Network Analysis Research Articles

Pooled network analysis of pesticide exposure mixtures in conventional and organic smallholder farmers in Uganda and Costa Rica

Pooled network analysis of pesticide exposure mixtures in conventional and organic smallholder farmers in Uganda and Costa Rica

Standoff Identification of Plastic Waste Using a Low-Cost Compact Laser-Induced Breakdown Spectroscopy (LIBS) Detection System.

We report the standoff/remote identification of post-consumer plastic waste by utilizing a low-cost and compact standoff laser-induced breakdown spectroscopy (ST-LIBS) detection system. A single plano-convex lens is used for collecting the optical emissions from the plasma at a standoff distance of 6.5 m. A compact non-gated Czerny-Turner charge-coupled device (CCD) spectrometer (CT-CCD) is utilized to analyze the optical response. The single lens and CT-CCD combination not only reduces the cost of the detection system by tenfold, but also decreases the collection system size and weight compared to heavy telescopic-based intensified CCD systems. All the samples investigated in this study were collected from a local recycling plant. All the measurements were performed with only a single laser shot which enables rapid identification while probing a large number of samples in real time. Furthermore, principal component analysis has shown excellent separation among the samples and an artificial neural network analysis has revealed that plastic waste can be identified within ∼10 ms only (testing time) with accuracies up to ∼99%. Finally, these results have the potential to build a compact and low-cost ST-LIBS detection system for the rapid identification of plastic waste for real-time waste management applications.

Symptom clusters and network analysis of patients with intermediate and advanced liver cancer treated with targeted immunotherapy.

This study aims to identify symptom clusters in patients with intermediate and advanced liver cancer receiving targeted immunotherapy, focusing on core and bridge symptoms to establish a foundation for precise symptom management. This study used a cross-sectional survey and utilized convenience sampling from May 2023 to January 2024 at a third-class hospital in Shanghai, China. The severity of symptoms in liver cancer patients during treatment was evaluated using the Memorial Symptom Assessment Scale. Network analysis was employed to depict the interrelation of symptom clusters and identify core and bridge symptoms. The symptoms were classified by severity into five clusters: oral, gastrointestinal, fatigue-related, body image, and pain-sleep. Within the symptom network, the core symptoms were pain, "I don't look like myself," and nausea, while the critical bridge symptoms included pain, itching, and feeling bloated. The strongest connections were observed between nausea and vomiting, followed by taste changes and dry mouth, as well as weight loss and "I don't look like myself." In patients receiving targeted immunotherapy for intermediate and advanced liver cancer, multiple symptoms can emerge simultaneously, forming interconnected clusters. By identifying and intervening in core and bridge symptoms, personalized management strategies can be developed to relieve other symptoms and disrupt connections between symptom clusters, thereby enhancing symptom management efficacy. This study has significant clinical and research implications, offering new insights to improve patients' quality of life and treatment outcomes.

A meta-analysis of genome-wide studies of resilience in the German population.

Resilience is the capacity to adapt to stressful life events. As such, this trait is associated with physical and mental functions and conditions. Here, we aimed to identify the genetic factors contributing to shape resilience. We performed variant- and gene-based meta-analyses of genome-wide association studies from six German cohorts (N = 15822) using the 11-item version of the Resilience Scale (RS-11) as outcome measure. Variant- and gene-level results were combined to explore the biological context using network analysis. In addition, we conducted tests of correlation between RS-11 and the polygenic scores (PGSs) for 12 personality and mental health traits in one of these cohorts (PROCAM-2, N = 3879). The variant-based analysis found no signals associated with resilience at the genome-wide level (p < 5 × 10-8), but suggested five genomic loci (p < 1 × 10-5). The gene-based analysis identified three genes (ROBO1, CIB3 and LYPD4) associated with resilience at genome-wide level (p < 2.48 × 10-6) and 32 potential candidates (p < 1 × 10-4). Network analysis revealed enrichment of biological pathways related to neuronal proliferation and differentiation, synaptic organization, immune responses and vascular homeostasis. We also found significant correlations (FDR < 0.05) between RS-11 and the PGSs for neuroticism and general happiness. Overall, our observations suggest low heritability of resilience. Large, international efforts will be required to uncover the genetic factors that contribute to shape trait resilience. Nevertheless, as the largest investigation of the genetics of resilience in general population to date, our study already offers valuable insights into the biology potentially underlying resilience and resilience's relationship with other personality traits and mental health.

Evolution of passing network in the Soccer World Cups 2010–2022

ABSTRACT This study investigates the evolution of passing networks (PN) at both team and player levels in the FIFA World Cups (WC) from 2010 to 2022. Analyzing 256 matches (7328 player observations) using a multiple-camera tracking system across four WCs, we considered six playing positions: goalkeeper (n = 521), central defender (n = 1192), fullback (n = 1223), midfielder (n = 2039), winger (n = 1320), and central forward (n = 1033). We used 17 network metrics and considered contextual variables such as team formation, and team ranking. Linear mixed-effect models analyzed differences in team and player PN parameters by year and team strength. Results showed a shift from possession-play to direct-play from the 2010 to 2018 WCs, with possession-play returning in 2022. Specifically, high- and low-quality teams significantly decreased their density, average degree (AD), modularity, and average path length in 2018 (p < 0.05). High-quality teams showed increased density, AD, and average weighted degree in 2022 (p < 0.05). Midfielders and central forwards exhibited significantly lower centrality parameters, whereas central defenders and goalkeepers showed increased centrality parameters (p < 0.05). This study highlights the evolutionary trends of passing relationships from a network analysis perspective over twelve years, providing insights into the changing dynamics of team interactions and positional prominence in elite soccer.

A multiscale functional map of somatic mutations in cancer integrating protein structure and network topology.

A major goal of cancer biology is to understand the mechanisms underlying tumorigenesis driven by somatically acquired mutations. Two distinct types of computational methodologies have emerged: one focuses on analyzing clustering of mutations within protein sequences and 3D structures, while the other characterizes mutations by leveraging the topology of protein-protein interaction network. Their insights are largely non-overlapping, offering complementary strengths. Here, we established a unified, end-to-end 3D structurally-informed protein interaction network propagation framework, NetFlow3D, that systematically maps the multiscale mechanistic effects of somatic mutations in cancer. The establishment of NetFlow3D hinges upon the Human Protein Structurome, a comprehensive repository we compiled that incorporates the 3D structures of every single protein as well as the binding interfaces of all known protein interactions in humans. NetFlow3D leverages the Structurome to integrate information across atomic, residue, protein and network levels: It conducts 3D clustering of mutations across atomic and residue levels on protein structures to identify potential driver mutations. It then anisotropically propagates their impacts across the protein interaction network, with propagation guided by the specific 3D structural interfaces involved, to identify significantly interconnected network "modules", thereby uncovering key biological processes underlying disease etiology. Applied to 1,038,899 somatic protein-altering mutations in 9,946 TCGA tumors across 33 cancer types, NetFlow3D identified 1,4444 significant 3D clusters throughout the Human Protein Structurome, of which ~55% would not have been found if using only experimentally-determined structures. It then identified 26 significantly interconnected modules that encompass ~8-fold more proteins than applying standard network analyses. NetFlow3D and our pan-cancer results can be accessed from http://netflow3d.yulab.org.

FOSL1-mediated LINC01566 negatively regulates CD4+ T-cell activation in myasthenia gravis

BackgroundMyasthenia gravis (MG) is an autoimmune disease characterized by pathogenic antibodies that target structures of the neuromuscular junction. The evidence suggests that the regulation of long noncoding RNAs (lncRNAs) that is mediated by transcription factors (TFs) plays a key role in the pathophysiology of MG. Nevertheless, the detailed molecular mechanisms of lncRNAs in MG remain largely undetermined.MethodsUsing microarray analysis, we analyzed the lncRNA levels in MG. By bioinformatics analysis, LINC01566 was found to potentially play an important role in MG. First, qRT‒PCR was performed to verify the LINC1566 expressions in MG patients. Then, fluorescence in situ hybridization was conducted to determine the localization of LINC01566 in CD4 + T cells. Finally, the impact of LINC01566 knockdown or overexpression on CD4 + T-cell function was also analyzed using flow cytometry and CCK-8 assay. A dual-luciferase reporter assay was used to validate the binding of the TF FOSL1 to the LINC01566 promoter.ResultsBased on the lncRNA microarray and differential expression analyses, we identified 563 differentially expressed (DE) lncRNAs, 450 DE mRNAs and 19 DE TFs in MG. We then constructed a lncRNA-TF-mRNA network. Through network analysis, we found that LINC01566 may play a crucial role in MG by regulating T-cell-related pathways. Further experiments indicated that LINC01566 is expressed at low levels in MG patients. Functionally, LINC01566 is primarily distributed in the nucleus and can facilitate CD4 + T-cell apoptosis and inhibit cell proliferation. Mechanistically, we hypothesized that LINC01566 may negatively regulate the expressions of DUSP3, CCR2, FADD, SIRPB1, LGALS3 and SIRPB1, which are involved in the T-cell activation pathway, to further influence the cellular proliferation and apoptosis in MG. Moreover, we found that the effect of LINC01566 on CD4 + T cells in MG was mediated by the TF FOSL1, and in vitro experiments indicated that FOSL1 can bind to the promoter region of LINC01566.ConclusionsIn summary, our research revealed the protective roles of LINC01566 in clinical samples and cellular experiments, illustrating the potential roles and mechanism by which FOSL1/LINC01566 negatively regulates CD4 + T-cell activation in MG.

Multi-Omics Analysis of Primary Prostate Cancer Datasets Reveals Novel Biomarkers.

Prostate cancer (PCa) ranks second in cancer-related deaths in men. Current screenings used in the diagnosis are not sufficient enough in the early stages therefore, more diagnostic biomarker studies are needed. We performed a meta-analysis on the biomarker potential of miRNAs, mRNAs, and methylation for the early stages of PCa by searching available microarrays from the GEO dataset for PCa tissue and benign prostatic hyperplasia (BPH) or normal adjacent to PCa. Target genes of miRNAs were determined using the miRWalk and miRDB datasets. The results were visualized using network analysis. qPCR quantification of potential miRNA and genes was performed in human prostate epithelial cell line (RWPE-1) and human prostate carcinoma epithelial cell line (22RV1). Our meta-analysis of potential biomarkers for the diagnosis of PCa identified several candidates. It was shown that miR-7-5p is overexpressed. CAMKK2, TMEM97 expression were upregulated and CLIP1 expression was downregulated and these genes were shown to be targets of miR-7-5p. CAMKK2, TMEM97, and CLIP1 genes were found to be hypermethylated. Although the changes in the expression levels of miR-7-5p and CAMKK2, TMEM97, and CLIP1 in the two cell lines used in our study were not consistent with the significant expression differences observed in the meta-analysis, our meta-analysis results would be promising in human prostate tissue or different human tumor cell line studies. This highlights the importance of our meta-analysis results in prostate cancer biomarker research, given the difficulty of experimental validation of our large-scale data meta-analysis results using a specific cell line.

Biosynthesized silver nanoparticles mediated by Ammi visnaga extract enhanced systemic resistance and triggered multiple defense-related genes, including SbWRKY transcription factors, against tobacco mosaic virus infection

BackgroundTobacco mosaic virus (TMV) is a highly infectious plant virus that affects a wide variety of plants and reduces crop yields around the world. Here, we assessed the effectiveness of using Ammi visnaga aqueous seed extract to synthesize silver nanoparticles (Ag-NPs) and their potential to combat TMV. Different techniques were used to characterize Ag-NPs, such as scanning and transmission electron microscopy (SEM, TEM), energy-dispersive X-ray spectroscopy (EDS), fourier transform infrared spectroscopy (FTIR), and dynamic light scattering (DLS).ResultsTEM demonstrated that the synthesized Ag-NPs had a spherical form with an average size of 23–30 nm and a zeta potential value of -15.9 mV, while FTIR revealed various functional groups involved in Ag-NP stability and capping. Interestingly, the Pre-treatment of tobacco plants (protective treatment) with Ag-NPs at 100–500 µg/mL significantly suppressed viral symptoms, while the Post-treatment (curative treatment) delayed their appearance. Furthermore, protective and curative treatments significantly increased chlorophyll a and b, total flavonoids, total soluble carbohydrates, and antioxidant enzymes activity (PPO, POX and CAT). Simultaneously, the application of Ag-NPs resulted in a decrease in levels of oxidative stress markers (H2O2 and MDA). The RT-qPCR results and volcano plot analysis showed that the Ag-NPs treatments trigger and regulate the transcription of ten defense-related genes (SbWRKY-1, SbWRKY-2, JERF-3, GST-1, POD, PR-1, PR-2, PR-12, PAL-1, and HQT-1). The heatmap revealed that GST-1, the primary gene involved in anthocyanidin production, was consistently the most expressed gene across all treatments throughout the study. Analysis of the gene co-expression network revealed that SbWRKY-19 was the most central gene among the studied genes, followed by PR-12 and PR-2.ConclusionsOverall, the reported antiviral properties (protective and/or curative) of biosynthesized Ag-NPs against TMV lead us to recommend using Ag-NPs as a simple, stable, and eco-friendly agent in developing pest management programs against plant viral infections.

Microvascular plasticity in mouse stroke model recovery: Anatomy statistics, dynamics measured by longitudinal in vivo two-photon angiography, network vectorization.

This manuscript quantitatively investigates remodeling dynamics of the cortical microvascular network (thousands of connected capillaries) following photothrombotic ischemia (cubic millimeter volume, imaged weekly) using a novel in vivo two-photon angiography and high throughput vascular vectorization method. The results suggest distinct temporal patterns of cerebrovascular plasticity, with acute remodeling peaking at one week post-stroke. The network architecture then gradually stabilizes, returning to a new steady state after four weeks. These findings align with previous literature on neuronal plasticity, highlighting the correlation between neuronal and neurovascular remodeling. Quantitative analysis of neurovascular networks using length- and strand-based statistical measures reveals intricate changes in network anatomy and topology. The distance and strand-length statistics show significant alterations, with a peak of plasticity observed at one week post-stroke, followed by a gradual return to baseline. The orientation statistic plasticity peaks at two weeks, gradually approaching the (conserved across subjects) stroke signature. The underlying mechanism of the vascular response (angiogenesis vs. tissue deformation), however, is yet unexplored. Overall, the combination of chronic two-photon angiography, vascular vectorization, reconstruction/visualization, and statistical analysis enables both qualitative and quantitative assessments of neurovascular remodeling dynamics, demonstrating a method for investigating cortical microvascular network disorders and the therapeutic modes of action thereof.

Antitumorigenic potential of Lactobacillus-derived extracellular vesicles: p53 succinylation and glycolytic reprogramming in intestinal epithelial cells via SIRT5 modulation

ObjectiveColorectal cancer progression involves complex cellular mechanisms. This study examines the effects of Lactobacillus plantarum-derived extracellular vesicles (LEVs) on the SIRT5/p53 axis, focusing on glycolytic metabolic reprogramming and abnormal proliferation in intestinal epithelial cells.MethodsLEVs were isolated from Lactobacillus plantarum and incubated with Caco-2 cells. Differential gene expression was analyzed through RNA sequencing and compared with TCGA-COAD data. Key target genes and pathways were identified using PPI network and pathway enrichment analysis. Various assays, including RT-qPCR, EdU staining, colony formation, flow cytometry, and Western blotting, were used to assess gene expression, cell proliferation, and metabolic changes. Co-immunoprecipitation confirmed the interaction between SIRT5 and p53, and animal models were employed to validate in vivo effects.ResultsBioinformatics analysis indicated the SIRT5/p53 axis as a critical pathway in LEVs' modulation of colorectal cancer. LEVs were found to inhibit colorectal cancer cell proliferation and glycolytic metabolism by downregulating SIRT5, influencing p53 desuccinylation. In vivo, LEVs regulated this axis, reducing tumor formation in mice. Clinical sample analysis showed that SIRT5 and p53 succinylation levels correlated with patient prognosis.ConclusionLactobacillus-derived extracellular vesicles play a pivotal role in suppressing colonic tumor formation by modulating the SIRT5/p53 axis. This results in decreased glycolytic metabolic reprogramming and reduced proliferation in intestinal epithelial cells.

Comparative Analysis of Networking and Mentorship in Enhancing Soft Skills AmongDental Undergraduates, A Quantitative Study in a private dental college.

Introduction: The acquisition of soft skills is essential for undergraduate Bachelor of Dental Surgery (BDS) students, enhancing their ability to communicate, collaborate, and adapt in the dynamic field of dental practice. While networking and mentorship are both recognized as valuable methods for developing these skills, their comparative effectiveness remains unclear. This study aims to evaluate the impact of networking and mentorship on the development of soft skills among BDS students in a private dental college. Methodology: A cross-sectional quantitative approach was used, involving a survey administered via Google Forms. The study population comprised 250 participants, including current BDS students, alumni, and faculty members from Liaquat College of Medicine and Dentistry. Data were collected over six weeks, focusing on participation in networking and mentorship activities, and self-assessment of soft skills development. Statistical analysis was conducted using SPSS 25 to compare the effectiveness of these two approaches. Results: Of the 250 respondents, 64% participated in networking activities, while 48% engaged in mentorship programs. Networking activities primarily included student organization gatherings and professional conferences, whereas mentorship was mostly one-on-one. Participants rated their competencies in various soft skills on a scale of 1 to 5. Networking was found to be more effective in enhancing communication, teamwork, problem-solving, and adaptability, with 48% of participants favoring it over mentorship. Mentorship, although less impactful in certain domains, provided significant individual guidance and career support. Conclusion: The study highlights the complementary roles of networking and mentorship in developing soft skills among BDS students. Networking was particularly effective in enhancing communication and teamwork, while mentorship offered personalized support. Integrating both approaches into dental curricula can provider a supportive learning environment, promoting comprehensive professional growth. Future research should consider diverse sampling and objective measures to validate these findings. This study highlights the importance of structured networking and mentorship programs in dental education, benefiting students, practitioners, and faculty alike.

Rosiglitazone attenuates Acute Kidney Injury from hepatic ischemia-reperfusion in mice by inhibiting arachidonic acid metabolism through the PPAR-γ/NF-κB pathway.

Acute Kidney Injury (AKI), a prevalent complication of Liver Transplantation (LT) that occurs during the perioperative period has been established to profoundly impact the prognosis of transplant recipients. This study aimed to investigate the mechanism of the hepatic IRI-induced AKI and to identify potential therapeutic targets for treating this condition and improving the prognosis of LT patients. An integrated transcriptomics and proteomics approach was employed to investigate transcriptional and proteomic alterations in hepatic IRI-induced AKI and the hypoxia-reoxygenation (H/R) model using TCMK-1 cells and the hepatic IRI-induced AKI mouse model using male C57BL/6J mice were employed to elucidate the underlying mechanisms. Hematoxylin-eosin staining, reverse transcription quantitative polymerase chain reaction, enzyme-linked immunosorbent assay and Western blot were used to assess the effect of Rosiglitazone(RGZ) on hepatic IRI-induced AKI in vitro and in vivo. According to the results, 322 genes and 128 proteins were differentially expressed between the sham and AKI groups. Furthermore, Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomics (KEGG) pathway analyses revealed significant enrichment in pathways related to amino acid and lipid metabolism. Additionally, the Protein-Protein Interaction (PPI) network analysis of the kidney tissues obtained from a hepatic IRI-induced AKI mouse model highlighted arachidonic acid metabolism as the most prominent pathway. Animal and cellular analyses further revealed that RGZ, a PPAR-γ agonist, could inhibit the expression of the PPAR-γ/NF-κB signaling pathway-associated proteins in in vitro and in vivo. These findings collectively suggest that RGZ ameliorates hepatic IRI-induced AKI via PPAR-γ/NF-κB signaling pathway modulation, highlighting PPAR-γ as a crucial therapeutic target for AKI prevention post-LT.

ExomiRHub: A comprehensive database for hosting and analyzing human disease-related extracellular microRNA transcriptomics data

Extracellular microRNA (miRNA) expression data generated by different laboratories exhibit heterogeneity, which poses challenges for biologists without bioinformatics expertise. To address this, we introduce ExomiRHub (http://www.biomedical-web.com/exomirhub/), a user-friendly database designed for biologists. This database incorporates 191 human extracellular miRNA expression datasets associated with 112 disease phenotypes, 62 treatments, and 24 genotypes, encompassing 29,198 and 23 sample types. ExomiRHub also integrates 16,012 miRNA transcriptomes of 156 cancer subtypes from The Cancer Genome Atlas. All the data in ExomiRHub were further standardized and curated with annotations. The platform offers 25 analytical functions, including differential expression, co-expression, Weighted Gene Co-Expression Network Analysis (WGCNA), feature selection, and functional enrichment, enabling users to select samples, define groups, and customize parameters for analyses. Moreover, ExomiRHub provides a web service that allows biologists to analyze their uploaded miRNA expression data. Four additional tools were developed to evaluate the functions and targets of miRNAs and miRNA variations. Through ExomiRHub, we identified extracellular miRNA biomarkers associated with angiogenesis for monitoring glioma progression, demonstrating its potential to significantly accelerate the discovery of extracellular miRNA biomarkers.

The Changsha historic urban area: a study on the evolution characteristics and influencing factors of the connectivity of construction land

This study aims to understand the connectivity characteristics of construction land during the spatial evolution of historic urban areas. The complex network analysis method is employed to examine the evolution of the spatial structure of construction land in the four periods of the Changsha historic urban area. The results indicate that the spatial network morphology of construction land follows a repeated development pattern resembling a cluster–mother–child relationship. Additionally, the vulnerability in the evolution of land use spatial relationships is very low, while the overall stability of the land use network structure decreases. The spatial equilibrium of land use shows a downwards trend, the accessibility of land where existing cultural relics and historic sites are located is generally moderate to low, and some plots require improvement. In the evolution of connectivity in the construction land of historic urban areas, the main development challenges are the uneven growth caused by imbalanced land value influenced by capital and the need to balance the preservation of land use patterns with improved accessibility to cultural relics and historic sites. Therefore, it is highly important to dynamically detect and optimize the network structure of construction land to protect and develop historic urban areas.

Mixbiotic society measures: Assessment of community well-going as living system.

Social isolation and fragmentation represent global challenges, with the former stemming from a lack of interaction and the latter from exclusive mobs-both rooted in communication issues. Addressing these challenges, the philosophical realm introduces the concept of the "mixbiotic society." In this framework, individuals with diverse freedoms and values mix together in physical proximity with diverse mingling, recognizing their respective "fundamental incapacities" and uniting in solidarity. This study aims to provide novel measures to balance freedom and solidarity, specifically the intermediate between isolation and mobbing, within a mixbiotic society. To achieve this, we introduce simplified measures to evaluate dynamic communication patterns. These measures complement traditional social network analysis of static structures and conventional entropy-based assessments of dynamic patterns. Our specific hypothesis posits that the measures corresponding to four distinct phases are established by representing communication patterns as multidimensional vectors. These measures include the mean of Euclidean distance to quantify "mobism" for fragmentation, the relative distance change for "atomism" indicating isolation, and a composite measure derived from multiplying the mean and variance of cosine similarity for "mixism," reflecting the well-going state of a mixbiotic society. Additionally, nearly negligible measures correspond to "nihilism." Through the evaluation of seven real-society datasets (high school, primary school, workplace, village, conference, online community, and email), we demonstrate the utility of the "mixism" measure in assessing freedom and solidarity in society. These measures can be employed to typify communities on a radar chart and a communication trajectory graph. The superiority of the measures lies in their ability to evaluate dynamic patterns, ease of calculation, and easily interpretable meanings compared to conventional analyses. As a future development, alongside additional validation using diverse datasets, the mixbiotic society measures will be employed to analyze social issues and applied in the fields of digital democracy and platform cooperativism.

Identification and prediction of frailty among community-dwelling older Japanese adults based on Bayesian network analysis: a cross-sectional and longitudinal study

BackgroundFrailty is a multifactorial syndrome; through this study, we aimed to investigate the physiological, psychological, and social factors associated with frailty and frailty worsening in community-dwelling older adults.MethodsWe conducted a cross-sectional and longitudinal study using data from the “Community Empowerment and Well-Being and Healthy Long-term Care: Evidence from a Cohort Study (CEC),” which focuses on community dwellers aged 65 and above in Japan. The sample of the cross-sectional study was drawn from a CEC study conducted in 2014 with a total of 673 participants. After excluding those who were frail during the baseline assessment (2014) and at the 3-year follow-up (2017), the study included 373 participants. Frailty assessment was extracted from the Kihon Checklist, while social relationships were assessed using the Social Interaction Index (ISI). Variable selection was performed using Least Absolute Shrinkage and Selection Operator (LASSO) regression and their predictive abilities were tested. Factors associated with frailty status and worsening were identified through the Maximum-min Hillclimb algorithm applied to Bayesian networks (BNs).ResultsAt baseline, 14.1% (95 out of 673) participants were frail, and 24.1% (90 out of 373) participants experienced frailty worsening at the 3-years follow up. LASSO regression identified key variables for frailty. For frailty identification (cross-sectional), the LASSO model’s AUC was 0.943 (95%CI 0.913–0.974), indicating good discrimination, with Hosmer–Lemeshow (H–L) test p = 0.395. For frailty worsening (longitudinal), the LASSO model’s AUC was 0.722 (95%CI 0.656–0.788), indicating moderate discrimination, with H–L test p = 0.26. The BNs found that age, multimorbidity, function status, and social relationships were parent nodes directly related to frailty. It revealed an 85% probability of frailty in individuals aged 75 or older with physical dysfunction, polypharmacy, and low ISI scores; however, if their social relationships and polypharmacy status improve, the probability reduces to 50.0%. In the longitudinal-level frailty worsening model, a 75% probability of frailty worsening in individuals aged 75 or older with declined physical function and ISI scores was noted; however, if physical function and ISI improve, the probability decreases to 25.0%.ConclusionFrailty and its progression are prevalent among community-dwelling older adults and are influenced by various factors, including age, physical function, and social relationships. BNs facilitate the identification of interrelationships among these variables, quantify the influence of key factors. However, further research is required to validate the proposed model.

A standardized image processing and data quality platform for rodent fMRI

Functional magnetic resonance imaging in rodents holds great potential for advancing our understanding of brain networks. Unlike the human community, there remains no standardized resource in rodents for image processing, analysis and quality control, posing significant reproducibility limitations. Our software platform, Rodent Automated Bold Improvement of EPI Sequences, is a pipeline designed to address these limitations for preprocessing, quality control, and confound correction, along with best practices for reproducibility and transparency. We demonstrate the robustness of the preprocessing workflow by validating performance across multiple acquisition sites and both mouse and rat data. Building upon a thorough investigation into data quality metrics across acquisition sites, we introduce guidelines for the quality control of network analysis and offer recommendations for addressing issues. Taken together, this software platform will allow the emerging community to adopt reproducible practices and foster progress in translational neuroscience.

Integrative transcriptome analysis reveals the molecular events underlying impaired T-cell responses in EGFR-mutant lung cancer

EGFR mutations are critical oncogenic drivers in lung adenocarcinoma (LUAD). However, the mechanisms by which they impact the tumor microenvironment (TME) and tumor immunity are unclear. Furthermore, the reasons underlying the poor response of EGFR-mutant (EGFR-MU) LUADs to immunotherapy with PD-1/PD-L1 inhibitors are unknown. Utilizing single-cell RNA (sc-RNA) and bulk RNA sequencing datasets, we conducted high-dimensional weighted gene coexpression network analysis to identify key genes and immune-related pathways contributing to the immunosuppressive TME. EGFR-MU cancer cells downregulated MHC class I genes to evade CD8+ cytotoxic T cells, expressed substantial levels of MHC class II molecules, and engaged with CD4+ regulatory T cells (Tregs). EGFR-MU tumors may recruit Tregs primarily through the CCL17/CCL22/CCR4 axis, leading to a Treg-enriched TME. High levels of MHC class II-positive cancer-associated fibroblasts and tumor endothelial cells were found within EGFR-MU tumors. Owing to the absence of costimulatory factors, they may inhibit rather than activate the tumor antigen-specific CD4+ T-cell response, contributing further to immune suppression. Multiplex immunohistochemistry analyses in a LUAD cohort confirmed increased expression of MHC class II molecules in cancer cells and fibroblasts in EGFR-MU tumors. Our research elucidates the highly immunosuppressive TME in EGFR-MU LUAD and suggests potential targets for effective immunotherapy.

Unveiling the molecular dynamics of low temperature preservation in postharvest lotus seeds: a transcriptomic perspective

BackgroundPostharvest quality deterioration poses a significant challenge to the commercial value of fresh lotus seeds. Low temperature storage is widely employed as the primary method for preserving postharvest lotus seeds during storage and transportation.ResultsThis approach effectively extends the storage life of lotus seeds, resulting in distinct physiological changes compared to room temperature storage, including a notable reduction in starch, protein, H2O2, and MDA content. Here, we conducted RNA-sequencing to generate global transcriptome profiles of postharvest lotus seeds stored under room or low temperature conditions. Principal component analysis (PCA) revealed that gene expression in postharvest lotus seeds demonstrated less variability during low temperature storage in comparison to room temperature storage. A total of 14,547 differentially expressed genes (DEGs) associated with various biological processes such as starch and sucrose metabolism, energy metabolism, and plant hormone signaling response were identified. Notably, the expression levels of DEGs involved in ABA signaling were significantly suppressed in contrast to room temperature storage. Additionally, nine weighted gene co-expression network analysis (WGCNA)-based gene molecular modules were identified, providing insights into the co-expression relationship of genes during postharvest storage.ConclusionOur findings illuminate transcriptional differences in postharvest lotus seeds between room and low temperature storage, offering crucial insights into the molecular mechanisms of low temperature preservation in lotus seeds.