GPR126, also known as ADGRG6, is one of the most deeply studied aGPCRs. Initially, GPR126 was thought to be a receptor associated with muscle development and was primarily expressed in the muscular and skeletal systems. With the deepening of research, it was found that GPR126 is expressed in multiple mammalian tissues and organs, and is involved in many biological processes such as embryonic development, nervous system development, and extracellular matrix interactions. Compared with other aGPCRs proteins, GPR126 has a longer N-terminal domain, which can bind to ligands one-to-one and one-to-many. Its N-terminus contains five domains, a CUB (complement C1r/C1s, Uegf, Bmp1) domain, a PTX (Pentraxin) domain, a SEA (Sperm protein, Enterokinase, and Agrin) domain, a hormone binding (HormR) domain, and a conserved GAIN domain. The GAIN domain has a self-shearing function, which is essential for the maturation, stability, transport and function of aGPCRs. Different SEA domains constitute different GPR126 isomers, which can regulate the activation and closure of downstream signaling pathways through conformational changes. GPR126 has a typical aGPCRs seven-transmembrane helical structure, which can be coupled to Gs and Gi, causing cAMP to up- or down-regulation, mediating transmembrane signaling and participating in the regulation of cell proliferation, differentiation and migration. GPR126 is activated in a tethered-stalk peptide agonism or orthosteric agonism, which is mainly manifested by self-proteolysis or conformational changes in the GAIN domain, which mediates the rapid activation or closure of downstream pathways by tethered agonists. In addition to the tethered short stem peptide activation mode, GPR126 also has another allosteric agonism or tunable agonism mode, which is specifically expressed as the GAIN domain does not have self-shearing function in the physiological state, NTF and CTF always maintain the binding state, and the NTF binds to the ligand to cause conformational changes of the receptor, which somehow transmits signals to the GAIN domain in a spatial structure. The GAIN domain can cause the 7TM domain to produce an activated or inhibited signal for signal transduction, For example, type IV collagen interacts with the CUB and PTX domains of GPR126 to activate GPR126 downstream signal transduction. GPR126 has homology of 51.6%-86.9% among different species, with 10 conserved regions between different species, which can be traced back to the oldest metazoans as well as unicellular animals.In terms of diseases, GPR126 dysfunction involves the pathological process of bone, myelin, embryo and other related diseases, and is also closely related to the occurrence and development of malignant tumors such as breast cancer and colon cancer. However, the biological function of GPR126 in various diseases and its potential as a therapeutic target still needs further research. This paper focuses on the structure, interspecies differences and conservatism, signal transduction and biological functions of GPR126, which provides ideas and references for future research on GPR126.

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.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Rare diseases have a significant and profound impact on society, the economy, and the healthcare system. The path to developing drugs for rare diseases is particularly arduous. Due to the small number of patients and limited market demand, pharmaceutical companies don′t have enough incentives and resources to invest in drug research and development. Additionally, the long development cycles, high costs, and high risks have led to a number of potential therapeutic drug failures at the early stages of development. This article summarizes a series of encouraging policies adopted by the National Medical Products Administration for rare diseases, which is an important public health issue, as well as the achievements in the review and approval of rare disease drugs in recent years. These policies have accelerated the approval process. Meanwhile, the policies ensure the safety and effectiveness of drugs and offer more treatment options and hopes to patients with rare diseases. With the continuous effort at optimizing the policy environment and the advancement of research and development technologies, China′s drug regulatory authorities will continue to focus on the clinical needs of rare diseases, to implement " patient-centered " approach to drug development, inject new vitality into the research and development of drugs of rare diseases, and offer more precise and effective treatment choices for patients with rare diseases.

Nephrotic syndrome (NS) has a variety of classifications, pathogenesis and pathological types. Clinical diagnosis primarily relies on serum biochemistry, while the specific classification necessitates renal puncture for biopsy, which is hindered by poor patient compliance. Therefore, it is of great significance for clinical diagnosis to find a non-invasive and rapid method to reflect the classification and progression of nephrotic syndrome. In this study, LC-MS metabolomics combined with receiver operating characteristic (ROC) and multiple linear regression analysis was used to screen and identify potential biomarkers capable of reflecting the typing and progression of nephrotic syndrome. According to the statistical parameters VIP>1, P<0.05 and AUC>0.5 obtained from the orthogonal partial least squares discriminant analysis (OPLS-DA) model, five potential classification markers were screened to distinguish membranous nephropathy (MN) from IgA nephropathy (IgAN), including indoleacetic acid, isoleucine proline, DL-indole-3-lactic acid, D-phenylalanine and L-tryptophan. Furthermore, using estimated glomerular filtration rate (eGFR) as the dependent variable, a multiple linear regression analysis was conducted to identify the potential progression markers capable of reflecting the progression of MN to uremia. These metabolites included alanylleucine, 9-capryloylcarnitine, gluconic acid, caprylyl glycine and sebacic acid. Potential markers of progression of IgA nephropathy to uremia comprised alanylleucine, 9-capryloylcarnitine, caprylyl glycine, and sebacic acid. This study provides a theoretical basis for the discovery of potential classification and progression biomarkers of kidney disease, and also offers a methodological reference for future research in this area. The protocol was approved by the Ethics Committee of Shanxi Provincial People's Hospital [(2020) Provincial Medical Ke Lun Shen Zi No. 30].

In this study, we investigated the anti-inflammatory effect and mechanism of tilianin in lipopolysaccharide (LPS)-induced RAW264.7 cells. The cell viability was detected by cell counting kit-8 (CCK-8) assay. The content of tumor necrosis factor α (TNF-α) and interleukin-6 (IL-6) were detected by enzyme-linked immuno sorbent assay (ELISA) kits. The content of nitric oxide (NO) was assayed by Griess reagent method. The level of intracellular reactive oxygen species (ROS) was detected by 2',7'-dichlorodihydrofluorescein diacetate (DCFH-DA) fluorescent probe. The protein levels of Toll like receptor 4 (TLR4), myeloid differentiation primary response gene 88 (Myd88), nuclear factors κB p65 (NF-κB p65), phosphorylated nuclear factor κB p65 (p-NF-κB p65), nuclear factor κB inhibitory protein α (IκBα) and phosphorylation nuclear factor κB inhibitory protein α (p-IκBα) were detected by Western blot. The mRNA and protein levels of NLRP3, pro-IL-1β, pro-IL-18 and pro-caspase-1 were detected by qRT-PCR and Western blot. Immunofluorescence staining was used to detect the nuclear translocation of NF-κB p65. The effect of tilianin on the TLR4/Myd88/NF-κB signaling pathway was further validated by using the TLR4 signaling inhibitor restatorvid (TAK242). The results showed that tilianin significantly reduced the levels of TNF-α, IL-6 and NO in the supernatant of RAW264.7 cells and decreased the content of intracellular ROS. Tilianin reduced the levels of TLR4, Myd88, p-NF-κB p65 and p-IκBα protein and nuclear translocation of NF-κB p65. Tilianin could reduce the protein levels of NLRP3, pro-IL-1β, pro-IL-18 and pro-caspase-1. Tilianin significantly inhibited the mRNA levels of NLRP3 and pro-IL-1β. The above research results indicated that tilianin could significantly alleviate the LPS-induced inflammatory response in RAW264.7 cells and its mechanism might be related to downregulate the TLR4/Myd88/NF-κB signaling pathway to inhibit NLRP3 inflammasome.

Objective To clarify the effects of 5G mobile phone radiofrequency radiation exposure on male mouse fertility and to preliminarily explore the underlying mechanisms. Methods Healthy male C57BL/6 mice aged 7-8 weeks were randomly assigned to Sham group, 3.5 GHz radiofrequency radiation group, and 4.9 GHz radiofrequency radiation group, with 16 mice in each group. The mice were exposed to 3.5 GHz or 4.9 GHz mobile phone radiofrequency radiation for 42 consecutive days (1 h per day). The sperm quality was evaluated using sperm count, deformity rate, and motility. H&E staining was performed to assess testicular tissue structure by observing the morphology of spermatogenic cells at various development stages, the diameter of seminiferous tubules, and the thickness of seminiferous epithelium. The sperm mitochondrial function was assessed using sperm mitochondrial membrane potential and testicular ATP content. The fertility of mice was evaluated through fertility rate, litter size, and survival rate of offspring. The underlying mechanisms were explored by detecting the methylation of LRGUK gene and its mRNA and protein levels. Results Compared with the Sham group, there were no significant changes in sperm count in the 3.5 GHz and 4.9 GHz groups; however, the sperm abnormality rate significantly increased (P < 0.05) and sperm motility significantly decreased (P < 0.05). The structure of testicular tissue, the function of sperm mitochondria, and fertility of mice showed no significant changes as compared with the Sham group. The methylation level of LRGUK gene in the testes significantly increased, while the mRNA and protein expression levels significantly decreased. Conclusion Exposure to 3.5 GHz and 4.9 GHz mobile phone radiofrequency radiation for 42 consecutive days can lead to an increase in sperm deformity rate and a decrease in sperm motility in mice, but has no significant effect on fertility, which may be related to an increase in methylation level of the LRGUK gene in the testes.

Objective:To assess the current situation, advantages, and difficulties of standardized management in Investigator-Initiated Clinical Trials (IIT).Methods:This article summarized the requirements and policies for clinical research management, the development of clinical research domestically and internationally, the achievements and advantages of clinical research management development in China, and the main problems and difficulties with the standardized IIT management in China, and compiled the experiences and models of several medical institutions in IIT management.Results:While China has a large number of clinical medical publications and is ranked high in the world, the quality of the publications needs to be further improved. Domestic management requirements for IIT were gradually improving, providing a basis for medical institutions to implement standardized management throughout the lifecycle of IIT, and achieve certain progress. However, there were still challenges in the departmental divisions, the unification of management standards, whole-process management and quality control, the scientific review, high-risk project management, and registration.Conclusions:Drawing on the excellent experience of domestic medical institutions, measures including identifying a primary responsible department, establishing unified supervision and inspection standards, and implementing a whole life cycle management may help overcome the challenges in IIT management and improve the quality and efficiency of IIT management.