Explore the vast range of titles available.

This study utilizes the Technology Acceptance Model (TAM) as its theoretical foundation to examine factors influencing the adoption of smart healthcare among community-dwelling older adults. Focusing on elderly residents in Shaoxing, Zhejiang Province, China, the “Smart Healthcare Usage Intention Scale” was developed based on TAM constructs and validated through reliability and validity testing. A total of 403 participants were recruited via convenience sampling between August 2024 and January 2025. Data were analyzed using descriptive statistics, t-tests, Pearson correlation analyses in SPSS 27.0, and structural equation modeling (SEM) in Amos 28.0 for path and mediation analyses. The results indicated a behavioral intention (BI) score of 10.00 ± 3.26. The model exhibited good fit (CMIN/DF = 2.713), revealing that personal tendency, social support, and perceived value had significant positive effects on both perceived usefulness (PU) and perceived ease of use (PEOU). Furthermore, PU and PEOU were found to positively influence BI, and PEOU also had a significant positive effect on PU. Mediation analysis identified six parallel and three serial mediating pathways, underscoring the essential mediating roles of PU and PEOU. These findings provide both theoretical and practical implications for promoting smart healthcare adoption in older adult populations.

Tetrastigma hemsleyanum Diels et Gilg. (T. hemsleyanum) is an economically and medicinally valuable species within the genus Tetrastigma. However, the material basis of its pharmacological action and the biomarkers associated with its anti-cancer and anti-inflammatory effects are still unclear. Additionally, the T. hemsleyanum industry cannot grow because there is a lack of a scientific, universal, and measurable quality control system. This study aimed to explore the chemical basis quality markers related to the anti-cancer and anti-inflammatory effects of T. hemsleyanum to establish an effective quality evaluation method. UPLC-Q-TOF-MSE fingerprint profiles of T. hemsleyanum from different origins were established. Pharmacodynamic studies used HepG2 and HuH-7 cells and LPS-induced RAW264.7 to evaluate the anti-tumor and anti-inflammatory effects of the active ingredients. The spectrum-effect relationships between UPLC fingerprints and anti-cancer and anti-inflammatory activities were evaluated using PCA and PLSR statistical methods. Moreover, docking analysis was performed to identify specific active biomarkers with molecular targets associated with cancer and inflammation. Chlorogenic acid, quinic acid, catechin, kaempferol 3-rutinoside, apigenin-8-C-glucoside, and linolenic acid were associated with anticancer activity, while chlorogenic acid, quercetin, quinic acid, kaempferol 3-rutinoside, rutinum, apigenin-8-C-glucoside, and linolenic acid were associated with anti-inflammatory activity. The spectrum-effect relationship of T. hemsleyanum was successfully established, and the biomarkers for anti-cancer and anti-inflammatory effects were preliminary confirmed. These findings provide a theoretical basis for the elucidation of the substance basis of T. hemsleyanum and lay the foundation for its rapid identification, quality control, industrial research, and utilization.

In the United States, the COVID-19 pandemic accelerated the adoption of telehealth in home health care (HHC), but its sustainability remains uncertain. Despite telehealth's potential benefits, including improved patient monitoring and expanded access, the lack of reimbursement and regulatory constraints may limit widespread adoption. Understanding how home health agencies (HHAs) perceive these challenges is critical for shaping future telehealth policy. To examine HHA stakeholders' perspectives on the adoption, implementation, and sustainability of telehealth in the postpandemic era, with particular attention to operational benefits, financial and regulatory barriers, and the impact of new Centers for Medicare & Medicaid Services (CMS) billing codes (G-codes) for telehealth documentation. Qualitative study using semistructured interviews conducted between February and December 2024. The study followed the Practical Implementation Sustainability Model (PRISM) framework for data collection and analysis. Participants were recruited from HHAs and home health policy organizations across the United States, representing a range of agency types and geographic regions. A purposive and snowball sampling strategy was used to recruit 14 stakeholders, including HHA leaders, HHC clinicians, and policy experts. Interviews were transcribed and analyzed thematically using both deductive codes from the PRISM framework and inductive codes to capture emergent themes. Participants described their experiences with telehealth in HHC, including its operational feasibility, clinical utility, financial impact, and response to new CMS G-codes introduced in July 2023 for telehealth documentation. Primary topics of focus included stakeholders' perceptions of telehealth's benefits, barriers, and future viability in HHC. Stakeholders identified 4 key themes: (1) telehealth offers operational efficiencies (eg, increased patient touchpoints and workforce support) and clinical benefits (eg, improved patient monitoring and potential reduction in rehospitalizations); (2) the lack of CMS reimbursement makes telehealth adoption financially unsustainable for many HHAs; (3) specific HHAs, particularly those integrated with health systems or serving high-risk patient populations, may derive sufficient benefits to continue telehealth use despite financial constraints; and (4) current regulatory policies, including new CMS G-codes, increase administrative burden without providing financial incentives and discouraging telehealth adoption. While stakeholders recognize the benefits of telehealth in HHC, financial and regulatory challenges pose substantial barriers to its sustainability. Policymakers must weigh the advantages of telehealth reimbursement and regulatory support against concerns about wasteful care.

Background There is currently a lack of functional assessment tools based on the International Classification of Functioning, Disability, and Health (ICF) theoretical framework that are specific for older adults. Objective The aim of the present study was to develop Chinese assessment standards of the ICF Geriatric Core Set for functional evaluation of older adults. Methods A two-stage study process was conducted to develop the assessment standards of the ICF Geriatric Core Set: establishment of candidate assessment standards, and a modified Delphi consensus process including a pilot survey and two-round formal expert survey. Thirty participants in the field of ICF and geriatric rehabilitation were recruited. The suitability of the assessment standards in the questionnaires was rated using a Likert 5-level scoring method. The arithmetic mean, the full mark ratio and the coefficient of variation (CV) were used as screening indicators for the assessment standards, and modification was made for several standards, in line with the Delphi results and the expert panel discussion. Results Thirty-three candidate assessment standards belonging to 17 categories were generated. A total of 26 and 24 experts in the field of ICF and geriatric rehabilitation participated in the two-round survey, respectively. Five standards belonging to four categories entered into the second-round survey directly, five standards belonged to five categories entered with minor modification, and nine standards belonging to seven categories were redesigned based on the literature and discussion of the expert panel. In the second-round survey,15 assessment standards belonging to 15 categories met the screening requirements and four assessment standards belonged to the two remaining categories that needed a criterion and which the expert panel discussed for the final decision. Conclusions Using the modified Delphi method, the assessment standards of the ICF Geriatric Core Set have been developed.Future work should focus on the reliability and validity of the the assessment standards and their application to the health management of older adults.

Background The present research aims to investigate the clinical diagnostic value of LncRNA HOXA distal transcript antisense RNA (HOTTIP) in acute respiratory distress syndrome (ARDS) of sepsis and its predictive significance for mortality. Methods One hundred eighteenth patients with sepsis and 96 healthy individuals were enrolled. RT-qPCR to examine HOTTIP levels. The incidence of ARDS and death was recorded. The diagnostic significance of HOTTIP in sepsis ARDS was examined using ROC and logistic regression analysis. The correlation between HOTTIP and disease severity was evaluated using Pearson’s coefficients. Kaplan-Meier analysis and COX regression were employed to examine the predictive significance of mortality. Validation of HOTTIP target miRNA by dual-luciferase assay. Results HOTTIP was persistently up-regulated in patients with ARDS sepsis than in patients without ARDS patients ( P  < 0.05). HOTTIP was a risk factor for the development of ARDS, which could be diagnosed in ARDS patients from non-ARDS patients (AUC = 0.847). Both the SOFA score ( r  = 0.6793) and the APACHE II score ( r  = 0.6384) were positively correlated with the HOTTIP levels. Furthermore, serum HOTTIP was an independent predictor of short-term mortality (HR = 4.813. 95%CI: 1.471–15.750, P  = 0.009) and noticeably predicted the occurrence of short-term death (log rank = 0.020). miR-574-5p, a target miRNA for HOTTIP, was reduced in patients with sepsis ARDS and negatively correlated with HOTTIP. Conclusions The presence of HOTTIP serves as a diagnostic biomarker for the occurrence of ARDS, exhibits correlation with disease severity, and provides predictive value of short-term mortality in sepsis patients. HOTTIP may be involved in ARDS progression by targeting miR-574-5p.

Background Dendrobium nobile and Dendrobium chrysotoxum are important species of the genus Dendrobium and have great economic and medicinal value. However, the medicinal properties of these two plants remain poorly understood. This study aimed to investigate the medical properties of D. nobile and D. chrysotoxum by conducting a comprehensive chemical profiling of the two plants. Additionally, active compounds and predictive targets for anti-hepatoma activity in D. chrysotoxum extracts were identified using Network Pharmacology. Results Chemical profiling showed that altogether 65 phytochemicals were identified from D. nobile and D. chrysotoxum , with major classes as alkaloids, terpenoids, flavonoids, bibenzyls and phenanthrenes. About 18 compounds were identified as the important differential metabolites in D. nobile and D. chrysotoxum . Furtherly, CCK-8 results showed that the extracts of stems and leaves of D. nobile and D. chrysotoxum could inhibit the growth of Huh-7 cells, and the anti-hepatoma activity of extracts were dose-dependent. Among the extracts, the extract of D. chrysotoxum showed significant anti-hepatoma activity. In order to find the potential mechanism of anti-hepatoma activity of D. chrysotoxum , five key compounds and nine key targets were obtained through constructing and analyzing the compound-target-pathway network. The five key compounds were chrysotobibenzyl, chrysotoxin, moscatilin, gigantol and chrysotoxene. Nine key targets, including GAPDH, EGFR, ESR1, HRAS, SRC, CCND1, HIF1A, ERBB2 and MTOR, could be considered as the core targets of the anti-hepatoma activity of D. chrysotoxum . Conclusions In this study, the chemical composition difference and anti-hepatoma activity of stems and leaves of D. nobile and D. chrysotoxum were compared, and the potential anti-hepatoma mechanism of D. chrysotoxum was revealed in a multi-target and multi-pathway manner.

Background: Standard single-cell RNA sequencing (scRNA-seq) analysis workflows face significant limitations, particularly the rigidity of clustering-dependent methods that can obscure subtle cellular heterogeneity and the potential loss of biologically meaningful cells during stringent quality control (QC) filtering. This study aims to develop scSelector (v1.0), an interactive software toolkit designed to empower researchers to flexibly select and analyze cell populations directly from low-dimensional embeddings, guided by their expert biological knowledge. Methods: scSelector was developed using Python, relying on core dependencies such as Scanpy (v1.9.0), Matplotlib (v3.4.0), and NumPy (v1.20.0). It integrates an intuitive lasso selection tool with backend analytical modules for differential expression and functional enrichment analysis. Furthermore, it incorporates Large Language Model (LLM) assistance via API integration (DeepSeek/Gemini) to provide automated, contextually informed cell-type and state prediction reports. Results: Validation across multiple public datasets demonstrated that scSelector effectively resolves functional heterogeneity within broader cell types, such as identifying distinct alpha-cell subpopulations with unique remodeling capabilities in pancreatic tissue. It successfully characterized rare populations, including platelets in PBMCs and extremely low-abundance endothelial cells in liver tissue (as few as 53 cells). Additionally, scSelector revealed that cells discarded by standard QC can represent biologically functional subpopulations, and it accurately dissected the states of outlier cells, such as proliferative NK cells. Conclusions: scSelector provides a flexible, researcher-centric platform that moves beyond the constraints of automated pipelines. By combining interactive selection with AI-assisted interpretation, it enhances the precision of scRNA-seq analysis and facilitates the discovery of novel cell types and complex cellular behaviors.

BackgroundExcess body mass index (BMI) plays a key role in the onset and progression of knee osteoarthritis (knee OA). However, the burden of knee OA attributable to high BMI at the global, Chinese, and regional levels have received far too little attention. The aim of this study is to provide evidence to support the design of policy by investigating long-term trends of years lived with disability (YLDs) for knee OA.MethodsTo illustrate the trends of YLDs for knee OA attributable to high BMI and the temporal trends of the YLDs rate by age, period, and cohort, Joinpoint regression software and age-period-cohort (APC) were used to analyze the YLDs data of knee OA from the Global Burden of Disease (GBD) 2019.ResultsIn China, there were 549,963.5 YLDs for knee OA attributable to high BMI in 2019, which had increased by 460.7% since 1990. From 1990 to 2019, age-standardized disability-adjusted life year rate (ASDR) of knee OA attributable to high BMI trended upwards. The average annual percent change (AAPC) of knee OA attributable to high BMI in China and globe were 3.019, 1.419%, respectively. The longitudinal age curve of the APC model showed that the YLDs rates of knee OA due to high BMI increased with age, and YLDs rates were higher among females than males. The period rate ratios (RRs) of knee OA due to high BMI increased significantly. The cohort RRs of knee OA due to high BMI increased among those born between 1900 and 1970. The net drifts of knee OA attributable to high BMI in China and globe were above 1. Compared with global condition, the net drift values of knee OA attributable to high BMI in China was higher. Compared with females, males had higher net drift value. Countries with high socio-demographic index (SDI) have a much higher burden of knee OA caused by high BMI than countries with low SDI.ConclusionIn China, high BMI is a substantial cause of knee OA, the incidence of which has been increasing since 1990. In addition, women and the elderly are more vulnerable to knee OA caused by high BMI. The Chinese government must take the long-term impact of high BMI on knee OA into account and implement effective public health policies and resort to interventions to reduce the burden as soon as possible.

There is growing evidence that autoimmune illnesses are associated with the metabolome and microbiota. Because Behçet's disease (BD) is not often diagnosed as a systemic disorder, the aim of this research was to investigate changes in gut flora and metabolites in BD patients. We used 16S rRNA gut microbiota gene sequencing and UPLC-QTOF-MS analysis to gather stool and serum samples from 12 age-matched healthy controls and 17 BD patients. The correlation between changes in gut microbiota and metabolites was then further analyzed. In contrast to healthy controls, our investigation revealed significant changes in the makeup of gut flora in BD patients. In particular, we observed that in the BD group, there was a large drop in clostridia but a noticeable rise in γ-proteobacteria and betaproteobacteria. The serum metabolomics profiles of BD patients and healthy controls may be reliably differentiated using unsupervised principal component analysis (PCA). Several metabolites, including L-phenylalaine, tricarballylic acid, beta-leucine, ketoleucine, ascorbic acid, l-glutamic acid, l-malic acid, d-glucopyranuronic acid, and methyl acetoacetate, were found to have differential expression between BD patients and healthy controls. All of these metabolites were significantly lower in the BD group. Furthermore, we discovered strong associations between the detected metabolites such as tricarballylic acid, L-malic acid, D-glucopyranuronic acid with certain microbial families, such Prevotellaceae and Alcaligenaceae. Patients with BD were found to have significant changes in the makeup of their gut flora and metabolites.

Knee osteoarthritis (KOA) is indeed a major global health issue, characterized as the most common form of osteoarthritis. It affects millions of people worldwide, leading to joint pain, stiffness, and functional limitations. As life expectancy increases and populations age, KOA's impact on quality of life and public health systems becomes more pronounced. Our objective was to evaluate pain-related behaviors, tibial cartilage pathology, and inflammatory factor expression levels in rats following different doses and administration times of monosodium iodoacetate (MIA) to explore its effects on KOA. The rats were allocated into two groups: an experimental group and a control group. In the experimental group, MIA was administered as a single intra-articular injection into the left knee joint to induce KOA. The dosage varied between 0.5 mg and 2.0 mg. Following the injection, assessments were conducted on days 3, 5, 7, 14, 21, and 28 to evaluate knee circumference, pain-related behavior, tibial cartilage pathology, and the expression levels of IL-1β and IL-10. The knee joint diameters expanded in a dose- and time-dependent manner, paralleled by corresponding reductions in MIA-induced paw withdrawal threshold (PWT) and weight-bearing distribution (WBD), both of which followed similar dose- and time-dependent patterns. Compared with controls, MIA-treated rats exhibited significantly heightened defensive behaviors (eg, paw licking, retraction), confirming successful inflammatory pain induction. Pain intensity analysis revealed lower pain scores in the 0.5 and 1.0 mg MIA groups relative to 1.5 and 2.0 mg groups across the study. Pain severity escalated sharply from day 0 to 7, stabilized until day 14, and peaked again at day 28. Histologically, the 1.5 and 2.0 mg MIA groups demonstrated early-stage KOA pathology (days 5-20), characterized by chondrocyte cloning and matrix disorganization, followed by mid-stage features (days 21-27) including localized cartilage defects, surface irregularities, hypocellularity, and vascular infiltration. By day 28, late-stage KOA hallmarks emerged, such as widespread cartilage degeneration, subchondral bone exposure, and peripheral osteophytes. These histological findings aligned with behavioral pain outcomes and ELISA results, collectively illustrating synchronized progression of inflammatory and structural pathology across all assays. The severity of pain, the extent of articular cartilage degeneration, and the level of inflammatory response following intra-articular MIA injection progressively worsened in a dose- and time-dependent fashion. In the MIA group, early-stage KOA cartilage pathology was observed between days 5 to 20 post-injection. By day 21, cartilage lesions progressed to mid-stage KOA cartilage, and by day 28, they advanced to late-stage KOA cartilage. The pain trajectory corresponded with the pathological features of MIA-induced KOA, offering valuable insights into optimal dosing and timing for targeted KOA pain management interventions.