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.

The chemical constituents of the petroleum ether extract derived from the 90% ethanol extract of Elephantopus scaber were investigated. By silica gel column chromatography, C_(18), MCI column chromatography and semi-preparative high performance liquid chromatography, ten compounds were isolated. Their structures were identified as 3β-hydroxy-6β,7β-epoxytaraxeran-14-ene(1), 3β-hydroxyolean-12-en-28-oic acid(2), D-friedoolean-14-ene-3β,7α-diol(3), 3β-hydroxy-11α-methoxyolean-12-ene(4), 3β-hydroxyolean-11,13(18)-diene(5), 11α-hydroxy-β-amyrin(6), betulinic acid(7), 3β-hydroxy-30-norlupan-20-one(8), 6-acetonylchelerythrine(9), and 4',5'-dehydrodiodictyonema A(10) by analysis of the 1D NMR, 2D NMR, MS, and IR spectral data. Among them, compound 1 was a new triterpene and other compounds except compounds 2 and 7 were isolated from this plant for the first time.
Triterpenes/isolation & purification* ; Drugs, Chinese Herbal/isolation & purification* ; Molecular Structure ; Asteraceae/chemistry* ; Chromatography, High Pressure Liquid ; Magnetic Resonance Spectroscopy

The chemical constituents of the chloroform extract of the 90% methanol extract obtained from the dried branches and leaves of Croton lauioides were investigated. By using silica gel column chromatography, C_(18 )column chromatography, MCI column chromatography, and semi-preparative high-performance liquid chromatography(HPLC), six compounds were isolated. Their structures were identified as lauioidine(1), 2α-methoxy-8α-hydroxy-6-oxogermacra-1(10),7(11)-dien-8,12-olide(2), myrrhanolide B(3), gossweilone(4), 6β,7β-epox-4α-hydroxyguaian-10-ene(5), and 4(15)-eudesmane-1β,5α-diol(6) by analyzing the HR-ESI-MS, IR, ECD, 1D NMR and 2D NMR data, as well as their physicochemical properties. All compounds were isolated from C. lauioides for the first time, among which compound 1 is a new nor-clerodane diterpenoid.
Croton/chemistry* ; Diterpenes, Clerodane/isolation & purification* ; Molecular Structure ; Drugs, Chinese Herbal/isolation & purification* ; Magnetic Resonance Spectroscopy ; Chromatography, High Pressure Liquid

Investigating the correlation between micronucleus formation and male infertility has the potential to improve clinical diagnosis and deepen our understanding of pathological progression. Our study enrolled 2252 male patients whose semen was analyzed from March 2023 to July 2023. Their clinical data, including semen parameters and age, were also collected. Genetic analysis was used to determine whether the sex chromosome involved in male infertility was abnormal (including the increase, deletion, and translocation of the X and Y chromosomes), and subsequent semen analysis was conducted for clinical grouping purposes. The participants were categorized into five groups: normozoospermia, asthenozoospermia, oligozoospermia, oligoasthenozoospermia, and azoospermia. Patients were randomly selected for further study; 41 patients with normozoospermia were included in the control group and 117 patients with non-normozoospermia were included in the study group according to the proportions of all enrolled patients. Cytokinesis-block micronucleus (CBMN) screening was conducted through peripheral blood. Statistical analysis was used to determine the differences in micronuclei (MNi) among the groups and the relationships between MNi and clinical data. There was a significant increase in MNi in infertile men, including those with azoospermia, compared with normozoospermic patients, but there was no significant difference between the genetic and nongenetic groups in azoospermic men. The presence of MNi was associated with sperm concentration, progressive sperm motility, immotile spermatozoa, malformed spermatozoa, total sperm count, and total sperm motility. This study underscores the potential utility of MNi as a diagnostic tool and highlights the need for further research to elucidate the underlying mechanisms of male infertility.
Humans ; Male ; Infertility, Male/genetics* ; Adult ; Micronucleus Tests ; Semen Analysis ; Oligospermia/genetics* ; Azoospermia/genetics* ; Chromosome Aberrations ; Sperm Count ; Micronuclei, Chromosome-Defective ; Middle Aged

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Objective To investigate the effects of Chaihuang Yishen Granules on renal fibrosis in unilateral ureteral obstruction(UUO)mice and its underlying mechanisms.Methods Twenty-four 8-week-old male C57BL/6 mice were randomly divided into control group,model group,and low and high dose groups of Chaihuang Yishen Granules(6 in each group).In control group,only right kidney ureter was exposed and dissected.In model group,the UUO animal model was established by UUO.In low and high dose groups,mice were administered intragastrically at doses of 3.8 and 7.6 g/kg of Chaihuang Yishen Granules respectively,following the model group's method to establish the UUO model.After 7 days,the mice were euthanized and renal samples were collected.HE and Masson staining were used to observe pathological changes and fibrosis degree of the kidneys in each group,Sirius red staining was used to observe collagen deposition.The expression levels of α-smooth muscle actin(α-SMA),fibronectin(FN),type Ⅰ collagen(Col-Ⅰ),glycogen synthase kinase 3β(GSK-3β),and β-catenin related proteins were detected using Western blotting.Changes in A33 and GSK-3β,β-catenin mRNA levels were measured by RT-PCR.Additionally,a normal transformed C3H mouse kidney-1(TCMK1)was used as control(normal group);an in vitro fibrosis model was established using TCMK1 stimulated with Transforming Growth Factor-β(TGF-β);and an in vitro drug model was established using TCMK1 treated with serum containing Chaihuang Yishen Granules.A33 was overexpressed in TCMK1 cells using a transfection with an A33 overexpression plasmid,and changes in fibrosis-related indicators and the expression of A33 and GSK-3β,β-catenin mRNA were observed.Results RT-PCR results showed that,compared with control group,A33 level was significantly increased in model group,while it was significantly reduced in both low and high dose groups of Chaihuang Yishen Granules(P＜0.05).Western blotting showed that the expression levels of fibrosis-related factors such as α-SMA,FN,Col-Ⅰ in model group were significantly higher than those in control group(P＜0.05);while compared with model group,the expression levels of α-SMA,FN,Col-Ⅰ in low and high dose groups of Chaihuang Yishen Granules were significantly lower(P＜0.05).HE,Masson,immunohistochemical staining results showed that model group had severe kidney structural damage,significant increase in collagen deposition,and significantly higher expression levels of GSK-3β and β-catenin proteins compared with those in control group(P＜0.01).In contrast,low and high dose groups of Chaihuang Yishen Granules had good kidney structure,significant improvement in kidney damage and fibrosis,and significantly lower expression levels of GSK-3β and β-catenin proteins compared with those in model group(P＜0.05).In vitro experiment results confirmed that,compared with normal group,A33 overexpression promoted the upregulation of fibrosis-related factors in TCMK1 cells,significantly increase the expression of downstream target genes GSK-3β and β-catenin mRNA in the Wnt/β-catenin signaling pathway(P＜0.05),and A33 overexpression reversed the cellular fibrosis changes downregulated by the serum containing Chaihuang Yishen Granules(P＜0.01).Conclusion Chaihuang Yishen Granules significantly improve renal fibrosis in UUO mice by downregulating the A33/Wnt/β-catenin signaling pathway,suggesting that A33 may be a potential therapeutic target for renal fibrosis.

Pharmacological perturbation studies based on protein-level signatures are fundamental for drug dis-covery.In the present study,we used a mass spectrometry(MS)-based proteomic platform to profile the whole proteome of the breast cancer MCF7 cell line under stress induced by 78 bioactive compounds.The integrated analysis of perturbed signal abundance revealed the connectivity between phenotypic behaviors and molecular features in cancer cells.Our data showed functional relevance in exploring the novel pharmacological activity of phenolic xanthohumol,as well as the noncanonical targets of clinically approved tamoxifen,lovastatin,and their derivatives.Furthermore,the rational design of synergistic inhibition using a combination of histone methyltransferase and topoisomerase was identified based on their complementary drug fingerprints.This study provides rich resources for the proteomic landscape of drug responses for precision therapeutic medicine.

Objective:To evaluate the effect of preemptive analgesia with ibuprofen on postoperative pain following single posterior tooth implantation, aiming to provide a clinical reference for its application.Methods:A multicenter, randomized, double-blind, placebo-controlled parallel-group trial was conducted. A total of 82 participants were included in the trial, meeting the eligibility criteria from April 2022 to April 2024 at the Capital Medical University School of Stomatology (40 cases), Beijing TianTan Hospital, Capital Medical University (22 cases), Beijing Chao-Yang Hospital, Capital Medical University (20 cases). Participants were randomly assigned in a 1∶1 ratio to either the ibuprofen group or the control group, with each group comprising 41 individuals. Participants in the ibuprofen group received 300 mg of sustained-release ibuprofen capsules orally 15 min before surgery, while the control group received a placebo. Both groups received the same postoperative analgesic regimen for 3 days. Pain scores were assessed using the numerical rating scale at 30 min, 4 h, 6 h, 8 h, 24 h, 48 h, and 72 h postoperatively, and the additional use of analgesic medication was recorded from days 4 to 6 postoperatively.Results:A total of 82 participants were initially enrolled in the study, with 7 dropouts (4 from the control group and 3 from the ibuprofen group), resulting in 75 participants (37 in the control group and 38 in the ibuprofen group) completing the trial. There were no reports of adverse events such as nausea or vomiting among the participants. The ibuprofen group exhibited significantly lower pain scores at 4 h, 6 h and 8 h [1.0 (0.0, 2.0), 1.0 (0.0, 2.0), 1.5 (0.0, 3.0) ] postoperatively compared to the control group 4 h, 6 h and 8 h [2.0 (1.0, 3.0), 3.0 (1.5, 4.0), 2.0 (1.0, 4.0)] ( Z=-1.99, P=0.047; Z=-3.01, P=0.003; Z=-2.10, P=0.036). The proportions of patients requiring additional analgesic medication between days 4 and 6 post-surgery were 18.4% (7/38) in the ibuprofen group and 27.0% (10/37) in the control group, with no significant difference (χ 2=0.79, P=0.373). The median additional medication usage postoperatively was [0.0 (0.0, 0.0) pills] in the ibuprofen group and [0.0 (0.0, 1.0) pills] in the control group, with no significant difference ( Z=-0.78, P=0.439). Conclusions:Preemptive analgesia with ibuprofen effectively reduces postoperative pain following tooth implantation, representing a safe and effective perioperative pain management strategy.