Angiopoietin-Related Protein 4-Transcript 3 Increases the Proliferation, Invasion, and Migration of Hepatocellular Carcinoma Cells and Inhibits Apoptosis.

To investigate the functional differences of angiopoietin-related protein 4 (ANGPTL4) transcripts in hepatocellular carcinoma (HCC) cells. By transfecting ANGPTL4-Transcript 1 and ANGPTL4-Transcript 3 overexpression vectors into HepG2 and Huh7 cell lines with ANGPTL4 knockdown, the effects of overexpression of two transcripts on cell viability, invasion, migration, and apoptosis were analyzed. The expression of two transcripts was compared in human liver cancer tissue, and their effects on tumor development were validated in vivo experiments in mice. Compared with control, the overexpression of ANGPTL4-Transcript 1 had no significant effect on viability, invasion, healing, and apoptosis of HepG2 and Huh7 cells. However, these two cell lines overexpressing ANGPTL4-Transcript 3 showed remarkably enhanced cell viability, invasive and healing ability, and decreased apoptosis ability. Furthermore, the mRNA level of ANGPTL4-Transcript 3 was significantly increased in human HCC tissues and promoted tumor growth compared with Transcript 1. Different transcripts of gene ANGPTL4 have distinct effects on HCC. The abnormally elevated Transcript 3 with the specific ability of promoting HCC proliferation, infiltration, and migration is expected to become a new biological marker and more precise intervention target for HCC.

Effect of Deletion of ANGPTL4 Gene on Viability, Migration and Invasion Ability and Apoptosis of Hepatocellular Carcinoma Cells.

BACKGROUND: Hepatocellular carcinoma (HCC) is a malignant tumor that impacts individuals worldwide and is particularly prevalent in Asia. Angiopoietin-like protein 4 (ANGPTL4) plays an important role in regulating glucose and lipid metabolism in mouse liver. We sought to explore the effects of the ANGPTL4 gene on cell viability, migration, invasive capacity, and apoptosis of HCC cells. METHODS: The expression of ANGPTL4 in HCC and paracancerous tissues was determined by immunohistochemistry and immunofluorescence assays. The ANGPTL4 knockdown cells were established by shRNA transfection. The effect of ANGPTL4 knockdown on HepG2 and Huh7 cells was determined by Cell Count Kit-8 (CCK-8), wound healing and transwell assays. Cell apoptosis was determined by flow cytometry. RESULTS: The ANGPTL4 expression was dramatically enhanced in HCC tissues than in paracancerous tissues (p < 0.001). HCC cell lines HepG2 and Huh7 with knockdown of ANGPTL4 gene showed lower cell viability, migration, and invasion ability while inducing higher apoptosis levels than the control group (p < 0.001). CONCLUSIONS: High expression of ANGPTL4 is closely related to HCC. Knockdown of ANGPTL4 significantly inhibits the proliferation of HCC cells. This study provides a rationale for the ANGPTL4 gene, a molecular marker of HCC.

Self-determined sequence exercise program for elderly with sarcopenia: A Randomized controlled trial with clinical assistance from explainable artificial intelligence.

To improve and even reverse sarcopenia in elderly people, this study developed a self-determined sequence exercise program consisting of strength training exercise, Yijinjing exercise (a traditional Chinese exercise), and hybrid strength training with Yijinjing exercise. Ninety-four community-dwelling older adults screened for sarcopenia using the Asian Working Group for Sarcopenia criteria were randomly assigned to 24 weeks of a control group (CG, n = 30), self-determined sequence exercise program group (SDSG, n = 34) or strength training group (STG, n = 30). The study examined the effects of three interventions on participantsL3 skeletal muscle fat density, L3 skeletal muscle fat area, L3 skeletal muscle density, L3 skeletal muscle area, muscle fat infiltration, relative skeletal muscle mass index, and grip strength using a repeated-measures ANOVA to evaluate the experimental data. To evaluate the real effect of this model in reversing sarcopenia after the intervention, nine classification models were trained. Significant interaction effects were observed with grip strength, RSMI, L3 SMD, and L3 SMA. At the 24th week, participants' grip strength, L3 SMFA, L3 SMA, and RSMI were improved significantly in the SDSG and STG. The SDSG achieved significantly greater RSMI and grip strength than the STG and CG after the intervention. The self-determined sequence exercise program exhibited better performance than the single type of exercise modality in reversing sarcopenia and improving older adults' skeletal muscle area. Consequently, the stacking model is feasible to make a prediction as to whether or not sarcopenia may be reversed in older adults.

Body landmarks and genetic algorithm-based approach for non-contact detection of head forward posture among Chinese adolescents: revitalizing machine learning in medicine.

Addressing the current complexities, costs, and adherence issues in the detection of forward head posture (FHP), our study conducted an exhaustive epidemiologic investigation, incorporating a comprehensive posture screening process for each participant in China. This research introduces an avant-garde, machine learning-based non-contact method for the accurate discernment of FHP. Our approach elevates detection accuracy by leveraging body landmarks identified from human images, followed by the application of a genetic algorithm for precise feature identification and posture estimation. Observational data corroborates the superior efficacy of the Extra Tree Classifier technique in FHP detection, attaining an accuracy of 82.4%, a specificity of 85.5%, and a positive predictive value of 90.2%. Our model affords a rapid, effective solution for FHP identification, spotlighting the transformative potential of the convergence of feature point recognition and genetic algorithms in non-contact posture detection. The expansive potential and paramount importance of these applications in this niche field are therefore underscored.

Identification of the molecular subgroups in Alzheimer's disease by transcriptomic data.

Background: Alzheimer's disease (AD) is a heterogeneous pathological disease with genetic background accompanied by aging. This inconsistency is present among molecular subtypes, which has led to diagnostic ambiguity and failure in drug development. We precisely distinguished patients of AD at the transcriptome level. Methods: We collected 1,240 AD brain tissue samples collected from the GEO dataset. Consensus clustering was used to identify molecular subtypes, and the clinical characteristics were focused on. To reveal transcriptome differences among subgroups, we certificated specific upregulated genes and annotated the biological function. According to RANK METRIC SCORE in GSEA, TOP10 was defined as the hub gene. In addition, the systematic correlation between the hub gene and "A/T/N" was analyzed. Finally, we used external data sets to verify the diagnostic value of hub genes. Results: We identified three molecular subtypes of AD from 743 AD samples, among which subtypes I and III had high-risk factors, and subtype II had protective factors. All three subgroups had higher neuritis plaque density, and subgroups I and III had higher clinical dementia scores and neurofibrillary tangles than subgroup II. Our results confirmed a positive association between neurofibrillary tangles and dementia, but not neuritis plaques. Subgroup I genes clustered in viral infection, hypoxia injury, and angiogenesis. Subgroup II showed heterogeneity in synaptic pathology, and we found several essential beneficial synaptic proteins. Due to presenilin one amplification, Subgroup III was a risk subgroup suspected of familial AD, involving abnormal neurogenic signals, glial cell differentiation, and proliferation. Among the three subgroups, the highest combined diagnostic value of the hub genes were 0.95, 0.92, and 0.83, respectively, indicating that the hub genes had sound typing and diagnostic ability. Conclusion: The transcriptome classification of AD cases played out the pathological heterogeneity of different subgroups. It throws daylight on the personalized diagnosis and treatment of AD.

The Effectiveness of a Hybrid Exercise Program on the Physical Fitness of Frail Elderly.

BACKGROUND: Frailty is a serious physical disorder affecting the elderly all over the world. However, the frail elderly have low physical fitness, which limits the effectiveness of current exercise programs. Inspired by this, we attempted to integrate Baduanjin and strength and endurance exercises into an exercise program to improve the physical fitness and alleviate frailty among the elderly. Additionally, to achieve the goals of personalized medicine, machine learning simulations were performed to predict post-intervention frailty. METHODS: A total of 171 frail elderly individuals completed the experiment, including a Baduanjin group (BDJ), a strength and endurance training group (SE), and a combination of Baduanjin and strength and endurance training group (BDJSE), which lasted for 24 weeks. Physical fitness was evaluated by 10-meter maximum walk speed (10 m MWS), grip strength, the timed up-and-go test (TUGT), and the 6 min walk test (6 min WT). A one-way analysis of variance (ANOVA), chi-square test, and two-way repeated-measures ANOVA were carried out to analyze the experimental data. In addition, nine machine learning models were utilized to predict the frailty status after the intervention. RESULTS: In 10 m MWS and TUGT, there was a significant interactive influence between group and time. When comparing the BDJ group and the SE group, participants in the BDJSE group demonstrated the maximum gains in 10 m MWS and TUGT after 24 weeks of intervention. The stacking model surpassed other algorithms in performance. The accuracy and precision rates were 75.5% and 77.1%, respectively. CONCLUSION: The hybrid exercise program that combined Baduanjin with strength and endurance training proved more effective at improving fitness and reversing frailty in elderly individuals. Based on the stacking model, it is possible to predict whether an elderly person will exhibit reversed frailty following an exercise program.

Hybrid Exercise Program for Sarcopenia in Older Adults: The Effectiveness of Explainable Artificial Intelligence-Based Clinical Assistance in Assessing Skeletal Muscle Area.

Background: Sarcopenia is a geriatric syndrome characterized by decreased skeletal muscle mass and function with age. It is well-established that resistance exercise and Yi Jin Jing improve the skeletal muscle mass of older adults with sarcopenia. Accordingly, we designed an exercise program incorporating resistance exercise and Yi Jin Jing to increase skeletal muscle mass and reverse sarcopenia in older adults. Additionally, machine learning simulations were used to predict the sarcopenia status after the intervention. Method: This randomized controlled trial assessed the effects of sarcopenia in older adults. For 24 weeks, 90 older adults with sarcopenia were divided into intervention groups, including the Yi Jin Jing and resistance training group (YR, n = 30), the resistance training group (RT, n = 30), and the control group (CG, n = 30). Computed tomography (CT) scans of the abdomen were used to quantify the skeletal muscle cross-sectional area at the third lumbar vertebra (L3 SMA). Participants' age, body mass, stature, and BMI characteristics were analyzed by one-way ANOVA and the chi-squared test for categorical data. This study explored the improvement effect of three interventions on participants' L3 SMA, skeletal muscle density at the third lumbar vertebra (L3 SMD), skeletal muscle interstitial fat area at the third lumbar vertebra region of interest (L3 SMFA), skeletal muscle interstitial fat density at the third lumbar vertebra (L3 SMFD), relative skeletal muscle mass index (RSMI), muscle fat infiltration (MFI), and handgrip strength. Experimental data were analyzed using two-way repeated-measures ANOVA. Eleven machine learning models were trained and tested 100 times to assess the model's performance in predicting whether sarcopenia could be reversed following the intervention. Results: There was a significant interaction in L3 SMA (p < 0.05), RSMI (p < 0.05), MFI (p < 0.05), and handgrip strength (p < 0.05). After the intervention, participants in the YR and RT groups showed significant improvements in L3 SMA, RSMI, and handgrip strength. Post hoc tests showed that the YR group (p < 0.05) yielded significantly better L3 SMA and RSMI than the RT group (p < 0.05) and CG group (p < 0.05) after the intervention. Compared with other models, the stacking model exhibits the best performance in terms of accuracy (85.7%) and F1 (75.3%). Conclusion: One hybrid exercise program with Yi Jin Jing and resistance exercise training can improve skeletal muscle area among older adults with sarcopenia. Accordingly, it is possible to predict whether sarcopenia can be reversed in older adults based on our stacking model.

The Role of ANGPTL Gene Family Members in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is highly aggressive with a poor prognosis and survival rate. Certain ANGPTL members have been implicated in tumor progression. However, the relevance of the ANGPTL gene family to HCC remains poorly understood. In this study, we explored the role of ANGPTLs in the prognosis of HCC. Methods: From the CCLE database, we studied the expression of ANGPTLs in a range of cancer cell lines. The UCSC, HCCDB, and Human Protein Atlas databases were used to analyze the differences in mRNA and protein expression of ANGPTLs in HCC tissues. Additionally, the correlation between ANGPTL mRNA and methylation levels and clinicopathological features were assessed in the TCGA database. The correlation between ANGPTL mRNA and overall survival was determined by the Kaplan-Meier plotter. cBioPortal database was used to analyze ANGPTL genomic alterations. Genes associated with ANGPTLs were determined by enrichment with KEGG. Moreover, the differentially expressed genes of ANGPTLs were analyzed by the LinkedOmics database, and the KEGG pathway and miRNA targets of ANGPTLs were also enriched. Results: There was a significant correlation between the ANGPTL members (excluding ANGPTL2) and the prognosis of HCC patients according to the Kaplan-Meier plotter analysis (p < 0.05). ANGPTL1 was the gene with the highest mutation frequency. ANGPTLs are involved in certain pathways that may influence the development of HCC. Conclusion: In summary, the expression of some members of ANGPTLs was significantly correlated with HCC prognosis, suggesting that the ANGPTL gene family members may be promising molecular markers for HCC treatment and prognosis.

Based on Network Pharmacology to Explore the Molecular Targets and Mechanisms of Gegen Qinlian Decoction for the Treatment of Ulcerative Colitis.

BACKGROUND: Gegen Qinlian (GGQL) decoction is a common Chinese herbal compound for the treatment of ulcerative colitis (UC). In this study, we aimed to identify its molecular target and the mechanism involved in UC treatment by network pharmacology and molecular docking. Material and Methods. The active ingredients of Puerariae, Scutellariae, Coptis, and Glycyrrhiza were screened using the TCMSP platform with drug-like properties (DL) ≥ 0.18 and oral availability (OB) ≥ 30%. To find the intersection genes and construct the TCM compound-disease regulatory network, the molecular targets were determined in the UniProt database and then compared with the UC disease differential genes with P value < 0.005 and ∣log2 (fold change) | >1 obtained in the GEO database. The intersection genes were subjected to protein-protein interaction (PPI) construction and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. After screening the key active ingredients and target genes, the AutoDock software was used for molecular docking, and the best binding target was selected for molecular docking to verify the binding activity. RESULTS: A total of 146 active compounds were screened, and quercetin, kaempferol, wogonin, and stigmasterol were identified as the active ingredients with the highest associated targets, and NOS2, PPARG, and MMP1 were the targets associated with the maximum number of active ingredients. Through topological analysis, 32 strongly associated proteins were found, of which EGFR, PPARG, ESR1, HSP90AA1, MYC, HSPA5, AR, AKT1, and RELA were predicted targets of the traditional Chinese medicine, and PPARG was also an intersection gene. It was speculated that these targets were the key to the use of GGQL in UC treatment. GO enrichment results showed significant enrichment of biological processes, such as oxygen levels, leukocyte migration, collagen metabolic processes, and nutritional coping. KEGG enrichment showed that genes were particularly enriched in the IL-17 signaling pathway, AGE-RAGE signaling pathway, toll-like receptor signaling pathway, tumor necrosis factor signaling pathway, transcriptional deregulation in cancer, and other pathways. Molecular docking results showed that key components in GGQL had good potential to bind to the target genes MMP3, IL1B, NOS2, HMOX1, PPARG, and PLAU. CONCLUSION: GGQL may play a role in the treatment of ulcerative colitis by anti-inflammation, antioxidation, and inhibition of cancer gene transcription.