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BACKGROUND: Increased oxidative stress (OS) activity following intracerebral hemorrhage (ICH) had significantly impacting patient prognosis. Identifying optimal genes associated with OS could enhance the understanding of OS after ICH. METHODS: We employed single-cell RNA sequencing (scRNA-seq) to investigate the heterogeneity of OS across various cellular tiers following ICH, aiming to acquire biological insights into ICH. We utilized AUCell, Ucell, singscore, ssgsea, and AddModuleScore algorithms, along with correlation analysis, to identify hub genes influencing high OS post-ICH. Furthermore, we employed four machine learning algorithms, eXtreme Gradient Boosting, Boruta, Random Forest, and Least Absolute Shrinkage and Selection Operator, to identify the optimal feature genes. To validate the accuracy of our analysis, we conducted validation in ICH animal experiments. RESULTS: After analyzing the scRNA-seq dataset using various algorithms, we found that OS activity exhibited heterogeneity across different cellular layers following ICH, with particularly heightened activity observed in monocytes. Further integration of bulk data and machine learning algorithms revealed that ANXA2 and COTL1 were closely associated with high OS after ICH. Our animal experiments demonstrated an increase in OS expression post-ICH. Additionally, the protein expression of ANXA2 and COTL1 was significantly elevated and co-localized with microglia. Pearson correlation coefficient analysis revealed a significant correlation between ANXA2 and OS, indicating strong consistency (r = 0.84, p < 0.05). Similar results were observed for COTL1 and OS (r = 0.69, p < 0.05). CONCLUSIONS: Following ICH, ANXA2 and COTL1 might penetrate the brain via monocytes, localize within microglia, and enhance OS activity. This might help us better understand OS after ICH.
Asunto(s)
Hemorragia Cerebral , Aprendizaje Automático , Estrés Oxidativo , Análisis de la Célula Individual , Hemorragia Cerebral/genética , Hemorragia Cerebral/metabolismo , Animales , Masculino , Algoritmos , Microglía/metabolismo , Humanos , Ratones , Análisis de Secuencia de ARN , Modelos Animales de Enfermedad , Monocitos/metabolismoRESUMEN
Objective Biochemical remission rates of endoscopic endonasal transsphenoidal surgery (EETS) and its associated predictive factors were evaluated in patients with somatotrophin pituitary adenomas. Methods The patients who underwent EETS in Jinling Hospital were identified between 2011 and 2020. The surgeons' experience, preoperative insulin-like growth factor 1 (IGF-1), basal growth hormone (GH) levels, nadir GH levels, and the tumor characteristics were analyzed for their relationships with endocrine outcomes. Total 98 patients were included for single factor analysis and regression analysis. They were divided into three groups according to the admission chronologic order. Results The overall remission rate of the patients was 57% (56/98) for all the patients over 10 years. In the single factor analysis, we found that the tumor size, cavernous invasion, and sellar invasion were valuable to predict the endocrine outcome after surgery. As for the suprasellar invasion, no significant difference was found between the noninvasive group and the invasive group. The preoperative IGF-1 level ( p = 0.166), basal GH level ( p = 0.001), and nadir GH level ( p = 0.004) were also different between the remission group and the nonremission group in the single factor analysis. The logistic regression analysis indicated that the preoperative nadir GH (odds ratio = 0.930, 95% confidence interval = 0.891-0.972, p = 0.001) was a significant predictor for the endocrine outcomes after surgery. Conclusion The surgeons' experience is an important factor that can affect the patients' endocrine outcomes after surgery. The macroadenomas with lateral invasion are more difficult to cure. Patients with higher preoperative nadir GH levels are less likely to achieve remission.
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Background: The global impact of the COVID-19 pandemic had significantly altered the daily routines of people worldwide. This study aimed to compare how sleeptime and depression among Chinese residents had differed between periods during and outside the epidemic. Furthermore, it delved into the interactive effect of age in this relationship. Method: Utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) study in 2015 and the recently released data from 2020, which covered the pandemic period. Depression was assessed using Center for Epidemiologic Studies Depression Scale (CESD-10), considering a score of 10 or higher as indicative of depression. Participants were categorized based on age, specifically those aged 60 years and older. multivariate logistic regression and interaction analyses were employed to assess the interplay of age, supported by subgroup and sensitivity analyses to reinforce our findings. Results: The 2020 database comprised 19,331 participants, while the 2015 database had 10,507 participants. Our findings demonstrated a significant correlation between sleeptime and depression in both unadjusted models and models adjusted for all variables in both datasets (p<0.001). Upon stratifying by age and adjusting for relevant factors, we identified an interaction effect among age, sleeptime, and depression (p=0.004 for the interaction in the 2020 database, compared to 0.004 in 2015). The restricted cubic spline analysis in both datasets showcased a nonlinear relationship between sleeptime and depression. Conclusions: During both epidemic and non-epidemic periods in China, there existed a correlation between sleep duration and depression, which interacts with age.
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Skeletal muscle aging is a key contributor to age-related frailty and sarcopenia with substantial implications for global health. Here we profiled 90,902 single cells and 92,259 single nuclei from 17 donors to map the aging process in the adult human intercostal muscle, identifying cellular changes in each muscle compartment. We found that distinct subsets of muscle stem cells exhibit decreased ribosome biogenesis genes and increased CCL2 expression, causing different aging phenotypes. Our atlas also highlights an expansion of nuclei associated with the neuromuscular junction, which may reflect re-innervation, and outlines how the loss of fast-twitch myofibers is mitigated through regeneration and upregulation of fast-type markers in slow-twitch myofibers with age. Furthermore, we document the function of aging muscle microenvironment in immune cell attraction. Overall, we present a comprehensive human skeletal muscle aging resource ( https://www.muscleageingcellatlas.org/ ) together with an in-house mouse muscle atlas to study common features of muscle aging across species.