Infants' cortisol reactivity and infant-mother cortisol synchrony in urban Chinese families: The role of maternal control strategy.

Maternal control strategy refers to a mother's practices used to impel, inhibit, guide, or shape their children's behaviors during mother-child interaction. The present study examined control strategies used by Chinese urban mothers and how they associated with infants' cortisol trajectory and infant-mother cortisol synchrony during a separation task. Participants were 115 infant-mother dyads. Maternal control strategy was assessed during mother-infant free-play when the infants were 6 months (T1) and 1 year (T2) old. Salivary cortisol samples were collected from both infants and mothers during a stress-inducing task at T2. The results indicated that mothers most frequently adopted the moderate power control strategy, at both T1 and T2. T1 maternal low control strategy significantly predicted infants' cortisol response curve, namely infants of mothers who predominantly adopted a low power control strategy had a more dynamic reactivity and recovery in their cortisol response to the separation task. Positive cortisol synchrony was observed between mothers and infants during the separation stress condition. In addition, T2 maternal high power control strategy accounted for inter-individual variations in infant-mother cortisol synchrony, such that mothers who predominantly adopted a high power control strategy exhibited a heightened level of cortisol synchrony with their infants. Our findings suggest that targeted training in maternal control strategies could help mothers calibrate their infants' adrenocortical regulation.

A Soft Inductive Bimodal Sensor for Proprioception and Tactile Sensing of Soft Machines.

The somatosensory system is crucial for living beings to survive and thrive in complex environments and to interact with their surroundings. Similarly, rapidly developed soft robots need to be aware of their own posture and detect external stimuli. Bending and force sensing are key for soft machines to achieve embodied intelligence. Here, we present a soft inductive bimodal sensor (SIBS) that uses the strain modulation of magnetic permeability and the eddy-current effect for simultaneous bidirectional bending and force sensing with only two wires. The SIBS is made of a flexible planar coil, a porous ferrite film, and a soft conductive film. By measuring the inductance at two different frequencies, the bending angle and force can be obtained and decoupled. Rigorous experiments revealed that the SIBS can achieve high resolution (0.44° bending and 1.09 mN force), rapid response, excellent repeatability, and high durability. A soft crawling robot embedded with one SIBS can sense its own shape and interact with and respond to external stimuli. Moreover, the SIBS is demonstrated as a wearable human-machine interaction to control a crawling robot via wrist bending and touching. This highlights that the SIBS can be readily implemented in diverse applications for reliable bimodal sensing.

T Cell-Derived Apoptotic Extracellular Vesicles Hydrolyze cGAMP to Alleviate Radiation Enteritis via Surface Enzyme ENPP1.

Radiation enteritis is the most common complication of pelvic radiotherapy, but there is no effective prevention or treatment drug. Apoptotic T cells and their products play an important role in regulating inflammation and maintaining physiological immune homeostasis. Here it is shown that systemically infused T cell-derived apoptotic extracellular vesicles (ApoEVs) can target mice irradiated intestines and alleviate radiation enteritis. Mechanistically, radiation elevates the synthesis of intestinal 2'3' cyclic GMP-AMP (cGAMP) and activates cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) proinflammatory pathway. After systemic infusion of ApoEVs, the ectonucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) enriches on the surface of ApoEVs hydrolyze extracellular cGAMP, resulting in inhibition of the cGAS-STING pathway activated by irradiation. Furthermore, after ApoEVs are phagocytosed by phagocytes, ENPP1 on ApoEVs hydrolyzed intracellular cGAMP, which serves as an intracellular cGAMP hydrolyzation mode, thereby alleviating radiation enteritis. The findings shed light on the intracellular and extracellular hydrolysis capacity of ApoEVs and their role in inflammation regulation.

Revealing the impact of autophagy-related genes in rheumatoid arthritis: Insights from bioinformatics.

Background: Rheumatoid arthritis is a systemic inflammatory autoimmune disease that severely impacts physical and mental health. Autophagy is a cellular process involving the degradation of cellular components in lysosomes. However, from a bioinformatics perspective, autophagy-related genes have not been comprehensively elucidated in rheumatoid arthritis. Methods: In this study, we performed differential analysis of autophagy-related genes in rheumatoid arthritis patients using the GSE93272 dataset from the Gene Expression Omnibus database. Marker genes were screened by least absolute shrinkage and selection operator. Based on marker genes, we used unsupervised cluster analysis to elaborate different autophagy clusters, and further identified modules strongly associated with rheumatoid arthritis by weighted gene co-expression network analysis. In addition, we constructed four machine learning models, random forest model, support vector machine model, generalized linear model and extreme gradient boosting based on marker genes, and based on the optimal machine learning model, a nomogram model was constructed for distinguishing between normal individuals and rheumatoid arthritis patients. Finally, five external independent rheumatoid arthritis datasets were used for the validation of our results. Results: The results showed that autophagy-related genes had significant expression differences between normal individuals and osteoarthritis patients. Through least absolute shrinkage and selection operator screening, we identified 31 marker genes and found that they exhibited significant synergistic or antagonistic effects in rheumatoid arthritis, and immune cell infiltration analysis revealed significant changes in immune cell abundance. Subsequently, we elaborated different autophagy clusters (cluster 1 and cluster 2) using unsupervised cluster analysis. Next, further by weighted gene co-expression network analysis, we identified a brown module strongly associated with rheumatoid arthritis. In addition, we constructed a nomogram model for five marker genes (CDKN2A, TP53, ATG16L2, FKBP1A, and GABARAPL1) based on a generalized linear model (area under the curve = 1.000), and the predictive efficiency and accuracy of this nomogram model were demonstrated in the calibration curves, the decision curves and the five external independent datasets were validated. Conclusion: This study identified marker autophagy-related genes in rheumatoid arthritis and analyzed their impact on the disease, providing new perspectives for understanding the role of autophagy-related genes in rheumatoid arthritis and providing new directions for its individualized treatment.

Host Volatiles Potentially Drive Two Evolutionarily Related Weevils to Select Different Grains.

The Sitophilus zeamais (maize weevil) and Sitophilus oryzae (rice weevil) are two insect pests that have caused huge economic losses to stored grains worldwide. It is urgent to develop an environmentally friendly strategy for the control of these destructive pests. Here, the olfactory-mediated selection preference of the two weevil species to three stored grains was analyzed, which should help establish a pull-push system in managing them. Bioassays showed that maize weevil adults prefer to select maize, followed by paddy and wheat, while rice weevil adults mainly migrate towards wheat. Volatile analyses revealed that 2-ethylhexanol, piperitone, and (+)-Δ-cadiene are the major components in volatiles from both maize and wheat, but the abundance of these chemicals is much lower in maize than that in wheat. The volatile limonene was only detected in paddy. Y-tube bioassays suggest that 2-ethylhexanol, piperitone, and (+)-Δ-cadiene were all attractive to both weevils, whereas limonene was attractive only to rice weevils. Overall, maize weevil appeared more sensitive to the tested volatiles based on having much lower effective concentrations of these volatiles needed to attract them. The differences in volatile profiles among the grains and the sensitivity of the two species towards these volatiles may explain the behavioral differences between maize and rice weevils in selecting host grains. The differences in sensitivity of maize and rice weevils towards host volatile components with abundance differences are likely determinants driving the two insect species to migrate towards different host grains.

Revisiting associations between behavioral inhibition/shyness and social competence in young Chinese children: Sociohistorical imprint on three samples.

While negative associations between behavioral inhibition/shyness and social competence are well established for children from Western cultures, the directions of these associations have been inconsistent for Chinese children, partly due to the ongoing social-cultural changes in China. Drawing from three samples of young Chinese children (born between 2009 and 2019), we aim at examining how inhibition/shyness predicts cooperative behaviors and prosocial behaviors throughout early childhood. In Study 1 (N = 700, children aged between 36 and 72 months), mother-reported inhibition/shyness was negatively associated with mother-reported cooperative and prosocial behaviors during the preschool years. In Study 2 (N = 251, at 6, 15, 25, and 37 months of children's ages), mother-reported inhibition/shyness in infancy was negatively associated with mother-reported cooperative behaviors but was not related to observed cooperative behaviors at the early preschool age. Infancy inhibition/shyness was negatively associated with mother-reported and observed prosocial behaviors. In Study 3 (N = 95, at 14, 25, 38, and 60 months of children's ages), the inhibition/shyness trait, assessed by both observation and maternal report, did not predict any indicators of cooperative behaviors. Early childhood inhibition/shyness, however, still predicted fewer observed and mother-reported prosocial behaviors. On balance, our research supports a negative association between early inhibition/shyness and later prosocial behaviors. The mixed findings concerning cooperative behaviors are interpreted in light of sociopolitical changes in China during the past two decades. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Apoptotic Extracellular Vesicles Induced Endothelial Cell-Mediated Autologous Stem Cell Recruitment Dominates Allogeneic Stem Cell Therapeutic Mechanism for Bone Repair.

Although stem cell therapy is proved to be a promising strategy for bone repair and regeneration, transplanted allogeneic stem cells generally suffer from unfavorable apoptosis instead of differentiation into osteocytes. How the apoptotic stem cells promote bone regeneration still needs to be uncovered. In this work, we found that apoptotic extracellular vesicles released by allogeneic stem cells are critical mediators for promoting bone regeneration. Based on the results of in vivo experiments, a mechanism of apoptotic stem cells determined autologous stem cell recruitment and enhance osteogenesis was proposed. The nanoscaled apoptotic extracellular vesicles released from transplanted stem cells were endocytosed by vascular endothelial cells and preferentially distribute at endoplasmic reticular region. The oxidized phosphatidylcholine enriched in the vesicles activated the endoplasmic reticulum stress and triggered the reflective elevation of adhesion molecules, which induced the recruitment of autologous stem cells located in the blood vessels, transported them into the defect region, and promoted osteogenesis and bone repair. These findings not only reveal the mechanism of stem cell therapy of bone defects but also provide a cue for investigation of the biological process of stem cell therapy for other diseases and develop stem cell therapeutic strategies.

Connecting the Dots: The Cerebral Lymphatic System as a Bridge Between the Central Nervous System and Peripheral System in Health and Disease.

As a recently discovered waste removal system in the brain, cerebral lymphatic system is thought to play an important role in regulating the homeostasis of the central nervous system. Currently, more and more attention is being focused on the cerebral lymphatic system. Further understanding of the structural and functional characteristics of cerebral lymphatic system is essential to better understand the pathogenesis of diseases and to explore therapeutic approaches. In this review, we summarize the structural components and functional characteristics of cerebral lymphatic system. More importantly, it is closely associated with peripheral system diseases in the gastrointestinal tract, liver, and kidney. However, there is still a gap in the study of the cerebral lymphatic system. However, we believe that it is a critical mediator of the interactions between the central nervous system and the peripheral system.

Neuroprotective Effects and Therapeutic Potential of Dichloroacetate: Targeting Metabolic Disorders in Nervous System Diseases.

Dichloroacetate (DCA) is an investigational drug used to treat lactic acidosis and malignant tumours. It works by inhibiting pyruvate dehydrogenase kinase and increasing the rate of glucose oxidation. Some studies have documented the neuroprotective benefits of DCA. By reviewing these studies, this paper shows that DCA has multiple pharmacological activities, including regulating metabolism, ameliorating oxidative stress, attenuating neuroinflammation, inhibiting apoptosis, decreasing autophagy, protecting the blood‒brain barrier, improving the function of endothelial progenitor cells, improving mitochondrial dynamics, and decreasing amyloid ß-protein. In addition, DCA inhibits the enzyme that metabolizes it, which leads to peripheral neurotoxicity due to drug accumulation that may be solved by individualized drug delivery and nanovesicle delivery. In summary, in this review, we analyse the mechanisms of neuroprotection by DCA in different diseases and discuss the causes of and solutions to its adverse effects.

Anoikis-related genes signature development for clear cell renal cell carcinoma prognosis and tumor microenvironment.

Clear cell renal cell carcinoma (ccRCC) is one of the most common primary malignancies of the urinary tract, highly heterogeneous, and increasing in incidence worldwide. Anoikis is a specific type of programmed cell death in which solid tumor cells or normal epithelial cells that do not have metastatic properties lose adhesion to the extracellular matrix or undergo inappropriate cell adhesion-induced apoptosis. Anoikis is thought to play a critical role in tumorigenesis, maintenance, and treatment, according to an increasing amount of research. However, there is still some uncertainty regarding the general impact of anoikis-related genes (ARGs) on the prognostic importance, tumor microenvironment characteristics, and treatment reaction of ccRCC patients. For this study, we used The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus datasets to access the RNA sequencing results and clinical information from ccRCC patients. 29 ARGs related to survival were found using differential analysis and univariate Cox regression analysis. The samples were then divided into two clusters that had different immune traits via unsupervised cluster analysis using 29 prognosis-associated differently expressed ARGs. Then, to build an ARGs signature, 7 genes (PLAU, EDA2R, AFP, PLG, TUBB3, APOBEC3G, and MALAT1) were found using Least Absolute Shrinkage and Selection Operator regression analysis. The new ARGs signature demonstrated outstanding prognostic capability for ccRCC patients' overall survival. In conclusion, for ccRCC patients, we created an ARGs signature that strongly connects to immunological traits and therapy response. Clinicians may find this ARGs signature helpful in developing more individualized and detailed treatment strategies for ccRCC patients.

Revealing the impact of TOX3 on osteoarthritis: insights from bioinformatics.

Osteoarthritis, a prevalent long-term condition of the joints, primarily impacts older individuals, resulting in discomfort, restrictions in mobility, and a decrease in overall well-being. Although Osteoarthritis is widely spread, there is a lack of successful interventions to stop the advancement of the condition. Numerous signaling pathways have been emphasized in recent research on Osteoarthritis, yet the diagnostic significance of numerous genes has not been investigated. To identify genes that were expressed differently in osteoarthritis, we utilized the Gene Expression Omnibus database. To identify marker genes, we built machine learning models including Least Absolute Shrinkage and Selection Operator and Random Forest. We categorized Osteoarthritis samples and performed immune cell infiltration analysis based on the expression patterns of these characteristic genes. Both the Least Absolute Shrinkage and Selection Operator and Random Forest models selected six marker genes (TOX3, ARG1, CST7, RERGL, COL11A1, NCRNA00185) out of a total of 17 differentially expressed genes. The osteoarthritis samples were categorized into two groups, namely a high expression group and a low expression group, based on the median levels of TOX3 expression. Comparative analysis of these groups identified 85 differentially expressed genes, showing notable enrichment in pathways related to lipid metabolism in the group with high expression. Analysis of immune cell infiltration revealed noticeable differences in immune profiles among the two groups. The group with high expression of TOX3 showed a notable increase in Mast cells and Type II IFN Response, whereas B cells, Cytolytic activity, Inflammation-promoting cells, NK cells, pDCs, T cell co-inhibition, Th1 cells, and Th2 cells were significantly decreased. We constructed a ceRNA network for TOX3, revealing 57 lncRNAs and 18 miRNAs involved in 57 lncRNA-miRNA interactions, and 18 miRNA-mRNA interactions with TOX3. Validation of TOX3 expression was confirmed using an external dataset (GSE29746), revealing a notable increase in Osteoarthritis samples. In conclusion, our study presents a comprehensive analysis identifying TOX3 as a potential feature gene in Osteoarthritis. The distinct immune profiles and involvement in fat metabolism pathways associated with TOX3 expression suggest its significance in Osteoarthritis pathogenesis. The study establishes a basis for comprehending the intricate correlation between characteristic genes and Osteoarthritis, as well as for the formulation of individualized therapeutic approaches.

Gut Bacteria Promote Phosphine Susceptibility of Tribolium castaneum by Aggravating Oxidative Stress and Fitness Costs.

Knowledge about resistance mechanisms can provide ideas for pesticide resistance management. Although several studies have unveiled the positive or negative impacts of gut microbes on host pesticide resistance, minimal research is available regarding the association between gut microbes and host phosphine resistance. To explore the influence of gut bacteria on host phosphine susceptibility and its molecular basis, mortality, fitness, redox responses, and immune responses of adult Tribolium castaneum were determined when it was challenged by phosphine exposure and/or gut bacteria inoculation. Five cultivable gut bacteria were excised from a population of phosphine-resistant T. castaneum. Among them, only Enterococcus sp. inoculation significantly promoted host susceptibility to phosphine, while inoculation of any other gut bacteria had no significant effect on host phosphine susceptibility. Furthermore, when T. castaneum was exposed to phosphine, Enterococcus sp. inoculation decreased the female fecundity, promoted host oxidative stress, and suppressed the expression and activity of host superoxide dismutase, catalase, and peroxidase. In the absence of phosphine, Enterococcus sp. inoculation also elicited overactive immune responses in T. castaneum, including the immune deficiency and Toll signaling pathways and the dual oxidase-reactive oxygen species system. These results indicate that Enterococcus sp. likely promotes host phosphine susceptibility by aggravating oxidative stress and fitness costs.

Physical Activity, Sedentary Behavior, and Osteoarthritis: A Two-Sample Mendelian Randomization Analysis.

Background: Sedentary behavior and physical activity are still ambiguous in their effects on osteoarthritis. We aimed to evaluate the effects of physical activity and sedentary behavior on osteoarthritis to provide a reference for the prevention of osteoarthritis. Methods: This study was conducted in Changchun, China in 2022. We used two-sample Mendelian randomization with the SNP as an instrumental variable to investigate the effect of physical activity and sedentary behavior on osteoarthritis. In addition, a two-step Mendelian randomization method was used to test whether mediating factors (BMI, smoking, Apolipoprotein B) were involved in mediating the effects of exposure factors on osteoarthritis. Results: TV watching was causally related to knee osteoarthritis and spine osteoarthritis, and they were positively correlated (knee osteoarthritis: OR=1.162,95 %CI: 1.027-1.315, P=0.017; spine osteoarthritis: OR=1.208,95 %CI: 1.033-1.413, P=0.018). BMI played a mediating role in the process of TV watching with knee osteoarthritis and spine osteoarthritis. ((The proportion of BMI mediating effect: knee osteoarthritis: 47.1% (95% CI: 36.7%~63.2%); spine osteoarthritis: 29.5% (95% CI: 19.3%~40.8%)). The proportion of Smoking mediating effect in the process of TV watching with spine osteoarthritis was 16.1% (95% CI: 3.7% ~ 31.6%). Conclusion: TV watching is a potential risk factor for osteoarthritis and plays a role through modifiable factors such as BMI and smoking, therefore, interventions on these factors have the potential to reduce the burden of osteoarthritis caused by longer TV watching times.

Deep learning-based detection and classification of lumbar disc herniation on magnetic resonance images.

Background: The severity assessment of lumbar disc herniation (LDH) on MR images is crucial for selecting suitable surgical candidates. However, the interpretation of MR images is time-consuming and requires repetitive work. This study aims to develop and evaluate a deep learning-based diagnostic model for automated LDH detection and classification on lumbar axial T2-weighted MR images. Methods: A total of 1115 patients were analyzed in this retrospective study; both a development dataset (1015 patients, 15 249 images) and an external test dataset (100 patients, 1273 images) were utilized. According to the Michigan State University (MSU) classification criterion, experts labeled all images with consensus, and the final labeled results were regarded as the reference standard. The automated diagnostic model comprised Faster R-CNN and ResNeXt101 as the detection and classification network, respectively. The deep learning-based diagnostic performance was evaluated by calculating mean intersection over union (IoU), accuracy, precision, sensitivity, specificity, F1 score, the area under the receiver operating characteristics curve (AUC), and intraclass correlation coefficient (ICC) with 95% confidence intervals (CIs). Results: High detection consistency was obtained in the internal test dataset (mean IoU = 0.82, precision = 98.4%, sensitivity = 99.4%) and external test dataset (mean IoU = 0.70, precision = 96.3%, sensitivity = 97.8%). Overall accuracy for LDH classification was 87.70% (95% CI: 86.59%-88.86%) and 74.23% (95% CI: 71.83%-76.75%) in the internal and external test datasets, respectively. For internal testing, the proposed model achieved a high agreement in classification (ICC = 0.87, 95% CI: 0.86-0.88, P < 0.001), which was higher than that of external testing (ICC = 0.79, 95% CI: 0.76-0.81, P < 0.001). The AUC for model classification was 0.965 (95% CI: 0.962-0.968) and 0.916 (95% CI: 0.908-0.925) in the internal and external test datasets, respectively. Conclusions: The automated diagnostic model achieved high performance in detecting and classifying LDH and exhibited considerable consistency with experts' classification.

Identifying Crucial Biomarkers in Osteoporosis and Ulcerative Colitis Through Bioinformatics Analysis of Co-expressed Genes.

Osteoporosis (OP) and ulcerative colitis (UC), prevalent immune diseases, exert a substantial socioeconomic impact globally. This study identifies biomarkers for these diseases, paving the way for in-depth research. Initially, the Gene Expression Omnibus (GEO) database was employed to analyze datasets GSE35958 and GSE87466. This analysis aimed to pinpoint co-expression differential genes (DEGs) between OP and UC. Subsequently, the Metascape database facilitated the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of these DEGs' co-expression. For network construction and visualization, the STRING11.5 database along with Cytoscape 3.7.2 (Cytoscape Team, USA) were utilized to create a protein-protein interaction (PPI) network. Moreover, Cytoscape's cytoHubba plugin was instrumental in identifying the central genes, known as hub genes. In the datasets GSE35958 and GSE87466, 156 co-expressed DEGs were discovered. The PPI network, constructed using STRING11.5 and Cytoscape 3.7.2, comprises 96 nodes and 222 connections. Notably, seven hub genes were identified, namely COL6A1, COL6A2, BGN, NID1, PLAU, TGFB1, and PLAUR. These DEGs were predominantly enriched in pathways such as extracellular matrix organization and collagen-containing extracellular matrix, as per GO analysis. For diagnostic model construction and hub gene validation, datasets GSE56815 and GSE107499 from the GEO database were employed. The top five hub genes were validated. In conclusion, the hub genes identified in this study played a significant role in the early diagnosis, prevention, and treatment of OP and UC. Furthermore, they provide fresh insights into the underlying mechanisms of these diseases' development and progression.

Molecular mechanism of Enterococcus faecalis-induced phosphine sensitivity in Tribolium castaneum (Coleoptera: Tenebrionidae).

Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae) has developed extensive resistance to the fumigant phosphine. Knowledge of the resistance mechanisms offers insight into resistance management. Although several studies have highlighted the positive or negative impacts of symbiotic microbiota on host pesticide resistance, little is known about the association between gut symbionts and host phosphine resistance. To reveal the effect of the gut bacterium, Enterococcus faecalis (Andrewes & Horder) (Lactobacillales: Enterococcaceae), on host phosphine resistance and its underlying mechanism, we investigated mortality, fitness, redox responses, and immune responses of adult T. castaneum when challenged with E. faecalis inoculation and/or phosphine exposure. When T. castaneum was exposed to phosphine, E. faecalis inoculation decreased its survival and female fecundity and aggravated its oxidative stress. Furthermore, E. faecalis inoculation suppressed the expression and activity of superoxide dismutase, catalase, and peroxidase in phosphine-exposed T. castaneum. Enterococcus faecalis inoculation also triggered excessive host immune responses, including the immune deficiency signaling pathway and the dual oxidase-reactive oxygen species system. These findings suggest that E. faecalis likely modulates host phosphine resistance by interfering with the redox system. This provides information for examining the symbiotic function in the insect-microorganism relationship and new avenues for pesticide resistance management.

Effects of blood pressure and antihypertensive drugs on osteoarthritis: a mendelian randomized study.

BACKGROUND: Previous studies have suggested that antihypertensive drugs may play a role in the treatment of osteoarthritis, but these studies may be limited by confounding factors and lead to biased results. Therefore, we conducted a Mendelian randomization study to investigate the effects of blood pressure and antihypertensive drugs on osteoarthritis. METHODS: We used published large-scale genome-wide association data and applied univariate and multivariate Mendelian randomization methods. The main analysis model was inverse variance weighting, and the reliability of the results was tested using MR-Egger intercept analysis, Cochran's Q test, and leave-one-out analysis. We comprehensively evaluated the relationship between systolic blood pressure, diastolic blood pressure, 12 antihypertensive drugs, and osteoarthritis. We also conducted verification in the independent queue of UK Biobank and built a simple linear regression model to obtain an independent comparison. RESULTS: We found no evidence that systolic and diastolic blood pressure significantly affected osteoarthritis. However, among antihypertensive drugs, we observed a significant positive correlation between potassium-preserving diuretics and aldosterone antagonists and all osteoarthritis (OR: 0.560, 95% CI 0.406-0.772, P = 0.0004). Sensitivity analysis showed no horizontal pleiotropy or heterogeneity, and the leave-one-out analysis demonstrated the reliability of the results. This result was replicated with nominally statistical significance in the validation cohort and exhibited significant correlation in the linear regression analysis. CONCLUSIONS: Our study suggested that controlling the protein targets of potassium-sparing diuretics and aldosterone antagonists may have beneficial results for osteoarthritis. These findings provide valuable medication strategies for the control of hypertension in patients with osteoarthritis.

Analysis of cuproptosis-related genes in Ulcerative colitis and immunological characterization based on machine learning.

Cuproptosis is a novel form of cell death, mediated by protein lipid acylation and highly associated with mitochondrial metabolism, which is regulated in the cell. Ulcerative colitis (UC) is a chronic inflammatory bowel disease that recurs frequently, and its incidence is increasing worldwide every year. Currently, a growing number of studies have shown that cuproptosis-related genes (CRGs) play a crucial role in the development and progression of a variety of tumors. However, the regulatory role of CRGs in UC has not been fully elucidated. Firstly, we identified differentially expressed genes in UC, Likewise, CRGs expression profiles and immunological profiles were evaluated. Using 75 UC samples, we typed UC based on the expression profiles of CRGs, followed by correlative immune cell infiltration analysis. Using the weighted gene co-expression network analysis (WGCNA) methodology, the cluster's differentially expressed genes (DEGs) were produced. Then, the performances of extreme gradient boosting models (XGB), support vector machine models (SVM), random forest models (RF), and generalized linear models (GLM) were constructed and predicted. Finally, the effectiveness of the best machine learning model was evaluated using five external datasets, receiver operating characteristic curve (ROC), the area under the curve of ROC (AUC), a calibration curve, a nomogram, and a decision curve analysis (DCA). A total of 13 CRGs were identified as significantly different in UC and control samples. Two subtypes were identified in UC based on CRGs expression profiles. Immune cell infiltration analysis of subtypes showed significant differences between immune cells of different subtypes. WGCNA results showed a total of 8 modules with significant differences between subtypes, with the turquoise module being the most specific. The machine learning results showed satisfactory performance of the XGB model (AUC = 0.981). Finally, the construction of the final 5-gene-based XGB model, validated by the calibration curve, nomogram, decision curve analysis, and five external datasets (GSE11223: AUC = 0.987; GSE38713: AUC = 0.815; GSE53306: AUC = 0.946; GSE94648: AUC = 0.809; GSE87466: AUC = 0.981), also proved to predict subtypes of UC with accuracy. Our research presents a trustworthy model that can predict the likelihood of developing UC and methodically outlines the complex relationship between CRGs and UC.

Colonization Resistance of Symbionts in Their Insect Hosts.

The symbiotic microbiome is critical in promoting insect resistance against colonization by exogenous microorganisms. The mechanisms by which symbionts contribute to the host's immune capacity is referred to as colonization resistance. Symbionts can protect insects from exogenous pathogens through a variety of mechanisms, including upregulating the expression of host immune-related genes, producing antimicrobial substances, and competitively excluding pathogens. Concordantly, insects have evolved fine-tuned regulatory mechanisms to avoid overactive immune responses against symbionts or specialized cells to harbor symbionts. Alternatively, some symbionts have evolved special adaptations, such as the formation of biofilms to increase their tolerance to host immune responses. Here, we provide a review of the mechanisms about colonization resistance of symbionts in their insect hosts. Adaptations of symbionts and their insect hosts that may maintain such symbiotic relationships, and the significance of such relationships in the coevolution of symbiotic systems are also discussed to provide insights into the in-depth study of the contribution of symbionts to host physiology and behavior.