Endoplasmic reticulum stress and autophagy in cerebral ischemia/reperfusion injury: PERK as a potential target for intervention.

JOURNAL/nrgr/04.03/01300535-202505000-00028/figure1/v/2024-07-28T173839Z/r/image-tiff Several studies have shown that activation of unfolded protein response and endoplasmic reticulum (ER) stress plays a crucial role in severe cerebral ischemia/reperfusion injury. Autophagy occurs within hours after cerebral ischemia, but the relationship between ER stress and autophagy remains unclear. In this study, we established experimental models using oxygen-glucose deprivation/reoxygenation in PC12 cells and primary neurons to simulate cerebral ischemia/reperfusion injury. We found that prolongation of oxygen-glucose deprivation activated the ER stress pathway protein kinase-like endoplasmic reticulum kinase (PERK)/eukaryotic translation initiation factor 2 subunit alpha (eIF2α)-activating transcription factor 4 (ATF4)-C/EBP homologous protein (CHOP), increased neuronal apoptosis, and induced autophagy. Furthermore, inhibition of ER stress using inhibitors or by siRNA knockdown of the PERK gene significantly attenuated excessive autophagy and neuronal apoptosis, indicating an interaction between autophagy and ER stress and suggesting PERK as an essential target for regulating autophagy. Blocking autophagy with chloroquine exacerbated ER stress-induced apoptosis, indicating that normal levels of autophagy play a protective role in neuronal injury following cerebral ischemia/reperfusion injury. Findings from this study indicate that cerebral ischemia/reperfusion injury can trigger neuronal ER stress and promote autophagy, and suggest that PERK is a possible target for inhibiting excessive autophagy in cerebral ischemia/reperfusion injury.

metaExpertPro: a computational workflow for metaproteomics spectral library construction and data-independent acquisition mass spectrometry data analysis.

Analysis of large-scale data-independent acquisition mass spectrometry (DIA-MS) metaproteomics data remains a computational challenge. Here, we present a computational pipeline called metaExpertPro for metaproteomics data analysis. This pipeline encompasses spectral library generation using data-dependent acquisition MS (DDA-MS), protein identification and quantification using DIA-MS, functional and taxonomic annotation, as well as quantitative matrix generation for both microbiota and hosts. By integrating FragPipe and DIA-NN, metaExpertPro offers compatibility with both Orbitrap and timsTOF MS instruments. To evaluate the depth and accuracy of identification and quantification, we conducted extensive assessments using human fecal samples and benchmark tests. Performance tests conducted on human fecal samples indicated that metaExpertPro quantified an average of 45,000 peptides in a 60-minute diaPASEF injection. Notably, metaExpertPro outperformed three existing software tools by characterizing a higher number of peptides and proteins. Importantly, metaExpertPro maintained a low factual false discovery rate (FDR) of approximately 5% for protein groups across four benchmark tests. Applying a filter of five peptides per genus, metaExpertPro achieved relatively high accuracy (F-score = 0.67-0.90) in genus diversity and showed a high correlation (rSpearman = 0.73-0.82) between the measured and true genus relative abundance in benchmark tests. Additionally, the quantitative results at the protein, taxonomy, and function levels exhibited high reproducibility and consistency across the commonly adopted public human gut microbial protein databases IGC and UHGP. In a metaproteomic analysis of dyslipidemia (DLP) patients, metaExpertPro revealed characteristic alterations in microbial functions and potential interactions between the microbiota and the host.

The role of dietary modification in the prevention and management of metabolic dysfunction-associated fatty liver disease: An international multidisciplinary expert consensus.

Metabolic dysfunction-associated fatty liver disease (MAFLD) or metabolic dysfunction-associated steatotic liver disease (MASLD), has become the leading cause of chronic liver disease worldwide. Optimal dietary intervention strategies for MAFLD are not standardized. This study aimed to achieve consensus on prevention of MAFLD through dietary modification. A multidisciplinary panel of 55 international experts, including specialists in hepatology, gastroenterology, dietetics, endocrinology and other medical specialties from six continents collaborated in a Delphi-based consensus development process. The consensus statements covered aspects ranging from epidemiology to mechanisms, management, and dietary recommendations for MAFLD. The recommended dietary strategies emphasize adherence to a balanced diet with controlled energy intake and personalized nutritional interventions, such as calorie restriction, high-protein, or low-carbohydrate diets. Specific dietary advice encouraged increasing the consumption of whole grains, plant-based proteins, fish, seafood, low-fat or fat-free dairy products, liquid plant oils, and deeply colored fruits and vegetables. Concurrently, it advised reducing the intake of red and processed meats, saturated and trans fats, ultra-processed foods, added sugars, and alcohol. Additionally, maintaining the Mediterranean or DASH diet, minimizing sedentary behavior, and engaging in regular physical activity are recommended. These consensus statements lay the foundation for customized dietary guidelines and proposing avenues for further research on nutrition and MAFLD.

Erythrocyte Very Long-Chain Saturated Fatty Acids, Gut Microbiota-Bile Acid Axis, and Incident Coronary Artery Disease in Adults: A Prospective Cohort Study.

BACKGROUND: Prior research has highlighted inverse associations between concentrations of circulating very long-chain saturated fatty acids (VLCSFAs) and coronary artery disease (CAD). However, the intricate links involving VLCSFAs, gut microbiota, and bile acids remain underexplored. OBJECTIVES: This study examined the association of erythrocyte VLCSFAs with CHD incidence, focusing on the mediating role of gut microbiota and fecal bile acids. METHODS: This 10-y prospective study included 2383 participants without CHD at baseline. Erythrocyte VLCSFAs [arachidic acid (C20:0), behenic acid (C22:0), and lignoceric acid (C24:0)] were measured using gas chromatography at baseline, and 274 CHD incidents were documented in triennial follow-ups. Gut microbiota in 1744 participants and fecal bile acid metabolites in 945 participants were analyzed using 16S ribosomal ribonucleic acid sequencing and ultra-performance liquid chromatography-tandem mass spectrometry at middle-term. RESULTS: The multivariable-adjusted hazard ratios (95% confidence interval) for CHD incidence in highest compared with lowest quartiles were 0.87 (0.61, 1.25) for C20:0, 0.63 (0.42, 0.96) for C22:0, 0.59 (0.41, 0.85) for C24:0, and 0.57 (0.39, 0.83) for total VLCSFAs. Participants with higher total VLCSFA concentrations exhibited increased abundances of Holdemanella, Coriobacteriales Incertae Sedis spp., Ruminococcaceae UCG-005 and UCG-010, and Lachnospiraceae ND3007 group. These 5 genera generated overlapping differential microbial scores (ODMSs) that accounted for 11.52% of the total VLCSFAs-CHD association (Pmediation = 0.018). Bile acids tauro_α_ and tauro_ß_muricholic acid were inversely associated with ODMS and positively associated with incident CHD. Opposite associations were found for glycolithocholic acid and glycodeoxycholic acid. Mediation analyses indicated that glycolithocholic acid, glycodeoxycholic acid, and tauro_α_ and tauro_ß_muricholic acid explained 56.40%, 35.19%, and 26.17% of the ODMS-CHD association, respectively (Pmediation = 0.002, 0.008, and 0.020). CONCLUSIONS: Elevated erythrocyte VLCSFAs are inversely associated with CHD risk in the Chinese population, with gut microbiota and fecal bile acid profiles potentially mediating this association. The identified microbiota and bile acid metabolites may serve as potential intervention targets in future studies. This trial was registered at www. CLINICALTRIALS: gov as NCT03179657.

Two-week continuous glucose monitoring-derived metrics and degree of hepatic steatosis: a cross-sectional study among Chinese middle-aged and elderly participants.

BACKGROUND: Continuous glucose monitoring (CGM) devices provide detailed information on daily glucose control and glycemic variability. Yet limited population-based studies have explored the association between CGM metrics and fatty liver. We aimed to investigate the associations of CGM metrics with the degree of hepatic steatosis. METHODS: This cross-sectional study included 1180 participants from the Guangzhou Nutrition and Health Study. CGM metrics, covering mean glucose level, glycemic variability, and in-range measures, were separately processed for all-day, nighttime, and daytime periods. Hepatic steatosis degree (healthy: n = 698; mild steatosis: n = 242; moderate/severe steatosis: n = 240) was determined by magnetic resonance imaging proton density fat fraction. Multivariate ordinal logistic regression models were conducted to estimate the associations between CGM metrics and steatosis degree. Machine learning models were employed to evaluate the predictive performance of CGM metrics for steatosis degree. RESULTS: Mean blood glucose, coefficient of variation (CV) of glucose, mean amplitude of glucose excursions (MAGE), and mean of daily differences (MODD) were positively associated with steatosis degree, with corresponding odds ratios (ORs) and 95% confidence intervals (CIs) of 1.35 (1.17, 1.56), 1.21 (1.06, 1.39), 1.37 (1.19, 1.57), and 1.35 (1.17, 1.56) during all-day period. Notably, lower daytime time in range (TIR) and higher nighttime TIR were associated with higher steatosis degree, with ORs (95% CIs) of 0.83 (0.73, 0.95) and 1.16 (1.00, 1.33), respectively. For moderate/severe steatosis (vs. healthy) prediction, the average area under the receiver operating characteristic curves were higher for the nighttime (0.69) and daytime (0.66) metrics than that of all-day metrics (0.63, P < 0.001 for all comparisons). The model combining both nighttime and daytime metrics achieved the highest predictive capacity (0.73), with nighttime MODD emerging as the most important predictor. CONCLUSIONS: Higher CGM-derived mean glucose and glycemic variability were linked with higher steatosis degree. CGM-derived metrics during nighttime and daytime provided distinct and complementary insights into hepatic steatosis.

Mapping the gut microecological multi-omics signatures to serum metabolome and their impact on cardiometabolic health in elderly adults.

BACKGROUND: Mapping gut microecological features to serum metabolites (SMs) will help identify functional links between gut microbiome and cardiometabolic health. METHODS: This study encompassed 836-1021 adults over 9.7 year in a cohort, assessing metabolic syndrome (MS), carotid atherosclerotic plaque (CAP), and other metadata triennially. We analyzed mid-term microbial metagenomics, targeted fecal and serum metabolomics, host genetics, and serum proteomics. FINDINGS: Gut microbiota and metabolites (GMM) accounted for 15.1% overall variance in 168 SMs, with individual GMM factors explaining 5.65%-10.1%, host genetics 3.23%, and sociodemographic factors 5.95%. Specifically, GMM elucidated 5.5%-49.6% variance in the top 32 GMM-explained SMs. Each 20% increase in the 32 metabolite score (derived from the 32 SMs) correlated with 73% (95% confidence interval [CI]: 53%-95%) and 19% (95% CI: 11%-27%) increases in MS and CAP incidences, respectively. Among the 32 GMM-explained SMs, sebacic acid, indoleacetic acid, and eicosapentaenoic acid were linked to MS or CAP incidence. Serum proteomics revealed certain proteins, particularly the apolipoprotein family, mediated the relationship between GMM-SMs and cardiometabolic risks. INTERPRETATION: This study reveals the significant influence of GMM on SM profiles and illustrates the intricate connections between GMM-explained SMs, serum proteins, and the incidence of MS and CAP, providing insights into the roles of gut dysbiosis in cardiometabolic health via regulating blood metabolites. FUNDING: This study was jointly supported by the National Natural Science Foundation of China, Key Research and Development Program of Guangzhou, 5010 Program for Clinical Research of Sun Yat-sen University, and the 'Pioneer' and 'Leading goose' R&D Program of Zhejiang.

Landscape of the gut mycobiome dynamics during pregnancy and its relationship with host metabolism and pregnancy health.

OBJECTIVE: The remodelling of gut mycobiome (ie, fungi) during pregnancy and its potential influence on host metabolism and pregnancy health remains largely unexplored. Here, we aim to examine the characteristics of gut fungi in pregnant women, and reveal the associations between gut mycobiome, host metabolome and pregnancy health. DESIGN: Based on a prospective birth cohort in central China (2017 to 2020): Tongji-Huaxi-Shuangliu Birth Cohort, we included 4800 participants who had available ITS2 sequencing data, dietary information and clinical records during their pregnancy. Additionally, we established a subcohort of 1059 participants, which included 514 women who gave birth to preterm, low birthweight or macrosomia infants, as well as 545 randomly selected controls. In this subcohort, a total of 750, 748 and 709 participants had ITS2 sequencing data, 16S sequencing data and serum metabolome data available, respectively, across all trimesters. RESULTS: The composition of gut fungi changes dramatically from early to late pregnancy, exhibiting a greater degree of variability and individuality compared with changes observed in gut bacteria. The multiomics data provide a landscape of the networks among gut mycobiome, biological functionality, serum metabolites and pregnancy health, pinpointing the link between Mucor and adverse pregnancy outcomes. The prepregnancy overweight status is a key factor influencing both gut mycobiome compositional alteration and the pattern of metabolic remodelling during pregnancy. CONCLUSION: This study provides a landscape of gut mycobiome dynamics during pregnancy and its relationship with host metabolism and pregnancy health, which lays the foundation of the future gut mycobiome investigation for healthy pregnancy.

Cross-Sectional and Prospective Association of Serum 25-Hydroxyvitamin D with Gut Mycobiota during Pregnancy among Women with Gestational Diabetes.

SCOPE: Little is known about the effect of blood vitamin D status on the gut mycobiota (i.e., fungi), a crucial component of the gut microbial ecosystem. The study aims to explore the association between 25-hydroxyvitamin D [25(OH)D] and gut mycobiota and to investigate the link between the identified mycobial features and blood glycemic traits. METHODS AND RESULTS: The study examines the association between serum 25(OH)D levels and the gut mycobiota in the Westlake Precision Birth Cohort, which includes pregnant women with gestational diabetes mellitus (GDM). The study develops a genetic risk score (GRS) for 25(OH)D to validate the observational results. In both the prospective and cross-sectional analyses, the vitamin D is associated with gut mycobiota diversity. Specifically, the abundance of Saccharomyces is significantly lower in the vitamin D-sufficient group than in the vitamin D-deficient group. The GRS of 25(OH)D is inversely associated with the abundance of Saccharomyces. Moreover, the Saccharomyces is positively associated with blood glucose levels. CONCLUSION: Blood vitamin D status is associated with the diversity and composition of gut mycobiota in women with GDM, which may provide new insights into the mechanistic understanding of the relationship between vitamin D levels and metabolic health.

Magnetoencephalography-derived oscillatory microstate patterns across lifespan: the Cambridge centre for ageing and neuroscience cohort.

The aging brain represents the primary risk factor for many neurodegenerative disorders. Whole-brain oscillations may contribute novel early biomarkers of aging. Here, we investigated the dynamic oscillatory neural activities across lifespan (from 18 to 88 years) using resting Magnetoencephalography (MEG) in a large cohort of 624 individuals. Our aim was to examine the patterns of oscillation microstates during the aging process. By using a machine-learning algorithm, we identify four typical clusters of microstate patterns across different age groups and different frequency bands: left-to-right topographic MS1, right-to-left topographic MS2, anterior-posterior MS3 and fronto-central MS4. We observed a decreased alpha duration and an increased alpha occurrence for sensory-related microstate patterns (MS1 & MS2). Accordingly, theta and beta changes from MS1 & MS2 may be related to motor decline that increased with age. Furthermore, voluntary 'top-down' saliency/attention networks may be reflected by the increased MS3 & MS4 alpha occurrence and complementary beta activities. The findings of this study advance our knowledge of how the aging brain shows dysfunctions in neural state transitions. By leveraging the identified microstate patterns, this study provides new insights into predicting healthy aging and the potential neuropsychiatric cognitive decline.

[Research progress on induced hepatic stellate cell ferroptosis in prevention and treatment of liver fibrosis].

Liver fibrosis is a key pathological stage in the progression of chronic liver disease. If the disease is mistreated, it can further deteriorate into liver failure, which seriously affects the quality of life of patients and brings heavy medical costs. Hepatic stellate cell(HSC) activation triggers extracellular matrix(ECM) deposition, which plays an important driving role in liver fibrosis, and ferroptosis is an effective strategy to clear or reverse the activation of HSCs into a deactivated phenotype. Therefore, inhibiting the activation and proliferation of HSCs by regulating ferroptosis is the key to the treatment of this disease, so as to derive the prospect of inducing ferroptosis of HSCs(including RNA-binding proteins, non-coding RNA, chemicals, and active components of traditional Chinese medicine) to intervene in liver fibrosis. On this basis, this paper started from the activation of HSCs to induce ECM deposition and focused on summarizing the mechanism of inducing HSC ferroptosis in delaying the progression of liver fibrosis, so as to continuously enrich the clinical practice of liver fibrosis and provide a reference for subsequent basic research.

Gut microbiota-bile acid axis mediated the beneficial associations between dietary lignans and hyperuricemia: a prospective study.

Background: The escalating prevalence of hyperuricemia is emerging as a significant public health concern. The association between dietary lignans and hyperuricemia is yet to be fully elucidated. Our study aims to evaluate the relationships between dietary lignan intake and hyperuricemia among middle-aged and elderly Chinese individuals, with an additional focus on investigating the underlying mechanisms. Methods: Dietary lignan intake was measured using a validated Food Frequency Questionnaire in 3801 participants at the baseline. Among them, 2552 participants were included in the longitudinal study with a median follow-up of 10.5 years. The gut microbiota was analyzed by shotgun metagenome sequencing in 1789 participants, and the targeted fecal metabolome was determined in 987 participants using UPLC-MS/MS at the midpoint of follow-up. Results: The multivariable-adjusted HRs (95% CIs) for hyperuricemia incidence in the highest quartile (vs. the lowest quartile) of dietary intake of total lignans, matairesinol, pinoresinol, and secoisolariciresinol were 0.93 (0.78-1.10), 0.77 (0.66-0.90), 0.83 (0.70-0.97), and 0.85 (0.73-1.00), respectively. The gut microbial and fecal metabolic compositions were significantly different across the dietary lignan groups and the hyperuricemia groups. The beneficial associations between dietary lignans and hyperuricemia might be mediated by several gut microbes (e.g., Fusobacterium mortiferum and Blautia sp. CAG-257) and the downstream bile acid products (e.g., NorCA, glycochenodeoxycholic acid, and glycoursodeoxycholic acid). Conclusion: We found that dietary lignans were inversely associated with hyperuricemia incidence, and the gut microbiota-bile acid axis might mediate this association. Our findings provide new perspectives on precise therapeutic targets and underlying mechanisms for conditions associated with elevated uric acid.

Multi-trajectories of body mass index, waist circumference, gut microbiota, and incident dyslipidemia: a 27-year prospective study.

Background: Evidence is insufficient to establish a longitudinal association between combined trajectories of body mass index (BMI) and waist circumference (WC) and dyslipidemia. Our study aimed to explore the association between multi-trajectories of BMI and WC and incident dyslipidemia and identify microbiota and metabolite signatures of these trajectories. Methods: Stratified by sex, we used a group-based trajectory modeling approach to identify distinct multi-trajectories of BMI and WC among 10,678 participants from the China Health and Nutrition Survey over a 24-year period. For each sex, we examined the associations between these multi-trajectories (1991-2015) and the onset dyslipidemia (2018) using multivariable logistic regression adjusting for sociodemographic and lifestyles factors. We characterized the gut microbial composition and performed LASSO and logistic regression to identify gut microbial signatures associated with these multi-trajectories in males and females, respectively. Results: We identified four multi-trajectories of BMI and WC among both males and females: Normal (Group 1), BMI&WC normal increasing (Group 2), BMI&WC overweight increasing (Group 3), and BMI&WC obesity increasing (Group 4). Among males, Group 2 (OR: 2.10, 95% CI: 1.28-3.46), Group 3 (OR: 2.69, 95% CI: 1.56-4.63) and Group 4 (OR: 3.56, 95% CI: 1.85-6.83) had higher odds of developing dyslipidemia. However, among females, only those in Group 2 (OR: 1.54, 95% CI: 1.03-2.30) were more likely to develop dyslipidemia. In males, compared with Group 1, we observed lower alpha-diversity within Groups 2,3, and 4, and significant beta-diversity differences within Groups 3 and 4 (p 0.001). We also identified 3, 8, and 4 characteristic bacterial genera in male Groups 2, 3 and 4, and 2 genera in female Group 2. A total of 23, 25 and 10 differential metabolites were significantly associated with the above genera, except for Group 2 in males. Conclusions: The ascending combined trajectories of BMI and WC are associated with a higher risk of dyslipidemia, even with normal baseline levels, especially in males. Shared and unique gut microbial and metabolic signatures among these high-risk trajectories could enhance our understanding of the mechanisms connecting obesity to dyslipidemia.

Effects of Connectivity Isomerization on Electron Transport Through Thiophene Heterocyclic Molecular Junction.

Connectivity isomerization of the same aromatic molecular core with different substitution positions profoundly affects electron transport pathways and single-molecule conductance. Herein, we designed and synthesized all connectivity isomers of a thiophene (TP) aromatic ring substituted by two dihydrobenzo[b]thiophene (BT) groups with ethynyl spacers (m,n-TP-BT, (m,n = 2,3; 2,4; 2,5; 3,4)), to systematically probe how connectivity contributes to single-molecule conductance. Single-molecule conductance measurements using a scanning tunneling microscopy break junction (STM-BJ) technique show ∼12-fold change in conductance values, which follow an order of 10-4.83 G0 (2,4-TP-BT) < 10-4.78 G0 (3,4-TP-BT) < 10-4.06 G0 (2,3-TP-BT) < 10-3.75 G0 (2,5-TP-BT). Electronic structure analysis and theoretical simulations show that the connectivity isomerization significantly changes electron delocalization and HOMO-LUMO energy gaps. Moreover, the connectivity-dependent molecular structures lead to different quantum interference (QI) effects in electron transport, e.g., a strong destructive QI near E = EF leads the smallest conductance value for 2,4-TP-BT. This work proves a clear relationship between the connectivity isomerization and single-molecule conductance of thiophene heterocyclic molecular junctions for the future design of molecular devices.

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.

Dietary intake of plant- and animal-derived protein and incident cardiovascular diseases: the pan-European EPIC-CVD case-cohort study.

BACKGROUND: Epidemiological evidence suggests that a potential association between dietary protein intake and cardiovascular disease (CVD) may depend on the protein source, that is, plant- or animal-derived, but past research was limited and inconclusive. OBJECTIVES: To evaluate the association of dietary plant- or animal-derived protein consumption with risk of CVD, and its components ischemic heart disease (IHD) and stroke. METHODS: This analysis in the European Prospective Investigation into Cancer and Nutrition (EPIC)-CVD case-cohort study included 16,244 incident CVD cases (10,784 IHD and 6423 stroke cases) and 15,141 subcohort members from 7 European countries. We investigated the association of estimated dietary protein intake with CVD, IHD, and stroke (total, fatal, and nonfatal) using multivariable-adjusted Prentice-weighted Cox regression. We estimated isocaloric substitutions of replacing fats and carbohydrates with plant- or animal-derived protein and replacing food-specific animal protein with plant protein. Multiplicative interactions between dietary protein and prespecified variables were tested. RESULTS: Neither plant- nor animal-derived protein intake was associated with incident CVD, IHD, or stroke in adjusted analyses without or with macronutrient-specified substitution analyses. Higher plant-derived protein intake was associated with 22% lower total stroke incidence among never smokers [HR 0.78, 95% confidence intervals (CI): 0.62, 0.99], but not among current smokers (HR 1.08, 95% CI: 0.83, 1.40, P-interaction = 0.004). Moreover, higher plant-derived protein (per 3% total energy) when replacing red meat protein (HR 0.52, 95% CI: 0.31, 0.88), processed meat protein (HR 0.39, 95% CI: 0.17, 0.90), and dairy protein (HR 0.54, 95% CI: 0.30, 0.98) was associated with lower incidence of fatal stroke. CONCLUSION: Plant- or animal-derived protein intake was not associated with overall CVD. However, the association of plant-derived protein consumption with lower total stroke incidence among nonsmokers, and with lower incidence of fatal stroke highlights the importance of investigating CVD subtypes and potential interactions. These observations warrant further investigation in diverse populations with varying macronutrient intakes and dietary patterns.

Rapid detection of trace nitrobenzene in water via SERS using a portable Raman spectrometer.

Nitrobenzene is currently the most widely used explosive substance, and is known for its high toxicity and mutagenicity. It can cause severe environmental and water pollution, posing a risk to public health. Among various explosives analysis methods, surface-enhanced Raman spectroscopy (SERS) has the advantages of fast analysis speed, low detection cost, and easy operation, and has become one of the most promising analytical detection methods. Here, we present a portable and reliable sol-based SERS method for the detection of trace amounts of 2,4,6-trinitrotoluene (TNT) in different water bodies. The Meisenheimer complex formed by nitrobenzene and hydrazine hydrate can assemble on unmodified Au nanoparticles in a sol via Au-N bonds, enabling rapid detection of TNT in seawater, lake water, and tap water using a portable Raman spectrometer. Experimental results show that this SERS method can complete the detection within a few minutes and the detection sensitivity can reach 0.01 mg L-1, which is far lower than China's national standard of no more than 0.5 mg L-1. Furthermore, this method was also successfully applied to detect trace 2,4-dinitrotoluene (2,4-DNT) and picric acid (2,4,6-trinitrophenol) in water, demonstrating its strong applicability for on-site detection of nitrobenzene explosives.

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.

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.

Development and validation of a model for predicting the risk of prostate cancer.

BACKGROUND: Abnormal hematologic parameters before patients undergoing prostate biopsy play a pivotal role in guiding the surgical management of prostate cancer (PCa) incidence. This study aims to establish the first nomogram for predicting PCa risk for better surgical management. METHODS: We retrospectively reviewed and analyzed the data including basic information, preoperative hematologic parameters, and imaging examination of 540 consecutive patients who underwent transrectal ultrasound (TRUS)-guided prostate biopsy for elevated prostate-specific antigen (PSA) in our medical center between 2017 and 2021. Logistic regression analysis was used to determine the risk factors for PCa occurrence, and the nomogram was constructed to predict PCa occurrence. Finally, the data including 121 consecutive patients in 2022 were prospectively collected to further verify the results. RESULTS: In retrospective analyses, univariate and multivariate logistic analyses identified that three variables including age, diabetes, and De Ritis ratio (aspartate transaminase/alanine transaminase, AST/ALT) were determined to be significantly associated with PCa occurrence. A nomogram was constructed based on these variables for predicting the risk of PCa, and a satisfied predictive accuracy of the model was determined with a C-index of 0.765, supported by a prospective validation group with a C-index of 0.736. The Decision curve analysis showed promising clinical application. In addition, our results also showed that the De Ritis ratio was significantly correlated with the clinical stage of PCa patients, including T, N, and M stages, but insignificantly related to the Gleason score. CONCLUSIONS: The increased De Ritis ratio was significantly associated with the risk and clinical stage of PCa and this nomogram with good discrimination could effectively improve individualized surgical management for patient underdoing prostate biopsy.