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Abstract Background Polymicrobial pulmonary infections, common in immunocompromised patients, often manifest more severe symptoms than monomicrobial infections. Clinical diagnosis delays may lead to mortality, emphasizing the importance of fast and accurate diagnosis for these patients. Metagenomic next-generation sequencing (mNGS), as an unbiased method capable of detecting all microbes, is a valuable tool to identify pathogens, particularly in cases where infections are difficult to diagnosis using conventional methods. Case presentation A 50-year-old male patient was admitted due to cough, expectoration and dyspnea. CT scan revealed diffuse inflammatory and cavernous lung lesion, and blood examination suggested a polymicrobial infection. However, no etiology was found by routine examination. mNGS of bronchoalveolar lavage fluid(BALF)simultaneously detected the presence of Pneumocystis jirovecii (P.jirovecii), Aspergillus fumigates (A.fumigates), Nocardia farcinica (N.farcinica), Salmonella enterica subsp. enterica (S.enterica subsp. enterica), and cytomegalovirus (CMV). The patient was successfully treated with compound sulfamethoxazole (SMZ-TMP), cefoperazone/sulbactam (SCF), moxifloxacin (MXF), voriconazole (VCZ), and ganciclovir. The patient recovered after two weeks of anti-infection therapy and maintained good health at a six-month follow-up. Conclusion For immunocompromised patients with multiple infections and atypical symptoms, mNGS emerged as a reliable approach to pathogen detection and guiding antibiotic therapy.

Abstract Mecoptera is a small relict order of insects within the Holometabola. Panorpidae is the most speciose family in Mecoptera. They are also known as scorpion flies due to the enlarged and upward recurved male genital bulb. Panorpa liui Hua, 1997, a member of Panorpidae, is a bivoltine species of seasonal color polyphenism in the lowland plain of northeastern China. In this study, we applied PacBio HiFi and Hi–C sequencing technologies to generate a chromosome-level genome reference of P. liui. The assembled genome is 678.26 Mbp in size, with 91.3% being anchored onto 23 pseudo–chromosomes. Benchmarking Universal Single–Copy Orthologs (BUSCO) estimation reveals the completeness of this assembly as 95.1%. By integrating full-length transcriptome and homologs of related species, we generated full annotation of this assembly, yielding a total of 15,960 protein–coding genes, of these, 15,892 genes were anchored on the 23 chromosomes. The high-quality genome provides critical genomic resources for population genetics and phylogenetic research on Mecoptera. It also offers valuable information for exploring the mechanisms underlying seasonal color polymorphism.

This study estimated population normalized mass loads (PNML) of quaternary ammonium compounds (QACs) including alkyltrimethylammonium chloride (ATMAC), benzylalkyldimethylammonium chloride (BAC), and dialkyldimethylammonium chloride (DADMAC) and assessed their associations with COVID-19 containment policies. We collected daily sludge specimens from five wastewater treatment plants in Beijing from July 2020 to May 2022. Using liquid chromatography-tandem mass spectrometry, we determined QAC concentrations and backward-estimated their PNML. We used COVID-19 Oxford Stringency Index and its metrics to measure containment policies. We analysed the relationship between QACs and containment measures using linear regression models. Among QACs categories, ΣBAC had median PNML of 94.54 μg/person/day, ΣDADMAC had 282.36 μg/person/day, and ΣATMAC had 802.55 μg/person/day. The ΣQACs median PNML was 1186.12 μg/person/day. The PNML of QACs appeared to have general increasing trend over time and were significantly different across seasons. PNML increased on average by 11 μg/person/day (95 % CI: 3.2, 19) for ΣBAC per 10-unit increase in Stringency Index score. Notably, higher stringency levels in three index indicators — workplace closures, internal movement restrictions, and public gathering restriction were positively associated with higher ΣQACs PNML. Sludge derived QACs may reflect the magnitude of disinfectant use at different stages of pandemic control response.

In order to meet the service quality requirements of emerging applications such as mobile Internet of things and intelligent logistics, with the progress of space and information technology, it has become one of the main methods to shorten the response time by deploying intelligent computing platforms in satellites for on-orbit data processing. At present, the scale of low-orbit satellites is huge, and they are often in areas that are difficult to directly measure and control, and there have many working modes, so they need the ability of independent control. Based on the introduction of the research status of the satellite intelligent computing platform, this paper analyzed the functional requirements of the satellite intelligent computing platform. On the basis of designing a set of general and open hardware architecture of satellite intelligent computing platform, this paper put forward the idea of autonomous management and control software architecture of satellite intelligent computing platform, and further described the internal composition and working principle of main control components, management and control components and collaborative components. On this basis, the key technologies related to autonomous management and control software were analyzed. Finally, the development direction of autonomous control software of satellite intelligent computing platform was prospected.

To address issues such as low availability of computing power in ultra-large scale computing clusters of intelligent computing centers, low maturity of domestically produced technologies, bottlenecks in large-scale networking efficiency, and complex operations and maintenance, a system based on cloud computing technology for constructing a ten-thousand card cluster in an intelligent computing center was proposed. A ten-thousand card cluster was constructed using 18 432 NPU units and an optimized RDMA network. A multi-plane network architecture was adopted, in conjunction with SDN technology to achieve RDMA network tenant isolation. The network load balancing strategy was optimized, resulting in a link load balancing error of less than 10% and an All-Reduce bandwidth of over 35 GB/s. By employing the optimized distributed storage protocol, the model’s breakpoint recovery time was reduced to half of its original duration. The validation results demonstrate that the domestic NPU ten-thousand card cluster, with the collaborative optimization of software and hardware, can not only meet the training needs of large models with hundreds of billions of parameters but also support the training tasks of large models with trillions of parameters.

Fei Chen,1,2,&ast; Jie Zhao,1,&ast; Rubing Mo,1 Xiuxiu Ding,1 Yue Zhang,1 Linhui Huang,1 Tian Xie,1 Yipeng Ding1 1Department of Respiratory and Critical Care Medicine, Hainan Affiliated Hospital of Hainan Medical University, Hainan General Hospital, Haikou City, Hainan Province, People’s Republic of China; 2Department of General Practice, Bai Majing Town Central Health Center, Danzhou City, Hainan Province, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yipeng Ding; Tian Xie, Department of Respiratory and Critical Care Medicine, Hainan Affiliated Hospital of Hainan Medical University, Hainan General Hospital, Haikou City, Hainan Province, People’s Republic of China, No. 19 Xiuhua Road, Xiuying District, Email ypding1961@163.com; hpphxietian@163.comBackground: Mutations in ADGRG6 are associated with a variety of cancers and multiple types of diseases. However, the impact of genetic variations in ADGRG6 on chronic obstructive pulmonary disease (COPD) susceptibility has not yet been evaluated.Methods: Considering the high prevalence of COPD among the elderly population in China, this study specifically targets the elderly Han population in Southern China as the study subject. Following the acquisition of participants’ whole-genome DNA, genotyping was conducted using the Agena MassARRAY platform. The online tool ‘SNPStats’, which utilizes logistic regression, was employed to analyze and assess the correlation. Multi-factor dimensionality reduction was utilized to clarify the impact of “SNP-SNP” interactions on COPD risk. The False-Positive Report Probability (FPRP) was applied to determine whether significant results are noteworthy findings.Results: The mutant allele “C” of rs11155242 was a protective genetic factor against COPD susceptibility (OR = 0.57, 95% CI = 0.36 to 0.91, p = 0.017). The heterozygous mutant genotype “CA” of rs11155242 was found to be significantly associated with reduced COPD risk (CA Vs AA: OR = 0.53, 95% CI = 0.32 to 0.90, p = 0.018). ADGRG6-rs11155242 was found to be strongly associated with a reduced risk of COPD in males, non-smokers, and subjects with a BMI below 24 kg/m2 (OR < 1, p < 0.05). The FPRP analysis indicated that the positive results identified in this study are noteworthy new findings.Conclusion: The mutant allele “C” and mutant genotype “CA” of rs11155242 act as protective genetic factors against COPD susceptibility. This study will provide a new research direction for the personalized prevention and treatment of COPD in the elderly Han population in southern China, and lay a potential scientific basis.Keywords: COPD, ADGRG6, genetic variants, mutant allele

To explore the role of cystic fibrosis transmembrane conduction regulator (CFTR)-Epithelial sodium channel (ENaC) in spinal cord edema after spinal cord injury (SCI) and the related mechanism.

Objective To explore the correlation between urinary mitochondrial DNA（mtDNA） and the severity and prognosis of primary membranous nephropathy（PMN）.MethodsA total of 56 patients were definitely diagnosed as PMN through renal biopsy from May 2022 to June 2023. Clinical and laboratory data were recorded. Morning mid-stream urine samples were collected for detecting the copy numbers of cytochrome-c oxidase-3（COX3） and NADH dehydrogenase subunit-1（ND1） genes in mtDNA. The correlation between baseline mtDNA copy number and nephrotic syndrome（NS） was examined through univariate and multivariate Logistic regression models. During follow-ups, Kaplan-Meier survival curves were plotted for analyzing the differential remission outcomes between high and low urinary mtDNA copy number groups.Results COX3 and ND1 copy numbers spiked in medium-risk group[COX3 = 5.532（5.318, 5.797）, ND1 = 5.575（5.270, 5.815）] and high-risk group [COX3 = 5.575（5.270, 5.815）, ND1 = 5.575（5.270, 5.815）] as compared with low-risk group[COX3 = 5.362（5.194, 5.508）, ND1 = 5.386（5.272, 5.528）]（P＜0.05）.COX3 and ND1 copy numbers were correlated positively with 24-hour urinary protein（P = 0.031, P = 0.041） and negatively with albumin（P = 0.032, P = 0.005）. The predictive value of COX3 and ND1 copy numbers in PMN with NS was examined with receiver operating characteristic（ROC） curve. And grouping was based upon optimal cutoff values of COX3 and ND1 copy numbers. The results indicated that the risk of nephrotic syndrome（NS） was higher in group with elevated COX3 and ND1 copy numbers versus group with lower copy numbers（Model 1: OR = 3.51, P = 0.019; OR = 2.89, P = 0.024）. After adjusting for age, gender, systolic blood pressure, diastolic blood pressure, anti-PLA2R antibodies and eGFR, the risk of NS remains higher in group with elevated COX3 and ND1 copy numbers（Model 3: OR = 2.65, P = 0.031; OR = 2.17, P = 0.029）. In terms of disease remission, Kaplan-Meier survival curve analysis revealed no significant correlation between COX3 and ND1 copy numbers and remission outcomes of PMN（log-rank test P = 0.630, P = 0.208）.ConclusionUrinary mtDNA is significantly higher in PMN patients of medium/high-risk group than those of low-risk group. Urinary mtDNA is associated with an elevated risk of NS in PMN patients, However, its predictive effect on disease remission requires further studies.

Abstract Background ADAM19 (ADAM Metallopeptidase Domain 19) is known to be involved in extracellular matrix (ECM) remodeling, yet its specific function in systemic sclerosis (SSc) fibrosis remains unclear. Objectives This study sought to clarify the role and underlying mechanism of ADAM19 in SSc skin fibrosis. Methods The expression of ADAM19 was assessed in skin tissues of SSc and wound healing using publicly available transcriptome datasets. This analysis was further validated through real-time PCR, western blot, and immunostaining in our SSc cohort, as well as in a mouse model of hypochlorite (HOCl)-induced fibrosis. To downregulate the expression of ADAM19, ADAM19 siRNA was employed. The influence of ADAM19 on fibroblast transcriptomics was examined using bulk RNA-seq. Data analysis and visualization were conducted using R packages, including edgeR, limma, clusterProfiler, ggplot2, gseaplot2, and complexheatmap. Results ADAM19 exhibited a significant upregulation in skin tissues of SSc patients, as well as in wound healing and a HOCl-induced fibrosis mouse model. Additionally, there was a notable positive correlation between ADAM19 and fibrosis-related genes, local skin score, Modified Rodnan skin score, skin thickness progression rate, and the presence of ARA antibodies in SSc patients. Furthermore, ADAM19 levels were markedly elevated in SSc primary dermal fibroblasts and TGF-β-stimulated healthy controls primary dermal fibroblasts. The downregulation of ADAM19 resulted in the repression of TGF-β-induced ECM deposition and fibroblast activation. ADAM19 was identified as a mediator for the shedding of neuregulin-1 (NRG1) in fibroblasts, a pro-fibrotic cytokine that must be cleaved to exert its function. Conclusion ADAM19 plays a role in TGF-β-induced ECM deposition and fibroblast activation by mediating the shedding of NRG1, ultimately contributing to the development of skin fibrosis in SSc.

Background: A quality diet and an active lifestyle are both important cornerstones of cardiovascular disease (CVD) prevention. However, despite their interlinked effects on metabolic health, the 2 behaviors are rarely considered jointly, particularly within the context of CVD prevention. We examined the independent, interactive, and joint associations of diet and physical activity with CVD hospitalization, CVD mortality, and all-cause mortality. Methods: CVD-free Australian participants aged 45–74 years (n = 85,545) reported physical activity, diet, sociodemographic, and lifestyle characteristics at baseline (2006–2009) and follow-up (2012–2015), and data were linked to hospitalization and death registries (03/31/2019 for CVD hospitalization and all-cause mortality and 12/08/2017 for CVD mortality). Diet quality was categorized as low, medium, and high based on meeting dietary recommendations. Physical activity was operationalized as (a) total moderate-to-vigorous physical activity (MVPA) as per guidelines, and (b) the composition of MVPA as the ratio of vigorous-intensity physical activity (VPA) to total MVPA. We used a left-truncated cause-specific Cox proportional hazards model using time-varying covariates. Results: During a median of 10.7 years of follow-up, 6576 participants were admitted to the hospital for CVD and 6581 died from all causes (876 from CVD during 9.3 years). A high-quality diet was associated with a 17% lower risk of all-cause mortality than a low-quality diet, and the highest MVPA category (compared with the lowest) was associated with a 44% and 48% lower risk of CVD and all-cause mortality, respectively. Multiplicative interactions between diet and physical activity were non-significant. For all outcomes, the lowest risk combinations involved a high-quality diet and the highest MVPA categories. Accounting for total MVPA, some VPA was associated with further risk reduction of CVD hospitalization and all-cause mortality. Conclusion: For CVD prevention and longevity, one should adhere to both a healthy diet and an active lifestyle and incorporate some VPA when possible.

Abstract Background Neurophobia is a global phenomenon, that influences both medical students and postgraduate trainees. We aimed to analyze the prevalence of neurophobia by conducting a systematic review and meta-analysis of studies on neurophobia, and potential associated risk factors. Methods The search was done in the PubMed, EMBASE, and Scopus databases for studies reporting neurophobia among medical students and young doctors for the period up to March 18, 2024. The overall prevalence and scores of four subcomponents of neurophobia were pooled. The potential heterogeneity was tested through meta-regression/subgroup analyses/influence analysis. Results Twenty-four studies from 30 countries met the inclusion criteria and involved 10,395 responding individuals. The estimated overall pooled prevalence of neurophobia was 46% (95%CI, 35-57%; I 2 = 98%). The result of the meta-regression revealed that geographic region was significantly associated with the prevalence (p = 0.006). The pooled scores of the four subcomponents of neurophobia were: difficulty 3.79 (95%CI, 3.47–4.12, I 2 = 99%), confidence 2.81 (95%CI, 2.39–3.24, I 2 = 99.5%), interest 3.22 (95%CI, 2.84–3.61, I 2 = 99.6%), and knowledge 2.73 (95%CI, 2.39–3.06, I 2 = 98.1%). Conclusions Neurophobia was widely prevalent among medical students and young doctors. The high prevalence and severity highlight the need for targeted interventions to reduce neurophobia.

Shuzhe Xiao,1,* Yue Ding,1,* Chen Du,1,* Yiting Lv,1 Shumei Yang,1,2 Qi Zheng,3 Zhiqiu Wang,3 Qiaoli Zheng,3 Meifang Huang,1 Qingyan Xiao,1 Zhuxiao Ren,2 Guangliang Bi,1 Jie Yang1,2 1Department of Neonatology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, People’s Republic of China; 2Department of Neonatology, Guangdong Women and Children Hospital, Guangzhou, 511442, People’s Republic of China; 3The First Clinical Medical College of Southern Medical University, Guangzhou, 510515, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jie Yang; Guangliang Bi, Email Jieyang0830@126.com; bader515@163.comBackground: Autophagy and immunity play important regulatory roles in lung developmental disorders. However, there is currently a lack of bioinformatics analysis on autophagy-related genes (ARGs) and immune infiltration in bronchopulmonary dysplasia (BPD). We aim to screen and validate the signature genes of BPD by bioinformatics and in vivo experiment.Methods: GSE8586 was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using the R program. Using cell-type identification with CIBERSORT to analyze the inflammatory and immune status of BPD. Subsequently, the hub genes were identified by Lasso and Cytoscape with three machine-learning algorithms (MCC, Degree and MCODE). In addition, hub genes were validated with ROC, single-cell sequence and IHC in hyperoxia mice. Finally, we searched the drug targets of these hub genes, and established a nomogram model for predicting the risk of BPD.Results: There were 73 the differentially expressed and autophagy-related genes (DE-ARGs) by overlapping the DEGs in GSE8586 and ARGs. Five hub genes, BRIX1, JUN, PES1, NR4A1 and RRP9, were lowly expressed in the BPD group and had high diagnostic value in the diagnostic model. All hub genes are mainly located in B cell, epithelial cell, fibroblast, endothelial cell, smooth muscle cell and pneumocyte in lung single-cell sequencing. Moreover, immune infiltration analysis showed immune cells were higher in the BPD group and were closely associated with hub genes. We also predict the drug targets of the genes. Finally, the IHC result in mice showed that expression of PES1, BRX1, RRP9, JUN, NR4A1 was lower in the hyperoxia group compared to the normoxia group.Conclusion: BRIX1, JUN, PES1, NR4A1, RRP9, may be promising therapeutic targets for BPD. Our findings provided researchers and clinicians with more evidence regarding immunotherapeutic strategies for BPD treatment.Keywords: BPD, autophagy, immune cell infiltration, single cell sequencing, biomarkers

The problem of data privacy protection in the information age deserves people’s attention. As a distributed machine learning technology, federated learning can effectively solve the problem of privacy security and data silos. Differential privacy(DP) technology is applied in federated learning(FL). By adding noise to raw data and model parameters, it can further enhance the degree of data privacy protection. Over the years, differential privacy technology based on federated learning framework has been developed, which is divided into central differential privacy federated learning(CDPFL) and local differential privacy federated learning(LDPFL). Although differential privacy may reduce the accuracy and convergence of federated learning models while protecting data privacy, researchers have proposed a variety of optimization methods to balance privacy protection and model performance. This paper comprehensively expounds the research status of differential privacy techniques based on the federated learning framework, first providing detailed introductions to federated learning and differential privacy technologies, and then summarizing the development status of two types of federated learning differential privacy(DPFL) techniques respectively; for CDPFL, the paper divides the discussion into first proposal of CDP and typical application examples, the impact of Gaussian mechanisms on model accuracy, optimization based on asynchronous differential privacy, and insights from other scholars; for LDPFL, the paper divides the discussion into first proposal of LDP and typical application examples, processing multidimensional data and improving model accuracy, existing methods and optimization for reducing communication costs, balancing privacy protection and data usability, LDPFL based on the Shuffle model, and insights from other scholars; following this, the paper addresses and summarizes the unique challenges introduced by incorporating differential privacy into federated learning and proposes solutions; finally, based on a summary of existing optimization techniques, the paper outlines future directions and specifically discusses three research ideas for enhancing the optimization effects of federated differential privacy: advanced optimization strategies combining Bayesian methods and the Alternating Direction Method of Multipliers (ADMM), integrating lattice homomorphic encryption techniques from cryptography to achieve more efficient differential privacy protection in federated learning, and exploring the application of zero-knowledge proof techniques in federated learning for privacy protection.

Texture and anisotropy control of rolled strip have always been a technical problem in titanium alloy industry, especially for near-alpha titanium alloys. In order to solve the above problems, we innovatively propose a process method for efficiently preparing weakly anisotropic alloy strips. In this paper, the texture evolution and anisotropy of TA18 titanium alloy strip under various rolling and heat treatment conditions were systematically studied by EBSD and other technical means. The results have showed that the hot-rolled TA18 titanium alloy has a distinct band microstructure along the RD. The obvious tensile properties anisotropy of hot-rolled TA18 titanium alloy is mainly due to the non-uniform microstructure formed and strong T-type micro-texture. The hot-rolled TA18 titanium alloy after 700 °C/3h heat treatment occurred complete recrystallization process, which formed the fine and uniform equiaxed grains. Texture components distribution of the titanium alloy changed from typical bimodal texture to the tendency of //normal direction (ND) base plane texture. The hot-rolled TA18 titanium alloy after heat treatment at 700 °C/3h, followed by rolling to 4.8 mm at room temperature and annealing at 730 °C/1h, could effectively reduce the anisotropy of titanium alloys. Finally, the formation of anisotropy of yield strength was considered as the different slip activation behaviors due to the influence of micro-texture orientation. This study innovatively proposes an efficient method for fabricating alloy strips with reduced anisotropy forTA18 titanium alloy strips.

Introduction: Intrahepatic cholangiocarcinoma (iCCA) is the second most common primary liver cancer after hepatocellular carcinoma. Through data mining of publicly available iCCA transcriptomic datasets from the Gene Expression Omnibus, we identified SFN as the most significantly up-regulated gene in iCCA compared to normal tissue, focusing on the Gene Ontology term ''cell proliferation'' (GO:0008283). SFN encodes the 14-3-3σ protein, also known as stratifin, which plays crucial roles in various cellular processes. Materials and methods: Immunohistochemistry was used to assess stratifin expression in 182 patients with localized iCCAs undergoing surgical resection. Patients were divided into low and high expression groups, and the association between stratifin expression and clinicopathological features was analyzed. Univariate and multivariate survival analyses were performed to assess overall survival (OS), disease-specific survival (DSS), local recurrence-free survival (LRFS), and metastasis-free survival (MeFS). Results: Elevated stratifin expression in iCCAs was significantly associated with the absence of hepatitis, positive surgical margins, advanced primary tumor stages, and higher histological grades (all p ≤ 0.011). Survival analyses demonstrated a significant negative association between stratifin expression and all prognostic indicators, including OS, DSS, LRFS, and MeFS (all p ≤ 0.0004). Multivariate analysis revealed that stratifin overexpression was significantly correlated with poorer outcomes in terms of DSS, LRFS, and MeFS (all p

Jiayi Ding,1 Xueliang Zhang,2 Le Guo,1 Jiabao Xiong,3 Chi Zhang,1 Zhong Du,3 Lijun Zhu,3 Nuernisha Alifu,1– 3 Biao Dong2,4 1Institute of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China; 2State Key Laboratory of Pathogenesis Prevention and Treatment of High Incidence Diseases in Central Asia, School of Medical Engineering and Technology Xinjiang Medical University, Urumqi, 830011, People’s Republic of China; 3Second Clinical Medical College, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China; 4State Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, 130012, People’s Republic of ChinaCorrespondence: Nuernisha Alifu, State Key Laboratory of Pathogenesis Prevention and Treatment of High Incidence Diseases in Central Asia, School of Medical Engineering and Technology Xinjiang Medical University, Urumqi, 830011, People’s Republic of China, Tel +86-18799167931, Email nens_xjmu@126.com Biao Dong, State Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, 130012, People’s Republic of China, Tel +86-13504329842, Email dongb@jlu.edu.cnPurpose: A synergistic treatment strategy of phototherapy and chemotherapy has been shown to improve efficacy and offer unique advantages over monotherapy. The purpose of this study is to explore a new nanocarrier system with liposome as the inner membrane and erythrocyte membrane as the outer membrane, which aims to realize the leak-free load of phototherapy drug indocyanine green (ICG) and chemotherapy drug doxorubicin (DOX), prolong the circulation time in vivo and improve the therapeutic effect.Patients and Methods: In this study, bilayer membrane-loaded ICG and DOX nanoparticles (RBC@ICG-DOX NPs) were prepared and characterized. For in vitro analysis, the biocompatibility and tumor inhibition properties of the nanoparticles were evaluated. For in vivo analysis, the antitumor properties of the nanoparticles were explored in a mouse subcutaneous tumor model.Results: RBC@ICG-DOX NPs were successfully prepared with strong safety and good blood compatibility, which can effectively reduce drug leakage and prolong drug circulation time in the body. In vitro performance evaluation showed that RBC@ICG-DOX NPs obtained excellent photothermal conversion ability and well reactive oxygen generation performance under near-infrared laser irradiation. Both in vitro and in vivo experiments showed well phototherapy-chemotherapy effect of RBC@ICG-DOX NPs with low toxic side effects.Conclusion: Drug delivery, imaging and tumor synergies were accomplished through combinatorial strategies as well as bilayer membrane encapsulation, opening up a new platform for the design of future tumor combination therapies.Keywords: erythrocyte membrane modification, indocyanine green, adriamycin, combination therapy, cervical cancer

Yuwei Jiang,1,&ast; Jiaoya Xu,1,2,&ast; Junyao Ding,1,&ast; Tao Liu,1 Yang Liu,1,3 Ping Huang,1 Qianlei Wang,1 Peiyong Zheng,1 Haiyan Song,1 Lili Yang1 1Institute of Digestive Diseases, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China; 2Department of Gout, Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China; 3Teaching Experiment Center, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Haiyan Song; Lili Yang, Institute of Digestive Diseases, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, 725 South Wanping Road, Shanghai, 200032, People’s Republic of China, Email songhy@126.com; yanglili76@126.comPurpose: Mitochondrial dysfunction mediated by c-Jun N-terminal kinase (JNK) plays an important role in lipotoxic liver injury in nonalcoholic steatohepatitis (NASH). This study aims to investigate the pharmacological mechanism of Jiangzhi Granule (JZG), a Chinese herbal formula against NASH, with a focus on its regulation of JNK signaling-mediated mitochondrial function.Methods: Hepatocytes were induced by palmitic acid (PA) for 24 h to establish an in vitro lipotoxic model, which was simultaneously treated with either JZG or vehicle control. Male C57BL/6J mice were fed a high-fat diet (HFD) for 22 weeks and then treated with JZG via gavage for additional 8 weeks. Lipotoxic injury in hepatocytes or mice liver tissues, as well as JNK signaling-related molecules, were further investigated.Results: JZG improved PA-induced lipid deposition, cell viability, apoptosis, and mitochondrial dysfunction in hepatocytes. In NASH mice, JZG reduced hepatosteatosis, and inflammatory infiltration, and improved mitochondrial morphology and quantity in liver tissues. Additionally, elevated phosphorylation ratio of non-receptor tyrosine kinase c-Src (Src) and reduced phosphorylation ratio of JNK and SH2-containing protein tyrosine phosphatase (SHP-1) were found in both hepatocytes and mice liver tissues treated with JZG versus those with the vehicle.Conclusion: Taken together, JZG could improve mitochondrial dysfunction and reduce lipotoxic liver injury in NASH in vivo and in vitro models. The inhibition of the JNK signaling pathway may contribute to the underlying mechanism of JZG in preventing and reversing NASH development. Keywords: nonalcoholic steatohepatitis, Jiangzhi Granule, c-Jun N-terminal kinase, mitochondrial dysfunction, lipotoxic injury

Abstract. Background:. As an essential part of health services, rehabilitation is of great significance to improve the health and quality of life of the whole population. Accelerating aging calls for a significant expansion of rehabilitation services in China, but rehabilitation needs remain unclear. We conducted the study to explore the rehabilitation needs in China and project the trend of rehabilitation needs from 2020 to 2034. Methods:. The data of health conditions that might potentially benefit from rehabilitation were obtained from Global Burden of Disease (GBD) study. Estimated annual percentage changes (EAPCs) were calculated to quantify the trends of the age-standardized rates. Projections of rehabilitation needs were made until 2034 using Bayesian age–period–cohort analysis (BAPC). Results:. Approximately 460 million persons (33.3% of the total population) need rehabilitation in China, contributing to 63 million years lived with disabilities (YLDs) in 2019. The number of prevalent cases that need rehabilitation increased from around 268 (95% uncertainty interval [UI]: 257–282) million in 1990 to almost 460 (95% UI: 443–479) million in 2019, representing an increase of 71.3%. The highest contribution to the need for rehabilitation was musculoskeletal disorders with about 322 (95% UI: 302–343) million persons in seven aggregate disease and injury categories, and hearing loss with over 95 (95% UI: 84–107) million people among 25 health conditions. Based on the projection results, there will be almost 636 million people (45% of the total population) needing rehabilitation services in China by 2034, representing an increase of 38.3%. The rehabilitation needs of neoplasms, cardiovascular diseases, and neurological disorders are expected to increase significantly from 2019 to 2034, with increases of 102.3%, 88.8% and 73.2%, respectively. Conclusions:. The need for rehabilitation in China substantially increased over the last 30 years. It is predicted that over two in five people will require rehabilitation by 2034, thus suggesting the need to develop rehabilitation services that meet individuals’ rehabilitation needs.

Objective‍ ‍To construct risk models for predicting the occurrence of high altitude de-acclimatization syndrome （HADAS） in the population returning from the plateau to the plain based on different machine learning algorithms and validate the predicting efficiency of these models. Methods‍ ‍Field or online surveys were conducted on the individuals who had ended their high-altitude living and returned to the plain areas from November 2020 to February 2024. Basic information， chronic mountain sickness （CMS）， HADAS symptoms and other data were collected. With the inclusion and exclusion criteria， totally 1 095 individuals were subjected and assigned into the modeling group. Positive events were defined as HADAS score >5. Then the modelling group was divided into a training set （n=766） and an internal test set （n=329） in a 7∶3 ratio. Least absolute shrinkage and selection operator （LASSO） regression was used to select independent variables. Risk prediction models for high-altitude adaptation symptoms were built based on 8 machine learning methods， including multiple factor logistic regression （LR）， decision tree （DT）， random forest （RF）， eXtreme gradient boosting （XGB）， support vector machine （SVM）， K-nearest neighbor （KNN）， light gradient boosting （LGB） and naïve bayes （NB）. The models were compared and evaluated using receiver operating characteristic （ROC） curves， calibration curves and confusion matrices in the internal test set. The final model was presented using a nomogram or Shapley additive explanations （SHAP） algorithm. In August 2024， another 132 individuals who returned to the plains and met the same criteria were recruited and served as the external validation group. Results‍ ‍There were 549 individuals （50.14%） out of the 1 095 subjects having HADAS symptoms. LASSO regression identified CMS score， age and duration of high-altitude residence as significant predictors. Among the 8 machine learning algorithms， the LR model was identified as the best， with an area under the curve （AUC） value of 0.819 （95%CI： 0.789~0.850） and 0.841 （95%CI： 0.799~0.884）， and an F1 score of 0.801 in the internal test set， respectively， and the AUC value and F1 score of the LR model were the largest among the 8 models in the internal test set. Spiegelhalter Z test of the calibration curve of the LR model indicated that its P=0.703 in the training set while P=0.281 in the internal test set. The AUC value of the LR model was 0.867（95%CI： 0.765~0.969） in the external validation set. Conclusion‍ ‍The LR model constructed based on indicators including CMS score， age and duration of high-altitude residence has a good overall performance in the internal test set， and good discriminating effect in the external validation set. The constructed nomogram is convenient for application.

The loss of speech function following a laryngectomy usually leads to severe physiological and psychological distress for laryngectomees. In clinical practice, most laryngectomees retain intact upper tract articulatory organs, emphasizing the significance of speech rehabilitation that utilizes articulatory motion information to effectively restore speech. This study proposed a deep learning-based end-to-end method for speech reconstruction using ultrasound tongue images. Initially, ultrasound tongue images and speech data were collected simultaneously with a designed Mandarin corpus. Subsequently, a speech reconstruction model was built based on adversarial neural networks. The model includes a pretrained feature extractor to process ultrasound images, an upsampling block to generate speech, and discriminators to ensure the similarity and fidelity of the reconstructed speech. Finally, both objective and subjective evaluations were conducted for the reconstructed speech. The reconstructed speech demonstrated high intelligibility in both Mandarin phonemes and tones. The character error rate of phonemes in automatic speech recognition was 0.2605, and tone error rate obtained from dictation tests was 0.1784, respectively. Objective results showed high similarity between the reconstructed and ground truth speech. Subjective perception results also indicated an acceptable level of naturalness. The proposed method demonstrates its capability to reconstruct tonal Mandarin speech from ultrasound tongue images. However, future research should concentrate on specific conditions of laryngectomees, aiming to enhance and optimize model performance. This will be achieved by enlarging training datasets, investigating the impact of ultrasound tongue imaging parameters, and further refining this method.

Abstract We present an analysis of lepton-jet azimuthal decorrelation in deep-inelastic scattering (DIS) at next-to-next-to-next-to-leading logarithmic (N3LL) accuracy, combined with fixed-order corrections at O α s 2 $$ \mathcal{O}\left({\alpha}_s^2\right) $$ . In this study, jets are defined in the lab frame using the anti-k T clustering algorithm and the winner-take-all recombination scheme. The N3LL resummation results are derived from the transverse-momentum dependent factorization formula within the soft-collinear effective theory, while the O α s 2 $$ \mathcal{O}\left({\alpha}_s^2\right) $$ fixed-order matching distribution is calculated using the NLOJET++ event generator. The azimuthal decorrelation between the jet and electron serves as a critical probe of the three-dimensional structure of the nucleon. Our numerical predictions provide a robust framework for precision studies of QCD and the nucleon’s internal structure through jet observables in DIS. These results are particularly significant for analyses involving jets in HERA data and the forthcoming electron-ion collider experiments.

Abstract Human-machine interaction has emerged as a revolutionary and transformative technology, bridging the gap between human and machine. Gesture recognition, capitalizing on the inherent dexterity of human hands, plays a crucial role in human-machine interaction. However, existing systems often struggle to meet user expectations in terms of comfort, wearability, and seamless daily integration. Here, we propose a handwriting recognition technology utilizing an intelligent hybrid-fabric wristband system. This system integrates spun-film sensors into textiles to form the smart fabric, enabling intelligent functionalities. A thermal encapsulation process is proposed to bond multiple spun-films without additional materials, ensuring the lightweight, breathability, and stretchability of the spun-film sensors. Furthermore, recognition algorithms facilitate precise accurate handwriting recognition of letters, with an accuracy of 96.63%. This system represents a significant step forward in the development of ergonomic and user-friendly wearable devices for enhanced human-machine interaction, particularly in the virtual world.

Abstract Background Although immunotherapy has achieved great progress in advanced triple-negative breast cancer (TNBC), there are still numerous patients who do not benefit from immunotherapy. Therefore, identification of the key molecule that induces immune escape and clarification of its specific mechanism in TNBC are urgently needed. Methods In this research, single cell sequencing and bulk sequencing were conducted for biomarker screening. Immunohistochemistry, multiplex immunofluorescence, and orthotopic TNBC tumor model were applied in identifying the key molecule driving immune escape. At the mechanical level, RNA sequencing, in vitro co-culturing system, flow cytometry, Western blotting, ELISA, and real-time qPCR were carried out. Results Mortality factor 4 like 2 (MORF4L2) expression is significantly up-regulated among patients who developed anti-PD1 resistance. MORF4L2 enhances anti-PD1 resistance by inducing the chemotaxis of macrophage infiltration and promoting their polarization towards the alternative activation phenotype (M2), thus creating an immunosuppressive microenvironment. Mechanistically, MORF4L2 actes as part of NuA4 histone acetyltransferase (HAT) complex, contributes to to histone 4 lysine 12 acetylation (H4K12Ac) and activates the downstream transcription of macrophage colony-stimulating factor (CSF1). CSF1 is secreted by tumor cells and binds to the macrophage-surface CSF1 receptor (CSF1R), which chemotactically converted and polarized macrophages to the M2 phenotype. Furthermore, we revealed that grainyhead like transcription factor 2 (GRHL2) could promote MORF4L2 transcription by binding to the MORF4L2 enhancer region. Notably, BLZ549, an inhibitor of CSF1R, restored the anti-PD1 sensitivity by blocking the GRHL2/MORF4L2/H4K12Ac/CSF1 axis. Conclusions GRHL2/MORF4L2/H4K12Ac/CSF1 axis plays an important role in anti-PD1 resistance. CSF1R inhibitors can reverse GRHL2/MORF4L2-mediated anti-PD1 resistance.

Abstract Background Enteric infections are among the most common infectious diseases. The aim of this article was to track the global trends in morbidity and mortality from enteric infections in 204 countries or territories from 1990 to 2019. Methods Data were obtained from the Global Burden of Disease 2019 study. Average annual percentage changes (AAPCs) in age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) were calculated to quantify trends in enteric infections. Age-period-cohort models were used to estimate the annual percentage changes from 0 to 4 to 80 − 84 years (local drifts), period and cohort effects between 1990 and 2019 in different socio-demographic index (SDI) regions. Results In 2019, there were 6.59 billion incident cases of enteric infections, and caused 1,748,251 deaths worldwide. From 1990 to 2019, the trend in the global ASIR of enteric infections was relatively stable, but that of ASMR declined (AAPC=-3.30, 95% confidence interval [CI]: -3.54 to -3.07), and global mortality decreased in all age groups. Meanwhile, decreasing trends in ASMR were observed in 173 countries/territories (P

Introduction: Over decades, the source-function relationships of bioactive polysaccharides have been progressively investigated, however, it is still unclear how a defined structure may conduce to the bioactivities of polysaccharides. Objectives: To explore the structure–function relationship of fungus polysaccharides, we employed a dextran sulfate sodium (DSS)‐induced colitis mouse model to compare the anti-inflammatory activity of two fungus polysaccharides from Dictyophora indusiata (DIP) and Tremella fuciformis (TFP), which exhibit distinct glycosidic linkages. Methods: The structures of DIP and TFP were characterized through molecular weight detection, molecular morphology analysis, methylation analysis, and NMR analysis. Subsequently, we employed a DSS-induced colitis model to assess the anti-inflammatory efficacy of DIP and TFP. The colitis symptoms, histological morphology, intestinal inflammatory cytokines, and the composition and function of gut microbiota before and after polysaccharides treatment in colitis mice were also investigated. Results: DIP, l,3-β-D-glucan with 1,4-β and 1,6-β-D-Glcp as branched chains, exhibited superior therapeutic effect than that of TFP consisted of a linear 1,3-α-D-mannose backbone with D-xylose and L-fucose in the side chains. Both DIP and TFP relieved DSS-induced colitis in a gut microbiota-dependent manner. Furthermore, metagenomics showed that DIP and TFP could partially reverse the bacterial function in colitis mice. Glycoside Hydrolase 1 (GH1) and GH3 were identified as being involved in hydrolyzing the glucose linkages in DIP, while GH92 and GH29 were predicted to be active in cleaving the α-1,3-linked mannose linkages and the glycosidic bonds of L-fucose residues in TFP. Conclusion: Our findings highlight the pivotal role of glycosidic linkages in anti-inflammatory activities of fungus polysaccharides and would promote the design and discovery of polysaccharides with designated activity to be used as functional foods and/or therapeutics.

Objective: The independent rôle of impulsivity in alcoholism patient’s suicidality is less elucidated. In this study, we intended to investigate how impulsivity and depression contribute to suicidality in patients with alcohol use disorder (AUD). Methods: We recruited 27 adult patients with AUD and major depressive disorder (AUD with MDD) and 33 with AUD only (AUD without MDD). We assessed suicidality, alcohol use severity, depression severity, impulsivity, and other psychiatric comorbidities. Suicidality was quantified for the frequency of previous history of suicide attempts and for current suicide intent/tendency. Impulsivity was measured using the Barratt Impulsiveness Scale (BIS). We addressed how impulsivity contributed to both suicidality indices in multiple ordinal regressions. Results: Patients with AUD with MDD versus those with AUD without MDD showed significantly higher suicidality (p < 0.001), significantly more severe alcohol (p < 0.01), significantly more polysubstance use (p < 0.05), significantly more anxiety comorbidities (p < 0.05), and significantly higher BIS scores (p < 0.001). In a better-fitting final model using regression with stepwise elimination, the BIS total score was independently and significantly associated with current suicide tendency (p < 0.05) and frequency of previous suicide attempts (p < 0.01). In contrast, the Hamilton Depression Rating Scale-17 score was significantly associated only with current suicidal tendencies (p < 0.01), but not with the frequency of previous attempts. Conclusion: Depressed patients relative to nondepressed individuals with AUD showed higher suicidality, Barratt impulsivity, and severity of alcohol use. Across groups, BIS impulsivity but not the severity of depression was found to predict suicidality. We suggest that suicide prevention efforts may include assessment of impulsivity in AUD patients.

Multi-sensor systems integrate diverse sensor data to achieve comprehensive and accurate environmental perception. However, how to effectively fuse heterogeneous data and realize the efficiency of real-time processing is still a hot and difficult issue in current research. Therefore, focusing on data fusion and arithmetic optimization of multi-source heterogeneous sensors, an innovative solution was proposed. Firstly, a data fusion system based on master-slave architecture was designed to solve the problem of multi-source heterogeneous data processing. Secondly, a three-layer "cloud-edge-end" architecture was implemented, leveraging edge servers to offload computational pressure from cloud servers, optimizing task scheduling strategies, and enabling coordinated management of network and computing resources. Finally, the delay and energy consumption requirements of tasks were modeled, and the optimization problem of minimizing system cost was constructed under resource constraints, which was transformed into Markov decision process (MDP) and solved with deep deterministic policy gradient (DDPG) algorithm. Simulation experiments show that the proposed architecture and scheduling algorithm exhibit excellent performance in reducing both latency and energy consumption, and provide a new idea for efficient data fusion and arithmetic optimization in multi-sensor systems.

With the rapid proliferation of Internet of things (IoT) devices, the frequency and intensity of attacks targeting these devices are constantly increasing. Therefore, it's quite important that security mechanisms are continuously updated to ensure the safety of IoT devices. However, as public awareness of privacy grows, many datasets are no longer shared, leading to the emergence of data silos, which hinders the improvement of IoT security. To address this issue, a federated reinforcement learning-based intrusion detection method was proposed, and experiments were conducted using two datasets from the Internet of medical things (IoMT) and Internet of vehicles (IoV) scenarios. Imbalanced traffic sample distributions were designed for each edge agent to simulate a real-world environment, allowing for the evaluation of the detection accuracy and robustness of the global model. Double deep Q-network (DDQN) was employed as the reinforcement learning framework for the edge agents, and the experimental results were evaluated using accuracy, precision, recall, and F1-score. The results demonstrate that the proposed method exhibits strong robustness and detection accuracy.

In the deep repair process of aircraft wing endplates， spoiler and other parts， the efficient removal of foam adhesive without damaging the aluminum alloy has been paid much attention in the field of aviation repair.In this study，the cured products of foam adhesive were analyzed using infrared spectroscopy and thermogravimetric analysis.Based on the swelling theory， dichloromethane was identified as the primary solvent for the adhesive remover.TiO2-modified SiO2 nanocapsules were introduced into dichloromethane as adsorbents and slow-release agents to reduce VOC emissions， extend the operating time of the adhesive remover， and improve its performance through mechanisms such as physical adsorption， physical isolation and slow release.Meanwhile， paraffin and polyethylene sheets were used as surface barriers， and Halox630 corrosion inhibitor was added to the formulation of the adhesive remover to effectively reduce the volatilization of the remover and the corrosion of the substrate.Results showed that the developed foam adhesive remover exhibited excellent degumming performance on residual foam adhesive on the surface of aluminum alloy， as well as outstanding softening and swelling effects on thermosetting adhesives.

Abstract Cancer is among the leading causes of death related diseases worldwide, and lung cancer has the highest mortality rate in the world. Transcription factors (TFs) constitute a class of structurally and functionally intricate proteins. Aberrant expression or functional deficiencies of transcription factors may give rise to abnormal gene expression, contributing to various diseases, including tumours. In this study, we propose to elucidate the potential role and mechanism of TFAP2A in NSCLC. We found that TFAP2A levels were significantly greater in tumour tissues than para-tumour tissues, and high expression of TFAP2A was associated with poor prognosis in NSCLC patients. Additionally, TFAP2A overexpression promoted NSCLC progression both in vivo and in vitro. Mechanistically, ESR2 is a potential target regulated by TFAP2A and that TFAP2A can bind to the promoter region of ESR2. Furthermore, the overexpression of both TFAP2A and ESR2 in NSCLC cells was associated with the overactivation of MAPK signalling, and the combination of PHTPP and osimertinib had a synergistic effect on suppressing tumour growth.

Abstract Sepsis, characterized as life-threatening organ dysfunction resulting from dysregulated host responses to infection, remains a significant challenge in clinical practice. Despite advancements in understanding host-bacterial interactions, molecular responses, and therapeutic approaches, the mortality rate associated with sepsis has consistently ranged between 10 and 16%. This elevated mortality highlights critical gaps in our comprehension of sepsis etiology. Traditionally linked to bacterial and fungal pathogens, recent outbreaks of acute viral infections, including Middle East respiratory syndrome coronavirus (MERS-CoV), influenza virus, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), among other regional epidemics, have underscored the role of viral pathogenesis in sepsis, particularly when critically ill patients exhibit classic symptoms indicative of sepsis. However, many cases of viral-induced sepsis are frequently underdiagnosed because standard evaluations typically exclude viral panels. Moreover, these viruses not only activate conventional pattern recognition receptors (PRRs) and retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs) but also initiate primary antiviral pathways such as cyclic guanosine monophosphate adenosine monophosphate (GMP-AMP) synthase (cGAS)-stimulator of interferon genes (STING) signaling and interferon response mechanisms. Such activations lead to cellular stress, metabolic disturbances, and extensive cell damage that exacerbate tissue injury while leading to a spectrum of clinical manifestations. This complexity poses substantial challenges for the clinical management of affected cases. In this review, we elucidate the definition and diagnosis criteria for viral sepsis while synthesizing current knowledge regarding its etiology, epidemiology, and pathophysiology, molecular mechanisms involved therein as well as their impact on immune-mediated organ damage. Additionally, we discuss clinical considerations related to both existing therapies and advanced treatment interventions, aiming to enhance the comprehensive understanding surrounding viral sepsis.

Abstract Background The modification of protein substrates by small ubiquitin-related modifier (SUMO) plays a vital role in plants subjected to biotic and abiotic stresses. However, its role in the stress responses of Brassica plants remains poorly understood. Results A genome-wide analysis revealed the presence of 30 SUMOylation genes in the Caixin genome. These results demonstrated that the Caixin genome contains all the necessary components for SUMOylation. Analysis of the cis-acting elements revealed that the promoters of SUMOylation genes presented diverse combinations of developmental and stress-related cis-regulatory elements. The RNA-seq data indicated that 23 SUMOylation genes presented relatively high expression levels under normal conditions and exhibited a notable decrease in expression following Pectobacterium carotovorum subsp. carotovorum (Pcc) infection. Additionally, dynamic alterations in SUMO conjugates were observed in response to Pcc infection. Conclusions The Caixin genome contains genes involved in SUMOylation. The majority of these genes presented multiple copies, and analyses of their transcription and protein profiles indicate that they may play a role in the response to Pcc infection.

Abstract Background We aimed to develop and validate models for predicting intensive care unit (ICU) mortality of critically ill adult patients as early as upon ICU admission. Methods Combined data of 79,657 admissions from two teaching hospitals’ ICU databases were used to train and validate the machine learning models to predict ICU mortality upon ICU admission and at 24 h after ICU admission by using logistic regression, gradient boosted trees (GBT), and deep learning algorithms. Results In the testing dataset for the admission models, the ICU mortality rate was 7%, and 38.4% of patients were discharged alive or dead within 1 day of ICU admission. The area under the receiver operating characteristic curve (0.856, 95% CI 0.845–0.867) and area under the precision-recall curve (0.331, 95% CI 0.323–0.339) were the highest for the admission GBT model. The ICU mortality rate was 17.4% in the 24-hour testing dataset, and the performance was the highest for the 24-hour GBT model. Conclusion The ADM models can provide crucial information on ICU mortality as early as upon ICU admission. 24 H models can be used to improve the prediction of ICU mortality for patients discharged more than 1 day after ICU admission.

Abstract Cranial radiation therapy (RT) for brain cancers is often associated with the development of radiation-induced cognitive dysfunction (RICD). RICD significantly impacts the quality of life for cancer survivors, highlighting an unmet medical need. Previous human studies revealed a marked reduction in plasma brain-derived neurotrophic factor (BDNF) post-chronic chemotherapy, linking this decline to a substantial cognitive dysfunction among cancer survivors. Moreover, riluzole (RZ)-mediated increased BDNF in vivo in the chemotherapy-exposed mice reversed cognitive decline. RZ is an FDA-approved medication for ALS known to increase BDNF in vivo. In an effort to mitigate the detrimental effects of RT-induced BDNF decline in RICD, we tested the efficacy of RZ in a cranially irradiated (9 Gy) adult mouse model. Notably, RT-exposed mice exhibited significantly reduced hippocampal BDNF, accompanied by increased neuroinflammation, loss of neuronal plasticity-related immediate early gene product, cFos, and synaptic density. Spatial transcriptomic profiling comparing the RT + Vehicle with the RT + RZ group showed gene expression signatures of neuroprotection of hippocampal excitatory neurons post-RZ. RT-exposed mice performed poorly on learning and memory, and memory consolidation tasks. However, irradiated mice receiving RZ (13 mg/kg, drinking water) for 6–7 weeks showed a significant improvement in cognitive function compared to RT-exposed mice receiving vehicle. Dual-immunofluorescence staining, spatial transcriptomics, and biochemical assessment of RZ-treated irradiated brains demonstrated preservation of synaptic integrity and mature neuronal plasticity but not neurogenesis and reduced neuroinflammation concurrent with elevated BDNF levels and transcripts compared to vehicle-treated irradiated brains. In summary, oral administration of RZ represents a viable and translationally feasible neuroprotective approach against RICD.

Hao Liu,1,2,&ast; Zhengze Zhang,1,2,&ast; Yuewen He,1,2 Longfei Ding,1,2 Tong Wu,1,2 Yong Wang,2,3 Wuhua Ma2 1Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People’s Republic of China; 2Department of Anesthesiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People’s Republic of China; 3State Key Laboratory of Traditional Chinese Medicine Syndrome, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Wuhua Ma; Yong Wang, Department of Anesthesiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, 16 Jichang Road, Guangzhou, Guangdong, 510405, People’s Republic of China, Tel +86 13318860680 ; +86 15920382796, Email tuesdaymorninggz@126.com; wangyong@gzucm.edu.cnPurpose: Numerous studies have identified a correlation between sleep and delirium; however, the causal relationship remains ambiguous. This bidirectional two-sample Mendelian randomization (MR) study was conducted to examine the possible causal relationships between sleep traits and delirium.Patients and Methods: Utilizing genome-wide association studies (GWAS), we identified ten sleep traits: chronotype, sleep duration, short sleep duration, long sleep duration, daytime napping, daytime sleepiness, insomnia, number of sleep episodes (NSE), sleep efficiency, and rapid eye movement sleep behavior disorder (RBD). In this MR study, genetic variants independently associated with exposures were selected as instrumental variables (IVs). To establish causal inferences, three regression models were employed—inverse variance weighted (IVW), MR Egger, and weighted median (WM) —and conducted sensitivity analyses to assess the robustness of our findings.Results: Our results suggest no significant causal association between the ten sleep traits and the risk of delirium. The reverse MR analysis revealed that delirium is associated with an increased propensity for morning chronotype [ORIVW, 1.025; 95% CI, 1.012– 1.036; p = 1.50E-05; adjusted p values (padjusted)= 1.35E-04] and a decreased risk of long sleep duration [ORIVW, 0.996; 95% CI, 0.993– 0.999; p = 0.013; padjusted= 0.059]. However, no robust evidence currently exists to substantiate a causal relationship between delirium and other sleep traits.Conclusion: Our bidirectional, two-sample MR analysis study did not provide definitive evidence that sleep traits may augment the susceptibility to delirium. However, the reverse MR results indicate that delirium may predispose patients to an earlier sleep-wake cycle. Additional large-scale investigations are necessary to examine the bidirectional causality between delirium and sleep traits.Keywords: sleep traits, delirium, Mendelian randomization analysis, genome-wide association studies

Lead-bismuth coolant in nuclear reactors generates and accumulates 210Po during operation, which has strong toxicity and high volatility. When the coolant leaks or the reactor is opened, some of the 210Po on the surface of the coolant and in the covering gas will diffuse out of the main system if not properly handled and released into the environment, posing a potential serious threat to the ecological environment and human health. The high-temperature distillation capture technology can effectively extract large amounts of 210Po from the lead-bismuth coolant. Since 210Po is an extremely toxic radioactive isotope with no stable isotope, and to facilitate the experimental study of the capture process, this study ultimately chose its isotopic cousin, Te, as a substitute for 210Po for experimental research. Measuring the trace amount of Te in the distillation capture product can provide strong support for the 210Po extraction process. In the experiment, Te was extracted from the distillation capture film using nitric acid, and the 717 strong basic anion resin was used to separate Te from the extraction solution to eliminate the interference of impurity ions. SnCl2 reduced Te4+ to Te in HCl medium, and the absorbance was measured on a spectrophotometer to obtain the content of trace Te in the sample. The influence of interfering ions in the extraction solution on the measurement value of Te was investigated; the effects of the pH of the column liquid, the concentration and amount of the elution agent, and the washing rate on the separation of Te were explored; and a spectrophotometric method for the determination of trace Te in the distillation capture product of lead-bismuth coolant was established. The results show that at room temperature, the HCl concentration of the column liquid is 4 mol/L, the eluent is ultrapure water, the washing rate is 2 mL/min. The 717 strong basic anion resin demonstrates excellent separation performance for Te across a concentration range of 0 to 10 mg/L, where the absorbance shows a strong linear correlation with Te concentration. The correlation coefficient is r2=0.999 9, with a relative standard deviation of measurement ranging from 0.3% to 2.7%(n=6). The recovery rate is between 96.0% and 101.9%. This measurement method satisfies the requirements for researching the 210Po extraction process.

Pod size is a key agronomic trait that influences peanut yield greatly. However, our understanding of the mechanisms underlying pod size is limited. In this study, we employed a segregating population derived from a cross between the small-pod line ND_S and the large-pod line ND_L to map quantitative trait loci (QTL) associated with pod size. Initial mapping performed using bulk segregant analysis revealed a candidate interval on chromosome A05 referred to as qPSW05. We refined this interval to a 256.9 kb genomic region using newly developed molecular markers. Through sequence and expression analyses, we identified the candidate gene AhXE45GC, which encodes an AN1 zinc finger protein. We discovered a 33-bp insertion in the intron of AhXE45GC in ND_S. Accessions that lack this insertion, such as ND_L, had significantly larger pods than those with the insertion, including ND_S. To facilitate marker-assisted selection for peanut pod size, we developed a molecular marker associated with this polymorphism. This marker could provide a valuable genetic resource for breeding high-yielding peanut varieties.

Xue Ding,1,&ast; Leilei Fan,2,&ast; Liran Xu,3 Xiuxia Ma,4 Pengfei Meng,4 Jie Li,4 Jiahe Li,3 Jingyu Yue4 1Department of Medicine, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China; 2Department of Cardiovascular, The First People’s Hospital of Zhengzhou, Zhengzhou, People’s Republic of China; 3Department of the First Clinical Medical College, Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China; 4Department of AIDS Clinical Research Center, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jingyu Yue, Department of AIDS Clinical Research Center, The First Affiliated Hospital of Henan University of Chinese Medicine, 19 Renmin Road, Zhengzhou, People’s Republic of China, Email yuejingyu@aliyun.comAbstract: Antiretroviral therapy can reduce human immunodeficiency virus (HIV) load to undetectable levels and restore CD4+ T cells to rebuild immune function in patients with HIV. However, some patients fail to achieve immune reconstitution despite treatment. Traditional Chinese medicine is an important branch of complementary and alternative medicine for the treatment of HIV infection, and a growing number of studies has demonstrated that traditional Chinese medicine can increase CD4+ T cell counts in patients, thereby promoting immune reconstitution, ameliorating symptoms and signs, and improving quality of life. Here, we review pathogenesis in immunological non-responders and research into their treatment with traditional Chinese medicine. Furthermore, we summarize potential future research directions, including elucidation of how traditional Chinese medicine can regulate CD4+ T cells to reduce opportunistic infections and improve quality of life in immunological non-responders.Keywords: immunological non-responders, drug mechanism, traditional Chinese medicine, future research directions

Abstract Background Evidence has revealed that oestrogen deprivation-induced osteolysis is microbiota-dependent and can be treated by probiotics. However, the underlying mechanism require further investigation. This study aims to provide additional evidence supporting the use of probiotics as an adjuvant treatment and to explore the pathophysiology of oestrogen-deprived osteolysis. Methods Forty-five SD rats were randomly divided into five groups (n = 9). Rats from four groups were ovariectomised and treated with NS, calcium, probiotics, or calcium + probiotics, while one group underwent a sham operation and was treated with NS. The osteometabolic effects were evaluated, and the mechanistic role of the probiotic supplement was explored. Results Intragastric administration of Bifidobacterium animalis subsp. lactis LPL-RH (LPL-RH) markedly suppressed osteoclastic activation and bone calcium loss by downregulating TRAP enzymatic activity, the OPG/RANKL ratio, and the downstream signalling pathway RANKL/TRAF6/NF-κB/NFATc1/TRAP in ovariectomised SD rats. LPL-RH also reduced CD4+IL-17 A+ TH17 cells in the bone marrow, the pro-osteoclastogenic cytokine IL-17 A, pro-inflammatory molecules (LPS), and its binding protein (LBP) in the blood. LPL-RH restored intestinal ZO-1, occludin, claudin 2, claudin 12, and claudin 15, which improved ileal histopathology, reduced ileal oxidative stress, and attenuated the LPS-responsive TLR4/MyD88/NF-κB pathway. Furthermore, 16 S rRNA sequencing revealed that LPL-RH altered the faecal microbiome by reducing the relative abundance of S24-7 at the family level and promoting Prevotella and Bacteroides at the genus level. Conclusion Collectively, LPL-RH suppressed osteoclastogenesis and osteolysis by modulating type 17 immunity and gut microbiome.

Abstract Evidence suggests that complex interactions among the gut microbiome, metabolic abnormalities, and brain have important etiological and therapeutic implications in major depressive disorder (MDD). However, the influence of microbiome-gut-brain cross-talk on cognitive impairment in MDD remains poorly characterized. We performed serum metabolomic profiling on 104 patients with MDD and 77 healthy controls (HCs), and also performed fecal metagenomic sequencing on a subset of these individuals, including 79 MDD patients and 60 HCs. The findings were validated in a separate cohort that included 40 patients with MDD and 40 HCs using serum-targeted metabolomics. Abnormal bile acid metabolism was observed in patients with MDD, which is related to cognitive dysfunction. The following gut microbiota corresponded to changes in bile acid metabolism and enzyme activities involved in the bile acid metabolic pathway, including Lachnospiraceae (Blautia_massiliensis, Anaerostipes_hadrus, Dorea_formicigenerans, and Fusicatenibacter_saccharivorans), Ruminococcaceae (Ruminococcus_bromii, Flavonifractor_plautii, and Ruthenibacterium_lactatiformans), and Escherichia_coli. Furthermore, a combinatorial marker classifier that robustly differentiated patients with MDD from HCs was identified. In conclusion, this study provides insights into the gut-brain interactions in the cognitive phenotype of MDD, indicating a potential therapeutic strategy for MDD-associated cognitive impairment by targeting the gut microbiota and bile acid metabolism.

Abstract Formation of granite-hosted tin deposits reflects the differentiation and maturation of continental crust. While rare in Earth’s early continental crust, the eastern Kaapvaal Craton in southern Africa may harbor the oldest known tin-bearing granites. Here we present a perspective of early continental evolution from the study of Archean detrital cassiterite from the volcano-sedimentary continental cover succession of the Dominion Group of the western Kaapvaal Craton. The cassiterites yield a concordia age of 3084.7 ± 2.3 million-year-old, representing the oldest detrital cassiterite ever found. They are enriched in hafnium, zirconium, niobium, and tantalum, depleted in tungsten, and have overall consistent δ18O values (mostly 3‒5‰) but heterogeneous δ122/118Sn values (−0.59 to 0.79‰). They likely originated from erosion of peraluminous granites, forming immediate basement of the Dominion Group. The occurrence of ~3.08 billion-year-old detrital cassiterite suggests widespread tin mineralization in the granites, the intrusion of which led to stabilization of the Kaapvaal craton.

Ke Wang,1,2,&ast; Jinlu Shang,3,&ast; Chao Tao,1,2,&ast; Mingquan Huang,4 Daiqing Wei,5 Liuxuan Yang,1 Jing Yang,1 Qingze Fan,1 Qian Ding,6 Meiling Zhou1 1Department of Pharmacy, the Affiliated Hospital, Southwest Medical University, Luzhou, People’s Republic of China; 2Department of Clinical Pharmacy, School of Pharmacy, Southwest Medical University, Luzhou, People’s Republic of China; 3Department of Pharmacy, West China Hospital Sichuan University Jintang Hospital, Chengdu, People’s Republic of China; 4Sichuan Treatment Center for Gynaecologic and Breast Diseases (Breast Surgery), the Affiliated Hospital, Southwest Medical University, Luzhou, People’s Republic of China; 5Department of Orthopaedics, the Affiliated Hospital, Southwest Medical University, Luzhou, People’s Republic of China; 6Department of Clinical Pharmacy, the Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Meiling Zhou, Department of Pharmacy, the Affiliated Hospital, Southwest Medical University, No. 25, Taiping Street, Luzhou, Sichuan, 646000, People’s Republic of China, Email meilzhou@163.com Qian Ding, Department of Clinical Pharmacy, the Third Hospital of Mianyang, Sichuan Mental Health Center, No. 190, East Section of Jiannan Road, Mianyang, Sichuan, 621000, People’s Republic of China, Email dingqian0506@163.comAbstract: Betulinic acid (BA) is a natural compound obtained from plant extracts and is known for its diverse pharmacological effects, including anti-tumor, antibacterial, anti-inflammatory, antiviral, and anti-atherosclerotic properties. Its potential in anti-tumor therapy has garnered considerable attention, particularly for the treatment of breast, lung, and liver cancers. However, the clinical utility of BA is greatly hindered by its poor water solubility, low bioavailability, and off-target toxicity. To address these issues, researchers have developed various BA-loaded nanoformulations, such as nanoparticles, liposomes, micelles, and nanofibers, aiming to improve its solubility and bioavailability, prolong plasma half-life, and enhance targeting ability, thereby augmenting its anti-cancer efficacy. In preparing this review, we conducted extensive searches in well-known databases, including PubMed, Web of Science, and ScienceDirect, using keywords like “betulinic acid”, “nanoparticles”, “drug delivery”, “tumor”, and “cancer”, covering the literature from 2014 to 2024. The review provides a comprehensive overview of recent advancements in the application of BA-loaded nano-delivery systems for anti-tumor therapy and offers insights into their future development prospects. Keywords: betulinic acid, nanoformulations, anti-tumor, bioavailability, targeting

Jia-Qing Sun,1,5,&ast; Bin Sheng,2,5,&ast; Sen Gao,2,5,&ast; Xun-Zhi Liu,2,5 Yue Cui,4,5 Zheng Peng,2,5 Xiang-Xin Chen,2,5 Peng-Fei Ding,3,5 Zong Zhuang,2,5 Ling-Yun Wu,2,5 Chun-Hua Hang,1– 5 Wei Li2– 5 1Department of Neurosurgery, Nanjing Drum Tower Hospital, Drum Tower Hospital Clinical College, Xuzhou Medical University, Nanjing, People’s Republic of China; 2Department of Neurosurgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, People’s Republic of China; 3Department of Neurosurgery, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, People’s Republic of China; 4Department of Neurosurgery, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China; 5Neurosurgery Institute of Nanjing University, Nanjing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Chun-Hua Hang; Zong Zhuang, Department of Neurosurgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, 210006, People’s Republic of China, Tel +86 25 83106666-11902 ; +86 25 83106666-11901, Email hang_neurosurgery@163.com; zhuangzong@njglyy.comPurpose: This study primarily elucidating the specific mechanism of SIRT2 on neuroinflammation and microglial pyroptosis in a mouse model of SAH.Patients and Methods: CSF were collected from 57 SAH patients and 11 healthy individuals. C57BL/6 mouse SAH model was established using prechiasmatic cistern blood injection and the in vitro hemoglobin (Hb) stimulation microglia model. Lentivirus was used as a vector for RNA interference technology to knock down the SIRT2 gene expression. Small interfering RNA was used to knockdown the expression of FOXO3a. The tools included measurements of brain water content, neurological scores, Western blot, PCR, ELISA, TEM, immunofluorescence, LDH assay, modified Garcia score, and balance beam tests to evaluate changes in pyroptosis and neuroinflammatory responses.Results: In CSF samples from SAH patients, elevated levels of SIRT2 and GSDMD were observed, with SIRT2 demonstrating particular diagnostic value for predicting prognosis at the 3-month follow-up. SIRT2 upregulation exacerbated neurological deficits, brain edema, and blood-brain barrier disruption in mice following SAH. SIRT2 increased GSDMD, caspase-1, and IL-1β/IL-18 expression, and amplified GSDMD-positive microglia. FOXO3a was also upregulated post-SAH. siRNA-mediated SIRT2 knockdown ameliorated microglial pyroptosis after SAH. FOXO3a siRNA reduced NLRP3 inflammasome activation and microglial pyroptosis severity, along with neuroinflammation post-SAH.Conclusion: In summary, SIRT2 promoted microglial pyroptosis, primarily by increasing the expression and activity of Foxo3a, thereby exacerbating neuroinflammatory damage following subarachnoid hemorrhage.Keywords: SIRT2, subarachnoid hemorrhage, FOXO3a, GSDMD, microglial pyroptosis

Fang Zhou Qu,1 Jiang Ding,2 Xi Feng An,3 Rui Peng,4 Ni He,5 Sheng Liu,1 Xin Jiang5 1Medical School, Xizang Minzu University, Xianyang, People’s Republic of China; 2Institute of Electrical Power Systems, Graz University of Technology, Graz, Austria; 3The First Affiliated Hospital of Jinan University, Guangzhou, People’s Republic of China; 4Affiliated Nanhua Hospital, University of South China, Hengyang, People’s Republic of China; 5Department of Cardiology, Shaanxi Provincial People’s Hospital, Xi’an, People’s Republic of ChinaCorrespondence: Xin Jiang, Department of Cardiology, Shaanxi Provincial People’s Hospital, Xi’an, Shanxi Province, People’s Republic of China, Email 18560453060@163.comPurpose: Heart failure (HF) is a clinical syndrome in which structural or functional abnormalities of the heart result in impaired ventricular filling or ejection capacity. In order to improve the adaptability of models to different patient populations and data situations. This study aims to develop predictive models for HF risk using six machine learning algorithms, providing valuable insights into the early assessment and recognition of HF by clinical features.Patients and Methods: The present study focused on clinical characteristics that significantly differed between groups with left ventricular ejection fractions (LVEF) [≤ 40% and > 40%]. Following the elimination of features with significant missing values, the remaining features were utilized to construct predictive models employing six machine learning algorithms. The optimal model was selected based on various performance metrics, including the area under the curve (AUC), accuracy, precision, recall, and F1 score. Utilizing the optimal model, the significance of clinical features was assessed, and those with importance values exceeding 0.8 were identified as crucial to the study. Finally, a correlation analysis was conducted to examine the relationships between these features and other significant clinical features.Results: The logistic regression (LR) model was determined to be the optimal machine learning algorithm in this study, achieving an accuracy of 0.64, a precision of 0.45, a recall of 0.72, an F1 score of 0.51, and an AUC of 0.81 in the training set and 0.91 in the testing set. In addition, the analysis of feature importance indicated that blood calcium, angiotensin-converting enzyme inhibitors (ACEI) dosage, mean hemoglobin concentration, and survival duration were critical to the study, each possessing importance values exceeding 0.8. Furthermore, correlation analysis revealed a strong relationship between blood calcium and ionized calcium (|cor|=0.99), as well as a significant association between ACEI dosage (|cor|=0.68) and left ventricular metrics (|cor|=0.58); on the other hand, no correlations were observed between mean hemoglobin levels and other clinical characteristics.Conclusion: The present study identified LR as the most effective risk prediction model for patients with HF, highlighting blood calcium, ACEI dosage, and mean hemoglobin level as significant predictors. These findings provide significant insights for the clinical prevention and early intervention of HF.Keywords: left ventricular ejection fractions, logistic regression, blood calcium, area under the curve, correlation analysis

Objective To investigate the factors affecting initial fracture (IF) in postmenopausal osteoporosis (PMOP).Methods The clinical data of PMOP patients who visited the department of orthopedics and endocrinology of Xi'an Central Hospital from January 2018 to December 2023 were retrospectively collected, and patients were divided into the IF group and non-fracture (NF) group based on their fracture history. Logistic regression was used to analyze the factors influencing the occurrence of IF in PMOP patients. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were used to explore the predictive value of relevant indicators.Results A total of 370 PMOP patients were included, with 256 in the IF group and 114 in the NF group. The incidence of IF was 69.19%. Logistic regression analysis showed that higher Johns Hopkins Fall Risk Assessment Tool (JHFRAT) scores [OR=1.339, 95%CI(1.151, 1.557)], higher neutrophil-to-lymphocyte ratio (NLR) [OR=2.163, 95%CI(1.105, 4.237)], and elevated alkaline phosphatase (ALP) levels [OR=1.014, 95%CI(1.004, 1.024)] were risk factors for IF in PMOP patients. In contrast, living in an urban area [OR=0.333, 95%CI(0.113, 0.984)], higher bone mineral density (BMD) [OR=0.609, 95%CI(0.395, 0.937)], higher systemic immune-inflammation index (SII) [OR=0.998, 95%CI(0.997, 0.999)], and higher uric acid (UA) levels [OR=0.992, 95%CI(0.987, 0.997)] were protective factors. ROC curve analysis showed that the AUC for the combined three indicators (JHFRAT score + NLR + SII) was 0.834 [95% CI (0.792, 0.876)].Conclusion In PMOP patients, higher JHFRAT scores, NLR, and ALP levels, as well as lower BMD, SII, and UA levels, increase the risk of IF. The combination of JHFRAT score, NLR, and SII has high predictive value for IF.

Objective To explore the risk factors of late postoperative pleural effusion in patients undergoing single-port thoracoscopic lung surgery, and to provide a basis for the whole-process management of surgical patients. Methods A retrospective analysis was conducted on the clinical data of 140 patients who underwent single port thoracoscopic lung surgery at the Department of Thoracic Surgery of Nanjing Chest Hospital from December 2021 to October 2022. According to the amount of pleural effusion, they were divided into four groups: no pleural effusion group (n=42), mild pleural effusion group (n=58), moderate pleural effusion group (n=11), and severe pleural effusion group (n=29). Univariate analysis and ordinal logistic regression analysis were used to compare the following variables: gender, age, body mass index, smoking history, complications, or previous history (hypertension, diabetes, coronary heart disease, tuberculosis), pleural thickening, chest adhesion, surgical technique and lymph node dissection, postoperative active breathing training, dietary habits (high protein diet, high fat diet, and average daily soup consumption). Results Univariate analysis showed that lobectomy (χ2=8.469, P=0.037), lymph node dissection (χ2=13.027, P=0.005), postoperative high protein diet (χ2=13.719, P=0.003), postoperative high fat diet (χ2=49.374, P＜0.001), and daily soup consumption (Z=30.707, P＜0.001) were associated with the amount of late postoperative pleural effusion in pulmonary surgery patients. The results of ordinal logistic regression analysis showed that high fat diet (OR=7.114, 95%CI: 3.191-15.877) and high mean daily soup consumption (OR=1.167, 95%CI: 1.062-1.283) were risk factors for late pleural effusion in patients undergoing lung surgery, while high protein diet (OR=0.229, 95%CI: 0.077-0.676) was a protective factor. Conclusion The amount of delayed pleural effusion after lung surgery is related to the early postoperative diet. Patients with a high fat diet and high daily soup consumption have a high risk of delayed pleural effusion, while high protein diet can reduce the risk of delayed pleural effusion.

Abstract Objective Evaluating the change trajectories of triglyceride‐glucose (TyG) index calculated after multiple tests in elderly heart failure (HF) patients may have clinical implications for predicting long‐term adverse cardiovascular events (MACEs). Methods This retrospective study included 1184 elderly HF (LVEF ≥50%) patients with diabetes admitted to our center between January 2015 and January 2020. Based on the multiple TyG levels detected during the exposure period with annual measurements, three distinct TyG trajectories were determined using latent mixture modeling: low‐stable group (TyG index 9.06, n = 204). The primary endpoint was the composite outcome of MACEs. Results There were significant increases in the prevalence of several cardiovascular risk factors and conditions, such as male gender, BMI, current smoker, hyperlipidemia, atrial fibrillation, old myocardial infarction, fasting glucose, triglycerides, and uric acid levels, from the Low‐Stable Group to the High‐Increasing Group (all P

Abstract This study presents a distributed electricity trading system using smart contracts to improve transaction efficiency and reduce costs in power markets. Three trading models are analyzed: centralized trading, blockchain-based decentralized trading, and smart contract-driven automated trading. The advantages and challenges of each model are examined, focusing on factors like node inclusion time, transaction costs, and price stability. The results show that the smart contract-driven model outperforms the others by increasing market efficiency, lowering transaction costs, and reducing price fluctuations. Through simulations and real-world analysis, this study provides support for using blockchain technology in power markets and offers practical advice for improving electricity trading systems. The findings suggest that the proposed system could greatly enhance transparency, efficiency, and cost-effectiveness in distributed energy markets, even in uncertain market conditions.

Sepsis is a multi-organ dysfunction syndrome caused by infection and immune dysfunction, with a high mortality rate. It affects multiple important organs such as the heart, lungs, kidneys, liver, and brain. Establishing corresponding animal models of organ dysfunction syndrome is an essential step in clarifying its pathogenesis, researching potential effective drugs, and evaluating the effectiveness and safety of treatment plans. This article first summarizes classic modeling methods for sepsis related organ injury, including the destruction of intestinal barrier tissue integrity and the implantation of pathogens or toxic drugs. The former mainly includes cecal ligation and puncture, ascending colon stent implantation, and cecal ligation incision. The latter is divided into intraperitoneal injection, intravenous injection, and intratracheal administration based on the clinical infection route being simulated. Cecal ligation and puncture and lipopolysaccharide intraperitoneal injection are the most commonly used methods. Secondly, this article summarizes the common modeling methods and evaluation methods for animal models of sepsis-induced cardiomyopathy, acute lung injury, acute kidney injury, acute liver injury, and brain dysfunction. It points out that almost all organ injuries use classic modeling methods, and different organ injury models have additional modifications according to their different pathogenesis. For example, in addition to the classic modeling methods, lipopolysaccharide instillation in the trachea is more effective in modeling acute lung injury as it better simulates lung barrier dysfunction. Cecal ligation and puncture followed by Pseudomonas instillation in the trachea in a secondary challenge model better represents sepsis-induced acute kidney injury. Intraperitoneal injection of galactosamine is a mature modeling method of sepsis-induced acute liver injury. Intracerebral injection of lipopolysaccharide is a feasible model of sepsis-associated encephalopathy. In addition to the different modeling methods, there are differences in the administration time, dosage and experimental time points according to the different experimental purposes. This article reviews the research progress of animal experimental models for sepsis-induced cardiomyopathy, acute lung injury, acute kidney injury, acute liver injury, and brain dysfunction, aiming to provide a reference for the selection of animal experimental models and optimization of experimental design.