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Abstract Background Since 2012, the World Health Organization has recommended seasonal malaria chemoprevention (SMC) with sulfadoxine-pyrimethamine plus amodiaquine (SPAQ) for children aged 3–⁠59 months in regions where malaria transmission is seasonal. Full ingestion of SMC medicines without spitting or vomiting during a complete 3-day course is critical to ensure effectiveness of SMC medicines and to avoid development of antimalarial resistance. Although evidence suggests that spitting or vomiting is not rare, there is limited analytical evidence on potential factors associated with spitting or vomiting in SMC campaigns. Methods We utilized data from SMC coverage surveys conducted in Burkina Faso, Chad, Togo and Nigeria between 2020 and 2022. Episodes of spitting or vomiting were defined as SMC-eligible children spitting out most of the dose or vomiting the entire dose within 30 min of SPAQ administration as reported by primary caregivers. We conducted a cross-sectional study using mixed-effects logistic regression with variables including household socioeconomic variables and caregiver knowledge of SMC, to identify factors associated with spitting or vomiting. Results The proportion of SMC-eligible children spitting or vomiting SPAQ doses ranged from 1.81% in Nigeria to 4.36% in Chad. The odds of spitting or vomiting were lower among children administered medicines under community distributor (CD) supervision, and whose primary caregivers had a high degree of knowledge of SMC. Spitting or vomiting were negatively associated with caregiver adherence to AQ administration and caregiver reporting of children’s adverse reactions to SMC medicines. Over half of the children experiencing a spitting or vomiting episode did not receive a replacement dose from CDs. Redosing was positively associated with caregiver educational attainment, caregiver knowledge of SMC, and directly supervised medicine administration. Conclusions CD-supervised administration of SPAQ can strengthen community engagement strategies to enhance appropriate administration and full ingestion of SMC medicines according to the SMC delivery protocol.

Abstract Behavioral and environmental risk factors are critical in the development and progression of cardiovascular disease (CVD). Understanding the molecular mechanisms underlying these risk factors will offer valuable insights for targeted preventive and therapeutic strategies. Epigenetic modifications, including DNA methylation, histone modifications, chromatin remodeling, noncoding RNA (ncRNA) expression, and epitranscriptomic modifications, have emerged as key mediators connecting behavioral and environmental risk factors to CVD risk and progression. These epigenetic alterations can profoundly impact on cardiovascular health and susceptibility to CVD by influencing cellular processes, development, and disease risk over an individual's lifetime and potentially across generations. This review examines how behavioral and environmental risk factors affect CVD risk and health outcomes through epigenetic regulation. We review the epigenetic effects of major behavioral risk factors (such as smoking, alcohol consumption, physical inactivity, unhealthy diet, and obesity) and environmental risk factors (including air and noise pollution) in the context of CVD pathogenesis. Additionally, we explore epigenetic biomarkers, considering their role as causal or surrogate indicators, and discuss epigenetic therapeutics targeting the mechanisms through which these risk factors contribute to CVD. We also address future research directions and challenges in leveraging epigenetic insights to reduce the burden of CVD related to behavioral and environmental factors and improve public health outcomes. This review aims to provide a comprehensive understanding of behavioral and environmental epigenetics in CVD and offer valuable strategies for therapeutic intervention.

Abstract Introduction Ciprofol is a novel propofol analogue with a characteristic of hemodynamic stability. At present, there is a lack of research comparing the hemodynamic stability of ciprofol and propofol during painless colonoscopy. In this study, we aim to test the hypothesis that ciprofol is superior to propofol in terms of hemodynamic stability for sedation anesthesia in patients undergoing colonoscopy. Methods A total of 222 patients were randomized into two groups. Patients in group P (n = 112) and group C (n = 110) received propofol and ciprofol sedation, respectively. Noninvasive blood pressure were monitored starting from induction (T 0) to the end of the procedure, at 2-min intervals (T 1 to T 10). Heart rate variability (HRV), pain injection, Modified Observer's Assessment of Alertness and Sedation (MOAA/S) score, body movement, doses of norepinephrine, modified Aldrete score, drug-related adverse reactions, and patient satisfaction and endoscopist satisfaction were recorded. Results In group C, fewer patients experienced a decrease in blood pressure with a higher HRV after induction sedation, the incidence of pain injection was reduced, the amount of norepinephrine dose was decreased, patient satisfaction was increased compared with group P (all P

Abstract This systematic review aimed to evaluate the effectiveness of combining radiomic and genomic models in predicting the long-term prognosis of patients with lung cancer and to contribute to the further exploration of radiomics. This study retrieved comprehensive literature from multiple databases, including radiomics and genomics, to study the prognosis of lung cancer. The model construction consisted of the radiomic and genomic methods. A comprehensive bias assessment was conducted, including risk assessment and model performance indicators. Ten studies between 2016 and 2023 were analyzed. Studies were mostly retrospective. Patient cohorts varied in size and characteristics, with the number of patients ranging from 79 to 315. The construction of the model involves various radiomic and genotic datasets, and most models show promising prediction performance with the area under the receiver operating characteristic curve (AUC) values ranging from 0.64 to 0.94 and the concordance index (C-index) values from 0.28 to 0.80. The combination model typically outperforms the single method model, indicating higher prediction accuracy and the highest AUC was 0.99. Combining radiomics and genomics in the prognostic model of lung cancer may improve the predictive performance. However, further research on standardized data and larger cohorts is needed to validate and integrate these findings into clinical practice. Critical relevance statement The combination of radiomics and genomics in the prognostic model of lung cancer improved prediction accuracy in most included studies. Key Points The combination of radiomics and genomics can improve model performance in most studies. The results of establishing prognosis models by different methods are discussed. The combination of radiomics and genomics may be helpful to provide better treatment for patients. Graphical Abstract

Abstract Resilience, the ability to maintain fundamental functionality amidst failures and errors, is crucial for complex networked systems. Most analytical approaches rely on predefined equations for node activity dynamics and simplifying assumptions on network topology, limiting their applicability to real-world systems. Here, we propose ResInf, a deep learning framework integrating transformers and graph neural networks to infer resilience directly from observational data. ResInf learns representations of node activity dynamics and network topology without simplifying assumptions, enabling accurate resilience inference and low-dimensional visualization. Experimental results show that ResInf significantly outperforms analytical methods, with an F1-score improvement of up to 41.59% over Gao-Barzel-Barabási framework and 14.32% over spectral dimension reduction. It also generalizes to unseen topologies and dynamics and maintains robust performance despite observational disturbances. Our findings suggest that ResInf addresses an important gap in resilience inference for real-world systems, offering a fresh perspective on incorporating data-driven approaches to complex network modeling.

Abstract Agent-based modeling and simulation have evolved as a powerful tool for modeling complex systems, offering insights into emergent behaviors and interactions among diverse agents. Recently, integrating large language models into agent-based modeling and simulation presents a promising avenue for enhancing simulation capabilities. This paper surveys the landscape of utilizing large language models in agent-based modeling and simulation, discussing their challenges and promising future directions. In this survey, since this is an interdisciplinary field, we first introduce the background of agent-based modeling and simulation and large language model-empowered agents. We then discuss the motivation for applying large language models to agent-based simulation and systematically analyze the challenges in environment perception, human alignment, action generation, and evaluation. Most importantly, we provide a comprehensive overview of the recent works of large language model-empowered agent-based modeling and simulation in multiple scenarios, which can be divided into four domains: cyber, physical, social, and hybrid, covering simulation of both real-world and virtual environments, and how these works address the above challenges. Finally, since this area is new and quickly evolving, we discuss the open problems and promising future directions. We summarize the representative papers along with their code repositories in https://github.com/tsinghua-fib-lab/LLM-Agent-Based-Modeling-and-Simulation .

Abstract Metabolic comorbidities, such as obesity and diabetes, are associated with subclinical alterations in both cardiac structure/function and natriuretic peptides prior to the onset of heart failure (HF). Despite this, the exact metabolic pathways of cardiac dysfunction which precede HF are not well-defined. Among older individuals without HF in the Multi-Ethnic Study of Atherosclerosis (MESA), we evaluated the associations of 47 circulating metabolites measured by 1H-NMR with echocardiographic measures of cardiac structure and function. We then evaluated associations of significant metabolites with circulating N-terminal pro-B-type natriuretic peptide (NT-proBNP). In a separate cohort, we evaluated differences between top metabolites in patients with HF with preserved ejection fraction (HFpEF) and comorbidity-matched controls. Genetic variants associated with top metabolites (mQTLs) were then related to echocardiographic measures and NT-proBNP. Among 3440 individuals with metabolic and echocardiographic data in MESA (62 ± 10 years, 52% female, 38% White), 10 metabolites broadly reflective of glucose and amino acid metabolism were associated with at least 1 measure of cardiac structure or function. Of these 10 metabolites, 4 (myo-inositol, glucose, dimethylsulfone, carnitine) were associated with higher NT-proBNP and 2 (d-mannose, acetone) were associated with lower NT-proBNP. In a separate cohort, patients with HFpEF had higher circulating myo-inositol levels compared with comorbidity-matched controls. Genetic analyses revealed that 1 of 6 known myo-inositol mQTLs conferred risk of higher NT-proBNP. In conclusion, metabolomic profiling identifies several novel metabolites associated with cardiac dysfunction in a cohort at high risk for HF, revealing pathways potentially relevant to future HF risk.

Abstract Objective To conduct a bibliometric analysis of the prospects and obstacles associated with dual- and multi-energy CT in thoracic disease, emphasizing its current standing, advantages, and areas requiring attention. Methods The Web of Science Core Collection was queried for relevant publications in dual- and multi-energy CT and thoracic applications without a limit on publication date or language. The Bibliometrix packages, VOSviewer, and CiteSpace were used for data analysis. Bibliometric techniques utilized were co-authorship analyses, trend topics, thematic map analyses, thematic evolution analyses, source’s production over time, corresponding author’s countries, and a treemap of authors’ keywords. Results A total of 1992 publications and 7200 authors from 313 different sources were examined in this study. The first available document was published in November 1982, and the most cited article was cited 1200 times. Siemens AG in Germany emerged as the most prominent author affiliation, with a total of 221 published articles. The most represented scientific journals were the “European Radiology” (181 articles, h-index = 46), followed by the “European Journal of Radiology” (148 articles, h-index = 34). Most of the papers were from Germany, the USA, or China. Both the keyword and topic analyses showed the history of dual- and multi-energy CT and the evolution of its application hotspots in the chest. Conclusion Our study illustrates the latest advances in dual- and multi-energy CT and its increasingly prominent applications in the chest, especially in lung parenchymal diseases and coronary artery diseases. Photon-counting CT and artificial intelligence will be the emerging hot technologies that continue to develop in the future. Critical relevance statement This study aims to provide valuable insights into energy-based imaging in chest disease, validating the clinical application of multi-energy CT together with photon-counting CT and effectively increasing utilization in clinical practice. Key Points Bibliometric analysis is fundamental to understanding the current and future state of dual- and multi-energy CT. Research trends and leading topics included coronary artery disease, pulmonary embolism, and radiation dose. All analyses indicate a growing interest in the use of energy-based imaging techniques for thoracic applications. Graphical Abstract

Abstract Background Obstructed labor (OL) and uterine rupture (UR) are common obstetric complications. This study explored the burden, risk factors, decomposition, and health inequalities associated with OL and UR to improve global maternal health. Methods This was a cross-sectional analysis study including data on OL and UR from the Global Burden of Diseases, and Risk Factors Study (GBD) 2019. The main outcome measures included the number and age-standardized rate (ASR) of incidence, disability-adjusted life years (DALYs), prevalence, and deaths. Results The global burden of OL and UR has declined, with a decrease in incidence (number in 2019: 9,410,500.87, 95%UI 11,730,030.94 to 7,564,568.91; ASR in 2019: 119.64 per 100,000, 95%UI 149.15 to 96.21; estimated annual percentage change [EAPC] from 1990 to 2019: -1.34, 95% CI -1.41 to -1.27) and prevalence over time. However, DALYs (number in 2019: 999,540.67, 95%UI 1,209,749.35 to 817,352.49; ASR in 2019: 12.92, 95%UI 15.63 to 10.56; EAPC from 1990 to 2019: -0.91, 95% CI -1.26 to -0.57) and deaths remain significant. ASR of DALYs increased for the 10–14 year-old age group (2.01, 95% CI 1.53 to 2.5), the 15–19 year-old age group (0.07, 95% CI -0.47 to 0.61), Andean Latin America (3.47, 95% CI 3.05 to 3.89), and Caribbean (4.16, 95% CI 6 to 4.76). Iron deficiency was identified as a risk factor for OL and UR, and its impact varied across different socio-demographic indices (SDIs). Decomposition analysis showed that population growth primarily contributed to the burden, especially in low SDI regions. Health inequalities were evident, the slope and intercept for DALYs were − 47.95 (95% CI -52.87 to -43.02) and − 29.29 (95% CI -32.95 to -25.63) in 1990, 39.37 (95%CI 36.29 to 42.45) and 24.87 (95%CI 22.56 to 27.18) in 2019. Concentration indices of ASR-DALYs were − 0.2908 in 1990 and − 0.2922 in 2019. Conclusion This study highlights the significant burden of OL and UR and emphasizes the need for continuous efforts to reduce maternal mortality and morbidity. Understanding risk factors and addressing health inequalities are crucial for the development of effective interventions and policies to improve maternal health outcomes globally.

Abstract Ferroptosis is an iron-dependent cell death form characterized by reactive oxygen species (ROS) overgeneration and lipid peroxidation. Myricetin, a flavonoid that exists in numerous plants, exhibits potent antioxidant capacity. Given that iron accumulation and ROS-provoked dopaminergic neuron death are the two main pathological hallmarks of Parkinson’s disease (PD), we aimed to investigate whether myricetin decreases neuronal death through suppressing ferroptosis. The PD models were established by intraperitoneally injecting 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) into rats and by treating SH-SY5Y cells with 1-methyl-4-phenylpyridinium (MPP+), respectively. Ferroptosis was identified by assessing the levels of Fe2+, ROS, malondialdehyde (MDA), and glutathione (GSH). The results demonstrated that myricetin treatment effectively mitigated MPTP-triggered motor impairment, dopamine neuronal death, and α-synuclein (α-Syn) accumulation in PD models. Myricetin also alleviated MPTP-induced ferroptosis, as evidenced by decreased levels of Fe2+, ROS, and MDA and increased levels of GSH in the substantia nigra (SN) and serum in PD models. All these changes were reversed by erastin, a ferroptosis activator. In vitro, myricetin treatment restored SH-SY5Y cell viability and alleviated MPP+-induced SH-SY5Y cell ferroptosis. Mechanistically, myricetin accelerated nuclear translocation of nuclear factor E2-related factor 2 (Nrf2) and subsequent glutathione peroxidase 4 (Gpx4) expression in MPP+-treated SH-SY5Y cells, two critical inhibitors of ferroptosis. Collectively, these data demonstrate that myricetin may be a potential agent for decreasing dopaminergic neuron death by inhibiting ferroptosis in PD.

Abstract During early embryonic development, the transition from totipotency to pluripotency is a fundamental and critical process for proper development. However, the regulatory mechanisms governing this transition remain elusive. Here, we conducted a comprehensive genome-wide CRISPR/Cas9 screen to investigate the 2-cell-like cells (2CLCs) phenotype in mouse embryonic stem cells (mESCs). This effort led to the identification of ten regulators that play a pivotal role in determining cell fate during this transition. Notably, our study revealed Mdm2 as a significant negative regulator of 2CLCs, as perturbation of Mdm2 resulted in a higher proportion of 2CLCs. Mdm2 appears to influence cell fate through its impact on cell cycle progression and H3K27me3 epigenetic modifications. In summary, the results of our CRISPR/Cas9 screen have uncovered several genes with distinct functions in regulating totipotency and pluripotency at various levels, offering a valuable resource for potential targets in future molecular studies.

BACKGROUND: Hemorrhagic shock (HS) causes severe organ damage, worsened by high-altitude conditions with lower oxygen and temperatures. Existing research lacks specific insights on brain and heart damage under these conditions. This study hypothesizes that high-altitude and cold (HAC) environments exacerbate HS-induced damage in the brain and heart, aiming to improve treatment strategies. MATERIALS AND METHODS: Twenty-four male Sprague-Dawley (SD) rats (200–250 g of weight) were randomly assigned into sham, HS + normal, HS + HAC (4,000 m), and HS + HAC (6,000 m). The HS model was established in SD rats (35% loss of total blood volume), and histopathological injuries of the brain and heart were detected using hematoxylin and eosin staining, Sirius red staining, and immunohistochemistry. Apoptosis of the brain and heart tissues was detected by terminal transferase-mediated dUTP nick end labeling (TUNEL) immunofluorescence staining. To determine the levels of tumor necrosis factor-α (TNF-α), interferon-gamma (IFN-γ), monocyte chemoattractant protein-1 (Mcp-1), BCL2-associated X (BAX), and myeloid cell leukemia-1 (Mcl-1) protein, western blotting assay was used. RESULTS: The HAC environment induced pathological damage to the brain and heart and aggravated the degree of cardiac fibrosis in HS rats. However, it did not cause apoptosis of the brain and heart. In addition, it upregulated TNF-α, IFN-γ, Mcp-1, and BAX protein levels, but downregulated Mcl-1 protein levels (P < 0.05). CONCLUSIONS: The HAC environment aggravated the degree of brain and heart damage in HS rats, which may be related to neuron nucleus pyknosis, myocardial fibrosis, and inflammatory and apoptosis activation.

Abstract Background and purpose The persistent progression of pneumonia is a critical determinant of adverse outcomes in patients afflicted with COVID-19. This study aimed to predict personalized COVID-19 pneumonia progression between the duration of two weeks and 1 month after admission by integrating radiological and clinical features. Methods A retrospective analysis, approved by the Institutional Review Board, encompassed patients diagnosed with COVID-19 pneumonia between December 2022 and February 2023. The cohort was divided into training and validation groups in a 7:3 ratio. A trained multi-task U-Net network was deployed to segment COVID-19 pneumonia and lung regions in CT images, from which quantitative features were extracted. The eXtreme Gradient Boosting (XGBoost) algorithm was employed to construct a radiological model. A clinical model was constructed by LASSO method and stepwise regression analysis, followed by the subsequent construction of the combined model. Model performance was assessed using ROC and decision curve analysis (DCA), while Shapley’s Additive interpretation (SHAP) illustrated the importance of CT features. Results A total of 214 patients were recruited in our study. Four clinical characteristics and four CT features were identified as pivotal components for constructing the clinical and radiological models. The final four clinical characteristics were incorporated as well as the RS_radiological model to construct the combined prediction model. SHAP analysis revealed that CT score difference exerted the most significant influence on the predictive performance of the radiological model. The training group’s radiological, clinical, and combined models exhibited AUC values of 0.89, 0.72, and 0.92, respectively. Correspondingly, in the validation group, these values were observed to be 0.75, 0.72, and 0.81. The DCA curve showed that the combined model exhibited greater clinical utility than the clinical or radiological models. Conclusion Our novel combined model, fusing quantitative CT features with clinical characteristics, demonstrated effective prediction of COVID-19 pneumonia progression from 2 weeks to 1 month after admission. This comprehensive model can potentially serve as a valuable tool for clinicians to develop personalized treatment strategies and improve patient outcomes.

With the rapid development of the Internet, digital technology is increasingly integrating into the modern circulation system. The influence mechanisms of land prices on the development of the circulation industry are gradually transforming. Using data from 104 major cities in China from 2003 to 2021, this study uses the panel two-way fixed effects model, moderating effects model and threshold regression method to examine the mechanisms by which land prices affect the circulation industry development and the moderating role of Internet development. The results show that elevated land prices significantly stimulate the growth of the circulation industry, leading to an expansion in the circulation industry scale, optimization of its structure, and enhancement of its facilities. The findings remain robust even after addressing endogeneity concerns and conducting various robustness tests. Moreover, the impact of high land prices on the circulation industry is more pronounced in small and medium-sized cities group as well as central region cities group. Real estate investment and industrial structure upgrading are the key channels through which high land prices promote the development of the circulation industry. Additionally, Internet development has a positive moderating effect on the promotion that high land prices stimulate the development of the circulation industry. Notably, only when Internet development surpasses a certain threshold that the promotional effect of land prices on the circulation industry development be fully realized. Based on the above conclusions, the government should continue to deepen the market-oriented reform of land elements, implement precise industrial policy support for the circulation industry and promote circulation digital transformation.

IntroductionWith the accelerating process of globalization, trade activities have had profound impacts on both the environment and economic development.MethodsThis paper comprehensively evaluates the synergistic effect of bilateral trade on “pollution reduction” and “carbon mitigation,” as well as “economic growth,” utilizing panel data from China and RCEP countries spanning the period from 1997 to 2020.ResultsThe empirical results reveal that bilateral trade significantly propels economic growth in RCEP countries and exhibits a positive “pollution reduction” effect, whereas its “carbon reduction” effect remains uncertain. To delve into the underlying reasons for bilateral trade’s failure to effectively mitigate carbon emissions, this paper undertakes a mechanism test along two opposing paths. Notably, the influence of bilateral trade on economic growth and “pollution reduction” in RCEP countries varies regionally. Specifically, bilateral trade is more efficacious in fostering economic growth in ASEAN countries. Additionally, bilateral trade enhances environmental quality in ASEAN countries, yet it deteriorates in non-ASEAN countries. Furthermore, this paper examines the intricate relationship between bilateral trade, economic growth, and “pollution reduction” through the application of the PVAR model. It concludes that optimizing environmental quality in RCEP countries is conducive to both local economic growth and bilateral trade.ConclusionThis study not only bears significant implications for understanding the complex interplay between economic growth, environmental quality, trade liberalization, and environmental policies, but also provides invaluable guidance for policy formulation and implementation aimed at achieving green transformation and fostering sustainable economic development.

Chemotherapy and radiotherapy in combination with sequence regimens are recognized as the current major strategy for suppressing postoperative tumor recurrence. However, systemic side effects and poor in-field cooperation of the two therapies seriously impair the therapeutic efficacy of patients. The combination of brachytherapy and chemotherapy through innovative biomaterials has proven to be an important strategy to achieve synergistic effects of radiotherapy and chemotherapy in-time and in-field. However, for postoperative chemoradiotherapy, as far as we know, there are few relevant reports. Herein, an injectable pH-responsive polypeptide-polysaccharide depot for concurrent in situ chemotherapy and brachytherapy was developed by encapsulating vincristine into iodine-125 radionuclide labeled hydrogel. This depot hydrogel was prepared by dynamic covalent bonds of Schiff base between aldehydeated hyaluronic acid and polyethylene glycol-polytyrosine. Therefore, this hydrogel enables smart response to tumor acidic microenvironment, rapid release of the encapsulated vincristine and an enhanced uptake effect by tumor cells, which significantly reduces IC50 of vincristine for the anaplasia Wilms' tumor cells in vitro. This depot hydrogel shows excellent stability and biocompatibility, and maintains for 14 days after in situ injection in a postoperative model of anaplasia Wilms' tumor. After injection at the cavity of tumor excision, responsively-released vincristine and the radioactive iodine-125 exerted excellent killing effects on residual tumor cells, inhibiting tumor relapse and liver metastasis of the recurrent tumor. Hence, this study proposes an effective therapeutic strategy for inhibiting anaplasia Wilms’ tumor recurrence, which provides a new approach for concurrent postoperative chemo-radiotherapy and a desirable guidance in regimen execution of pediatric refractory tumors.

Water bodies are crucial components of urban ecology. The development of rapid and timely water-quality assessment tools using easily measured variables is essential for the health management of urban water bodies. In this study, we focused on the dissolved oxygen (DO) of Baiyangdian Lake using 251 sets of empirically measured water quality data and corresponding Sentinel-2 satellite images. Nine machine learning algorithms were then used to develop a rapid detection algorithm for the spatial distribution of the DO concentration in Baiyangdian Lake. This study successfully applied these methods to invert the DO concentration in Baiyangdian Lake during spring, summer, and autumn. The results indicated that extra tree regression (ETR) provided the most accurate and stable results for inverting the DO concentration among the nine machine learning methods. In contrast, AdaBoost regression (ABR), Bayesian ridge regression (BRR), and support vector machines (SVM) exhibit relatively poor regression performance and lack sensitivity to DO concentrations. Moreover, the DO concentration in Baiyangdian Lake ranged from approximately 0 to 12 mg/L, with notable spatiotemporal variations. The highest overall DO concentration was observed in the spring, particularly in the southern region. The DO concentration significantly decreased during summer compared to that in spring, with higher values in the southwestern area and lower values in the northern region. The DO concentration reached its lowest value in autumn, with slightly higher values in the southern region. This study focused on the estimation and inversion of DO concentrations in the water bodies of Baiyangdian Lake. By introducing and comparing the performances of commonly used machine learning models, a rapid estimation of the DO concentration was achieved, thereby overcoming the limitations of traditional water quality monitoring methods in DO inversion. It not only intuitively explained the temporal and spatial variation patterns of DO concentration but also laid a foundation for further in-depth exploration of the interactions between DO and other water quality parameters.

Abstract Aging and regeneration represent complex biological phenomena that have long captivated the scientific community. To fully comprehend these processes, it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions. Conventional omics methodologies, such as genomics and transcriptomics, have been instrumental in identifying critical molecular facets of aging and regeneration. However, these methods are somewhat limited, constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations. The advent of emerging spatiotemporal multi-omics approaches, encompassing transcriptomics, proteomics, metabolomics, and epigenomics, furnishes comprehensive insights into these intricate molecular dynamics. These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells, tissues, and organs, thereby offering an in-depth understanding of the fundamental mechanisms at play. This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research. It underscores how these methodologies augment our comprehension of molecular dynamics, cellular interactions, and signaling pathways. Initially, the review delineates the foundational principles underpinning these methods, followed by an evaluation of their recent applications within the field. The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field. Indubitably, spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration, thus charting a course toward potential therapeutic innovations.

Abstract Background The application of radiomics in thoracic lymph node metastasis (LNM) of lung adenocarcinoma is increasing, but diagnostic performance of radiomics from primary tumor to predict LNM has not been systematically reviewed. Therefore, this study sought to provide a general overview regarding the methodological quality and diagnostic performance of using radiomic approaches to predict the likelihood of LNM in lung adenocarcinoma. Methods Studies were gathered from literature databases such as PubMed, Embase, the Web of Science Core Collection, and the Cochrane library. The Radiomic Quality Score (RQS) and the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) were both used to assess the quality of each study. The pooled sensitivity, specificity, and area under the curve (AUC) of the best radiomics models in the training and validation cohorts were calculated. Subgroup and meta-regression analyses were also conducted. Results Seventeen studies with 159 to 1202 patients each were enrolled between the years of 2018 to 2022, of which ten studies had sufficient data for the quantitative evaluation. The percentage of RQS was between 11.1% and 44.4% and most of the studies were considered to have a low risk of bias and few applicability concerns in QUADAS-2. Pyradiomics and logistic regression analysis were the most commonly used software and methods for radiomics feature extraction and selection, respectively. In addition, the best prediction models in seventeen studies were mainly based on radiomics features combined with non-radiomics features (semantic features and/or clinical features). The pooled sensitivity, specificity, and AUC of the training cohorts were 0.84 (95% confidence interval (CI) [0.73–0.91]), 0.88 (95% CI [0.81–0.93]), and 0.93(95% CI [0.90–0.95]), respectively. For the validation cohorts, the pooled sensitivity, specificity, and AUC were 0.89 (95% CI [0.82–0.94]), 0.86 (95% CI [0.74–0.93]) and 0.94 (95% CI [0.91–0.96]), respectively. Conclusions Radiomic features based on the primary tumor have the potential to predict preoperative LNM of lung adenocarcinoma. However, radiomics workflow needs to be standardized to better promote the applicability of radiomics. Trial registration CRD42022375712.

Tetanus toxin (TeNT) is one of the most toxic proteins. Neutralizing antibodies against TeNT are effective in prevention and treatment. In this study, 14 anti-tetanus nanobodies were obtained from a phage display nanobody library by immunizing a camel with the C-terminal receptor-binding domain of TeNT (TeNT-Hc) as the antigen. After fusion with the human Fc fragment, 11 chimeric heavy-chain antibodies demonstrated nanomolar binding toward TeNT-Hc. The results of toxin neutralization experiments showed that T83–7, T83–8, and T83–13 completely protected mice against 20 × the median lethal dose (LD50) at a low concentration. The neutralizing potency of T83–7, T83–8, and T83–13 against TeNT is 0.4 IU/mg, 0.4 IU/mg and 0.2 IU/mg, respectively. In the prophylactic setting, we found that 5 mg/kg of T83–13 provided the mice with full protection from tetanus, even when they were injected 14 days before exposure to 20 × LD50 TeNT. T83–7 and T83–8 were less effective, being fully protective only when challenged 7 or 10 days before exposure, respectively. In the therapeutic setting, 12 h after exposure to TeNT, 1 ~ 5 mg/kg of T83–7, and T83–8 could provide complete protection for mice against 5 × LD50 TeNT, while 1 mg/kg T83–13 could provide complete protection 24 h after exposure to 5 × LD50 TeNT. Our results suggested that these antibodies represent prophylactic and therapeutic activities against TeNT in a mouse model. The T83–7, T83–8, and T83–13 could form the basis for the subsequent development of drugs to treat TeNT toxicity.

Aba Prefecture is a prominent Tibetan inhabited area with profound Tibetan Buddhist sites that need to be protected. This study demonstrates that the value of religious sites lies in their terrain-based nature with perceptions by people, and advocates to interpret and preserve them from the religious landscape perspective. Using geographic data and online geo-tagged images, geographical and visual characteristics of religious landscapes in Aba Prefecture are drawn with the support of MaxEnt and FCN models. The results of the two models are cross-validated and complimented, to ensure that the analyzed religious landscape is interpreted in religious atmosphere, geographic context, and visual perception. Further, this study provides region-specific preservation proposals for religious landscapes in Aba Prefecture and a transferable preservation framework for religious landscapes in other regions.

Global regional conflicts are on the rise, threatening both local and global stability and development. This article used monthly and daily nighttime light (NTL) imagery from December 2021 to April 2022 to analyze NTL dynamics during the initial period of the Russia–Ukraine conflict at the national and subnational (oblast and city) levels. In addition, a novel method was proposed to quantify the direct impact of the conflict at the pixel level. In this study, a new conflict effect index (CEI) was constructed to distinguish conflict-damaged area (CDA) and conflict-recovered area (CRA) and to quantify the direct damage and subsequent recovery caused by the conflict. The results indicate that the outbreak of the conflict led to a significant decrease in NTL intensity of about 56% across Ukraine. The pixel-level CEI indicated that the onset of the conflict had a broad impact across Ukraine, with the affected area shrinking as the conflict progressed. Damaged areas accounted for 12% of Ukraine at the start of the conflict, but decreased at an average rate of 2963.25 km2/day over the following week, while the size of recovered areas peaked at 9258.75 km2 during the conflict, but decreased to a low of 3750 km2. The maximum rate of change in the area of the CDA and CRA was −67% and 135%, respectively. The study demonstrates that NTL data can capture the direct destruction of conflict and help to support humanitarian relief and postdisaster reconstruction efforts.

With the increasing demand for DC transmission from new energy sources and the increasing DC load, the original AC distribution network system cannot meet the demand for power transmission, and AC-DC distribution network has become one of the development directions of future distribution network. When photovoltaic system is connected to AC/DC distribution system, unplanned island operation may occur on both AC and DC sides of the system. When unplanned islanding occurs in the system, maintenance personnel and system equipment fail to detect islanding in time and operate normally, which may pose a great threat to the safety of equipment and personnel. Therefore, it is necessary to accurately identify the operating state of the system, and then provide accurate judgment information for the action of the micro-switch to operate the photovoltaic system with islanding phenomenon through the micro-switch integrated with islanding detection algorithm, so as to ensure the safety and stability of the distribution system and load. In order to identify the running state of the system reliably, this paper analyzes the changes of the system electrical quantity before and after the islanding, and based on this, puts forward an islanding detection method. First of all, this paper uses a variety of data preprocessing techniques to clean and extract the features of the original data, and selects six island characteristic indicators such as voltage, current and output active power as detection features to generate a feature vector set to improve the quality and accuracy of the data. Secondly, this paper adopts three classification algorithms, including KNN, random forest and XGBoost, to integrate and learn the model, so as to improve the accuracy and robustness of the islanding detection task. Finally, it is verified by experiments that the islanding detection method based on multi-classification fusion model proposed in this paper has high fault detection accuracy and robustness, and has a wide application prospect and popularization value in practical application, which can provide performance improvement and stability guarantee for micro-cluster switches.

Abstract Background Prognosis is critically important in stroke cases, with angiogenesis playing a key role in determining outcomes. This study aimed to investigate the potential protective effects of Atractylenolide I (Atr I), Atractylenolide III (Atr III), and Paeoniflorin (Pae) in promoting angiogenesis following cerebral ischemia. Methods The bEnd.3 cell line was used to evaluate the effects of these three compounds on vascular endothelial cell proliferation, migration, and tube formation. Male C57BL/6 mice underwent transient middle cerebral artery occlusion (MCAO), followed by daily intragastric administration of the Chinese medicine compounds to assess their impact on brain protection and angiogenesis. In vivo experiments included measuring infarct size and assessing neurological function. Immunofluorescence staining and an angiogenesis antibody array were used to evaluate angiogenesis in ischemic brain tissue. Functional enrichment analysis was performed to further investigate the pathways involved in the protective effects of the compounds. Molecular docking analysis explored the potential binding affinity of the compounds to insulin-like growth factor 2 (IGF-2), and Western blotting was used to measure levels of angiogenesis-related proteins. Results In vitro, the combination of Atr I, Atr III, and Pae enhanced cell proliferation, promoted migration, and stimulated tube formation. In vivo, the combined treatment significantly facilitated neurological function recovery and angiogenesis by day 14. The treatment also increased levels of angiogenesis-related proteins, including IGF-2. Pearson correlation analysis revealed a strong positive association between IGF-2 levels in ischemic brain tissue and angiogenesis, suggesting a good affinity of the compounds for the IGF-2 binding site, as supported by molecular docking analysis. Conclusion The administration of Atr I, Atr III, and Pae has shown significant enhancements in long-term stroke recovery in mice, likely due to the promotion of angiogenesis via increased activation of the IGF-2 pathway in ischemic brain tissue. Graphical Abstract

BackgroundThe association between body mass index (BMI) and rapid eye-movement (REM) sleep-related behavioral disorder (RBD) in Parkinson’s disease (PD) remains unknown. Our study was to investigate the association of BMI with RBD in PD patients.MethodsIn this cross-sectional study, a total of 1,115 PD participants were enrolled from Parkinson’s Progression Markers Initiative (PPMI) database. BMI was calculated as weight divided by height squared. RBD was defined as the RBD questionnaire (RBDSQ) score with the cutoff of 5 or more assessed. Univariable and multivariable logistic regression models were performed to examine the associations between BMI and the prevalence of RBD. Non-linear correlations were explored with use of restricted cubic spline (RCS) analysis. And the inflection point was determined by the two-line piecewise linear models.ResultsWe identified 426 (38.2%) RBD. The proportion of underweight, normal, overweight and obese was 2.61, 36.59, 40.36, and 20.44%, respectively. In the multivariate logistic regression model with full adjustment for confounding variables, obese individuals had an odds ratio of 1.77 (95% confidence interval: 1.21 to 2.59) with RBD compared with those of normal weight. In the RCS models with three knots, BMI showed a non-linear association with RBD. The turning points of BMI estimated from piecewise linear models were of 28.16 kg/m2, 28.10 kg/m2, and 28.23 kg/m2 derived from univariable and multivariable adjusted logistic regression models. The effect modification by depression on the association between BMI and RBD in PD was also found in this study. Furthermore, the sensitivity analyses linked with cognition, education, and ethnic groups indicated the robustness of our results.ConclusionThe current study found a significant dose–response association between BMI and RBD with a depression-based difference in the impact of BMI on RBD in PD patients.

This paper presents a framework for interpreting regional features of houses in the Tibetan-Qiang region by Deep Learning (DL) and Image Landscape (IL), which learns the typical features from online building photos in different subordinate areas of the whole region through a set of datasets and DL models. The contribution of this framework is taking online building images as a proxy of rural building characteristics, which significantly improves the scope and efficiency of related built heritage studies and accurately reveals the representative features of houses in remote rural areas. The results are validated by established studies, and the framework can be transferred to other regions through the provided path and openly published datasets.

BackgroundBotulinum neurotoxin (BoNT) produced by Clostridium botulinum is one of the most potent known toxins. Moreover, BoNT is classified as one of the most important biological warfare agents that threatens the biosafety of the world. Currently, the approved treatment for botulism in humans is the use of polyvalent horse serum antitoxins. However, they are greatly limited because of insufficient supply and adverse reactions. Thus, treatment of human botulism requires the development of effective toxin-neutralizing antibodies. Considering their advantages, neutralizing nanobodies will play an increasing role as BoNTs therapeutics.MethodsHerein, neutralizing nanobodies binding to the heavy chain (Hc) domain of BoNT/B (BHc) were screened from a phage display library. Then, BoNT/B-specific clones were identified and fused with the human Fc fragment (hFc) to form chimeric heavy chain antibodies. Finally, the affinity, specificity, and neutralizing activity of antibodies against BoNT/B in vivo were evaluated.ResultsThe B5-hFc, B9-hFc and B12-hFc antibodies demonstrated high affinity for BHc in the nanomolar range. The three antibodies were proven to have potent neutralizing activity against BoNT/B in vivo.ConclusionThe results demonstrate that inhibiting toxin binding to the host receptor is an efficient strategy and the three antibodies could be used as candidates for the further development of drugs to prevent and treat botulism.

IntroductionSeasonal human coronavirus NL63 (HCoV-NL63) is a frequently encountered virus linked to mild upper respiratory infections. However, its potential to cause more severe or widespread disease remains an area of concern. This study aimed to investigate a rare localized epidemic of HCoV-NL63-induced respiratory infections among pediatric patients in Guilin, China, and to understand the viral subtype distribution and genetic characteristics.MethodsIn this study, 83 pediatric patients hospitalized with acute respiratory infections and positive for HCoV-NL63 were enrolled. Molecular analysis was conducted to identify the viral subgenotypes and to assess genetic variations in the receptor-binding domain of the spiking protein.ResultsAmong the 83 HCoV-NL63-positive children, three subgenotypes were identified: C4, C3, and B. Notably, 21 cases exhibited a previously unreported subtype, C4. Analysis of the C4 subtype revealed a unique amino acid mutation (I507L) in the receptor-binding domain of the spiking protein, which was also observed in the previously reported C3 genotype. This mutation may suggest potential increases in viral transmissibility and pathogenicity.DiscussionThe findings of this study highlight the rapid mutation dynamics of HCoV-NL63 and its potential for increased virulence and epidemic transmission. The presence of a unique mutation in the C4 subtype, shared with the C3 genotype, raises concerns about the virus’s evolving nature and its potential public health implications. This research contributes valuable insights into the understanding of HCoV-NL63’s epidemiology and pathogenesis, which is crucial for effective disease prevention and control strategies. Future studies are needed to further investigate the biological significance of the observed mutation and its potential impact on the virus’s transmissibility and pathogenicity.

IntroductionAging is a complex, time-dependent biological process that involves a decline of overall function. Over the past decade, the field of intestinal microbiota associated with aging has received considerable attention. However, there is limited information surrounding microbiota-gut-brain axis (MGBA) to further reveal the mechanism of aging.MethodsIn this study, locomotory function and sensory function were evaluated through a series of behavioral tests.Metabolic profiling were determined by using indirect calorimetry.16s rRNA sequence and targeted metabolomics analyses were performed to investigate alterations in the gut microbiota and fecal short-chain fatty acids (SCFAs). The serum cytokines were detected by a multiplex cytokine assay.The expression of proinflammatory factors were detected by western blotting.ResultsDecreased locomotor activity, decreased pain sensitivity, and reduced respiratory metabolic profiling were observed in aged mice. High-throughput sequencing revealed that the levels of genus Lactobacillus and Dubosiella were reduced, and the levels of genus Alistipes and Bacteroides were increased in aged mice. Certain bacterial genus were directly associated with the decline of physiological behaviors in aged mice. Furthermore, the amount of fecal SCFAs in aged mice was decreased, accompanied by an upregulation in the circulating pro-inflammatory cytokines and increased expression of inflammatory factors in the brain.DiscussionAging-induced microbial dysbiosis was closely related with the overall decline in behavior, which may attribute to the changes in metabolic products, e.g., SCFAs, caused by an alteration in the gut microbiota, leading to inflammaging and contributing to neurological deficits. Investigating the MGBA might provide a novel viewpoint to exploring the pathogenesis of aging and expanding appropriate therapeutic targets.

Summary: Histone deacetylases (HDACs) regulate gene expression and innate immunity. Previously, we showed that HDAC5 is degraded during Vaccinia virus (VACV) infection and is a restriction factor for VACV and herpes simplex virus type 1. Here, we report that HDAC5 promotes interferon regulatory factor 3 (IRF3) activation downstream of Toll-IL-1 receptor (TIR) domain-containing adaptor molecule-1 or Sendai virus-mediated stimulation without requiring HDAC activity. Loss of HDAC5-mediated IRF3 activation is restored by re-introduction of HDAC5 but not HDAC1 or HDAC4. The antiviral activity of HDAC5 is antagonized by VACV protein C6 and orthologs from the orthopoxviruses cowpox, rabbitpox, camelpox, monkeypox, and variola. Infection by many of these viruses induces proteasomal degradation of HDAC5, and expression of C6 alone can induce HDAC5 degradation. Mechanistically, C6 binds to the dimerization domain of HDAC5 and prevents homodimerization and heterodimerization with HDAC4. Overall, this study describes HDAC5 as a positive regulator of IRF3 activation and provides mechanistic insight into how the poxviral protein C6 binds to HDAC5 to antagonize its function.

Abstract Objective Antibody-drug conjugates (ADCs) that target human epidermal growth factor receptor 2 (HER2) are leading a new era of targeted cancer therapy. These drugs have also been associated with several fatal adverse events, such as pneumonia, interstitial lung disease, and infection. We performed a meta-analysis of randomized controlled trials (RCTs) to estimate the incidence and risk of fatal adverse events in cancer patients treated with HER2-targeted ADCs. Methods We performed a systematic search in Embase, PubMed, Web of Science, and Scopus databases from inception to February 1, 2022, and the last search was updated to July 1, 2023. The eligible studies for inclusion in our analysis were limited to RCTs of HER2-targeted ADCs that were approved by the US Food and Drug Administration and examined on cancer patients with available data on fatal adverse events. The protocol for this study was registered in PROSPERO (No. CRD42022331627). Results Fifteen studies (13 RCTs) involving 7,277 patients were finally included for meta-analysis. Of these patients, 4,246 received HER2-targeted ADCs and 3,481 received the control treatment. The data were combined using Bayesian hierarchical modeling, which allowed for the estimation of the mean incidence of fatal adverse events to be 0.78% (95% CrI: 0.28-1.37%, τ = 0.006) for the patients treated with HER2-targeted ADCs. The relative risk was 0.80 (95% CrI, 0.5–1.26, τ = 0.17) compared to control patients. Among 43 reported deaths caused by HER2-targeted ADCs, the most common fatal adverse event was respiratory toxicity, including pneumonia, pneumonitis, and interstitial lung disease. On subgroup analysis, no difference in the risk of fatal adverse events was found between different HER2-targeted ADCs or cancer types. Conclusion Our findings suggest that the risk of fatal adverse events with HER2-targeted ADCs may be lower compared to standard control therapies in cancer patients, and there is no significant difference in risk observed between different HER2-targeted ADCs or cancer types. However, the most common fatal adverse event was respiratory toxicity, suggesting that cancer patients who use the above drugs should strengthen respiratory system monitoring and take preventive measures in some severe cases.

Abstract Cancer therapeutic vaccine can induce antigen-specific immune response, which has shown great potential in cancer immunotherapy. As the key factor of vaccine, antigen plays a central role in eliciting antitumor immunity. However, the insufficient antigen delivery and low efficiency of antigen presentation by dendritic cells (DCs) have greatly restricted the therapeutic efficiency of vaccine. Here we developed a kind of DC hybrid zinc phosphate nanoparticles to co-deliver antigenic peptide and photosensitive melanin. Owing to the chelating ability of Zn2+, the nanoparticles can co-encapsulate antigenic peptide and melanin with high efficiency. The nanovaccine showed good physiological stability with the hydration particle size was approximately 30 nm, and zeta potential was around − 10 mV. The nanovaccine showed homologous targeting effect to DCs in vivo and in vitro, efficiently delivering antigen to DCs. Meanwhile, the nanovaccine could effectively reflux to the tumor-draining lymph nodes. When combined with near-infrared irradiation, the nanovaccine induced effective mild heat in vitro and in vivo to promote antigen presentation. After administrating to MC38 tumor-bearing mice, the hybrid nanovaccine effectively promoted the maturation of DCs, the expansion of cytotoxic T lymphocytes and helper T cells, and the secretion of immunostimulatory cytokines, thereby significantly inhibiting tumor growth. Graphical Abstract

Abstract Autonomic symptoms (AS) are critical in Parkinson’s disease (PD). We aimed to determine the relative significance of clinical factors allowing predictions about incidence of AS, and examine AS profiles among PD patients by motor subtype and its relation to AS. The cross-sectional data of a multicentre sample, including 714 PD patients and 194 healthy controls from Parkinson’s Progression Marker Initiative study and Pingchan granule study were analyzed, stratified by PD subtypes [postural instability and gait disturbances (PIGD), tremor dominant (TD), and indeterminate] and domain autonomic dysfunction. Compared with healthy controls, PD patients scored higher in the total Scales for Outcomes in Parkinson's Disease-Autonomic dysfunction score and in several domain scores in particular, and there was a significant overlap in domain AS. Risk factors of individual domain autonomic dysfunction were heterogeneous. PIGD and indeterminate were the predominant subtypes in pupillomotor and thermoregulatory symptoms. TD and indeterminate were more likely to suffer from cardiovascular problem. The odd in sexual dysfunction was significant for PIGD. Gastrointestinal and urinary symptoms seemed not to be associated with a specific subtype. Our study demonstrated that AS were highly heterogeneous and 3 subtypes differed in autonomic performance, providing clues to understand mechanisms underlying AS in PD.

To explore the effects of different water-saving treatments on rice plant growth and select suitable water-saving irrigation strategies for aerobic rice varieties, we conducted relevant field experiments from June to October 2023 at Jiangsu Runguo Agricultural Development Co., Ltd., China, which is located in a north subtropical monsoon climate where the soil is alkaline sandy loam. Four water treatments were set up, including the control of local conventional irrigation (CK, without water stress), mild water-saving treatment (W1, 20% more water saved than CK), moderate water-saving treatment (W2, 30% more water saved than CK), and severe water-saving treatment (W3, 40% more water saved than CK). The experiment results showed that rice plant heights were inhibited and leaf chlorophyll contents increased under all water-saving treatments compared to CK. Among them, the MDA content in paddy leaves under the W1 treatment decreased, while the activities of SOD and POD were enhanced and the membrane lipid peroxidation capacity of rice was also enhanced. Meanwhile, the results showed that the rice yield and quality under the W1 treatment significantly improved. Based on those experiments, a comprehensive evaluation of rice plant height, chlorophyll content, grain yield, yield components, and rice quality was conducted using the TOPSIS entropy weight method. It was preliminarily concluded that the suitable irrigation scheme for south and central Jiangsu was 20% water-saving irrigation compared with CK. In summary, under the premise of maintaining the economic yield of rice cultivation, an appropriate water irrigation plan helped save water resources and promote rice growth.

Abstract The respiratory system’s complex cellular heterogeneity presents unique challenges to researchers in this field. Although bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) have provided insights into cell types and heterogeneity in the respiratory system, the relevant specific spatial localization and cellular interactions have not been clearly elucidated. Spatial transcriptomics (ST) has filled this gap and has been widely used in respiratory studies. This review focuses on the latest iterative technology of ST in recent years, summarizing how ST can be applied to the physiological and pathological processes of the respiratory system, with emphasis on the lungs. Finally, the current challenges and potential development directions are proposed, including high-throughput full-length transcriptome, integration of multi-omics, temporal and spatial omics, bioinformatics analysis, etc. These viewpoints are expected to advance the study of systematic mechanisms, including respiratory studies.

Abstract Background To investigate the impact of the coronavirus disease 2019 (COVID-19) outbreak on the prevalence of respiratory viruses among pediatric patients with acute respiratory infections in Xuzhou from 2015–2021. Methods Severe acute respiratory infection (SARI) cases in hospitalized children were collected from 2015–2021 in Xuzhou, China. Influenza virus(IFV), respiratory syncytial virus (RSV), human parainfluenza virus type 3(hPIV-3), human rhinovirus (hRV), human adenovirus(hAdV), human coronavirus(hCoV) were detected by real-time fluorescence polymerase chain reaction(RT-qPCR), and the results were statistically analyzed by SPSS 23.0 software. Results A total of 1663 samples with SARI were collected from 2015–2021, with a male-to-female ratio of 1.67:1 and a total virus detection rate of 38.5% (641/1663). The total detection rate of respiratory viruses decreased from 46.2% (2015–2019) to 36% (2020–2021) under the control measures for COVID-19 (P 0.05). After the control measures, the detection rate of hPIV-3 decreased in all age groups, and the detection rate of hCoV increased in all except the 1 ~ 3 years old group. Conclusions Implementing control measures for COVID-19 outbreak curbed the spread of respiratory viruses among children as a whole. However, the epidemic of RV and RSV was not affected by the COVID-19 control policy.

Abstract Background Hemophagocytic lymphohistiocytosis (HLH) is a rare and life-threatening disorder characterized by systemic inflammation and organ failure as a result of dysregulated immune cell activation. HLH can be induced by a variety of factors including infection, tumours and autoimmune disease and can also occur in patients following solid organ transplantation. Occurrence of HLH and lupus nephritis (LN) successively within a short period of time after renal transplantation is uncommon. Case presentation We described an 11-year-old female post-transplant patient who presented with hemocytopenia, fever, elevated serum ferritin, splenomegaly, hyperlipidemia, and hypofibrinemia, and was clinically diagnosed with HLH. After comprehensive treatment with corticosteroids, intravenous immunoglobulin (IVIG), and reducing immunosuppressants, her condition improved, but then hematuria ensued. The transplant kidney biopsy showed LN. She was treated with hydroxychloroquine and methylprednisolone while intensive immunosuppressive agents were given. She has remained in remission for two years until now. Conclusions The main inducing factors of HLH should be identified as early as possible, and accurate treatment plans should be taken. The long-course IVIG regimen may be one of the effective treatments for virus-induced HLH. After remission of HLH, we need to be alert to the recurrence of autoimmune diseases in patients with underlying diseases, and timely increase immunosuppressants.

Glioblastoma multiforme is one of the most common primary tumors of the central nervous system, with a very poor prognosis. Cancer cells have been observed to upregulate pH regulators, such as monocarboxylate transporters (MCTs), with an increase in MCT4 expression being observed in several malignancies. MCT4/ recombinant cluster of differentiation 147 (CD147) transporter complex was reported to stimulate vascular endothelial growth factor (VEGF) via the phosphatidylinositol 3 kinase (PI3K) /protein kinase B (Akt) pathway, which has been proven to mediate glioblastoma invasion and migration. The present study aimed to clarify the role of the MCT4/CD147 transporter complex in glioblastoma cell proliferation, migration, and invasion. In this work, lentiviral vectors were used to overexpress MCT4/CD147 and small interfering RNA (siRNA) was used to silence MCT4/CD147 in the human glioma cell lines U87 and U251, respectively. The effects on cell proliferation, migration and invasiveness, as well as the protein expression levels of MCT4 and CD147, extracellular lactate content and Akt activation were assessed by MTT, wound-healing and invasion assays, western blotting and colorimetric method, respectively. The analysis results suggested that cell proliferation, migration, invasion, and Akt activation were decreased by siRNA in all cell lines, but were increased by lentivirus-mediated MCT4 overexpression. These findings suggest that inhibiting the activity and expression of the MCT4/CD147 transporter complex via metabolic-targeting drugs, particularly in cells with a high rate of glycolysis, should be explored as a novel strategy for glioblastoma treatment.

The deep sea is one of the least-explored ecosystems on Earth. Deep-sea virus communities are crucial components of this ecosystem and play crucial roles in food webs and biogeochemical cycles. Viruses that infect bacteria and archaea in the deep sea regulate microbial abundance and community structure, thereby influencing nutrient cycling throughout the deep sea and extending to the global ocean. By manipulating microbial communities through cell lysis, viruses promote the release of organic carbon and enhance the host’s ability to adapt to extreme environments through the expression of auxiliary metabolic genes during host infection. This adaptation enables virus to thrive in the deep sea via lysogenic life strategies. However, our knowledge of deep-sea viruses remains limited. This review explores the importance of viruses in deep-sea ecosystems, focusing on their community structure, diversity, interactions with host cells, ecological functions, and impacts on biogeochemical cycles. It also highlights current challenges in deep-sea virology and provides prospects for future research into deep-sea viruses.

Cardiometabolic disorders encompass a broad range of cardiovascular complications associated with metabolic dysfunction. These conditions have an increasing share in the health burden worldwide due to worsening endemic of hypertension, obesity, and diabetes. Previous studies have identified Tumor Protein p53-inducible Nuclear Protein 2 (Trp53inp2) as a molecular link between hyperglycemia and cardiac hypertrophy. However, its role in cardiac pathology has never been determined in vivo. In this study, we generated a cardiac specific knockout model of Trp53inp2 (Trp53inp2-cKO) and investigated the impact of Trp53inp2 inactivation on the pathogenesis of heart failure under mechanic or/and metabolic stresses. Based on echocardiography assessment, inactivation of Trp53inp2 in heart led to accelerated onset of HFrEF in response to pressure-overload, with significantly reduced ejection fraction and elevated heart failure marker genes comparing to the control mice. In contrast, inactivation of Trp53inp2 ameliorated cardiac dysfunction induced by combined stresses of high fat diet and moderate pressure overload (Cardiometabolic Disorder Model). Moreover, Trp53inp2 inactivation led to reduced expression of glucose metabolism genes in lean, pressure-overloaded hearts. However, the same set of genes were significantly induced in the Trp53inp2-cKO hearts under both mechanical and metabolic stresses. In summary, we have demonstrated for the first time that cardiomyocyte Trp53inp2 has diametrically differential roles in the pathogenesis of heart failure and glucose regulation under mechanical vs. mechanical plus metabolic stresses. This insight suggests that Trp53inp2 may exacerbate the cardiac dysfunction during pressure overload injury but have a protective effect in cardiac diastolic function in cardiometabolic disease.

Objective: To explore the potential imaging biomarkers for predicting Traditional Chinese medicine (TCM) deficiency and excess syndrome in prostate cancer (PCa) patients by radiomics approach based on MR imaging. Methods: A total of 121 PCa patients from 2 centers were divided into 1 training cohort with 84 PCa patients and 1 validation cohort with 37 PCa patients. The PCa patients were divided into deficiency and excess syndrome group according to TCM syndrome differentiation. Radiomic features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging and apparent diffusion coefficient images originated from diffusion-weighted imaging. A radiomic signature was constructed after reduction of dimension in training group by the minimum redundancy maximum relevance and the least absolute shrinkage and selection operator. The performance of the model was evaluated by receiver operating characteristic (ROC) curve and calibration curve. Results: The radiomic scores of PCa with TCM excess syndrome group were statistically higher than those of PCa with TCM deficiency syndrome group among T2WI, diffusion-weighted imaging and apparent diffusion coefficient imaging models. The area under ROC curves for T2WI, diffusion-weighted imaging and apparent diffusion coefficient imaging models were 0.824, 0.824, 0.847 in the training cohort and 0.759, 0.750, 0.809 in the validation cohort, respectively. The apparent diffusion coefficient imaging model had the best discrimination in separating patients with TCM excess syndrome and deficiency syndrome, and its accuracy was 0.788, 0.778 in the training and validation cohort, respectively. The calibration curve demonstrated that there was a high consistency between the prediction of radiomic scores and the actual classification of TCM's deficiency and excess syndrome in PCa. Conclusion: The radiomic signature based on MR imaging can be performed as a non-invasive, potential approach to discriminate TCM deficiency syndrome from excess syndrome in PCa, in which apparent diffusion coefficient imaging model has the best diagnostic efficiency.

Abstract This research proposes a deep-learning paradigm, termed functional learning (FL), to physically train a loose neuron array, a group of non-handcrafted, non-differentiable, and loosely connected physical neurons whose connections and gradients are beyond explicit expression. The paradigm targets training non-differentiable hardware, and therefore solves many interdisciplinary challenges at once: the precise modeling and control of high-dimensional systems, the on-site calibration of multimodal hardware imperfectness, and the end-to-end training of non-differentiable and modeless physical neurons through implicit gradient propagation. It offers a methodology to build hardware without handcrafted design, strict fabrication, and precise assembling, thus forging paths for hardware design, chip manufacturing, physical neuron training, and system control. In addition, the functional learning paradigm is numerically and physically verified with an original light field neural network (LFNN). It realizes a programmable incoherent optical neural network, a well-known challenge that delivers light-speed, high-bandwidth, and power-efficient neural network inference via processing parallel visible light signals in the free space. As a promising supplement to existing power- and bandwidth-constrained digital neural networks, light field neural network has various potential applications: brain-inspired optical computation, high-bandwidth power-efficient neural network inference, and light-speed programmable lens/displays/detectors that operate in visible light.

Abstract Background Liver fibrosis and hepatocellular carcinogenesis secondary to liver fibrosis are serious liver diseases with no effective treatments. Mori fructus aqueous extracts (MFAEs) have served as successful treatments for many types of liver injury including fibrosis although the molecular mechanisms are unknown at present. Purpose To investigate the effect of MFAEs in alleviating acute and chronic liver injury and tried to decipher the underlying mechanism. Methods and results Mice were divided into 5 groups (n = 8) for acute (groups: control, 0.3% CCl4, bifendate (BD), 100 and 200 mg/kg MFAEs, 7 d) and chronic (groups: control, 10% CCl4, BD, 100 and 200 mg/kg MFAEs, 4 weeks) liver injury study. Each mouse was injected intraperitoneally with 10 µL/g corn oil containing CCl4 expect the control group. HepG2 cells were used in vitro study. Eighteen communal components were identified by UPLC-LTQ-Orbitrap-MS. We utilized a mouse model for acute and chronic liver injury using CCl4 and MFAEs administration effectively blocked fibrosis and significantly inhibited inflammation in the liver. MFAEs activated the nuclear factor erythroid derived 2 like 2/heme oxygenase 1 (Nrf2/HO-1) pathway and promoted the synthesis of the antioxidants glutathione (GSH), superoxidedismutase (SOD) and glutathione peroxidase (GSH-Px) that resulted in reduced levels of CCl4-induced oxidative stress molecules including reactive oxygen species. These extracts administered to mice also inhibited ferroptosis in the liver by regulating the expression of Acyl-CoA synthetase long chain family member 4 (ACSL4), solute carrier family 7 member 11 (SLC7A11) and glutathione peroxidase 4 (GPX4), thus reducing the occurrence of liver fibrosis. Both in vivo and in vitro tests indicated that the mechanism of MFAEs protection against liver fibrosis was linked to activation of Nrf2 signaling. These effects were blocked in vitro by the addition of a specific Nrf2 inhibitor. Conclusion MFAEs inhibited oxidative stress, ferroptosis and inflammation of the liver by activating Nrf2 signal pathway and provided a significant protective effect against CCl4-induced liver fibrosis. Graphical Abstract

Wheat plants are impacted by Fusarium head blight (FHB) infection, which poses a huge threat to wheat growth, development, storage and food safety. In this study, a fungal strain was isolated from diseased wheat plants and identified as Fusarium asiaticum F1, known to be a member of the Fusarium graminearum species complex, agents causally responsible for FHB. In order to control this disease, new alternatives need to be developed for the use of antagonistic bacteria. Bacillus velezensis E2 (B. velezensis E2), isolated from a previous investigation in our laboratory, showed a notable inhibitory effect on F. asiaticum F1 growth and deoxynivalenol (DON) synthesis in grains. The spore germination of F. asiaticum F1 was significantly reduced and the spores showed vesicular structures when treated with B. velezensis E2. Observations using scanning electron microscopy (SEM) showed that the hyphae of F. asiaticum F1 were shrunken and broken when treated with B. velezensis E2. The RNA-seq results of F1 hyphae treated with B. velezensis E2 showed that differentially expressed genes (DEGs), which were involved in multiple metabolic pathways such as toxin synthesis, autophagy process and glycan synthesis, especially the genes associated with DON synthesis, were significantly downregulated. In summary, those results showed that B. velezensis E2 could inhibit F. asiaticum F1 growth and reduce the gene expression of DON synthesis caused by F1. This study provides new insights and antagonistic mechanisms for the biological control of FHB during wheat growth, development and storage.

Creative social enterprises are increasingly emerging in rural regions, motivated by a desire to take social responsibility through creative approaches. These enterprises integrate entrepreneurial activities with creative social attributes and are sometimes set in rural collaborative workspaces (CWSs) facilitating entrepreneurial activities. Under the frame of entrepreneurial ecosystems (EEs), we argue that CWSs can be seen as brokers, who (1) link resources as liaisons, (2) hold and pass resources as gatekeepers, (3) enhance resource flows as coordinators, and (4) reproduce experiences as representatives. Against this backdrop, this paper presents a case study of two creative social enterprises in a CWS with a cooperative structure in rural Upper Austria by analyzing entrepreneurial biographies about the demand and use of entrepreneurial resources. Through a comparison between before and after the emergence of the CWS, the findings suggest that the EE for creative and social entrepreneurship undergoes two different types of transformation, a radical and a gradual one. The brokerage process of the CWS enhances local resource networks’ transformation of EE and brings the transformation in terms of translocal resources and integral EE of enterprises in the CWS. Additionally, the CWS generates social impacts on the local community through social enterprises. This paper contributes to ecosystem literature by introducing an actor-centric perspective and giving new insights into social entrepreneurship and the transformative power of CWSs as brokers.

With the changing global climate, drought stress will pose a considerable challenge to the sustainable development of agriculture in arid regions. The objective of this study was to explore the resistance and water demand of cotton plants to water stress during the flowering and boll setting stage. The experimental plot was in Huaxing Farm of Changji city. The plots were irrigated, respectively, at 100% (as the control), 90%, 85% and 80% of the general irrigation amount in the local area. The relationship between the various measured indexes and final yield under different deficit irrigation (DI) treatments was studied. The results showed that deficit irrigation impacted the growth and development processes of cotton during the flowering and boll setting stage. There was a high negative correlation (R2 > 0.95) between the maximum leaf area index and yield. Similarly, there was a high correlation between malondialdehyde content and yield. Meanwhile, 90% of the local cotton irrigation contributed to water saving and even increasing cotton yield. Furthermore, based on the results, the study made an initial optimization to the local irrigation scheme by utilizing the DSSAT model. It was found that changing the irrigation interval to 12 days during the stage could further enhance cotton yield and conserve resources.

Pulmonary fibrosis (PF) is a major public health issue with limited treatment options. As the active ingredient of the n-butanol extract of Amygdalus mongolica (BUT), amygdalin inhibits PF. However, its mechanisms of action are unclear and need further verification. Therefore, the purpose of the present studies was to investigate the anti-fibrotic effects of BUT on PF by serum metabolomics and the transforming growth factor β (TGF-β) pathway. Sixty male Sprague-Dawley rats were randomly divided into control, untreated PF, prednisone-treated (5 mg/kg), and BUT-treated (1.75, 1.25, 0.75 g/kg) groups, and the respective drugs were administered intragastrically for 21 days. The serum metabolomics profiles were determined by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) and metabolism network analysis. The expression of TGF-β1, Smad-3, Smad-7, and α-smooth muscle actin (α-SMA) was measured using a real-time polymerase chain reaction in the lung tissue. BUT significantly alleviated fibrosis by reducing the mRNA expressions of TGF-β1 (from 1.73 to 1.13), Smad-3 (from 2.01 to 1.19), and α-SMA (from 2.14 to 1.19) and increasing that of Smad7 (from 0.17 to 0.62). Twenty-eight potential biomarkers associated with PF were identified. In addition, four key biomarkers were restored to baseline levels following BUT treatment, with the lowest dose showing optimal effect. Furthermore, A. mongolica BUT was found to improve PF by the pentose phosphate pathway and by taurine, hypotaurine, and arachidonic acid metabolism. These findings revealed the mechanism of A. mongolica BUT antifibrotic effects and metabolic activity in PF rats and provided the experimental basis for its clinical application.

ABSTRACT The N4-like viruses, which were recently assigned to the novel viral family Schitoviridae in 2021, belong to a podoviral-like viral lineage and possess conserved genomic characteristics and a unique replication mechanism. Despite their significance, our understanding of N4-like viruses is primarily based on viral isolates. To address this knowledge gap, this study has established a comprehensive N4-like viral data sets comprising 342 high-quality N4-like viruses/proviruses (144 viral isolates, 158 uncultured viruses, and 40 integrated N4-like proviruses). These viruses were classified into 97 subfamilies (89 of which are newly identified), 148 genera (100 of which are newly identified), and 253 species (177 of which are newly identified). The study reveals that N4-like viruses inhibit the polar region, oligotrophic open oceans, and the human gut, where they infect various bacterial lineages, such as Alpha/Beta/Gamma/Epsilon-proteobacteria in the Proteobacteria phylum. Although N4-like viral endogenization appears to be prevalent in Proteobacteria, it has also been observed in Firmicutes. Additionally, the phylogenetic analysis has identified evolutionary divergence within the hallmark genes of N4-like viruses, indicating a complex origin of the different conserved parts of viral genomes. Moreover, 1,101 putative auxiliary metabolic genes (AMGs) were identified in the N4-like viral pan-proteome, which mainly participate in nucleotide and cofactor/vitamin metabolisms. Of these AMGs, 27 were found to be associated with virulence, suggesting their potential involvement in the spread of bacterial pathogenicity. Importance The findings of this study are significant, as N4-like viruses represent a unique viral lineage with a distinct replication mechanism and a conserved core genome. This work has resulted in a comprehensive global map of the entire N4-like viral lineage, including information on their distribution in different biomes, evolutionary divergence, genomic diversity, and the potential for viral-mediated host metabolic reprogramming. As such, this work significantly contributes to our understanding of the ecological function and viral-host interactions of bacteriophages.

Summary: Since the successful approval of gemtuzumab ozogamicin, antibody-drug conjugates (ADCs) have emerged as a pivotal category of targeted therapies for cancer. Among these ADCs, the use of monomethyl auristatin E (MMAE) as a payload is prevalent in the development of ADC drugs, which has significantly improved overall therapeutic efficacy against various malignancies. However, increasing clinical observations have raised concerns regarding the potential nervous system toxicity associated with MMAE-based ADCs. Specifically, a higher incidence of peripheral neuropathy has been reported in ADCs incorporating MMAE as payloads. Considering the increasing global use of MMAE-based ADCs, it is imperative to provide an inclusive overview of diagnostic and management strategies for this adverse event. In this review, we examine current information and what future research directions are required to better understand and manage this type of clinical challenge.