Scalable Video Object Segmentation With Identification Mechanism

This paper delves into the challenges of achieving scalable and effective multi-object modeling for semi-supervised Video Object Segmentation (VOS). Previous VOS methods decode features with a single positive object, limiting the learning of multi-object representation as they must match and segment each target separately under multi-object scenarios. Additionally, earlier techniques catered to specific application objectives and lacked the flexibility to fulfill different speed-accuracy requirements. To address these problems, we present two innovative approaches, Associating Objects with Transformers (AOT) and Associating Objects with Scalable Transformers (AOST). In pursuing effective multi-object modeling, AOT introduces the IDentification (ID) mechanism to allocate each object a unique identity. This approach enables the network to model the associations among all objects simultaneously, thus facilitating the tracking and segmentation of objects in a single network pass. To address the challenge of inflexible deployment, AOST further integrates scalable long short-term transformers that incorporate scalable supervision and layer-wise ID-based attention. This enables online architecture scalability in VOS for the first time and overcomes ID embeddings' representation limitations. Given the absence of a benchmark for VOS involving densely multi-object annotations, we propose a challenging Video Object Segmentation in the Wild (VOSW) benchmark to validate our approaches. We evaluated various AOT and AOST variants using extensive experiments across VOSW and five commonly used VOS benchmarks, including YouTube-VOS 2018 & 2019 Val, DAVIS-2017 Val & Test, and DAVIS-2016. Our approaches surpass the state-of-the-art competitors and display exceptional efficiency and scalability consistently across all six benchmarks. Moreover, we notably achieved the 1st position in the 3 rd Large-scale Video Object Segmentation Challenge. Project page: https://github.com/yoxu515/aot-benchmark.

Baseline Uric Acid Levels and Intravenous Thrombolysis Outcomes in Patients With Acute Ischemic Stroke: A Prospective Cohort Study

BACKGROUND

The study aimed to investigate the relationship between uric acid (UA) levels and functional outcomes at 3 months in patients with acute ischemic stroke (AIS) who underwent intravenous thrombolysis (IVT).

METHODS AND RESULTS

This prospective cohort study included 1001 consecutive patients with AIS who underwent IVT. The correlation between UA levels and post-IVT AIS outcomes was examined. Any nonlinear relationship was assessed using a restricted cubic spline function. The nonlinear P value for the association of UA levels with favorable (modified Rankin Scale [mRS] score ≤2) and excellent (mRS score ≤1) outcomes at 3 months post-IVT were <0.001 and 0.001, respectively. However, for patients with and without hyperuricemia, no evident nonlinear relationship was observed between UA levels and favorable 3-month post-IVT outcomes, with nonlinear P values of 0.299 and 0.207, respectively. The corresponding interaction analysis yielded a P value of 0.001, indicating significant heterogeneity. Similar results were obtained for excellent outcomes at 3 months post-IVT. In the hyperuricemia group, increased UA levels by 50 μmol/L reduced the odds of a favorable 3-month post-AIS outcome (odds ratio [OR], 0.75 [95% CI, 0.57-0.97]). Conversely, in the nonhyperuricemia group, a similar UA increase was linked to higher favorable outcome odds (OR, 1.31 [95% CI, 1.15-1.50]).

CONCLUSIONS

An inverted U-shaped nonlinear relationship was observed between UA levels and favorable and excellent outcomes at 3 months in patients with AIS who underwent IVT. Higher UA levels predict favorable outcomes in patients without hyperuricemia but unfavorable outcomes in those with hyperuricemia.

Medical long-tailed learning for imbalanced data: Bibliometric analysis

BACKGROUND

In the last decade, long-tail learning has become a popular research focus in deep learning applications in medicine. However, no scientometric reports have provided a systematic overview of this scientific field. We utilized bibliometric techniques to identify and analyze the literature on long-tailed learning in deep learning applications in medicine and investigate research trends, core authors, and core journals. We expanded our understanding of the primary components and principal methodologies of long-tail learning research in the medical field.

METHODS

Web of Science was utilized to collect all articles on long-tailed learning in medicine published until December 2023. The suitability of all retrieved titles and abstracts was evaluated. For bibliometric analysis, all numerical data were extracted. CiteSpace was used to create clustered and visual knowledge graphs based on keywords.

RESULTS

A total of 579 articles met the evaluation criteria. Over the last decade, the annual number of publications and citation frequency both showed significant growth, following a power-law and exponential trend, respectively. Noteworthy contributors to this field include Husanbir Singh Pannu, Fadi Thabtah, and Talha Mahboob Alam, while leading journals such as IEEE ACCESS, COMPUTERS IN BIOLOGY AND MEDICINE, IEEE TRANSACTIONS ON MEDICAL IMAGING, and COMPUTERIZED MEDICAL IMAGING AND GRAPHICS have emerged as pivotal platforms for disseminating research in this area. The core of long-tailed learning research within the medical domain is encapsulated in six principal themes: deep learning for imbalanced data, model optimization, neural networks in image analysis, data imbalance in health records, CNN in diagnostics and risk assessment, and genetic information in disease mechanisms.

CONCLUSION

This study summarizes recent advancements in applying long-tail learning to deep learning in medicine through bibliometric analysis and visual knowledge graphs. It explains new trends, sources, core authors, journals, and research hotspots. Although this field has shown great promise in medical deep learning research, our findings will provide pertinent and valuable insights for future research and clinical practice.

Mortality associated with polymyalgia rheumatica in the United States in the 1999-2020 period: a multiple-cause-of-death study

OBJECTIVE

Multicause-of-death methods were used to analyze mortality and leading causes of death associated with polymyalgia rheumatica (PMR) in the United States from 1999 to 2020.

MATERIALS AND METHODS

We analyzed mortality data from the Centers for Disease Control and Prevention (CDC) Data analysis system and selected death certificates that listed PMR as the cause of death based on the International Statistical Classification of Diseases and Related Health Problems (ICD-10) category code. Relevant mortality rates, number of deaths and historical trends were analyzed. The number of PMR-related deaths and age-standardized mortality rate (ASMR) trend charts were made using Excel 2010 version and trend lines were added.

RESULTS

Over the last 22 years, the total number of PMR-related deaths in the United States was 15,421 women (89.8%), a ratio of about 1:9 men to women. When PMR is listed as the underlying cause of death, the ASMR for women and men (per 100,000 people) is approximately 1.8-5.1:1, and when it is listed as the non-underlying cause of death, it is 1.8-3.3:1. PMR deaths are more frequent in individuals aged 70 years and above, with patients aged 80 years and above being most affected. Among different ethnicities, the highest number of deaths was found in Caucasians, followed by Black or African American. When it comes to causes of death, heart disease still ranks first, followed by cancer. In addition, we also found that when PMR combined with malignant tumors as a multiple cause of death, the number of female deaths was higher than that of male deaths, the overall number of deaths of both showed an upward trend, and the overall ASMR of both showed a downward trend.

CONCLUSIONS

In the past 22 years, we have observed a low mortality rate of PMR in the United States. However, for patients with PMR, especially elderly women, medical workers should be vigilant and pay attention to whether they are combined with other complications, such as malignant neoplasms, and make timely diagnosis and treatment to further reduce the mortality rate of patients with PMR.

A host-microbiota interactome reveals extensive transkingdom connectivity

The myriad microorganisms that live in close association with humans have diverse effects on physiology, yet the molecular bases for these impacts remain mostly unknown1-3. Classical pathogens often invade host tissues and modulate immune responses through interactions with human extracellular and secreted proteins (the 'exoproteome'). Commensal microorganisms may also facilitate niche colonization and shape host biology by engaging host exoproteins; however, direct exoproteome-microbiota interactions remain largely unexplored. Here we developed and validated a novel technology, BASEHIT, that enables proteome-scale assessment of human exoproteome-microbiome interactions. Using BASEHIT, we interrogated more than 1.7 million potential interactions between 519 human-associated bacterial strains from diverse phylogenies and tissues of origin and 3,324 human exoproteins. The resulting interactome revealed an extensive network of transkingdom connectivity consisting of thousands of previously undescribed host-microorganism interactions involving 383 strains and 651 host proteins. Specific binding patterns within this network implied underlying biological logic; for example, conspecific strains exhibited shared exoprotein-binding patterns, and individual tissue isolates uniquely bound tissue-specific exoproteins. Furthermore, we observed dozens of unique and often strain-specific interactions with potential roles in niche colonization, tissue remodelling and immunomodulation, and found that strains with differing host interaction profiles had divergent interactions with host cells in vitro and effects on the host immune system in vivo. Overall, these studies expose a previously unexplored landscape of molecular-level host-microbiota interactions that may underlie causal effects of indigenous microorganisms on human health and disease.

Organo-Ptii Complexes for Potent Photodynamic Inactivation of Multi-Drug Resistant Bacteria and the Influence of Configuration

PtII based organometallic photosensitizers (PSs) have emerged as novel potent photodynamic inactivation (PDI) reagents through their enhanced intersystem crossing (ISC) processes. Currently, few PtII PSs have been investigated as antibacterial materials, with relatively poor performances reported and with structure-activity relationships not well described. Herein, a pair of configurational isomers are reported of Bis-BODIPY (4,4-difluoro-boradizaindacene) embedded PtII PSs. The cis-isomer (cis-BBP) displayed enhanced 1O2 generation and better bacterial membrane anchoring capability as compared to the trans-isomer (trans-BBP). The effective PDI concentrations (efficiency > 99.9%) for cis-BBP in Acinetobacter baumannii (multi-drug resistant (MDR)) and Staphylococcus aureus are 400 nM (12 J cm-2) and 100 nM (18 J cm-2), respectively; corresponding concentrations and light doses for trans-BBP in the two bacteria are 2.50 µM (30 J cm-2) and 1.50 µM (18 J cm-2), respectively. The 50% and 90% minimum inhibitory concentration (MIC50 and MIC90) ratio of trans-BBP to cis-BBP is 22.22 and 24.02 in A. baumannii (MDR); 21.29 and 22.36 in methicillin resistant S. aureus (MRSA), respectively. Furthermore, cis-BBP displays superior in vivo antibacterial performance, with acceptable dark and photoinduced cytotoxicity. These results demonstrate cis-BBP is a robust light-assisted antibacterial reagent at sub-micromolecular concentrations. More importantly, configuration of PtII PSs should be an important issue to be considered in further PDI reagents design.

Efficient removal of tetracycline hydrochloride through novel Fe/BiOBr/Bi2WO6 photocatalyst prepared by dual-strategy under visible-light irradiation

It is important to investigate whether combining two modification strategies has a synergistic effect on the activity of photocatalysts. In this manuscript, Fe-doped BiOBr/Bi2WO6 heterojunctions were synthesized by a one-pot solvothermal method, and excellent photocatalytic performance was obtained for the degradation of tetracycline hydrochloride (TCH) in water without the addition of surfactant. Combining experiments and characterization, the synergistic effect between Fe ion doping and the BiOBr/Bi2WO6 heterojunction was elucidated. The Fe/BiOBr/Bi2WO6 composite photocatalyst had a beneficial void structure, enhanced visible light response, and could inhibit the recombination of photogenerated support well, which improved the photocatalytic activity. The presented experiments demonstrate that Fe/BiOBr/Bi2WO6 removes 97% of TCH from aqueous solution, while pure BiOBr and Bi2WO6 only remove 56% and 65% of TCH, respectively. Finally, the separation and transfer mechanisms of photoexcited carriers were determined in conjunction with the experimental results. This study provides a new direction for the design of efficient photocatalysts through the use of a dual co-modification strategy.

Cost-Effectiveness Analysis of Sintilimab Plus Chemotherapy in Advanced Non-Squamous Non-Small Cell Lung Cancer: A Societal Perspective

INTRODUCTION

The updated ORIENT-11 study demonstrated that sintilimab, when combined with chemotherapy, had promising survival advantage compared to standard chemotherapy alone in the first-line treatment for previously untreated, locally advanced or metastatic non-squamous non-small cell lung cancer (nsNSCLC). This study aims to evaluate the cost-effectiveness of sintilimab plus chemotherapy for advanced nsNSCLC from a Chinese societal perspective.

METHODS

A partitioned survival model with a embedded decision tree was developed to assess the economic value of sintilimab plus chemotherapy over a lifetime horizon. Clinical data was captured from the updated ORIENT-11 study, while costs, health productivity losses, and utility values were collected from a nationwide cross-sectional survey in tertiary hospitals across multiple provinces in China. The primary outcomes were measured using the metrics of quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICER). Costs and health outcomes were discounted at an annual rate of 5% per annum. Sensitivity analyses, including one-way and probabilistic sensitivity analyses, subgroup analyses, and scenario analyses, were performed.

RESULTS

Compared to standard chemotherapy, treatment with sintilimab plus chemotherapy incurred a mean total cost of $23,979 and gained 0.98 QALYs over the lifetime horizon, resulting in an ICER of $24,568 per QALY gained. The use of sintilimab accumulated direct non-medical costs of $9262 and indirect costs of $6780 over 16 years. Probabilistic sensitivity analyses showed an 84.2% probability of sintilimab plus chemotherapy being cost-effective at a threshold of three times China's per capita gross domestic product in 2022 ($38,201). The model was most sensitive to the discount rate of QALYs and costs, as well as the costs of pemetrexed, sintilimab, and subsequent therapy in progressive disease state. Subgroup analyses indicated favorable incremental net monetary benefits in all subgroups.

CONCLUSION

Sintilimab plus chemotherapy is a cost-effective first-line treatment therapy for advanced nsNSCLC in China when compared to standard chemotherapy. These findings, along with the improved progression-free survival and overall survival (OS) observed in ORIENT-11, support the use of this regimen in eligible candidates for advanced nsNSCLC.

Association of Craniocervical Sagittal Alignment With the Outcomes of Cervical Disc Replacement

STUDY DESIGN

Retrospective cohort study.

OBJECTIVE

To explore the association between craniocervical sagittal balance and clinical and radiological outcomes of cervical disc replacement (CDR).

METHODS

Patients who underwent 1-level and 2-level CDR were retrospectively analyzed. Clinical outcomes were evaluated using scores on the Japanese Orthopaedic Association (JOA), Visual Analogue Scale (VAS), and Neck Disability Index (NDI). The craniocervical sagittal alignment parameters, including the C0-C2 Cobb angle, C2-C7 Cobb angle, C2 slope, T1 slope, C2-C7 sagittal vertical axis (SVA), C1-C7 SVA, the center of gravity of the head (CGH)-C7 SVA, and range of motion (ROM) at the surgical segments were measured.

RESULTS

A total of 169 patients were involved. Significantly lower pre- and postoperative C2 slope and CGH-C7 SVA were found in arthroplasty levels with better ROMs. Patients with a higher preoperative C2 slope and CGH-C7 SVA had lower cervical lordosis and ROM after surgery. There were no significant differences in the clinical outcomes between patients with different sagittal balance statuses. C2-C7 SVA and CGH-C7 SVA were significantly associated with radiographic adjacent segment pathology (rASP).

CONCLUSION

Craniocervical sagittal balance is associated with cervical lordosis and ROM at the index level after CDR. A higher preoperative SVA is related to the presence and progression of rASP. A relationship between sagittal alignment and clinical outcomes was not observed.

Application of 18F-FDG PET/CT imaging radiomics in the differential diagnosis of single-nodule pulmonary metastases and second primary lung cancer in patients with colorectal cancer

OBJECTIVE

It is crucially essential to differentially diagnose single-nodule pulmonary metastases (SNPMs) and second primary lung cancer (SPLC) in patients with colorectal cancer (CRC), which has important clinical implications for treatment strategies. In this study, we aimed to establish a feasible differential diagnosis model by combining 18F-fluorodeoxyglucose positron-emission tomography (18F-FDG PET) radiomics, computed tomography (CT) radiomics, and clinical features.

MATERIALS AND METHODS

CRC patients with SNPM or SPLC who underwent 18F-FDG PET/CT from January 2013 to July 2022 were enrolled in this retrospective study. The radiomic features were extracted by manually outlining the lesions on PET/CT images, and the radiomic modeling was realized by various screening methods and classifiers. In addition, clinical features were analyzed by univariate analysis and logistic regression (LR) analysis to be included in the combined model. Finally, the diagnostic performances of these models were illustrated by the receiver operating characteristic (ROC) curves and the area under the curve (AUC).

RESULTS

We studied data from 61 patients, including 36 SNPMs and 25 SPLCs, with an average age of 65.56 ± 10.355 years. Spicule sign and ground-glass opacity (GGO) were significant independent predictors of clinical features (P = 0.012 and P < 0.001, respectively) to build the clinical model. We achieved a PET radiomic model (AUC = 0.789), a CT radiomic model (AUC = 0.818), and a PET/CT radiomic model (AUC = 0.900). The PET/CT radiomic models were combined with the clinical model, and a well-performing model was established by LR analysis (AUC = 0.940).

CONCLUSIONS

For CRC patients, the radiomic models we developed had good performance for the differential diagnosis of SNPM and SPLC. The combination of radiomic and clinical features had better diagnostic value than a single model.

(-)-Asarinin alleviates gastric precancerous lesions by promoting mitochondrial ROS accumulation and inhibiting the STAT3 signaling pathway

BACKGROUND

(-)-Asarinin (Asarinin) is the primary component in the extract of the herb Asarum sieboldii Miq. It possesses various functions, including pain relief, anti-viral and anti-tuberculous bacilli effects, and inhibition of tumor growth. Gastric precancerous lesion (GPL) is a common but potentially carcinogenic chronic gastrointestinal disease, and its progression can lead to gastric dysfunction and cancer development. However, the protective effects of asarinin against GPL and the underlying mechanisms remain unexplored.

METHODS

A premalignant cell model (methylnitronitrosoguanidine-induced malignant transformation of human gastric epithelial cell strain, MC cells) and a GPL animal model were established and then were treated with asarinin. The cytotoxic effect of asarinin was assessed using a CCK8 assay. Detection of intracellular reactive oxygen species (ROS) using DCFH-DA. Apoptosis in MC cells was evaluated using an annexin V-FITC/PI assay. We performed western blot analysis and immunohistochemistry (IHC) to analyze relevant markers, investigating the in vitro and in vivo therapeutic effects of asarinin on GPL and its intrinsic mechanisms.

RESULTS

Our findings showed that asarinin inhibited MC cell proliferation, enhanced intracellular ROS levels, and induced cell apoptosis. Further investigations revealed that the pharmacological effects of asarinin on MC cells were blocked by the ROS scavenger N-acetylcysteine. IHC revealed a significant upregulation of phospho-signal transducer and activator of transcription 3 (p-STAT3) protein expression in human GPL tissues. In vitro, asarinin exerted its pro-apoptotic effects in MC cells by modulating the STAT3 signaling pathway. Agonists of STAT3 were able to abolish the effects of asarinin on MC cells. In vivo, asarinin induced ROS accumulation and inhibited the STAT3 pathway in gastric mucosa of mice, thereby halting and even reversing the development of GPL.

CONCLUSION

Asarinin induces apoptosis and delays the progression of GPL by promoting mitochondrial ROS production, decreasing mitochondrial membrane potential (MMP), and inhibiting the STAT3 pathway.

Undercoordination Chemistry of Sulfur Electrocatalyst in Lithium-Sulfur Batteries

Undercoordination chemistry is an effective strategy to modulate the geometry-governed electronic structure and thereby regulate the activity of sulfur electrocatalysts. Efficient sulfur electrocatalysis is requisite to overcome the sluggish kinetics in lithium-sulfur (Li-S) batteries aroused by multi-electron transfer and multi-phase conversions. Recent advances unveil the great promise of undercoordination chemistry in facilitating and stabilizing sulfur electrochemistry, yet a related review with systematicness and perspectives is still missing. Herein, it is carefully combed through the recent progress of undercoordination chemistry in sulfur electrocatalysis. The typical material structures and operational strategies are elaborated, while the underlying working mechanism is also detailly introduced and generalized into polysulfide adsorption behaviors, polysulfide conversion kinetics, electron/ion transport, and dynamic reconstruction. Moreover, perspectives on the future development of undercoordination chemistry are further proposed.

Anti-Fatigue Tandem Organic Photovoltaics for Indoor Illumination

The ability of achieving high efficiency makes tandem organic photovoltaics (PVs) a competitive technique in potential indoor applications. Except high efficiency, reliable indoor energy supply also calls for outstanding stability. However, unavoidable unstable voltage supply from the circuit control system for indoor light sources like light emitting diodes (LED) and incandescent lamps would cause carrier density fluctuation and device fatigue driven by periodic light/dark switching. In this work, the strobing-induced fatigue within the bulk heterojunction (BHJ)/interconnecting layer (ICL) interface is first revealed and overcome. Based on reliable and effective interfacial doping between conjugated acceptor and metal oxide, the interfacial capacitance that determines the strobing-induced fatigue, has been significantly restrained. The imbalance carrier migration and fierce inter-layer accommodating during the burn-in stage caused by light strobing are substantially diminished. Benefit from this method, the stability of tandem devices is highly enhanced under strobing indoor illumination, and a champion efficiency (35.02%) is obtained. The method provides guidance for further material design for interconnecting layers in organic photovoltaics.

DNA Methylation Analysis Reveals Potential Mechanism in Takifugu rubripes Against Cryptocaryon irritans Infection

Takifugu rubripes (T. rubripes) is a valuable commercial fish, and Cryptocaryon irritans (C. irritans) has a significant impact on its aquaculture productivity. DNA methylation is one of the earliest discovered ways of gene epigenetic modification and also an important form of modification, as well as an essential type of alteration that regulates gene expression, including immune response. To further explore the anti-infection mechanism of T. rubripes in inhibiting this disease, we determined genome-wide DNA methylation profiles in the gill of T. rubripes using whole-genome bisulfite sequencing (WGBS) and combined with RNA sequence (RNA-seq). A total of 4659 differentially methylated genes (DMGs) in the gene body and 1546 DMGs in the promoter between the infection and control group were identified. And we identified 2501 differentially expressed genes (DEGs), including 1100 upregulated and 1401 downregulated genes. After enrichment analysis, we identified DMGs and DEGs of immune-related pathways including MAPK, Wnt, ErbB, and VEGF signaling pathways, as well as node genes prkcb, myca, tp53, and map2k2a. Based on the RNA-Seq results, we plotted a network graph to demonstrate the relationship between immune pathways and functional related genes, in addition to gene methylation and expression levels. At the same time, we predicted the CpG island and transcription factor of four immune-related key genes prkcb and mapped the gene structure. These unique discoveries could be helpful in the understanding of C. irritans pathogenesis, and the candidate genes screened may serve as optimum methylation-based biomarkers that can be utilized for the correct diagnosis and therapy T. rubripes in the development of the ability to resist C. irritans infection.

Application of deep learning in radiation therapy for cancer

In recent years, with the development of artificial intelligence, deep learning has been gradually applied to clinical treatment and research. It has also found its way into the applications in radiotherapy, a crucial method for cancer treatment. This study summarizes the commonly used and latest deep learning algorithms (including transformer, and diffusion models), introduces the workflow of different radiotherapy, and illustrates the application of different algorithms in different radiotherapy modules, as well as the defects and challenges of deep learning in the field of radiotherapy, so as to provide some help for the development of automatic radiotherapy for cancer.

RPA-CRISPR/Cas9-based method for the detection of Toxoplasma gondii: A proof of concept

Toxoplasma gondii is a widespread and specialized intracellular protozoan pathogen that affects one third of the world' s population, posing a great threat to public health. As the definitive host, cats excrete oocysts and play a crucial role in the transmission of toxoplasmosis. The current diagnostic tools usually require bulky equipment and expertize, which hinders the efficient diagnosis and intervention of Toxoplasma infection in cats. In this study, we combined (RPA) with clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 technique to establish an easier method for the detection of T. gondii oocysts in cat fecal samples. The sensitivity, specificity, and practicability of the established RPA-CRISPR/Cas9 method were evaluated using a lateral flow strip, with the limitation of detection determined at 10 plasmid copies/μL (corresponding to about one oocyst), cross reactivity to none of Giardia lamblia, Cryptosporidium sp., Microsporidium biberi and Blastocystis hominis that also commonly found in cats, and comparable performance in detecting T. gondii in clinical samples to conventional PCR amplification. This RPA-CRISPR/Cas9 method provides an alternative to conventional molecular tools used in the clinical diagnosis of Toxoplasma infection in cats and other animals.

Shell buckling for programmable metafluids

The pursuit of materials with enhanced functionality has led to the emergence of metamaterials-artificially engineered materials whose properties are determined by their structure rather than composition. Traditionally, the building blocks of metamaterials are arranged in fixed positions within a lattice structure1-19. However, recent research has revealed the potential of mixing disconnected building blocks in a fluidic medium20-27. Inspired by these recent advances, here we show that by mixing highly deformable spherical capsules into an incompressible fluid, we can realize a 'metafluid' with programmable compressibility, optical behaviour and viscosity. First, we experimentally and numerically demonstrate that the buckling of the shells endows the fluid with a highly nonlinear behaviour. Subsequently, we harness this behaviour to develop smart robotic systems, highly tunable logic gates and optical elements with switchable characteristics. Finally, we demonstrate that the collapse of the shells upon buckling leads to a large increase in the suspension viscosity in the laminar regime. As such, the proposed metafluid provides a promising platform for enhancing the functionality of existing fluidic devices by expanding the capabilities of the fluid itself.

Effect of SIRT1 gene single-nucleotide polymorphisms on susceptibility to type 1 diabetes in a Han Chinese population

AIMS

SIRT1 deficiency has been associated with diabetes, and a variant of the SIRT1 gene has been found to be involved in human autoimmune diabetes; however, it is unclear whether this genetic variation exists in Han Chinese with type 1 diabetes (T1D) and whether it contributes to development of T1D. Therefore, we aimed to explore the association of the SIRT1 gene single-nucleotide polymorphisms (SNPs) rs10997866 and rs3818292 in a Han Chinese population with T1D.

METHODS

This study recruited 2653 unrelated Han Chinese individuals, of whom 1289 had T1D and 1364 were healthy controls. Allelic and genotypic distributions of SIRT1 polymorphisms (rs10997866 and rs3818292) were determined by MassARRAY. Basic characteristics, genotype and allele frequencies of selected SNPs were compared between the T1D patients and healthy controls. Further genotype-phenotype association analysis of the SNPs was performed on the T1D patients divided into three groups according to genotype. Statistical analyses included the chi-square test, Mann‒Whitney U test, Kruskal‒Wallis H test and logistic regression.

RESULTS

The allelic (G vs. A) and genotypic (GA vs. AA) distributions of SIRT1 rs10997866 were significantly different in T1D patients and healthy controls (P = 0.039, P = 0.027), and rs10997866 was associated with T1D susceptibility under dominant, overdominant and additive models (P = 0.026, P = 0.030 and P = 0.027, respectively). Moreover, genotype-phenotype association analysis showed the GG genotype of rs10997866 and the GG genotype of rs3818292 to be associated with higher titers of IA-2A (P = 0.013 and P = 0.038, respectively).

CONCLUSION

SIRT1 rs10997866 is significantly associated with T1D susceptibility, with the minor allele G conferring a higher risk of T1D. Moreover, SIRT1 gene rs10997866 and rs3818292 correlate with the titer of IA-2A in Han Chinese individuals with T1D.

[Clinical application of split liver transplantation: a single center report of 203 cases]

Objective: To investigate the safety and therapeutic effect of split liver transplantation (SLT) in clinical application. Methods: This is a retrospective case-series study. The clinical data of 203 consecutive SLT, 79 living donor liver transplantation (LDLT) and 1 298 whole liver transplantation (WLT) performed at the Third Affiliated Hospital of Sun Yat-sen University from July 2014 to July 2023 were retrospectively analyzed. Two hundred and three SLT liver grafts were obtained from 109 donors. One hundred and twenty-seven grafts were generated by in vitro splitting and 76 grafts were generated by in vivo splitting. There were 90 adult recipients and 113 pediatric recipients. According to time, SLT patients were divided into two groups: the early SLT group (40 cases, from July 2014 to December 2017) and the mature SLT technology group (163 cases, from January 2018 to July 2023). The survival of each group was analyzed and the main factors affecting the survival rate of SLT were analyzed. The Kaplan-Meier method and Log-rank test were used for survival analysis. Results: The cumulative survival rates at 1-, 3-, and 5-year were 74.58%, 71.47%, and 71.47% in the early SLT group, and 88.03%, 87.23%, and 87.23% in the mature SLT group, respectively. Survival rates in the mature SLT group were significantly higher than those in the early SLT group (χ2=5.560,P=0.018). The cumulative survival rates at 1-, 3- and 5-year were 93.41%, 93.41%, 89.95% in the LDLT group and 87.38%, 81.98%, 77.04% in the WLT group, respectively. There was no significant difference among the mature SLT group, the LDLT group and the WLT group (χ2=4.016, P=0.134). Abdominal hemorrhage, infection, primary liver graft nonfunction,and portal vein thrombosis were the main causes of early postoperative death. Conclusion: SLT can achieve results comparable to those of WLT and LDLT in mature technology liver transplant centers, but it needs to go through a certain time learning curve.

[Progress and controversy in minimally invasive approach to radical cholecystectomy for gallbladder cancer]

Surgical treatment is one of the most important forms of treatment in patients with gallbladder cancer. With the development of minimally invasive technology, the feasibility, safety and efficacy of minimally invasive approaches such as laparoscopic or robotic-assisted radical cholecystectomy for gallbladder cancer have received continuous attention.For patients with an early T-stage (Tis or T1a), laparoscopic simple cholecystectomy is safe and economical, with a good prognosis for postoperative patients, and it has been widely accepted and performed. Radical resection of advanced gallbladder cancer requires resection of the gallbladder, its liver bed, and other neighboring invaded organs, as well as clearance of regional lymph nodes, which requires experienced gallbladder cancer treatment teams to strictly grasp the indications, select appropriate patients, and formulate a good surgical strategy to ensure the therapeutic effect. Meanwhile, robot-assisted radical resection for gallbladder cancer has been performed in a few centers and shows good clinical potential, but more high-quality studies are needed to further evaluate its value in gallbladder cancer treatment.

BRCC3 Regulation of ALK2 in Vascular Smooth Muscle Cells: Implication in Pulmonary Hypertension

BACKGROUND

An imbalance of antiproliferative BMP (bone morphogenetic protein) signaling and proliferative TGF-β (transforming growth factor-β) signaling is implicated in the development of pulmonary arterial hypertension (PAH). The posttranslational modification (eg, phosphorylation and ubiquitination) of TGF-β family receptors, including BMPR2 (bone morphogenetic protein type 2 receptor)/ALK2 (activin receptor-like kinase-2) and TGF-βR2/R1, and receptor-regulated (R) Smads significantly affects their activity and thus regulates the target cell fate. BRCC3 modifies the activity and stability of its substrate proteins through K63-dependent deubiquitination. By modulating the posttranslational modifications of the BMP/TGF-β-PPARγ pathway, BRCC3 may play a role in pulmonary vascular remodeling, hence the pathogenesis of PAH.

METHODS

Bioinformatic analyses were used to explore the mechanism of BRCC3 deubiquitinates ALK2. Cultured pulmonary artery smooth muscle cells (PASMCs), mouse models, and specimens from patients with idiopathic PAH were used to investigate the rebalance between BMP and TGF-β signaling in regulating ALK2 phosphorylation and ubiquitination in the context of pulmonary hypertension.

RESULTS

BRCC3 was significantly downregulated in PASMCs from patients with PAH and animals with experimental pulmonary hypertension. BRCC3, by de-ubiquitinating ALK2 at Lys-472 and Lys-475, activated receptor-regulated Smad1/5/9 (Smad1/5/9), which resulted in transcriptional activation of BMP-regulated PPARγ, p53, and Id1. Overexpression of BRCC3 also attenuated TGF-β signaling by downregulating TGF-β expression and inhibiting phosphorylation of Smad3. Experiments in vitro indicated that overexpression of BRCC3 or the de-ubiquitin-mimetic ALK2-K472/475R attenuated PASMC proliferation and migration and enhanced PASMC apoptosis. In SM22α-BRCC3-Tg mice, pulmonary hypertension was ameliorated because of activation of the ALK2-Smad1/5-PPARγ axis in PASMCs. In contrast, Brcc3-/- mice showed increased susceptibility of experimental pulmonary hypertension because of inhibition of the ALK2-Smad1/5 signaling.

CONCLUSIONS

These results suggest a pivotal role of BRCC3 in sustaining pulmonary vascular homeostasis by maintaining the integrity of the BMP signaling (ie, the ALK2-Smad1/5-PPARγ axis) while suppressing TGF-β signaling in PASMCs. Such rebalance of BMP/TGF-β pathways is translationally important for PAH alleviation.

Prognostic value of time-varying dead space estimates in mechanically ventilated patients with acute respiratory distress syndrome

Background

The dead space fraction (VD/VT) has proven to be a powerful predictor of higher mortality in acute respiratory distress syndrome (ARDS). However, its measurement relies on expired carbon dioxide, limiting its widespread application in clinical practice. Several estimates employing routine variables have been found to be reliable substitutes for direct measurement of VD/VT. In this study, we evaluated the prognostic value of these dead space estimates obtained in the first 7 days following the initiation of ventilation.

Methods

This retrospective observational study was conducted using data from the Chinese database in intensive care (CDIC). Eligible participants were adult ARDS patients receiving invasive mechanical ventilation while in the intensive care unit between 1st January 2014 and 31st March 2021. We collected data during the first 7 days of ventilation to calculate various dead space estimates, including ventilatory ratio (VR), corrected minute ventilation (V ˙ Ecorr ), VD/VT (Harris-Benedict), VD/VT (Siddiki estimate), and VD/VT (Penn State estimate) longitudinally. A time-dependent Cox model was used to handle these time-varying estimates.

Results

A total of 392 patients (median age 66 [interquartile range: 55-77] years, median SOFA score 9 [interquartile range: 7-12]) were finally included in our analysis, among whom 132 (33.7%) patients died within 28 days of admission. VR (hazard ratio [HR]=1.04 per 0.1 increase, 95% confidence interval [CI]: 1.01 to 1.06; P=0.013), V ˙ Ecorr (HR=1.08 per 1 increase, 95% CI: 1.04 to 1.12; P < 0.001), VD/VT (Harris-Benedict) (HR=1.25 per 0.1 increase, 95% CI: 1.06 to 1.47; P=0.006), and VD/VT (Penn State estimate) (HR=1.22 per 0.1 increase, 95% CI: 1.04 to 1.44; P=0.017) remained significant after adjustment, while VD/VT (Siddiki estimate) (HR=1.10 per 0.1 increase, 95% CI: 1.00 to 1.20; P=0.058) did not. Given a large number of negative values, VD/VT (Siddiki estimate) and VD/VT (Penn State estimate) were not recommended as reliable substitutes. Long-term exposure to VR >1.3, V ˙ Ecorr >7.53, and VD/VT (Harris-Benedict) >0.59 was independently associated with an increased risk of mortality in ARDS patients. These findings were validated in the fluid and catheter treatment trial (FACTT) database.

Conclusions

In cases where VD/VT cannot be measured directly, early time-varying estimates of VD/VT such as VR, V ˙ Ecorr , and VD/VT (Harris-Benedict) can be considered for predicting mortality in ARDS patients, offering a rapid bedside application.

Financial toxicity of informal caregivers of colorectal cancer patients: A cross-sectional study

PURPOSE

To assess the level of financial toxicity of informal caregivers of colorectal cancer patients and explore the related key influencing factors.

METHOD

A descriptive survey design was used in this study. Data were collected from 236 informal caregivers of colorectal cancer patients between March 2023 and July 2023 from a major hospital in central China (Henan province). Potential influence factors of financial toxicity, including basic information, perceived stress, and social support were analyzed using multivariate linear regression.

RESULTS

The financial toxicity score of 236 caregivers of colorectal cancer patients was 19.42 ± 9.72. One hundred and fourteen caregivers (accounting for 48.31%) of colorectal cancer patients had high levels of financial toxicity. Financial toxicity scores of caregivers were negatively correlated with perceived stress (r = -0.421, P < 0.001) and positively correlated with social support (r = 0.416, P < 0.001). Our multivariate regression analysis identified some factors that directly affected caregivers' financial toxicity, including caregiver age (t = 2.105, P = 0.036), medical insurance (t = 2.462, P = 0.015), average household income (t = 2.995, P = 0.003), place of residence (t = 2.872, P = 0.004), perceived stress (t = -4.945, P < 0.001), and social support (t = 4.513, P < 0.001).

CONCLUSIONS

Caregivers of colorectal cancer patients generally experience a higher level of financial toxicity, which could be eased by lower perceived stress and higher social support. In clinical practice, it is necessary to comprehensively assess the level of financial toxicity of particular caregivers and enact targeted interventions such as increasing communication and actively providing information to address the high medical costs, reducing the detrimental effects of financial toxicity, and improving the quality of colorectal cancer care.

Efficacy and Safety of Preoperative Transcatheter Rectal Arterial Chemoembolisation in Patients with Locally Advanced Rectal Cancer: Results from a Prospective, Phase II PCAR Trial

AIMS

The PCAR study aimed to assess the efficacy and safety of preoperative transcatheter rectal arterial chemoembolisation (TRACE) in patients with locally advanced rectal cancer (LARC).

MATERIALS AND METHODS

This was a single-centre, prospective, phase II trial conducted in China. Eligible patients were adults aged 18 years and older with histologically confirmed stage II or III rectal carcinoma and an Eastern Cooperative Oncology Group performance status of 0-1. Patients received TRACE with oxaliplatin, followed by radiotherapy with a cumulative dose of 45 Gy (1.8 Gy/time/day, five times a week for 5 weeks) and received oral S1 capsules twice daily (7 days a week for 4 weeks). Patients underwent total mesorectal excision 4-8 weeks after the completion of chemoradiotherapy, followed by mFOLFOX6 or CAPOX regimens for 4-6 months. The hypothesis of this study was that adding TRACE to preoperative neoadjuvant chemoradiotherapy would improve tumour regression and prognosis. The primary end point was the pathological complete response rate; secondary end points included the major pathological response rate, anal preservation rate, 5-year disease-free survival (DFS), 5-year overall survival and treatment-related adverse events.

RESULTS

In total, 111 LARC patients received TRACE and subsequent scheduled treatment plans. The pathological complete response and major pathological response rates were 20.72% and 48.65%, respectively. The 5-year DFS and 5-year overall survival were 61.89% (95% confidence interval 51.45-74.45) and 74.80% (95% confidence interval 65.05-86.01), respectively. Grade 3-4 toxicities were reported in 29 patients (26.13%). The postoperative complication rate was 21.62%, without serious surgical complications. Multivariate Cox regression analysis showed that ypN stage (hazard ratio = 4.242, 95% confidence interval 2.101-8.564, P = 0.00017) and perineural invasion (hazard ratio = 2.319, 95% confidence interval 1.058-5.084, P = 0.0487) were independent risk factors associated with DFS, whereas ypN stage (hazard ratio = 3.164, 95% confidence interval 1.347-7.432, P = 0.0101), perineural invasion (hazard ratio = 4.118, 95% confidence interval 1.664-10.188, P = 0.0134) and serum carbohydrate antigen 199 (CA199; hazard ratio = 4.142, 95% confidence interval 1.290-13.306, P = 0.0344) were independent predictors for overall survival.

CONCLUSION

The current study provides evidence that adding TRACE to neoadjuvant chemoradiotherapy can improve the pathological remission rate in LARC patients with acceptable toxicity. Given its promising effectiveness and safe profile, incorporating TRACE into the standard treatment strategy for patients with LARC should be considered.

CircMLH3 induces mononuclear macrophage pyroptosis in sepsis by sponging miR-590-3p to regulate TAK1 expression

Sepsis is a fatal syndrome characterized by uncontrolled systemic inflammatory responses. Circular RNAs (circRNAs) are involved in the modulation of various pathophysiological processes, but their potential role in sepsis has largely been unexplored. In this study, we observed differential expression of circMLH3 between healthy volunteers and septic patients, and revealed the value of circMLH3 for sepsis diagnosis and prognostic prediction. Interestingly, we discovered a correlation between the expression level of circMLH3 and the degree of pyroptosis, a critical mechanism contributing to uncontrolled inflammation in sepsis patients. Knocking down circMLH3 alleviated macrophage pyroptosis whereas overexpressing circMLH3 aggravated pyroptosis. circMLH3 regulated macrophage pyroptosis by sponging miR-590-3p and subsequently modulating TAK1 expression. Furthermore, we found that the miR-590-3p/TAK1 axis inhibited the activation of pro-caspase-1 and the NLRP3 inflammasome. miR-590-3p overexpression had a protective effect by reducing macrophage pyroptosis, thereby alleviating sepsis-induced lung injury and systemic inflammatory responses. In conclusion, our study elucidated the circMLH3/miR-590-3p/TAK1 signaling pathway and identified its role in regulating mononuclear macrophage pyroptosis, thus providing potential novel targets and strategies for sepsis diagnosis and therapy.

Reclassification of therapeutic response of unresectable hepatocellular carcinoma to anti-angiogenic therapy and immunotherapy using alpha RECIST

OBJECTIVES

To assess the therapeutic response of HCC to antiangiogenic therapy plus immunotherapy by integrating RECIST 1.1 and alpha-fetoprotein (AFP) response at the 6th week to predict overall survival (OS).

METHODS

This retrospective study included 150 and 214 patients with HCC who received combination therapy in training and validation cohorts. The medical images and AFP levels obtained at baseline and 6th week were collected. AFP response stratification: partial response (PR): AFP% ≥ 75% decline; stable disease (SD): AFP% < 75% decline and  ≤ 10% elevation; progressive disease (PD): AFP% > 10% elevation. The alpha-RECIST was: PR: RECIST 1.1-PR or AFP-PR; PD: AFP-PD or RECIST 1.1-PD and does not satisfy AFP-PR; SD: neither PR nor PD. OS was compared using Kaplan-Meier curves. The predictive ability of various criteria was evaluated using the concordance index and time-dependent area under the receiver-operating characteristic curve.

RESULTS

RECIST 1.1 achieved significant OS stratification (p = 0.020) for AFP < 20 ng/mL. For AFP ≥ 20 ng/mL, alpha-RECIST showed better performance than RECIST 1.1, mRECIST, and AFP response according to C-index (0.73 vs 0.66 vs 0.68 vs 0.69). The National Cancer Center (NCC) strategy utilized RECIST 1.1 for AFP < 20 ng/mL and alpha-RECIST for AFP ≥ 20 ng/mL and showed better performance than RECIST 1.1, mRECIST and AFP response according to C-index (0.73 vs 0.67 vs 0.69 vs 0.64). The performances of alpha-RECIST and NCC Strategy were confirmed in the validation cohort (C-index = 0.77 and 0.74).

CONCLUSIONS

The alpha-RECIST and NCC Strategy achieved better survival stratification in patients with HCC under combination therapy in the AFP ≥ 20 ng/mL group and the whole cohort compared to the RECIST 1.1, mRECIST, and AFP response.

CLINICAL TRANSLATIONAL RELEVANCE

The alpha-RECIST and National Cancer Center strategy are optimal methods for determining therapeutic response to a combination of anti-angiogenic therapy plus immunotherapy and facilitating accurate prognostic stratification for HCC in the AFP ≥ 20 ng/mL group and the whole cohort, which may help oncologists for early identification of responders and progression at 6 weeks and clinical decision-making.

KEY POINTS

• RECIST 1.1 is indicated for patients with baseline alpha-fetoprotein (AFP) < 20 ng/mL. • For patients with baseline AFP ≥ 20 ng/mL, integrating RECIST 1.1 and AFP response (alpha-RECIST) may aid in the early identification of survival benefits and progression definition prior to the administration of additional efficacious drugs. • The National Cancer Center strategy is an optimal stratified strategy for determining therapeutic response to a combination of anti-angiogenic therapy and immunotherapy for HCC based on baseline AFP levels.

Polyphenolic Platform Ameliorated Sanshool for Skin Photoprotection

Natural evolution has nurtured a series of active molecules that play vital roles in physiological systems, but their further applications have been severely limited by rapid deactivation, short cycle time, and potential toxicity after isolation. For instance, the instability of structures and properties has greatly descended when sanshool is derived from Zanthoxylum xanthoxylum. Herein, natural polyphenols are employed to boost the key properties of sanshool by fabricating a series of nanoparticles (NPs). The intracellular evaluation and in vivo animal model are conducted to demonstrate the decreased photodamage score and skin-fold thickness of prepared NPs, which can be attributed to the better biocompatibility, improved free radical scavenging, down-regulated apoptosis ratios, and reduced DNA double-strand breaks compared to naked sanshool. This work proposes a novel strategy to boost the key properties of naturally occurring active molecules with the assistance of natural polyphenol-based platforms.

Estimating the carbon footprint of Mexican food consumption based on a high-resolution environmentally extended input-output model

Increased global attention is being paid to the food-health-climate trilemma. In this study, we evaluate the climate impacts of Mexico's food consumption patterns by creating a high-resolution (262 sectors) Environmentally Extended Input-Output (EEIO) model called MXEEIO. We focus on the differences between food away from home (FAFH) and food at home (FAH) and compare Mexico's results with those of the USA. The results show that the main components of food spending in Mexico were meat, baked products, and beverages, raising concerns about their potential negative health effects if consumed excessively. Mexico's total greenhouse gas (GHG) emissions from food consumption were estimated at 149 million metric tons (MMT) in 2013, as opposed to 797 MMT for the USA. Meat and dairy products were the main contributors to Mexico's food-related GHG emissions, accounting for 57% of total emissions. Mexico spent a much smaller proportion of food-related income on FAFH than the USA (13% vs. 52%), suggesting great potential for growth as Mexico's per capita GDP continues to rise. Detailed contribution analysis shows that reducing Mexico's food-related GHG emissions would benefit most from a transition to low-carbon cattle farming, but mitigation efforts in other sectors such as crop cultivation and electricity generation are also important. Overall, our study underscores the significance of food-related GHG emissions in Mexico, especially those from meat and dairy products, and the mitigation challenges these sectors face.

Fascia iliaca compartment block mitigates the fluctuations in heart rate variability and reduces pain with opioid consumption in elderly individuals with hip fractures: A randomized controlled trial

Background

Hip fractures, commonly known as the "terminal fracture of life," frequently necessitate prompt surgical intervention and are accompanied by significant perioperative pain.

Objective

This investigation was performed to assess the impact of fascia iliaca compartment block (FICB) on heart rate variability during the perioperative period in elderly individuals with hip fractures.

Design

Single-center, randomized, controlled clinical trial.

Setting

The study was conducted from September 2021 to February 2023 at one tertiary care hospital in China.

Participants

Patients aged ≥60 years who underwent general anesthesia for hip fracture surgery were screened for enrollment. Eighty patients were initially assessed for eligibility, 70 underwent randomization, and 62 were included in the final analysis.

Methods

Preoperatively, the patients were randomly allocated to either receive (Group F) or not receive (Group C) ultrasound-guided suprainguinal FICB. The primary endpoint was heart rate variability indicators at the corresponding time points. The secondary endpoints included the mean arterial pressure and heart rate measured at different time points [upon admission to the operating room (T1), during positioning (T2), at the time of skin incision (T3), 30 min after the start of surgery (T4), and 6 h postoperatively (T5)] and visual analogue scale (VAS) score, dose of oral pain medication over 24 h, and satisfaction scores were valued.

Results

Compared with Group C, Group F had a significantly reduced low-frequency band, high-frequency band, and low-/high-frequency band ratio at T3, T4, and T5 (P < 0.05). Group F also had a lower heart rate at T2, T3, T4, and T5 (P < 0.05). Moreover, Group F had lower flurbiprofen dosages at 24 h postoperatively (P < 0.05) and lower resting VAS scores at 6 and 24 h postoperatively (P < 0.05).

Conclusion

Utilization of ultrasound-guided FICB has the potential to yield efficacious analgesic effects, mitigate the pronounced fluctuations in heart rate induced by surgical stimulation, and maintain autonomic function stability to a certain degree.

Defective transfer of parental histone decreases frequency of homologous recombination by increasing free histone pools in budding yeast

Recycling of parental histones is an important step in epigenetic inheritance. During DNA replication, DNA polymerase epsilon subunit DPB3/DPB4 and DNA replication helicase subunit MCM2 are involved in the transfer of parental histones to the leading and lagging strands, respectively. Single Dpb3 deletion (dpb3Δ) or Mcm2 mutation (mcm2-3A), which each disrupts one parental histone transfer pathway, leads to the other's predominance. However, the biological impact of the two histone transfer pathways on chromatin structure and DNA repair remains elusive. In this study, we used budding yeast Saccharomyces cerevisiae to determine the genetic and epigenetic outcomes from disruption of parental histone H3-H4 tetramer transfer. We found that a dpb3Δ mcm2-3A double mutant did not exhibit the asymmetric parental histone patterns caused by a single dpb3Δ or mcm2-3A mutation, suggesting that the processes by which parental histones are transferred to the leading and lagging strands are independent. Surprisingly, the frequency of homologous recombination was significantly lower in dpb3Δ, mcm2-3A and dpb3Δ mcm2-3A mutants, likely due to the elevated levels of free histones detected in the mutant cells. Together, these findings indicate that proper transfer of parental histones during DNA replication is essential for maintaining chromatin structure and that lower homologous recombination activity due to parental histone transfer defects is detrimental to cells.

Exploration of Exopolysaccharide from Leuconostoc mesenteroides HDE-8: Unveiling Structure, Bioactivity, and Food Industry Applications

A strain of Leuconostoc mesenteroides HDE-8 was isolated from homemade longan fermentation broth. The exopolysaccharide (EPS) yield of the strain was 25.1 g/L. The EPS was isolated and purified, and the structure was characterized using various techniques, including X-ray diffraction (XRD), nuclear magnetic resonance (NMR) spectroscopy, Fourier-transform infrared (FT-IR) spectroscopy, high-performance size exclusion chromatography (HPSEC), and scanning electron microscopy (SEM). The monosaccharide composition of the EPS was glucose, with a molecular weight (Mw) of 1.7 × 106 Da. NMR spectroscopy revealed that the composition of the HDE-8 EPS consisted of D-glucose pyranose linked by α-(1→4) and α-(1→6) bonds. The SEM analysis of the EPS showed an irregular sheet-like structure. Physicochemical analysis demonstrated that EPSs exhibit excellent thermal stability and high viscosity, making them suitable for fermentation in heat-processed and acidic foods. Additionally, milk coagulation tests showed that the presence of EPSs promotes milk coagulation when supplemented with sucrose. It suggests that EPSs have wide-ranging potential applications as food additives, improving the texture and taste of dairy products. This study provides practical guidance for the commercial use of HDE-8 EPSs in the food and related industries.

Two Decades' advancements and Research trends in needle-type Sensor technology: A scientometric analysis

Needle-type sensor, characterized by its slender, elongated shape, is a promising sensing method due to its rapid response, high sensitivity, and portability. Recently, the needle-type sensor technology has garnered increasing attention, leading to its accelerated development and extensive use in medical and healthcare, environmental monitoring, and geosciences. However, there remains a need for a comprehensive review of existing research. Here, we utilize scientometric analysis, which is booming recently, to conduct a comprehensive investigation of the needle-type sensor field. This analysis covers various aspects, including annual trends, journals, institutions, countries, disciplines, authors, references, and keywords of 136,667 publications from the Web of Science Core Collection (WoSCC) database spanning from January 1, 2004, to January 1, 2024. Additionally, we identify current hotspots, frontiers, and predict future trends. Eventually, three research hotspots are refined: multidisciplinary materials science, sensor miniaturization and integration, and biomedical engineering, indicating that further investigations may focus on creating biocompatible materials to enhance sensing properties, optimizing sensor structure through miniaturization and integration methods, and improving clinical applications in biomedical engineering. This work may facilitate the development of needle-type sensors.

Combination of theoretical analysis and experiments: Exploring the role of PLA2G7 in human cancers, including renal cancer

Background

The pivotal role of phospholipase A2 group VII (PLA2G7) has been identified in specific human cancers, such as prostate cancer, diffuse large B cell lymphoma, and melanoma. Given PLA2G7's significant involvement in established tumors, exploring its role in other cancers is highly relevant.

Methods

In this study, we acquired and analyzed data from The Cancer Genome Atlas database, the UCSC XENA website, and other online platforms including Gene Set Cancer Analysis, cBioPortal, Tumor Immune Estimation Resource, and TISIDB to investigate PLA2G7's role in human cancers, including renal cancer. Furthermore, in vitro experiments, including immunofluorescence, western blotting, and CCK-8 assays, were conducted to elucidate PLA2G7's role in renal cancer. Finally, the relationship between PLA2G7 and various drug sensitivity was explored.

Results

Our findings demonstrate that PLA2G7 is highly expressed and may serve as a valuable candidate biomarker in pan-cancer. PLA2G7 exhibits distinct alteration frequencies across human cancers and is correlated with tumor mutation burden, tumor microenvironment, DNA stemness score, RNA stemness score, tumorigenesis, tumor immunity, and microsatellite instability in pan-cancer. Immunofluorescence and western blotting revealed a relative high level of PLA2G7 protein in renal cancer cell lines (ACHN and 786-O), predominantly localized in the cytoplasm. Treatment with a PLA2G7 gene inhibitor (darapladib) significantly decreased the viability of ACHN and 786-O cell lines. Additionally, we observed an association between PLA2G7 mRNA levels and various drug sensitivity.

Conclusions

Our study suggests that PLA2G7 has the potential to serve as a valuable biomarker and therapeutic target for cancer, particularly in the context of renal cancer.

Amplitude Analysis of the B^{0}→K^{*0}μ^{+}μ^{-} Decay

An amplitude analysis of the B^{0}→K^{*0}μ^{+}μ^{-} decay is presented using a dataset corresponding to an integrated luminosity of 4.7  fb^{-1} of pp collision data collected with the LHCb experiment. For the first time, the coefficients associated to short-distance physics effects, sensitive to processes beyond the standard model, are extracted directly from the data through a q^{2}-unbinned amplitude analysis, where q^{2} is the μ^{+}μ^{-} invariant mass squared. Long-distance contributions, which originate from nonfactorizable QCD processes, are systematically investigated, and the most accurate assessment to date of their impact on the physical observables is obtained. The pattern of measured corrections to the short-distance couplings is found to be consistent with previous analyses of b- to s-quark transitions, with the largest discrepancy from the standard model predictions found to be at the level of 1.8 standard deviations. The global significance of the observed differences in the decay is 1.4 standard deviations.

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

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

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

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

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Affiliation(s)

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

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

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

Discovery of SQSTM1/p62-dependent P-bodies that regulate the NLRP3 inflammasome

Autophagy and ribonucleoprotein granules, such as P-bodies (PBs) and stress granules, represent vital stress responses to maintain cellular homeostasis. SQSTM1/p62 phase-separated droplets are known to play critical roles in selective autophagy; however, it is unknown whether p62 can exist as another form in addition to its autophagic droplets. Here, we found that, under stress conditions, including proteotoxicity, endotoxicity, and oxidation, autophagic p62 droplets are transformed to a type of enlarged PBs, termed p62-dependent P-bodies (pd-PBs). p62 phase separation is essential for the nucleation of pd-PBs. Mechanistically, pd-PBs are triggered by enhanced p62 droplet formation upon stress stimulation through the interactions between p62 and DDX6, a DEAD-box ATPase. Functionally, pd-PBs recruit the NLRP3 inflammasome adaptor ASC to assemble the NLRP3 inflammasome and induce inflammation-associated cytotoxicity. Our study shows that p62 droplet-to-PB transformation acts as a stress response to activate the NLRP3 inflammasome process, suggesting that persistent pd-PBs lead to NLRP3-dependent inflammation toxicity.

Sustainable Blue Foods from Rice-Animal Coculture Systems

Global interest grows in blue foods as part of sustainable diets, but little is known about the potential and environmental performance of blue foods from rice-animal coculture systems. Here, we compiled a large experimental database and conducted a comprehensive life cycle assessment to estimate the impacts of scaling up rice-fish and rice-crayfish systems in China. We find that a large amount of protein can be produced from the coculture systems, equivalent to ∼20% of freshwater aquaculture and ∼70% of marine wild capture projected in 2030. Because of the ecological benefits created by the symbiotic relationships, cocultured fish and crayfish are estimated to be carbon-negative (-9.8 and -4.7 kg of CO2e per 100 g of protein, respectively). When promoted at scale to displace red meat, they can save up to ∼98 million tons of greenhouse gases and up to ∼13 million hectares of farmland, equivalent to ∼44% of China's total rice acreage. These results suggest that rice-animal coculture systems can be an important source of blue foods and contribute to a sustainable dietary shift, while reducing the environmental footprints of rice production. To harvest these benefits, robust policy supports are required to guide the sustainable development of coculture systems and promote healthy and sustainable dietary change.

Individual Beliefs and Experiences With Brain Health Dietary Supplements in the United States

BACKGROUND

Although the use of brain health dietary supplements (brain DS) has increased, there is limited research on safety and risk of these products. Brain DS may be beneficial for improving memory, concentration, and focus but may also carry risks.

OBJECTIVES

To assess brain DS users' utilization experiences and identify factors associated with likelihood of brain DS use among nonusers.

DESIGN

An internet-based cross-sectional survey study was conducted using a sample of middle-aged US adults. Respondents' sociodemographic characteristics and health beliefs regarding brain DS were collected. Brain DS users' utilization experiences such as negative side effects and spending were also collected.

PARTICIPANTS AND SETTING

Purposive sampling was utilized for users and nonusers sample recruitment.

MAIN OUTCOME MEASURES

Brain DS users' utilization experience and future likelihood of brain DS use among nonusers.

STATISTICAL ANALYSES PERFORMED

Descriptive statistics on brain DS users' utilization experiences were reported. Ordinal logistic regression with sociodemographic and belief characteristics as predictors was employed to identify factors associated with the likelihood of brain DS among nonusers.

RESULTS

Five hundred twenty-five respondents (mean age = 43.8 ± 9.2 years) completed the survey. Among 260 users, primary reasons for use were enhancing memory (n = 136) and helping concentration and focus (n = 108). During the past year, 40% spent $50 to $200 (range = $0 to >$1,000) and 37% reported experiencing negative side effects. Among 265 nonusers, being female (odds ratio 2.04, 95% CI 1.21 to 3.45), perceived susceptibility to brain problems (odds ratio 1.90, 95% CI 1.28 to 2.83), recommendation from others (odds ratio 1.55, 95% CI 1.03 to 2.35) and perceived benefits of brain DS (odds ratio 2.82, 95% CI 1.60 to 4.96) were significantly associated with increased likelihood of future brain DS use.

CONCLUSIONS

Individual spending on brain DS varies and about 40% of users reported experiencing negative side effects. As individuals primarily rely on healthcare providers for recommendations, health care providers should be prepared to engage in discussions about brain DS with patients.

[Propensity score matching analysis of the short-term efficacy of Kamikawa versus double- tract reconstruction in laparoscopic proximal gastric cancer surgery]

Objective: To compare the short-term efficacy of Kamikawa anastomosis and double-tract reconstruction (DTR) after proximal gastrectomy. Methods: This was a propensity score matched, retrospective, cohort study. Inclusion criteria comprised age 20-70 years, diagnosis of gastric cancer by pathological examination of preoperative endoscopic biopsies, tumor diameter ≤4 cm, and location in the upper 1/3 of the stomach (including the gastroesophageal junction), and TNM stage IA, IB, or IIA. The study cohort comprised 73 patients who had undergone laparoscopic proximal gastric cancer radical surgery in the Department of Gastroenterology, Tangdu Hospital, Air Force Medical University between June 2020 and February 2023, 19 of whom were in the Kamikawa group and 54 in the DTR group. After using R language to match the baseline characteristics of patients in a ratio of 1:2, there were 17 patients in the Kamikawa group and 34 in the DTR group. Surgery-related conditions, postoperative quality of life, and postoperative complications were compared between the two groups. Results: After propensity score matching, there were no statistically significant differences in baseline data between the two groups (P>0.05). Compared with the DTR group, the Kamikawa group had longer operative times (321.5±15.7 minutes vs. 296.8±26.1 minutes, t=32.056, P<0.001), longer anastomosis times (93.0±6.8 minutes vs. 45.3±7.7 minutes, t=56.303, P<0.001), and less bleeding (76 [54~103] mL vs.112 [82~148) mL, Z=71.536, P<0.001); these differences are statistically significant. There were no statistically significant differences between the two groups in tumor size, time to first postoperative passage of gas, postoperative hospital stay, number of lymph nodes removed, duration of lymph node dissection, or total hospitalization cost (all P>0.05). The median follow-up time was 6.1 ± 1.8 months. As to postoperative quality of life, the Kamikawa group had a lower rate of upper gastrointestinal contrast reflux than did the DTR group (0 vs. 29.4% [10/34], χ2=6.220, P=0.013); this difference is statistically significant. However, differences between the two groups in quality of life score on follow-up of 3 months and 6 months on the Gastroesophageal Reflux Disease (GERD) scale were not statistically significant (all P>0.05). The incidence of postoperative complications was 2/17 in the Kamikawa group, which is significantly lower than the 41.2% (14/34) in the DTR group (χ2=4.554, P=0.033). Conclusion: Kamikawa anastomosis and DTR are equally safe and effective procedures for reconstructing the digestive tract after proximal gastric surgery. Although Kamikawa anastomosis takes slightly longer and places higher demands on the surgical team, it is more effective at preventing postoperative reflux.

Targeted exosome-based nanoplatform for new-generation therapeutic strategies

Exosomes, typically 30-150 nm in size, are lipid-bilayered small-membrane vesicles originating in endosomes. Exosome biogenesis is regulated by the coordination of various mechanisms whereby different cargoes (e.g. proteins, nucleic acids, and lipids) are sorted into exosomes. These components endow exosomes with bioregulatory functions related to signal transmission and intercellular communication. Exosomes exhibit substantial potential as drug-delivery nanoplatforms owing to their excellent biocompatibility and low immunogenicity. Proteins, miRNA, siRNA, mRNA, and drugs have been successfully loaded into exosomes, and these exosome-based delivery systems show satisfactory therapeutic effects in different disease models. To enable targeted drug delivery, genetic engineering and chemical modification of the lipid bilayer of exosomes are performed. Stimuli-responsive delivery nanoplatforms designed with appropriate modifications based on various stimuli allow precise control of on-demand drug delivery and can be utilized in clinical treatment. In this review, we summarize the general properties, isolation methods, characterization, biological functions, and the potential role of exosomes in therapeutic delivery systems. Moreover, the effective combination of the intrinsic advantages of exosomes and advanced bioengineering, materials science, and clinical translational technologies are required to accelerate the development of exosome-based delivery nanoplatforms.

LysSYL: a broad-spectrum phage endolysin targeting Staphylococcus species and eradicating S. aureus biofilms

BACKGROUND

Staphylococcus aureus and its single or mixed biofilm infections seriously threaten global public health. Phage therapy, which uses active phage particles or phage-derived endolysins, has emerged as a promising alternative strategy to antibiotic treatment. However, high-efficient phage therapeutic regimens have yet to be established.

RESULTS

In this study, we used an enrichment procedure to isolate phages against methicillin-resistant S. aureus (MRSA) XN108. We characterized phage SYL, a new member of the Kayvirus genus, Herelleviridae family. The phage endolysin LysSYL was expressed. LysSYL demonstrated stability under various conditions and exhibited a broader range of efficacy against staphylococcal strains than its parent phage (100% vs. 41.7%). Moreover, dynamic live/dead bacterial observation demonstrated that LysSYL could completely lyse MRSA USA300 within 10 min. Scan and transmission electron microscopy revealed evident bacterial cell perforation and deformation. In addition, LysSYL displayed strong eradication activity against single- and mixed-species biofilms associated with S. aureus. It also had the ability to kill bacterial persisters, and proved highly effective in eliminating persistent S. aureus when combined with vancomycin. Furthermore, LysSYL protected BALB/c mice from lethal S. aureus infections. A single-dose treatment with 50 mg/kg of LysSYL resulted in a dramatic reduction in bacterial loads in the blood, liver, spleen, lungs, and kidneys of a peritonitis mouse model, which resulted in rescuing 100% of mice challenged with 108 colony forming units of S. aureus USA300.

CONCLUSIONS

Overall, the data provided in this study highlight the strong therapeutic potential of endolysin LysSYL in combating staphylococcal infections, including mono- and mixed-species biofilms related to S. aureus.

Carbon capture and utilization by algae with high concentration CO2 or bicarbonate as carbon source

Algae plays a key role in carbon capture and utilization (CCU) as it can capture and use the atmospheric CO2 for conversion of value-added products. Concentrated CO2 is common in flue gas and provides opportunities for algae cultivation. The drawbacks are mass transfer limitation, poor CO2 dissolution, and challenges to reach optimal levels for algal growth at given flue gas levels. Bicarbonate is flexible to be used as carbon source and owns the potential to enhance the efficiency of biological carbon fixation by algae. The requirements of algae strains are more stringent. To improve the industrial scale-up of CCU, system optimization is of great importance. More novel algal strains that can grow rapidly under harsh environment and provide valuable bio-products should be developed for large-scale production. Algae-driven CCU is promising for achieving carbon-neutrality.

A case report of atypical chronic myeloid leukemia with complete hematological and major molecular response to Venetoclax/Azacitidine treatment

Atypical Chronic Myeloid Leukemia (aCML), a myeloproliferative neoplasm with poor prognosis, was reclassified as aCML by the ICC classification, and as MDS/MPN with neutrophilia by the WHO 2022 classification. Due to the heterogeneity of its clinical features and the lack of unique biomarkers, as well as limited treatment options, aCML currently lacks a standardized treatment protocol. In this case report, we reviewed a young man diagnosed with aCML who achieved complete clinical and hematologic remission subsequent to receiving a therapeutic regimen combining Venetoclax and Azacitidine.

Enhanced Therapeutic Potential of Hybrid Exosomes Loaded with Paclitaxel for Cancer Therapy

The advancement of exosome studies has positioned engineered exosomes as crucial biomaterials for the development of advanced drug delivery systems. This study focuses on developing a hybrid exosome system by fusing mesenchymal stem cells (MSCs) exosomes with folate-targeted liposomes. The aim was to improve the drug loading capacity and target modification of exosome nanocarriers for delivering the first-line chemotherapy drug paclitaxel (PTX) and its effectiveness was assessed through cellular uptake studies to evaluate its ability to deliver drugs to tumor cells in vitro. Additionally, in vivo experiments were conducted using a CT26 tumor-bearing mouse model to assess the therapeutic efficacy of hybrid exosomes loaded with PTX (ELP). Cellular uptake studies demonstrated that ELP exhibited superior drug delivery capabilities to tumor cells in vitro. Moreover, in vivo experiments revealed that ELP significantly suppressed tumor growth in the CT26 tumor-bearing mouse model. Notably, for the first time, we examined the tumor microenvironment following intratumoral administration of ELP. We observed that ELP treatment activated CD4+ and CD8+ T cells, reduced the expression of M2 type tumor-associated macrophages (TAMs), polarized TAMs towards the M1 type, and decreased regulatory T cells (Tregs). Our research highlights the considerable therapeutic efficacy of ELP and its promising potential for future application in cancer therapy. The development of hybrid exosomes presents an innovative approach to enhance drug delivery and modulate the tumor microenvironment, offering exciting prospects for effective cancer treatment strategies.

The role of deubiquitinases in cardiac disease

Deubiquitinases are a group of proteins that identify and digest monoubiquitin chains or polyubiquitin chains attached to substrate proteins, preventing the substrate protein from being degraded by the ubiquitin-proteasome system. Deubiquitinases regulate cellular autophagy, metabolism and oxidative stress by acting on different substrate proteins. Recent studies have revealed that deubiquitinases act as a critical regulator in various cardiac diseases, and control the onset and progression of cardiac disease through a board range of mechanism. This review summarizes the function of different deubiquitinases in cardiac disease, including cardiac hypertrophy, myocardial infarction and diabetes mellitus-related cardiac disease. Besides, this review briefly recapitulates the role of deubiquitinases modulators in cardiac disease, providing the potential therapeutic targets in the future.