Objective To explore the feasibility and reference value of allogeneic lung transplantation and postoperative monitoring in miniature pigs for lung transplantation research. Methods Two miniature pigs (R1 and R2) underwent left lung allogeneic transplantation. Complement-dependent cytotoxicity tests and blood cross-matching were performed before surgery. The main operative times and partial pressure of arterial oxygen (PaO₂) after opening the pulmonary artery were recorded during surgery. Postoperatively, routine blood tests, biochemical blood indicators and inflammatory factors were detected, and pathological examinations of multiple organs were conducted. Results The complement-dependent cytotoxicity test showed that the survival rate of lymphocytes between donors and recipients was 42.5%-47.3%, and no agglutination reaction occurred in the cross-matching. The first warm ischemia times of D1 and D2 were 17 min and 10 min, respectively, and the cold ischemia times were 246 min and 216 min, respectively. Ultimately, R1 and R2 survived for 1.5 h and 104 h, respectively. Postoperatively, in R1, albumin (ALB) and globulin (GLB) decreased, and alanine aminotransferase increased; in R2, ALB, GLB and aspartate aminotransferase all increased. Urea nitrogen and serum creatinine increased in both recipients. Pathological results showed that in R1, the transplanted lung had partial consolidation with inflammatory cell infiltration, and multiple organs were congested and damaged. In R2, the transplanted lung had severe necrosis with fibrosis, and multiple organs had mild to moderate damage. The expression levels of interleukin-1β and interleukin-6 increased in the transplanted lungs. Conclusions The allogeneic lung transplantation model in miniature pigs may systematically evaluate immunological compatibility, intraoperative function and postoperative organ damage. The data obtained may provide technical references for subsequent lung transplantation research.

ObjectiveTo develop an intervention program based on a shared mental model to enhance the communication and collaboration skills of nurses in multidisciplinary teams in stroke rehabilitation wards. MethodsUsing the shared mental model as the theoretical framework, the intervention program was preliminarily drafted through literature review to establish a theoretical foundation and qualitative research to identify clinical needs. The Delphi method was then used to revise and refine the program. ResultsBased on literature review and qualitative research, intervention elements were extracted across four dimensions: equipment, tasks, team interaction and team members, forming the initial draft of the intervention program. Two rounds of consultations were conducted with 18 experts, achieving a 100% valid response rate in both rounds. The expert authority coefficients were 0.87 and 0.90, respectively. In the second round of consultation, the variation coefficients for the importance scores of each item ranged from 0 to 0.20 (overall Kendall's W = 0.272, P < 0.001), and the variation coefficients for feasibility scores ranged from 0 to 0.21 (overall Kendall's W = 0.275, P < 0.001). The final intervention program included five first-level indicators, eight second-level indicators, and 29 third-level indicators, aligning with the four dimensions of the shared mental model. ConclusionThe intervention program was developed to enhance the communication and collaboration skills of nurses in multidisciplinary teams in stroke rehabilitation wards based on the shared mental model.

OBJECTIVE To construct an intelligent pharmaceutical Q&A platform for precision medication with low “artificial intelligence （AI） hallucination”， aiming to enhance the accuracy， consistency， and traceability of medication consultations. METHODS Medication package inserts were batch-processed and converted into structured data through Python programming to build a local pharmaceutical knowledge base. The retrieval and question-answering processes were designed based on large language models， and system integration and localized deployment were completed on Dify platform. By designing typical clinical medication questions and comparing the output of the intelligent pharmaceutical Q&A platform with the online version of DeepSeek across dimensions such as peak time retrieval， half-life， and dosage adjustment reasoning for patients with renal impairment， the accuracy and reliability of its retrieval and reasoning results were evaluated. RESULTS The intelligent pharmaceutical Q&A platform， constructed based on local drug package inserts， achieved 100% accuracy in retrieval and reasoning for peak time， half-life， and dosage adjustment schemes. In comparison， the online version of DeepSeek demonstrated accuracies of 30%（6/20）， 50%（10/20）， and 38%（23/60） across these three dimensions， respectively. CONCLUSIONS The constructed intelligent pharmaceutical Q&A platform is capable of accurately retrieving and extracting information from the local knowledge base based on clinical inquiries， thereby avoiding the occurrence of AI hallucinations and providing reliable medication decision support for healthcare professionals.

Patients with chronic cholestatic liver diseases face numerous challenges in the detection， assessment， and management of suspected drug-induced liver injury （DILI）， and in particular， it is difficult to distinguish cholestatic DILI from the progression of underlying cholestatic liver diseases clinically and histologically. Currently， there is a lack of related research and management guidelines for DILI with chronic cholestatic liver diseases. This article discusses the potential risks， causality， and classification criteria for chronic cholestatic liver diseases with DILI， in order to improve the understanding of such diseases among clinicians and provide a reference for prevention， treatment， and management strategies.

With the continuous development of society, a large number of new chemicals are continuously emerging, which presents a challenge to current risk assessment and safety management of chemicals. Traditional toxicology research methods have certain limitations in quickly, efficiently, and accurately assessing the toxicity of many chemicals, and cannot meet the actual needs. In response to this challenge, computational toxicology that use mathematical and computer models to achieve the prediction of chemical toxicity has emerged. In the meantime, as researchers increasingly pay attention to understanding the interaction mechanisms between exogenous chemical substances and the body from the system level, and multiomics technologies develop rapidly such as genomics, transcriptomics, proteomics, and metabolomics, huge amounts of data have been generated, providing rich information resources for studying the interactions between chemical substances and biological molecules. System toxicology and network toxicology have also developed accordingly. Of these, network toxicology can integrate these multiomics data to construct biomolecular networks, and then quickly predict the key toxicological targets and pathways of chemicals at the molecular level. This paper outlined the concept and development of network toxicology, summarized the main methods and supporting tools of network toxicology research, expounded the application status of network toxicology in studying potential toxicity of exogenous chemicals such as agricultural chemicals, environmental pollutants, industrial chemicals, and foodborne chemicals, and analyzed the development prospects and limitations of network toxicology research. This paper aimed to provide a reference for the application of network toxicology in other fields.

Staphylococcus aureus is a Gram-positive bacterium with strong pathogenicity. With the widespread use of antibiotics， its multi-drug resistance has gradually increased. Among them， methicillin-resistant S. aureus （MRSA） is one of the main pathogens of hospital and community infections. Antimicrobial peptides are short-chain peptides with good antibacterial effects and low drug resistance， which have been widely studied in recent years. This study summarizes the mechanism of action of antimicrobial peptides and related study on antimicrobial peptides against MRSA from different sources. It is found that the mechanisms of action of antimicrobial peptides include targeting bacterial cell membranes， bacterial cells， and bacterial cell walls， etc. Besides isolating antimicrobial peptides with anti-MRSA activity from animals， plants， and microorganisms， antimicrobial peptides can also be obtained through synthetic methods. Among them， GHa-derived peptides from animal sources， Ib-AMP4 from plant sources， Ph-SA from microbial sources， the synthetic peptide LLKLLLKLL-NH2， and so on， due to their effective antibacterial activity， rapid bactericidal speed， and low toxicity， are promising candidates for anti-MRSA drugs.

ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

ObjectiveTo explore the mechanism by which Xiaoyaosan regulates HPT axis dysfunction in the rat model with the syndrome of liver depression and spleen deficiency by observing its effect on the glycoprotein hormone α-subunit （CGA）/glutathione peroxidase 2 （GPX2）/thyroid-stimulating hormone β-subunit （TSHβ） pathway for thyroid hormone synthesis. MethodsSeventy-two male SD rats were randomized into six groups： normal， model， high-dose （16.7 g·kg^-1）， medium-dose （8.35 g·kg^-1）， and low-dose （4.175 g·kg^-1） Xiaoyaosan， and fluoxetine （0.001 8 g·kg^-1） groups， with 12 rats in each group. The rat model of liver depression and spleen deficiency was induced by chronic restraint stress for 21 days. The intervention groups were treated with Xiaoyaosan decoctions or fluoxetine suspension， respectively. After modeling， hematoxylin-eosin staining was employed to observe morphological changes in the thyroid and pituitary tissue of the rats. Serum levels of triiodothyronine （T3）， tetraiodothyronine （T4）， and thyroid-stimulating hormone （TSH） were measured by enzyme-linked immunosorbent assay （ELISA）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot were employed to determine the mRNA and protein levels， respectively， of TSH receptor （TSHR） in the thyroid tissue， thyrotropin-releasing hormone receptor （TRHR） and TSHβ in the pituitary tissue， and thyrotropin-releasing hormone （TRH）， CGA， GPX2， and TSHβ in the hypothalamic tissue. ResultsCompared with the normal group， the model group showed significant atrophy and irregularity of thyroid follicles， a marked reduction in colloid secretion， extensive vacuolar degeneration of adenocytes in the anterior pituitary， lowered serum levels of T3， T4， and TSH （P<0.01）， and down-regulated mRNA and protein levels of TSHR in the thyroid tissue， TRHR and TSHβ in the pituitary tissue， and TRH， CGA， GPX2， and TSHβ in the hypothalamic tissue （P<0.01）. Compared with the model group， high- and medium-dose Xiaoyaosan and fluoxetine alleviated the pathological changes in the thyroid and pituitary tissue， outperforming the low-dose Xiaoyaosan group. Moreover， they elevated the serum levels of T3， T4， and TSH （P<0.05， P<0.01）. The serum TSH level was also elevated in the low-dose Xiaoyaosan group （P<0.05）. The mRNA and protein levels of TSHR in the thyroid， TRHR and TSHβ in the pituitary， and TRH， CGA， GPX2， and TSHβ in the hypothalamus were up-regulated in the high- and medium-dose Xiaoyaosan groups （P<0.05， P<0.01）. Additionally， the mRNA and protein levels of TSHβ in the hypothalamus were up-regulated in the low-dose Xiaoyaosan group （P<0.01）. In the fluoxetine group， the mRNA and protein levels of TSHR in the thyroid， TRHR in the pituitary， and TRH， CGA， and GPX2 in the hypothalamus were up-regulated （P<0.05， P<0.01）. ConclusionThe downregulation of CGA/GPX2/TSHβ pathway may be one of the biological mechanisms underlying HPT axis dysfunction in the rat model with the syndrome of liver depression and spleen deficiency. Xiaoyaosan may regulate the HPT axis dysfunction by up-regulating the CGA/GPX2/TSHβ pathway.

ObjectiveTo explore the effects of angle and original moisture content on the moisture distribution， migration and contents of effective components in the drying process of sliced Salviae Miltiorrhizae Radix et Rhizoma（SMRR）. MethodsSet the slicing angles of SMRR at 30°， 45°， and 90°. Cut the fresh samples， 1/3 dehydrated samples， and 2/3 dehydrated samples， dry them in an oven at 40 ℃ and take samples at the set time points. Low-field nuclear magnetic resonance（LF-NMR） and magnetic resonance imaging（MRI） were used to analyze the changes in transverse relaxation time（T₂） of SMRR samples in 9 treatment groups at specific times， as well as the distribution and migration of water in the samples. The contents of tanshinone Ⅱ_A， tanshinone Ⅰ， cryptotanshinone， and salvianolic acid B in samples from 9 different treatment groups were determined by high performance liquid chromatography（HPLC）， and the best processing technology of SMRR was screened by combining with One-way ANOVA， Duncan multiple comparison and principal component analysis（PCA）. ResultsThe moisture content of dry basis of SMRR in each treatment group decreased with the extension of drying time. The drying rate of fresh cut group decreased slowly at first， while the drying rate of water loss group showed a trend of increasing at first and then decreasing. The internal water of SMRR could be divided into three states， including bound water， non flowing water and free water. During the drying process， the water migration law showed that the free water of fresh cut group disappeared after drying for 12 h， the content of bound water gradually decreased， and the overall fluidity deteriorated. In the water loss group， part of the free water was transformed into more cohesive and non flowing water after drying for 3 h， and the three kinds of water basically disappeared after drying for 12 h. The MRI results showed that the entire dehydration process slowly moved from the outer side to the center， and the internal water eventually dissipated. In terms of the contents of active ingredients， the order of the effect of slicing angle on the total content of active ingredients in SMRR was 30°>45°>90°. The content of tanshinones was ranked as 1/3 dehydrated group>2/3 dehydrated group>fresh cut group， and the content of salvianolic acid B was ranked as 1/3 dehydrated group>fresh cut group>2/3 dehydrated group. Combined with the results of PCA and comprehensive scoring results， the overall level of effective component content in SMRR was the highest when cut at 30° after 1/3 of water loss. ConclusionAfter comprehensive evaluation， SMRR can be sliced at 30° after 1/3 of water loss. It is not only easy to cut， but also the surface and cross-sectional colors remain basically unchanged after drying， which is similar to the color under traditional processing， and the effective ingredients are preserved the highest. This study can provide a basis for the optimization of processing technology of SMRR.

The innate immune system can be boosted in response to subsequent triggers by pre-exposure to microbes or microbial products, known as “trained immunity”. Compared to classical immune memory, innate trained immunity has several different features. Firstly, the molecules involved in trained immunity differ from those involved in classical immune memory. Innate trained immunity mainly involves innate immune cells (e.g., myeloid immune cells, natural killer cells, innate lymphoid cells) and their effector molecules (e.g., pattern recognition receptor (PRR), various cytokines), as well as some kinds of non-immune cells (e.g., microglial cells). Secondly, the increased responsiveness to secondary stimuli during innate trained immunity is not specific to a particular pathogen, but influences epigenetic reprogramming in the cell through signaling pathways, leading to the sustained changes in genes transcriptional process, which ultimately affects cellular physiology without permanent genetic changes (e.g., mutations or recombination). Finally, innate trained immunity relies on an altered functional state of innate immune cells that could persist for weeks to months after initial stimulus removal. An appropriate inducer could induce trained immunity in innate lymphocytes, such as exogenous stimulants (including vaccines) and endogenous stimulants, which was firstly discovered in bone marrow derived immune cells. However, mature bone marrow derived immune cells are short-lived cells, that may not be able to transmit memory phenotypes to their offspring and provide long-term protection. Therefore, trained immunity is more likely to be relied on long-lived cells, such as epithelial stem cells, mesenchymal stromal cells and non-immune cells such as fibroblasts. Epigenetic reprogramming is one of the key molecular mechanisms that induces trained immunity, including DNA modifications, non-coding RNAs, histone modifications and chromatin remodeling. In addition to epigenetic reprogramming, different cellular metabolic pathways are involved in the regulation of innate trained immunity, including aerobic glycolysis, glutamine catabolism, cholesterol metabolism and fatty acid synthesis, through a series of intracellular cascade responses triggered by the recognition of PRR specific ligands. In the view of evolutionary, trained immunity is beneficial in enhancing protection against secondary infections with an induction in the evolutionary protective process against infections. Therefore, innate trained immunity plays an important role in therapy against diseases such as tumors and infections, which has signature therapeutic effects in these diseases. In organ transplantation, trained immunity has been associated with acute rejection, which prolongs the survival of allografts. However, trained immunity is not always protective but pathological in some cases, and dysregulated trained immunity contributes to the development of inflammatory and autoimmune diseases. Trained immunity provides a novel form of immune memory, but when inappropriately activated, may lead to an attack on tissues, causing autoinflammation. In autoimmune diseases such as rheumatoid arthritis and atherosclerosis, trained immunity may lead to enhance inflammation and tissue lesion in diseased regions. In Alzheimer’s disease and Parkinson’s disease, trained immunity may lead to over-activation of microglial cells, triggering neuroinflammation even nerve injury. This paper summarizes the basis and mechanisms of innate trained immunity, including the different cell types involved, the impacts on diseases and the effects as a therapeutic strategy to provide novel ideas for different diseases.