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.

Objective:To investigate the clinical manifestation, therapy, and prognosis of Susac syndrome and enhance the understanding of this disease.Methods:A case summary was made.The clinical data of two siblings with Susac syndrome treated at Children′s Medical Center, Peking University First Hospital in January 2024 were summarized.Reported cases of pediatric Susac syndrome were reviewed.Results:The onset of the disease in the two siblings was at the age of 3.00 and 6.75 years, with recurrent headaches, tinnitus, hearing loss and encephalopathy symptoms.Cranial magnetic resonance imaging showed multiple cerebral microbleeding and microinfarction lesions, " snowball like" in the corpus callosum and diffuse white matter edema in the brain.Audiometry revealed sensorineural hearing loss.In one case, ophthalmic fluorescein angiography revealed ischemic changes due to branch retinal artery occlusions.No pathogenic variants were detected in gene testing.This child was diagnosed with Susac syndrome, and the symptoms were improved after treatment with Corticosteroids and Rituximab.No relapse was observed during the 9-month follow-up.A total of 20 pediatric cases of Susac syndrome were retrieved, including 18 reported previously and 2 cases from this study.There were 2 boys and 18 girls, with the age of onset ranging from 2.5 to 17.0 years.The common initial symptoms included headache (19 cases), vertigo and tinnitus or hearing loss (9 cases), and vision impairment or visual field defect (4 cases). The symptoms were improved after immunotherapy.Conclusions:With a low incidence, Susac syndrome is rare in children and difficult to diagnose.There may be a genetic predisposition in such disease.Early diagnosis and immunotherapy can low the relapse and improve the prognosis.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

The minor purchasing process and mode of some hospital were introduced,and the implementation of the hospital's minor purchasing projects in the past year was analyzed.The causes for high failure rate of purchasing were pointed out including long interval between project creation and procurement,unreasonable demand presentation,insufficient demand demonstration and lack of active participation of suppliers.Some suggestions were put forward such as timely adjustment of demands,strengthening of demand demonstration,improvement of supplier motivation and enhancement of procurement process management,which were of great significance for increasing the success rate of minor purchasing of the hospital.[Chinese Medical Equipment Journal,2025,46(8):91-95]

Follicular lymphoma(FL)is a type of non-Hodgkin's lymphoma,and its treatment options face many challenges.This paper discusses the pathogenesis and treatment of FL based on the clear-turbid theory in traditional Chinese medicine(TCM)."The clear and the turbid being related,and the rise and fall of qi being disorderly"is the basic pathogenesis of FL.As the disease progres-ses,"evil qi being blocked inside,and turbid evil harming the clear"aggravates,and finally"evil qi is strong and the disease progres-ses,and evil poison is generated inside".Based on this theory,the method of raising the clear and lowering the turbid and the method of dispersing the clear and removing the turbid are proposed to treat FL.The emphasis of raising the clear and lowering the turbid is to take raising and lowering as the key,movement and stillness as the pivot,and to treat the middle jiao;the emphasis of dispersing the clear and removing the turbid is to clear the triple jiao,warm the yang and invigorate the qi,and harmonize the spleen and kidney.Ca-ses are attached to illustrate,providing new ideas for the TCM treatment of FL.

Objective:To assess the efficacy and safety profile of antaitasvir phosphate combined with yiqibuvir in the treatment of chronic hepatitis C (CHC) of various genotypes, without cirrhosis or with compensated cirrhosis.Methods:394 cases with CHC from 22 centers were collected from October 2021 to April 2023. They were randomly assigned to receive either the experimental drugs (antaitasvir phosphate 100 mg+yiqibuvir 600 mg) or placebo treatment in a 3∶1 ratio. The patients were administered drugs once a day for 12 consecutive weeks, and then followed up for 24 weeks after treatment cessation. All subjects were unblinded at the four-week follow-up following drug discontinuation, with the experimental drug group continuing to complete subsequent post-discontinuation follow-up. The placebo group was switched to receive the experimental drugs for a repeated 12-week treatment period and followed up for another 24 weeks after discontinuation of the drug (placebo delayed treatment phase).The sustained virologic response rate (SVR12) was observed for subjects in the double-blind phase and the placebo delayed-treatment phase at 12 weeks after treatment cessation.Virological resistance analysis was performed on subjects who failed treatment. The primary efficacy endpoint was SVR12. The number and percentage of subjects who achieved "HCV RNA

Asarum forbesii is a perennial herb born in a shaded and humid environment, which is warm in nature. With the efficacy of warming lung, resolving fluid retention, and relieving coughs, it can be used to treat the syndrome of cold fluid accumulating in lung. To investigate the effects of different shading conditions on the composition and efficacy of A. forbesii, this study planted A. forbesii under 20% natural light(NL20), 40% natural light(NL40), 60% natural light(NL60), and 80% natural light(NL80) and utilized ultra performance liquid chromatography(UPLC) and micro broth 2-fold dilution method to detect the volatile chemical compounds and the minimum inhibitory concentration. At the same time, the study investigated the effects of A. forbesii grown under different shading conditions on the signs, pathological changes of lung tissues, serum cytokine levels, activities of mitochondrial respiratory chain complexes Ⅰ-Ⅴ in lung tissues, and relative expression of related genes of mice with syndrome of cold fluid accumulating in lung. The results indicated that with the increase of shading, the content of kakuol, methyl eugenol, and asarinin in A. forbesii and the antibacterial effect showed a tendency of increasing first and then decreasing, and the NL40 group was significantly better than the other groups. Under the conditions of NL20 and NL40, A. forbesii significantly alleviated the pathological damage to lung tissues, restored the homeostasis of the lung, and enhanced the energy metabolism level of mice with syndrome of cold fluid accumulating in lung. In addition, A. forbesii planted under the two conditions reduced the content of interleukin-8(IL-8), interleukin-13(IL-13), tumor necrosis factor-α(TNF-α), and mucin 5AC(MUC5AC), increased the levels of interleukin-10(IL-10) and aquaporin 1(AQP1), lowered the expression of MMP9, VEGF, TGF-β, and MAPK3. In conclusion, the therapeutic effect of A. forbesii on the syndrome of cold fluid accumulating in lung was positively correlated with the degree of shading, and the chemical composition and efficacy of warming lung and resolving fluid retention were optimal under the conditions of NL20-NL40. This study can provide reference for the pharmacological research and cultivation of A. forbesii.
Animals ; Mice ; Lung/pathology* ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Light ; Cytokines/genetics* ; Humans

OBJECTIVES: This study aimed to investigate the impact of foam macrophages (FMs) on the intracellular survival of Mycobacterium tuberculosis (MTB) and identify the molecular mechanisms influencing MTB survival. METHODS: An in vitro FM model was established using oleic acid induction. Transcriptomic and metabolomic analyses were conducted to identify the key molecular pathways involved in FM-mediated MTB survival. RESULTS: Induced FMs effectively restricted MTB survival. Transcriptomic and metabolomic profiling revealed distinct changes in gene and metabolite expression in FMs during MTB infection compared with normal macrophages. Integrated analyses identified significant alterations in the cyclic adenosine monophosphate (cAMP) signaling pathway, indicating that its activation contributes to the FM-mediated restriction of MTB survival. CONCLUSIONS FMs inhibit MTB survival. The cAMP signaling pathway is a key contributor. These findings enhance the understanding of the role of FMs in tuberculosis progression, suggest potential targets for host-directed therapies, and offer new directions for developing diagnostic and therapeutic strategies against tuberculosis.
Mycobacterium tuberculosis/physiology* ; Transcriptome ; Metabolomics ; Foam Cells/microbiology* ; Humans ; Metabolome ; Tuberculosis/microbiology* ; Gene Expression Profiling

BACKGROUND: The clinical impact of post-percutaneous coronary intervention (PCI) quantitative flow ratio (QFR) in patients treated with PCI for chronic total occlusion (CTO) was still undetermined. METHODS: All CTO vessels treated with successful anatomical PCI in patients from PANDA III trial were retrospectively measured for post-PCI QFR. The primary outcome was 2-year vessel-oriented composite endpoints (VOCEs, composite of target vessel-related cardiac death, target vessel-related myocardial infarction, and ischemia-driven target vessel revascularization). Receiver operator characteristic curve analysis was conducted to identify optimal cutoff value of post-PCI QFR for predicting the 2-year VOCEs, and all vessels were stratified by this optimal cutoff value. Cox proportional hazards models were employed to calculate the hazard ratio (HR) with 95% CI. RESULTS: Among 428 CTO vessels treated with PCI, 353 vessels (82.5%) were analyzable for post-PCI QFR. 31 VOCEs (8.7%) occurred at 2 years. Mean value of post-PCI QFR was 0.92 ± 0.13. Receiver operator characteristic curve analysis shown the optimal cutoff value of post-PCI QFR for predicting 2-year VOCEs was 0.91. The incidence of 2-year VOCEs in the vessel with post-PCI QFR < 0.91 (n = 91) was significantly higher compared with the vessels with post-PCI QFR ≥ 0.91 (n = 262) (22.0% vs. 4.2%, HR = 4.98, 95% CI: 2.32-10.70). CONCLUSIONS Higher post-PCI QFR values were associated with improved prognosis in the PCI practice for coronary CTO. Achieving functionally optimal PCI results (post-PCI QFR value ≥ 0.91) tends to get better prognosis for patients with CTO lesions.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.