Based on the theory of 'spleen governing the containment of blood' in The Classic of Difficult Issues （《难经》）， it is proposed that medication toxicity damaging the middle jiao （焦） and failure of the spleen to contain blood constitute the core pathogenesis of cancer therapy induced thrombocytopenia （CTIT）. It is believed that the anti-tumor drug toxicity directly hits middle jiao， leading to spleen qi depletion， impairment of transportation and transformation， and insufficiency of the source of blood production. Consequently， the vessels and collaterals are deprived of nourishment and become structurally damaged. Blood fails to be contained and stored within the vessels， resulting in extravasation beyond the vascular system. Persistent retention of drug toxicity may further cause stasis due to blood deviating from its normal pathway and gradually consume the essence. In view of this root deficiency with branch excess， it is proposed that the treatment should focus on fortifying spleen， boosting qi and containing blood， with the aim of restoring spleen and stomach transportation functions， repairing vascular damage， and recovering the spleen's blood-containing function. According to individual syndrome patterns， prescriptions may be supplemented with herbs that stabilize vessels and consolidate collaterals， remove stasis and promote regeneration， and replenish essence and nourish marrow， providing new perspectives for the prevention and treatment of CTIT with traditional Chinese medicine.

RNA-based gene therapy has been widely used for various diseases, and extensive studies have proved that suitable delivery routes greatly help the development of RNA therapeutics. Identifying a safe and effective delivery system is key to realizing RNA therapeutics' clinical translation. Inhalation is a non-invasive pulmonary delivery modality that can enhance the retention of therapeutic agents in the lungs with negligible toxicity, thereby improving patient compliance. Inhaled RNA therapeutics are increasingly becoming an area of focus for researchers; however, only several clinical trials have explored inhaled delivery of RNA for pulmonary diseases. This review presents an overview of recent advances in inhaled delivery systems for RNA therapeutics, including viral and nonviral systems, highlighting state of the art regarding inhalation in the messenger RNA (mRNA) field. We also summarize the applications of mRNA inhalants in infectious and other lung diseases. Simultaneously, the research progresses on small interfering RNAs (siRNAs), antisense oligonucleotides (ASOs), and different types of RNA are also discussed to provide new strategies for developing RNA inhalation therapy. Finally, we clarify the challenges inhaled RNA-based therapeutics face before their widespread adoption and provide insights to help advance this exciting field to the bedside.

Sigma-1 receptor (σ ₁R) has become a focus point of drug discovery for central nervous system (CNS) diseases. A series of novel 1-phenylethan-1-one O-(2-aminoethyl) oxime derivatives were synthesized. In vitro biological evaluation led to the identification of 1a, 14a, 15d and 16d as the most high-affinity (K _i < 4 nmol/L) and selective σ ₁R agonists. Among these, 15d, the most metabolically stable derivative exhibited high selectivity for σ ₁R in relation to σ ₂R and 52 other human targets. In addition to low CYP450 inhibition and induction, 15d also exhibited high brain permeability and excellent oral bioavailability. Importantly, 15d demonstrated effective antipsychotic potency, particularly for alleviating negative symptoms and improving cognitive impairment in experimental animal models, both of which are major challenges for schizophrenia treatment. Moreover, 15d produced no significant extrapyramidal symptoms, exhibiting superior pharmacological profiles in relation to current antipsychotic drugs. Mechanistically, 15d inhibited GSK3β and enhanced prefrontal BDNF expression and excitatory synaptic transmission in pyramidal neurons. Collectively, these in vivo proof-of-concept findings provide substantial experimental evidence to demonstrate that modulating σ ₁R represents a potential new therapeutic approach for schizophrenia. The novel chemical entity along with its favorable drug-like and pharmacological profile of 15d renders it a promising candidate for treating schizophrenia.

Numerous studies on the formation and consolidation of memory have shown that memory processes are characterized by phase-dependent and dynamic regulation. Memory retrieval, as the only representation of memory content and an active form of memory processing that induces memory reconsolidation, has attracted increasing attention in recent years. Although the molecular mechanisms specific to memory retrieval-induced reconsolidation have been gradually revealed, an understanding of the time-dependent regulatory mechanisms of this process is still lacking. In this study, we applied a transcriptome analysis of memory retrieval at different time points in the recent memory stage. Differential expression analysis and Short Time-series Expression Miner (STEM) depicting temporal gene expression patterns indicated that most differential gene expression occurred at 48 h, and the STEM cluster showing the greatest transcriptional upregulation at 48 h demonstrated the most significant difference. We then screened the differentially-expressed genes associated with that met the expression patterns of those cluster-identified genes that have been reported to be involved in learning and memory processes in addition to dipeptidyl peptidase 9 (DPP9). Further quantitative polymerase chain reaction verification and pharmacological intervention suggested that DPP9 is involved in 48-h fear memory retrieval and viral vector-mediated overexpression of DPP9 countered the 48-h retrieval-induced attenuation of fear memory. Taken together, our findings suggest that temporal gene expression patterns are induced by recent memory retrieval and provide hitherto undocumented evidence of the role of DPP9 in the retrieval-induced reconsolidation of fear memory.
Animals ; Fear/physiology* ; Male ; Dipeptidyl-Peptidases and Tripeptidyl-Peptidases/genetics* ; Memory Consolidation/physiology* ; Time Factors ; Mental Recall/drug effects* ; Mice ; Gene Expression Profiling

Combined with elastic network model (ENM), the perturbation response scanning (PRS) has emerged as a robust technique for pinpointing allosteric interactions within proteins. Here, we proposed the PRS analysis of drug-target networks (DTNs), which could provide a promising avenue in network medicine. We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework, for drug repurposing of multiple sclerosis (MS). First, the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes. Then, based on topological analysis and functional annotation, the neurotransmission module was identified as the "therapeutic module" of MS. Further, perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis, giving a list of repurposable drugs for MS. Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of serotonin 2B receptor (HTR2B). Finally, we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex. These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS. As a useful systematic method, our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

OBJECTIVE: To assess health equity in the Yangtze River region to improve understanding of the correlation between hand, foot, and mouth disease (HFMD) and socioeconomic factors. METHODS: From 2014-2016, data on HFMD incidence, population statistics, economic indicators, and meteorology from 26 cities along the Yangtze River were analyzed. A multi-city random-effects meta-analysis was performed to study the relationship between temperature and HFMD transmission, and health equity was assessed with respect to socio-economic impact. RESULTS: Over the study period, 919,458 HFMD cases were reported, with Shanghai (162,303) having the highest incidence and Tongling (5,513) having the lowest. Males were more commonly affected (male-to-female ratio, 1.49:1). The exposure-response relationship had an M-shaped curve, with two HFMD peaks occurring at 4 °C and 26 °C. The relative risk had two peaks at 1.30 °C (1.834, 95% CI: 1.204-2.794) and 31.4 °C (1.143, 95% CI: 0.901-1.451), forming an M shape, with the first peak higher than the second. The most significant impact of temperature on HFMD was observed between -2 °C and 18.1 °C. The concentration index (0.2463) indicated moderate concentration differences, whereas the Theil index (0.0418) showed low inequality in distribution. CONCLUSION The incidence of HFMD varied across cities, particularly with changes in temperature. Economically prosperous areas showed higher risks, indicating disparities. Targeted interventions in these areas are crucial for mitigating the risk of HFMD.
Female ; Humans ; Male ; China/epidemiology* ; Cities/epidemiology* ; Hand, Foot and Mouth Disease/transmission* ; Incidence ; Risk Factors ; Temperature

ObjectiveTo understand the infection characteristics of multidrug-resistant organisms (MDROs) in hospitalized patients in a tertiary sentinel hospital in Shanghai, so as to provide an evidence for the development of targeted prevention and control measures. MethodsData of MDROs strains and corresponding medical records of some hospitalized patients in a hospital in Shanghai from 2021 to 2023 were collected, together with an analysis of the basic information, clinical treatment, underlying diseases and sources of sample collection. ResultsA total of 134 strains of MDROs isolated from hospitalized patients in this hospital were collected from 2021 to 2023 , including 63 strains of methicillin-resistant Staphylococcus aureus (MRSA), 57 strains of carbapenem-resistant Acinetobacter baumannii (CRAB), and 14 strains of carbapenem-resistant Klebsiella pneumoniae (CRKP). Of the 134 strains, 30 strains were found in 2021, 47 strains in 2022 and 57 strains in 2023. The male-to-female ratio of patients was 2.05∶1, with the highest percentage (70.90%) in the age group of 60‒<90 years. The primary diagnosis was mainly respiratory disease, with lung and respiratory tract as the cheif infection sites. There was no statistically significant difference in the distribution of strains between different genders and infection sites (P>0.05). However, the differences in the distribution of strains between different ages and primary diagnosis were statistically significant (P<0.05). Patients who were admitted to the intensive care unit (ICU), had urinary tract intubation, were not artery or vein intubated, were not on a ventilator, were not using immunosuppresants or hormones, and were not applying radiotherapy or chemotherapy were in the majority. There was no statistically significant difference in the distribution of strains for whether received radiotherapy or chemotherapy or not (P>0.05), while the differences in the distribution of strains with ICU admission history, urinary tract intubation, artery or vein intubation, ventilator use, and immunosuppresants or hormones use or not were statistically significant (all P<0.05). The type of specimen was mainly sputum, the hospitalized ward was mainly comprehensive ICU, the sampling time was mainly in the first quarter throughout the year, the number of underlying diseases was mainly between 1 to 2 kinds, the application of antibiotics ≥4 kinds, and those who didn’t receive any surgery recently accounted for the most. There were statistically significant differences in the distribution of strains between different specimen types, wards occupied and history of ICU stay (P<0.05), but no statistically significant difference in the distribution of strains between different sampling times, number of underlying diseases and types of antibiotics applied (P>0.05). ConclusionThe situation of prevention and control on MDROs in this hospital is still serious. Focus should be placed on high-risk factors’ and infection monitoring and preventive measures should be strengthened to reduce the incidence rate of MDROs infection.

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:Exercise as a form of active rehabilitation can improve the dysfunction caused by peripheral nerve injury,and different exercise modalities target different lesion sites and recovery mechanisms. OBJECTIVE:To comprehensively analyze the application and mechanisms of different exercise modalities in functional recovery from peripheral nerve injury. METHODS:A computerized search was conducted in PubMed and CNKI databases for relevant literature published before January 2024.The search terms used were"peripheral nerve injury,spinal cord,exercise,cerebral cortex,muscle atrophy,mirror therapy,blood flow restriction training"in both English and Chinese.Finally,77 articles were included for review. RESULTS AND CONCLUSION:Peripheral nerve injury can cause systemic pathological changes such as skeletal muscle atrophy,corresponding spinal cord segmental lesions,and sensorimotor cortex remodeling.Aerobic exercise can improve dysfunction by enhancing the immune response,promoting glial cell polarization,and promoting the release of nerve growth factor.Blood flow restriction exercise can regulate the secretion of muscle growth factor,promote muscle growth and enhance muscle strength.Mirror movement has a good effect in activating the cerebral cortex and reducing cortical remodeling.Different exercise modalities have potential benefits in functional recovery after peripheral nerve injury;however,there are still some problems and challenges,such as the choice of exercise modalities,the control of exercise intensity and frequency,and the detailed analysis of mechanisms.