OBJECTIVE To compare the efficacy and safety of evolocumab and probucol in patients with ultra-high-risk atherosclerotic cardiovascular disease （ASCVD） following percutaneous coronary intervention （PCI）. METHODS A retrospective analysis was conducted on 156 ultra-high-risk ASCVD patients who underwent PCI in our institution between January 1， 2023 and December 31， 2024. According to the lipid-lowering regimen， the patients were categorized into evolocumab group （ n ＝86） and probucol group （ n ＝70）. Changes in lipid parameters [total cholesterol （TC）， low-density lipoprot ein cholesterol （LDL-C）， high-density lipoprotein cholesterol （HDL-C）， triglycerides， lipoprotein （a）， and lipid goal achievement rate ] ， inflammatory markers [interleukin-6 （IL-6） and C-reactive protein （CRP） ] ， and cardiac function indices （left ventricular ejection fraction， left ventricular end-systolic diameter， left ventricular end-diastolic diameter， and N-terminal pro-B-type natriuretic peptide） were compared between two groups at baseline and after 6 months of treatment. The incidence of adverse clinical events during treatment， including acute myocardial infarction， in-stent restenosis， acute heart failure， cerebral hemorrhage， and stroke， was also evaluated. RESULTS No statistically significant differences were observed between the two groups at baseline （ P ＞0.05）. After 6 months of treatment， both groups demonstrated significant improvements in lipid profiles （except HDL-C） and inflammatory markers compared to those at baseline （ P ＜0.05）. The evolocumab group exhibited greater reductions in TC， LDL-C， IL-6， and CRP， along with a higher lipid target achievement rate， compared with the probucol group （ P ＜0.05）. There were no statistically significant differences in the cardiac function-related indicators before and after treatment between the two groups， nor in the incidence of adverse events during the treatment （ P ＞0.05）. CONCLUSIONS For ultra-high-risk ASCVD patients after PCI， both of the above treatment options are associated with improvements in blood lipid and inflammatory response， with good safety during short-term follow-up. Evolocumab shows superior efficacy in TC， LDL-C and inflammatory markers reduction and lipid target achievement， compared to probucol.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

Objective To evaluate the impact of an integrated management mode of prenatal diagnosis-postnatal treatment for congenital heart disease (CHD) on perioperative and long-term outcomes of the arterial switch operation (ASO), and to analyze the efficacy of ASO in a single center. Methods This retrospective study analyzed the clinical data of 183 children who underwent ASO at Guangdong Provincial People’s Hospital from 2018 to 2024. The cohort included 106 (57.9%) patients of transposition of the great arteries with intact ventricular septum (TGA/IVS), 61 (33.3%) patients of transposition of the great arteries with ventricular septal defect (TGA/VSD), and 16 (8.7%) patients of Taussig-bing anomaly (TBA). Perioperative indicators were compared between 91 patients in the prenatal-postnatal integrated management group (an integrated group) and 92 patients in the traditional management group (a non-integrated group). Long-term survival and reoperation rates were analyzed using Kaplan-Meier curves. Results The overall perioperative mortality rate was 4.9% (9/183), showing a downward trend year by year. The primary cause of perioperative mortality was low cardiac output syndrome (LCOS), which occurred in 12 patients (6.6% incidence) with a mortality rate of 75.0%. The integrated group had a higher proportion of males (89.0% vs. 72.8%, P<0.05) and lower body weight [3.1 (2.7, 3.3) kg vs. 3.3 (3.0, 3.7) kg, P<0.05] compared to the non-integrated group. The age at surgery was significantly earlier in the integrated group [7 (3, 10) d vs. 14 (9, 48) d, P<0.05], and all children in the integrated group underwent ASO within the optimal surgical window (100.0% vs. 82.6%, P<0.05). Intraoperatively, cardiopulmonary bypass time [173 (150, 207) min vs. 186 (159, 237) min, P<0.05] and aortic cross-clamp time [100 (90, 117) min vs. 116 (97, 142) min, P<0.05] were significantly shorter in the integrated group. Although the integrated group had longer postoperative mechanical ventilation time [145 (98, 214) h vs. 116 (77, 147) h, P<0.05] and higher 48-hour maximum vasoactive inotropic score [15 (10, 21) points vs. 12 (8, 16) points, P<0.05], there was no statistically significant difference in the incidence of severe complications (LCOS, necrotizing enterocolitis, extracorporeal membrane oxygenation) or mortality rate (3.3% vs. 6.5%, P=0.51) between the two groups, despite earlier surgical intervention and a higher proportion of critically ill cases in the integrated group. The length of hospital stay in the emergency surgery group was significantly shorter than that in the elective surgery group [20 (15, 28) d vs. 25 (21, 30) d, P<0.05], suggesting that early surgery may be of potential benefit. A total of 163 patients were successfully followed up for a median of 4.7 years, with a 5-year survival rate of 95.1% and a freedom from reintervention survival rate of 95.1%. There were no late deaths, and the most common postoperative complication was pulmonary artery stenosis. Conclusion The integrated management model allowed critically ill children with lower body weights to safely undergo surgery, significantly optimizing the timing of surgery and shortening intraoperative times. The long-term risk of reoperation after ASO is primarily concentrated on pulmonary artery stenosis, necessitating long-term follow-up and monitoring.

ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

Objective: To explore the impact of donor reentry experience, specifically among those with a single reactive serological result who completed the reentry process, on their willingness to return for future blood donation, and to examine the mediating roles of blood donation knowledge and trait anxiety. Methods: A cross-sectional survey was conducted between November and December 2025. A total of 386 blood donors from the Changsha Blood Center were categorized into a reentry group (n=123) and a control group (n=263). Data on demographic characteristics, blood donation knowledge (BDKQ), trait anxiety (STAI-T), and blood donation return intention (BDRIS) were collected via questionnaires. SPSS 27.0 and AMOS 28.0 were used for statistical analyses, including independent-samples t-test, one-way ANOVA, multiple linear regression, and path analysis for mediating effect testing. Results: There were statistically significant differences in age, occupation, education level, monthly income and donation frequency between the reentry group and the control group (all P<0.05). The reentry group scored significantly higher in blood donation knowledge and blood donation return intention than the control group (both P<0.05). The mean BDRIS score was 11.51±3.62, indicating a relatively high intention to return. Blood donation knowledge was significantly negatively correlated with trait anxiety (r=-0.15, P<0.05) and positively correlated with blood donation return intention (r=0.19, P<0.05); trait anxiety was significantly negatively correlated with blood donation return intention (r=-0.33, P<0.05). Significant differences in BDRIS scores were found based on group (reentry vs control), age, and number of previous donations (all P<0.05). Multiple linear regression showed that BDKQ positively predicted BDRIS (β=0.11, P<0.05), while STAI-T negatively predicted BDRIS (β=-0.27, P<0.05). Path analysis further revealed that the reentry experience had no direct effect on the intention to return. However, it exerted a positive influence through two indirect pathways: 1) a simple mediating effect via increased blood donation knowledge (β=0.17, accounting for 25.0% of the total effect), and 2) a chain mediating effect through "increased blood donation knowledge → decreased trait anxiety" (β=0.05, accounting for 8.1% of the total effect). The model fit indices reached the ideal fitting criteria. Conclusion: The donor reentry experience does not directly enhance the intention to return for blood donation. Rather, it may exert an indirect positive influence by increasing blood donation knowledge and through the sequential pathway of "increased knowledge → decreased trait anxiety". Blood collection institutions should leverage the reentry process as an opportunity for education and psychological support to improve donor retention rate.

With the widespread application of low-dose computed tomography (CT), the detection rate of multiple lung cancers (MLCs) is gradually increasing. The diagnosis and treatment of MLCs have become a major challenge in clinical practice in thoracic surgery and oncology. In April 2025, the Lung Cancer Professional Committee of the China Anti-Cancer Association (CACA) organized multidisciplinary experts from both domestic and international fields to release the first edition of the CACA Expert Consensus on the Diagnosis and Treatment of Multiple Lung Cancers, providing systematic recommendations for the diagnostic system, molecularassessment strategies, and surgical and non-surgical management of MLCs. This article provides a detailed interpretation of the core content of this consensus and, by incorporating the latest research progress in the field, delves into the pathogenesis, precise diagnostic strategies, and individualized treatment pathways for multiple lung cancers, aiming to offer a more comprehensive reference for clinical practice.

Fibrosis, the pathological scarring of vital organs, is a severe and often irreversible condition that leads to progressive organ dysfunction. It is particularly pronounced in organs like the liver, kidneys, lungs, and heart. Despite its clinical significance, the full understanding of its etiology and complex pathogenesis remains incomplete, posing substantial challenges to diagnosing, treating, and preventing the progression of fibrosis. Among the various molecular players involved, platelet-derived growth factor-C (PDGF-C) has emerged as a crucial factor in fibrotic diseases, contributing to the pathological transformation of tissues in several key organs. PDGF-C is a member of the PDGFs family of growth factors and is synthesized and secreted by various cell types, including fibroblasts, smooth muscle cells, and endothelial cells. It acts through both autocrine and paracrine mechanisms, exerting its biological effects by binding to and activating the PDGF receptors (PDGFRs), specifically PDGFRα and PDGFRβ. This binding triggers multiple intracellular signaling pathways, such as JAK/STAT, PI3K/AKT and Ras-MAPK pathways. which are integral to the regulation of cell proliferation, survival, migration, and fibrosis. Notably, PDGF-C has been shown to promote the proliferation and migration of fibroblasts, key effector cells in the fibrotic process, thus accelerating the accumulation of extracellular matrix components and the formation of fibrotic tissue. Numerous studies have documented an upregulation of PDGF-C expression in various fibrotic diseases, suggesting its significant role in the initiation and progression of fibrosis. For instance, in liver fibrosis, PDGF-C stimulates hepatic stellate cell activation, contributing to the excessive deposition of collagen and other extracellular matrix proteins. Similarly, in pulmonary fibrosis, PDGF-C enhances the migration of fibroblasts into the damaged areas of lungs, thereby worsening the pathological process. Such findings highlight the pivotal role of PDGF-C in fibrotic diseases and underscore its potential as a therapeutic target for these conditions. Given its central role in the pathogenesis of fibrosis, PDGF-C has become an attractive target for therapeutic intervention. Several studies have focused on developing inhibitors that block the PDGF-C/PDGFR signaling pathway. These inhibitors aim to reduce fibroblast activation, prevent the excessive accumulation of extracellular matrix components, and halt the progression of fibrosis. Preclinical studies have demonstrated the efficacy of such inhibitors in animal models of liver, kidney, and lung fibrosis, with promising results in reducing fibrotic lesions and improving organ function. Furthermore, several clinical inhibitors, such as Olaratumab and Seralutinib, are ongoing to assess the safety and efficacy of these inhibitors in human patients, offering hope for novel therapeutic options in the treatment of fibrotic diseases. In conclusion, PDGF-C plays a critical role in the development and progression of fibrosis in vital organs. Its ability to regulate fibroblast activity and influence key signaling pathways makes it a promising target for therapeutic strategies aiming at combating fibrosis. Ongoing research into the regulation of PDGF-C expression and the development of PDGF-C/PDGFR inhibitors holds the potential to offer new insights and approaches for the diagnosis, treatment, and prevention of fibrotic diseases. Ultimately, these efforts may lead to the development of more effective and targeted therapies that can mitigate the impact of fibrosis and improve patient outcomes.

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.