Peak Performance: Characteristics and Key Factors in the Development of the World Top-8 Swimmers Based on Longitudinal Data.

PURPOSE: This study aimed to investigate the peak performance characteristics of the world top-8 swimmers and the key factors involved in the journey toward achieving better peak performance. METHODS: The results of the world top-8 swimmers from 2001 to 2022 were collected from the World Aquatics performance database. Progression to peak performance was tracked with individual quadratic trajectories (1191 cases). Utilizing k-means clustering to group competitive feature variables, this study investigated key developmental factors through a binary logistic regression model, using the odds ratio (OR) to represent whether a factor was favorable (OR > 1) or unfavorable (OR < 1). RESULTS: Significant differences (P < .001) in the peak age between men (23.54/3.80) and women (22.31/4.60) were noticed, while no significant differences (P > .05) in the peak-performance window for both sexes appeared. Peak performance occurred at later ages for the sprint for both sexes, and women had a longer duration in peak-performance window for sprint (P < .05). Peak-performance occurred at later ages for the breaststroke and butterfly for both sexes (P < .05). Binary logistic regression revealed that high first-participation performance (OR = 1.502), high major-competition performance (OR = 4.165), early first-major-competition age (OR = 1.441), participation frequency above 4 times/year in both phase 2 (4.3-8.0 times/y, OR = 3.940; 8.1-20.0 times/y, OR = 5.122) and phase 3 (4.1-7.5 times/y: OR = 5.548; 7.7-15.0 times/y: OR = 7.526), and a career length of 10 years or more (10-15 y, OR = 2.102; 16-31 y, OR = 3.480) were favorable factors for achieving better peak performance. CONCLUSIONS: Peak performance characteristics varied across sex, swimming stroke, and race distance in the world top-8 swimmers. Meanwhile, the research indicated that certain specific developmental factors were key conditions for the world top-8 swimmers to achieve better peak performance in the future.

Cognitive trajectories in older adults and the role of depressive symptoms: A 7-year follow-up study.

OBJECTIVES: To examine different trajectories of cognitive changes in elderly adults and explore the mediating role of depressive symptoms. DESIGN: A 7-year, community-based, prospective cohort study. SETTING: The downtown neighborhood of Shanghai, China. PARTICIPANTS: A cohort of 394 older adults, with an average age of 71.8 years, was recruited in 2015 and has been reassessed every two years until 2021. METHODS: Latent Class Growth Analysis was used to model aging trajectories and Linear Mixed-Effect Models for Repeated Measures were used to estimate the least squares mean changes of cognition between subjects with depression (DEP+) and without (DEP-) across all visits. RESULTS: Three cognitive trajectories were identified: the "successful aging" (SA) trajectory had the best and most consistent performance (n=229, 55.9%); the "normal aging" (NA) trajectory showed lower but stable cognition (n=141, 37.3%); while the "cognitive decline" (CD) trajectory displayed poor and declining cognition (n=24, 6.8%). Depressive symptoms were found to be influential across all trajectories. In the CD trajectory, the MoCA scores of the DEP+ group increased in within-group comparisons and were significantly higher than those of the DEP- group at visits 1 and 3 in between-group comparisons. A similar trend was observed in the NA trajectory, though it did not reach statistical significance. CONCLUSIONS: Our research suggests that mild and decreasing depressive symptoms can be a reversible factor that might slow down the irreversible cognitive decline in the elderly. Therefore, we suggest that even mild depressive symptoms in the elderly should be monitored and detected.

Gut microbiome features and metabolites in non-alcoholic fatty liver disease among community-dwelling middle-aged and older adults.

BACKGROUND: The specific microbiota and associated metabolites linked to non-alcoholic fatty liver disease (NAFLD) are still controversial. Thus, we aimed to understand how the core gut microbiota and metabolites impact NAFLD. METHODS: The data for the discovery cohort were collected from the Guangzhou Nutrition and Health Study (GNHS) follow-up conducted between 2014 and 2018. We collected 272 metadata points from 1546 individuals. The metadata were input into four interpretable machine learning models to identify important gut microbiota associated with NAFLD. These models were subsequently applied to two validation cohorts [the internal validation cohort (n = 377), and the prospective validation cohort (n = 749)] to assess generalizability. We constructed an individual microbiome risk score (MRS) based on the identified gut microbiota and conducted animal faecal microbiome transplantation experiment using faecal samples from individuals with different levels of MRS to determine the relationship between MRS and NAFLD. Additionally, we conducted targeted metabolomic sequencing of faecal samples to analyse potential metabolites. RESULTS: Among the four machine learning models used, the lightGBM algorithm achieved the best performance. A total of 12 taxa-related features of the microbiota were selected by the lightGBM algorithm and further used to calculate the MRS. Increased MRS was positively associated with the presence of NAFLD, with odds ratio (OR) of 1.86 (1.72, 2.02) per 1-unit increase in MRS. An elevated abundance of the faecal microbiota (f__veillonellaceae) was associated with increased NAFLD risk, whereas f__rikenellaceae, f__barnesiellaceae, and s__adolescentis were associated with a decreased presence of NAFLD. Higher levels of specific gut microbiota-derived metabolites of bile acids (taurocholic acid) might be positively associated with both a higher MRS and NAFLD risk. FMT in mice further confirmed a causal association between a higher MRS and the development of NAFLD. CONCLUSIONS: We confirmed that an alteration in the composition of the core gut microbiota might be biologically relevant to NAFLD development. Our work demonstrated the role of the microbiota in the development of NAFLD.

Mapping multi-omics characteristics related to short-term PM2.5 trajectory and their impact on type 2 diabetes in middle-aged and elderly adults in Southern China.

The relationship between PM2.5 and metabolic diseases, including type 2 diabetes (T2D), has become increasingly prominent, but the molecular mechanism needs to be further clarified. To help understand the mechanistic association between PM2.5 exposure and human health, we investigated short-term PM2.5 exposure trajectory-related multi-omics characteristics from stool metagenome and metabolome and serum proteome and metabolome in a cohort of 3267 participants (age: 64.4 ± 5.8 years) living in Southern China. And then integrate these features to examine their relationship with T2D. We observed significant differences in overall structure in each omics and 193 individual biomarkers between the high- and low-PM2.5 groups. PM2.5-related features included the disturbance of microbes (carbohydrate metabolism-associated Bacteroides thetaiotaomicron), gut metabolites of amino acids and carbohydrates, serum biomarkers related to lipid metabolism and reducing n-3 fatty acids. The patterns of overall network relationships among the biomarkers differed between T2D and normal participants. The subnetwork membership centered on the hub nodes (fecal rhamnose and glycylproline, serum hippuric acid, and protein TB182) related to high-PM2.5, which well predicted higher T2D prevalence and incidence and a higher level of fasting blood glucose, HbA1C, insulin, and HOMA-IR. Our findings underline crucial PM2.5-related multi-omics biomarkers linking PM2.5 exposure and T2D in humans.

LINC01559 promotes lung adenocarcinoma metastasis by disrupting the ubiquitination of vimentin.

BACKGROUND: Distant metastasis is the major cause of lung adenocarcinoma (LUAD)-associated mortality. However, molecular mechanisms involved in LUAD metastasis remain to be fully understood. While the role of long non-coding RNAs (lncRNAs) in cancer development, progression, and treatment resistance is being increasingly appreciated, the list of dysregulated lncRNAs that contribute to LUAD pathogenesis is also rapidly expanding. METHODS: Bioinformatics analysis was conducted to interrogate publicly available LUAD datasets. In situ hybridization and qRT-PCR assays were used to test lncRNA expression in human LUAD tissues and cell lines, respectively. Wound healing as well as transwell migration and invasion assays were employed to examine LUAD cell migration and invasion in vitro. LUAD metastasis was examined using mouse models in vivo. RNA pulldown and RNA immunoprecipitation were carried out to test RNA-protein associations. Cycloheximide-chase assays were performed to monitor protein turnover rates and Western blotting was employed to test protein expression. RESULTS: The expression of the lncRNA LINC01559 was commonly upregulated in LUADs, in particular, in those with distant metastasis. High LINC01559 expression was associated with poor outcome of LUAD patients and was potentially an independent prognostic factor. Knockdown of LINC01559 diminished the potential of LUAD cell migration and invasion in vitro and reduced the formation of LUAD metastatic lesions in vivo. Mechanistically, LINC01559 binds to vimentin and prevents its ubiquitination and proteasomal degradation, leading to promotion of LUAD cell migration, invasion, and metastasis. CONCLUSION: LINC01559 plays an important role in LUAD metastasis through stabilizing vimentin. The expression of LINC01559 is potentially an independent prognostic factor of LUAD patients, and LINC01559 targeting may represent a novel avenue for the treatment of late-stage LUAD.

Proteome-wide profiling reveals dysregulated molecular features and accelerated aging in osteoporosis: A 9.8-year prospective study.

The role of circulatory proteomics in osteoporosis is unclear. Proteome-wide profiling holds the potential to offer mechanistic insights into osteoporosis. Serum proteome with 413 proteins was profiled by liquid chromatography-tandem mass spectrometry (LC-MS/MS) at baseline, and the 2nd, and 3rd follow-ups (7704 person-tests) in the prospective Chinese cohorts with 9.8 follow-up years: discovery cohort (n = 1785) and internal validation cohort (n = 1630). Bone mineral density (BMD) was measured using dual-energy X-ray absorptiometry (DXA) at follow-ups 1 through 3 at lumbar spine (LS) and femoral neck (FN). We used the Light Gradient Boosting Machine (LightGBM) to identify the osteoporosis (OP)-related proteomic features. The relationships between serum proteins and BMD in the two cohorts were estimated by linear mixed-effects model (LMM). Meta-analysis was then performed to explore the combined associations. We identified 53 proteins associated with osteoporosis using LightGBM, and a meta-analysis showed that 22 of these proteins illuminated a significant correlation with BMD (p < 0.05). The most common proteins among them were PHLD, SAMP, PEDF, HPTR, APOA1, SHBG, CO6, A2MG, CBPN, RAIN APOD, and THBG. The identified proteins were used to generate the biological age (BA) of bone. Each 1 SD-year increase in KDM-Proage was associated with higher risk of LS-OP (hazard ratio [HR], 1.25; 95% CI, 1.14-1.36, p = 4.96 × 10-06 ), and FN-OP (HR, 1.13; 95% CI, 1.02-1.23, p = 9.71 × 10-03 ). The findings uncovered that the apolipoproteins, zymoproteins, complements, and binding proteins presented new mechanistic insights into osteoporosis. Serum proteomics could be a crucial indicator for evaluating bone aging.

Voxel-wise mapping of DCE-MRI time-intensity-curve profiles enables visualizing and quantifying hemodynamic heterogeneity in breast lesions.

OBJECTIVES: To propose a novel model-free data-driven approach based on the voxel-wise mapping of DCE-MRI time-intensity-curve (TIC) profiles for quantifying and visualizing hemodynamic heterogeneity and to validate its potential clinical applications. MATERIALS AND METHODS: From December 2018 to July 2022, 259 patients with 325 pathologically confirmed breast lesions who underwent breast DCE-MRI were retrospectively enrolled. Based on the manually segmented breast lesions, the TIC of each voxel within the 3D whole lesion was classified into 19 subtypes based on wash-in rate (nonenhanced, slow, medium, and fast), wash-out enhancement (persistent, plateau, and decline), and wash-out stability (steady and unsteady), and the composition ratio of these 19 subtypes for each lesion was calculated as a new feature set (type-19). The three-type TIC classification, semiquantitative parameters, and type-19 features were used to build machine learning models for identifying lesion malignancy and classifying histologic grades, proliferation status, and molecular subtypes. RESULTS: The type-19 feature-based model significantly outperformed models based on the three-type TIC method and semiquantitative parameters both in distinguishing lesion malignancy (respectively; AUC = 0.875 vs. 0.831, p = 0.01 and 0.875vs. 0.804, p = 0.03), predicting tumor proliferation status (AUC = 0.890 vs. 0.548, p = 0.006 and 0.890 vs. 0.596, p = 0.020), but not in predicting histologic grades (p = 0.820 and 0.970). CONCLUSION: In addition to conventional methods, the proposed computational approach provides a novel, model-free, data-driven approach to quantify and visualize hemodynamic heterogeneity. CLINICAL RELEVANCE STATEMENT: Voxel-wise intra-lesion mapping of TIC profiles allows for visualization of hemodynamic heterogeneity and its composition ratio for differentiation of malignant and benign breast lesions. KEY POINTS: • Voxel-wise TIC profiles were mapped, and their composition ratio was compared between various breast lesions. • The model based on the composition ratio of voxel-wise TIC profiles significantly outperformed the three-type TIC classification model and the semiquantitative parameters model in lesion malignancy differentiation and tumor proliferation status prediction in breast lesions. • This novel, data-driven approach allows the intuitive visualization and quantification of the hemodynamic heterogeneity of breast lesions.

Comparing a new multimorbidity index with other multimorbidity measures for predicting disability trajectories.

BACKGROUND: The optimal multimorbidity measures for predicting disability trajectories are not universally agreed upon. We developed a multimorbidity index among middle-aged and older community-dwelling Chinese adults and compare its predictive ability of disability trajectories with other multimorbidity measures. METHODS: This study included 17,649 participants aged ≥50 years from the China Health and Retirement Longitudinal Survey 2011-2018. Two disability trajectory groups were estimated using the total disability score differences calculated between each follow-up visit and baseline. A weighted index was constructed using logistic regression models for disability trajectories based on the training set (70 %). The index and the condition count were used, along with the pattern identified by the latent class analysis to measure multimorbidity at baseline. Logistic regression models were used in the training set to examine associations between each multimorbidity measure and disability trajectories. C-statistics, integrated discrimination improvements, and net reclassification indices were applied to compare the performance of different multimorbidity measures in predicting disability trajectories in the testing set (30 %). RESULTS: In the newly developed multimorbidity index, the weights of the chronic conditions varied from 1.04 to 2.55. The multimorbidity index had a higher predictive performance than the condition count. The condition count performed better than the multimorbidity pattern in predicting disability trajectories. LIMITATION: Self-reported chronic conditions. CONCLUSIONS: The multimorbidity index may be considered an ideal measurement in predicting disability trajectories among middle-aged and older community-dwelling Chinese adults. The condition count is also suggested due to its simplicity and superior predictive performance.

Laparoscopic radical surgery for locally advanced T4 transverse colon cancer and prognostic factors analysis: Evidence from multi-center databases.

The safety and efficacies of laparoscopic radical procedures are still controversial for locally advanced pathological T4 (pT4) TCC (transverse colon cancer). Therefore, the aim of this study is to evaluate the oncologic and perioperative outcomes and to recognize the prognostic factors in radical resection for pT4 TCC derived from multi-center databases. 314 patients with TCC who underwent radical resection between January 2004 and May 2017, including 139 laparoscopic resections and 175 open resections, were extracted from multicenter databases. Oncological as well as perioperative outcomes were investigated. The baseline characteristics of the 2 groups did not differ significantly. Nevertheless, the laparoscopic technique was found to be linked with a significantly longer duration of surgery (208.96 vs 172.89 minutes, P = .044) and a significantly shorter postoperative hospital stay (12.23 vs 14.48 days, P = .014) when compared to the conventional open approach. In terms of oncological outcomes, lymph node resection (16.10 vs 13.66, P = .886), 5-year overall survival (84.7% vs 82.7%, P = .393), and disease-free survival (82.7% vs 83.9%, P = .803) were similar between the 2 approaches. Based on multivariate analysis, it was determined that differentiation and N classification were both independent prognostic factors for overall survival. However, it was found that only N classification was an independent prognostic factor for disease-free survival. These findings underscore the significance of differentiation and N classification as key determinants of patient outcomes in this context. Overall, the laparoscopic approach may offer advantages in terms of shorter hospital stays, while maintaining comparable oncological outcomes. Laparoscopic radical procedure can gain a couple of short-term benefits without reducing long-term oncological survival for patients with pT4 TCC.

Engineering contact curved interface with high-electronic-state active sites for high-performance potassium-ion batteries.

Potassium-ion batteries (PIBs) have attracted ever-increasing interest due to the abundant potassium resources and low cost, which are considered a sustainable energy storage technology. However, the graphite anodes employed in PIBs suffer from low capacity and sluggish reaction kinetics caused by the large radius of potassium ions. Herein, we report nitrogen-doped, defect-rich hollow carbon nanospheres with contact curved interfaces (CCIs) on carbon nanotubes (CNTs), namely CCI-CNS/CNT, to boost both electron transfer and potassium-ion adsorption. Density functional theory calculations validate that engineering CCIs significantly augments the electronic state near the Fermi level, thus promoting electron transfer. In addition, the CCIs exhibit a pronounced affinity for potassium ions, promoting their adsorption and subsequently benefiting potassium storage. As a result, the rationally designed CCI-CNS/CNT anode shows remarkable cyclic stability and rate capability. This work provides a strategy for enhancing the potassium storage performance of carbonaceous materials through CCI engineering, which can be further extended to other battery systems.

Early-life exposure to the Great Chinese Famine and gut microbiome disruption across adulthood for type 2 diabetes: three population-based cohort studies.

BACKGROUND: The early life stage is critical for the gut microbiota establishment and development. We aimed to investigate the lifelong impact of famine exposure during early life on the adult gut microbial ecosystem and examine the association of famine-induced disturbance in gut microbiota with type 2 diabetes. METHODS: We profiled the gut microbial composition among 11,513 adults (18-97 years) from three independent cohorts and examined the association of famine exposure during early life with alterations of adult gut microbial diversity and composition. We performed co-abundance network analyses to identify keystone taxa in the three cohorts and constructed an index with the shared keystone taxa across the three cohorts. Among each cohort, we used linear regression to examine the association of famine exposure during early life with the keystone taxa index and assessed the correlation between the keystone taxa index and type 2 diabetes using logistic regression adjusted for potential confounders. We combined the effect estimates from the three cohorts using random-effects meta-analysis. RESULTS: Compared with the no-exposed control group (born during 1962-1964), participants who were exposed to the famine during the first 1000 days of life (born in 1959) had consistently lower gut microbial alpha diversity and alterations in the gut microbial community during adulthood across the three cohorts. Compared with the no-exposed control group, participants who were exposed to famine during the first 1000 days of life were associated with consistently lower levels of keystone taxa index in the three cohorts (pooled beta - 0.29, 95% CI - 0.43, - 0.15). Per 1-standard deviation increment in the keystone taxa index was associated with a 13% lower risk of type 2 diabetes (pooled odds ratio 0.87, 95% CI 0.80, 0.93), with consistent results across three individual cohorts. CONCLUSIONS: These findings reveal a potential role of the gut microbiota in the developmental origins of health and disease (DOHaD) hypothesis, deepening our understanding about the etiology of type 2 diabetes.

Effectiveness and safety of interspinous spacer versus decompressive surgery for lumbar spinal stenosis: A meta-analysis of randomized controlled trials.

STUDY DESIGN: A meta-analysis of randomized controlled trials. OBJECTIVE: Our meta-analysis was conducted to investigate whether interspinous spacer (IS) results in better performance for patients with lumbar spinal stenosis (LSS) when compared with decompressive surgery (DS). BACKGROUND DATA: DS and IS are common surgeries for the treatment of LSS. However, controversy remains as to whether the IS is superior to DS. METHODS: We comprehensively searched PubMed, EMBASE, and Cochrane Central Register of Controlled Trials for prospective randomized controlled trials that compared IS versus DS for LSS. The retrieved results were last updated on July 30, 2023. RESULTS: Eight studies involving 852 individuals were included in the meta-analysis. The pooled data indicated that IS was superior to DS considering shorter operation time (P = .003), lower dural violation rate (P = .002), better Zurich Claudication Questionnaire Physical function score (P = .03), and smaller foraminal height decrease (P = .004), but inferior to DS considering the higher rate of reoperation (P < .0001). There was no significant difference between the 2 groups regarding hospital stay (P = .26), blood loss (P = .23), spinous process fracture (P = .09), disc height decrease (P = .87), VAS leg pain score (P = .43), VAS back pain score (P = .26), Oswestry Disability Index score (P = .08), and Zurich Claudication Questionnaire symptom severity (P = .50). CONCLUSIONS: In summary, we considered that IS had similar effects with DS in hospital stay, blood loss, spinous process fracture, disc height decrease, VAS score, Oswestry Disability Index score, and Zurich Claudication Questionnaire Symptom severity, and was better in some indices such as operation time, dural violation, Zurich Claudication Questionnaire Physical function, and foraminal height decrease than DS. However, due to the higher rate of reoperation in the IS group, we considered that both IS and DS were acceptable strategies for treating LSS. As a novel technique, further well-designed studies with longer-term follow-up are needed to evaluate the effectiveness and safety of IS.

Dietary intake and serum levels of copper and zinc and risk of hepatocellular carcinoma: A matched case-control study.

BACKGROUND: Copper and zinc are involved in the development of multiple malignancies; yet, epidemiological evidence on hepatocellular carcinoma (HCC) is limited. This study aimed to investigate the association between dietary intake and serum levels of copper and zinc with the risk of HCC. METHODS: A total of 434 case-control pairs matched for sex and age (±1 year) were included in this study. Cases with newly diagnosed HCC were from the Guangdong Liver Cancer Cohort (GLCC) study, and healthy controls were from the Guangzhou Nutrition and Health Study (GNHS). A semi-quantitative 79-item food frequency questionnaire (FFQ) was used to assess habitual dietary intakes of copper and zinc. Serum levels of copper and zinc were measured by using inductively coupled plasma mass spectrometry. The copper (Cu)/ zinc (Zn) ratio was computed by dividing copper levels by zinc levels. Conditional logistic regression models were performed to calculate the odds ratio (OR) and 95% confidence intervals (CI) for per 1 standard deviation increase (per-SD increase) in copper and zinc levels. RESULTS: Higher dietary intake (ORper-SD increase = 0.65, 95% CI: 0.44, 0.96, Ptrend = 0.029) and serum levels of zinc (ORper-SD increase = 0.11, 95% CI: 0.04, 0.30, Ptrend <0.001) were both associated with a lower risk of HCC. Subgroup analyses showed that the inverse association was only pronounced in men but not in women (Pinteraction = 0.041 for dietary zinc intake and 0.010 for serum zinc levels). Serum copper levels (ORper-SD increase = 2.05, 95% CI: 1.39, 3.03, Ptrend = 0.020) and serum Cu/Zn ratio (ORper-SD increase = 6.53, 95% CI: 2.52, 16.92, Ptrend<0.001) were positively associated with HCC risk, while dietary copper intake and dietary Cu/Zn ratio were not associated with HCC risk. CONCLUSION: Zinc may be a protective factor for HCC, especially among men, but the effects of copper on HCC risk are not clear.

SNHG3/WISP2 Axis Promotes Hela Cell Migration and Invasion via Activating Wnt/ß-Catenin Signaling.

BACKGROUND/AIM: Cervical cancer (CC) poses a significant threat to women's health and has a relatively poor prognosis due to local invasion and metastasis. It is, therefore, crucial to elucidate the molecular mechanisms of CC metastasis. SNHG3 has been implicated in various tumor metastasis processes, but its involvement in CC has not been thoroughly studied. Our study aimed to investigate the role of SNHG3 in metastasis and elucidate its underlying mechanisms in CC. MATERIALS AND METHODS: LncRNA SNHG3 expression in CC tissues was analyzed using TCGA and GSE27469 databases. Normal cervical epithelial cells and CC cell lines were used to detect mRNA expression of SNHG3 via quantitative reverse transcription polymerase chain reaction (qRT-PCR). With RNA interference (RNAi) technology, antisense oligonucleotides (ASO) can act on HeLa cells to knockdown target gene expression. The influence of SNHG3 on cell migration and invasion were determined by wound healing and transwell assays. Transcriptome sequencing (RNA-seq) was used to seek abnormally expressed genes between SNHG3 knockdown cells and control cells. The expressions of epithelial-mesenchymal transition (EMT) and Wnt/ß-catenin signaling related proteins were detected using western blot. RESULTS: SNHG3 was obviously up-regulated in CC tissues and cell lines, and ectopic expression of SNHG3 was associated with lymph node metastasis of CC. Knockdown of SNHG3 significantly inhibited cell migration and invasion in CC. Further molecular mechanism studies showed that SNHG3 knockdown could down-regulate the expression of WNT1 Inducible Signaling Pathway Protein 2 (WISP2) so as to inhibit the activation of the Wnt/ß-catenin signaling pathway, and regulated the expression of EMT-related markers, that promoted the protein expression of E-cadherin, as well as decreased the expression of N-cadherin and vimentin. CONCLUSION: SNHG3 appears to exert a pro-metastatic effect in CC, as evidenced by inhibition of cell migration and invasion upon SNHG3 knockdown. EMT also appears to be attenuated. Of interest is the down-regulation of WISP2 following SNHG3 knockdown leads to the inactivation of the Wnt/ß-catenin signaling pathway.

Bio-inspired nanocomposite coatings on orthodontic archwires with corrosion resistant and antibacterial properties.

The corrosion resistance and antibacterial properties of fixed orthodontic devices are insufficient in the complex oral cavity, which delays tooth movement and causes enamel demineralization. To overcome the challenges, this research constructs a series of polydopamine-graphene oxide (PDA-GO) nanocoatings on representative NiTi archwires via self-assembly. The morphology, chemical structure, and multifunctional properties of coatings showed tunability dependent on the PDA/GO ratio. Optimized PDA-GO coatings with uniform and dense characteristics prolonged the diffusion path for the corrosive medium and reduced Ni dissolution in NiTi alloys. Meanwhile, the applied coatings endowed NiTi alloys with antibacterial activity against Streptococcus mutans due to the surface structures and inherent properties of PDA-GO. In vitro cytotoxicity tests further verified their good biocompatibility. This bio-inspired nanocomposite coating provides a practical reference for modification of dental metal surfaces to better behave in the intraoral environment.

Dietary protein intake and changes in muscle mass measurements in community-dwelling middle-aged and older adults: A prospective cohort study.

BACKGROUND & AIMS: Increasing dietary protein intake can be an efficient strategy to prevent sarcopenia. Nevertheless, due to the discrepancy in the population and their dietary pattern, evidence suggested the effects of dietary protein amount or source on sarcopenia prevention varies. This prospective cohort study investigated the correlation between dietary protein intakes or sources and changes in muscle mass measurements. Additionally, the study explored the link between dietary protein and the prevalence of sarcopenia. METHODS: Participants aged 40 to 75 were from Guangzhou Nutrition and Health Study (GNHS) 2011-2013 and returned in 2014-2017. Validated 79-item food frequency questionnaires were applied to calculate the amount of total, animal, and plant protein intakes and animal-to-plant protein ratio (APR). The body composition was examined by dual-energy x-ray absorptiometry (DXA) to calculate the appendicular lean mass (ALM) and its index (ASMI). Sarcopenia was diagnosed based on the 2019 Asia Working Group of Sarcopenia's criteria. ANCOVA was utilized to compare the differences of Δ ALM and Δ ASMI across the quartiles of the dietary protein, and linear regression was employed to examine dose-response associations. Multilinear mixed-effect models were employed to evaluate whether protein intake relates to annual changes in ALM and ASMI. Multivariable logistic regressions were performed to analyze the associations between dietary protein and sarcopenia. RESULTS: In total, 2709 participants during the 3.2-year follow-up period were considered eligible for analysis. Higher dietary protein intakes (total, animal, plant) in both sexes could preserve more ALM and ASMI in a dose-response manner (all P-trend < 0.05). The annual estimated preservations of ASMI were greater in the highest dietary protein intakes (total, animal, plant) quartile than the lowest (0.05-0.13 kg/m2/y, all P < 0.05). In women, the risk of sarcopenia was reduced by 35%-50 % in the highest protein intake (total, animal, plant) quartile than the lowest. The APR did not display any significant associations. CONCLUSIONS: Higher dietary protein intake, regardless of animal or plant sources, is associated with less muscle loss and a lower prevalence of sarcopenia in middle-aged and older Chinese, particularly women. GOV IDENTIFIER: NCT03179657.

The associations of erythrocyte membrane polyunsaturated fatty acids with skeletal muscle loss: A prospective cohort study.

BACKGROUND & AIMS: Polyunsaturated fatty acids (PUFAs) may play a vital role in maintaining skeletal muscle mass in the aged population. This study investigated the longitudinal relationship between the concentrations of erythrocyte membrane PUFAs and age-related changes in skeletal muscle mass over an average 6.5 years of follow-up in a Chinese middle-aged and older adult population. METHODS: A total of 1494 participants aged 57.4 ± 4.7 years were included in this study. Skeletal muscle mass was determined using dual-energy X-ray absorptiometry. Per year percent changes in the skeletal muscle index (Δ% SMI), appendicular skeletal muscle index (Δ% ASMI), and total body lean mass index (Δ% TBLMI) from baseline were calculated. Concentrations of total and individual cis-n-3 and cis-n-6 PUFAs of the erythrocyte membrane were determined using gas-liquid chromatography. RESULTS: Fully adjusted linear regression models showed that per unit increases in the concentrations of C18:2 n-6, C20:4 n-6, C22:4 n-6, and total n-6 PUFAs resulted in increases of 0.022%-0.155 % in the Δ% SMI (P for linearity: <0.001-0.006). Restricted cubic spline analysis revealed an inverted U-shaped relationship between the concentrations of C20:2 n-6, C22:5 n-3, C22:6 n-3, and total n-3 PUFAs and the Δ% SMI (P for non-linearity: <0.001-0.036). In addition, an inverted U-shaped curve was also detected for the relationships of the linoleic acid/α-linolenic acid ratio (P for non-linearity = 0.010) and n-6/n-3 PUFA ratio (P for non-linearity = 0.013) with the Δ% SMI, with the Δ% SMI peaking at respective ratios of 124.96 and 3.69. Similar associations were revealed by the Bayesian kernel machine regression model. No interaction effect was detected between the individual PUFAs for the Δ% SMI in the bivariate exposure-response analysis. Overall, similar results were observed for the Δ% ASMI and Δ% TBLMI. CONCLUSIONS: The associations between different individual PUFAs and age-related muscle loss in middle-aged and older adults may be different. Our results suggest that high concentrations of erythrocyte membrane n-6 PUFAs may be correlated with less skeletal muscle mass loss, whereas extremely high concentrations of n-3 PUFAs may be correlated with more muscle loss.

Comprehensive analysis of Cuproplasia and immune microenvironment in lung adenocarcinoma.

Background: Trace elements such as copper are essential for human health. Recently the journal Nat Rev Cancer has put forward the concept of Cuproplasia, a way of promoting tumor growth through reliance on copper. We attempted to conduct a comprehensive analysis of Cuproplasia-related genes in lung adenocarcinoma (LUAD) to explore the mechanism of action of Cuproplasia-related genes in LUAD. Method: Transcriptome data and clinical information of LUAD were obtained from TCGA-LUAD and GSE31210, and prognostic models of Cuproplasia-related genes were constructed and verified by regression analysis of GSVA, WGCNA, univariate COX and lasso. The signal pathways affected by Cuproplasia-related genes were analyzed by GO, KEGG and hallmarK pathway enrichment methods. Five immunocell infiltration algorithms and IMVIGOR210 data were used to analyze immune cell content and immunotherapy outcomes in the high-low risk group. Results: In the results of WGCNA, BROWN and TURQUOISE were identified as modules closely related to Cuproplasia score. In the end, lasso regression analysis established a Cuproplasia-related signature (CRS) based on 24 genes, and the prognosis of high-risk populations was worse in TCGA-LUAD and GSE31210 datasets. The enrichment analysis showed that copper proliferation was mainly through chromosome, cell cycle, dna replication, g2m checkpoint and other pathways. Immunoinfiltration analysis showed that there were differences in the content of macrophages among the four algorithms. And IMVIGOR210 found that the lower the score, the more effective the immunotherapy was. Conclusion: The Cuproplasia related gene can be used to predict the prognosis and immunotherapy outcome of LUAD patients, and may exert its effect by affecting chromosome-related pathways and macrophages.

Cohort Profile: Guangzhou Nutrition and Health Study (GNHS): A Population-Based Multi-Omics Study.

BACKGROUND: The Guangzhou Nutrition and Health Study (GNHS) aims to assess the determinants of metabolic disease in nutritional aspects, as well as other environmental and genetic factors, and explore possible biomarkers and mechanisms with multi-omics integration. METHODS: The population-based sample of adults in Guangzhou, China (baseline: 40-83 years old; n = 5118) was followed up about every 3 years. All will be tracked via on-site follow-up and health information systems. We assessed detailed information on lifestyle factors, physical activities, dietary assessments, psychological health, cognitive function, body measurements, and muscle function. Instrument tests included dual-energy X-ray absorptiometry scanning, carotid artery and liver ultrasonography evaluations, vascular endothelial function evaluation, upper-abdomen and brain magnetic resonance imaging, and 14-d real-time continuous glucose monitoring tests. We also measured multi-omics, including host genome-wide genotyping, serum metabolome and proteome, gut microbiome (16S rRNA sequencing, metagenome, and internal transcribed spacer 2 sequencing), and fecal metabolome and proteome. RESULTS: The baseline surveys were conducted from 2008 to 2015. Now, we have completed 3 waves. The 3rd and 4th follow-ups have started but have yet to end. A total of 5118 participants aged 40-83 took part in the study. The median age at baseline was approximately 59.0 years and the proportion of female participants was about 69.4%. Among all the participants, 3628 (71%) completed at least one on-site follow-up with a median duration of 9.48 years. CONCLUSION: The cohort will provide data that have been influential in establishing the role of nutrition in metabolic diseases with multi-omics.

Classification of attention deficit/hyperactivity disorder based on EEG signals using a EEG-Transformer model∗.

Objective. Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in adolescents that can seriously impair a person's attention function, cognitive processes, and learning ability. Currently, clinicians primarily diagnose patients based on the subjective assessments of the Diagnostic and Statistical Manual of Mental Disorders-5, which can lead to delayed diagnosis of ADHD and even misdiagnosis due to low diagnostic efficiency and lack of well-trained diagnostic experts. Deep learning of electroencephalogram (EEG) signals recorded from ADHD patients could provide an objective and accurate method to assist physicians in clinical diagnosis.Approach. This paper proposes the EEG-Transformer deep learning model, which is based on the attention mechanism in the traditional Transformer model, and can perform feature extraction and signal classification processing for the characteristics of EEG signals. A comprehensive comparison was made between the proposed transformer model and three existing convolutional neural network models.Main results. The results showed that the proposed EEG-Transformer model achieved an average accuracy of 95.85% and an average AUC value of 0.9926 with the fastest convergence speed, outperforming the other three models. The function and relationship of each module of the model are studied by ablation experiments. The model with optimal performance was identified by the optimization experiment.Significance. The EEG-Transformer model proposed in this paper can be used as an auxiliary tool for clinical diagnosis of ADHD, and at the same time provides a basic model for transferable learning in the field of EEG signal classification.