates TMFP, has considerable accuracy in predicting pCR after nCRT in patients with locally advanced rectal cancer. This may provide a basis for more precisely selecting individualized therapy.

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

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

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

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

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

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

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.

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.

METHODS

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds.

FINDINGS

The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.

INTERPRETATION

Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere.

FUNDING

Bill & Melinda Gates Foundation.

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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[Analysis of 9 patients with adolescence-onset methylenetetrahydrofolate reductase deficiency]

Objective: To explore the diagnosis and treatment of adolescence-onset methylenetetrahydrofolate reductase (MTHFR) deficiency. Methods: This was a retrospective case study. Nine patients with adolescence-onset MTHFR deficiency were diagnosed at Peking University First Hospital from January 2016 to December 2022, and followed up for more than 1 year. Their general information, clinical manifestations, laboratory tests, cranial images, MTHFR gene variants, diagnosis, treatment, and outcome were analyzed retrospectively. Results: The 9 patients came from 8 families. They had symptoms at age of 8.0 years to 17.0 years and diagnosed at 9.0 years to 17.5 years. Eight were male and 1 was female. Two patients were brothers, the elder brother developed abnormal gait at 17.0 years; and the younger brother was then diagnosed at 15.0 years of age and treated at the asymptomatic stage, who was 18.0 years old with normal condition during this study. The main manifestations of the 8 symptomatic patients included progressive dyskinesia and spastic paralysis of the lower limbs, with or without intellectual decline, cognitive impairment and behavioral abnormalities. Totally, 15 variants of MTHFR gene were identified in the 9 patients, including 8 novel variants. Five patients had brain image abnormalities. Increased plasma total homocysteine level (65-221 μmol/L) was found in all patients, and decreased to 20-70 μmol/L after treatment with betaine and calcium folinate. Besides, the 8 symptomatic patients had their behavior and cognitive problems significantly improved, with a legacy of lower limb motor disorders. Conclusions: Late-onset MTHFR deficiency can occur in adolescence. The diagnosis is usually delayed because of non-specific clinical symptoms. The test of blood total homocysteine could be used as a selective screening test. Eight novel varients of MTHFR gene were identified. Timely treatment can improve clinical condition significantly, and pre-symptomatic treatment may prevent brain damage.

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.

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950-2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020-21 COVID-19 pandemic period.

METHODS

22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution.

FINDINGS

Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5-65·1] decline), and increased during the COVID-19 pandemic period (2020-21; 5·1% [0·9-9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98-5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50-6·01) in 2019. An estimated 131 million (126-137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7-17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8-24·8), from 49·0 years (46·7-51·3) to 71·7 years (70·9-72·5). Global life expectancy at birth declined by 1·6 years (1·0-2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67-8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4-52·7]) and south Asia (26·3% [9·0-44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations.

INTERPRETATION

Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic.

FUNDING

Bill & Melinda Gates Foundation.

Global trends in deaths and disability-adjusted life years of diabetes attributable to second-hand smoke and the association with smoke-free policies

OBJECTIVES

The diabetic burden attributable to second-hand smoke (SHS) is a global public health challenge. We sought to explore the diabetic burden attributable to SHS by age, sex, and socioeconomic status during 1990-2019 and to evaluate the health benefit of smoke-free policies on this burden.

STUDY DESIGN

Cross-sectional study.

METHODS

The diabetic burden attributable to SHS was extracted from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 dataset. Country-level smoke-free policies were obtained from the World Health Organization Global Health Observatory. The deaths or disability-adjusted life years (DALYs) were quantified, and the average annual percentage changes were calculated. Hierarchical linear mixed models were applied to evaluate the health effects.

RESULTS

From 1990 to 2019, the absolute number of global deaths and DALYs of diabetes attributable to SHS has doubled, and the age-standardised rate has significantly increased. The disease burden was higher in females than in males and increased with increasing age. The SHS-related diabetic burden varied across regions and countries. Age-standardised death or DALY rates first increased and then decreased with increased Socio-demographic Index (SDI), peaking in the 0.60-0.70 range. In low to low-middle, and middle to high-middle SDI countries, SHS-related diabetic deaths and DALYs were significantly lower in countries with more than 3 smoke-free public places than in countries with 0-2 smoke-free public places.

CONCLUSIONS

More attention should be paid to females and the elderly, who bear a heavy SHS-related diabetic burden. Banning smoking in public places was associated with reduced burden of SHS-attributable diabetes, especially in low to middle social development countries.

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

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

Global, regional, and national burden of neck pain, 1990-2020, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021

BACKGROUND

Neck pain is a highly prevalent condition that leads to considerable pain, disability, and economic cost. We present the most current estimates of neck pain prevalence and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) by age, sex, and location, with forecasted prevalence to 2050.

METHODS

Systematic reviews identified population-representative surveys used to estimate the prevalence of and YLDs from neck pain in 204 countries and territories, spanning from 1990 to 2020, with additional data from opportunistic review. Medical claims data from Taiwan (province of China) were also included. Input data were pooled using DisMod-MR 2.1, a Bayesian meta-regression tool. Prevalence was forecast to 2050 using a mixed-effects model using Socio-demographic Index as a predictor and multiplying by projected population estimates. We present 95% UIs for every metric based on the 2·5th and 97·5th percentiles of 100 draws of the posterior distribution.

FINDINGS

Globally, in 2020, neck pain affected 203 million (95% uncertainty interval [UI] 163-253) people. The global age-standardised prevalence rate of neck pain was estimated to be 2450 (1960-3040) per 100 000 population and global age-standardised YLD rate was estimated to be 244 (165-346) per 100 000. The age-standardised prevalence rate remained stable between 1990 and 2020 (percentage change 0·2% [-1·3 to 1·7]). Globally, females had a higher age-standardised prevalence rate (2890 [2330-3620] per 100 000) than males (2000 [1600-2480] per 100 000), with the prevalence peaking between 45 years and 74 years in male and female sexes. By 2050, the estimated global number of neck pain cases is projected to be 269 million (219-322), with an increase of 32·5% (23·9-42·3) from 2020 to 2050. Decomposition analysis of the projections showed population growth was the primary contributing factor, followed by population ageing.

INTERPRETATION

Although age-standardised rates of neck pain have remained stable over the past three decades, by 2050 the projected case numbers are expected to rise. With the highest prevalence in older adults (higher in females than males), a larger effect expected in low-income and middle-income countries, and a rapidly ageing global population, neck pain continues to pose a challenge in terms of disability burden worldwide. For future planning, it is essential we improve our mechanistic understanding of the different causes and risk factors for neck pain and prioritise the consistent collection of global neck pain data and increase the number of countries with data on neck pain.

FUNDING

Bill & Melinda Gates Foundation and Global Alliance for Musculoskeletal Health.

Autonomic neural regulation in mediating the brain-bone axis: mechanisms and implications for regeneration under psychological stress

Efficient regeneration of bone defects caused by disease or significant trauma is a major challenge in current medicine, which is particularly difficult yet significant under the emerging psychological stress in the modern society. Notably, the brain-bone axis has been proposed as a prominent new concept in recent years, among which autonomic nerves act as an essential and emerging skeletal pathophysiological factor related to psychological stress. Studies have established that sympathetic cues lead to impairment of bone homeostasis mainly through acting on mesenchymal stem cells (MSCs) and their derivatives with also affecting the hematopoietic stem cell (HSC)-lineage osteoclasts, and the autonomic neural regulation of stem cell lineages in bone is increasingly recognized to contribute to the bone degenerative disease, osteoporosis. This review summarizes the distribution characteristics of autonomic nerves in bone, introduces the regulatory effects and mechanisms of autonomic nerves on MSC and HSC lineages, and expounds the crucial role of autonomic neural regulation on bone physiology and pathology, which acts as a bridge between the brain and the bone. With the translational perspective, we further highlight the autonomic neural basis of psychological stress-induced bone loss and a series of pharmaceutical therapeutic strategies and implications toward bone regeneration. The summary of research progress in this field will add knowledge to the current landscape of inter-organ crosstalk and provide a medicinal basis for the achievement of clinical bone regeneration in the future.

First demonstration of 30 eVee ionization energy resolution with Ricochet germanium cryogenic bolometers

The future Ricochet experiment aims to search for new physics in the electroweak sector by measuring the Coherent Elastic Neutrino-Nucleus Scattering process from reactor antineutrinos with high precision down to the sub-100 eV nuclear recoil energy range. While the Ricochet collaboration is currently building the experimental setup at the reactor site, it is also finalizing the cryogenic detector arrays that will be integrated into the cryostat at the Institut Laue Langevin in early 2024. In this paper, we report on recent progress from the Ge cryogenic detector technology, called the CryoCube. More specifically, we present the first demonstration of a 30 eVee (electron equivalent) baseline ionization resolution (RMS) achieved with an early design of the detector assembly and its dedicated High Electron Mobility Transistor (HEMT) based front-end electronics with a total input capacitance of about 40 pF. This represents an order of magnitude improvement over the best ionization resolutions obtained on similar phonon-and-ionization germanium cryogenic detectors from the EDELWEISS and SuperCDMS dark matter experiments, and a factor of three improvement compared to the first fully-cryogenic HEMT-based preamplifier coupled to a CDMS-II germanium detector with a total input capacitance of 250 pF. Additionally, we discuss the implications of these results in the context of the future Ricochet experiment and its expected background mitigation performance.

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

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

[The effect of Ba Duan Jin on the balance of community-dwelling older adults: a cluster randomized control trial]

Objective: To assess the effectiveness of a 6-month Ba Duan Jin exercise program in improving the balance of community-dwelling older adults. Methods: A two arms, parallel-group, cluster randomized controlled trial was conducted in 1 028 community residents aged 60-80 years in 40 communities in 5 provinces of China. Participants in the intervention group (20 communities, 523 people) received Ba Duan Jin exercise 5 days/week, 1 hour/day for 6 months, and three times of falls prevention health education, and the control group (20 communities, 505 people) received falls prevention health education same as the intervention group. The Berg balance scale (BBS) score was the leading outcome indicator, and the secondary outcome indicators included the length of time of standing on one foot (with eyes open and closed), standing in a tandem stance (with eyes open and closed), the closed circle test, and the timed up to test. Results: A total of 1 028 participants were included in the final analysis, including 731 women (71.11%) and 297 men (28.89%), and the age was (69.87±5.67) years. After the 3-month intervention, compared with the baseline data, the BBS score of the intervention group was significantly higher than the control group by 3.05 (95%CI: 2.23-3.88) points (P<0.001). After the 6-month intervention, compared with the baseline data, the BBS score of the intervention group was significantly higher than the control group by 4.70 (95%CI: 4.03-5.37) points (P<0.001). Ba Duan Jin showed significant improvement (P<0.05) in all secondary outcomes after 6 months of exercise in the intervention group compared with the control group. Conclusions: This study showed that Ba Duan Jin exercise can improve balance in community-dwelling older adults aged 60-80. The longer the exercise time, the better the improvement.

China's prevention and control experience of echinococcosis: A 19-year retrospective

Echinococcosis poses a significant threat to public health. The Chinese government has implemented prevention and control measures to mitigate the impact of the disease. By analyzing data from the Chinese Center for Disease Control and Prevention and the State Council of the People's Republic of China, we found that implementation of these measures has reduced the infection rate by nearly 50% between 2004 to 2022 (from 0.3975 to 0.1944 per 100,000 person-years). Nonetheless, some regions still bear a significant disease burden, and lack of detailed information limites further evaluation of the effects on both alveolar and cystic echinococcosis. Our analysis supports the continuing implementation of these measures and suggests that enhanced wildlife management, case-based strategies, and surveillance systems will facilitate disease control.

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

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

Pharmacokinetics of intravenous and topical lidocaine in patients undergoing thoracoscopic pulmonary resection: a comparative study

OBJECTIVE

Lidocaine was the commonly used local anesthetic. The present study aimed to compare the pharmacokinetics of intravenous and topical lidocaine in patients undergoing thoracoscopic pulmonary resection.

PATIENTS AND METHODS

Sixty patients who were scheduled for thoracoscopic pulmonary resection were screened and randomly assigned to the intravenous lidocaine group and topical lidocaine group. After induction, the patient in the intravenous group was given an intravenous bolus of 1.5 mg/kg lidocaine, while the patient in the topical group was given 3.0 mg/kg lidocaine via the "spray-as-you-go" method. Arterial blood was sampled at preset intervals, and plasma concentrations of lidocaine and its metabolites [monoethylglycinexylidide (MEGX) and glycinexylidide (GX)] were measured by ultra-performance liquid chromatography-tandem mass spectrometry.

RESULTS

Following intravenous administration, plasma lidocaine concentration reached its peak with a time to reach Cmax (Tmax) of 0.05 h and then decreased in a biphasic manner with a very short half-life time (T1/2) of 1.85 h. After topical administration, lidocaine was well absorbed, with Tmax of 0.21 h and bioavailability of 71.02%. The mean Tmax, Cmax, and area under the curve from the time (AUC0-t) of MEGX and GX were higher in the topical group than in the intravenous group. There were no obvious differences in the Cmax, T1/2, clearance, or apparent volume of distribution of lidocaine between the two groups. No obvious adverse events were observed.

CONCLUSIONS

Topical administration of 3 mg/kg lidocaine via the "spray-as-you-go" method is an effective and safe technology for patients undergoing thoracoscopic pulmonary resection.

Loneliness Predicts Progression of Frailty in Married and Widowed, but Not Unmarried Community Dwelling Older Adults

BACKGROUND

Loneliness is highly prevalent among older adults and is associated with frailty. Most studies consider loneliness in isolation without consideration for structural and functional measures of social relationships - and longitudinal studies are scarce.

OBJECTIVES

This study examined longitudinal associations between loneliness and frailty and analyzed how structural and functional social measures influence these associations.

DESIGN

Linear mixed effects models examined longitudinal associations between loneliness and frailty assessed with the frailty index (scale 0-100). Models were adjusted for baseline age, gender, education, depressive symptoms, global cognition, and structural (e.g., social network, marital status), and functional social measures (e.g., social, cognitive, and physical activity, and social support).

PARTICIPANTS

Loneliness and frailty data from 1,931 older adults without dementia at baseline from the Rush Memory and Aging Project were examined (mean age 79.6 ± 7.7 years, 74.9% female).

MEASUREMENTS

Baseline loneliness assessed by the de Jong Gierveld Loneliness Scale was the predictor of interest.

RESULTS

Frailty increased significantly over a mean follow-up period of 4.6 years. Effects of loneliness on frailty were modified by marital status. Loneliness predicted an additional accumulation of 0.37 and 0.34 deficits on the frailty index per year in married and widowed individuals respectively, compared to those who were not lonely (married: p=0.009, CI 0.09, 0.64; widowed: p=0.005, CI 0.1, 0.58). Loneliness did not predict frailty progression in unmarried individuals.

CONCLUSIONS

Loneliness predicts frailty progression, highlighting the importance of social determinants on physical health in aging.

Global Burden of Alzheimer's Disease and Other Dementias Attributed to High Fasting Plasma Glucose from 1990 to 2019

BACKGROUND

Burden of Alzheimer's disease (AD) and other dementias have grown rapidly over the decades, and high fasting plasma glucose (HFPG) was one of the well-established risk factors. It is urgently needed to estimate the global burden of AD and other dementias attributable to high fasting plasma glucose between regions, countries, age groups, and sexes to inform development of effective primary disease prevention strategies and intervention policies.

METHODS

The burden of AD and other dementias attributable to HFPG was estimated based on a modeling strategy using the Global Burden of Disease Study 2019 dataset. The disease burden and time trend globally and by region, country, development level, age group, and sex were evaluated.

RESULTS

The number of AD and other dementias-related deaths attributable to HFPG increased from 42,998.23 (95% uncertainty interval, UI: 4459.86-163,455.78, the year of 1990) to 159,244.53 deaths (95% UI 18,385.23-583,514.15, the year of 2019). The age-standardized death rate increased from 1.69 (95% UI 0.18-6.54) in 1990 to 2.24 (95% UI 0.26-8.24) in 2019. The burden was higher in more developed regions. The burden in women was double that in men, that HFPG-attributable AD and other dementias caused 99,812.79 deaths (95% UI 9005.67-387,160.60) in women and 59,431.74 deaths (95% UI 5439.02-214,819.23) in men, with age-standardized death rate of 2.27 (95% UI 0.20-8.79) per 100,000 population in women and 2.20 (95% UI 0.20-8.00) in men.

CONCLUSION

Findings from the current study emphasizes the urgent requirement for targeted interventions in high-development regions, as well as the importance of proactive measures in middle-development countries in protection of AD and other dementias. The gender disparity necessitates the integration of gender-specific considerations in targeted approaches in prevention of AD and other dementias.

A prospective study of drug-drug interaction between antiepileptic drugs and meropenem in patients in a tertiary hospital in China from January 2020 to March 2023

OBJECTIVE

This study aimed to determine the minimum interaction between different antiepileptic drugs (AEDs) and meropenem (MEPM) for clinical treatment.

PATIENTS AND METHODS

The data of 91 patients enrolled in the neurology department from January 2020 to March 2023 for clinical trials were measured and observed. Self-controlled studies were conducted to monitor the trough concentrations of valproic acid (VPA), carbamazepine (CBZ) and levotiracetam (LEV) before and after MEPM usage. Relevant indicators of liver and kidney function were also monitored.

RESULTS

The serum VPA trough concentrations were 36.25±8.22 μg/ml at 24±12 h and 34.99±11.17 μg/ml at 96±12 h after MEPM use; the difference was significant (p<0.05). Decreased CBZ trough concentrations were also identified after MEPM usage (96±12 h), whereas LEV trough concentrations were not affected. An increased liver injury rate (χ2 =8.744, p<0.05) and a decreased kidney injury rate (χ2 =5.393, p<0.05) were found in the VPA group only.

CONCLUSIONS

The interaction between VPA and MEPM decreased serum VPA concentrations, increased liver injury rates, and decreased kidney injury rates. In addition, the co-administration of MEPM and CBZ reduced serum CBZ concentrations. Clinicians should be aware of this potential interaction and closely monitor the relevant biochemical indices and number of seizures.

[Research progress of bariatric and metabolic surgery in the prevention of gastroesophageal reflux disease]

Gastroesophageal reflux disease (GERD) is a common digestive tract disease. Obesity is an independent risk factor for GERD. Laparoscopic sleeve gastrectomy (laparoscopic sleeve gastrectomy, LSG) is becoming more popular in bariatric metabolic surgery and is simple to perform with fewer complications, but its efficacy in treating postoperative anti-reflux in obese patients remains controversial. LSG has been reported to disrupt anti-reflux barrier function, such as altered cardiac notch, disruption of diaphragmatic continuity, and increased hiatal hernia after surgery. The cardiac notch is one of the important anti-reflux barriers at the gastroesophageal junction, and its accentuation has been shown to be effective in alleviating the symptoms of GERD, and LSG combined with angle of cardiac notch accentuation is expected to be an effective measure to prevent GERD after obesity surgery. Therefore, this article mainly reviews the research on the prevention of GERD by bariatric surgery, aiming to explore the effective treatment of GERD in obese patients after surgery, so as to improve the symptoms and quality of life of patients with GERD, and provide reference for the surgical treatment of GERD.

Test of CP Symmetry in Hyperon to Neutron Decays

The quantum entangled J/ψ→Σ^{+}Σ[over ¯]^{-} pairs from (1.0087±0.0044)×10^{10}  J/ψ events taken by the BESIII detector are used to study the nonleptonic two-body weak decays Σ^{+}→nπ^{+} and Σ[over ¯]^{-}→n[over ¯]π^{-}. The CP-odd weak decay parameters of the decays Σ^{+}→nπ^{+} (α_{+}) and Σ[over ¯]^{-}→n[over ¯]π^{-} (α[over ¯]_{-}) are determined to be 0.0481±0.0031_{stat}±0.0019_{syst} and -0.0565±0.0047_{stat}±0.0022_{syst}, respectively. The decay parameter α[over ¯]_{-} is measured for the first time, and the accuracy of α_{+} is improved by a factor of 4 compared to the previous results. The simultaneously determined decay parameters allow the first precision CP symmetry test for any hyperon decay with a neutron in the final state with the measurement of A_{CP}=(α_{+}+α[over ¯]_{-})/(α_{+}-α[over ¯]_{-})=-0.080±0.052_{stat}±0.028_{syst}. Assuming CP conservation, the average decay parameter is determined as ⟨α_{+}⟩=(α_{+}-α[over ¯]_{-})/2=-0.0506±0.0026_{stat}±0.0019_{syst}, while the ratios α_{+}/α_{0} and α[over ¯]_{-}/α[over ¯]_{0} are -0.0490±0.0032_{stat}±0.0021_{syst} and -0.0571±0.0053_{stat}±0.0032_{syst}, where α_{0} and α[over ¯]_{0} are the decay parameters of the decays Σ^{+}→pπ^{0} and Σ[over ¯]^{-}→p[over ¯]π^{0}, respectively.

Measurement of Energy-Dependent Pair-Production Cross Section and Electromagnetic Form Factors of a Charmed Baryon

We study the process e^{+}e^{-}→Λ_{c}^{+}Λ[over ¯]_{c}^{-} at twelve center-of-mass energies from 4.6119 to 4.9509 GeV using data samples collected by the BESIII detector at the BEPCII collider. The Born cross sections and effective form factors (|G_{eff}|) are determined with unprecedented precision after combining the single and double-tag methods based on the decay process Λ_{c}^{+}→pK^{-}π^{+}. Flat cross sections around 4.63 GeV are obtained and no indication of the resonant structure Y(4630), as reported by Belle, is found. In addition, no oscillatory behavior is discerned in the |G_{eff}| energy dependence of Λ_{c}^{+}, in contrast to what is seen for the proton and neutron cases. Analyzing the cross section together with the polar-angle distribution of the Λ_{c}^{+} baryon at each energy point, the moduli of electric and magnetic form factors (|G_{E}| and |G_{M}|) are extracted and separated. For the first time, the energy dependence of the form factor ratio |G_{E}/G_{M}| is observed, which can be well described by an oscillatory function.

Tests of Light-Lepton Universality in Angular Asymmetries of B^{0}→D^{*-}ℓν Decays

We present the first comprehensive tests of the universality of the light leptons in the angular distributions of semileptonic B^{0}-meson decays to charged spin-1 charmed mesons. We measure five angular-asymmetry observables as functions of the decay recoil that are sensitive to lepton-universality-violating contributions. We use events where one neutral B is fully reconstructed in ϒ(4S)→BB[over ¯] decays in data corresponding to 189  fb^{-1} integrated luminosity from electron-positron collisions collected with the Belle II detector. We find no significant deviation from the standard model expectations.

Precise Measurement of the D_{s}^{+} Lifetime at Belle II

We measure the lifetime of the D_{s}^{+} meson using a data sample of 207  fb^{-1} collected by the Belle II experiment running at the SuperKEKB asymmetric-energy e^{+}e^{-} collider. The lifetime is determined by fitting the decay-time distribution of a sample of 116×10^{3} D_{s}^{+}→ϕπ^{+} decays. Our result is τ_{D_{s}^{+}}=(499.5±1.7±0.9)  fs, where the first uncertainty is statistical and the second is systematic. This result is significantly more precise than previous measurements.

[Research advances in imaging techniques related to the diagnosis of pneumoconiosis]

Occupational pneumoconiosis (hereinafter referred to as pneumoconiosis) is the most harmful occupational disease in China. According to the current standard GBZ 70-2015 Diagnosis of Occupational Pneumoconiosis, pneumoconiosis is mainly diagnosed and staged by high kilovolt or digital radiography. Chest radiography in pneumoconiosis is the most widely studied and mature imaging technique in the diagnosis of pneumoconiosis. However, this technique has some limitations in the screening of some early pneumoconiosis and occupational health examination, and there is a certain risk of missed diagnosis and misdiagnosis. With the continuous development of imaging examination technology, computed tomography, magnetic resonance imaging, positron emission tomography-computed tomography and artificial intelligence technology as auxiliary imaging examination methods have shown different diagnostic values in the research of auxiliary diagnosis of pneumoconiosis. This paper summarizes the advantages and problems in the application of various kinds of imaging techniques, which provides a direction for the future research of imaging techniques related to the diagnosis of pneumoconiosis.

Determination of Spin-Parity Quantum Numbers for the Narrow Structure near the pΛ[over ¯] Threshold in e^{+}e^{-}→pK^{-}Λ[over ¯]+c.c

A narrow structure in the pΛ[over ¯] system near the mass threshold, named as X(2085), is observed in the process e^{+}e^{-}→pK^{-}Λ[over ¯] with a statistical significance greater than 20σ. Its spin and parity are determined for the first time to be J^{P}=1^{+} in an amplitude analysis, with a statistical significance greater than 5σ over other quantum numbers (0^{-},1^{-} and 2^{+}). The pole positions of X(2085) are measured to be M_{pole}=(2084_{-2}^{+4}±9)  MeV and Γ_{pole}=(58_{-3}^{+4}±25)  MeV, where the first uncertainties are statistical and the second ones are systematic. The analysis is based on the study of the process e^{+}e^{-}→pK^{-}Λ[over ¯] and uses the data samples collected with the BESIII detector at the center-of-mass energies sqrt[s]=4.008, 4.178, 4.226, 4.258, 4.416, and 4.682 GeV with a total integrated luminosity of 8.35  fb^{-1}.

Precise Measurement of the e^{+}e^{-}→D_{s}^{*+}D_{s}^{*-} Cross Sections at Center-of-Mass Energies from Threshold to 4.95 GeV

The process e^{+}e^{-}→D_{s}^{*+}D_{s}^{*-} is studied with a semi-inclusive method using data samples at center-of-mass energies from threshold to 4.95 GeV collected with the BESIII detector operating at the Beijing Electron Positron Collider. The Born cross sections of the process are measured for the first time with high precision in this energy region. Two resonance structures are observed in the energy-dependent cross sections around 4.2 and 4.4 GeV. By fitting the cross sections with a coherent sum of three Breit-Wigner amplitudes and one phase-space amplitude, the two significant structures are assigned masses of (4186.8±8.7±30) and (4414.6±3.4±6.1)  MeV/c^{2}, widths of (55±15±53) and (122.5±7.5±8.1)  MeV, where the first errors are statistical and the second ones are systematic. The inclusion of a third Breit-Wigner amplitude is necessary to describe a structure around 4.79 GeV.

[Epidemic trends and predictive analysis of other infectious diarrhea in Jiangxi Province, 2017-2022]

Objective: To analyze epidemic trends of other infectious diarrhea in Jiangxi Province from 2017 to 2022, and explore the application of autoregressive integrated moving average (ARIMA) model in the prediction of the incidence of other infectious diarrhea in Jiangxi Province, providing reference for the prediction and prevention and control of other infectious diarrhea. Methods: To conduct a descriptive epidemiological analysis of other infectious diarrhea cases in Jiangxi Province from 2017 to 2022, and establish an ARIMA model to predict the number of other infectious diarrhea cases in 2023. Results: From 2017 to 2022, Jiangxi Province reported 204 842 cases of other infectious diarrhea. The annual average reported incidence rate was 74.32/100 000. The cases were reported in each age group with obvious seasonal characteristics of the main peak. There were two peak periods of incidence in winter and spring (from January to March) and in summer and autumn (from July to September) and the peak value was higher in winter and spring. All parameters of the model ARIMA (0,1,2)(2,1,0)12 and ARIMA (1,0,0)(2,1,0)12 were statistically significant (P<0.05), and the minimum values of Bayesian information criterion were 13.83 and 9.12, respectively. The residual series were all white noise (P>0.05); The predicted value of the model is in good agreement with the actual value, and the predicted trend is consistent with the actual trend. The model has a good prediction effect. Conclusions: The other infectious diarrhea occurred in 2017-2022 was still the first case of notifiable disease in Jiangxi Province. The prevention and control situation cannot be ignored. Disease monitoring and health education for families of children under 3 years of age and scattered children among key populations for prevention and control should be strengthened during the epidemic season. The ARIMA model can be used for short-term prediction and trend analysis of other infectious diarrhea outbreaks in Jiangxi Province.

First Experimental Study of the Purely Leptonic Decay D_{s}^{*+}→e^{+}ν_{e}

Using 7.33  fb^{-1} of e^{+}e^{-} collision data taken with the BESIII detector at the BEPCII collider, we report the first experimental study of the purely leptonic decay D_{s}^{*+}→e^{+}ν_{e}. Our data contain a signal of this decay with a statistical significance of 2.9σ. The branching fraction of D_{s}^{*+}→e^{+}ν_{e} is measured to be (2.1_{-0.9_{stat}}^{+1.2}±0.2_{syst})×10^{-5}, corresponding to an upper limit of 4.0×10^{-5} at the 90% confidence level. Taking the total width of the D_{s}^{*+} [(0.070±0.028)  keV] predicted with the radiative D_{s}^{*+} decay from the lattice QCD calculation as input, the decay constant of the D_{s}^{*+} is determined to be f_{D_{s}^{*+}}=(214_{-46_{stat}}^{+61}±44_{syst})  MeV, corresponding to an upper limit of 354 MeV at the 90% confidence level.

Global, regional, and national incidence of six major immune-mediated inflammatory diseases: findings from the global burden of disease study 2019

Background

The causes for immune-mediated inflammatory diseases (IMIDs) are diverse and the incidence trends of IMIDs from specific causes are rarely studied. The study aims to investigate the pattern and trend of IMIDs from 1990 to 2019.

Methods

We collected detailed information on six major causes of IMIDs, including asthma, inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, psoriasis, and atopic dermatitis, between 1990 and 2019, derived from the Global Burden of Disease study in 2019. The average annual percent change (AAPC) in number of incidents and age standardized incidence rate (ASR) on IMIDs, by sex, age, region, and causes, were calculated to quantify the temporal trends.

Findings

In 2019, rheumatoid arthritis, atopic dermatitis, asthma, multiple sclerosis, psoriasis, inflammatory bowel disease accounted 1.59%, 36.17%, 54.71%, 0.09%, 6.84%, 0.60% of overall new IMIDs cases, respectively. The ASR of IMIDs showed substantial regional and global variation with the highest in High SDI region, High-income North America, and United States of America. Throughout human lifespan, the age distribution of incident cases from six IMIDs was quite different. Globally, incident cases of IMIDs increased with an AAPC of 0.68 and the ASR decreased with an AAPC of -0.34 from 1990 to 2019. The incident cases increased across six IMIDs, the ASR of rheumatoid arthritis increased (0.21, 95% CI 0.18, 0.25), while the ASR of asthma (AAPC = -0.41), inflammatory bowel disease (AAPC = -0.72), multiple sclerosis (AAPC = -0.26), psoriasis (AAPC = -0.77), and atopic dermatitis (AAPC = -0.15) decreased. The ASR of overall and six individual IMID increased with SDI at regional and global level. Countries with higher ASR in 1990 experienced a more rapid decrease in ASR.

Interpretation

The incidence patterns of IMIDs varied considerably across the world. Innovative prevention and integrative management strategy are urgently needed to mitigate the increasing ASR of rheumatoid arthritis and upsurging new cases of other five IMIDs, respectively.

Funding

The Global Burden of Disease Study is funded by the Bill and Melinda Gates Foundation. The project funded by Scientific Research Fund of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital (2022QN38).

Image-Guided Superficial Radiation Therapy Has Superior 2-Year Recurrence Rates to Mohs Micrographic Surgery

PURPOSE/OBJECTIVE(S)

Non-melanoma skin cancers (NMSCs) are the most common malignancy in the USA, and incidence is rising. Mohs micrographic surgery (MMS) is a tissue-sparing surgical technique often used in NMSCs. Superficial radiation therapy (SRT) was widely used prior to the advent of MMS, but MMS has superior recurrence rates and replaced SRT as a first-line therapy. Image-guided SRT (IGSRT) was invented in 2015 and utilizes ultrasound to improve SRT precision and produces minimal side effects (99% grade 1 or 2).[1] The hypothesis is that NMSCs treated with IGSRT will have improved 2-year recurrence rates of compared to those treated with Mohs micrographic surgery.

MATERIALS/METHODS

This retrospective cohort study compared the 2-year recurrence probability of early stage NMSCs (squamous and basal cell carcinomas (SCCs and BCCs)) treated by IGSRT (2,286 lesions) to data on NMSCs treated by MMS (5,391 lesions) via one sample proportion tests. IGSRT-treated NMSC data is from a database published by Yu et al.[1] The 2-year recurrence probability statistical analysis is from McClure et al.[2] Medical Subject Headings were used to search PubMed for reports of 2-year recurrence rates of NMSCs treated by MMS. Seventeen studies were screened; 14 studies were excluded for lack of 2-year time to event analysis, or irrelevant patient population (non-BCC/SCC study, advanced disease), leaving 3 studies for comparison.

RESULTS

IGSRT-treated NMSCs have a statistically significantly improved 2-year recurrence rates compared to MMS-treated (p<0.001 for pooled data). When separated by histology, 2-year recurrence rates of all reported SCCs and BCCs treated by MMS were also inferior to those treated by IGSRT, p<0.001, p = 0.0218, respectively.

CONCLUSION

In this analysis, IGSRT has superior 2-year recurrence rates. Limitations include insufficient follow-up to report on the 5-year recurrence probability and inability to adjust for confounding factors beyond histology. This data implies that IGSRT is a well-tolerated, paradigm-shifting treatment option for patients with early stage NMSCs who cannot tolerate or refuse surgery. IGSRT provides patients the choice of treatment modality that best aligns with their goals of care.

Target Volumes Comparison between Postoperative Simulation MRI and Preoperative Diagnostic MRI for Prone Breast Radiotherapy after Breast-Conserving Surgery

PURPOSE/OBJECTIVE(S)

To investigate the correlation and difference between target volumes determined by postoperative prone positioning magnetic resonance imaging (MRI) and preoperative prone diagnostic MRI for breast radiotherapy after breast-conserving surgery (BCS) based on deformable image registration (DIR).

MATERIALS/METHODS

A total of 17 patients undergoing prone whole breast-irradiation after BCS were enrolled, all these patients were undergoing preoperative and postoperative prone MRI scans. The gross tumor volume (GTV) was delineated on the preoperative MRI images, then expanding 10 mm to simulate the preoperative lumpectomy cavity (LC). The LC were expended to clinical target volume (CTV), and planning target volume (PTV) on preoperative and postoperative MRI sequences, respectively. Preoperative and postoperative MRI was registered based on DIR by a commercially available software system. The target volume, the distance between the centers of mass (dCOM), conformity index (CI), degree of inclusion (DI) were compared to explore the target volume variation for pre- and post-surgery delineation. And evaluated the relationship between CILC/CIPTV and clinical factors.

RESULTS

The volume of GTVpre was 3.05cm3(range, 1-23.63cm3). The median volume of LCpre were 26.84 cm3 (range, 11.75-102.28 cm3). 0.85cm3 smaller than the LCpre, the LCpost were 25.99 cm3 (range, 5.98-41.95) (P = 0.04). The dCOM, CI, and DI between LCpre and LCpost were 1.371cm (range, 0.533-5.447), 0.221 (range, 0.041-0.516), and 0.472 (range, 0.108-0.804). There was no significant statistically difference between PTVpre and PTVpost (120.73cm3 vs 131.67cm3, p = 0.723). Compared with LC, the CI and DI between PTVpre and PTVpost were increased to 0.446 (range, 0.233-0.700), 0.636 (range, 0.362-0.834), respectively. Meanwhile, the dCOM was reduced to 1.239cm (range, 0.413-3.642). There was no obvious linear correlation between the CI with the GTV volume, the ratio of the primary tumor volume to the breast volume, the distance from the primary tumor to the nipple and chest wall, and the Body Mass Index (BMI), respectively.

CONCLUSION

For prone breast irradiation, even based on DIR, the spatial correspondence of the target volumes between preoperative and postoperative MRI images were still poor. Therefore, it is not reasonable to delineate postoperative LC refer to preoperative diagnostic MRI based on DIR. Preoperative MRI also cannot provide individualized guidance for LC delineation according to tailored patient.

[Value of postoperative radiotherapy and analysis of prognostic factors in early-stage neuroendocrine carcinoma of cervix]

Objective: To evaluate the effect of postoperative radiotherapy and high-risk pathological factors on the prognosis of early-stage neuroendocrine carcinoma of cervix (NECC). Methods: A single-center retrospective cohort study of early-stage NECC in Peking Union Medical College Hospital from January 2011 to April 2022 were enrolled. The patients were treated with radical hysterectomy±adjuvant treatment. They were divided into postoperative non-radiation group and postoperative radiation group. The possible postoperative recurrence risk factors identified by univariate analysis were assessed using multivariate logistic regression. The Kaplan-Meier method was used to analyze the progression free survival (PFS), overall survival (OS), recurrence rate, and mortality rate. Results: (1) Sixty-two cases were included in the study, including 33 cases in postoperative non-radiation group and 29 cases in postoperative radiation group. (2) The median follow-up time was 37 months (ranged 12-116 months), with 23 cases (37%) experienced recurrences. There were 7 cases (11%) pelvic recurrences and 20 cases (32%) distant recurrences, in which including 4 cases (6%) both pelvic and distant recurrences. Compared with postoperative non-radiation group, the postoperative radiation group had a lower pelvic recurrence rate (18% vs 3%; P=0.074) but without statistic difference, a slightly elevated distant recurrence rate (24% vs 41%; P=0.150) and overall recurrence rate (33% vs 41%; P=0.513) without statistically significances. Univariate analysis showed that lymph-vascular space invasion and the depth of cervical stromal invasion≥1/2 were risk factors for postoperative recurrence (all P<0.05). Multivariate analysis showed lymph-vascular space invasion was an independent predictor for postoperative recurrence (OR=23.03, 95%CI: 3.55-149.39, P=0.001). (3) During the follow-up period, 18 cases (29%, 18/62) died with tumor, with 10 cases (30%, 10/33) in postoperative non-radiation group and 8 cases (28%, 8/29) in postoperative radiation group, without significant difference (P=0.814). The postoperative 3-year and 5-year survival rate was 79.2%, 60.8%. The depth of cervical stromal invasion≥1/2 was more common in postoperative radiation group (27% vs 64%; P=0.011), and postoperative radiation in such patients showed an extended trend in PFS (32.3 vs 53.9 months) and OS (39.4 vs 73.4 months) but without statistic differences (P=0.704, P=0.371). Compared with postoperative non-radiation group, the postoperative radiation did not improve PFS (54.5 vs 37.3 months; P=0.860) and OS (56.2 vs 62.4 months; P=0.550) in patients with lymph-vascular space invasion. Conclusions: Postoperative radiation in early-stage NECC patients has a trend to reduce pelvic recurrence but not appear to decrease distant recurrence and overall recurrence, and has not improved mortality. For patients with the depth of cervical stromal invasion≥1/2, postoperative radiation has a trend of prolonging OS and PFS but without statistic difference. Lymph-vascular space invasion is an independent predictor for postoperative recurrence, but postoperative radiation in such patients does not seem to have any survival benefits.

Search for Λ[over ¯]-Λ Baryon-Number-Violating Oscillations in the Decay J/ψ→pK^{-}Λ[over ¯]+c.c

We report on the first search for Λ[over ¯]-Λ oscillations in the decay J/ψ→pK^{-}Λ[over ¯]+c.c. by analyzing 1.31×10^{9}  J/ψ events accumulated with the BESIII detector at the BEPCII collider. The J/ψ events are produced using e^{+}e^{-} collisions at a center of mass energy sqrt[s]=3.097  GeV. No evidence for hyperon oscillations is observed. The upper limit for the oscillation rate of Λ[over ¯] to Λ hyperons is determined to be P(Λ)=[B(J/ψ→pK^{-}Λ+c.c.)/B(J/ψ→pK^{-}Λ[over ¯]+c.c.)]<4.4×10^{-6} corresponding to an oscillation parameter δm_{ΛΛ[over ¯]} of less than 3.8×10^{-18}  GeV at the 90% confidence level.

Search for a τ^{+}τ^{-} Resonance in e^{+}e^{-}→μ^{+}μ^{-}τ^{+}τ^{-} Events with the Belle II Experiment

We report the first search for a nonstandard-model resonance decaying into τ pairs in e^{+}e^{-}→μ^{+}μ^{-}τ^{+}τ^{-} events in the 3.6-10  GeV/c^{2} mass range. We use a 62.8  fb^{-1} sample of e^{+}e^{-} collisions collected at a center-of-mass energy of 10.58 GeV by the Belle II experiment at the SuperKEKB collider. The analysis probes three different models predicting a spin-1 particle coupling only to the heavier lepton families, a Higgs-like spin-0 particle that couples preferentially to charged leptons (leptophilic scalar), and an axionlike particle, respectively. We observe no evidence for a signal and set exclusion limits at 90% confidence level on the product of cross section and branching fraction into τ pairs, ranging from 0.7 to 24 fb, and on the couplings of these processes. We obtain world-leading constraints on the couplings for the leptophilic scalar model for masses above 6.5  GeV/c^{2} and for the axionlike particle model over the entire mass range.

Measurement of CP Violation in B^{0}→K_{S}^{0}π^{0} Decays at Belle II

We report a measurement of the CP-violating parameters C and S in B^{0}→K_{S}^{0}π^{0} decays at Belle II using a sample of 387×10^{6}  BB[over ¯] events recorded in e^{+}e^{-} collisions at a center-of-mass energy corresponding to the ϒ(4S) resonance. These parameters are determined by fitting the proper decay-time distribution of a sample of 415 signal events. We obtain C=-0.04_{-0.15}^{+0.14}±0.05 and S=0.75_{-0.23}^{+0.20}±0.04, where the first uncertainties are statistical and the second are systematic.

Racial differences in healthcare utilization among patients with suspected or diagnosed preeclampsia: A retrospective cohort study

OBJECTIVES

To analyze healthcare resource utilization and severe maternal morbidity (SMM) in Black and White patients with preeclampsia diagnosis versus signs/symptoms.

STUDY DESIGN

This was a retrospective cohort study analyzing data from the IBM® Explorys Database between 7/31/2012-12/31/2020. Demographic, clinical, and laboratory data were extracted. Healthcare utilization and SMM were analyzed during the antepartum period (20 weeks of gestation until delivery) among Black and White patients with signs/symptoms of preeclampsia, with a diagnosis of preeclampsia, or neither (control).

MAIN OUTCOME MEASURES

Healthcare utilization and SMM in those with a preeclampsia diagnosis or signs/symptoms of preeclampsia only were compared with a control group (White patients with no preeclampsia diagnosis or signs/symptoms).

RESULTS

Data from 38,190 Black and 248,568 White patients were analyzed. Patients with preeclampsia diagnosis or signs/symptoms were more likely to visit the emergency room compared to those without diagnosis or signs/symptoms. Black patients with signs/symptoms of preeclampsia had the highest elevated risk (odds ratio [OR] = 3.4), followed by Black patients with a preeclampsia diagnosis (OR = 3.2), White patients with signs/symptoms (OR = 2.2), and White patients with a preeclampsia diagnosis (OR = 1.8). More Black patients experienced SMM (SMM rate 6.1% [Black with preeclampsia diagnosis] and 2.6% [Black with signs/symptoms]) than White patients (5.0% [White with preeclampsia diagnosis] and 2.0% [White with signs/symptoms]). SMM rates were higher for Black preeclampsia patients with severe features than for White preeclampsia patients with severe features (8.9% vs 7.3%).

CONCLUSIONS

Compared with White patients, Black patients had higher rates of antepartum emergency care and antepartum SMM.