Hygroscopicity research has long been a key focus and hot topic in Chinese materia medica（CMM）. Elucidating hygroscopic mechanisms plays a vital role in formulation design， process optimization， and storage condition selection. Hygroscopic models serve as essential tools for characterizing CMM hygroscopic mechanisms， with various types available. The double exponential model is a kinetic mathematical model constructed based on the law of conservation of energy and Fick's first law of diffusion， tailored to the physical properties of CMM extracts. In recent years， this model has been extensively applied to simulate the dynamic moisture absorption behavior of CMM extracts and solid dosage forms under varying humidity conditions. It has revealed the correlation between moisture absorption kinetic parameters and material properties， offering a new perspective for characterizing the moisture uptake behavior of CMM. This paper systematically reviews the application progress of this model in the field of CMM， analyzes its advantages， disadvantages， and challenges in this domain， and explores its potential application trends in other fields. It aims to provide references for elucidating the moisture absorption mechanisms of CMM and researching moisture-proofing technologies， while also offering insights for its broader application in food and polymer materials.

Objective: To characterize perioperative dynamic changes in immune-cell phenotypes and inflammatory cytokines in patients undergoing CPB (cardiopulmonary bypass) cardiac surgery, and to explore their associations with postoperative outcomes. Methods: In this prospective cohort study, 120 adult patients who underwent elective cardiac surgery under CPB at West China Hospital from May 2022 to March 2023 were enrolled. Perioperative immune-cell phenotypes and concentrations of 40 inflammation-related cytokines were measured. The primary outcomes were the sequential organ failure assessment (SOFA) score at 24 h after surgery and ΔSOFA (the peak SOFA score within 48 h after surgery minus the preoperative SOFA score). Secondary outcomes included major adverse cardiovascular events (MACE), acute kidney injury (AKI), respiratory failure, severe liver injury, and infection. Results: The mean age of enrolled patients was 57±10 years. Of these, 52% (62/120) were male and 90% (108/120) underwent valve surgery. During the rewarming to the end of CPB, neutrophil counts rapidly increased (7.39×10 /L vs preoperative 3.07×10 /L, P<0.001), with significant upregulation of CD11b (7.30×10 /L vs preoperative 3.05×10 /L, P<0.001) and CD54 (7.15×10 /L vs preoperative 2.99×10 /L, P<0.001). Lymphocyte counts increased at the end of CPB (1.75×10 /L vs preoperative 1.12×10 /L, P<0.001) but decreased significantly at 24 h after surgery (0.59×10 /L vs preoperative 1.12×10 /L, P<0.001). Plasma analysis showed that multiple pro-inflammatory cytokines increased during CPB and remained elevated up to 24 h after surgery; five chemokines and the anti-inflammatory cytokine IL-10 peaked at the end of CPB. The SOFA score increased from 1 (1, 2) preoperatively to 7 (5, 10) at 24 h after surgery, with a ΔSOFA of 6 (4, 8). Within 30 days after surgery, 48 patients (40.0%) developed AKI, 17 (14.2%) developed infection, 4 (3.3%) developed severe liver injury, 3 (2.5%) developed respiratory failure, and 3 (2.5%) experienced MACE. During the 2-year follow-up, 8 patients (6.7%) experienced MACE and 5 (4.2%) died. Conclusion: Multi-organ dysfunction is common after cardiac surgery under CPB (median ΔSOFA, 6), accompanied by perioperative activation of multiple immune-cell subsets and upregulation of pro-inflammatory, anti-inflammatory, and chemotactic mediators. This study provides data-driven evidence and research clues for further investigation of the associations between CPB-related immune perturbations and postoperative organ dysfunction and clinical outcomes.

Bronchial asthma （BA） is a common chronic inflammatory airway disease characterized by airway hyperresponsiveness and reversible airflow limitation. Lung macrophages （LMs）， as important effector cells of the innate immune system， play an important role in recognizing and engulfing pathogens， clearing harmful particles， and regulating immune responses. LMs can be polarized to M1 （pro-inflammatory） or M2 （anti-inflammatory） in different immune environments and participate in promoting or inhibiting inflammatory response， as well as lung parenchyma injury and repair （airway remodeling）， playing a key role in the BA occurrence and development. Regulating the polarization balance of macrophages can not only inhibit the inflammatory response in the airway and reduce airway hyperresponsiveness， but also improve airway remodeling and immune regulation， reduce airway mucus secretion， and alleviate the clinical BA symptoms. Traditional Chinese medicine and its active ingredients， especially polysaccharides and saponins， can regulate the polarization balance of M1/M2 macrophages. Traditional Chinese medicine compounds can balance the secretion of anti-inflammatory and pro-inflammatory factors by staging treatment and targeting the polarization state of M1/M2 macrophages， inhibit inflammatory response in the airway， reduce airway remodeling， and improve the BA symptoms. This paper summarized the research progress on the regulation of M1/M2 macrophage polarization by traditional Chinese medicine and its active ingredients， aiming to provide scientific evidence for the precise targeted therapy of BA.

Bronchial asthma （BA） is a common chronic inflammatory airway disease characterized by airway hyperresponsiveness and reversible airflow limitation. Lung macrophages （LMs）， as important effector cells of the innate immune system， play an important role in recognizing and engulfing pathogens， clearing harmful particles， and regulating immune responses. LMs can be polarized to M1 （pro-inflammatory） or M2 （anti-inflammatory） in different immune environments and participate in promoting or inhibiting inflammatory response， as well as lung parenchyma injury and repair （airway remodeling）， playing a key role in the BA occurrence and development. Regulating the polarization balance of macrophages can not only inhibit the inflammatory response in the airway and reduce airway hyperresponsiveness， but also improve airway remodeling and immune regulation， reduce airway mucus secretion， and alleviate the clinical BA symptoms. Traditional Chinese medicine and its active ingredients， especially polysaccharides and saponins， can regulate the polarization balance of M1/M2 macrophages. Traditional Chinese medicine compounds can balance the secretion of anti-inflammatory and pro-inflammatory factors by staging treatment and targeting the polarization state of M1/M2 macrophages， inhibit inflammatory response in the airway， reduce airway remodeling， and improve the BA symptoms. This paper summarized the research progress on the regulation of M1/M2 macrophage polarization by traditional Chinese medicine and its active ingredients， aiming to provide scientific evidence for the precise targeted therapy of BA.

Aluminum adjuvants are widely used in the field of vaccines due to their ability to induce efficient and long-lasting immune responses and good safety profile. With the development of immunology, the requirements for adjuvants have gradually increased, and traditional aluminum adjuvants can no longer meet all the needs of application. The development of novel aluminum adjuvants has become a hot research topic in order to achieve good immunity-enhancing effects and induce specific types and strengths of immune responses. This review briefly introduces the mechanism of action and safety of aluminum adjuvants, with focus on the research progress of novel aluminum adjuvants in recent years, mainly including nano-aluminum adjuvants and composite aluminum adjuvants (aluminum adjuvants compounded with immunity-stimulating molecules or delivery carriers), and a prospect of their future research direction, aiming to provide some reference for the further development and clinical application of aluminum adjuvants.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Based on whole-genome identification of the TPS gene family in Perilla frutescens and screening, cloning, bioinformatics, and expression analysis of the synthetic enzyme for the insect-resistant component germacrene D, this study lays the foundation for understanding the biological function of the TPS gene family and the insect resistance mechanism in P. frutescens. This study used bioinformatics tools to identify the TPS gene family of P. frutescens based on its whole genome and predicted the physicochemical properties, systematic classification, and promoter cis-elements of the proteins. The relative content of germacrene D was detected in both normal and insect-infested leaves of P. frutescens, and the germacrene D synthase was screened and isolated. Gene cloning, bioinformatics analysis, and expression profiling were then performed. The results showed that a total of 99 TPS genes were identified in the genome, which were classified into the TPS-a, TPS-b, TPS-c, TPS-e/f, and TPS-g subfamilies. Conserved motif analysis showed that the TPS in P. frutescens has conserved structural characteristics within the same subfamily. Promoter cis-element analysis predicted the presence of light-responsive elements, multiple hormone-responsive elements, and stress-responsive elements in the TPS family of P. frutescens. Transcriptome data revealed that most of the TPS genes in P. frutescens were highly expressed in the leaves. GC-MS analysis showed that the relative content of germacrene D significantly increased in insect-damaged leaves, suggesting that it may act as an insect-resistant component. The germacrene D synthase gene was screened through homologous protein binding gene expression and was found to belong to the TPS-a subfamily, encoding a 64.89 kDa protein. This protein was hydrophilic, lacked a transmembrane structure and signal peptide, and was predominantly expressed in leaves, with significantly higher expression in insect-damaged leaves compared to normal leaves. In vitro expression results showed that germacrene D synthase tended to form inclusion bodies. Molecular docking showed that farnesyl pyrophosphate(FPP) fell into the active pocket of the protein and interacted strongly with six active sites. This study provides a foundation for further research on the biological functions of the TPS gene family in P. frutescens and the molecular mechanisms underlying its insect resistance.
Perilla frutescens/chemistry* ; Plant Proteins/chemistry* ; Multigene Family ; Sesquiterpenes, Germacrane/metabolism* ; Alkyl and Aryl Transferases/chemistry* ; Phylogeny ; Gene Expression Regulation, Plant

OBJECTIVE: To study the results, re-donation situation and characteristics of single-reagent reactive blood donors who were put into the reentry strategy in Wuhan area, explore the rationality and effectiveness of the current reentry strategy, and provide data support for the improvement of the reentry process of blood donors. METHODS: From January 2020 to December 2023, blood donors who conform the reentry criteria and voluntarily applied for returning to Wuhan Blood Center were tested and the results were analyzed. According to the reentry strategy, serological testing and nucleic acid testing were carried out in parallel, serological testing was performed by ELISA with reagents from two different manufacturers, and the primary reactive samples were tested by double-well retest, and HBV/HCV/HIV nucleic acid detection was performed by RT-PCR with an individual donor test mode. Supplementary HBcAb testing was applied for HBV single reagent reactivity by chemiluminescence method. Supplementary TP-WB testing was applied for returning blood donors with repeated TP single reagent reactivity. If returning blood donors with HIV single reagent reactivity were repeated single reagent reactivity, the samples were sent to local CDC for confirmatory test. RESULTS: 7 098 blood donors were qualified for reentry, 716 donors voluntarily applied for reentry, 436 donors successfully reentry, 251 donors entered the next round, 29 donors could not reentry. The reentry rates for the past four years were 66.67%（42/63）, 54.73%（81/148）, 60.71%（136/224） and 62.99%（177/281）, respectively. Up to December 31, 2023, 275 donors donated blood again, and the donation rates for past four years were 76.19%（32/42）, 72.84%（59/81）, 61.76%（84/136） and 56.50%（100/177）, respectively. After donating blood, 31 donors were disqualified again by blood screening and subjected to permanent deferral. The results of returning to the team had statistical differences in reentry items, educational level, age, and marriage（P < 0.05）. CONCLUSION The current reentry strategy adopted by the blood donation and supply institution can effectively retain part of blood donors, reduce the negative emotions of blood donors and increase blood resources.
Humans ; Blood Donors ; China ; Hepatitis B ; Enzyme-Linked Immunosorbent Assay ; Hepatitis C ; Male

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*