Background With China's socio-economic development, the dietary structure of Chinese residents has gradually shifted from a traditional Eastern pattern characterized by high carbohydrate intake to a relatively high-fat Western dietary model, alongside a growing burden of chronic diseases. However, dietary changes may vary across different occupational groups. Objective To analyze the long-term trends in dietary energy and three major macronutrient intake among various occupational groups aged 18-59 years in nine provinces of China from 1989 to 2018, providing a scientific basis for developing occupation-specific dietary intervention strategies. Methods Based on 11 waves of data (1989–2018) from the China Health and Nutrition Survey (CHNS), 57458 employed individuals aged 18-59 years were selected as observation subjects after applying inclusion and exclusion criteria. Joinpoint regression was used to analyze temporal trends by calculating the annual percentage change (APC) and average annual percentage change (AAPC) with 95% confidence intervals. The analysis covered the energy supply ratio from the three major macronutrients and the proportion of the participants within the acceptable macronutrient distribution ranges (AMDR) for the total occupational population and specific occupational group. Results From 1989 to 2018, the dietary structure of the occupational population in the nine provinces gradually Westernized. The carbohydrate energy supply ratio showed a decreasing trend (AAPC=−0.77%, 95%CI: −1.00%, −0.55%, P<0.05), while the fat energy supply ratio increased (AAPC=1.42%, 95%CI: 1.07%, 1.77%, P<0.05). The protein energy supply ratio remained largely unchanged (AAPC=−0.19%, 95%CI: −0.08%, 0.46%, P>0.05), and the total energy intake declined (AAPC=−0.62%, 95%CI: −0.94%, −0.30%, P<0.05). Among the occupational groups studied, white-collar workers were the first to show characteristics of dietary Westernization. Using the AMDR as the criterion, their average fat energy supply ratio first exceeded the AMDR upper limit (30%) in 1993, and their average carbohydrate energy supply ratio first fell below the AMDR lower limit (50%) in 2006, both time points being earlier than other occupational groups. Agricultural workers lagged in this transition (their average fat energy supply ratio first reached ≥30% in 2011), but their rate of increase in the fat energy supply ratio was the fastest among all occupational groups (AAPC=1.59%, 95%CI: 0.90%, 2.30%, P<0.05; P for trend comparison between groups<0.05). The other three occupational groups (blue-collar workers, service workers, and others) generally fell between these two extremes. Taking the fat energy supply ratio as an example, their AAPCs of increase were 1.02% (95%CI: 0.73%, 1.32%, P<0.05) for blue-collar workers, 0.85% (95%CI: 0.61%, 1.09%, P<0.05) for service workers, and 0.88% (95%CI: 0.58%, 1.17%, P<0.05) for others. Conclusion From 1989 to 2018, the macronutrient structure of the occupational population aged 18-59 years in nine China provinces is gradually Westernized. The energy supply ratios of carbohydrates and proteins primarily face issues of potential inadequacy, while the fat energy supply ratio is excessively high. Furthermore, the patterns of change vary among different occupational groups. It is recommended to propose personalized dietary advice tailored to specific occupations.

Surface proteins play pivotal roles in physiological processes, including cell recognition, signal transduction, substance transport, and immune responses. However, challenges persist in characterizing abnormal surface proteins in disease states and identifying therapeutic targets, due to the low abundance of these proteins within the total proteome and the frequent presence of their complex glycosylation modifications. Recent years have witnessed the vigorous development of chemical proteomics, leading to the successful creation of various chemical probes for the labeling and characterization of cell surface proteins. These techniques have subsequently been applied to the detection of disease surface proteins and the discovery of corresponding targets. Surface protein characterization techniques based on chemical proteomics are discussed herein, focusing on the principles of amino acid-targeted labeling, proximity labeling, and glycoprotein capture. The novelty, advantages, and limitations of techniques such as targeted lysine labeling, peroxidase and photocatalytic proximity labeling, and chemical glycan capture and metabolic glycan labeling are elaborated, and their applications across various biological models and disease types are described, aiming to provide some reference for target discovery and drug development targeting surface proteins.

Autism spectrum disorder （ASD）， also known as autism， is a series of neurodevelopmental disorders characterized by social disorders and repetitive stereotyped behaviors/narrow interests. Its pathogenesis is complex， and there is a lack of effective treatment drugs， with some cases having adverse outcomes. Recent studies have consistently revealed that individuals with autism spectrum disorder （ASD） commonly exhibit characteristics such as gut microbiota dysbiosis （abnormal Bacteroidetes/Firmicutes ratio）， impaired intestinal barrier function （elevated serum levels of zonulin and LPS）， and intestinal immune dysregulation （increased pro-inflammatory cytokines including IL-6 and TNF-α）， suggesting that gastrointestinal abnormalities may influence central nervous system development through neuroendocrine， immunoregulatory， and metabolic pathways. Consequently， growing scholarly attention has focused on dietary interventions as potential approaches to alleviate clinical symptoms in children with ASD. This review systematically summarizes the role of gut microbiota and their metabolite alterations in ASD pathogenesis， along with recent advancements in understanding the microbiota-gut-brain axis mechanisms. Additionally， it elaborates on the therapeutic effects and underlying biological basis of restrictive diet therapy， modified diet therapy， and nutritional supplementation therapy in promoting the health of children with ASD. This systematic review reveals that children with ASD exhibit significant gut microbiota dysbiosis （e.g.， increased Clostridium， decreased Faecalibacterium） and abnormal metabolite profiles （e.g.， altered short-chain fatty acid spectra， elevated 4EPS levels）. These alterations exacerbate neuroinflammation and immune dysregulation through the microbiota-gut-brain axis， thereby impacting nervous system development and function. Furthermore， interventions such as ketogenic diets， camel milk， and specific nutritional supplements can alleviate certain ASD symptoms by modulating gut microbiota， restoring intestinal barrier function， and improving metabolic pathways. Future investigations should aim to create multi-omics evaluation systems for pinpointing potential beneficiaries， devise individualized intervention strategies rooted in microbiome characteristics， and verify their therapeutic value and safety in large-scale randomized controlled trials. These efforts are crucial to transitioning ASD treatment from symptomatic control to address disease etiology， thereby paving the way for improving prognoses.

This paper primarily investigated the protective effects and potential mechanisms of total saponins from Ginseng Radix et Rhizoma and Notoginseng Radix et Rhizoma in alleviating isoprenaline(ISO)-induced hypertrophy and damage in H9c2 cardiomyocytes. Initially, H9c2 cardiomyocytes were used as the research subject to analyze the effects of ISO at different concentrations on cell hypertrophy and damage. On this basis, the H9c2 cardiomyocytes were divided into blank, model, and high-dose(200 μg·mL~(-1)), medium-dose(100 μg·mL~(-1)), and low-dose(50 μg·mL~(-1)) groups of total saponins from Ginseng Radix et Rhizoma and Notoginseng Radix et Rhizoma. Cell hypertrophy and damage models were induced by treating cells with 400 μmol·L~(-1) ISO for 24 hours. The Incucyte live-cell analysis system was utilized to observe the status, size changes, and confluence of the cells in each group. Cell viability was detected by using the CCK-8 assay. Western blot analysis was employed to detect the expression of Ras-associated protein 7A(RAB7A), sequestosome 1(SQSTM1/p62), autophagy-related protein Beclin1, and microtubule-associated protein 1 light chain 3(LC3). Immunofluorescence was used to detect the expression level of the autophagy marker Beclin1 in H9c2 cells. The results demonstrated that compared with the blank group, the model group showed a significant reduction in cell viability(P<0.01) and a marked increase in cell hypertrophy, with an average cell length growth of 13.53%. Compared with the model group, the high-dose, medium-dose, and low-dose groups of total saponins from Ginseng Radix et Rhizoma and Notoginseng Radix et Rhizoma exhibited reduced hypertrophy, with respective growths of 6.89%, 8.30%, and 8.49% and a significant decrease in growth rates(P<0.01). Cell viability in the high-dose of total saponins from Ginseng Radix et Rhizoma and Notoginseng Radix et Rhizoma was also significantly increased(P<0.01). Western blot and immunofluorescence results indicated that compared with the blank group, the model group showed changes in Beclin1, RAB7A, and p62 expression, as well as the LC3Ⅱ/LC3Ⅰ ratio, although most changes were not statistically significant. In the groups treated with total saponins from Ginseng Radix et Rhizoma and Notoginseng Radix et Rhizoma, the expression of autophagy-related proteins Beclin1 and RAB7A and the LC3Ⅱ/LC3Ⅰ ratio were significantly increased(P<0.05), while p62 expression significantly decreased(P<0.05). These findings collectively suggested that pretreatment of cells with total saponins from Ginseng Radix et Rhizoma and Notoginseng Radix et Rhizoma significantly enhanced autophagy activity in cells. In summary, total saponins from Ginseng Radix et Rhizoma and Notoginseng Radix et Rhizoma inhibit ISO-induced hypertrophy and damage in H9c2 cells by promoting autophagy, demonstrating potential cardioprotective effects and providing new insights and scientific evidence for their preventive and therapeutic use in cardiovascular diseases.
Autophagy/drug effects* ; Saponins/pharmacology* ; Panax notoginseng/chemistry* ; Panax/chemistry* ; Animals ; Rats ; Cell Line ; Drugs, Chinese Herbal/pharmacology* ; Rhizome/chemistry* ; Isoproterenol/adverse effects* ; Myocytes, Cardiac/cytology* ; Hypertrophy/drug therapy*

The study aims to explore the herb-drug interaction between Xuefu Zhuyu Decoction(XFZY) and atorvastatin(AT). Reverse transcription polymerase chain reaction(RT-PCR) was used to analyze the transcription levels of proteins related to drug metabolism and transport in LS174T cells, detect the intracellular drug uptake under various substrate concentrations and incubation time, and optimize the model reaction conditions of transporter multidrug resistance protein 1(MDR1)-specific probe Rhodamine 123 and AT to establish a cell model for investigating the human intestinal drug interaction. The cell counting kit-8(CCK-8) method was adopted to evaluate the cytotoxicity of XFZY on LS174T cells. After a single and continuous 48 h culture with XFZY, AT or Rhodamine 123 was added for co-incubation. The effect and mechanism of XFZY on human intestinal absorption of AT were analyzed by measuring the intracellular drug concentrations and transcription levels of related transporters and metabolic enzymes. The results of in vitro experiments show that a single co-culture with a high concentration of XFZY significantly increases the intracellular concentrations of Rhodamine 123 and AT. A high concentration of XFZY co-culture for 48 h increases the AT uptake level, significantly induces the CYP3A4 and UGT1A1 gene expression levels, and inhibits the OATP2B1 gene expression level. To compare with the evaluation results of the in vitro human cell model, the pharmacokinetic experiment of XFZY combined with AT was carried out in rats. Sprague-Dawley(SD) rats were randomly divided into a blank control group and an XFZY group. After 14 days of continuous intragastric administration, AT was given in combination. The liquid chromatography-mass spectrometry(LC-MS)/MS method was used to detect the concentrations of AT and metabolites 2-hydroxyatorvastatin acid(2-HAT), 4-hydroxyatorvastatin acid(4-HAT), atorvastatin lactone(ATL), 2-hydroxyatorvastatin lactone(2-HATL), and 4-hydroxyatorvastatin lactone(4-HATL) in plasma samples, and the pharmacokinetic parameters were calculated. Pharmacokinetic analysis in rats shows that continuous administration of XFZY does not significantly change the pharmacokinetic characteristics of AT in rats, but the AUC_(0-6 h) values of AT and metabolites 2-HAT, 4-HAT, and 2-HATL increase by 21.37%, 14.94%, 12.42%, and 6.68%, respectively. The metabolic rate of the main metabolites shows a downward trend. The study indicates that administration combined with XFZY can significantly increase the uptake level of AT in human intestinal cells and increase the exposure level of AT and main metabolites in rats to varying degrees. The mechanism may be mainly due to the inhibition of intestinal MDR1 transport activity.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Atorvastatin/administration & dosage* ; Humans ; Rats ; Rats, Sprague-Dawley ; Male ; Intestines/cytology* ; Intestinal Mucosa/metabolism* ; Herb-Drug Interactions ; Cytochrome P-450 CYP3A/metabolism* ; Intestinal Absorption/drug effects*

Optical imaging is highly valued for its superior temporal and spatial resolution. This is particularly important in near-infrared II (NIR-II, 1 000-3 000 nm) imaging, which offers advantages such as reduced tissue absorption, minimal scattering, and low autofluorescence. These characteristics make NIR-II imaging especially suitable for deep tissue visualization, where high contrast and minimal background interference are critical for accurate diagnosis and monitoring. Currently, inorganic fluorescent probes—such as carbon nanotubes, rare earth nanoparticles, and quantum dots—offer high brightness and stability. However, they are hindered by ambiguous structures, larger sizes, and potential accumulation toxicity in vivo. In contrast, organic fluorescent probes, including small molecules and polymers, demonstrate higher biocompatibility but are limited by shorter emission wavelengths, lower quantum yields, and reduced stability. Recently, gold clusters have emerged as a promising class of nanomaterials with potential applications in biocatalysis, fluorescence sensing, biological imaging, and more. Water-soluble gold clusters are particularly attractive as fluorescent probes due to their remarkable optical properties, including strong photoluminescence, large Stokes shifts, and excellent photostability. Furthermore, their outstanding biocompatibility—attributed to good aqueous stability, ultra-small hydrodynamic size, and high renal clearance efficiency—makes them especially suitable for biomedical applications. Gold clusters hold significant potential for NIR-II fluorescence imaging. Atomic-precision gold clusters, typically composed of tens to hundreds of gold atoms and measuring only a few nanometers in diameter, possess well-defined three-dimensional structures and clear spatial coordination. This atomic-level precision enables fine-tuned structural regulation, further enhancing their fluorescence properties. Variations in cluster size, surface ligands, and alloying elements can result in distinct physicochemical characteristics. The incorporation of different atoms can modulate the atomic and electronic structures of gold clusters, while diverse ligands can influence surface polarity and steric hindrance. As such, strategies like alloying and ligand engineering are effective in enhancing both fluorescence and catalytic performance, thereby meeting a broader range of clinical needs. In recent years, gold clusters have attracted growing attention in the biomedical field. Their application in NIR-II imaging has led to significant progress in vascular, organ, and tumor imaging. The resulting high-resolution, high signal-to-noise imaging provides powerful tools for clinical diagnostics. Moreover, biologically active gold clusters can aid in drug delivery and disease diagnosis and treatment, offering new opportunities for clinical therapeutics. Despite the notable achievements in fundamental research and clinical translation, further studies are required to address challenges related to the standardized synthesis and complex metabolic behavior of gold clusters. Resolving these issues will help accelerate their clinical adoption and broaden their biomedical applications.

Objective: To understand the dynamic temporal evolution pathways of Internet addiction among university students and to identify the core driving nodes, so as to provide theoretical evidences for the precise implementation of targeted interventions. Methods: Using a convenient cluster sampling method, a total of 1 066 full time freshmen and sophomores were recruited from three universities in Guizhou, Jiangxi, and Guangdong Provinces for a follow up survey (T1:January-March 2024; T2:January-March 2025). The Revised Chen Internet Addiction Scale (CIAS-R) was employed to assess the status of Internet addiction among university students, and cross sectional as well as cross lagged panel network models were constructed to analyze Internet addiction and its multidimensional influencing factors. Results: The T1 network comprised 19 nodes and 114 non zero edges, while the T2 network comprised 19 nodes and 126 non zero edges. Cross sectional network analysis revealed the strongest association between "insufficient sleep" and "daytime fatigue"; the core nodes were "first thought upon waking for going online" and "feeling low after disconnection" (characteristics of psychological dependence) at T1, while the core nodes shifted to "impaired health" and "excitement when online" (characteristics of functional impairment and addictive psychodynamic features) at T2. Cross lagged network analysis further indicated that "reduced leisure" directly predicted "sleep compression", and a bidirectional relationship was observed between "needing more time to achieve satisfaction" and "academic decline". Conclusions Internet addiction among university students exhibits dynamic evolutionary characteristics. Stage specific targeted interventions focusing on core driving nodes are needed, integrating behavioral regulation and academic support to break the vicious cycle and enhancing the ability to cope with real life demands.

Objective To evaluate the value of a nomogram model based on ultrasonographic features and inflammatory indicators in the preoperative noninvasive prediction of pathological grading of urothelial carcinoma of bladder(UCB).Methods A retrospective analysis was conducted on 471 patients with pathologically confirmed UCB,and the patients were assigned to high-grade group(401 cases)or low-grade group(70 cases).Basic clinical data(gender,age,macroscopic hematuria),ultrasonographic features(lesion location,blood flow signal,etc.),and blood inflammatory indicators(e.g.neutrophil-to-lymphocyte ratio[NLR])were collected.Independent predictors were screened using univariate and multivariate logistic regression,and a nomogram model was constructed.Model performance was evaluated using the receiver operating characteristic(ROC)curve,calibration curve,and decision curve analysis(DCA).Results Multivariate logistic analysis identified gender(odds ratio[OR]=2.68),age(OR=1.08),macroscopic hematuria(OR=3.19),lesion located in the trigone(OR=4.59),positive blood flow signal(OR=2.87),and NLR(OR=1.03)were independent predictors of high-grade UCB(all P＜0.05).The combined model(clinical features+ultrasonographic characteristics+inflammatory indicators)achieved an area under curve(AUC)of 0.892,which was significantly higher than the clinical feature-only model(AUC=0.799)and the clinical+ultrasonographic model(AUC=0.856).The calibration curve demonstrated good consistency between predicted and actual outcomes,and DCA confirmed its optimal clinical net benefit.Conclusion The nomogram model integrating clinical features,ultrasonographic characteristics,and inflammatory indicators can effectively discriminate UCB pathological grading,providing a reliable preoperative noninvasive assessment tool for personalized treatment decisions.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

Background and Objectives: The Fractional Flow Reserve and Intravascular UltrasoundGuided Intervention Strategy for Clinical Outcomes in Patients with Intermediate Stenosis (FLAVOUR) trial demonstrated non-inferiority of fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) compared with intravascular ultrasound (IVUS)-guided PCI. We sought to investigate the cost-effectiveness of FFR-guided PCI compared to IVUS-guided PCI in Korea. Methods: A 2-part cost-effectiveness model, composed of a short-term decision tree model and a long-term Markov model, was developed for patients who underwent PCI to treat intermediate stenosis (40% to 70% stenosis by visual estimation on coronary angiography).The lifetime healthcare costs and quality-adjusted life-years (QALYs) were estimated from the healthcare system perspective. Transition probabilities were mainly referred from the FLAVOUR trial, and healthcare costs were mainly obtained through analysis of Korean National Health Insurance claims data. Health utilities were mainly obtained from the Seattle Angina Questionnaire responses of FLAVOUR trial participants mapped to EQ-5D. Results: From the Korean healthcare system perspective, the base-case analysis showed that FFR-guided PCI was 2,451 U.S. dollar lower in lifetime healthcare costs and 0.178 higher in QALYs compared to IVUS-guided PCI. FFR-guided PCI remained more likely to be cost-effective over a wide range of willingness-to-pay thresholds in the probabilistic sensitivity analysis. Conclusions Based on the results from the FLAVOUR trial, FFR-guided PCI is projected to decrease lifetime healthcare costs and increase QALYs compared with IVUS-guided PCI in intermediate coronary lesion, and it is a dominant strategy in Korea.