Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

BackgroundBoth modified Suanzaoren Decoction and estazolam serve as effective treatments for chronic insomnia disorder （CID）. Default mode network （DMN） dysfunction is recognized as the primary pathophysiological mechanism underlying CID. However， it remains unclear whether the two treatments exert their therapeutic effects via convergent modulation of DMN functional connectivity. ObjectiveTo investigate the convergent remodeling characteristics of bidirectional effective connectivity （EC） of core DMN nodes with both the intra-network and the remaining whole-brain regions in CID patients with Yin-deficiency and fire-hyperactivity syndrome following the treatment with modified Suanzaoren Decoction or estazolam， so as to provide neuroimaging evidence for the convergent neural mechanisms underlying the therapeutic effects of both therapies in treating CID. MethodsEighty-two patients diagnosed with CID according to the International Classification of Sleep Disorder， third edition （ICSD-3） were consecutively recruited from the outpatient clinic of the Inner Mongolia Autonomous Region Mental Health Center from October 2020 to September 2023. Based on treatment preference， patients were assigned to receive a 6-week intervention in either the modified Suanzaoren Decoction group （n=52） or the estazolam group （n=30）. Ultimately， 66 patients completed follow-up assessments （modified Suanzaoren Decoction group， n=41； estazolam group， n=25）. All CID patients underwent resting-state functional magnetic resonance imaging scanning before and after treatment. Core DMN nodes including medial prefrontal cortex （mPFC）， bilateral inferior parietal lobule （IPL）， and precuneus （PCUN） were selected as seed regions. Granger causality analysis （GCA） was employed to assess bidirectional EC between the seed regions and both the other intra-DMN nodes and the remaining whole-brain regions. Hepatic and renal function indices were detected pre- and post-treatment to evaluate the safety profiles of both treatments. ResultsAt baseline， significant between-group differences were identified in EC from the left IPL to the left middle fronto-orbital gyrus/gyrus rectus （t=5.24， Z=4.84， voxel-level P<0.001， cluster-level P<0.05， GRF-corrected）， with the modified Suanzaoren Decoction group exhibiting stronger EC than the estazolam group. No significant between-group differences were observed in EC between other core DMN nodes and remaining whole-brain regions （P>0.05）. Within-group pre- to post-treatment comparisons demonstrated consistent connectivity alterations in both groups. Specifically， EC from the left IPL to the supplementary motor area （SMA） decreased after treatment （modified Suanzaoren Decoction group： t=-6.28， Z=5.208； estazolam group： t=-5.58， Z=4.425）. Conversely， EC from the SMA to the left IPL increased （modified Suanzaoren Decoction group： t=5.89， Z=4.968； estazolam group： t=6.15， Z=4.720）. Furthermore， both groups demonstrated reduced EC from the PCUN to the left IPL （modified Suanzaoren Decoction group： t=-5.85， Z=4.94； estazolam group： t=-5.75， Z=4.515）， and elevated EC from the left IPL to the PCUN （modified Suanzaoren Decoction group： t=5.29， Z=4.579； estazolam group： t=4.55， Z=3.826） （voxel-level P<0.001， cluster-level P<0.05， GRF-corrected）. No significant pre- to post-treatment differences were observed in hepatic or renal function indices in either group （P>0.05）. ConclusionIn CID patients with Yin-deficiency and fire-hyperactivity syndrome， both modified Suanzaoren Decoction and estazolam induce convergent bidirectional remodeling of EC between the left IPL and the SMA and the PCUN. ［Funded by Natural Science Fund Project of Inner Mongolia Autonomous Region （number， 2019MS08099）； ClinicalTrials.gov number， NCT06452953］

OBJECTIVE To evaluate the quality of Lufu Pill （LFP）.METHODS The high-performance liquid chromatography （HPLC） fingerprint of LFP was established using the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （2012 Edition）， and similarity evaluation was performed. Hierarchical cluster analysis （HCA）， principal component analysis （PCA）， and orthogonal partial least squares-discriminant analysis （OPLS-DA） were performed using SIMCA 14.1 software. The contents of strychnine， brucine， liquiritin， notoginsenoside R 1 ， ginsenoside Rg 1 ， ginsenoside Rb 1 ， licoricesaponin G 2 ， and ginsenoside Rd in 12 batches of samples were determined by the HPLC method.RESULTS A total of 26 common peaks were identified in the HPLC fingerprint of 12 batches of LFP samples， and eight common peaks were identified as strychnine （peak 3）， brucine （peak 4）， liquiritin （peak 6）， notoginsenoside R 1 （peak 7）， ginsenoside Rg 1 （peak 8）， ginsenoside Rb 1 （peak 15）， licoricesaponin G 2 （peak 17）， and ginsenoside Rd （peak 18）. The similarities of 12 batches of LFP samples were all greater than 0.90. The results of HCA and PCA both showed that the 12 batches of samples were divided into two categories： S2， S4-S6， and S12 were grouped into one category， while S1， S3， S7-S11 were grouped into another category. The upper control limits for Hotelling’s T 2 and DMod X were 16.631 and 1.578， respectively. The variable importance in projection values of ginsenoside Rg 1 （peak 8）， ginsenoside Rb 1 （peak 15）， peak 20， strychnine （peak 3）， peak 11， notoginsenoside R 1 （peak 7）， peak 2， peak 17， peak 13， peak 10， ginsenoside Rd （peak 18）， peak 23， peak 26， peak 21， and peak 24 were greater than 1.The content determination results showed that strychnine， brucine， liquiritin， notoginsenoside R 1 ， ginsenoside Rg 1 ， ginsenoside Rb 1 ， licoricesaponin G 2 ， and ginsenoside Rd were 0.005%-0.018%， 0.005%-0.010%， 0.050%-0.118%， 0.033%-0.073%， 0.132%-0.248%， 0.122%-0.242%， 0.021%-0.043%， and 0.016%-0.048%， respectively.CONCLUSIONS The established HPLC fingerprint and content determination method are accurate and reproducible， and can be used for the quality evaluation of LFP. Ginsenoside Rg 1 ， ginsenoside Rb 1 ， strychnine， notoginsenoside R 1 ， and ginsenoside Rd may be the differential components affecting its overall quality.

BACKGROUND: Generalized pustular psoriasis (GPP), a rare and recurrent autoinflammatory disease, imposes a substantial burden on patients and society. Awareness of GPP in China remains limited. METHODS: This cross-sectional survey, conducted between September 2021 and May 2023 across 14 hospitals in China, included GPP patients of all ages and disease phases. Data collected encompassed demographics, clinical characteristics, economic impact, disease severity, quality of life, and treatment-related complications. Risk factors for GPP recurrence were analyzed. RESULTS: Among 127 patients (female/male ratio = 1.35:1), the mean age of disease onset was 25 years (1st quartile [Q1]-3rd quartile [Q3]: 11-44 years); 29.2% had experienced GPP for more than 10 years. Recurrence occurred in 75.6% of patients, and nearly half reported no identifiable triggers. Younger age at disease onset ( P  = 0.021) and transitioning to plaque psoriasis ( P  = 0.022) were associated with higher recurrence rates. The median diagnostic delay was 8 months (Q1-Q3: 2-41 months), and 32.3% of patients reported misdiagnoses. Comorbidities were present in 53.5% of patients, whereas 51.1% experienced systemic complications during treatment. Depression and anxiety affected 84.5% and 95.6% of patients, respectively. During GPP flares, the median Dermatology Life Quality Index score was 19.0 (Q1-Q3: 13.0-23.5). This score showed significant differences between patients with and without systemic symptoms; it demonstrated correlations with both depression and anxiety scores. Treatment costs caused financial hardship in 55.9% of patients, underscoring the burden associated with GPP. CONCLUSIONS The substantial disease and economic burdens among Chinese GPP patients warrant increased attention. Patients with early onset disease and those transitioning to plaque psoriasis require targeted interventions to mitigate the high recurrence risk.
Humans ; Male ; Female ; Psoriasis/pathology* ; Adult ; Cross-Sectional Studies ; Adolescent ; Child ; Young Adult ; Quality of Life ; Middle Aged ; China/epidemiology* ; Recurrence ; Risk Factors ; Surveys and Questionnaires ; East Asian People

A new method was developed for simultaneous and efficient determination of linear perfluorooctanoic acid(n-PFOA)and linear perfluorooctane sulfonate(n-PFOS),and their typical branched isomers in seawater by online solid phase extraction-liquid chromatography-tandem mass spectrometry(Online SPE-LC-MS/MS).Only centrifugation of the seawater sample was required to remove the particulate matter,and then the seawater sample was directly injected and analyzed by online SPE-LC-MS/MS.An Eclipse Plus-C18 guard column was selected as SPE column for online enrichment of linear and branched isomers,and a F5 PFP column(150 mm×2.1 mm,2.7 μm)was used as the analytical column.Under the optimized experimental conditions,the separation and detection of all PFOA and PFOS linear and branched isomers could be completed within 20 min.The spiked recoveries of various target compounds ranged from 82.9%to 107.7%with detection limits and limits of quantification of 0.10-1.05 ng/L and 0.30-2.11 ng/L,respectively.The method was characterized by good precision(RSD≤9.10%)and linearity(R2≥0.990).Subsequently,linear and branched isomers of PFOA and PFOS in surface and bottom seawater samples collected from the Laizhou Bay of China were determined.The results showed that the detection rate of all the four branched PFOA isomers were 100%,with the highest average concentration of 25.85 ng/L found for 6m-PFOA,which accounted for 11.79%of the∑PFOA.For the five branched isomers of PFOS,the highest detection rate of 90.84%was found for 5m-PFOS.The highest average concentration of 0.64 ng/L was observed for 3m-PFOS,accounting for 19.88%of ∑PFOS.The proposed method provided an effective detection tool for qualitative and quantitative detection of PFOA and PFOS isomers in the marine aquatic environment.

Breast cancer is one of the most common malignant tumors among women worldwide, with an increasing incidence rate year by year, making it a significant public health concern. With the continuous advancement of tumor biology research, N 6-methyladenosine (m 6A) modification, as an important form of RNA modification, has attracted growing attention. The m 6A modification, the most prevalent RNA modification in eukaryotes, occurs in almost all types of RNA and plays a critical role in the occurrence, progression, and metastasis of breast cancer. It influences cell proliferation, apoptosis, and alterations in the tumor microenvironment, though the specific mechanisms underlying these effects require further in-depth investigation. Moreover, the specific patterns of m 6A modification demonstrate its potential as a novel biomarker for breast cancer, which could provide new directions for early diagnosis and prognosis evaluation.

Objective: To explore relationship of sleep quality with overweight and obesity among middle school students, so as to provide a reference basis for improving adolescent sleep health. Methods: From September to December 2023, 5 713 middle school students aged 13 to 18 were selected by stratified cluster random sampling method in six regions, including Shanghai, Suzhou, Taiyuan, Wuyuan, Xingyi and Urumqi. Sleep quality survey was conducted on middle school students by Pittsburgh Sleep Quality Index. Height and weight were measured, and World Health Organization s standards for growth and development of children and adolescents was used to evaluate their nutritional status. Both χ 2 test and Logistic regression analysis were used to analyze the association between sleep quality and nutritional status of middle school students. Results: The non compliance detection rate of sleep quality was 38.4% among girls, but 29.2% among boys, and the difference was of statistical significance( χ 2=54.08, P < 0.01 ). The detection rate of substandard sleep quality was 34.2% in the group with normal nutritional status, 38.3% in the group with overweight, 43.7% in the group with obesity and 26.0% in the group with emaciation, and the difference in the rates of substandard sleep quality among middle school students of different nutritional status was statistically significant ( χ 2=68.15, P <0.01). Logistic regression analysis showed that, after controlling for mental health and physical activity, the detection rate of substandard sleep quality in the obese groups was 1.30 times higher than that in the normal group, respectively( OR =1.30, 95% CI =1.06- 1.59 , P <0.01). Conclusions Sleep quality is correlated with overweight and obesity among middle school students, and there are gender differences. Intervention policies should be formulated according to the characteristics of different genders.