Cuproptosis-Related lncRNA Predict Prognosis and Immune Response of LUAD.

Background: Lung cancer is the leading cause of cancer deaths worldwide, primarily due to lung adenocarcinoma (LUAD). However, the heterogeneity of programmed cell death results in varied prognostic and predictive outcomes. This study aimed to develop an LUAD evaluation marker based on cuproptosis-related lncRNAs. Methods: First, transcriptome data and clinical data related to LUAD were downloaded from the Cancer Genome Atlas (TCGA), and cuproptosis-related genes were analyzed to identify cuproptosis-related lncRNAs. Univariate, LASSO, and multivariate Cox regression analyses were conducted to construct cuproptosis-associated lncRNA models. LUAD patients were categorized into high-risk and low-risk groups using prognostic risk values. Kaplan-Meier analysis, PCA, GSEA, and nomograms were employed to evaluate and validate the results. Results: 7 cuproptosis-related lncRNAs were identified, and a risk model was created. High-risk tumors exhibited cuproptosis-related gene alterations in 95.54% of cases, while low-risk tumors showed alterations in 85.65% of cases, mainly involving TP53. The risk value outperformed other clinical variables and tumor mutation burden as a predictor of 1-, 3-, and 5-year overall survival. The cuproptosis-related lncRNA-based risk model demonstrated high validity for LUAD evaluation, potentially influencing individualized treatment approaches. Expression analysis of four candidate cuproptosis-related lncRNAs (AL606834.1, AL161431.1, AC007613.1, and LINC02835) in LUAD tissues and adjacent normal tissues revealed significantly higher expression levels of AL606834.1 and AL161431.1 in LUAD tissues, positively correlating with tumor stage, lymph node metastasis, and histopathological grade. Conversely, AC007613.1 and LINC02835 exhibited lower expression levels, negatively correlating with these factors. High expression of AL606834.1 and AL161431.1 indicated poor prognosis, while low expression of AC007613.1 and LINC02835 was associated with unfavorable outcomes. Univariate and multivariate analyses confirmed these lncRNAs as independent risk factors for LUAD prognosis. Conclusion: The 4 cuproptosis-related (lncRNAsAL606834.1, AL161431.1, AC007613.1, and LINC02835) can accurately predict the prognosis of patients with LUAD and may provide new insights into clinical applications and immunotherapy.

Effects of steam explosion pretreatment on the digestive properties and gut microbiota of Laminaria japonica polysaccharide.

BACKGROUND: Laminaria japonica polysaccharide, which is an important bioactive substance of Laminaria japonica with anti-inflammatory and antioxidant effects. In this study, the molecular weight, functional groups and surface morphology were investigated to evaluate the digestive properties of Laminaria japonica polysaccharide before and after steam explosion. RESULTS: The results indicated that the Laminaria japonica polysaccharide entered the large intestine to be utilized by the gut microbiota after passing through the oral, gastric and small intestinal. Meanwhile, Laminaria japonica polysaccharide of steam explosion promoted the growth of beneficial bacteria Phascolarctobacterium and Intestinimonas, and increased the content of acetic, propionic and butyric acids, which was 2.29-folds, 2.60-folds and 1.63-folds higher than the control group after 48 h of fermentation. CONCLUSION: This study reveals that the effect of steam explosion pretreatment on the digestion in vitro and gut microbiota of Laminaria japonica polysaccharide will provide a basic theoretical basis for the potential application of Laminaria japonica polysaccharide as a prebiotic in the food industry. © 2024 Society of Chemical Industry.

Measures to prevent and treat Nipah virus disease: research priorities for 2024-29.

Nipah virus causes highly lethal disease, with case-fatality rates ranging from 40% to 100% in recognised outbreaks. No treatments or licensed vaccines are currently available for the prevention and control of Nipah virus infection. In 2019, WHO published an advanced draft of a research and development roadmap for accelerating development of medical countermeasures, including diagnostics, therapeutics, and vaccines, to enable effective and timely emergency response to Nipah virus outbreaks. This Personal View provides an update to the WHO roadmap by defining current research priorities for development of Nipah virus medical countermeasures, based primarily on literature published in the last 5 years and consensus opinion of 15 subject matter experts with broad experience in development of medical countermeasures for Nipah virus or experience in the epidemiology, ecology, or public health control of outbreaks of Nipah virus. The research priorities are organised into four main sections: cross-cutting issues (for those that apply to more than one category of medical countermeasures), diagnostics, therapeutics, and vaccines. The strategic goals and milestones identified in each section focus on key achievements that are needed over the next 6 years to ensure that the necessary tools are available for rapid response to future outbreaks of Nipah virus or related henipaviruses.

LASSO-derived nomogram for early identification of pediatric monogenic lupus.

BACKGROUND: Monogenic lupus is defined as systemic lupus erythematosus (SLE)/SLE-like patients with either dominantly or recessively inherited pathogenic variants in a single gene with high penetrance. However, because the clinical phenotype of monogenic SLE is extensive and overlaps with that of classical SLE, it causes a delay in diagnosis and treatment. Currently, there is a lack of early identification models for clinical practitioners to provide early clues for recognition. Our goal was to create a clinical model for the early identification of pediatric monogenic lupus, thereby facilitating early and precise diagnosis and treatment for patients. METHODS: This retrospective cohort study consisted of 41 cases of monogenic lupus treated at the Department of Pediatrics at Peking Union Medical College Hospital from June 2012 to December 2022. The control group consisted of classical SLE patients recruited at a 1:2 ratio. Patients were randomly divided into a training group and a validation group at a 7:3 ratio. A logistic regression model was established based on the least absolute shrinkage and selection operator to generate the coefficient plot. The predictive ability of the model was evaluated using receiver operator characteristic curves and the area under the curve (AUC) index. RESULTS: A total of 41 cases of monogenic lupus patients and 82 cases of classical SLE patients were included. Among the monogenic lupus cases (with a male-to-female ratio of 1:1.05 and ages of onset ranging from birth to 15 years), a total of 18 gene mutations were identified. The variables included in the coefficient plot were age of onset, recurrent infections, intracranial calcifications, growth and developmental delay, abnormal muscle tone, lymphadenopathy/hepatosplenomegaly, and chilblain-like skin rash. Our model demonstrated satisfactory diagnostic performance through internal validation, with an AUC value of 0.97 (95% confidence interval = 0.92-0.97). CONCLUSIONS: We summarized and analyzed the clinical characteristics of pediatric monogenic lupus and developed a predictive model for early identification by clinicians. Clinicians should exercise high vigilance for monogenic lupus when the score exceeds - 9.032299.

Corrigendum: Intratumor tertiary lymphatic structure evaluation predicts the prognosis and immunotherapy response of patients with colorectal cancer.

[This corrects the article DOI: 10.3389/fimmu.2024.1302903.].

Understanding nanoparticle-liver interactions in nanomedicine.

INTRODUCTION: Understanding the interactions between administered nanoparticles and the liver is crucial for developing safe and effective nanomedicines. As the liver can sequester up to 99% of these particles due to its major phagocytic role, understanding these interactions is vital for clinical translation. AREAS COVERED: This review highlights recent studies on nanoparticle-liver interactions, including the influence of nanoparticle physicochemical properties on delivery, strategies to enhance delivery efficiency by modulating liver Kupffer cells, and their potential for treating certain hepatic diseases. Additionally, we discuss how aging impacts the liver's phagocytic functions. EXPERT OPINION: While liver accumulation can hinder nanomedicine safety and effectiveness, it also presents opportunities for treating certain liver diseases. A thorough understanding of nanoparticle-liver interactions is essential for advancing the clinical application of nanomedicines.

Identification of immune-associated biomarkers of diabetes nephropathy tubulointerstitial injury based on machine learning: a bioinformatics multi-chip integrated analysis.

BACKGROUND: Diabetic nephropathy (DN) is a major microvascular complication of diabetes and has become the leading cause of end-stage renal disease worldwide. A considerable number of DN patients have experienced irreversible end-stage renal disease progression due to the inability to diagnose the disease early. Therefore, reliable biomarkers that are helpful for early diagnosis and treatment are identified. The migration of immune cells to the kidney is considered to be a key step in the progression of DN-related vascular injury. Therefore, finding markers in this process may be more helpful for the early diagnosis and progression prediction of DN. METHODS: The gene chip data were retrieved from the GEO database using the search term ' diabetic nephropathy '. The ' limma ' software package was used to identify differentially expressed genes (DEGs) between DN and control samples. Gene set enrichment analysis (GSEA) was performed on genes obtained from the molecular characteristic database (MSigDB. The R package 'WGCNA' was used to identify gene modules associated with tubulointerstitial injury in DN, and it was crossed with immune-related DEGs to identify target genes. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on differentially expressed genes using the 'ClusterProfiler' software package in R. Three methods, least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE) and random forest (RF), were used to select immune-related biomarkers for diagnosis. We retrieved the tubulointerstitial dataset from the Nephroseq database to construct an external validation dataset. Unsupervised clustering analysis of the expression levels of immune-related biomarkers was performed using the 'ConsensusClusterPlus 'R software package. The urine of patients who visited Dongzhimen Hospital of Beijing University of Chinese Medicine from September 2021 to March 2023 was collected, and Elisa was used to detect the mRNA expression level of immune-related biomarkers in urine. Pearson correlation analysis was used to detect the effect of immune-related biomarker expression on renal function in DN patients. RESULTS: Four microarray datasets from the GEO database are included in the analysis : GSE30122, GSE47185, GSE99340 and GSE104954. These datasets included 63 DN patients and 55 healthy controls. A total of 9415 genes were detected in the data set. We found 153 differentially expressed immune-related genes, of which 112 genes were up-regulated, 41 genes were down-regulated, and 119 overlapping genes were identified. GO analysis showed that they were involved in various biological processes including leukocyte-mediated immunity. KEGG analysis showed that these target genes were mainly involved in the formation of phagosomes in Staphylococcus aureus infection. Among these 119 overlapping genes, machine learning results identified AGR2, CCR2, CEBPD, CISH, CX3CR1, DEFB1 and FSTL1 as potential tubulointerstitial immune-related biomarkers. External validation suggested that the above markers showed diagnostic efficacy in distinguishing DN patients from healthy controls. Clinical studies have shown that the expression of AGR2, CX3CR1 and FSTL1 in urine samples of DN patients is negatively correlated with GFR, the expression of CX3CR1 and FSTL1 in urine samples of DN is positively correlated with serum creatinine, while the expression of DEFB1 in urine samples of DN is negatively correlated with serum creatinine. In addition, the expression of CX3CR1 in DN urine samples was positively correlated with proteinuria, while the expression of DEFB1 in DN urine samples was negatively correlated with proteinuria. Finally, according to the level of proteinuria, DN patients were divided into nephrotic proteinuria group (n = 24) and subrenal proteinuria group. There were significant differences in urinary AGR2, CCR2 and DEFB1 between the two groups by unpaired t test (P < 0.05). CONCLUSIONS: Our study provides new insights into the role of immune-related biomarkers in DN tubulointerstitial injury and provides potential targets for early diagnosis and treatment of DN patients. Seven different genes ( AGR2, CCR2, CEBPD, CISH, CX3CR1, DEFB1, FSTL1 ), as promising sensitive biomarkers, may affect the progression of DN by regulating immune inflammatory response. However, further comprehensive studies are needed to fully understand their exact molecular mechanisms and functional pathways in DN.

TYMS Knockdown Suppresses Cells Proliferation, Promotes Ferroptosis via Inhibits PI3K/Akt/mTOR Signaling Pathway Activation in Triple Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is characterized by a grim prognosis and numerous challenges. The objective of our study was to examine the role of thymidylate synthase (TYMS) in TNBC and its impact on ferroptosis. The expression of TYMS was analyzed in databases, along with its prognostic correlation. TYMS positive expression was identified through immunohistochemistry (IHC), while real-time quantitative PCR (qRTPCR) was employed to measure TYMS mRNA levels in various cell lines. Western blotting was utilized to assess protein expression. Cell proliferation, mobility, apoptosis, and reactive oxygen species (ROS) levels were evaluated using CCK8, wound scratch healing assay, transwell assay, and flow cytometry, respectively. Additionally, a tumor xenograft model was established in BALB/c nude mice for further investigation. Tumor volume and weight were measured, and histopathological analysis using hematoxylin and eosin (H&E) staining was conducted to assess tumor tissue changes. IHC staining was employed to detect the expression of Ki67 in tumor tissues. High expression of TYMS was observed in TNBC and was found to be correlated with poor prognosis in patients. Among various cell lines, TYMS expression was highest in BT549 cells. Knockdown of TYMS resulted in suppression of cell proliferation and mobility, as well as promotion of apoptosis. Furthermore, knockdown of TYMS led to increased accumulation of ROS and Fe2+ levels, along with upregulation of ACLS4 expression and downregulation of glutathione peroxidase 4 (GPX4) expression. In vivo studies showed that knockdown of TYMS inhibited tumor growth. Additionally, knockdown of TYMS was associated with inhibition of mTOR, p-PI3K, and p-Akt expression. Our research showed that the knockdown of TYMS suppressed the TNBC progression by inhibited cells proliferation via ferroptosis. Its underlying mechanism is related to the PI3K /Akt pathway. Our study provides a novel sight for the suppression effect of TYMS on TNBC.

Whole genome resequencing reveals the adaptability of native chickens to drought, tropical and frigid environments in Xinjiang.

Chickens exhibit extensive genetic diversity and are distributed worldwide. Different chicken breeds have evolved to thrive in diverse environmental conditions. However, research on the genetic mechanisms underlying chicken adaptation to extreme environments, such as tropical, frigid and drought-prone regions, remains limited. In this study, we conducted whole-genome sequencing of 240 individuals from six native chicken breeds in Xinjiang, China, as well as 4 publicly available chicken breeds inhabiting regions with varying annual precipitations, temperatures, and altitudes. Our analysis revealed several genetic variants among the examined breeds. Furthermore, we investigated the genetic diversity and population structure of breeds residing in extreme drought and temperature environments by comparing them. Notably, native chicken breeds exhibited different genetic diversity and population structures. Moreover, we identified candidate genes associated with chicken adaptability to the environment, such as CORO2A, CTNNA3, AGMO, GRID2, BBOX1, COL3A1, INSR, SOX5, MAP2 and PLPPR1. Additionally, pathways such as lysosome, cysteine and methionine metabolism, glycosaminoglycan degradation, and Wnt signaling may be play crucial roles in regulating chicken adaptation to drought environments. Overall, these findings contribute to our understanding of the genetic mechanisms governing chicken adaptation to extreme environments, and also offer insights for enhancing the resilience of chicken breeds to different climatic conditions.

Multiplex cerebrospinal fluid proteomics identifies biomarkers for diagnosis and prediction of Alzheimer's disease.

Recent expansion of proteomic coverage opens unparalleled avenues to unveil new biomarkers of Alzheimer's disease (AD). Among 6,361 cerebrospinal fluid (CSF) proteins analysed from the ADNI database, YWHAG performed best in diagnosing both biologically (AUC = 0.969) and clinically (AUC = 0.857) defined AD. Four- (YWHAG, SMOC1, PIGR and TMOD2) and five- (ACHE, YWHAG, PCSK1, MMP10 and IRF1) protein panels greatly improved the accuracy to 0.987 and 0.975, respectively. Their superior performance was validated in an independent external cohort and in discriminating autopsy-confirmed AD versus non-AD, rivalling even canonical CSF ATN biomarkers. Moreover, they effectively predicted the clinical progression to AD dementia and were strongly associated with AD core biomarkers and cognitive decline. Synaptic, neurogenic and infectious pathways were enriched in distinct AD stages. Mendelian randomization did not support the significant genetic link between CSF proteins and AD. Our findings revealed promising high-performance biomarkers for AD diagnosis and prediction, with implications for clinical trials targeting different pathomechanisms.

Single-Cell RNA Sequencing Reveals Transcriptional Signatures and Cell-Cell Communication in Diabetic Retinopathy.

BACKGROUND: Diabetic retinopathy (DR) is a major cause of vision loss in workingage individuals worldwide. Cell-to-cell communication between retinal cells and retinal pigment epithelial cells (RPEs) in DR is still unclear, so this study aimed to generate a single-cell atlas and identify receptor‒ligand communication between retinal cells and RPEs. METHODS: A mouse single-cell RNA sequencing (scRNA-seq) dataset was retrieved from the GEO database (GSE178121) and was further analyzed with the R package Seurat. Cell cluster annotation was performed to further analyze cell‒cell communication. The differentially expressed genes (DEGs) in RPEs were explored through pathway enrichment analysis and the protein‒ protein interaction (PPI) network. Core genes in the PPI were verified by quantitative PCR in ARPE-19 cells. RESULTS: We observed an increased proportion of RPEs in STZ mice. Although some overall intercellular communication pathways did not differ significantly in the STZ and control groups, RPEs relayed significantly more signals in the STZ group. In addition, THBS1, ITGB1, COL9A3, ITGB8, VTN, TIMP2, and FBN1 were found to be the core DEGs of the PPI network in RPEs. qPCR results showed that the expression of ITGB1, COL9A3, ITGB8, VTN, TIMP2, and FBN1 was higher and consistent with scRNA-seq results in ARPE-19 cells under hyperglycemic conditions. CONCLUSION: Our study, for the first time, investigated how signals that RPEs relay to and from other cells underly the progression of DR based on scRNA-seq. These signaling pathways and hub genes may provide new insights into DR mechanisms and therapeutic targets.

Quantum-Confined Perovskite Nanocrystals Enabled by Negative Catalyst Strategy for Efficient Light-Emitting Diodes.

The perovskite nanocrystals (PeNCs) are emerging as a promising emitter for light-emitting diodes (LEDs) due to their excellent optical and electrical properties. However, the ultrafast growth of PeNCs often results in large sizes exceeding the Bohr diameter, leading to low exciton binding energy and susceptibility to nonradiative recombination, while small-sized PeNCs exhibit a large specific surface area, contributing to an increased defect density. Herein, Zn2+ ions as a negative catalyst to realize quantum-confined FAPbBr3 PeNCs with high photoluminescence quantum yields (PL QY) over 90%. Zn2+ ions exhibit robust coordination with Br- ions is introduced, effectively retarding the participation of Br- ions in the perovskite crystallization process and thus facilitating PeNCs size control. Notably, Zn2+ ions neither incorporate into the perovskite lattice nor are absorbed on the surface of PeNCs. And the reduced growth rate also promotes sufficient octahedral coordination of PeNC that reduces defect density. The LEDs based on these optimized PeNCs exhibits an external quantum efficiency (EQE) of 21.7%, significantly surpassing that of the pristine PeNCs (15.2%). Furthermore, the device lifetime is also extended by twofold. This research presents a novel approach to achieving high-performance optoelectronic devices.

Precision arbovirus serology with a pan-arbovirus peptidome.

Arthropod-borne viruses represent a crucial public health threat. Current arboviral serology assays are either labor intensive or incapable of distinguishing closely related viruses, and many zoonotic arboviruses that may transition to humans lack any serologic assays. In this study, we present a programmable phage display platform, ArboScan, that evaluates antibody binding to overlapping peptides that represent the proteomes of 691 human and zoonotic arboviruses. We confirm that ArboScan provides detailed antibody binding information from animal sera, human sera, and an arthropod blood meal. ArboScan identifies distinguishing features of antibody responses based on exposure history in a Colombian cohort of Zika patients. Finally, ArboScan details epitope level information that rapidly identifies candidate epitopes with potential protective significance. ArboScan thus represents a resource for characterizing human and animal arbovirus antibody responses at cohort scale.

Relationship between dietary fiber intake and chronic diarrhea in adults.

BACKGROUND: Dietary fiber is essential for human health and can help reduce the symptoms of constipation. However, the relationship between dietary fiber and diarrhea is, poorly understood. AIM: To evaluate the relationship between dietary fiber and chronic diarrhea. METHODS: This retrospective study was conducted using data from the United States National Health and Nutrition Examination Survey, conducted between 2005 and 2010. Participants over the age of 20 were included. To measure dietary fiber consumption, two 24-hour meal recall interviews were conducted. The independent relationship between the total amount of dietary fiber and chronic diarrhea was evaluated with multiple logistic regression and interaction analysis. RESULTS: Data from 12829 participants were analyzed. Participants without chronic diarrhea consumed more dietary fiber than participants with chronic diarrhea (29.7 vs 28.5, P = 0.004). Additionally, in participants with chronic diarrhea, a correlation between sex and dietary fiber intake was present: Women who consume more than 25 g of dietary fiber daily can reduce the occurrence of chronic diarrhea. CONCLUSION: Dietary fiber can reduce the occurrence of chronic diarrhea.

Orally administrated liquid metal agents for inflammation-targeted alleviation of inflammatory bowel diseases.

Rapid drug clearance and off-target effects of therapeutic drugs can induce low bioavailability and systemic side effects and gravely restrict the therapeutic effects of inflammatory bowel diseases (IBDs). Here, we propose an amplifying targeting strategy based on orally administered gallium (Ga)-based liquid metal (LM) nano-agents to efficiently eliminate reactive oxygen and nitrogen species (RONS) and modulate the dysregulated microbiome for remission of IBDs. Taking advantage of the favorable adhesive activity and coordination ability of polyphenol structure, epigallocatechin gallate (EGCG) is applied to encapsulate LM to construct the formulations (LM-EGCG). After adhering to the inflamed tissue, EGCG not only eliminates RONS but also captures the dissociated Ga to form EGCG-Ga complexes for enhancive accumulation. The detained composites protect the intestinal barrier and modulate gut microbiota for restoring the disordered enteral microenvironment, thereby relieving IBDs. Unexpectedly, LM-EGCG markedly decreases the Escherichia_Shigella populations while augmenting the abundance of Akkermansia and Bifidobacterium, resulting in favorable therapeutic effects against the dextran sulfate sodium-induced colitis.

Latent profiles of narrative competence and professional identity among nursing students: A cross-sectional analytic study based on the Ring theory of personhood.

AIM: To identify latent profiles of narrative competence in nursing students and examine the association between the potential competence profiles and professional identity from a person-centred perspective. BACKGROUND: According to the Ring theory of personhood, nursing students can develop their professional identities from individual, relational and social aspects through interaction with patients, as well as listening to, understanding and responding to patients' disease narratives. However, few studies have examined the relationship between narrative competence and professional identity through the quantitative method. DESIGN: A cross-sectional analytic study. METHODS: A total of 472 nursing students responded to the survey between March and May 2023. The Professional Identity Questionnaire for Nurse Students and the Narrative Competence Scale were given to participants. Latent profile analysis was conducted to identify narrative competence profiles. The Bolck-Croon-Hagenaars method was used to analyse whether these latent profiles for narrative competence affected nursing students' general, individual, interpersonal and social professional identities. RESULTS: Latent profiles were identified as "low narrative competence" (12.1 %), "relatively low narrative competence" (39.9 %), "moderate narrative competence" (40.1 %) and "high narrative competence" (7.9 %). The profiles only show level differences rather than combinations of competence areas. These profiles had varying effects on the nursing students' general professional identities, as well as their individual, relational and social professional identities. CONCLUSION: This study highlights the significance of providing tailored guidance and support to nursing students, taking into account their unique narrative competency profile, to promote the formation of professional identity from individual, relational and social aspects. Nursing educators should effectively distinguish nursing students with inadequate narrative competence and value patients' disease narratives to promote narrative competence and professional identity.

Predicting High-Risk Esophageal Varices in Cirrhosis: A Multi-Parameter Splenic CT Study.

RATIONALE AND OBJECTIVES: To explore the value of splenic hemodynamic parameters from low-dose one-stop dual-energy and perfusion CT (LD-DE&PCT) in non-invasively predicting high-risk esophageal varices (HREV) in cirrhotic patients. METHODS: We retrospectively analyzed cirrhotic patients diagnosed with esophageal varices (EV) through clinical, laboratory, imaging, and endoscopic examinations from September 2021 to December 2023 in our hospital. All patients underwent LD-DE&PCT to acquire splenic iodine concentration and perfusion parameters. Radiation dose was recorded. Patients were classified into non-HREV and HREV groups based on endoscopy. Univariate and multivariate logistic regression analysis were performed, and the prediction model for HREV was constructed. P < 0.05 was considered statistically significant. RESULTS: Univariate analysis revealed that significant differences were found in portal iodine concentration (PIC), blood flow (BF), permeability surface (PS), spleen volume (V-S), total iodine concentration (TIC), and total blood volume of the spleen (BV-S) between groups. TIC demonstrated the highest predictive value with an area under the curve (AUC) value of 0.87. Multivariate analysis showed that PIC, PS, and BV-S were independent risk factors for HREV. The logistic regression model for predicting HREV had an AUC of 0.93. The total radiation dose was 20.66 ± 4.07 mSv. CONCLUSION: Splenic hemodynamic parameters obtained from LD-DE&PCT can non-invasively and accurately assess the hemodynamic status of the spleen in cirrhotic patients with EV and predict the occurrence of HREV. Despite the retrospective study design and limited sample size of this study, these findings deserve further validation through prospective studies with larger cohorts.

Omni-dimensional dynamic convolution feature coordinate attention network for pneumonia classification.

Pneumonia is a serious disease that can be fatal, particularly among children and the elderly. The accuracy of pneumonia diagnosis can be improved by combining artificial-intelligence technology with X-ray imaging. This study proposes X-ODFCANet, which addresses the issues of low accuracy and excessive parameters in existing deep-learning-based pneumonia-classification methods. This network incorporates a feature coordination attention module and an omni-dimensional dynamic convolution (ODConv) module, leveraging the residual module for feature extraction from X-ray images. The feature coordination attention module utilizes two one-dimensional feature encoding processes to aggregate feature information from different spatial directions. Additionally, the ODConv module extracts and fuses feature information in four dimensions: the spatial dimension of the convolution kernel, input and output channel quantities, and convolution kernel quantity. The experimental results demonstrate that the proposed method can effectively improve the accuracy of pneumonia classification, which is 3.77% higher than that of ResNet18. The model parameters are 4.45M, which was reduced by approximately 2.5 times. The code is available at https://github.com/limuni/X-ODFCANET .

Genetic diversity and shallow genetic differentiation of the endangered scaly-sided merganser Mergus squamatus.

Examining patterns of genetic diversity are crucial for conservation planning on endangered species, while inferring the underlying process of recent anthropogenic habitat modifications in the context potential long-term demographic changes remains challenging. The globally endangered scaly-sided merganser (SSME), Mergus squamatus, is endemic to a narrow range in Northeast Asia, and its population has recently been contracted into two main breeding areas. Although low genetic diversity has been suggested in the Russian population, the genetic status and demographic history of these individuals have not been fully elucidated. We therefore examined the genetic diversity and structure of the breeding populations of the SSME and investigated the relative importance of historical and recent demographic changes to the present-day pattern of genetic diversity. Using 10 nuclear microsatellite (SSR) markers and mitochondrial DNA (mtDNA) control region sequences, we found limited female-inherited genetic diversity and a high level of nuclear genetic diversity. In addition, analysis of both markers consistently revealed significant but weak divergence between the breeding populations. Inconsistent demographic history parameters calculated from mtDNA and bottleneck analysis results based on SSR suggested a stable historical effective population size. By applying approximate Bayesian computation, it was estimated that populations started to genetically diverge from each other due to recent fragmentation events caused by anthropogenic effects rather than isolation during Last Glacial Maximum (LGM) and post-LGM recolonization. These results suggest that limited historical population size and shallow evolutionary history may be potential factors contributing to the contemporary genetic diversity pattern of breeding SSME populations. Conservation efforts should focus on protecting the current breeding habitats from further destruction, with priority given to both the Russian and Chinese population, as well as restoring the connected suitable breeding grounds.