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Abstract Sulfur-containing units are fundamental components widely found in bioactive compounds, prompting notable efforts toward developing synthetic methodologies for incorporating sulfur functionality into organic precursors. The synthesis of sulfinate esters and sulfinamides has garnered significant interest owing to their immense potential for applications, especially in drug development. However, most existing synthetic protocols suffer from some limitations. To address these challenges, we herein present a practical and efficient approach for the reductive sulfinylation of diverse nucleophiles with sulfonylpyridinium salts (SulPy) through the nucleophilic chain substitution, namely SNC reaction, which involves S(VI) to S(IV) nucleophilic chain isomerization process. These versatile sulfinylation reagents can be readily accessed from diverse commercially available resourses. The late-stage modification of complex molecules and the ability to rapidly synthesize numerous sulfinyl bioisosteres of various drugs highlights the utility of this protocol.

Abstract Background Teat number is one of the most important indicators to evaluate the lactation performance of sows, and increasing the teat number has become an important method to improve the economic efficiency of farms. Therefore, it is particularly important to deeply analyze the genetic mechanism of teat number traits in pigs. In this study, we detected Single Nucleotide Ploymorphism (SNP), Insertion-Deletion (InDel) and Structural variant (SV) by high-coverage whole-genome resequencing data, and selected teat number at birth and functional teat number as two types of teat number traits for genome-wide association study (GWAS) to reveal candidate genes associated with pig teat number traits. Results In this study, we used whole genome resequencing data from 560 Yorkshire sows to detect SNPs, InDels and SVs, and performed GWAS for the traits of born teat number and functional teat number, and detected a total of 85 significant variants and screened 214 candidate genes, including HEG1, XYLT1, SULF1, MUC13, VRTN, RAP1A and NPVF. Among them, HEG1 and XYLT1 were the new candidate genes in this study. The co-screening and population validation of multiple traits suggested that HEG1 may have a critical effect on the born teat number. Conclusion Our study shows that more candidate genes associated with pig teat number traits can be identified by GWAS with different variant types. Through large population validation, we found that HEG1 may be a new key candidate gene affecting pig teat number traits. In conclusion, the results of this study provide new information for exploring the genetic mechanisms affecting pig teat number traits and genetic improvement of pigs.

Spiking Neural Network (SNN) simulation is very important for studying brain function and validating the hypotheses for neuroscience, and it can also be used in artificial intelligence. Recently, GPU-based simulators have been developed to support the real-time simulation of SNN. However, these simulators’ simulating performance and scale are severely limited, due to the random memory access pattern and the global communication between devices. Therefore, we propose an efficient distributed heterogeneous SNN simulator based on the Sunway accelerators (including SW26010 and SW26010pro), named SWsnn, which supports accurate simulation with small time step (1/16 ms), randomly delay sizes for synapses, and larger scale network computing. Compared with existing GPUs, the Local Dynamic Memory (LDM) (similar to cache) in Sunway is much bigger (4 MB or 16 MB in each core group). To improve the simulation performance, we redesign the network data storage structure and the synaptic plasticity flow to make most random accesses occur in LDM. SWsnn hides Message Passing Interface (MPI)-related operations to reduce communication costs by separating SNN general workflow. Besides, SWsnn relies on parallel Compute Processing Elements (CPEs) rather than serial Manage Processing Element (MPE) to control the communicating buffers, using Register-Level Communication (RLC) and Direct Memory Access (DMA). In addition, SWsnn is further optimized using vectorization and DMA hiding techniques. Experimental results show that SWsnn runs 1.4−2.2 times faster than state-of-the-art GPU-based SNN simulator GPU-enhanced Neuronal Networks (GeNN), and supports much larger scale real-time simulation.

Abstract Studies in SIV-infected macaques show that the virus reservoir is particularly refractory to conventional suppressive antiretroviral therapy (ART). We posit that optimized ART regimens designed to have robust penetration in tissue reservoirs and long-lasting antiviral activity may be advantageous for HIV or SIV remission. Here we treat macaques infected with RT-SHIV with oral emtricitabine/tenofovir alafenamide and long-acting cabotegravir/rilpivirine without (n = 4) or with (n = 4) the immune activator vesatolimod after the initial onset of viremia. We document full suppression in all animals during treatment (4-12 months) and no virus rebound after treatment discontinuation (1.5-2 years of follow up) despite CD8 + T cell depletion. We show efficient multidrug penetration in virus reservoirs and persisting rilpivirine in plasma for 2 years after the last dose. Our results document a type of virus remission that is achieved through early treatment initiation and provision of ultra long-lasting antiviral activity that persists after treatment cessation.

Abstract Background The establishment of apicobasal polarity in epithelial cells is of critical importance in morphogenesis of mammary gland and other secretive gland tissues. The demise of the polarity is a critical step in early stages of tumorigenesis such as in breast ductal carcinoma in situ. The underlying molecular mechanism thus warrants in-depth investigations. Results Protein kinase C isoform ζ (PKCζ), which is highly expressed in breast cancer cells, accumulates in the nuclei of human mammary epithelial cells overexpressing human rhomboid family-1 (RHBDF1), an endoplasmic reticulum membrane protein. Nuclear translocation of PKCζ results in the failure of the formation of the cytosolic apicobasal polarity complex Par, of which PKCζ is an essential component. Additionally, enhanced nuclear translocation of PKCζ is accompanied by an inhibition of the expression of cell tight junction and adherens junction proteins and an increase of cell mobility. Mechanistically, RHBDF1 is able to interact with importin β1 and PKCζ and promote PKCζ phosphorylation. Consistently, treatment of RHBDF1-overexpressing cells with an inhibitor of PKCζ phosphorylation leads to restoration of apicobasal polarity and cell-cell junctions, as well as suppressed cell mobility. Conclusions RHBDF1-facilitated nuclear translocation of PKCζ is critically responsible for the dismantlement of epithelial cell apicobasal polarity, and thus may serve as a target in the development of therapeutic approaches against early stages of breast cancer.

Abstract Background The use of mesenchymal stem cells (MSCs) is recognized as a promising strategy for the treatment of androgenetic alopecia (AGA). However, the underlying mechanism remains to be explored. Here, we evaluated the therapeutic effects and potential mechanisms of the use of human umbilical cord mesenchymal stem cells (hUCMSCs) in dihydrotestosterone (DHT)-induced AGA models in vivo and in vitro. Methods Intradermal transplantation of hUCMSCs was performed in AGA model mice and therapeutic effects were evaluated using histological and immunofluorescence staining. Transwell assays were used for co-culture of hUCMSCs and dermal papilla cells (DPCs), and communication was assessed using RT-qPCR, immunofluorescence, and apoptosis analysis. Interactions between DPCs and hair follicle stem cells (HFSCs) were investigated using RT-qPCR, EdU assays, and cell cycle analysis. Results Treatment of AGA mice with hUCMSCs promoted hair growth, HFs density, skin thickness, and anagen phase activation, while inhibiting DPCs apoptosis, and promoting HFSCs proliferation. In vitro, hUCMSCs activated Wnt/β-catenin signaling in DPCs via Wntless (Wls), while stimulating growth factor secretion and HFSCs proliferation. Blocking β-catenin degradation with MSAB increased DPCs apoptosis, reduced growth factor secretion, and retarded HFSCs proliferation. Conclusion hUCMSCs promoted hair regeneration in AGA model mice. This was found to be dependent on reducing DPCs apoptosis, thereby relieving the inhibitory effects of DPCs on the growth of HFSCs. The activation of the Wnt/β-catenin signaling pathway was shown to play a crucial role in the promotion of hair growth by hUCMSCs in AGA mice.

Abstract Background Gliomas are the most common malignant brain tumors characterized by angiogenesis and invasive growth. A detailed understanding of its molecular characteristics could provide potential therapeutic targets. In the present study, we sought to explore the key gene CXCL8 in methionine metabolism in gliomas and its potential role in angiogenesis. Methods U251 glioma cells were divided into control and methionine-restriction tolerant (constructed with 1/4 of the standard level of methionine in the culture medium) groups for transcriptome and metabolome analysis. To confirm the functions and mechanism of CXCL8 in glioma, heat map, volcano map, Go enrichment, gene set enrichment analysis (GSEA), protein–protein interaction network analysis, RT-PCR, western blotting assays, chicken embryo chorioallantoic membrane (CAM) test, chicken embryo yolk sac membrane (YSM) test and transplantation tumor nude mice model were performed. The TCGA database, CGGA database and clinical tissue samples were used to analyze CXCL8’s significance on prognosis for patients with glioma. Results CXCL8 expression was significantly up-regulated in methionine-restricted tolerance cells, it also activated vascular system development and triggered angiogenesis. CXCL8 expression is negatively correlated with survival prognosis in gliomas. Conclusions Glioma cells promote angiogenesis in methionine-restricted environments through the activation of CXCL8, compensating for nutrient deprivation, and possibly contributing to the failure of antiangiogenic therapy.

Introduction Material and methods Results Conclusions

Oil shale, the most important unconventional oil and gas reservoir resource, is characterized by large geological reserves, difficult development technology, and great development potential. Although it cannot be exploited in a large area due to cost issues, with the development and utilization of conventional oil and gas reservoir resources, it is the main direction of future oil exploitation. Based on the classification of in situ conversion technologies of oil shale electric heating into in situ conversion process technology, ElectrofracTM technology, geothermal fuel cell heating technology, high-voltage power frequency electric heating technology, and other electric heating technology, this paper summarizes the research progress on existing electric heating technologies to provide a reference for the engineering research and development of oil shale electric heating in situ mining technology.

In the engineering of oil shale, in situ extraction technology using electric heating involves heating the oil shale reservoir with an electric heater at high temperatures to convert the solid kerogen in oil shale into liquid hydrocarbons. These liquid hydrocarbons are then extracted from underground using traditional oil and gas drilling and production techniques. This paper discusses the pyrolysis mechanism, pore evolution, mineral transformation, and classification of electric heating technology for oil shale. It also summarizes research progress aimed at improving in situ extraction technology for oil shale, providing valuable insights for further research and development in this field.

Accurately diagnosing Alzheimer’s disease is essential for improving elderly health. Meanwhile, accurate prediction of the mini-mental state examination score also can measure cognition impairment and track the progression of Alzheimer’s disease. However, most of the existing methods perform Alzheimer’s disease diagnosis and mini-mental state examination score prediction separately and ignore the relation between these two tasks. To address this challenging problem, we propose a novel multi-task learning method, which uses feature interaction to explore the relationship between Alzheimer’s disease diagnosis and mini-mental state examination score prediction. In our proposed method, features from each task branch are firstly decoupled into candidate and non-candidate parts for interaction. Then, we propose feature sharing module to obtain shared features from candidate features and return shared features to task branches, which can promote the learning of each task. We validate the effectiveness of our proposed method on multiple datasets. In Alzheimer’s disease neuroimaging initiative 1 dataset, the accuracy in diagnosis task and the root mean squared error in prediction task of our proposed method is 87.86% and 2.5, respectively. Experimental results show that our proposed method outperforms most state-of-the-art methods. Our proposed method enables accurate Alzheimer’s disease diagnosis and mini-mental state examination score prediction. Therefore, it can be used as a reference for the clinical diagnosis of Alzheimer’s disease, and can also help doctors and patients track disease progression in a timely manner.

Autism Spectrum Disorder (ASD) is a highly disabling mental disease that brings significant impairments of social interaction ability to the patients, making early screening and intervention of ASD critical. With the development of the machine learning and neuroimaging technology, extensive research has been conducted on machine classification of ASD based on structural Magnetic Resonance Imaging (s-MRI). However, most studies involve with datasets where participants’ age are above 5 and lack interpretability. In this paper, we propose a machine learning method for ASD classification in children with age range from 0.92 to 4.83 years, based on s-MRI features extracted using Contrastive Variational AutoEncoder (CVAE). 78 s-MRIs, collected from Shenzhen Children’s Hospital, are used for training CVAE, which consists of both ASD-specific feature channel and common-shared feature channel. The ASD participants represented by ASD-specific features can be easily discriminated from Typical Control (TC) participants represented by the common-shared features. In case of degraded predictive accuracy when data size is extremely small, a transfer learning strategy is proposed here as a potential solution. Finally, we conduct neuroanatomical interpretation based on the correlation between s-MRI features extracted from CVAE and surface area of different cortical regions, which discloses potential biomarkers that could help target treatments of ASD in the future.

Abstract Single-cell RNA sequencing (scRNA-seq) is a key technology for investigating cell development and analysing cell diversity across various diseases. However, the high dimensionality and extreme sparsity of scRNA-seq data pose great challenges for accurate cell type annotation. To address this, we developed a new cell-type annotation model called scGAA (general gated axial-attention model for accurate cell-type annotation of scRNA-seq). Based on the transformer framework, the model decomposes the traditional self-attention mechanism into horizontal and vertical attention, considerably improving computational efficiency. This axial attention mechanism can process high-dimensional data more efficiently while maintaining reasonable model complexity. Additionally, the gated unit was integrated into the model to enhance the capture of relationships between genes, which is crucial for achieving an accurate cell type annotation. The results revealed that our improved transformer model is a promising tool for practical applications. This theoretical innovation increased the model performance and provided new insights into analytical tools for scRNA-seq data.

Cadmium (Cd), a widespread and serious environmental pollutant, has recently garnered increasing scientific scrutiny due to its profound adverse effects. Although the evidence for Cd-induced reproductive toxicity is well established, it remains elusive on the intricate dose-response relationship and underlying molecular mechanisms, especially for transgenerational toxicity in animals. Here, we employed fruit fly (Drosophila melanogaster) as a model organism to examine the reproductive performance across five generations by parental exposure to varying concentrations of Cd (5, 50, and 500 μM). Firstly, our observations on the number of eggs laid, pupae formed, and adult flies emerged on the directly exposed generation (F0) confirmed a dose-dependent decline in fecundity. Transcriptome analysis revealed that, Cd-induced oxidative stress and ion transport disruption in the F0 generation could underlie synaptic dysfunction and impaired follicle cell development, impacting reproductive behavior and oocyte fertility. Employing dose-response analysis, Wnt signaling pathway and mTOR signaling pathway were identified as early molecular responses to Cd-induced toxicity. Secondly, sustained detrimental effects were observed for at least two to three generations after Cd removal. At the epigenetic level, Cd could perturb fecundity across generations by modulating Dnmt2 expression, a pivotal regulator of methylation processes. Moreover, despite phenotypic recovery in F4, persistent molecular changes indicate enduring toxicity, highlighting the need for vigilance against environmental Cd contamination and its long-term effects. Collectively, our findings enhance the understanding of Cd-induced reproductive toxicity and its transgenerational effects, and highlight the need to further improve the assessment of the multigenerational consequences of environmental Cd contamination.

BackgroundDiagnosing bipolar disorder poses a challenge in clinical practice and demands a substantial time investment. With the growing utilization of artificial intelligence in mental health, researchers are endeavoring to create AI-based diagnostic models. In this context, some researchers have sought to develop machine learning models for bipolar disorder diagnosis. Nevertheless, the accuracy of these diagnoses remains a subject of controversy. Consequently, we conducted this systematic review to comprehensively assess the diagnostic value of machine learning in the context of bipolar disorder.MethodsWe searched PubMed, Embase, Cochrane, and Web of Science, with the search ending on April 1, 2023. QUADAS-2 was applied to assess the quality of the literature included. In addition, we employed a bivariate mixed-effects model for the meta-analysis.Results18 studies were included, covering 3152 participants, including 1858 cases of bipolar disorder. 28 machine learning models were encompassed. Sensitivity and specificity in discriminating between bipolar disorder and normal individuals were 0.88 (9.5% CI: 0.74~0.95) and 0.89 (95% CI: 0.73~0.96) respectively, and the SROC curve was 0.94(95% CI: 0.92~0.96). The sensitivity and specificity for distinguishing between bipolar disorder and depression were 0.84 (95%CI: 0.80~0.87) and 0.82 (95%CI: 0.75~0.88) respectively. The SROC curve was 0.89 (95%CI: 0.86~0.91).ConclusionsMachine learning methods can be employed for discriminating and diagnosing bipolar disorder. However, in current research, they are predominantly utilized for binary classification tasks, limiting their progress in clinical practice. Therefore, in future studies, we anticipate the development of more multi-class classification tasks to enhance the clinical applicability of these methods.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023427290, identifier CRD42023427290.

Introduction: EGFR tyrosine kinase inhibitor (TKI) is the standard adjuvant treatment for patients with stages IB to IIIA EGFR-mutated NSCLC. Nevertheless, adapting this approach to include a molecular residual disease (MRD)-guided de-escalation strategy warrants further investigation. Methods: From January 2019 to December 2022, 71 patients with stages I to III NSCLC and EGFR (exon 19 deletion or L858R) mutations were enrolled in this observational study. A total of 375 blood samples were analyzed using the MRD_Navigator assay. Among them, 27 patients suspended EGFR TKI treatment based on undetectable MRD and were thus included in the adaptive, de-escalation group. Results: Overall, the sensitivity of longitudinal MRD was 86.2%. Only four patients (11.8%) recurred with longitudinal undetectable MRD, indicating a negative predictive value of 88.2%. Of the patients who had detectable MRD after surgery, nine subsequently received EGFR TKI treatment, with only one (11.1%) achieving persistent circulating tumor DNA clearance post–EGFR TKI. Furthermore, 22 patients with stages IB to III disease who had previously suspended their TKI treatment based on undetectable MRD were included in the adaptive group, with an average duration of TKI 3.9 (range: 0–35.0) months. The 2-year disease-free survival rate of these 22 patients was 80.2%, and the median was not reached. Five patients (n = 5 of 22, 22.7%) had disease recurrence during the period of drug cessation but were stable under EGFR TKI treatment until the latest follow-up. Two patients remained in complete remission. Conclusions: Our initial findings underscore the potential of an adaptive, de-escalation approach to adjuvant EGFR TKIs based on circulating tumor DNA-MRD monitoring.

Medical images and radiology reports are essential for physicians to diagnose medical conditions. However, the vast diversity and cross-source heterogeneity inherent in these data have posed significant challenges to the generalizability of current data-mining methods for clinical decision-making. Recently, multimodal large language models (MLLMs), especially Gemini-Vision-series (Gemini) and GPT-4-series (GPT-4) models, have revolutionized numerous domains, significantly impacting the medical field. In this study, we conducted a detailed evaluation of the performance of the Gemini series models (including Gemini-1.0-Pro-Vision, Gemini-1.5-Pro, and Gemini-1.5-Flash) and GPT series models (including GPT-4o, GPT-4-Turbo, and GPT-3.5-Turbo) across 14 medical datasets, covering 5 medical imaging categories (dermatology, radiology, dentistry, ophthalmology, and endoscopy) and 3 radiology report datasets. The investigated tasks encompass disease classification, lesion segmentation, anatomical localization, disease diagnosis, report generation, and lesion detection. Moreover, we also validated the performance of the Claude-3-Opus, Yi-Large, Yi-Large-Turbo, and LLaMA 3 models to gain a comprehensive understanding of the MLLM models in the medical field. Our experimental results demonstrated that Gemini-series models excelled in report generation and lesion detection but faces challenges in disease classification and anatomical localization. Conversely, GPT-series models exhibited proficiency in lesion segmentation and anatomical localization but encountered difficulties in disease diagnosis and lesion detection. Additionally, both the Gemini series and GPT series contain models that have demonstrated commendable generation efficiency. While both models hold promise in reducing physician workload, alleviating pressure on limited healthcare resources, and fostering collaboration between clinical practitioners and artificial intelligence technologies, substantial enhancements and comprehensive validations remain imperative before clinical deployment.

With the rapidly development of biotechnology, it is now possible to obtain single-cell multi-omics data in the same cell. However, how to integrate and analyze these single-cell multi-omics data remains a great challenge. Herein, we introduce an interpretable multitask framework (scMoMtF) for comprehensively analyzing single-cell multi-omics data. The scMoMtF can simultaneously solve multiple key tasks of single-cell multi-omics data including dimension reduction, cell classification and data simulation. The experimental results shows that scMoMtF outperforms current state-of-the-art algorithms on these tasks. In addition, scMoMtF has interpretability which allowing researchers to gain a reliable understanding of potential biological features and mechanisms in single-cell multi-omics data.

Porcine hemagglutinating encephalomyelitis virus (PHEV), porcine pseudorabies virus (PRV), and classical swine fever virus (CSFV) are currently prevalent worldwide and cause similar neurological symptoms in infected pigs. It is very important to establish a detection method that can rapidly and accurately detect and differentiate these three viruses. Targeting the PHEV N gene, PRV gB gene, and CSFV 5′ untranslated region (5′UTR), three pairs of specific primers and probes were designed, and a triplex crystal digital reverse transcription-PCR (cdRT-PCR) was developed to detect PHEV, PRV, and CSFV. The results indicated that this assay had high sensitivity, and the limitation of detection (LODs) for PHEV, PRV, and CSFV were 4.812, 4.047, and 5.243 copies/reaction, respectively, which was about 50 times higher than that of multiplex real-time quantitative RT-PCR (RT-qPCR). This assay showed good specificity, without cross-reaction with other important swine pathogens, i.e., FMDV, PRRSV, PEDV, SIV, TGEV, PoRV, and PCV2. This assay had high repeatability, with intra-assay coefficients of variation (CVs) of 0.73–1.87%, and inter-assay CVs of 0.57–2.95%. The developed assay was used to test 1,367 clinical tissue samples from Guangxi province in China, and the positive rates of PHEV, PRV, and CSFV were 3.44% (47/1,367), 1.24% (17/1,367), and 1.90% (26/1,367), respectively, with a coincidence rate of 98.98% and a Kappa value of 0.94 to the reference multiplex RT-qPCR. The established triplex cdRT-PCR was a highly rapid, sensitive, and accurate assay to detect and differentiate PHEV, PRV, and CSFV.

BackgroundPsoriatic arthritis (PSA) is an inflammatory joint disease associated with psoriasis (PSO) that can be easily missed. Existing PSA screening tools ignore objective serologic indicators. The aim of this study was to develop a disease screening model and the Psoriatic Arthritis Inflammation Index (PSAII) based on serologic data to enhance the efficiency of PSA screening.MethodA total of 719 PSO and PSA patients from the National Health and Nutrition Examination Survey (NHANES) (as training set and test set) and 135 PSO and PSA patients who were seen at The First Affiliated Hospital of Zhejiang Chinese Medical University (as external validation set) were selected, 31 indicators for these patients were collected as potential input features for the model. Least Absolute Shrinkage and Selection Operator (LASSO) was used to identify PSA-related features. Five models of logistic regression (LR), random forest, k-nearest neighbor, gradient augmentation and neural network were developed in the training set using quintuple cross validation. And we developed PSAII based on the results of LASSO regression and weights of logistic model parameters. All performance metrics are derived on the test set and the external validation set.ResultsFive variables were selected to build models, including age, lymphocyte percentage, neutrophil count, eosinophilic count, and C-reactive protein. In all established models, the LR model performed the best, with an Area Under Curve (AUC) of 0.87 (95% confidence interval (CI): 0.83-0.90) on the test set; on the external validation set the AUC was 0.82 (95%CI: 0.74-0.90). The PSAII formula was PSAII = percentage of lymphocytes × C-reactive protein/(neutrophil count × eosinophilic count × 10). The AUC of PSAII in the test is 0.93 (95%CI: 0.88-0.97), and the cutoff value is 18. The AUC of the external validation set is 0.81 (95%CI: 0.72-0.89).ConclusionsThis study developed and validated five models to assist screening for PSA by analyzing serum data from NHANES and Chinese populations. The LR model demonstrated the best performance. We created PSAII for PSA screening. However, the high false positive rate of PSAII makes it necessary to combine it with other PSA screening tools when applied.

Acute-on-chronic liver failure (ACLF) and decompensated cirrhosis (DC) are life-threatening syndromes that can develop at the end-stage of chronic hepatitis B virus (HBV) infection. Both ACLF and DC are complicated by hepatic and extrahepatic pathogeneses. To better understand the compartment-specific metabolic modulations related to their pathogenesis, HBV-DC, HBV-ACLF patients, and controls (30 each) were analyzed by metabolomics using portal (Port), hepatic vein (Hep), and peripheral (Peri) serum. Compartment ratios of metabolites (RatioHep/Port, RatioPeri/Hep, and RatioPort/Peri) were calculated. The liver tissues (10 per group) were analyzed using transcriptomics and metabolomics. An additional 75 patients with ACLF, 20 with DC, and 20 with liver cirrhosis (LC) were used to confirm oxlipid dysregulation. Both multi-omics datasets suggest suppressed energy, amino acid, and pyrimidine metabolism in the ACLF/DC liver. The serum metabolomic variations were contributed primarily by disease rather than sampling compartments, as both HBV-ACLF and HBV-DC patients demonstrated abnormal profiles of amino acids and peptides, indoles, purines, steroids, and benzimidazoles. In ACLF/DC patients, impaired hepatic metabolism resulted in a highly correlated hepatic and portal vein serum metabolome and release of inflammatory lipids and heme metabolites from the liver. HBV-ACLF showed higher RatioPeri/Hep of extrahepatic inflammatory oxlipids, while HBV-DC patients showed higher RatioPort/Peri of gut microbial metabolites. An inflammatory oxlipid outburst was confirmed in the early stages of HBV-ACLF. The inflammatory effects of the selected oxlipids were confirmed in monocytes. These findings support a synergy between liver-specific mechanisms and systemic inflammation in ACLF/DC development, and that pro-inflammatory oxlipids are metabolic signatures of early HBV-ACLF.

Abstract Background Glucagon-like peptide-1 receptor (GLP1R) agonists have been shown to reduce major cardiovascular events in diabetic patients, but their role in heart failure (HF) remains controversial. Recent evidence implies their potential benefits on cardiometabolism such as lipid metabolism, which may contribute to lowering the risk of HF. Consequently, we designed a Mendelian randomization (MR) study to investigate the causal relationships of circulating lipids mediating GLP1R agonists in HF. Methods The available cis-eQTLs for GLP1R target gene were selected as instrumental variables (IVs) of GLP1R agonism. Positive control analyses of type 2 diabetes mellitus (T2DM) and body mass index (BMI) were conducted to validate the enrolled IVs. Two-sample MR was performed to evaluate the associations between GLP1R agonism and HF as well as left ventricular ejection fraction (LVEF). Summary data for HF and LVEF were obtained from two genome-wide association studies (GWASs), which included 977,323 and 40,000 individuals of European ancestry, respectively. The primary method employed was the random-effects inverse variance weighted, with several other methods used for sensitivity analyses, including MR-Egger, MR PRESSO, and weighted median. Additionally, multivariable MR and mediation MR were applied to identify potentially causal lipid as mediator. Results A total of 18 independent IVs were included. The positive control analyses showed that GLP1R agonism significantly reduced the risk of T2DM (OR = 0.79, 95% CI = 0.75–0.85, p

Abstract Seed size/weight plays an important role in determining crop yield, yet only few genes controlling seed size have been characterized in soybean. Here, we perform a genome-wide association study and identify a major quantitative trait locus (QTL), named GmSW17 (Seed Width 17), on chromosome 17 that determine soybean seed width/weight in natural population. GmSW17 encodes a ubiquitin-specific protease, an ortholog to UBP22, belonging to the ubiquitin-specific protease (USPs/UBPs) family. Further functional investigations reveal that GmSW17 interacts with GmSGF11 and GmENY2 to form a deubiquitinase (DUB) module, which influences H2Bub levels and negatively regulates the expression of GmDP-E2F-1, thereby inhibiting the G1-to-S transition. Population analysis demonstrates that GmSW17 undergo artificial selection during soybean domestication but has not been fixed in modern breeding. In summary, our study identifies a predominant gene related to soybean seed weight, providing potential advantages for high-yield breeding in soybean.

Abstract Alkylamine structures represent one of the most functional and widely used in organic synthesis and drug design. However, the general methods for the functionalization of the shielded and deshielded alkyl radicals remain elusive. Here, we report a general deoxygenative amination protocol using alcohol-derived carbazates and nitrobenzene under electrochemical conditions. A range of primary, secondary, and tertiary alkylamines are obtained. This practical procedure can be scaled up through electrochemical continuous flow technique.

This study explores the potential of Artificial Intelligence (AI) in early screening and prognosis of Dry Eye Disease (DED), aiming to enhance the accuracy of therapeutic approaches for eye-care practitioners. Despite the promising opportunities, challenges such as diverse diagnostic evidence, complex etiology, and interdisciplinary knowledge integration impede the interpretability, reliability, and applicability of AI-based DED detection methods. The research conducts a comprehensive review of datasets, diagnostic evidence, and standards, as well as advanced algorithms in AI-based DED detection over the past five years. The DED diagnostic methods are categorized into three groups based on their relationship with AI techniques: (1) those with ground truth and/or comparable standards, (2) potential AI-based methods with significant advantages, and (3) supplementary methods for AI-based DED detection. The study proposes suggested DED detection standards, the combination of multiple diagnostic evidence, and future research directions to guide further investigations. Ultimately, the research contributes to the advancement of ophthalmic disease detection by providing insights into knowledge foundations, advanced methods, challenges, and potential future perspectives, emphasizing the significant role of AI in both academic and practical aspects of ophthalmology.

AIM: To investigate ocular surface disorders and tear function changes in patients with acne vulgaris and explore the potential relationship between acne vulgaris and dry eye. METHODS: This cross-sectional study included right eyes of 53 patients with acne vulgaris and 54 healthy controls. The participants completed the Ocular Surface Disease Index (OSDI) questionnaire. The following ocular surface-related parameters were measured: tear meniscus height (TMH), noninvasive tear breakup time (NIBUT), Schirmer I test (SIT), lipid layer thickness (LLT) score of the tear film, meibum score, meibomian gland orifice obstruction score, the ratio of meibomian gland loss, conjunctival hyperemia score, and corneal fluorescein staining (CFS) score. RESULTS: The stability of the tear film decreased in acne vulgaris patients. In the acne group, the TMH and NIBUT were lower, whereas the OSDI, meibum score, meibomian gland orifice obstruction score, ratio of meibomian gland loss, and conjunctival hyperemia score were higher compared with controls (P0.05). In two dry eye groups, the TMH, NIBUT, and LLT score were lower in the acne with dry eye (acne-DE) group, and the meibum score, meibomian gland orifice obstruction score, ratio of meibomian gland loss and conjunctival hyperemia score in the acne-DE group were higher (P0.05). CONCLUSION: Patients with moderate-to-severe acne vulgaris are more likely to experience dry eye than those without acne vulgaris. Reduced tear film stability and meibomian gland structure dysfunction are more pronounced in patients with moderate-to-severe acne and dry eye.

Abstract Introduction Postherpetic neuralgia (PHN), a complication of herpes zoster, significantly impacts the quality of life of affected patients. Research indicates that early intervention for pain can reduce the occurrence or severity of PHN. This study aims to develop a predictive model and scoring table to identify patients at risk of developing PHN following acute herpetic neuralgia, facilitating informed clinical decision-making. Methods We conducted a retrospective review of 524 hospitalized patients with herpes zoster at The First Affiliated Hospital of Zhejiang Chinese Medical University from December 2020 to December 2023 and classified them according to whether they had PHN, collecting a comprehensive set of 30 patient characteristics and disease-related indicators, 5 comorbidity indicators, 2 disease score values, and 10 serological indicators. Relevant features associated with PHN were identified using the least absolute shrinkage and selection operator (LASSO). Then, the patients were divided into a training set and a test set in a 4:1 ratio, with comparability tested using univariate analysis. Six models were established in the training set using machine learning methods: support vector machines, logistic regression, random forest, k-nearest neighbor, gradient boosting, and neural network. The performance of these models was evaluated in the test set, and a nomogram based on logistic regression was used to create a PHN prediction score table. Results Eight non-zero characteristic variables selected from the LASSO regression results were included in the model, including age [area under the curve (AUC) = 0.812, p

Abstract Recently, environmental temperature has been shown to regulate bone homeostasis. However, the mechanisms by which cold exposure affects bone mass remain unclear. In our present study, we observed that exposure to cold temperature (CT) decreased bone mass and quality in mice. Furthermore, a transplant of exosomes derived from the plasma of mice exposed to cold temperature (CT-EXO) can also impair the osteogenic differentiation of BMSCs and decrease bone mass by inhibiting autophagic activity. Rapamycin, a potent inducer of autophagy, can reverse cold exposure or CT-EXO-induced bone loss. Microarray sequencing revealed that cold exposure increases the miR-25-3p level in CT-EXO. Mechanistic studies showed that miR-25-3p can inhibit the osteogenic differentiation and autophagic activity of BMSCs. It is shown that inhibition of exosomes release or downregulation of miR-25-3p level can suppress CT-induced bone loss. This study identifies that CT-EXO mediates CT-induced osteoporotic effects through miR-25-3p by inhibiting autophagy via targeting SATB2, presenting a novel mechanism underlying the effect of cold temperature on bone mass.

Adipose tissue inflammation is now considered to be a key process underlying metabolic diseases in obese individuals. However, it remains unclear how adipose inflammation is initiated and maintained or the mechanism by which inflammation develops. We found that microRNA-802 (Mir802) expression in adipose tissue is progressively increased with the development of dietary obesity in obese mice and humans. The increasing trend of Mir802 preceded the accumulation of macrophages. Adipose tissue-specific knockout of Mir802 lowered macrophage infiltration and ameliorated systemic insulin resistance. Conversely, the specific overexpression of Mir802 in adipose tissue aggravated adipose inflammation in mice fed a high-fat diet. Mechanistically, Mir802 activates noncanonical and canonical NF-κB pathways by targeting its negative regulator, TRAF3. Next, NF-κB orchestrated the expression of chemokines and SREBP1, leading to strong recruitment and M1-like polarization of macrophages. Our findings indicate that Mir802 endows adipose tissue with the ability to recruit and polarize macrophages, which underscores Mir802 as an innovative and attractive candidate for miRNA-based immune therapy for adipose inflammation.

Porcine hemagglutinating encephalomyelitis virus (PHEV) is the only known porcine neurotropic coronavirus, which is prevalent worldwide at present. It is of great significance to understand the genetic and evolutionary characteristics of PHEV in order to perform effective measures for prevention and control of this disease. In this study, a total of 6,986 tissue samples and nasopharyngeal swabs were collected from different regions of Guangxi province in southern China during 2021-2024, and were tested for PHEV using a quadruplex RT-qPCR. The positivity rate of PHEV was 2.81% (196/6,986), of which tissue samples and nasopharyngeal swabs had 2.05% (87/4,246) and 3.98% (109/2,740) positivity rates, respectively. Fifty PHEV positive samples were selected for PCR amplification and gene sequencing. Sequence analysis revealed that the nucleotide homology and amino acid similarities of S, M, and N genes were 94.3%-99.3% and 92.3%-99.2%, 95.0%-99.7% and 94.7%-100.0%, 94.0%-99.5% and 93.5%-99.3%, respectively, indicating M and N genes were more conservative than S gene. Phylogenetic trees based on these three genes revealed that PHEV strains from different countries could be divided into two groups G1 and G2, and the PHEV strains from Guangxi province obtained in this study distributed in subgroups G1c and G2b. Bayesian analysis revealed that the population size of PHEV has been in a relatively stable state since its discovery until it expanded sharply around 2015, and still on the slow rise thereafter. S gene sequences analysis indicated that PHEV strains existed variation of mutation, and recombination. The results indicated that the prevalent PHEV strains in Guangxi province had complex evolutionary trajectories and high genetic diversity. To the best of our knowledge, this is the first report on the genetic and evolutionary characteristics of PHEV in southern China.

Objective: This study utilized network meta-analysis (NMA) to compare the efficacy of five commonly used traditional Chinese medicine monomers in reducing intimal hyperproliferation in arterial balloon injury models. Methods: Relevant literature up to January 2024 was systematically retrieved from seven major databases. The intima-to-media (I/M) ratio was chosen as the primary outcome measure. The risk of bias in animal studies was assessed using the SYstematic Review Centre for Laboratory Animal Experimentation (SYRCLE) tool. Statistical analysis was conducted using Stata 17 software. Results: A total of 43 studies were included in this meta-analysis. NMA results showed that in the rat model, compared to the control group, GS (SMD: 0.99, 95%CI: 1.25 to −0.73), ASIV (SMD: 1.16, 95%CI: 1.65 to −0.67), TMP (SMD: 0.68, 95%CI: 1.31 to −0.05), and TPNS (SMD: 1.36, 95%CI: 1.91 to −0.80) exhibited inhibitory effects on postoperative intimal hyperproliferation, reducing the I/M ratio. In the rabbit model, compared to the control group, TPNS (SMD: 1.23, 95%CI: 1.97 to −0.49) inhibited postoperative intimal hyperproliferation and reduced the I/M ratio. Superiority ranking analysis suggested that total Panax notoginseng saponin (TPNS) might be the most effective traditional Chinese medicine monomer in reducing intimal hyperproliferation in arterial balloon injury models, lowering the I/M ratio. Conclusion: NMA indicates that traditional Chinese medicine monomers can effectively reduce postoperative intimal hyperproliferation in arterial balloon injury models, lowering the I/M ratio, with TPNS showing optimal efficacy. However, the research on TIIA is insufficient, and the limited sample size may affect the robustness of the results. Furthermore, the majority of research on traditional Chinese medicine monomers is currently limited to the experimental stage, lacking further clinical validation. Conducting standardized animal experiments and reporting their findings can enhance the quality of evidence from animal studies, laying the foundation for future clinical trials.

Abstract It remains a challenge to produce soft robots that can mimic the responsive adaptability of living organisms. Rather than fabricating soft robots from bulk hydrogels,hydrogels are integrated into the interfacial assembly of aqueous two‐phase systems to generate ultra‐soft and elastic all‐aqueous aquabots that exhibit responsive adaptability, that can shrink on demand and have electrically conductive functions. The adaptive functions of the aquabots provide a new platform to develop minimally invasive surgical devices, targeted drug delivery systems, and flexible electronic sensors and actuators.

Abstract Background To establish a method to induce Campylobacter jejuni colonization in the intestines of C57BL/6 mice through antibiotic-induced microbiome depletion. Results Fifty-four female C57BL/6 mice were divided into the normal, control, and experimental groups. The experimental group was administered intragastric cefoperazone sodium and sulbactam sodium (50 mg/mL) for 2 days; then, the experimental and control mice were intragastrically administered 200 µL C. jejuni, which was repeated once more after 2 days. Animal feces were collected, and the HipO gene of C. jejuni was detected using TaqMan qPCR from day 1 to day 14 after modeling completion. Immunofluorescence was used to detect intestinal C. jejuni colonization on day 14, and pathological changes were observed using hematoxylin and eosin staining. Additionally, 16S rDNA analyses of the intestinal contents were conducted on day 14. In the experimental group, C. jejuni was detected in the feces from days 1 to 14 on TaqMan qPCR, and immunofluorescence-labeled C. jejuni were visibly discernable in the intestinal lumen. The intestinal mucosa was generally intact and showed no significant inflammatory-cell infiltration. Diversity analysis of the colonic microbiota showed significant inter-group differences. In the experimental group, the composition of the colonic microbiota differed from that in the other 2 groups at the phylum level, and was characterized by a higher proportion of Bacteroidetes and a lower proportion of Firmicutes. Conclusions Microbiome depletion induced by cefoperazone sodium and sulbactam sodium could promote long-term colonization of C. jejuni in the intestines of mice.

Abstract Actinobacillus pleuropneumoniae (APP) causes porcine pleuropneumonia (PCP), which is clinically characterized by acute hemorrhagic, necrotizing pneumonia, and chronic fibrinous pneumonia. Although many measures have been taken to prevent the disease, prevention and control of the disease are becoming increasingly difficult due to the abundance of APP sera, weak vaccine cross-protection, and increasing antibiotic resistance in APP. Therefore, there is an urgent need to develop novel drugs against APP infection to prevent the spread of APP. Naringin (NAR) has been reported to have an excellent therapeutic effect on pulmonary diseases, but its therapeutic effect on lung injury caused by APP is not apparent. Our research has shown that NAR was able to alleviate APP-induced weight loss and quantity of food taken and reduce the number of WBCs and NEs in peripheral blood in mice; pathological tissue sections showed that NAR was able to prevent and control APP-induced pathological lung injury effectively; based on the establishment of an in vivo/in vitro model of APP inflammation, it was found that NAR was able to play an anti-inflammatory role through inhibiting the MAPK/NF-κB signaling pathway and exerting anti-inflammatory effects; additionally, NAR activating the Nrf2 signalling pathway, increasing the secretion of antioxidant enzymes Nqo1, CAT, and SOD1, inhibiting the secretion of oxidative damage factors NOS2 and COX2, and enhancing the antioxidant stress ability, thus playing an antioxidant role. In summary, NAR can relieve severe lung injury caused by APP by reducing excessive inflammatory response and improving antioxidant capacity.

Glucagon-like peptide-1 (GLP-1) is a 30-amino acid peptide hormone that is mainly expressed in the intestine and hypothalamus. In recent years, basic and clinical studies have shown that GLP-1 is closely related to lipid metabolism, and it can participate in lipid metabolism by inhibiting fat synthesis, promoting fat differentiation, enhancing cholesterol metabolism, and promoting adipose browning. GLP-1 plays a key role in the occurrence and development of metabolic diseases such as obesity, nonalcoholic fatty liver disease, and atherosclerosis by regulating lipid metabolism. It is expected to become a new target for the treatment of metabolic disorders. The effects of GLP-1 and dual agonists on lipid metabolism also provide a more complete treatment plan for metabolic diseases. This article reviews the recent research progress of GLP-1 in lipid metabolism.

Abstract Necroptosis is a lytic form of regulated cell death reported to contribute to inflammatory diseases of the gut, skin and lung, as well as ischemic-reperfusion injuries of the kidney, heart and brain. However, precise identification of the cells and tissues that undergo necroptotic cell death in vivo has proven challenging in the absence of robust protocols for immunohistochemical detection. Here, we provide automated immunohistochemistry protocols to detect core necroptosis regulators – Caspase-8, RIPK1, RIPK3 and MLKL – in formalin-fixed mouse and human tissues. We observed surprising heterogeneity in protein expression within tissues, whereby short-lived immune barrier cells were replete with necroptotic effectors, whereas long-lived cells lacked RIPK3 or MLKL expression. Local changes in the expression of necroptotic effectors occurred in response to insults such as inflammation, dysbiosis or immune challenge, consistent with necroptosis being dysregulated in disease contexts. These methods will facilitate the precise localisation and evaluation of necroptotic signaling in vivo.

Abstract Macroautophagy is a process that cells engulf cytosolic materials by autophagosomes and deliver them to lysosomes for degradation. The biogenesis of autophagosomes requires ATG2 as a lipid transfer protein to transport lipids from existing membranes to phagophores. It is generally believed that endoplasmic reticulum is the main source for lipid supply of the forming autophagosomes; whether ATG2 can transfer lipids from other organelles to phagophores remains elusive. In this study, we identified a new ATG2A-binding protein, ANKFY1. Depletion of this endosome-localized protein led to the impaired autophagosome growth and the reduced autophagy flux, which largely phenocopied ATG2A/B depletion. A pool of ANKFY1 co-localized with ATG2A between endosomes and phagophores and depletion of UVRAG, ANKFY1 or ATG2A/B led to reduction of PI3P distribution on phagophores. Purified recombinant ANKFY1 bound to PI3P on membrane through its FYVE domain and enhanced ATG2A-mediated lipid transfer between PI3P-containing liposomes. Therefore, we propose that ANKFY1 recruits ATG2A to PI3P-enriched endosomes and promotes ATG2A-mediated lipid transfer from endosomes to phagophores. This finding implicates a new lipid source for ATG2A-mediated phagophore expansion, where endosomes donate PI3P and other lipids to phagophores via lipid transfer.

Abstract Background Prior studies have reported a potential relationship between depressive disorder (DD), immune function, and inflammatory response. Some studies have also confirmed the correlation between immune and inflammatory responses and Bell’s palsy. Considering that the pathophysiology of these two diseases has several similarities, this study investigates if DD raises the risk of developing Bell’s palsy. Methods This nationwide propensity score-weighting cohort study utilized Taiwan National Health Insurance data. 44,198 patients with DD were identified as the DD cohort and 1,433,650 adult subjects without DD were identified as the comparison cohort. The inverse probability of treatment weighting (IPTW) strategy was used to balance the differences of covariates between two groups. The 5-year incidence of Bell’s palsy was evaluated using the Cox proportional-hazard model, presenting results in terms of hazard ratios (HRs) and 95% confidence intervals (CIs). Results The average age of DD patients was 48.3 ± 17.3 years, and 61.86% were female. After propensity score-weighting strategy, no significant demographic differences emerged between the DD and comparison cohort. The Cox proportional hazards model revealed a statistically significant adjusted IPTW-HR of 1.315 (95% CI: 1.168–1.481) for Bell’s palsy in DD patients compared to comparison subjects. Further independent factors for Bell’s palsy in this model were age (IPTW-HR: 1.012, 95% CI: 1.010–1.013, p

Generating novel molecules to satisfy specific properties is a challenging task in modern drug discovery, which requires the optimization of a specific objective based on satisfying chemical rules. Herein, we aim to optimize the properties of a specific molecule to satisfy the specific properties of the generated molecule. The Matched Molecular Pairs (MMPs), which contain the source and target molecules, are used herein, and logD and solubility are selected as the optimization properties. The main innovative work lies in the calculation related to a specific transformer from the perspective of a matrix dimension. Threshold intervals and state changes are then used to encode logD and solubility for subsequent tests. During the experiments, we screen the data based on the proportion of heavy atoms to all atoms in the groups and select 12365, 1503, and 1570 MMPs as the training, validation, and test sets, respectively. Transformer models are compared with the baseline models with respect to their abilities to generate molecules with specific properties. Results show that the transformer model can accurately optimize the source molecules to satisfy specific properties.

With the rapid development of the electric vehicle (EV) industry, various issues, such as the suboptimal deployment of charging facilities and inadequate distribution, hinder improvements in user satisfaction with EVs. Moreover, the interests of multiple stakeholders, including power grid companies and transportation departments, are not sufficiently addressed. To tackle these challenges, this paper proposes a comprehensive evaluation method for EV charging network service quality that integrates user satisfaction. First, considering the coupled dynamics of the EV charging network, we construct a service quality evaluation index system. Then, using a combination of the entropy weight method (EWM) and the analytic hierarchy process (AHP) with game theory, we determine the composite weights for the index system. Finally, we use the improved R-method evaluation model to theoretically verify the charging network in a particular area. The results show that the evaluation method proposed in this paper realizes differentiated evaluation for different planning schemes, highlights the weak links in the operation process of the charging network, and provides a theoretical reference for decision making about charging station planning.

Summary: Leptomeningeal metastases (LMs) remain a devastating complication of non-small cell lung cancer (NSCLC), particularly following osimertinib resistance. We conducted single-cell RNA sequencing on cerebrospinal fluid (CSF) from EGFR-mutant NSCLC with central nervous system metastases. We found that macrophages of LMs displayed functional and phenotypic heterogeneity and enhanced immunosuppressive properties. A population of lipid-associated macrophages, namely RNASE1_M, were linked to osimertinib resistance and LM development, which was regulated by Midkine (MDK) from malignant epithelial cells. MDK exhibited significant elevation in both CSF and plasma among patients with LMs, with higher MDK levels correlating to poorer outcomes in an independent cohort. Moreover, MDK could promote macrophage M2 polarization with lipid metabolism and phagocytic function. Furthermore, malignant epithelial cells in CSF, particularly after resistance to osimertinib, potentially achieved immune evasion through CD47-SIRPA interactions with RNASE1_M. In conclusion, we revealed a specific subtype of macrophages linked to osimertinib resistance and LM development, providing a potential target to overcome LMs.

Abstract Glaucoma is a leading cause of irreversible blindness worldwide and is characterized by progressive retinal ganglion cell (RGC) degeneration and vision loss. Since irreversible neurodegeneration occurs before diagnosable, early diagnosis and effective neuroprotection are critical for glaucoma management. Small extracellular vesicles (sEVs) are demonstrated to be potential novel biomarkers and therapeutics for a variety of diseases. In this study, it is found that intravitreal injection of circulating plasma‐derived sEVs (PDEV) from glaucoma patients ameliorated retinal degeneration in chronic ocular hypertension (COH) mice. Moreover, it is found that PDEV‐miR‐29s are significantly upregulated in glaucoma patients and are associated with visual field defects in progressed glaucoma. Subsequently, in vivo and in vitro experiments are conducted to investigate the possible function of miR‐29s in RGC pathophysiology. It is showed that the overexpression of miR‐29b‐3p effectively prevents RGC degeneration in COH mice and promotes the neuronal differentiation of human induced pluripotent stem cells (hiPSCs). Interestingly, engineered sEVs with sufficient miR‐29b‐3p delivery exhibit more effective RGC protection and neuronal differentiation efficiency. Thus, elevated PDEV‐miR‐29s may imply systemic regulation to prevent RGC degeneration in glaucoma patients. This study provides new insights into PDEV‐based glaucoma diagnosis and therapeutic strategies for neurodegenerative diseases.

In this paper, an experimental and theoretical study on the uniaxial tensile behavior of a fiber-reinforced polymer (FRP) grid-engineered cementitious composite (ECC) composite layer is described. Based on the test parameters, including the ECC material properties, the ECC cross-sectional area and the FRP grid cross-sectional area, three groups of ECC specimens and six groups of composite layer specimens were tested to reveal their joint action mechanism and tensile behavior. The experimental results showed two failure modes: fibers were pulled off or pulled out in the ECC specimens, and in the composite layer specimens, part of the fiber bars in the FRP grid was pulled off. The stress–strain curves show three stages: the elastic stage, softening stage and hardening stage. Due to the reinforcement of the FRP grid, the ultimate stress of the composite layer increased significantly compared with that of the ECC specimens. The composite layer softening strain was primarily related to the ECC softening strain, and the ultimate strain was primarily related to the FRP grid fracture strain. Moreover, a three-stage model was proposed to predict the stressstrain relationship, exhibiting a higher prediction accuracy and smaller dispersion compared with the three existing models.

IntroductionBasal cell carcinoma (BCC) is the most common skin cancer, lacking reliable biomarkers or therapeutic targets for effective treatment. Genome-wide association studies (GWAS) can aid in identifying drug targets, repurposing existing drugs, predicting clinical trial side effects, and reclassifying patients in clinical utility. Hence, the present study investigates the association between plasma proteins and skin cancer to identify effective biomarkers and therapeutic targets for BCC.MethodsProteome-wide mendelian randomization was performed using inverse-variance-weight and Wald Ratio methods, leveraging 1 Mb cis protein quantitative trait loci (cis-pQTLs) in the UK Biobank Pharma Proteomics Project (UKB-PPP) and the deCODE Health Study, to determine the causal relationship between plasma proteins and skin cancer and its subtypes in the FinnGen R10 study and the SAIGE database of Lee lab. Significant association with skin cancer and its subtypes was defined as a false discovery rate (FDR) < 0.05. pQTL to GWAS colocalization analysis was executed using a Bayesian model to evaluate five exclusive hypotheses. Strong colocalization evidence was defined as a posterior probability for shared causal variants (PP.H4) of ≥0.85. Mendelian randomization-Phenome-wide association studies (MR-PheWAS) were used to evaluate potential biomarkers and therapeutic targets for skin cancer and its subtypes within a phenome-wide human disease category.ResultsPTGES2, RNASET2, SF3B4, STX8, ENO2, and HS3ST3B1 (besides RNASET2, five other plasma proteins were previously unknown in expression quantitative trait loci (eQTL) and methylation quantitative trait loci (mQTL)) were significantly associated with BCC after FDR correction in the UKB-PPP and deCODE studies. Reverse MR showed no association between BCC and these proteins. PTGES2 and RNASET2 exhibited strong evidence of colocalization with BCC based on a posterior probability PP.H4 >0.92. Furthermore, MR-PheWAS analysis showed that BCC was the most significant phenotype associated with PTGES2 and RNASET2 among 2,408 phenotypes in the FinnGen R10 study. Therefore, PTGES2 and RNASET2 are highlighted as effective biomarkers and therapeutic targets for BCC within the phenome-wide human disease category.ConclusionThe study identifies PTGES2 and RNASET2 plasma proteins as novel, reliable biomarkers and therapeutic targets for BCC, suggesting more effective clinical application strategies for patients.

The 2H‐MoTe2 is a well‐known layered 2D semiconductor that is considered as a promising material for next‐generation microelectronic and optoelectronic devices. Te‐deficiency‐induced defective structures, like Te vacancy and mirror twin boundary (MTB), would be generated at elevated temperatures. However, the temperature‐dependent evolution of such defects and their influence on the macroscopic electrical transport property of 2H‐MoTe2 is unclear. Herein, the semiconductor–metal transition phenomenon in 2H‐MoTe2−x mediated by the evolving disordered MTB network with increasing Te deficiency is reported on. The samples are grown by molecular beam epitaxy, while the Te deficiency is tuned by post‐growth flash annealing in ultra‐high vacuum. Low‐temperature scanning tunneling microscope investigation discloses the medium‐range disorder evolution of the MTB network incorporated in the 2H‐MoTe2, which eventually transforms to an ordered metallic Mo5Te8 metastable phase. The scanning tunneling spectroscopy shows rich in‐gap states localized at the MTBs, which provide a conducting channel in the semiconductor. The ultra‐high vacuum in situ transport measurement shows a gradual decrease of resistance of the sample upon flash annealing from 50 to 480 °C, confirming the influence of Te deficiency on the transport property, which would play an essential role in the device performance and durability.

Abstract Ir(III) carbene complexes have been explored as one of the best blue phosphors for their high performance. Herein, the authors designed and synthesized a series of blue‐emitting Ir(III) phosphors (f‐ct9a–c), featuring fac‐coordinated cyano‐imidazo[4,5‐b]pyridin‐2‐ylidene cyclometalates. These Ir(III) complexes exhibit true‐blue emission with a peak maximum spanning 448–467 nm, with high photoluminescence quantum yields of 81–88% recorded in degassed toluene. Moreover, OLED devices bearing phosphors f‐ct9a and f‐ct9b deliver maximum external quantum efficiencies (EQEmax) of 25.9% and 30.3%, together with Commission Internationale de L'Eclairage (CIEx,y) coordinates of (0.157, 0.225) and (0.142, 0.169), respectively. Remarkably, the f‐ct9b‐based device displays an incredible EQE of 29.0% at 5000 cd·m−2. The hyper‐OLED device based on f‐ct9b and ν‐DABNA exhibits an EQEmax of 34.7% and CIEx,y coordinates of (0.122, 0.131), affirming high potentials in achieving efficient blue electroluminescence.

The global spread of highly pathogenic avian influenza (HPAI) A (H5N1) clade 2.3.4.4b virus since 2021 necessitates a re-evaluation of the role of vaccination in controlling HPAI outbreaks among poultry, which has been controversial because of the concern of silent spread with viral mutation and spillover to human. We systematically reviewed and meta-analyzed all existing data from experimental challenge trials to assess the efficacy of HPAI vaccines against mortality in specific pathogen free (SPF) chickens, with evaluation of the certainty of evidence (CoE) using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Out of 223 screened publications, 46 trials met our eligibility criteria. Inactivated vaccines showed an efficacy of 95% (risk ratio [RR] = 5% [95% CI: 1% to 17%], I2 = 0%, CoE high) against homologous strains and an efficacy of 78% (RR = 22% [95% CI: 14% to 37%], I2 = 18%, CoE high) against heterologous strains (test for subgroup difference p = 0.02). Live recombinant vaccines exhibited the highest efficacy at 97% (RR = 3% [95% CI: 1% to 13%], I2 = 0%, CoE high). Inactivated recombinant vaccines had an overall efficacy of 90% (RR = 10% [95% CI: 6% to 16%], I2 = 47%, CoE high). Commercial vaccines showed an overall efficacy of 91% (RR = 9% [95% CI: 5% to 17%], I2 = 23%, CoE high), with 96% efficacy (RR = 4% [95% CI: 1% to 21%], I2 = 0%, CoE high) against homologous strains and 90% efficacy (RR = 10% [95% CI: 5% to 20%], I2 = 31%, CoE moderate) against heterologous strains. Our systematic review offers an updated and unbiased assessment of vaccine efficacy against HPAI-related mortality, providing timely and crucial information for re-evaluating the role of vaccination in poultry avian influenza control policy amist the global HPAI outbreak post-2021.

The increasing demand for immune cell applications, both in clinical settings and in research laboratories, has highlighted the critical need for cryopreservation (banking) methods for T cells. While conventional techniques such as freezing with liquid nitrogen remain prevalent, they pose significant challenges including high equipment costs, safety considerations, and logistical hurdles in transportation. Our cryopreservation medium, C80EZ®, represents a novel approach, leveraging biocompatible polysaccharides as cryoprotectants to enable safe storage at −80°C. This paper presents a comprehensive series of tests assessing the effectiveness of C80EZ® in shielding T cells from the detrimental effects of cryopreservation. Importantly, our findings demonstrate that C80EZ® not only ensures the survival of T cells, with a particular emphasis on preserving the CD8+ subsets, but also maintains their critical function in targeting and eliminating cancer cells.

The principle and application of oil shale in-situ mining technology are reviewed. Oil shale is rich in resources and is an important supplement to petroleum and natural gas as a source of energy. Currently, ground retorting technology is the primary way to produce shale oil because of its elaborated processing method and equipment. However, this technology has several disadvantages such as low thermal efficiency, high environmental pollution and inability to exploit deeply buried oil shale. A novel method called oil shale in-situ mining technology is efficient and environmentally friendly. This technology can exploit deep oil shale while reducing pollution and greenhouse effect. Based on the data collected, this paper summarizes the development of global underground in-situ oil shale mining technology, introduces four heating transfer principles and mathematical models of conduction heating, convection heating, radiation heating and combustion heating, clarifies the process flow, as well as presents advantages and disadvantages of different technologies. It provides a reference for the research of oil shale in-situ mining technology, and also looks into the technologyâs prospects for industrialization, integrating with greenization, information and intelligence.

Abstract Background Cell-free DNA (cfDNA) contains a large amount of molecular information that can be used for multi-cancer early detection (MCED), including changes in epigenetic status of cfDNA, such as cfDNA fragmentation profile. The fragmentation of cfDNA is non-random and may be related to cfDNA methylation. This study provides clinical evidence for the feasibility of inferring cfDNA methylation levels based on cfDNA fragmentation patterns. We performed whole-genome bisulfite sequencing and whole-genome sequencing (WGS) on both healthy individuals and cancer patients. Using the information of whole-genome methylation levels, we investigated cytosine–phosphate–guanine (CpG) cleavage profile and validated the method of predicting the methylation level of individual CpG sites using WGS data. Results We conducted CpG cleavage profile biomarker analysis on data from both healthy individuals and cancer patients. We obtained unique or shared potential biomarkers for each group and built models accordingly. The modeling results proved the feasibility to predict the methylation status of single CpG sites in cfDNA using cleavage profile model from WGS data. Conclusion By combining cfDNA cleavage profile of CpG sites with machine learning algorithms, we have identified specific CpG cleavage profile as biomarkers to predict the methylation status of individual CpG sites. Therefore, methylation profile, a widely used epigenetic biomarker, can be obtained from a single WGS assay for MCED.