Association between atherogenic index of plasma and depressive symptoms in US adults: Results from the National Health and Nutrition Examination Survey 2005 to 2018.

OBJECTIVE: This study, utilizing data from the U.S. National Health and Nutrition Examination Survey (NHANES) between 2005 and 2018, investigates the association between the atherogenic index of plasma (AIP), a lipid biomarker, and symptoms of depression in American adults. METHODS: In this cross-sectional study of 12,534 adults aged 20 years and older, depressive symptoms were measured utilizing the Patient Health Questionnaire-9 (PHQ-9) scale. Weighted logistic regression models were employed to scrutinize the independent relationship between AIP levels and the likelihood of developing such symptoms. Moreover, a series of subgroup analyses were conducted to delve deeper into these relationships. RESULTS: Following adjustment for confounders, logistic regression by grouping AIP into quartiles revealed a significant association between AIP and an augmented likelihood of self-reported depression. Participants in the fourth quartile (Q4) exhibited a higher odds ratio (OR = 1.34, 95 % CI: 1.02-1.75, p < 0.05) compared to those in the first quartile (Q1). Notably, subgroup analysis unveiled significant interactions involving the smoking and diabetes subgroups, indicating that smoking status and diabetes may modify the relationship between AIP and depression incidence. CONCLUSION: This study reveals a positive correlation between AIP and the self-reported likelihood of depression among US adults, thereby underscoring AIP's potential clinical utility as a biomarker for depressive disorders. Our findings emphasize the necessity to consider and optimize cardiovascular health factors within depression management strategies and offer fresh insights into the development of risk stratification and intervention methods for psychiatric conditions.

Mitogenomic architecture and evolution of the soil ciliates Colpoda.

Colpoda are cosmopolitan unicellular eukaryotes primarily inhabiting soil and benefiting plant growth, but they remain one of the least understood taxa in genetics and genomics within the realm of ciliated protozoa. Here, we investigate the architecture of de novo assembled mitogenomes of six Colpoda species, using long-read sequencing and involving 36 newly isolated natural strains in total. The mitogenome sizes span from 43 to 63 kbp and typically contain 28-33 protein-coding genes. They possess a linear structure with variable telomeres and central repeats, with one Colpoda elliotti strain isolated from Tibet harboring the longest telomeres among all studied ciliates. Phylogenomic analyses reveal that Colpoda species started to diverge more than 326 million years ago, eventually evolving into two distinct groups. Collinearity analyses also reveal significant genomic divergences and a lack of long collinear blocks. One of the most notable features is the exceptionally high level of gene rearrangements between mitochondrial genomes of different Colpoda species, dominated by gene loss events. Population-level mitogenomic analysis on natural strains also demonstrates high sequence divergence, regardless of geographic distance, but the gene order remains highly conserved within species, offering a new species identification criterion for Colpoda species. Furthermore, we identified underlying heteroplasmic sites in the majority of strains of three Colpoda species, albeit without a discernible recombination signal to account for this heteroplasmy. This comprehensive study systematically unveils the mitogenomic structure and evolution of these ancient and ecologically significant Colpoda ciliates, thus laying the groundwork for a deeper understanding of the evolution of unicellular eukaryotes.IMPORTANCEColpoda, one of the most widespread ciliated protozoa in soil, are poorly understood in regard to their genetics and evolution. Our research revealed extreme mitochondrial gene rearrangements dominated by gene loss events, potentially leading to the streamlining of Colpoda mitogenomes. Surprisingly, while interspecific rearrangements abound, our population-level mitogenomic study revealed a conserved gene order within species, offering a potential new identification criterion. Phylogenomic analysis traced their lineage over 326 million years, revealing two distinct groups. Substantial genomic divergence might be associated with the lack of extended collinear blocks and relaxed purifying selection. This study systematically reveals Colpoda ciliate mitogenome structures and evolution, providing insights into the survival and evolution of these vital soil microorganisms.

Expanding the therapeutic potential of Salvia miltiorrhiza: a review of its pharmacological applications in musculoskeletal diseases.

Salvia miltiorrhiz, commonly known as "Danshen" in Chinese medicine, has longstanding history of application in cardiovascular and cerebrovascular diseases. Renowned for its diverse therapeutic properties, including promoting blood circulation, removing blood stasis, calming the mind, tonifying the blood, and benefiting the "Qi", recent studies have revealed its significant positive effects on bone metabolism. This potential has garnered attention for its promising role in treating musculoskeletal disorders. Consequently, there is a high anticipation for a comprehensive review of the potential of Salvia miltiorrhiza in the treatment of various musculoskeletal diseases, effectively introducing an established traditional Chinese medicine into a burgeoning field. AIM OF THE REVIEW: Musculoskeletal diseases (MSDs) present significant challenges to healthcare systems worldwide. Previous studies have demonstrated the high efficacy and prospects of Salvia miltiorrhiza and its active ingredients for treatment of MSDs. This review aims to illuminate the newfound applications of Salvia miltiorrhiza and its active ingredients in the treatment of various MSDs, effectively bridging the gap between an established medicine and an emerging field. METHODS: In this review, previous studies related to Salvia miltiorrhiza and its active ingredients on the treatment of MSD were collected, the specific active ingredients of Salvia miltiorrhiza were summarized, the effects of Salvia miltiorrhiza and its active ingredients for the treatment of MSDs, as well as their potential molecular mechanisms were reviewed and discussed. RESULTS: Based on previous publications, Salvianolic acid A, salvianolic acid B, tanshinone IIA are the representative active ingredients of Salvia miltiorrhiza. Their application has shown significant beneficial outcomes in osteoporosis, fractures, and arthritis. Salvia miltiorrhiza and its active ingredients protect against MSDs by regulating different signaling pathways, including ROS, Wnt, MAPK, and NF-κB signaling. CONCLUSION: Salvia miltiorrhiza and its active ingredients demonstrate promising potential for bone diseases and have been explored across a wide variety of MSDs. Further exploration of Salvia miltiorrhiza's pharmacological applications in MSDs holds great promise for advancing therapeutic interventions and improving the lives of patients suffering from these diseases.

Evolutionary Genomics of Sister Species Differing in Effective Population Sizes and Recombination Rates.

Studies of closely related species with known ecological differences provide exceptional opportunities for understanding the genetic mechanisms of evolution. In this study, we compared population-genomics data between Daphnia pulex and Daphnia pulicaria, two reproductively compatible sister species experiencing ecological speciation, the first largely confined to intermittent ponds and the second to permanent lakes in the same geographic region. Daphnia pulicaria has lower genome-wide nucleotide diversity, a smaller effective population size, a higher incidence of private alleles, and a substantially more linkage disequilibrium than D. pulex. Positively selected genes in D. pulicaria are enriched in potentially aging-related categories such as cellular homeostasis, which may explain the extended life span in D. pulicaria. We also found that opsin-related genes, which may mediate photoperiodic responses, are under different selection pressures in these two species. Genes involved in mitochondrial functions, ribosomes, and responses to environmental stimuli are found to be under positive selection in both species. Additionally, we found that the two species have similar average evolutionary rates at the DNA-sequence level, although approximately 160 genes have significantly different rates in the two lineages. Our results provide insights into the physiological traits that differ within this regionally sympatric sister-species pair that occupies unique microhabitats.

A high-resolution haplotype-resolved Reference panel constructed from the China Kadoorie Biobank Study.

Precision medicine depends on high-accuracy individual-level genotype data. However, the whole-genome sequencing (WGS) is still not suitable for gigantic studies due to budget constraints. It is particularly important to construct highly accurate haplotype reference panel for genotype imputation. In this study, we used 10 000 samples with medium-depth WGS to construct a reference panel that we named the CKB reference panel. By imputing microarray datasets, it showed that the CKB panel outperformed compared panels in terms of both the number of well-imputed variants and imputation accuracy. In addition, we have completed the imputation of 100 706 microarrays with the CKB panel, and the after-imputed data is the hitherto largest whole genome data of the Chinese population. Furthermore, in the GWAS analysis of real phenotype height, the number of tested SNPs tripled and the number of significant SNPs doubled after imputation. Finally, we developed an online server for offering free genotype imputation service based on the CKB reference panel (https://db.cngb.org/imputation/). We believe that the CKB panel is of great value for imputing microarray or low-coverage genotype data of Chinese population, and potentially mixed populations. The imputation-completed 100 706 microarray data are enormous and precious resources of population genetic studies for complex traits and diseases.

Evolutionary Insights from a Large-Scale Survey of Population-Genomic Variation.

The field of genomics has ushered in new methods for studying molecular-genetic variation in natural populations. However, most population-genomic studies still rely on small sample sizes (typically, <100 individuals) from single time points, leaving considerable uncertainties with respect to the behavior of relatively young (and rare) alleles and, owing to the large sampling variance of measures of variation, to the specific gene targets of unusually strong selection. Genomic sequences of ∼1,700 haplotypes distributed over a 10-year period from a natural population of the microcrustacean Daphnia pulex reveal evolutionary-genomic features at a refined scale, including previously hidden information on the behavior of rare alleles predicted by recent theory. Background selection, resulting from the recurrent introduction of deleterious alleles, appears to strongly influence the dynamics of neutral alleles, inducing indirect negative selection on rare variants and positive selection on common variants. Temporally fluctuating selection increases the persistence of nonsynonymous alleles with intermediate frequencies, while reducing standing levels of variation at linked silent sites. Combined with the results from an equally large metapopulation survey of the study species, classes of genes that are under strong positive selection can now be confidently identified in this key model organism. Most notable among rapidly evolving Daphnia genes are those associated with ribosomes, mitochondrial functions, sensory systems, and lifespan determination.

Eurycomanone stimulates bone mineralization in zebrafish larvae and promotes osteogenic differentiation of mesenchymal stem cells by upregulating AKT/GSK-3ß/ß-catenin signaling.

Background: Eurycomanone (EN) is a diterpenoid compound isolated from the roots of Eurycoma longifolia (E. longifolia). Previous studies have confirmed that E. longifolia can enhance bone regeneration and bone strength. We previously isolated and identified ten quassinoids from E. longifolia, and the result displayed that five aqueous extracts have the effects on promotion of bone formation, among whom EN showed the strongest activity. However, the molecular mechanism of EN on bone formation was unknown, and we further investigated in this study. Methods: After the verification of purity of extracted EN, following experiments were conducted. Firstly, the pharmacologic action of EN on normal bone mineralization and the therapeutic effect of EN on Dex-induced bone loss using zebrafish larvae. The mineralization area and integral optical density (IOD) were evaluated using alizarin red staining. Then the vital signaling pathways of EN relevant to OP was identified through network pharmacology analysis. Eventually in vitro, the effect of EN on cell viability, osteogenesis activities were investigated in human bone marrow mesenchymal stem cells (hMSCs) and C3H10 cells, and the molecular mechanisms by which applying AKT inhibitor A-443654 in hMSCs. Results: In zebrafish larvae, the administration in medium of EN (0.2, 1, and 5 µM) dramatically enhanced the skull mineralization area and integral optical density (IOD), and increased mRNA expressions of osteoblast formation genes (ALP, RUNX2a, SP7, OCN). Meanwhile, exposure of EN remarkably alleviated the inhibition of bone formation induced by dexamethasone (Dex), prominently improved the mineralization, up-regulated osteoblast-specific genes and down-regulated osteoclast-related genes (CTSK, RANKL, NFATc1, TRAF6) in Dex-treated bone loss zebrafish larvae. Network pharmacology outcomes showed the MAPK and PI3K-AKT signaling pathways are closely associated with 10 hub genes (especially AKT1), and AKT/GSK-3ß/ß-catenin was selected as the candidate analysis pathway. In hMSCs and C3H10 cells, results showed that EN at appropriate concentrations of 0.008-5 µM effectively increased the cell proliferation. In addition, EN (0.04, 0.2, and 1 µM) significantly stimulated osteogenic differentiation and mineralization as well as significantly increased the protein phosphorylation of AKT and GSK-3ß, and expression of ß-catenin, evidencing by the results of ALP and ARS staining, qPCR and western blotting. Whereas opposite results were presented in hMSCs when treated with AKT inhibitor A-443654, which effectively inhibited the pro-osteogenesis effect induced by EN, suggesting EN represent powerful potential in promoting osteogenesis of hMSCs, which may be closely related to the AKT/GSK-3ß/ß-catenin signaling pathway. Conclusions: Altogether, our findings indicate that EN possesses remarkable effect on bone formation via activating AKT/GSK-3ß/ß-catenin signaling pathway in most tested concentrations. The translational potential of this article: This study demonstrates EN is a new effective monomer in promoting bone formation, which may be a promising anabolic agent for osteoporosis (OP) treatment.

Early Lactate/Albumin and Procalcitonin/Albumin Ratios as Predictors of 28-Day Mortality in ICU-Admitted Sepsis Patients: A Retrospective Cohort Study.

BACKGROUND Lactate/albumin (LA/ALB) and procalcitonin/albumin (PCT/ALB) ratios have been implicated in predicting mortality in sepsis patients. However, their prognostic value and relationship to sepsis severity require further investigation. This retrospective study aimed to assess the prognostic value of lactate/albumin (LA/ALB) and procalcitonin/albumin (PCT/ALB) ratios in septic patients admitted to the Intensive Care Unit (ICU). MATERIAL AND METHODS A total of 340 adult sepsis patients admitted to the ICU were included in the derivation cohort. LA/ALB and PCT/ALB ratios were calculated and analyzed in relation to sepsis severity and survival status. Additionally, a validation cohort of 75 sepsis patients from another medical center was selected. RESULTS In the derivation cohort, higher LA/ALB and PCT/ALB ratios and SOFA scores were significantly associated with increased mortality (P<0.001). The LA/ALB and PCT/ALB ratios positively correlated with SOFA score. Survival analysis revealed significantly higher 28-day mortality in sepsis patients with elevated PCT/ALB (≥0.256) and LA/ALB (≥0.079) ratios upon ICU admission. The constructed prediction model incorporating LA/ALB ratio, PCT/ALB ratio, and SOFA score yielded an AUC of 0.826, demonstrating good predictive ability. The associations between LA/ALB and PCT/ALB ratios and 28-day mortality in sepsis patients were validated in the validation cohort. CONCLUSIONS The LA/ALB and PCT/ALB ratios at ICU admission provide valuable prognostic information for predicting 28-day mortality in sepsis patients. Combining these ratios with SOFA score improves the assessment of prognosis in sepsis patients.

Metformin attenuates diabetes-induced osteopenia in rats is associated with down-regulation of the RAGE-JAK2-STAT1 signal axis.

Background: Osteopenia and fragile fractures are diabetes-associated complications. Many hypoglycemic drugs have effects on bone metabolism. Metformin, as is a prescribed medication for type 2 diabetes mellitus (T2DM), had been reported to have osteoprotective effects beyond its hypoglycemic effect, however the potential mechanism behind these effects remains unclear. In this study, we aimed to investigate the comprehensive effects of metformin on bone metabolism in T2DM rat model and elucidate the potential mechanism. Methods: Goto-Kakizaki spontaneous T2DM rats with significant hyperglycemia were treated with/without metformin for 20 weeks. Glucose tolerance was tested and all rats were weighed every two weeks. The osteoprotective effects of metformin in diabetic rats were determined by quantifying serum bone biomarkers, µ-CT imaging, histological staining, bone histomorphometry, and biomechanical properties analyses. Potential targets of metformin in the treatment of T2DM and osteoporosis were predicted using network pharmacology. The effects of metformin on mesenchymal stem cells (C3H10) cultured in high glucose medium were evaluated by CCK-8 assay, alkaline phosphatase (ALP) staining, qPCR and western blotting. Results: This study demonstrated that metformin significantly attenuated osteopenia, decreased serum glucose and glycated serum protein (GSP) levels, improved bone microarchitecture, and biomechanical properties in GK rats with T2DM. Metformin significantly increased biomarkers of bone formation, and significantly decreased muscle ubiquitin C (Ubc) expression. Network pharmacology analysis found that signal transducer and activator of transcription1 (STAT1) would be a potential target of metformin for regulating bone metabolism. Metformin increased C3H10 â€‹cell viability in vitro, alleviated ALP inhibition caused by hyperglycemia, increased the osteogenic gene expression of runt-related transcription factor 2 (RUNX2), collagen type I alpha 1 (Col1a1), osteocalcin (OCN), and ALP, while suppressing RAGE and STAT1 expression. Metformin also increased the protein expression of Osterix and decreased that of RAGE, p-JAK2, and p-STAT1. Conclusions: Our results demonstrate that metformin attenuated osteopenia and improved bone microarchitecture in GK rats with T2DM and significantly promoted stem cell osteogenic differentiation under high glucose condition. The effects of metformin on bone metabolism are closely associated with the suppression of RAGE-JAK2-STAT1 signaling axis. The translational potential of this article: Our research provides experiment evidence and potential mechanistic rationale for the use of metformin as an effective candidate for diabetes-induced osteopenia treatment.

The Genome-wide Signature of Short-term Temporal Selection.

Despite evolutionary biology's obsession with natural selection, few studies have evaluated multi-generational series of patterns of selection on a genome-wide scale in natural populations. Here, we report on a nine-year population-genomic survey of the microcrustacean Daphnia pulex. The genome-sequences of > 800 isolates provide insights into patterns of selection that cannot be obtained from long-term molecular-evolution studies, including the pervasiveness of near quasi-neutrality across the genome (mean net selection coefficients near zero, but with significant temporal variance about the mean, and little evidence of positive covariance of selection across time intervals), the preponderance of weak negative selection operating on minor alleles, and a genome-wide distribution of numerous small linkage islands of observable selection influencing levels of nucleotide diversity. These results suggest that fluctuating selection is a major determinant of standing levels of variation in natural populations, challenge the conventional paradigm for interpreting patterns of nucleotide diversity and divergence, and motivate the need for the development of new theoretical expressions for the interpretation of population-genomic data.

Evolutionary Insights from a Large-scale Survey of Population-genomic Variation.

Results from data on > 1000 haplotypes distributed over a nine-year period from a natural population of the microcrustacean Daphnia pulex reveal evolutionary-genomic features at a refined scale, including key population-genetic properties that are obscured in studies with smaller sample sizes. Background selection, resulting from the recurrent introduction of deleterious alleles, appears to strongly influence the dynamics of neutral alleles, inducing indirect negative selection on rare variants and positive selection on common variants. Fluctuating selection increases the persistence of nonsynonymous alleles with intermediate frequencies, while reducing standing levels of variation at linked silent sites. Combined with the results from an equally large metapopulation survey of the study species, regions of gene structure that are under strong purifying selection and classes of genes that are under strong positive selection in this key species can be confidently identified. Most notable among rapidly evolving Daphnia genes are those associated with ribosomes, mitochondrial functions, sensory systems, and lifespan determination.

Evolution of sex determination in crustaceans.

Sex determination (SD) involves mechanisms that determine whether an individual will develop into a male, female, or in rare cases, hermaphrodite. Crustaceans harbor extremely diverse SD systems, including hermaphroditism, environmental sex determination (ESD), genetic sex determination (GSD), and cytoplasmic sex determination (e.g., Wolbachia controlled SD systems). Such diversity lays the groundwork for researching the evolution of SD in crustaceans, i.e., transitions among different SD systems. However, most previous research has focused on understanding the mechanism of SD within a single lineage or species, overlooking the transition across different SD systems. To help bridge this gap, we summarize the understanding of SD in various clades of crustaceans, and discuss how different SD systems might evolve from one another. Furthermore, we review the genetic basis for transitions between different SD systems (i.e., Dmrt genes) and propose the microcrustacean Daphnia (clade Branchiopoda) as a model to study the transition from ESD to GSD.

Prognostic signature construction and immunotherapy response analysis for Uterine Corpus Endometrial Carcinoma based on cuproptosis-related lncRNAs.

BACKGROUND: As a general female malignant tumor, Uterine Corpus Endometrial Carcinoma (UCEC) has high mortality and relapses. Cuproptosis was found to play an essential role in tumor by more and more researches. However, it is still unclear of the prognostic value and function of cuproptosis related Long non-coding RNA (lncRNA) in UCEC. METHODS: Sequencing data with the corresponding clinical data and cuproptosis-related genes (CRGs) data were obtained from the Cancer Gene Atlas (TCGA) database and cuproptosis related studies. Pearson test was applied to select cuproptosis-related lncRNAs (CRLs). Prognosis associated CRLs was identified by univariate Cox analysis and the predictors were determined by least absolute shrinkage and selection operator (Lasso)-Cox and multivariate Cox analyses to construct the cuproptosis-related lncRNA prognostic signature (CRLPS). The performance of the CRLPs was evaluated by consistency index (C-index) and Kaplan-Meier analysis. A nomogram model was constructed for survival prediction and the accuracy of the model was evaluated by calibration curve. Finally, immune related analyses were applied to predict immune responses and identify drugs with potential efficacy for the overall survival (OS). RESULTS: A total of 734 CRLs were found and 29 of them were identified as prognosis related lncRNAs. 12 CRLs were finally determined to build the CRLPS which revealed good ability on prognosis predicting. Subsequently, risk score of the CRLPS and grade were assessed as independent prognosis factors for UCEC, based on which the prognostic model provided the highest prediction accuracy of 99.7%. The calibration curve suggested that the prediction results consisted well with the observation. Enrichment analysis showed the CRLPS was mainly associated with tumor development and immune response. Patients in low tumor mutation burden (TMB) group had poorer OS. Significant difference was found in tumor immune dysfunction and exclusion (TIDE) score between different risk score groups. Finally, based on the CRLPs, drug sensitivity analysis identified nine anticancer drugs with potential efficacy on prognosis. CONCLUSION: Cuproptosis-related lncRNA prognostic signature was constructed for UCEC for the first time. Its high reliability and accuracy on predicting prognosis and immunotherapy response provided new perspective to explore the tumor mechanism and improve clinical prognosis. Nine discovered sensitive drugs provided important clues for personalized treatment of UCEC.

Identification of drug targets and prognosis projection for uterine carcinosarcoma based on alternative splicing events.

BACKGROUND: Uterine carcinosarcoma (UCS) is an invasive variant of endometrial cancer. The complicated heterogeneity and low frequency of UCS suggest the relevant research is lack. There is an urgent need to further explore the pathogenic mechanism and identify new biomarkers of UCS from different angels to improve its diagnosis and prognosis. OBJECTIVE: This study is to explore the importance of alternative splicing (AS) events in UCS, construct AS-based prognosis model and excavate key splicing factors (SFs). METHOD: UCS related gene transcriptome data and AS events data were collected from The Cancer Genome Atlas (TCGA) and TCGA SpliceSeq database. The AS events related to survival were determined by Cox regression analysis, Least absolute shrinkage and selection operator (Lasso) regression analysis and optimal subset analysis. The corresponding risk score was calculated and its efficiency on prognosis was evaluated by Kaplan-Meier (K-M) survival estimate and validated by the receiver operating characteristic (ROC) curve. The prognosis model was constructed with risk score and clinic characters as independent variables to predict patients' survival. On the other hand, Kendall test was applied to inspect the correlation between the SFs and the prognosis-related AS events and a AS-SF network was constructed. Finally, the key SFs were screened through network nodes analysis and survival analysis. RESULT: Seven AS events the most related to survival were detected and the risk score was obtained. K-M survival estimate and ROC curve validation suggested the risk score was effective. Then Cox model was constructed based on the risk score and a nomogram model was obtained which provided the highest prediction accuracy of 95%. Through the AS-SF network analysis, 16 SFs were screened, among which four survival-related SFs were eventually obtained. CONCLUSION: The prognosis model could predict the survival rate of UCS patients by their clinical characters and AS-based risk score. And four newly discovered SFs could reveal the molecular mechanism of UCS and act as the potential drug targets and prognosis biomarkers.

Anticancer Benefit of Metformin in Patients With Early-Stage Pancreatic Cancer: A Retrospective Cohort Study.

Background: Epidemiologic studies have produced conflicting results on the effects of metformin on pancreatic cancer. This study aimed to observe and analyze whether metformin use is associated with better prognosis in pancreatic cancer. Materials and Methods: In this retrospective cohort study, all baseline data were retrieved from The Chinese Medicine Information Retrieval System (https://dc.wzhospital.cn/vpn/index.html) of The First Affiliated Hospital of Wenzhou Medical University. Survival data were collected by follow-up visits and medical records. Overall survival was the primary endpoint, while progression-free survival and disease-free survival were secondary endpoints. Progression or recurrence was assessed with radiologic images. Results: Seventy-six metformin users and 92 metformin nonusers diagnosed with pancreatic cancer from 2012 to 2020 in this hospital were enrolled. The adjusted hazard ratio for overall survival for metformin users was 0.50 (95% confidence interval = 0.33-0.76), where median overall survival was 16.0 months for metformin users versus 11.5 months for metformin nonusers. The protective effect was also found by analyzing progression-free survival (adjusted hazard ratio = 0.39, 95% confidence interval = 0.18-0.86) and disease-free survival (adjusted hazard ratio = 0.30, 95% confidence interval = 0.14-0.68). In the subgroup analysis, metformin use had a statistically significant association with prolongation of survival in stage I to II pancreatic cancer patients (hazard ratio = 0.47, 95% confidence interval = 0.25-0.91), but not for advanced tumor stage (hazard ratio for IV stage = 0.62, 95% confidence interval = 0.33-1.19), after adjustment for other risk factors. Conclusion: Metformin use is related to favorable survival outcomes of pancreatic cancer, especially in early tumor stage.

Phase Transition between Crystalline Variants of Ordinary Ice.

Water is one of the most abundant molecules on Earth. However, this common and "simple" material has more than 18 different phases, which poses a great challenge to theoretically study the nature of water and ice. We designed two reaction coordinates that can distinguish between water and various ice states and used them to efficiently sample all possible states of the system in all-atom molecular dynamics simulation at ambient temperature and pressure. Various structural and thermodynamics properties, including the water-ice phase diagrams, can thus be calculated. We also present a simple model that successfully explains the thermodynamic stability of different ice states. Our work provides effective methods and data for theoretical studies of different phases of water and ice.

A Naive Bayes model on lung adenocarcinoma projection based on tumor microenvironment and weighted gene co-expression network analysis.

Based on the lung adenocarcinoma (LUAD) gene expression data from the cancer genome atlas (TCGA) database, the Stromal score, Immune score and Estimate score in tumor microenvironment (TME) were computed by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm. And gene modules significantly related to the three scores were identified by weighted gene co-expression network analysis (WGCNA). Based on the correlation coefficients and P values, 899 key genes affecting tumor microenvironment were obtained by selecting the two most correlated modules. It was suggested through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis that these key genes were significantly involved in immune-related or cancer-related terms. Through univariate cox regression and elastic network analysis, genes associated with prognosis of the LUAD patients were screened out and their prognostic values were further verified by the survival analysis and the University of ALabama at Birmingham CANcer (UALCAN) database. The results indicated that eight genes were significantly related to the overall survival of LUAD. Among them, six genes were found differentially expressed between tumor and control samples. And immune infiltration analysis further verified that all the six genes were significantly related to tumor purity and immune cells. Therefore, these genes were used eventually for constructing a Naive Bayes projection model of LUAD. The model was verified by the receiver operating characteristic (ROC) curve where the area under curve (AUC) reached 92.03%, which suggested that the model could discriminate the tumor samples from the normal accurately. Our study provided an effective model for LUAD projection which improved the clinical diagnosis and cure of LUAD. The result also confirmed that the six genes in the model construction could be the potential prognostic biomarkers of LUAD.

The Linkage-Disequilibrium and Recombinational Landscape in Daphnia pulex.

By revealing the influence of recombinational activity beyond what can be achieved with controlled crosses, measures of linkage disequilibrium (LD) in natural populations provide a powerful means of defining the recombinational landscape within which genes evolve. In one of the most comprehensive studies of this sort ever performed, involving whole-genome analyses on nearly 1,000 individuals of the cyclically parthenogenetic microcrustacean Daphnia pulex, the data suggest a relatively uniform pattern of recombination across the genome. Patterns of LD are quite consistent among populations; average rates of recombination are quite similar for all chromosomes; and although some chromosomal regions have elevated recombination rates, the degree of inflation is not large, and the overall spatial pattern of recombination is close to the random expectation. Contrary to expectations for models in which crossing-over is the primary mechanism of recombination, and consistent with data for other species, the distance-dependent pattern of LD indicates excessively high levels at both short and long distances and unexpectedly low levels of decay at long distances, suggesting significant roles for factors such as nonindependent mutation, population subdivision, and recombination mechanisms unassociated with crossing over. These observations raise issues regarding the classical LD equilibrium model widely applied in population genetics to infer recombination rates across various length scales on chromosomes.

An integrated pan-cancer analysis of identifying biomarkers about the EGR family genes in human carcinomas.

BACKGROUND: The early growth response (EGR) family genes, including EGR1, EGR2, EGR3 and EGR4, play important roles in transcriptional regulation and have been reported to be involved in the process of cell growth and apoptosis in a variety of human tumors. However, there have been no systematic pan-cancer analysis about EGR family genes. OBJECTIVE: This study is to clarify the functions and roles of EGR family genes in human pan-cancer. METHOD: Based on the cancer genome atlas (TCGA) datasets, the University of California Santa Cruz (UCSC) database and several comprehensive bioinformatics methods, we evaluated the expression levels and prognostic values of EGR family genes and explored their relationships with tumor microenvironment (TME), tumor mutation burden (TMB), microsatellite instability (MSI), immune infiltration and immunohistochemistry (IHC). RESULT: It was found that the expressions of EGR1, EGR2 and EGR3 were abnormally low in 15 cancers, 11 cancers and 13 cancers, respectively, while the expression of EGR4 was abnormally high in 9 cancers and abnormally low in 5 cancers, compared with the corresponding control samples. The expressions of EGR family genes were significantly associated with prognosis, immune score, stromal score, MSI, TMB and immune infiltration for multiple cancers. Moreover, immunohistochemical results manifested that the protein expressions of EGR1 and EGR3 might cause clinical tumor progression in some cancers. CONCLUSION: These findings elucidated the important roles of the EGR family genes in tumor development and provided clues for further study of the EGR family genes as potential biomarkers in pan-cancer.

The Role of TAMs in Tumor Microenvironment and New Research Progress.

Tumor-associated macrophages (TAMs) are an important part of tumor microenvironment (TME) and play a key role in TME, participating in the process of tumor occurrence, growth, invasion, and metastasis. Among them, metastasis to tumor tissue is the key step of malignant development of tumor. In this paper, the latest progress in the role of TAMs in the formation of tumor microenvironment is summarized. It is particularly noteworthy that cell and animal experiments show that TAMs can provide a favorable microenvironment for the occurrence and development of tumors. At the same time, clinical pathological experiments show that the accumulation of TAMs in tumor is related to poor clinical efficacy. Finally, this paper discusses the feasibility of TAMs-targeted therapy as a new indirect cancer therapy. This paper provides a theoretical basis for finding a potentially effective macrophage-targeted tumor therapy.