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 explore the prospective associations between physical activity and incident ischemic stroke in adults.Methods:Data of China Kadoorie Biobank study in Tongxiang of Zhejiang were used. After excluding participants with cancers, strokes, heart diseases and diabetes at baseline study, a total of 53 916 participants aged 30-79 years were included in the final analysis. The participants were divided into 5 groups according to the quintiles of their physical activity level. Cox proportional hazard regression models was used to calculate the hazard ratios ( HR) for the analysis on the association between baseline physical activity level and risk for ischemic stroke. Results:The total physical activity level in the participants was (30.63±15.25) metabolic equivalent (MET)-h/d, and it was higher in men [(31.04±15.48) MET-h/d] than that in women [(30.33±15.07) MET-h/d] ( P<0.001). In 595 526 person-years of the follow-up (average 11.4 years), a total of 1 138 men and 1 082 women were newly diagnosed with ischemic stroke. Compared to participants with the lowest physical activity level (<16.17 MET-h/d), after adjusting for socio-demographic factors, lifestyle, BMI, waist circumference, and SBP, the HRs for the risk for ischemic stroke in those with moderate low physical activity level (16.17-24.94 MET-h/d), moderate physical activity level (24.95-35.63 MET-h/d), moderate high physical activity level (35.64-43.86 MET-h/d) and the highest physical activity level (≥43.87 MET-h/d) were 0.93 (95% CI: 0.83-1.04), 0.87 (95% CI: 0.76-0.98), 0.82 (95% CI: 0.71-0.95) and 0.76 (95% CI: 0.64-0.89), respectively. Conclusion:Improving physical activity level has an effect on reducing the risk for ischemic stroke.

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 develop a robotic digestive endoscope system (RDES) and to evaluate its feasibility, safety and control performance by experiments.Methods:The RDES was designed based on the master-slave control system, which consisted of 3 parts: the integrated endoscope, including a knob and button robotic control system integrated with a gastroscope; the robotic mechanical arm system, including the base and arm, as well as the endoscopic advance-retreat control device (force-feedback function was designed) and the endoscopic axial rotation control device; the control console, including a master manipulator and an image monitor. The operator sit far away from the endoscope and controlled the master manipulator to bend the end of the endoscope and to control advance, retract and rotation of the endoscope. The air supply, water supply, suction, figure fixing and motion scaling switching was realized by pressing buttons on the master manipulator. In the endoscopy experiments performed on live pigs, 5 physicians each were in the beginner and advanced groups. Each operator operated RDES and traditional endoscope (2 weeks interval) to perform porcine gastroscopy 6 times, comparing the examination time. In the experiment of endoscopic circle drawing on the inner wall of the simulated stomach model, each operator in the two groups operated RDES 1∶1 motion scaling, 5∶1 motion scaling and ordinary endoscope to complete endoscopic circle drawing 6 times, comparing the completion time, accuracy (i.e. trajectory deviation) and workload.Results:RDES was operated normally with good force feedback function. All porcine in vivo gastroscopies were successful, without mucosal injury, bleeding or perforation. In beginner and advanced groups, the examination time of both RDES and ordinary endoscopy tended to decrease as the number of operations increased, but the decrease in time was greater for operating RDES than for operating ordinary endoscope (beginner group P=0.033; advanced group P=0.023). In the beginner group, the operators operating RDES with 1∶1 motion scaling or 5∶1 motion scaling to complete endoscopic circle drawing had shorter completion time [1.68 (1.40, 2.17) min, 1.73 (1.47, 2.37) min VS 4.13 (2.27, 5.16) min, H=32.506, P<0.001], better trajectory deviation (0.50±0.11 mm, 0.46±0.11 mm VS 0.82±0.26 mm, F=38.999, P<0.001], and less workload [42.00 (30.00, 50.33) points, 43.33 (35.33, 54.00) points VS 52.67 (48.67, 63.33) points, H=20.056, P<0.001] than operating ordinary endoscope. In the advanced group, the operators operating RDES with 1∶1 or 5∶1 motion scaling to complete endoscopic circle drawing had longer completion time than operating ordinary endoscope [1.72 (1.37, 2.53) min, 1.57 (1.25, 2.58) min VS 1.15 (0.86, 1.58) min, H=13.233, P=0.001], but trajectory deviation [0.47 (0.13, 0.57) mm, 0.44 (0.39, 0.58) mm VS 0.52 (0.42, 0.59) mm, H=3.202, P=0.202] and workload (44.62±21.77 points, 41.24±12.57 points VS 44.71±17.92 points, F=0.369, P=0.693) were not different from those of the ordinary endoscope. Conclusion:The RDES enables remote control, greatly reducing the endoscopists' workload. Additionally, it gives full play to the cooperative motion function of the large and small endoscopic knobs, making the control more flexible. Finally, it increases motion scaling switching function to make the control of endoscope more flexible and more accurate. It is also easy for beginners to learn and master, and can shorten the training period. So it can provide the possibility of remote endoscopic control and fully automated robotic endoscope.