Objective To systematically analyze the literature characteristics of Journal of Organ Transplantation since its inception. Methods Using the China National Knowledge Infrastructure (CNKI) academic journal full-text database as the data source, all articles published in the Journal of Organ Transplantation from January 2010 to August 2025 were retrieved. After excluding non-academic papers, a total of 1 568 research papers were included. R language 4.3.0, Bibliometrix package 3.2.1, and Citespace software were used to analyze the number of publications, publishing institutions, authors, keywords and other aspects. Results The number of publications in Journal of Organ Transplantation increased from an average of 82 articles per year in the early years after its inception to 113 articles per year in recent years, a growth of 37.8%. The geographical distribution of publishing institutions covers 32 provinces, cities and autonomous regions nationwide, mainly concentrated in the South China, East China and North China regions, and has now basically covered the central and western regions in recent years. The author collaboration network includes 45 authors distributed across 7 major collaboration clusters, forming a stable multi-level national research system centered on key university-affiliated hospitals. The high-frequency keywords are dominated by "liver transplantation" (425 times) and "kidney transplantation" (396 times). The theme evolution shows a clear three-stage characteristic: initially focusing on clinical technology application, deepening to immune mechanism exploration in the middle stage, and recently (since 2022) focusing on cutting-edge research areas such as xenotransplantation. Conclusions Journal of Organ Transplantation has witnessed the rapid development of China's organ transplantation cause, fully reflecting the research status and trends in China's organ transplantation field, and has provided an important platform for the future development and international cooperation in China's organ transplantation field.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

The plants of the genus Caragana Fabr. are desert plants of the Leguminosae family, which are widely used in traditional ethnomedicine, with the effects of nourishing Yin and nourishing blood, dispelling wind and removing dampness, clearing heat and detoxifying toxins. The anti-inflammatory effect of Caragana Fabr. has attracted much attention, the research on the related mechanism has made some progress, but it lacks systematic collation. By summarising the anti-inflammatory effects of the active ingredients of Caragana Fabr., the authors found that they have good anti-inflammatory activities on different inflammatory cell models in vitro, and have good improvement effects on rheumatoid arthritis, colitis, complex nephritis, and acute lung injury and other disease models. The anti-inflammatory effects of the active components of this genus mainly include the reduction of the levels of a variety of pro-inflammatory factors, and the signalling pathways involved mainly include TLR4/NF-κB, TLR4/MAPK, TLR4/NF-κB/IRF3, JAK/STAT-1, ERK/STAT-1 and so on. Therefore, the paper mainly reviews the research progress on the anti-inflammatory effects and mechanisms of the Caragana Fabr. plants and their active components according to disease types, with a view to providing reference for the in-depth study of their anti-inflammatory activities and the development of new products with related functions.

ObjectiveTo find out whether there is any difference in the monitoring results of mosq-ovitraps placed in different orientations in multi-storey residential areas, so as to provide a scientific basis for routine and emergency monitoring of Aedes albopictus with mosq-ovitraps in residential areas. MethodsFrom July 6th to October 26th 2023, one mosquito ovitrap was set up in each of the 4 orientations of east, south, west and north around the buildings in a multi-storey residential area in Jinhui Town, Fengxian District, Shanghai. Data was collected and recorded 72 hours after placement. The chi-square test was used to compare the mosquito ovitrap indices (MOIs) of two independent samples, and the Kruskal⁃Wallis H test was used to compare the MOIs of multiple independent samples. ResultsAfter 16 weeks of surveillance, 997 mosquito ovitraps were recovered, of which 211 were positive, with the mosquito ovitrap index (MOI) of 21.16% and the Aedes albopictus density index of 1.03 mosquitoes·ovitrap^-1. The MOIs were higher in September (24.22%) and October (23.96%), and the MOIs in the west, south and north within the two months were all above 20.00%. From July to October, the MOIs in the east, west, south and north were 20.70%, 22.20%, 25.50% and 16.20%, respectively, and the difference in MOIs among the 4 orientations was not statistically significant (χ²=6.647, P=0.084). Stratified analysis by month showed that in August, the south side of the multi-storey residential areas had the highest MOI (31.30%), the north side had the lowest MOI (1.30%), and there was a statistically significant difference in MOI in the east, west, south and north (χ²=25.986, P<0.001). In October, the MOI in the west was the highest (33.30%) and the MOI in the east was the lowest (6.30%), the difference in MOIs of the 4 orientations was statistically significant (χ²=12.007, P=0.007). The MOIs in the south side of the building in the outskirts of the residential area from the 1st week in July to the 4th week in October was lower (19.20%) than that in the south side of the inner building (31.70%), and the difference in MOI was statistically significant (χ²=5.118, P=0.024). ConclusionThe study of MOI in different orientations in a multi-storey residential area is a preliminary exploration based on field work, and the results show that there is a difference in MOIs in different orientations during the peak breeding period of mosquitoes. Further indicators such as temperature, humidity and wind speed in different orientations can be collected to explore the influencing factors of MOIs.

ObjectiveGliomas in the motor functional area can damage the corticospinal tract (CST), leading to motor dysfunction. Currently, there is a lack of unified methods for evaluating the extent of CST damage, especially in patients with high surgical risk where the minimum distance from the lesion to the CST is less than 10 mm. This study aims to further clarify the classification method and clinical significance of CST morphological changes in these patients. MethodsThis retrospective study analyzed 109 high-risk functional area glioma patients who underwent neurosurgical treatment with preoperative diffusion tensor imaging (DTI) imaging and intraoperative neurostimulation guidance between 2014 and 2024. All patients had a lesion-to-tract distance (LTD) of less than 10 mm between the CST and the lesion. Preoperative DTI evaluation of CST involvement-induced morphological changes were reviewed. Patients were divided into 3 groups: 17 cases (15.6%) with symmetric CST morphology compared to the healthy side (CST symmetry), 48 cases (44.0%) with significant CST morphology changes compared to the healthy side (CST deformation), and 44 cases (40.4%) with CST overlap with the tumor (CST overlap). Then we classified patients according to preoperative assessment of tumor-induced morphological changes, and analyze postoperative motor function for each category. ResultsPostoperative pathology showed a significantly higher proportion of high-grade gliomas (HGG) in the CST overlap group compared to the other two groups (P=0.001). Logistic regression analysis showed that CST overlap was a predictor of HGG (P=0.000). The rate of total tumor resection in the CST deformation group and overlap group was lower than in the CST symmetric group (P=0.008). There was a total of 41 postoperative hemiplegic patients, with 4 cases (23.5%) in the CST symmetric group, 11 cases (22.9%) in the CST deformation group, and 26 cases (59.1%) in the CST overlap group. CST overlap with the tumor predicted postoperative hemiplegia (P=0.016). Two-way ANOVA analysis of the affected/healthy side and CST morphology groups showed significant main effects of CST grouping and healthy-affected side (P=0.017 and P=0.010), with no significant interaction (P=0.31). The fractional anisotropy (FA) value in the CST overlap group and the affected side was lower. A decrease in the FA value on the affected side predicted postoperative hemiplegia (sensitivity 69.2%, specificity 71.9%). ConclusionWe have established a method to predict postoperative hemiplegia in high-risk motor functional area glioma patients based on preoperative CST morphological changes. CST overlap leads to a decrease in CST FA values. This method can be used for precise patient management and aid in accurate preoperative surgical planning.

OBJECTIVE To study the safety of Shuangshu decoction in rats and its efficacy in improving functional dyspepsia （FD） in rats. METHODS In safety test， 40 rats were divided into blank control group， Shuangshu decoction low-dose， medium- dose and high-dose groups [108， 216， 324 g/（kg·d）， calculated by raw medicine， the same applies below]； they were given relevant medicine intragastrically， for continuous 14 days. The mortality and toxic reactions of rats were recorded， and the organ indexes of the liver， kidney， spleen， lung and heart of rats were calculated； the pathological morphological changes in the liver， kidney， spleen， lung， heart， stomach， duodenum， and colon were observed to evaluate the acute toxicity of Shuangshu decoction. Another 40 rats were grouped and administered in the same way for 30 consecutive days. The mortality and toxic reactions of the rats were recorded， and the corresponding organ indexes were calculated. The pathological morphological changes in the corresponding organs were observed， and blood routine and serum biochemical indicators were measured， in order to assess the subacute toxicity of Shuangshu decoction. In pharmacodynamic experiments: 50 rats were divided into blank control group， model group， and Shuangshu decoction low-， medium-， and high-dose groups （9.45， 18.9， 37.8 g/kg）， with 10 rats in each group. Except for blank control group， rats in all other groups were used to establish the FD rat model by subcutaneous injection of loperamide （3.5 mg/kg）. Rats in each group were administered the corresponding drug solution/normal saline intragastrically， once a day， for 14 consecutive days. After the last medication， fecal moisture content， intestinal propulsion rate， gastric emptying rate and serum level of motilin were all detected， and interstitial cell of Cajal （ICC） ultrastructure of rats was observed in colon tissue. RESULTS The safety experiments showed that no death occurred in each dose group， and no significant difference was found in organ coefficient， routine blood and serum biological index， compared to blank control group （P＞0.05）； no abnormality was found in organ appearance and pathological sections. The results of the pharmacodynamic experiments showed that， compared with the blank control group， the fecal moisture content， gastric emptying rate， intestinal propulsion rate， and serum motilin levels in the model group were significantly decreased （P＜0.05）； in the colonic tissue， the mitochondria in the ICC exhibited severe swelling with the disappearance of cristae， and the endoplasmic reticulum was dilated. Compared with model group， the rats in Shuangshu decoction high-dose group showed significant increases in the above quantitative indicators （P＜ 0.05）； additionally， there was a large number of mitochondria in the ICC of the colonic tissue， with clear cristae and regular arrangement. CONCLUSIONS Shuangshu decoction is safe and has a beneficial improving effect on FD rats； its mechanism of action may be related to the regulation of gastrointestinal hormone expression to promote gastric emptying and intestinal propulsion， as well as the repair of mitochondrial structure in ICCs to restore gastrointestinal function.

ObjectiveTo improve the quality and service performance of community visual health services in Shanghai, and to establish a set of reasonable and effective evaluation index system for community visual health services. MethodsCentered on the national and Shanghai-based visual health policies and based on the current status and development trends of community visual health service program in Shanghai, the candidate indicators were formed through literature review and expert interviews, firstly. The framework of an evaluation index system was formulated through qualitative research successively, which was further revised and perfected using the Delphi method. Coefficient weights were calculated using the analytic hierarchy process (AHP), culminating in the establishment of the community visual health evaluation index system, lastly. ResultsA total of 22 visual health experts from district-level center for disease control, hospital ophthalmology and leaders in charging of visual health service in community health centers participated in the Delphi questionnaire survey, with a questionnaire recovery rate of 100% and an expert authority coefficient of 0.86, indicating high credibility. After a round of correspondence to experts’ importance ratings and discussions, a comprehensive evaluation index system comprising 3 primary indicators, 12 secondary indicators, and 47 tertiary indicators, along with 5 additional indicators, was finalized. ConclusionAn index system tailored to effective evaluation for community visual health initiatives was drawn up in this study, which can promote the capacity building in community eye health services, facilitating the high-quality development of visual health courses, and enhancing residents’ eye health.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

Objective: To investigate the distribution of IgM anti-A/B titers among group O whole blood donors in Jiangsu, establish a low-titer threshold, and analyze the demographic characteristics of low-titer donors, so as to provide data for recruiting low-titer group O whole blood (LTOWB) donors. Methods: Plasma samples from 1 009 group O whole blood donors were tested for IgM anti-A and anti-B titers using the microplate technique. The distribution of antibody titers was analyzed to establish a low-titer threshold. The distribution trends of titers across different demographic groups were also analyzed. Results: The peak titer for anti-A, anti-B were 64 (31.5%), 4 (23.8%), respectively, The proportion of donors with both anti-A and anti-B titers below 64 was 97.3% (982/1 009). The mean anti-A titer was higher than anti-B titer. Anti-A titers were higher in female donors than in male donors (P<0.05). The anti-A titers differed significantly among different age groups (P<0.05). However, no significant difference in titers was observed based on the number of donations (P>0.05). Conclusion: A titer of 64 can be used as the reference threshold of LTOWB in Jiangsu. Male donors of appropriate age are more suitable than female donors for establishing an emergency panel of LTOWB mobile donors.