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.

Distinct from the complementary inhibition mechanism through binding to the target with three-dimensional conformation of small molecule inhibitors, targeted protein degradation technology takes tremendous advantage of endogenous protein degradation pathway inside cells to degrade plenty of “undruggable” target proteins, which provides a novel route for the treatment of many serious diseases, mainly including proteolysis-targeting chimeras, lysosome-targeting chimeras, autophagy-targeting chimeras, antibody-based proteolysis-targeting chimeras, etc. Unlike proteolysis-targeting chimeras first found in 2001, which rely on ubiquitin-proteasome system to mainly degrade intracellular proteins of interest, lysosome-targeting chimeras identified in 2020, which was act as the fastly developing technology, utilize cellular lysosomal pathway through endocytosis mediated by lysosome-targeting receptor to degrade both extracellular and membrane proteins. As an emerging biomedical technology, nucleic acid-driven lysosome-targeting chimeras utilize nucleic acids as certain components of chimera molecule to replace with ligand to lysosome-targeting receptor or protein of interest, exhibiting broad application prospects and potential clinical value in disease treatment and drug development. This review mainly introduced present progress of nucleic acid-driven lysosome-targeting chimeras technology, including its basic composition, its advantages compared with antibody or glycopeptide-based lysosome-targeting chimeras, and focused on its chief application, in terms of the type of lysosome-targeting receptors. Most research about the development of nucleic acid-driven lysosome-targeting chimeras focused on those which utilized cation-independent mannose-6-phosphonate receptor as the lysosome-targeting receptor. Both mannose-6-phosphonate-modified glycopeptide and nucleic aptamer targeting cation-independent mannose-6-phosphonate receptor, even double-stranded DNA molecule moiety can be taken advantage as the ligand to lysosome-targeting receptor. The same as classical lysosome-targeting chimeras, asialoglycoprotein receptor can also be used for advance of nucleic acid-driven lysosome-targeting chimeras. Another new-found lysosome-targeting receptor, scavenger receptor, can bind dendritic DNA molecules to mediate cellular internalization of complex and lysosomal degradation of target protein, suggesting the successful application of scavenger receptor-mediated nucleic acid-driven lysosome-targeting chimeras. In addition, this review briefly overviewed the history of lysosome-targeting chimeras, including first-generation and second-generation lysosome-targeting chimeras through cation-independent mannose-6-phosphonate receptor-mediated and asialoglycoprotein receptor-mediated endocytosis respectively, so that a clear timeline can be presented for the advance of chimera technique. Meantime, current deficiency and challenge of lysosome-targeting chimeras was also mentioned to give some direction for deep progress of lysosome-targeting chimeras. Finally, according to faulty lysosomal degradation efficiency, more cellular mechanism where lysosome-targeting chimeras perform degradation of protein of interest need to be deeply explored. In view of current progress and direction of nucleic acid-driven lysosome-targeting chimeras, we discussed its current challenges and development direction in the future. Stability of natural nucleic acid molecule and optimized chimera construction have a great influence on the biological function of lysosome-targeting chimeras. Discovery of novel lysosome-targeting receptors and nucleic aptamer with higher affinity to the target will greatly facilitate profound advance of chimera technique. In summary, nucleic acid-driven lysosome-targeting chimeras have many superiorities, such as lower immunogenicity, expedient synthesis of chimera molecules and so on, in contrast to classical lysosome-targeting chimeras, making it more valuable. Also, the chimera technology provides new ideas and methods for biomedical research, drug development and clinical treatment, and can be used more widely through further research and optimization.

Objective To investigate the relationship between brain white matter lesions (WML) and triglyceride glucose (TyG) index in non-diabetic elderly individuals based on magnetic resonance imaging. Methods A total of 523 non-diabetic elderly individuals aged ≥ 60 years were selected from Jinan, Shandong Province, China from June 2018 to December 2019. According to the quartiles of TyG index, there were 133 participants in the first quartile (Q1) group, 127 in the second quartile (Q2) group, 132 in the third quartile (Q3) group, and 131 in the fourth quartile (Q4) group. All participants underwent brain magnetic resonance imaging to evaluate paraventricular, deep, and total WML volumes, as well as Fazekas scores. Results Compared with Q1, Q2, and Q3 groups, Q4 group showed significant increase in periventricular, deep, and total WML volumes (P < 0.05). The proportion of participants with a Fazekas score ≥ 2 in the periventricular, deep, and total WML was higher in the Q4 group compared with the Q1 and Q2 groups (P < 0.05). The proportion of participants with a Fazekas score ≥ 2 in deep WML was higher in Q4 group than in Q3 group (P < 0.05). TyG index was significantly positively correlated with periventricular, deep, and total WML volumes (r = 0.401, 0.405, and 0.445, P < 0.001). After adjusting for confounding factors, TyG index was still significantly positively correlated with periventricular, deep, and total WML volumes (P < 0.001). Logistic regression analysis showed that compared with Q1 group, the risk of Fazekas score ≥ 2 in periventricular WML was 1.950-fold (95% confidence interval [CI]: 1.154-3.294, P = 0.013) in Q3 group and 3.411-fold (95% CI: 1.984-5.863, P < 0.001) in Q4 group, the risk of Fazekas score ≥ 2 in total WML was 2.529-fold (95%CI: 1.444-4.430, P = 0.001) in Q3 group and 4.486-fold (95%CI: 2.314-8.696, P < 0.001) in Q4 group. The risk of Fazekas score ≥ 2 in deep WML was 2.953-fold (95%CI: 1.708-5.106, P < 0.001) in Q4 group compared with Q1 group. Conclusion Increased TyG index is an independent risk factor for WML in non-diabetic elderly individuals.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

ObjectiveRecent studies have highlighted the critical role of NUDT19 in the initiation, progression, and prognosis of specific cancer types. However, its involvement in pan-cancer analysis has not been fully characterized. This study aims to systematically explore the expression patterns, clinical significance, and immune-related functions of NUDT19 in various cancer types through multi-omics analysis, further revealing its potential role in cancer, particularly its functional and therapeutic target value in leukemia. MethodsTo achieve this goal, various bioinformatics approaches were employed to evaluate the expression patterns, clinical significance, and immune-related functions of NUDT19 in tumors and normal tissues. Additionally, we analyzed the mutation characteristics of NUDT19 and its relationship with epigenetic modifications. Using the single-cell analysis tool SingleCellBase, we explored the distribution of NUDT19 across different cell subpopulations in tumors. To validate these findings, qRT-PCR was used to measure NUDT19 expression levels in specific tumor cell lines, and we established acute myeloid leukemia (AML) cell lines (HL-60 and THP-1) to conduct NUDT19 knockdown and overexpression experiments, assessing its effects on leukemia cell proliferation, apoptosis, and invasion. ResultsPan-cancer analysis revealed the dysregulated expression of NUDT19 across multiple cancer types, which was closely associated with poor prognosis, clinical staging, and diagnostic markers. Furthermore, NUDT19 was significantly correlated with tumor biomarkers, immune-related genes, and immune cell infiltration in different cancers. Mutation analysis showed that multiple mutations in NUDT19 were significantly associated with epigenetic changes. Single-cell analysis revealed the heterogeneity of NUDT19 expression in cancer cells, suggesting its potentially diverse functional roles in different cell subpopulations. qRT-PCR experiments confirmed the significant upregulation of NUDT19 in various tumor cell lines. In AML cell lines, NUDT19 knockdown led to reduced cell proliferation and invasion, with increased apoptosis, while NUDT19 overexpression significantly enhanced cell proliferation and invasion while reducing apoptosis. ConclusionThis study demonstrates the diverse roles of NUDT19 in various cancer types, with a particularly prominent functional role in leukemia. NUDT19 is not only associated with tumor initiation and progression but may also influence cancer progression through the regulation of immune microenvironment and epigenetic mechanisms. Our research highlights the potential of NUDT19 as a therapeutic target, particularly for targeted therapies in malignancies such as leukemia, with significant clinical application prospects.

Background::Carotid intima-media thickness (IMT) and diameter, stiffness, and wave reflections, are independent and important clinical biomarkers and risk predictors for cardiovascular diseases. The purpose of the present study was to establish nationwide reference values of carotid properties for healthy Chinese adults and to explore potential clinical determinants.Methods::A total of 3053 healthy Han Chinese adults (1922 women) aged 18-79 years were enrolled at 28 collaborating tertiary centers throughout China between April 2021 and July 2022. The real-time tracking of common carotid artery walls was achieved by the radio frequency (RF) ultrasound system. The IMT, diameter, compliance coefficient, β stiffness, local pulse wave velocity (PWV), local systolic blood pressure, augmented pressure (AP), and augmentation index (AIx) were then automatically measured and reported. Data were stratified by age groups and sex. The relationships between age and carotid property parameters were analyzed by Jonckheere-Terpstra test and simple linear regressions. The major clinical determinants of carotid properties were identified by Pearson’s correlation, multiple linear regression, and analyses of covariance.Results::All the parameters of carotid properties demonstrated significantly age-related trajectories. Women showed thinner IMT, smaller carotid diameter, larger AP, and AIx than men. The β stiffness and PWV were significantly higher in men than women before forties, but the differences reversed after that. The increase rate of carotid IMT (5.5 μm/year in women and 5.8 μm/year in men) and diameter (0.03 mm/year in both men and women) were similar between men and women. For the stiffness and wave reflections, women showed significantly larger age-related variations than men as demonstrated by steeper regression slopes (all P for age by sex interaction <0.05). The blood pressures, body mass index (BMI), and triglyceride levels were identified as major clinical determinants of carotid properties with adjustment of age and sex. Conclusions::The age- and sex-specific reference values of carotid properties measured by RF ultrasound for healthy Chinese adults were established. The blood pressures, BMI, and triglyceride levels should be considered for clinical application of corresponding reference values.

Acute mitral regurgitation(MR)in the setting of myocardial infarction(MI)may be the result of papillary muscle rupture(PMR).The clinical presentation can be catastrophic,with refractory cardiogenic shock.This condition is associated with high morbidity and mortality.Transcatheter edge-to-edge repair(TEER)has become increasingly common in treating severe mitral regurgitation.This case details a successful TEER is feasible and safe in patients with acute MR following MI.TEER is an emerging treatment option in this clinical scenario that should be taken into consideration.

Objective To monitor the antifungal resistance of clinical isolates of Candida spp.in the East China region.Methods MALDI-TOF MS or molecular methods were used to re-identify the strains collected from January 2018 to December 2022.Antifungal susceptibility testing was performed using the broth microdilution method.The susceptibility test results were interpreted according to the breakpoints of 2022 Clinical and Laboratory Standards Institute(CLSI)documents M27 M44s-Ed3 and M57s-Ed4.Results A total of 3 026 strains of Candida were collected,65.33％of which were isolated from sterile body sites,mainly from blood(38.86％)and pleural effusion/ascites(10.21％).The predominant species of Candida were Candida albicans(44.51％),followed by Candida parapsilosis complex(19.46％),Candida tropicalis(13.98％),Candida glabrata(10.34％),and other Candida species(0.79％).Candida albicans showed overall high susceptibility rates to the 10 antifungal drugs tested(the lowest rate being 93.62％).Only 2.97％of the strains showed dose-dependent susceptibility(SDD)to fluconazole.Candida parapsilosis complex had a SDD rate of 2.61％and a resistance rate of 9.42％to fluconazole,and susceptibility rates above 90％to other drugs.Candida glabrata had a SDD rate of 92.01％and a resistance rate of 7.99％to fluconazole,resistance rates of 32.27％and 48.24％to posaconazole and voriconazole non-wild-type strains(NWT),respectively,and susceptibility rates above 90％to other drugs.Candida tropicalis had resistance rates of 29.55％and 26.24％to fluconazole and voriconazole,respectively,resistance rates of 76.60％and 21.99％to posaconazole and echinocandins non-wild-type strains(NWT),and a resistance rate of 2.36％to echinocandins.Conclusions The prevalence and species distribution of Candida spp.in the East China region are consistent with previous domestic and international reports.Candida glabrata exhibits certain degree of resistance to fluconazole,while Candida tropicalis demonstrates higher resistance to triazole drugs.Additionally,echinocandins resistance has emerged in Candida albicans,Candida glabrata,Candida tropicalis,and Candida parapsilosis.

To understand the distribution of ticks in the Wuwei Region,enrich tick species data,and provide a basis for the prevention of tick-borne diseases,tick were collected using flagging and tick-picking methods during the highest activity period from April to September in 2021 and 2022 in the mountainous areas of Wuwei City.The ticks were identified based on morpho-logical and molecular biological characteristics,and characteristic sequences were obtained.A systematic evolutionary tree was constructed using the neighbor-joining method in MEGA 11.0 software.In total,7 342 ticks collected in Wuwei,which be-longed to 5 species from 4 genera with in the Ixodidae family,which included Dermacentor nuttalli,Hyalomma asiaticum,Ixodes canisuga,Haemaphysalis longicornis and Haema-physalis danieli.Ticks of the same species clustered together into the same branch of an evolutionary tree.In the Wuwei Re-gion,five common tick species are found across various habi-tats,with each habitat featuring different distributions of tick species and populations.The Dermacentor nuttalli is the dom-inant tick species in this area.

Objective:To analyze the distribution characteristics of prognostic factors affecting recurrence in peripheral T-cell lymphoma(PTCL)patients with different levels of histone deacetylase(HDAC)based on latent class analysis.Methods:112 PTCL patients who were treated in our hospital from September 2012 to September 2019 were selected and divided into recurrence group and non-recurrence group.The clinical data of the two groups of patients were compared.Multivariate logistic regression was used to analyze the risk factors for recurrence.Latent class analysis was used to compare the distribution characteristics of prognostic factors affecting recurrence between the high-risk group and the low-risk group.Results:There were 87 patients(77.68％)in recurrence group and 25 patients(22.32％)in non-recurrence group.The result of multivariate logistic regression showed that ECOG score ≥2,Ann Arbor stage Ⅲ-Ⅳ,IPI score＞2,bone marrow involvement,elevated serum β2-microglobulin(β2-MG),short-term efficacy not reaching complete remission(CR)or partial remission(PR),and the high expression of HDAC were all independent risk factors for recurrence in patients with PTCL(P＜0.05).The recurrence rate of patients with high HDAC levels was significantly higher than that of patiens with low HDAC levels(P＜0.05).The results of cluster analysis showed that the risk of recurrence was obviously clustered,and the patients could be divided into high recurrence risk group(HDAC＞5 points)and low recurrence risk group(HDAC≤5 points).The results of latent class analysis showed that patients with multiple risk factors account for a higher proportion in the high recurrence risk group,compared with the low recurrence risk group(P＜0.05).Conclusion:There are differences in recurrence rates among PTCL patients with different HDAC levels and in distribution characteristics of risk factors between high recurrence risk and low recurrence risk groups.