Objective To investigate the species of sandflies and the prevalence of Leishmania infections in sandflies from selected areas of northern and northwestern China, so as to provide insights into identification of leishmaniasis vectors and assessment of epidemiological trends of leishmaniasis in China. Methods Sandfly samples were collected from Mentougou District of Beijing Municipality, Xiangning County in Linfen City of Shanxi Province, Ejin Banner in Alxa League of Inner Mongolia Autonomous Region, and Payzawat County of Karamay District of Karamay City, Gaochang District of Turpan City in Xinjiang Uygur Autonomous Region from July 2023 to July 2024. Approximately 100 intact female sandfly samples were randomly selected from each site and the species of sandflies was identified according to morphological characteristics and molecular assays. Female sandflies originating from the same habitat were grouped into pools of 10 individuals. Leishmania infection was detected using polymerase chain reaction (PCR) assay targeting the internal transcribed spacer 1 (ITS-1) gene, and the prevalence of Leishmania infection was calculated in sandflies from different sampling sites using the minimum infection rate (MIR) method. In addition, positive amplicons were sequenced and subjected to phylogenetic analysis. Results A total of 6 155 sandflies were collected from different environments at sampling sites across the six aforementioned regions from July 2023 to July 2024. Phlebotomus chinensis (96.00%) was the dominant sandfly species in Mentougou District, Beijing Municipality, with a small proportion of Ph. sergenti (4.00%), and only Ph. chinensis was found in Xiangning County, Linfen City, Shanxi Province. Ph. wui was the only sandfly species detected in Ejin Banner, Alxa League, Inner Mongolia Autonomous Region, and Payzawat County, Kashgar City, Xinjiang Uygur Autonomous Region, and Ph. caucasicus (97.70%) was the dominant sandfly species in Karamay District, Karamay City, Xinjiang Uygur Autonomous Region, with a small proportion of Ph. wui (2.30%), while Ph. alexandri was the only species in Gaochang District, Turpan City, Xinjiang Uygur Autonomous Region. A total of 40, 60, 34, 18, 18, and 22 pools of sandfly samples were tested from Mentougou District in Beijing Municipality, Xiangning County in Linfen City of Shanxi Province, Ejin Banner in Alxa League of Inner Mongolia Autonomous Region, Payzawat County in Kashgar City, Karamay District in Karamay City, and Gaochang District in Turpan City of Xinjiang Uygur Autonomous Region, respectively. L. infantum was detected in Ph. chinensis samples from Mentougou District in Beijing Municipality, and Xiangning County of Linfen City in Shanxi Province, with MIR of 0.25% to 1.00%, and L. donovani was detected in Ph. wui from Ejin Banner in Alxa League of Inner Mongolia Autonomous Region, and Payzawat County in Kashgar City of Xinjiang Uygur Autonomous Region, with MIR of 0.56% to 0.88%; however, no Leishmania infection was detected in Ph. caucasicus from Karamay District in Karamay City or Ph. alexandri from Gaochang District in Turpan City of Xinjiang Uygur Autonomous Region. Phylogenetic analysis showed that the Leishmania ITS-1 gene sequences obtained from Mentougou District in Beijing Municipality and Xiangning County in Linfen City of Shanxi Province were clustered into the same clade with the reference sequences of L. infantum ITS-1 gene, while the Leishmania ITS-1 gene sequences obtained from Ejin Banner in Alxa League of Inner Mongolia Autonomous Region and Payzawat County in Kashgar City of Xinjiang Uygur Autonomous Region were clustered into the same clade with the reference sequences of L. donovani ITS-1 gene. Conclusions There are variations in sandfly species in selected areas of northern and northwestern China, and variations in the species of Leishmania infecting sandflies. Improved surveillance of sandfly vectors and targeted control strategies with adaptations to geographical features and leishmaniasis vectors are recommended.

ObjectiveThis study employs a special conformational engineering (CE) technology to construct an α-chymotrypsin-like active center, which includes a catalytic triad, an oxyanion hole, and a substrate-binding site, on silver nanoparticles (AgNPs), thereby creating an AgNP-based artificial hydrolase with high catalytic activity. This study provides a new approach for the design of highly efficient artificial enzymes and enzyme-mimicking. MethodsAgNPs were chosen as the scaffold to build the an α-chymotrypsin-like active center. A special CE procedure enables the designed peptide, Triad5, to adopt an α‑helical conformation on AgNPs, with the key catalytic residues located on one side of the α-helix forming a catalytic active center with a catalytic triad, an oxyanion hole, and a substrate-binding site. The CE procedure consists of three steps, including conformation induction via trifluoroethanol (TFE), conformation stabilization on AgNPs via Ag-S bonds, and TFE removal via lyophilization. Circular dichroism (CD) spectra were used to confirm the formation and stabilization of the α-helix conformation. Mutations of the key residues combined with stopped-flow kinetic experiments were used to demonstrate the indispensability of each key residue and the synergistic effects among the catalytic triad, the oxyanion hole, and the substrate-binding site. ResultsCD spectra show that the designed Triad5 alone is in random coil conformation; when conjugated on AgNPs, Triad5 still remains largely unstructured; but after the CE treatment, Triad5 adopts a typical α-helical conformation on AgNPs as designed, thus produces an AgNP-based artificial hydrolase, Silverzyme. Silverzyme exhibits extremely high hydrolytic activity towards p-nitrophenyl acetate (p-NPA), with an extremely high catalytic turnover number per active site of 3.5 s^-1, which is even higher than that of α-chymotrypsin. As a comparison, the AgNP-Triad5 conjugate without CE treatment shows much lower catalytic activity than Silverzyme, highlighting the important role of the right conformation of the active center for the catalytic activity and the power of the CE treatment. When the key residues of the catalytic triad of Silverzyme were mutated to alanine, the overall catalytic efficiency of this mutant dropped by about 2 orders of magnitude, unambiguously demonstrating the key role of the designed catalytic triad. Similarly, when the residues for the oxyanion hole were deleted, the mutant with the intact catalytic triad also showed significantly decreased catalytic activity, highlighting the indispensable role of the oxyanion hole for the catalytic activity. Unexpectedly, when both the catalytic triad and the oxyanion hole were kept intact, a slight change of the binding site also resulted in significantly decreased catalytic activity, indicating that the designed binding site is at the right position to align the substrate in the right orientation in the active center for catalytic hydrolysis. These results confirm the synergy among the catalytic triad, the oxyanion hole, and the substrate-binding site, indicating successful mimicking of the active center of α-chymotrypsin. Moreover, Silverzyme shows better thermal stability than α-chymotrypsin, and can even hydrolyze the tough non-activated ester diethyl phthalate, a priority pollutant by the United States Environmental Protection Agency (USEPA). ConclusionThis study successfully mimicked the complex catalytic active center of α-chymotrypsin using a conformational engineering strategy, and produced a highly active artificial hydrolase with a well-defined structure and catalytic mechanism. The findings highlight the significant potential of conformational engineering.

Abstract Adolescents are a high risk group for non suicidal self injury (NSSI), and the severity of the issue has been increasing. However, stigma originating from self perceptions, the public, and healthcare professionals poses significant barriers to help seeking and recovery among adolescents with NSSI. The paper systematically reviews the main intervention strategies targeting NSSI related stigma in adolescents, along with their effectiveness, from three perspectives: educational approaches, contact based interventions, and public advocacy against stigma, aiming to inform the development of a scientific, effective, and multi stakeholder collaborative integrated intervention framework to provide a basis for reducing and ultimately eliminating stigma associated with adolescent NSSI.

The translation of genetic findings from genome-wide association studies into actionable therapeutics persists as a critical challenge in Alzheimer's disease (AD) research. Here, we present PI4AD, a computational medicine framework that integrates multi-omics data, systems biology, and artificial neural networks for therapeutic discovery. This framework leverages multi-omic and network evidence to deliver three core functionalities: clinical target prioritisation; self-organising prioritisation map construction, distinguishing AD-specific targets from those linked to neuropsychiatric disorders; and pathway crosstalk-informed therapeutic discovery. PI4AD successfully recovers clinically validated targets like APP and ESR1, confirming its prioritisation efficacy. Its artificial neural network component identifies disease-specific molecular signatures, while pathway crosstalk analysis reveals critical nodal genes (e.g., HRAS and MAPK1), drug repurposing candidates, and clinically relevant network modules. By validating targets, elucidating disease-specific therapeutic potentials, and exploring crosstalk mechanisms, PI4AD bridges genetic insights with pathway-level biology, establishing a systems genetics foundation for rational therapeutic development. Importantly, its emphasis on Ras-centred pathways-implicated in synaptic dysfunction and neuroinflammation-provides a strategy to disrupt AD progression, complementing conventional amyloid/tau-focused paradigms, with the future potential to redefine treatment strategies in conjunction with mRNA therapeutics and thereby advance translational medicine in neurodegeneration.

OBJECTIVE: Rheumatoid arthritis (RA) is a systemic autoimmune disease that affects the small joints of the whole body and degrades the patients' quality of life. Zhengqing Fengtongning (ZF) is a traditional Chinese medicine preparation used to treat RA. ZF may cause liver injury. In this study, we aimed to develop a prediction model for abnormal liver function caused by ZF. METHODS: This retrospective study collected data from multiple centers from January 2018 to April 2023. Abnormal liver function was set as the target variable according to the alanine transaminase (ALT) level. Features were screened through univariate analysis and sequential forward selection for modeling. Ten machine learning and deep learning models were compared to find the model that most effectively predicted liver function from the available data. RESULTS: This study included 1,913 eligible patients. The LightGBM model exhibited the best performance (accuracy = 0.96) out of the 10 learning models. The predictive metrics of the LightGBM model were as follows: precision = 0.99, recall rate = 0.97, F1_score = 0.98, area under the curve (AUC) = 0.98, sensitivity = 0.97 and specificity = 0.85 for predicting ALT < 40 U/L; precision = 0.60, recall rate = 0.83, F1_score = 0.70, AUC = 0.98, sensitivity = 0.83 and specificity = 0.97 for predicting 40 ≤ ALT < 80 U/L; and precision = 0.83, recall rate = 0.63, F1_score = 0.71, AUC = 0.97, sensitivity = 0.63 and specificity = 1.00 for predicting ALT ≥ 80 U/L. ZF-induced abnormal liver function was found to be associated with high total cholesterol and triglyceride levels, the combination of TNF-α inhibitors, JAK inhibitors, methotrexate + nonsteroidal anti-inflammatory drugs, leflunomide, smoking, older age, and females in middle-age (45-65 years old). CONCLUSION This study developed a model for predicting ZF-induced abnormal liver function, which may help improve the safety of integrated administration of ZF and Western medicine. Please cite this article as: Yu Z, Kou F, Gao Y, Lyu CM, Gao F, Wei H. A machine learning model for predicting abnormal liver function induced by a Chinese herbal medicine preparation (Zhengqing Fengtongning) in patients with rheumatoid arthritis based on real-world study. J Integr Med. 2025; 23(1): 25-35.
Humans ; Arthritis, Rheumatoid/drug therapy* ; Drugs, Chinese Herbal/therapeutic use* ; Female ; Middle Aged ; Male ; Retrospective Studies ; Machine Learning ; Adult ; Aged ; Liver/physiopathology* ; Alanine Transaminase/blood*

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

RNA modifications constitute a crucial class of post-transcriptional chemical alterations that profoundly influence RNA stability and translational efficiency, thereby shaping cellular protein expression profiles. These diverse chemical marks are ubiquitously involved in key biological processes, including cell proliferation, differentiation, apoptosis, and metastatic potential, and they exert precise regulatory control over these functions. A major advance in the field is the recognition that RNA modifications do not act in isolation. Instead, they participate in complex, dynamic interactions—through synergistic enhancement, antagonism, competitive binding, and functional crosstalk—forming what is now termed the “RNA modification interactome” or “RNA modification interaction network.” The formation and functional operation of this interactome rely on a multilayered regulatory framework orchestrated by RNA-modifying enzymes—commonly referred to as “writers,” “erasers,” and “readers.” These enzymes exhibit hierarchical organization within signaling cascades, often functioning in upstream-downstream sequences and converging at critical regulatory nodes. Their integration is further mediated through shared regulatory elements or the assembly into multi-enzyme complexes. This intricate enzymatic network directly governs and shapes the interdependent relationships among various RNA modifications. This review systematically elucidates the molecular mechanisms underlying both direct and indirect interactions between RNA modifications. Building upon this foundation, we introduce novel quantitative assessment frameworks and predictive disease models designed to leverage these interaction patterns. Importantly, studies across multiple disease contexts have identified core downstream signaling axes driven by specific constellations of interacting RNA modifications. These findings not only deepen our understanding of how RNA modification crosstalk contributes to disease initiation and progression, but also highlight its translational potential. This potential is exemplified by the discovery of diagnostic biomarkers based on interaction signatures and the development of therapeutic strategies targeting pathogenic modification networks. Together, these insights provide a conceptual framework for understanding the dynamic and multidimensional regulatory roles of RNA modifications in cellular systems. In conclusion, the emerging concept of RNA modification crosstalk reveals the extraordinary complexity of post-transcriptional regulation and opens new research avenues. It offers critical insights into the central question of how RNA-modifying enzymes achieve substrate specificity—determining which nucleotides within specific RNA transcripts are selectively modified during defined developmental or pathological stages. Decoding these specificity determinants, shaped in large part by the modification interactome, is essential for fully understanding the biological and pathological significance of the epitranscriptome.