Sedentary behavior patterns and bone health among overweight/obesity older women: a cross-sectional study.

Background: Recent studies have indicated an association between sedentary behavior (SB), particularly patterns of SB, and bone health. However, it remains uncertain how different patterns of SB in overweight/obesity older women impact their bone health. This study aimed to investigate the association between objectively measured SB patterns and bone health in Chinese community-dwelling overweight/obesity older women. Methods: Cross-sectional data were obtained from a baseline survey of Physical Activity and Health in Older Women Study. Quantitative ultrasound was used to measure speed of sound (SOS), broadband ultrasound attenuation (BUA), bone quality index (BQI) and T value to evaluate bone health. SB patterns were measured using triaxial accelerometers, including sedentary time in SB bouts of ≥ 10, 30, and 60 min, number of SB bouts ≥ 10, 30, and 60 min. Multiple linear regression was used to examine the associations of different SB patterns with bone health. Results: After adjusting for confounders, sedentary time in SB bouts ≥ 60 min, number of SB bouts ≥ 60 min were significantly associated with bone health, with a lower SOS [ß = -2.75, 95% confidence interval (CI): -4.96 to -0.53, P = 0.015], BUA (ß = -1.20, 95% CI: -2.14 to -0.26, P = 0.013), BQI (ß = -1.56, 95% CI: -2.63 to -0.49, P = 0.004), T value (ß = -0.08, 95% CI: -0.14 to -0.03, P = 0.004) per 60 min increase of sedentary time in SB bouts ≥ 60 min, and a lower SOS (ß = -3.97, 95% CI: -7.54 to -0.40, P = 0.029), BUA (ß = -1.80, 95% CI: -3.44 to -0.16, P = 0.031), BQI (ß = -2.28, 95% CI: -4.08 to -0.47, P = 0.014) and T value (ß = -0.12, 95% CI: -0.22 to -0.03, P = 0.013) per bout increase of SB bouts ≥ 60 min, respectively. Conclusion: Limiting the duration of prolonged sedentary bouts and minimizing the occurrence of number of SB bouts ≥ 60 min could be essential in bone health management, especially for those older people who are overweight/obesity.

Siglec-G Suppresses CD8+ T Cells Responses through Metabolic Rewiring and Can be Targeted to Enhance Tumor Immunotherapy.

CD8+ T cells play a critical role in cancer immune-surveillance and pathogen elimination. However, their effector function can be severely impaired by inhibitory receptors such as programmed death-1 (PD-1) and T cell immunoglobulin domain and mucin domain-3 (Tim-3). Here Siglec-G is identified as a coinhibitory receptor that limits CD8+ T cell function. Siglec-G is highly expressed on tumor-infiltrating T cells and is enriched in the exhausted T cell subset. Ablation of Siglec-G enhances the efficacy of adoptively transferred T cells and chimeric antigen receptor (CAR) T cells in suppressing solid tumors growth. Mechanistically, sialoglycan ligands, such as CD24 on tumor cells, activate the Siglec-G-SHP2 axis in CD8+ T cells, impairing metabolic reprogramming from oxidative phosphorylation to glycolysis, which dampens cytotoxic T lymphocyte (CTL) activation, expansion, and cytotoxicity. These findings discover a critical role for Siglec-G in inhibiting CD8+ T cell responses, suggesting its potential therapeutic effect in adoptive T cell therapy and tumor immunotherapy.

Establishment and validation of a ferroptosis-related prognostic signature for hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer with high heterogeneity. The prognosis of HCC is quite poor and the prognostic prediction also has challenges. Ferroptosis is recently recognized as a kind of iron-dependent cell death, which is involved in tumor progression. However, further study is needed to validate the influence of drivers of ferroptosis (DOFs) on the prognosis of HCC. Methods: The FerrDb database and the Cancer Genome Atlas (TCGA) database were applied to retrieve DOFs and information of HCC patients respectively. HCC patients were randomly divided into training and testing cohorts with a 7:3 ratio. Univariate Cox regression, LASSO and multivariate Cox regression analyses were carried out to identify the optimal prognosis model and calculate the risk score. Then, univariate and multivariate Cox regression analyses were performed to assess the independence of the signature. At last, gene functional, tumor mutation and immune-related analyses were conducted to explore the underlying mechanism. Internal and external databases were used to confirm the results. Finally, the tumor tissue and normal tissue from HCC patients were applied to validate the gene expression in the model. Results: Five genes were identified to develop as a prognostic signature in the training cohort relying on the comprehensive analysis. Univariate and multivariate Cox regression analyses confirmed that the risk score was able to be an independent factor for the prognosis of HCC patients. Low-risk patients showed better overall survival than high-risk patients. Receiver operating characteristic (ROC) curve analysis confirmed the signature's predictive capacity. Furthermore, internal and external cohorts were consistent with our results. There was a higher proportion of nTreg cell, Th1 cell, macrophage, exhausted cell and CD8+T cell in the high-risk group. The Tumor Immune Dysfunction and Exclusion (TIDE) score suggested that high-risk patients could respond better to immunotherapy. Besides, the experimental results showed that some genes were differentially expressed between tumor and normal tissues. Conclusion: In summary, the five ferroptosis gene signature showed potential in prognosis of patients with HCC and could also be regarded as a value biomarker for immunotherapy response in these patients.

Development of a metabolism-related signature for predicting prognosis, immune infiltration and immunotherapy response in breast cancer.

Breast cancer (BRCA) is the most commonly diagnosed cancer and among the top causes of cancer deaths globally. The abnormality of the metabolic process is an important characteristic that distinguishes cancer cells from normal cells. Currently, there are few metabolic molecular models to evaluate the prognosis and treatment response of BRCA patients. By analyzing RNA-seq data of BRCA samples from public databases via bioinformatic approaches, we developed a prognostic signature based on seven metabolic genes (PLA2G2D, GNPNAT1, QPRT, SHMT2, PAICS, NT5E and PLPP2). Low-risk patients showed better overall survival in all five cohorts (TCGA cohort, two external validation cohorts and two internal validation cohorts). There was a higher proportion of tumor-infiltrating CD8+ T cells, CD4+ memory resting T cells, gamma delta T cells and resting dendritic cells and a lower proportion of M0 and M2 macrophages in the low-risk group. Low-risk patients also showed higher ESTIMATE scores, higher immune function scores, higher Immunophenoscores (IPS) and checkpoint expression, lower stemness scores, lower TIDE (Tumor Immune Dysfunction and Exclusion) scores and IC50 values for several chemotherapeutic agents, suggesting that low-risk patients could respond more favorably to immunotherapy and chemotherapy. Two real-world patient cohorts receiving anti-PD-1 therapy were applied for validating the predictive results. Molecular subtypes identified based on these seven genes also showed different immune characteristics. Immunohistochemical data obtained from the human protein atlas database demonstrated the protein expression of signature genes. This research may contribute to the identification of metabolic targets for BRCA and the optimization of risk stratification and personalized treatment for BRCA patients.

Diffusion Tensor Imaging Observation of Frontal Lobe Multidirectional Transcranial Direct Current Stimulation in Stroke Patients with Memory Impairment.

Stroke is a group of diseases caused by the sudden rupture or blockage of blood vessels in the brain that prevent blood from flowing into the brain, resulting in brain tissue damage and dysfunction. Stroke has the characteristics of high morbidity, high disability, and high mortality. To investigate the effect of multidirectional transcranial direct current stimulation (tDCS) of the prefrontal lobe in stroke memory disorder. We evaluated 60 patients with poststroke memory impairment who underwent magnetic resonance diffusion tensor imaging (DTI) during their admission to our hospital between January 2018 and December 2020. The patients were divided into the prefrontal group (n = 15), dorsolateral group (n = 15), prefrontal + dorsolateral group (n = 15), and pseudostimulation group (n = 15). Assessments using the Rivermead Behavioral Memory Test (RBMT), Montreal Cognitive Assessment Scale (MoCA), Lovingston Occupational Therapy Cognitive Scale (LOTCA), and frontal lobe fractional anisotropy (FA) were performed before and after treatment. The RBMT, MoCA, and LOTCA scores in the prefrontal + dorsolateral group were significantly higher than those in the dorsolateral, prefrontal, and sham groups (all P < 0.05). The posttreatment FA value of the frontal lobe was significantly higher in the prefrontal + dorsolateral group than in the dorsolateral, prefrontal, and sham stimulation groups (all P < 0.05). The FA value of the frontal lobe was significantly lower in patients with severe memory impairment than in patients with mild-moderate memory impairment (P < 0.05). The area under the receiver operating characteristic curve was 0.801 (95% CI: 0.678-0.925, P < 0.05), and the optimal cut-off value was 0.34, with a sensitivity and specificity of 81.60% and 72.70%, respectively. Prefrontal lobe + dorsolateral tDCS is beneficial in the treatment of post-stroke memory impairment. The DTI FA value can be useful in determining the degree of memory impairment.