Identifying diagnostic indicators for type 2 diabetes mellitus from physical examination using interpretable machine learning approach.

Background: Identification of patients at risk for type 2 diabetes mellitus (T2DM) can not only prevent complications and reduce suffering but also ease the health care burden. While routine physical examination can provide useful information for diagnosis, manual exploration of routine physical examination records is not feasible due to the high prevalence of T2DM. Objectives: We aim to build interpretable machine learning models for T2DM diagnosis and uncover important diagnostic indicators from physical examination, including age- and sex-related indicators. Methods: In this study, we present three weighted diversity density (WDD)-based algorithms for T2DM screening that use physical examination indicators, the algorithms are highly transparent and interpretable, two of which are missing value tolerant algorithms. Patients: Regarding the dataset, we collected 43 physical examination indicator data from 11,071 cases of T2DM patients and 126,622 healthy controls at the Affiliated Hospital of Southwest Medical University. After data processing, we used a data matrix containing 16004 EHRs and 43 clinical indicators for modelling. Results: The indicators were ranked according to their model weights, and the top 25% of indicators were found to be directly or indirectly related to T2DM. We further investigated the clinical characteristics of different age and sex groups, and found that the algorithms can detect relevant indicators specific to these groups. The algorithms performed well in T2DM screening, with the highest area under the receiver operating characteristic curve (AUC) reaching 0.9185. Conclusion: This work utilized the interpretable WDD-based algorithms to construct T2DM diagnostic models based on physical examination indicators. By modeling data grouped by age and sex, we identified several predictive markers related to age and sex, uncovering characteristic differences among various groups of T2DM patients.

Geraniol attenuates oxygen-glucose deprivation/reoxygenation-induced ROS-dependent apoptosis and permeability of human brain microvascular endothelial cells by activating the Nrf-2/HO-1 pathway.

Blood-brain barrier breakdown and ROS overproduction are important events during the progression of ischemic stroke aggravating brain damage. Geraniol, a natural monoterpenoid, possesses anti-apoptotic, cytoprotective, anti-oxidant, and anti-inflammatory activities. Our study aimed to investigate the effect and underlying mechanisms of geraniol in oxygen-glucose deprivation/reoxygenation (OGD/R)-induced human brain microvascular endothelial cells (HBMECs). Apoptosis, caspase-3 activity, and cytotoxicity of HBMECs were evaluated using TUNEL, caspase-3 activity, and CCK-8 assays, respectively. The permeability of HBMECs was examined using FITC-dextran assay. Reactive oxygen species (ROS) production was measured using the fluorescent probe DCFH-DA. The protein levels of zonula occludens-1 (ZO-1), occludin, claudin-5, ß-catenin, nuclear factor erythroid 2-related factor 2 (Nrf2), and heme oxygenase-1 (HO-1) were determined by western blotting. Geraniol showed no cytotoxicity in HBMECs. Geraniol and ROS scavenger N-acetylcysteine (NAC) both attenuated OGD/R-induced apoptosis and increase of caspase-3 activity and the permeability to FITC-dextran in HBMECs. Geraniol relieved OGD/R-induced ROS accumulation and decrease of expression of ZO-1, occludin, claudin-5, and ß-catenin in HBMECs. Furthermore, we found that geraniol activated Nrf2/HO-1 pathway to inhibit ROS in HBMECs. In conclusion, geraniol attenuated OGD/R-induced ROS-dependent apoptosis and permeability in HBMECs through activating the Nrf2/HO-1 pathway.

Erratum: FAM72A promotes glioma progression by regulating mitophagy through the Pink1/Parkin signaling pathway: Erratum.

[This corrects the article DOI: 10.7150/jca.82949.].

Wide-range soft anisotropic thermistor with a direct wireless radio frequency interface.

Temperature sensors are one of the most fundamental sensors and are found in industrial, environmental, and biomedical applications. The traditional approach of reading the resistive response of Positive Temperature Coefficient thermistors at DC hindered their adoption as wide-range temperature sensors. Here, we present a large-area thermistor, based on a flexible and stretchable short carbon fibre incorporated Polydimethylsiloxane composite, enabled by a radio frequency sensing interface. The radio frequency readout overcomes the decades-old sensing range limit of thermistors. The composite exhibits a resistance sensitivity over 1000 °C-1, while maintaining stability against bending (20,000 cycles) and stretching (1000 cycles). Leveraging its large-area processing, the anisotropic composite is used as a substrate for sub-6 GHz radio frequency components, where the thermistor-based microwave resonators achieve a wide temperature sensing range (30 to 205 °C) compared to reported flexible temperature sensors, and high sensitivity (3.2 MHz/°C) compared to radio frequency temperature sensors. Wireless sensing is demonstrated using a microstrip patch antenna based on a thermistor substrate, and a battery-less radio frequency identification tag. This radio frequency-based sensor readout technique could enable functional materials to be directly integrated in wireless sensing applications.

Relationship among physical exercise, social support and sense of coherence in rural left-behind children.

OBJECTIVE: Sense of coherence has significant implications for the mental health of left-behind children in rural China. This study was conducted to explore the impact of physical exercise and social support on sense of coherence in rural left-behind children. METHODS: A survey was conducted among 964 rural left-behind children in Hunan Province of China aged 10-15 (Mage = 12.01 ± 1.97 years; 529 girls and 435 boys). AMOS 21.0 software was applied to build the model and perform cross-lagged analysis. RESULTS: Physical exercise and social support in left-behind children predict each other, and physical exercise can positively predict social support and sense of coherence in left-behind children two months later (P < 0.05); social support can significantly positively predict sense of coherence in left-behind children two months later (P < 0.05). CONCLUSIONS: Both physical exercise and social support have an impact on sense of coherence in left-behind children, and physical exercise can affect sense of coherence in left-behind children through the mediating effect of social support.

Comparison of Glenohumeral Bone Morphology Between Patients With Versus Without Anterior Shoulder Instability.

Background: The stability of the glenohumeral joint is associated with anatomic characteristics including bony structures and soft tissues. Purpose: To compare the differences in specific bony glenohumeral geometries between shoulders with anterior shoulder instability (ASI), unaffected contralateral shoulders, and healthy control shoulders. Study Design: Cross-sectional study; Level of evidence, 3. Methods: Shoulder computed tomography (CT) scans of 36 patients with ASI and 36 matched healthy controls were retrieved and 3-dimensionally reconstructed. We measured the glenoid radius of curvature (GROC) in the anterior-posterior (AP) and superior-inferior directions, humeral head radius of curvature (HROC) in the AP direction, conformity index, glenoid height, glenoid width, glenoid index, stability angle, glenoid version, and glenoid depth. The differences between the groups were statistically calculated. CT scans of the unaffected contralateral shoulders from 21 of the ASI patients were also collected to identify the consistency of the bony structures in bilateral shoulders. Results: Patients with ASI had greater GROC in the AP direction (P < .001), HROC in the AP direction (P = .002), glenoid height (P = .005), and glenoid index (P < .001) and smaller conformity index (P < .001), glenoid width (P = .002), stability angle (P < .001), and glenoid depth (P < .001). In addition, the glenoid of the ASI patients was more anteverted compared with that of controls (P = .001). There was no statistical difference in half the measurements between the bilateral shoulder joints in patients with ASI. Conclusion: In this study, glenohumeral geometric differences were found between ASI patients and healthy control participants. Glenoid curvature and conformity index, based on bilateral comparisons of affected and contralateral shoulders, appear inherent and may predict ASI risk.

Attention-based deep clustering method for scRNA-seq cell type identification.

Single-cell sequencing (scRNA-seq) technology provides higher resolution of cellular differences than bulk RNA sequencing and reveals the heterogeneity in biological research. The analysis of scRNA-seq datasets is premised on the subpopulation assignment. When an appropriate reference is not available, such as specific marker genes and single-cell reference atlas, unsupervised clustering approaches become the predominant option. However, the inherent sparsity and high-dimensionality of scRNA-seq datasets pose specific analytical challenges to traditional clustering methods. Therefore, a various deep learning-based methods have been proposed to address these challenges. As each method improves partially, a comprehensive method needs to be proposed. In this article, we propose a novel scRNA-seq data clustering method named AttentionAE-sc (Attention fusion AutoEncoder for single-cell). Two different scRNA-seq clustering strategies are combined through an attention mechanism, that include zero-inflated negative binomial (ZINB)-based methods dealing with the impact of dropout events and graph autoencoder (GAE)-based methods relying on information from neighbors to guide the dimension reduction. Based on an iterative fusion between denoising and topological embeddings, AttentionAE-sc can easily acquire clustering-friendly cell representations that similar cells are closer in the hidden embedding. Compared with several state-of-art baseline methods, AttentionAE-sc demonstrated excellent clustering performance on 16 real scRNA-seq datasets without the need to specify the number of groups. Additionally, AttentionAE-sc learned improved cell representations and exhibited enhanced stability and robustness. Furthermore, AttentionAE-sc achieved remarkable identification in a breast cancer single-cell atlas dataset and provided valuable insights into the heterogeneity among different cell subtypes.

National and subnational trends in cancer burden in China, 2005-20: an analysis of national mortality surveillance data.

BACKGROUND: Cancer has been the leading cause of death since 2010 in China, with increasing incidence, mortality, and burden. We aimed to assess national and subnational changes in the cancer burden from 2005 to 2020 in China using data from the National Mortality Surveillance System. METHODS: We extracted data on cancer-related deaths from the National Mortality Surveillance System, which accounts for 24·3% of the country's population with national and provincial representativeness. Data for the surveillance population stratified by age and sex were extracted from the National Bureau of Statistics of China. We estimated mortality and years of life lost (YLLs) for all cancers and for 23 cancer groups by age and sex, nationally, and for 31 provinces in China between 2005 and 2020. We calculated age-standardised mortality and YLL rates using the China 2020 census as the reference population. Average annual percent changes in age-standardised rates for mortality and YLLs were calculated to assess trends over the study period. Decomposition analysis was used to assess the drivers of changes in cancer-related death due to three explanatory components: population growth, population ageing, and age-specific mortality rates in China. FINDINGS: The total number of cancer-related deaths increased by 21·6% to 2 397 772 and YLLs increased by 5·0% to 56 598 975 between 2005 and 2020. The three leading fatal cancer types remained stable for both sexes over the study period: tracheal, bronchus, and lung cancer; liver cancer; and stomach cancer. The fourth and fifth leading cancers also remained stable among males (oesophageal, and colon and rectum), while colon and rectum cancer replaced oesophageal cancer as the fourth and breast cancer replaced colon and rectum cancer as the fifth leading cause of cancer-related death among females. Age-standardised mortality rates and age-standardised YLL rates for almost all cancer types (except for prostate for male and multiple myeloma for female) decreased significantly in both sexes in urban areas. Age-standardised YLL rates increased for about half of all cancers for both sexes in rural areas. Leading fatal types were leukaemia and brain and nervous system cancer in younger groups (aged 0-19 years); liver, tracheal, bronchus, and lung, or breast cancers in middle-aged groups (aged 40-59 years); and tracheal, bronchus, and lung, liver, or stomach cancers in older adults (aged ≥60 years) in 2020. The leading causes of cancer-related mortality varied for each province, with tracheal, bronchus, and lung or liver cancer at the top in 30 provinces. INTERPRETATION: The cancer burden in China appeared to be shifting towards that in high-income countries from 2005 to 2020. Adjustments to existing health plans and actions are needed to reduce the burdens of tracheal, bronchus, and lung cancer or other leading and emerging cancers. FUNDING: National Key Research and Development Program of China.

Efficacy of DAIR in managing Candida parapsilosis-infected total knee arthroplasty with five-year follow-up: A case report and review of literature.

RATIONALE: Fungal periprosthetic joint infections (fPJIs) are relatively uncommon, accounting for approximately 1% of all PJIs. Revision surgery is typically recommended for fungal infections; however, the physical and financial impact on patients is significant. In this report, we present a case of fPJI successfully treated with debridement, antibiotics, and implant retention (DAIR) with a favorable outcome over a 5-year period. PATIENT CONCERN: A 56-year-old male patient presented with a non-healing surgical incision 1 week after undergoing primary total knee arthroplasty on the right side. DIAGNOSIS: Microbiological culture of the wound effusion identified Candida parapsilosis. Postoperatively, the patient exhibited a significant decrease in serum albumin levels and poor glycemic control. Both C-reactive protein and erythrocyte sedimentation rate were elevated. INTERVENTIONS: A comprehensive DAIR procedure was performed, along with continuous closed irrigation using fluconazole for 1 week. The patient received intravenous voriconazole for 4 weeks, followed by oral fluconazole for an additional 3 months. OUTCOMES: At 1- and 5-year follow-up appointments, the patient C-reactive protein and erythrocyte sedimentation rate levels were within normal limits, and there was no evidence of swelling, erythema, or tenderness in the right knee joint, indicating no signs of infection. LESSONS: DAIR is an effective treatment for early fPJIs, and continuous closed irrigation may provide specific advantages. The patient nutritional status plays a crucial role in the management of periprosthetic infections.

Target discovery of bioactive natural products with native-compound-coupled CNBr-activated Sepharose 4B beads (NCCB): Applications, mechanisms and outlooks.

Natural products (NPs) represent a treasure trove for drug discovery and development due to their chemical structural diversity and a broad spectrum of biological activities. Uncovering the biological targets and understanding their molecular mechanism of actions are crucial steps in the development of clinical therapeutics. However, the structural complexity of NPs and intricate nature of biological system present formidable challenges in target identification of NPs. Although significant advances have been made in the development of new chemical tools, these methods often require high levels of synthetic skills for preparing chemical probes. This can be costly and time-consuming relaying on operationally complicated procedures and instruments. In recent efforts, we and others have successfully developed an operationally simple and practical chemical tool known as native-compound-coupled CNBr-activated Sepharose 4B beads (NCCB) for NP target identification. In this approach, a native compound readily reacts with commercial CNBr-activated Sepharose 4B beads with a process that is easily performed in any biology laboratory. Based on NCCB, our group has identified the direct targets of more than 60 NPs. In this review, we will elucidate the application scopes, including flavonoids, quinones, terpenoids and others, characteristics, chemical mechanisms, procedures, advantages, disadvantages, and future directions of NCCB in specific target discovery.

Attention Mechanism-Based Graph Neural Network Model for Effective Activity Prediction of SARS-CoV-2 Main Protease Inhibitors: Application to Drug Repurposing as Potential COVID-19 Therapy.

Compared to de novo drug discovery, drug repurposing provides a time-efficient way to treat coronavirus disease 19 (COVID-19) that is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 main protease (Mpro) has been proved to be an attractive drug target due to its pivotal involvement in viral replication and transcription. Here, we present a graph neural network-based deep-learning (DL) strategy to prioritize the existing drugs for their potential therapeutic effects against SARS-CoV-2 Mpro. Mpro inhibitors were represented as molecular graphs ready for graph attention network (GAT) and graph isomorphism network (GIN) modeling for predicting the inhibitory activities. The result shows that the GAT model outperforms the GIN and other competitive models and yields satisfactory predictions for unseen Mpro inhibitors, confirming its robustness and generalization. The attention mechanism of GAT enables to capture the dominant substructures and thus to realize the interpretability of the model. Finally, we applied the optimal GAT model in conjunction with molecular docking simulations to screen the Drug Repurposing Hub (DRH) database. As a result, 18 drug hits with best consensus prediction scores and binding affinity values were identified as the potential therapeutics against COVID-19. Both the extensive literature searching and evaluations on adsorption, distribution, metabolism, excretion, and toxicity (ADMET) illustrate the premium drug-likeness and pharmacokinetic properties of the drug candidates. Overall, our work not only provides an effective GAT-based DL prediction tool for inhibitory activity of SARS-CoV-2 Mpro inhibitors but also provides theoretical guidelines for drug discovery in the COVID-19 treatment.

Recent advances of antitumor leading compound Erianin: Mechanisms of action and structural modification.

Erianin, a bioactive compound extracted from Dendrobium, a traditional Chinese medicine, exhibits remarkable anti-cancer properties through diverse molecular mechanisms and has attracted the attention of medicinal chemists. However, the low solubility in water, rapid metabolism and elimination from the body lead to poor bioavailability of Erianin, and greatly hinder its clinical application. The development of new Erianin derivatives is continuously proceed to improve its anticancer effects. In recent years, although important progress in the development of Erianin and the publication of some reviews in this aspect, the mechanism against various cancers, pharmacokinetic study, structural modification as well as structure-activity relationships have not been thoroughly considered. This review is aimed at providing complete picture regarding the above aspects by reviewing studies from 2000 to 2023.06. This review also supplies some important viewpoints on the design and future directions for the development of Erianin derivatives as possible clinically effective anticancer agents.

Native-compound-Coupled Affinity Matrix (NCAM) in target identification and validation of bioactive compounds: Application, mechanism and outlooks.

In drug discovery and development, the direct target identification of bioactive small molecules plays a significant role for understanding the mechanism of action, predicting the side effects, and rationally designing more potent compounds. However, due to the complicated regulatory processes in a cell together with thousands of biomacromolecules, target identification is always the major obstacle. New methods and technologies are continuously invented to tackle this problem. Nevertheless, the mainly used tools possess several disadvantages. High synthetic skills are typically required to laboriously synthesize a probe for protein enrichment. To detect the ligand-protein interaction by analyzing proteins' responses to proteolytic or thermal treatment, costly and precise instruments are always necessary. Therefore, convenient and practical techniques are urgently needed. Over the past decades, a strategy using native compounds without the requirement of chemical modification, also termed Native-compound-Coupled Affinity Matrix (NCAM), is developing continuously. Two practical tactics based on "label-free" compounds have been invented and used, that is Photo-cross-linked Small-molecule Affinity Matrix (PSAM) and Native-compound-Coupled CNBr-activated Beads (NCCB). Presently, we will elucidate the characteristics, coupling mechanism, advantages and disadvantages, and future prospect of NCAM in specific target identification and validation.

HOPEXGB: A Consensual Model for Predicting miRNA/lncRNA-Disease Associations Using a Heterogeneous Disease-miRNA-lncRNA Information Network.

Predicting disease-related microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) is crucial to find new biomarkers for the prevention, diagnosis, and treatment of complex human diseases. Computational predictions for miRNA/lncRNA-disease associations are of great practical significance, since traditional experimental detection is expensive and time-consuming. In this paper, we proposed a consensual machine-learning technique-based prediction approach to identify disease-related miRNAs and lncRNAs by high-order proximity preserved embedding (HOPE) and eXtreme Gradient Boosting (XGB), named HOPEXGB. By connecting lncRNA, miRNA, and disease nodes based on their correlations and relationships, we first created a heterogeneous disease-miRNA-lncRNA (DML) information network to achieve an effective fusion of information on similarities, correlations, and interactions among miRNAs, lncRNAs, and diseases. In addition, a more rational negative data set was generated based on the similarities of unknown associations with the known ones, so as to effectively reduce the false negative rate in the data set for model construction. By 10-fold cross-validation, HOPE shows better performance than other graph embedding methods. The final consensual HOPEXGB model yields robust performance with a mean prediction accuracy of 0.9569 and also demonstrates high sensitivity and specificity advantages compared to lncRNA/miRNA-specific predictions. Moreover, it is superior to other existing methods and gives promising performance on the external testing data, indicating that integrating the information on lncRNA-miRNA interactions and the similarities of lncRNAs/miRNAs is beneficial for improving the prediction performance of the model. Finally, case studies on lung, stomach, and breast cancers indicate that HOPEXGB could be a powerful tool for preclinical biomarker detection and bioexperiment preliminary screening for the diagnosis and prognosis of cancers. HOPEXGB is publicly available at https://github.com/airpamper/HOPEXGB.

The association between nasal mucosa bacteria and serum metals in children with nasal diseases.

Allergic rhinitis (AR) and adenoid hypertrophy (AH) are common nasal diseases in children. Studies have shown that heavy metals are environmental risk factors for nasal diseases, and the pathogenic mechanisms may be related to dysregulation of nasal mucosal microbiota. However, it is unclear how heavy metal exposure relates to the nasal mucosal microbiota in nasal diseases. Therefore, we explored serum metal exposure levels and nasal mucosal microbiota composition in children with different nasal disease, and further studied the potential correlation between metal exposure and disease-related taxa. There were 64 children recruited for this study. The 23 metals concentrations in serum were measured by inductively coupled plasma mass spectrometry, and nasal mucosal bacteria was identified by 16S rRNA sequencing. Nasal diseases (AR and AH) in children were associated with alterations in the abundance and diversity of the nasal mucosal microbiota. The nasal microbiota of children with AR showed lower diversity, while the microbiota of children with AH showed higher diversity. Linear discriminant analysis Effect Size showed 108 differentially abundant taxa between AR and control groups, 35 differentially abundant taxa among large adenoid, moderate adenoid and small adenoid groups. The serum zinc concentration was negatively correlated with Pielou's eveness index and Simpson's Index in children classified by adenoid size. The spearman correlation analysis showed that multiple disease-related taxa were closely associated with metal concentrations in serum. Our findings may support a link between metal exposure and the diversity and composition of nasal bacteria in children with nasal disease, which present new evidence for the effects of metals on children health.

Sex-Specific Differences in Left Ventricular Mass and Volumes with Body Mass Index among Children Aged 6 to 8: A Cross-Sectional Study in China.

Few studies have examined the sex differences in left ventricle (LV) structure and physiology from early life stages. We aimed to assess the role of sex and overweight/obesity on left ventricular mass (LVM) and LV volume in Chinese children without preexisting cardiovascular risk factors. We selected 934 healthy children aged 6-8 years from an existing cohort in Beijing, China. Linear regression models were used to regress body mass index (BMI), fat mass, systolic blood pressure, diastolic blood pressure, waist circumference, and visceral fat area (VFA) with LVM, left ventricle end-diastolic volume (LVEDV) and end-systolic volume (LVESV). Higher BMI, fat mass, waist circumference, VFA, and stroke volume (SV) predicted higher LVM, LVEDV, and LVESV in both sexes. Multivariable analysis showed that boys with an elevated BMI had greater LV hypertrophy. LVEDV and LVESV were higher among boys than among girls and increased with higher BMI in both boys and girls. LVEDV and LVESV were associated with VFA in boys. We observed sex differences in LVM, LVESV, and LVEDV among prepubertal children, independent of obesity, with higher values observed in boys. Sex differences in cardiac structure in children may help explain the higher incidence of cardiovascular disease in male adults. Whether interventions to reduce childhood obesity can improve the trajectory of cardiac dynamics is worth investigating.

Bilateral anterior congenital radial head dislocation in adults: a case report and literature review.

Objective: Congenital dislocation of the radial head (CRHD) is a rare condition, with bilateral anterior cases being even less common worldwide. Only a few cases had residual pain after adulthood, even when left untreated. Herein, we describe an adult case of bilateral anterior CRHD with significant pain and snapping during motion. The aim of this study was to report the physical and radiological findings, treatment methods, and short-term outcomes of our case and to review adult CRHD cases in the literature. Patient: A 21-year-old male patient presented to our hospital with chief complaints of snapping and exacerbated pain during motion in his left elbow. Diagnoses and interventions: Detailed medical history and physical examination results were recorded. Radiographic examinations were performed on the bilateral elbow, and the diagnosis of bilateral anterior congenital radial head dislocation was confirmed. To relieve the pain and snapping in the left elbow, we performed open reduction and fixation of the radial head with annular ligament reconstruction and ulnar osteotomy. Postoperatively, the elbow rested at 90° flexion with a cast for 16 weeks, and the K-wire was removed on the 10th week; afterward, active functional exercises were performed. Outcomes: The patient was followed-up for 1 year. The pain in his left elbow was relieved with a reduction in the visual analog scale score from 7 to 3. The range of motion of the left elbow was changed from 0° to 135° (preoperative) to -5° to 120° (postoperative) (extension-flexion) without any snapping. However, restrictions in external rotation have not yet been fully resolved. Further physical rehabilitation is required. Conclusion: When managing patients with congenital radial head dislocation, the contralateral elbow should be evaluated to identify potential bilateral cases. Surgical options should be discussed with adult patients only for the strong need for functional improvement, although the outcomes may not be fully satisfactory.

Validation of "Life's Essential 8" Metrics With Cardiovascular Structural Status in Children: The PROC Study in China.

Background Life's Essential 8 (LE8) metrics for cardiovascular health (CVH) aid primordial prevention in US populations. Methods and Results We conducted a child cohort study (PROC [Beijing Child Growth and Health Cohort]) with baseline (2018-2019) and follow-up (2020-2021) assessments, enrolling disease-free 6- to 10-year-old children from 6 elementary schools in Beijing. We collected LE8-assessed components via questionnaire surveys and 3 cardiovascular structural parameters by 2-dimensional M-mode echocardiography: left ventricular mass (LVM), LVM index, and carotid intima-media thickness. Compared with 1914 participants (mean age, 6.6 years) at baseline, we saw lower mean CVH scores at follow-up (n=1789; 8.5 years). Among LE8 components, diet presented the lowest perfect-score prevalence (5.1%). Only 18.6% of participants had physical activity ≥420 min/wk, 55.9% had nicotine exposure, and 25.2% had abnormal sleep duration. Prevalence of overweight/obesity was 26.8% at baseline and 38.2% at follow-up. We noted optimal blood lipid scores in 30.7%, while 12.9% of children had abnormal fasting glucose. Normal BP was 71.6% at baseline and 60.3% at follow-up. LVM (g), LVM index (g/m2.7), and carotid intima-media thickness (mm) were significantly lower in children with high (56.8, 33.2, 0.35) or moderate CVH scores (60.6, 34.6, 0.36), compared with children with low CVH scores (67.9, 37.1, 0.37). Adjusting for age/sex, LVM (ß=11.8 [95% CI, 3.5-20.0]; P=0.005), LVM index (ß=4.4 [95% CI, 0.5-8.3]; P=0.027), and carotid intima-media thickness (ß=0.016 [95% CI, 0.002-0.030]; P=0.028) were higher in the low-CVH group. Conclusions CVH scores were suboptimal, declining with age. LE8 metrics indicated worse CVH in children with abnormal cardiovascular structural measurements, suggesting the validity of LE8 in assessing child CVH. Registration URL: https://www.chictr.org.cn/index.html; Unique identifier: ChiCTR2100044027.

FAM72A promotes glioma progression by regulating mitophagy through the Pink1/Parkin signaling pathway.

Background: There is growing evidence that aberrant expression of FAM72A contributes to biological dysfunction, especially mitochondrial dysfunction. However, its role in most tumors remains unclear, especially in glioma. Methods: Herein, a high-throughput sequencing approach was used here to identify FAM72A as the target molecule. Next, we detected the protein and mRNA expression levels of FAM72A in normal brain tissue (NBT) as well as different grades of glioma tissue. CCK-8, colony formation, Transwell assays, and Western blotting, were all used to determine the molecular effects of FAM72A on glioma cells. Results: FAM72A was significantly upregulated in glioma, was significantly correlated with WHO grade and was associated with poor clinical outcomes. In functional assays, FAM72A was shown to promote glioma cell growth. Subsequent mechanistic studies indicated that FAM72A promoted glioma progression by regulating mitophagy through the Pink1/Parkin signaling pathway. In addition, FAM72A promoted mitophagy and maintained Pink1 stability through the Pink1/Parkin signaling pathway. Finally, FAM72A promoted tumor immune escape by upregulating PD-L1 expression. Conclusion: All of these data indicate that FAM72A confers an aggressive phenotype and poor prognosis on gliomas. Targeting FAM72A might represent a new therapeutic strategy for glioma.