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Lameness adversely affects the welfare and productivity of dairy cows. This study quantifies and analyzes key gait characteristics of cows with varying locomotion scores, evaluating their effectiveness for lameness detection in computer vision systems while considering individual specificity. Six key characteristics—back arch, head bob, speed, step overlap, supporting phase, and hoof step time—were analyzed to assess their distribution across different locomotion scores. Through a comparative analysis of single-parameter and multiple-parameter classification models, we quantitatively demonstrated that models using multiple characteristics significantly outperformed single-parameter models, achieving an accuracy of 84% and a Macro-F1 score of 0.81, while better accounting for individual variability. Among the characteristics, step overlap, supporting phase, and back arch showed higher relative importance in the classifiers. Back arch was a strong indicator of severe lameness, while step overlap and supporting phase were more effective for detecting mild cases. A hierarchical classification approach further improved performance by minimizing the impact of less relevant characteristics. This study highlights the importance of integrating multiple gait and posture features for robust lameness detection, providing practical insights for automated systems.

Liver fibrosis is a manifestation of chronic liver injury. It leads to hepatic dysfunction and is a critical element in the pathogenesis of cirrhosis and hepatocellular carcinoma. The activation of hepatic stellate cells (HSC) plays a central role in liver fibrogenesis of different etiologies. To elucidate the molecular mechanism of this phenomenon, it is important to analyze the changes in gene expression that accompany the HSC activation process. In this study, we isolated quiescent and activated HSCs from control mice and mice with CCl4-induced liver fibrosis, respectively, and performed RNA sequencing to compare the differences in gene expression patterns between the two types of HSCs. We also reanalyzed public gene expression data for fibrotic liver tissues isolated from patients with HBV infection, HCV infection, and nonalcoholic fatty liver disease to investigate the gene expression changes during liver fibrosis of these three etiologies. We detected 146 upregulated and 18 downregulated genes in activated HSCs, which were implicated in liver fibrosis as well. Among the overlapping genes, seven transcription factor-encoding genes, ARID5B, GATA6, MITF, PBX1, PLAGL1, SOX4, and SOX9, were upregulated, while one, RXRA, was downregulated. These genes were suggested to play a critical role in HSC activation, and subsequently, in the promotion of liver fibrosis. We undertook the RNA sequencing of quiescent and activated HSCs and analyzed the expression profiles of genes associated with HSC activation in liver fibrotic tissues from different liver diseases, and also aimed to elucidate the changes in gene expression patterns associated with HSC activation and liver fibrosis.

Urinary incontinence (UI) might be linked to suicidal ideation, but we do not yet have all the relevant details. This study aimed to dig deeper into the connection between UI and suicidal ideation using data from the National Health and Nutrition Examination Survey (NHANES). We examined 31,891 participants aged ≥ 20 years from NHANES 2005-2018 who provided complete information. We used standardized surveys to check for UI and signs of suicidal ideation. To better understand this relationship, we used statistical tools such as multivariable logistic regression, subgroup analysis, and sensitivity analyses. Among the 31,891 participants, 28.9% reported UI and 10.7% reported suicidal ideation. Those with UI exhibited a significantly greater incidence of suicidal ideation (15.5%) than did those without UI (8.8%, P < 0.001). After adjusting for various factors, including age, sex, marital status, socioeconomic status, educational level, lifestyle factors, and chronic comorbidities, UI remained significantly associated with suicidal ideation (OR:1.54, 95% CI = 1.39-1.7, P < 0.001). Among all types of UI, MUI participants were more likely to experience suicidal ideation. Compared with no UI, higher odds of suicidal ideation suffered from MUI (OR:2.11, 95%CI:1.83-2.44, P < 0.001), SUI (OR:1.4, 95%CI:1.19-1.65, P < 0.001), UUI(OR:1.37,95%CI:1.16-1.62, P < 0.001) after full adjustment. With the exception of individuals living with a partner, the remaining subgroups exhibited a positive correlation between urinary incontinence and suicidal ideation, considering that factors such as age, sex, and prevalent comorbidities such as hypertension, depression, and diabetes did not reveal any statistically significant interactions (all P > 0.05). Sensitivity analyses, incorporating imputed missing covariates, did not substantially alter the results (OR: 1.53, 95% CI: 1.4-1.68, P < 0.001). Urinary incontinence may correlate with increased suicidal ideation risk, priority screening for suicidal ideation and timely intervention are essential for individuals with urinary incontinence, but prospective studies are needed to verify the results.

Lameness significantly compromises dairy cattle welfare and productivity. Early detection enables prompt intervention, enhancing both animal health and farm efficiency. Current computer vision approaches often rely on isolated lameness feature quantification, disregarding critical interdependencies among gait parameters. This limitation is exacerbated by the distinct kinematic patterns exhibited across lameness severity grades, ultimately reducing detection accuracy. This study presents an integrated computer vision and deep-learning framework for dairy cattle lameness detection and severity classification. The proposed system comprises (1) a Cow Lameness Feature Map (CLFM) model extracting holistic gait kinematics (hoof trajectories and dorsal contour) from walking sequences, and (2) a DenseNet-Integrated Convolutional Attention Module (DCAM) that mitigates inter-individual variability through multi-feature fusion. Experimental validation utilized 3150 annotated lameness feature maps derived from 175 Holsteins under natural walking conditions, demonstrating robust classification performance. The classification accuracy of the method for varying degrees of lameness was 92.80%, the sensitivity was 89.21%, and the specificity was 94.60%. The detection of healthy and lameness dairy cows’ accuracy was 99.05%, the sensitivity was 100%, and the specificity was 98.57%. The experimental results demonstrate the advantage of implementing lameness severity-adaptive feature weighting through hierarchical network architecture.

Pulmonary hypertension (PH) is a progressive cardiopulmonary disorder. It features elevated pulmonary arterial pressure, which leads to right ventricular failure and increased mortality. PH’s insidious nature, with no specific clinical symptoms, hinders early diagnosis. Recent investigations have implicated vascular cell senescence in the pathogenesis of PH; however, the identification of early diagnostic biomarkers and the development of senescence-targeted therapeutics remain areas of unmet need.In this study, an integrative transcriptomic analysis of multiple datasets was undertaken to delineate differentially expressed senescence-related genes (DESRGs). Feature genes were selected via the implementation of LASSO regression, random forest, and support vector machine algorithms. Subsequently, a diagnostic nomogram was constructed, predicated on six hub genes. The discriminative capacity of the nomogram was rigorously validated utilizing external datasets. Single-gene gene set enrichment analysis (GSEA) was executed to elucidate potential biological functions. The expression profiles of core genes were corroborated through single-cell RNA sequencing and qPCR in an in vitro hypoxia model of pulmonary artery smooth muscle cells. Finally, connectivity map (cMAP) analysis and molecular docking were employed to identify potential therapeutic small molecules.The analysis identified 20 DESRGs. Six feature genes (LCN2, CBS, ABCB1, NQO1, TWIST1, TLR8) were consistently selected by all three machine learning methods. The diagnostic nomogram exhibited an area under the curve (AUC) of 0.974 in the training cohort and demonstrated robust performance in independent validation cohorts. Notably, CBS, TLR8, and NQO1 were significantly downregulated in validation datasets, single-cell sequencing, and the in vitro hypoxia model. GSEA revealed significant enrichment of innate immune responses, the IL-17 pathway, and oxidative stress. cMAP analysis identified TUL-XXI039 as a potential therapeutic compound, with molecular docking studies predicting strong binding affinities (binding energies < -8.0 kcal/mol) to CBS, TLR8, and NQO1.This study introduces a novel, high-precision diagnostic model for PH based on senescence-related genes, underscoring CBS, TLR8, and NQO1 as promising biomarker candidates. TUL-XXI039 emerges as a potential multi-target therapeutic candidate for PH, thus meriting further investigation.

Cuproptosis is a novel form of cell death, correlated with the tricarboxylic acid (TCA) cycle. However, the metabolic features and the benefit of immune checkpoint inhibitor (ICI) therapy based on cuproptosis have not yet been elucidated in Hepatocellular carcinoma (HCC). First, we identified and validated three cuproptosis subtypes based on 10 cuproptosis-related genes (CRGs) in HCC patients. We explored the correlation between three cuproptosis subtypes and metabolism-related pathways. Besides, a comprehensive immune analysis of three cuproptosis subtypes was performed. Then, we calculated the cuproptosis-related gene prognostic index (CRGPI) score for predicting prognosis and validated its predictive capability by Decision curve analysis (DCA). We as well explored the benefit of ICI therapy of different CRGPI subgroups in two anti-PD1/PD-L1 therapy cohorts (IMvigor210 cohort and GSE176307). Finally, we performed the ridge regression algorithm to calculate the IC50 value for drug sensitivity and Gene set enrichment analysis (GSEA) analysis to explore the potential mechanism. We found that cluster A presented a higher expression of FDX1 and was correlated with metabolism, glycolysis, and TCA cycle pathways, compared with the other two clusters. HCC patients with high CRGPI scores had a worse OS probability, and we further found that the CRGPI-high group had high expression of PD1/PDL1, TMB, and better response (PR/CR) to immunotherapy in the IMvigor210 cohort and GSE176307. These findings highlight the importance of CRGPI serving as a potential biomarker for both prognostic and immunotherapy for HCC patients. Generally, our results provide novel insights about cuproptosis into immune therapeutic strategies.

1-Methylnaphthalene is a critical component for constructing fuel surrogates of diesel and aviation kerosene. However, the reaction pathways of 1-methylnaphthalene included in existing detailed chemical kinetic models vary from each other, leading to discrepancies in the simulation of ignition and oxidation processes. In the present study, reaction classes and pathways involved in the combustion of 1-methylnaphthalene were analyzed, and effects of rate constants of reactions related to 1-methylnaphthalene and its significant intermediates on ignition delay times and species concentration profiles were discussed, involving hydrogen abstraction and substitution reactions of 1-methylnaphthalene, oxidation, isomerization, and addition reactions of 1-naphthylmethyl, hydrogen abstraction and oxidation reactions of indene, as well as the oxidation of indenyl and naphthalene. On this basis, a new detailed chemical kinetic model for 1-methylnaphthalene was developed, which includes 1389 species and 7185 reactions. The validation of this mechanism shows that it can predict accurately the available experimental ignition delay times, species concentration profiles, and laminar flame speeds of 1-methylnaphthalene. Finally, reaction paths and sensitivity analysis of ignition delay times were performed using the proposed reaction mechanism, and the result shows that the conversion of 1-methylnaphthalene to 1-naphthaldehyde plays an important role in its ignition.

Research on the potential association between life-ever gallstones and depressive symptoms is limited. This study aims to evaluate whether the presence of gallstone disease is associated with depressive symptoms. In this cross-sectional study, we analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2017-March 2020 cycles. The presence of depressive symptoms and gallstone disease was assessed using questionnaire responses. Adjusted odds ratios (OR) were calculated using a multivariate logistic regression model, with adjustments made for age, sex, race, body mass index, history of cardiovascular disease, hypertension, arthritis, and pulmonary disease across different models. Subgroup and sensitivity analyses were conducted to ensure the stability of the results. This study included 6201 adults aged 20 years and above, with 539(8.7%) experiencing depressive symptoms. After adjusting for age, sex, race, body mass index, CVD history, hypertension, arthritis, pulmonary disease, depressive symptoms were possibly associated with life-ever gallstones (OR 1.37, 95% CI 0.91–2.08).When depressive symptoms were categorized as mild, moderate, moderately severe, and severe,life-ever gallstones was possibly associated with mild depressive symptoms (OR 1.12, 95% CI 0.81–1.56), moderate depressive symptoms (OR 1.37, 95% CI 0.89–2.12), moderately severe depressive symptoms (OR 1.93, 95% CI 0.93–3.99), and severe depressive symptoms (OR 0.67, 95% CI 0.16–2.88).As a continuous variable, life-ever gallstones was associated with the PHQ-9 score (OR 0.42, 95% CI 0.02–0.83). The results remained stable after multiple imputation for all missing data. This cross-sectional study demonstrates no significant association between life-ever gallstones and depressive symptoms in US adults.

Numerous cancer types present the aberrant TANK-binding kinase 1 (TBK1) expression, which plays an important role in driving inflammation and innate immunity. However, the prognostic role of TBK1 and its relationship with immune cell infiltration in hepatocellular carcinoma (HCC) remain unclear. The expression and prognostic value of TBK1 was analyzed by Tumor Immune Estimation Resource (TIMER), Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA), Clinical Proteomic Tumor Analysis Consortium (CPTAC) and further confirmed in the present cohort of patients with HCC. The association between TBK1 and HCC immune infiltrates, and its potential mechanism were investigated analyses of the Tumor Immune Estimation Resource, tumor-immune system interactions database (TISIDB), CIBERSORT, STRING, and Metascape. The effect of TBK1 on immune infiltrates and the therapeutic value of targeting TBK1 were further investigated in a HCC mouse model by treatment with a TBK1 antagonist. The level of TBK1 expression in HCC was higher than that measured in normal tissues, and associated with poorer overall survival (GEPIA: hazard ratio [HR]=1.80, =0.038; Kaplan-Meier plotter: HR=1.87, <0.001; CPTAC: HR=2.23, =0.007; Our cohort: HR=2.92, =0.002). In addition, high TBK1 expression was found in HCC with advanced TNM stage and identified as an independent poor prognostic factor for overall survival among patients with HCC. In terms of immune infiltration, tumor tissues from HCC patients with high TBK1 expression had a low proportion of CD8 T cells, and TBK1 expression did not show prognostic value in HCC patients with enriched CD8+ T cells. Furthermore, TBK1 expression was positively correlated with the markers of T cell exhaustion and immunosuppressive cells in the HCC microenvironment. Mechanistically, the promotion of HCC immunosuppression by TBK1 was involved in the regulation of inflammatory cytokines. experiments revealed that treatment with a TBK1 antagonist delayed HCC growth by increasing the number of tumor-infiltrating CD8+ T cells. The up-regulated expression of TBK1 may be useful in predicting poor prognosis of patients with HCC. In addition, TBK1, which promotes the HCC immunosuppressive microenvironment, may be a potential immunotherapeutic target for patients with HCC.

UFMylation, a ubiquitin-like modification, is crucial for cellular processes and is linked to human diseases, including cancer. However, its role in cancer remains unclear. Here, we report that UFL1 promotes breast tumor growth by remodeling lipid metabolism. Mechanistically, UFL1 interacts with and UFMylates AKT, enhancing its localization at the endoplasmic reticulum and phosphorylation by PDK1 and mTORC2, thereby increasing AKT-mediated lipid synthesis. Moreover, AKT phosphorylates UFL1, boosting its activity. Thus, UFL1 and AKT form a positive feedback loop, accelerating lipid synthesis and breast tumor growth. Clinically, UFL1 levels are increased in human breast tumors and are associated with poor clinical outcomes in breast cancer patients. Importantly, UFMylation inhibitors sensitize breast cancer cells to AKT inhibitors and anticancer drugs. Our findings reveal a critical role for UFMylation in lipid metabolism and identify the UFL1-AKT axis as a potential therapeutic target in breast cancer. The role of protein UFMylation in cancer remains to be understood. Here, the authors show that UFM1-specific ligase 1 and AKT positively regulate each other through UFMylation and phosphorylation, facilitating lipid synthesis and breast tumor growth.