Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

Objective To explore the time-varying characteristics and correlation degree of autonomous rehabili-tation behavior and related symptoms of middle-aged stroke patients,and to provide a basis for clinical transitional nursing and precise rehabilitation.Methods Ecological momentary assessment was used to select 57 middle-aged stroke patients who underwent rehabilitation treatment in the Rehabilitation Medicine Department of a tertiary com-prehensive hospital in Wuhan from March 15 to August 30,2024,using convenience sampling method.Their au-tonomous rehabilitation behavior and related symptoms(fatigue,pain,emotion,sensation)were continuously monitored for 2 weeks.A hierarchical linear model was used to analyze the correlation between behavior and symptoms.Results The autonomous rehabilitation behavior of middle-aged stroke patients showed a fluctuating increasing trend,and the symptom score showed a slow decreasing trend.The hierarchical linear model showed that compared with female patients,male patients have longer duration of autonomous rehabilitation behavior(P＜0.05).The number and duration of autonomous rehabilitation behaviors in patients without fatigue were higher(P＜0.05).The number of autonomous rehabilitation behaviors in patients without pain was higher than that in patients with pain(P＜0.05).The number of autonomous rehabilitation behavior items among patients who perceived more pleasure in rehabilitation was higher than that among patients with greater difficulty in rehabilitation challenges(P＜0.05).Patients with high rehabilitation confidence have higher numbers and duration of autonomous rehabilitation behaviors compared to pa-tients with low rehabilitation confidence(P＜0.05).Conclusion There are significant individual differences and dy-namic changes in the autonomous rehabilitation behavior and related symptoms of middle-aged stroke patients.Nurs-ing staff should accurately implement personalized rehabilitation services during the transition period,enhance pa-tients'autonomy and self-management ability in home-based rehabilitation,in order to improve the overall rehabilita-tion effect.

Objective:To predict mechanical complications (MC) following spinal deformity surgery for adult spine deformity (ASD) using machine learning models, identify key risk factors, and develop a visualizable tool for individualized risk assessment.Methods:Clinical and radiological data from 525 patients with ASD who underwent surgery in our hospital between January 2017 and December 2021 were collected. Patients were randomly assigned to a training set (70%) and a test set (30%) for model development. The cohort included 88 males and 437 females, with a mean age of 42.2±18.1 years. Variables included demographic data, comorbidities, local and systemic radiological parameters, paraspinal muscle fat infiltration (FI), and vertebral bone quality (VBQ) scores. Multiple machine learning algorithms: Random Forest (RF), Gaussian Naive Bayes (GNB), Light GBM, Support Vector Machine (SVM), XGBoost (XGB), and Logistic Regression (LR) were trained and evaluated. Model performance was compared using the receiver operating characteristic curve (ROC) and precision-recall curve (PRC). SHAP (Shapley Additive Explanations) was used to rank risk factors, while LIME (Local Interpretable Model-Agnostic Explanations) was applied to visualize MC risk in individual cases.Results:Of the 525 patients, 135 (25.7%) developed postoperative MC. Among these, 80 (59.3%) experienced proximal junction kyphosis or failure (PJK/PJF), 7 (5.2%) had distal junction kyphosis or failure (DJK/DJF), 28 (20.7%) sustained rod fractures, and 29 (21.5%) showed significant loss of correction. In the validation cohort, the RF model achieved the highest area under the curve (AUC=0.80), followed by GNB (0.77), XGB (0.76), LR (0.74), LightGBM (0.73), and SVM (0.66). The RF model also demonstrated the best PRC value (0.58), highest sensitivity (0.65), and lowest Brier score (0.20). GNB, Light GBM, and LR models achieved the highest accuracy (0.78 each), while LightGBM exhibited the highest specificity (0.93). SHAP analysis identified higher preoperative VBQ scores, larger T 1 pelvic angle (TPA), and higher paraspinal muscle FI as the main risk factors for MC. Based on the RF model, a LIME-based tool was successfully constructed for individualized MC risk estimation. Conclusion:The RF model demonstrated the best overall predictive performance for MC. A machine learning-based prediction model has the potential to provide valuable guidance for surgical decision-making in ASD patients.

Objective:To develop and validate clinical predictive models for identifying poor short-term response to recombinant human growth hormone(rhGH) treatment in children with short stature.Methods:A retrospective analysis was conducted on 118 children diagnosed with growth hormone deficiency or idiopathic short stature who were treated at the First Affiliated Hospital of Zhengzhou University and two other hospitals between January 1, 2020, and January 1, 2024. A poor response to rhGH was defined as a height increase of less than 0.2 standard deviation score(SDS) after 6 months of rhGH treatment. LASSO regression was used to identify predictive variables from baseline and follow-up data. Two logistic regression models were conducted: Model A(incorporating baseline variables only) and model B(incorporating both baseline and follow-up variables), and nomograms were created for visualization. External data and internal resampling were used for dual validation of the models, and their performance was compared.Results:A total of 118 children with short stature were included. Six baseline predictive variables(diagnosis, initial height SDS, bone age, bone age-chronological age difference, rhGH dose, and gender) and one follow-up variable(height SDS after 3 months of rhGH treatment) were identified. Area under the curve values for Model A and Model B were 0.753(95% CI 0.696-0.811) and 0.930(95% CI 0.891-0.975), respectively. Calibration curves, decision curve analysis, and other evaluation metrics demonstrated good discrimination and clinical utility for both models. Model B, incorporating the 3-month follow-up variable, showed superior predictive performance compared to Model A. Conclusions:The clinical prediction models developed in this study(Model A and Model B) are practical and reliable tools for quantitatively, conveniently, and intuitively identifying children with short stature at risk of poor response to rhGH treatment.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

This study investigated the effects and underlying mechanisms of vanillic acid(VA) against cardiac fibrosis(CF) induced by isoproterenol(ISO) in mice. Male C57BL/6J mice were randomly divided into control group, VA group(100 mg·kg~(-1), ig), ISO group(10 mg·kg~(-1), sc), ISO + VA group(10 mg·kg~(-1), sc + 100 mg·kg~(-1), ig), ISO + dynamin-related protein 1(Drp1) inhibitor(Mdivi-1) group(10 mg·kg~(-1), sc + 50 mg·kg~(-1), ip), and ISO + VA + Mdivi-1 group(10 mg·kg~(-1), sc + 100 mg·kg~(-1), ig + 50 mg·kg~(-1), ip). The treatment groups received the corresponding medications once daily for 14 consecutive days. On the day after the last administration, cardiac functions were evaluated, and serum and cardiac tissue samples were collected. These samples were analyzed for serum aspartate aminotransferase(AST), lactate dehydrogenase(LDH), creatine kinase-MB(CK-MB), cardiac troponin I(cTnI), reactive oxygen species(ROS), interleukin(IL)-1β, IL-4, IL-6, IL-10, IL-18, and tumor necrosis factor-α(TNF-α) levels, as well as cardiac tissue catalase(CAT), glutathione(GSH), malondialdehyde(MDA), myeloperoxidase(MPO), superoxide dismutase(SOD), total antioxidant capacity(T-AOC) activities, and cytochrome C levels in mitochondria and cytoplasm. Hematoxylin-eosin, Masson, uranium acetate and lead citrate staining were used to observe morphological and mitochondrial ultrastructural changes in the cardiac tissues, and myocardial injury area and collagen volume fraction were calculated. Flow cytometry was applied to detect the relative content and M1/M2 polarization of cardiac macrophages. The mRNA expression levels of macrophage polarization markers [CD86, CD206, arginase 1(Arg-1), inducible nitric oxide synthase(iNOS)], CF markers [type Ⅰ collagen(Coll Ⅰ), Coll Ⅲ, α-smooth muscle actin(α-SMA)], and cytokines(IL-1β, IL-4, IL-6, IL-10, IL-18, TNF-α) in cardiac tissues were determined by quantitative real-time PCR. Western blot was used to detect the protein expression levels of Coll Ⅰ, Coll Ⅲ, α-SMA, Drp1, p-Drp1, voltage-dependent anion channel(VDAC), hexokinase 1(HK1), NOD-like receptor protein 3(NLRP3), apoptosis-associated speck-like protein(ASC), caspase-1, cleaved-caspase-1, gasdermin D(GSDMD), cleaved N-terminal gasdermin D(GSDMD-N), IL-1β, IL-18, B-cell lymphoma-2(Bcl-2), B-cell lymphoma-xl(Bcl-xl), Bcl-2-associated death promoter(Bad), Bcl-2-associated X protein(Bax), apoptotic protease activating factor-1(Apaf-1), pro-caspase-3, cleaved-caspase-3, pro-caspase-9, cleaved-caspase-9, poly(ADP-ribose) polymerase-1(PARP-1), and cleaved-PARP-1 in cardiac tissues. The results showed that VA significantly improved cardiac function in mice with CF, reduced myocardial injury area and cardiac index, and decreased serum levels of AST, CK-MB, cTnI, LDH, ROS, IL-1β, IL-6, IL-18, and TNF-α. VA also lowered MDA and MPO levels, mRNA expressions of IL-1β, IL-6, IL-18, and TNF-α, and mRNA and protein expressions of Coll Ⅰ, Coll Ⅲ, and α-SMA in cardiac tissues, and increased serum levels of IL-4 and IL-10, cardiac tissue levels of CAT, GSH, SOD, and T-AOC, and mRNA expressions of IL-4 and IL-10. Additionally, VA ameliorated cardiac pathological damage, inhibited myocardial cell apoptosis, inflammatory infiltration, and collagen fiber deposition, reduced collagen volume fraction, and alleviated mitochondrial damage. VA decreased the ratio of F4/80~+CD86~+ M1 cells and the mRNA expressions of CD86 and iNOS in cardiac tissue, and increased the ratio of F4/80~+CD206~+ M2 cells and the mRNA expressions of CD206 and Arg-1. VA also reduced protein expressions of p-Drp1, VDAC, NLRP3, ASC, caspase-1, cleaved-caspase-1, GSDMD, GSDMD-N, IL-1β, IL-18, Bad, Bax, Apaf-1, cleaved-caspase-3, cleaved-caspase-9, cleaved-PARP-1, and cytoplasmic cytochrome C, and increased the expressions of HK1, Bcl-2, Bcl-xl, pro-caspase-3, pro-caspase-9 proteins, as well as the Bcl-2/Bax and Bcl-xl/Bad ratios and mitochondrial cytochrome C content. These results indicate that VA has a significant ameliorative effect on ISO-induced CF in mice, alleviates ISO-induced oxidative damage and inflammatory response, and its mechanism may be closely related to the inhibition of Drp1/HK1/NLRP3 and mitochondrial apoptosis signaling pathways, suppression of myocardial cell inflammatory infiltration and collagen fiber deposition, reduction of collagen volume fraction and CollⅠ, Coll Ⅲ, and α-SMA expressions, thus mitigating CF.
Animals ; Isoproterenol/adverse effects* ; Male ; Mice ; Signal Transduction/drug effects* ; Vanillic Acid/administration & dosage* ; Dynamins/genetics* ; Mice, Inbred C57BL ; Fibrosis/genetics* ; Apoptosis/drug effects* ; Mitochondria/metabolism* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Myocardium/metabolism* ; Humans

This study aims to explore the specific mechanism by which puerarin inhibits ferroptosis and improves the myocardial contractile function in myocardial hypertrophy through the nuclear factor erythroid 2-related factor 2(Nrf2)/antioxidant response element(ARE)/heme oxygenase-1(HO-1) signaling pathway. The hypertrophic cardiomyocyte model was established using phenylephrine, and H9c2 cells were divided into control group, model group, puerarin group, and puerarin+ML385 group. Cell viability and surface area were detected by cell counting kit-8(CCK-8) and immunofluorescence experiments. The mitochondrial membrane potential and Ca~(2+) concentration were measured. The ferroptosis-related indicators were detected by biochemical and fluorescence staining methods. The expression of proteins related to ferroptosis and the Nrf2/ARE/HO-1 signaling pathway was detected by Western blot. A myocardial hypertrophy model was established, and 40 rats were randomly divided into sham group, model group, puerarin group, and puerarin+Nrf2 inhibitor(ML385) group, with 10 rats in each group. Echocardiogram, hemodynamic parameters, and myocardial hypertrophy parameters were measured. Histopathological changes of myocardial tissues were observed by hematoxylin and eosin(HE) staining and Masson staining. Biochemical methods, enzyme-linked immunosorbent assay(ELISA), and fluorescence staining were used to detect inflammatory factors and ferroptosis-related indicators. Immunohistochemistry was used to detect the expression of proteins related to ferroptosis and the Nrf2/ARE/HO-1 signaling pathway. Cell experiments showed that puerarin intervention significantly enhanced the viability of hypertrophic cardiomyocytes, reduced their surface area, and restored mitochondrial membrane potential and Ca~(2+) homeostasis. Mechanism studies revealed that puerarin promoted Nrf2 nuclear translocation, upregulated the expression of HO-1, solute carrier family 7 member 11(SLC7A11), and glutathione peroxidase 4(GPX4), and decreased malondialdehyde(MDA), reactive oxygen species(ROS), and iron levels. These protective effects were reversed by ML385. In animal experiments, puerarin improved cardiac function in rats with myocardial hypertrophy, alleviated myocardial hypertrophy and fibrosis, inhibited inflammatory responses and ferroptosis, and promoted nuclear Nrf2 translocation and HO-1 expression. However, combined intervention with ML385 led to deterioration of hemodynamics and a rebound in ferroptosis marker levels. In conclusion, puerarin may inhibit cardiomyocyte ferroptosis through the Nrf2/ARE/HO-1 signaling pathway, thereby improving myocardial contractile function in myocardial hypertrophy.
Animals ; NF-E2-Related Factor 2/genetics* ; Rats ; Ferroptosis/drug effects* ; Signal Transduction/drug effects* ; Isoflavones/pharmacology* ; Male ; Rats, Sprague-Dawley ; Cardiomegaly/genetics* ; Myocytes, Cardiac/metabolism* ; Antioxidant Response Elements/drug effects* ; Myocardial Contraction/drug effects* ; Heme Oxygenase-1/genetics* ; Cell Line

BACKGROUND: Chronic kidney disease (CKD) poses a major global health challenge, often foreshadowing poor patient outcomes. The C-reactive protein to albumin ratio (CAR) serves as a pivotal biomarker, demonstrating a strong correlation with adverse outcomes in cardiovascular disease (CVD). This study sought to examine the correlation between CAR and the risk of all-cause and cardiovascular mortality in patients with CKD stages 3-5. METHODS: This study utilized data of CKD patients from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2010, with follow-up to December 31, 2019. The optimal CAR cutoff value was identified utilizing the method of maximally selected rank statistics. Multivariable Cox proportional hazards regression model, restricted cubic splines (RCS) model, and subgroup analysis were employed to assess the association between CAR and mortality among CKD patients. RESULTS: During a median (with interquartile range) follow-up period of 115 (112,117) months among 2,841 CKD individuals, 1,893 deaths were observed, including 692 deaths due to CVD events. Based on the RCS analysis, a non-linear correlation was observed between CAR and mortality. Using 0.3 as the optimal CAR cutoff value, the cohort was divided into high and low groups. In the fully adjusted model, CKD patients with high CAR values exhibited an elevated risk of all-cause mortality (hazard ratio [HR] 1.53, 95% confidence interval [CI] 1.28-1.83, P < 0.001) and cardiovascular mortality (HR 1.48, 95% CI 1.08-2.02, P = 0.014). Compared to the population aged >65 years (HR 1.32, 95% CI 0.99-1.76, P = 0.064), the risk of cardiovascular mortality was significantly higher in those aged ≤65 years (HR 2.19, 95% CI 1.18-4.09, P = 0.014) with elevated CAR levels. CONCLUSIONS A notable correlation exists between the elevation of CAR and increased all-cause and cardiovascular mortality, suggesting its potential as an independent indicator for evaluating the prognosis of patients with CKD stages 3-5.
Humans ; Renal Insufficiency, Chronic/epidemiology* ; Cardiovascular Diseases/blood* ; Male ; Female ; Middle Aged ; C-Reactive Protein/metabolism* ; Aged ; Biomarkers/blood* ; Nutrition Surveys ; Adult ; United States/epidemiology* ; Serum Albumin/analysis*

Objective To evaluate the changes of perivascular space(PVS)in patients with subacute ischemic stroke(IS),as well as the relationship between PVS and cognitive dysfunction in IS patients,and to analyze the relationship between PVS indicators and cognitive function in subacute IS patients of different ages.Methods A total of 44 healthy controls(HC)and 39 patients with subacute IS were prospectively included.Automated quantitative analysis of MRI data was conducted to determine pPVS in the white matter and subcortical regions.Differences in pPVS between patients with subacute IS and HC were compared.Correlations between age,pPVS,and cognitive dysfunction were analyzed and modeled.Results Compared with the HC,the white matter pPVS in patients with subacute IS was significantly reduced(t=-2.21,P=0.031).In patients with subacute IS,the white matter pPVS showed a significant positive correlation with lesion volume(r=0.42,P=0.030)and mini-mental state examination(MMSE)scores(r=0.44,P=0.018).Both white matter pPVS(r=-0.42,P=0.010)and MMSE scores(r=-3.82,P=0.000 7)were negatively correlated with age.When age was over 61.35 years,there was a positive correlation between the white matter pPVS and MMSE scores.Conclusion PVS are closely related to cognitive impairment in patients with subacute IS.Age is a significant modulating factor in the relationship between PVS and cognitive dysfunction.Early monitoring of PVS and targeting it for intervention may positively impact the improvement of cognitive dysfunction following IS.

Extensive epigenetic reprogramming involves in memory CD8+ T-cell differentiation. The elaborate epigenetic rewiring underlying the heterogeneous functional states of CD8+ T cells remains hidden. Here, we profile single-cell chromatin accessibility and map enhancer-promoter interactomes to characterize the differentiation trajectory of memory CD8+ T cells. We reveal that under distinct epigenetic regulations, the early activated CD8+ T cells divergently originated for short-lived effector and memory precursor effector cells. We also uncover a defined epigenetic rewiring leading to the conversion from effector memory to central memory cells during memory formation. Additionally, we illustrate chromatin regulatory mechanisms underlying long-lasting versus transient transcription regulation during memory differentiation. Finally, we confirm the essential roles of Sox4 and Nrf2 in developing memory precursor effector and effector memory cells, respectively, and validate cell state-specific enhancers in regulating Il7r using CRISPR-Cas9. Our data pave the way for understanding the mechanism underlying epigenetic memory formation in CD8+ T-cell differentiation.
CD8-Positive T-Lymphocytes/metabolism* ; Cell Differentiation ; Chromatin/immunology* ; Animals ; Mice ; Immunologic Memory ; Epigenesis, Genetic ; SOXC Transcription Factors/immunology* ; NF-E2-Related Factor 2/immunology* ; Mice, Inbred C57BL ; Gene Regulatory Networks ; Enhancer Elements, Genetic