ObjectiveBased on traditional quality evaluation of Gardeniae Fructus（GF） recorded in historical materia medica， this study systematically compared the quality differences between wild and cultivated GF from morphological characteristics， microscopic features， and contents of primary and secondary metabolites. MethodsVernier calipers and analytical balances were used to measure the length， diameter and individual fruit weight of wild and cultivated GF， and the aspect ratio was calculated. A colorimeter was used to determine the chromaticity value of wild and cultivated GF， and the paraffin sections of them were prepared by safranin-fast green staining and examined under an optical microscope to observe their microstructure. Subsequently， the contents of water-soluble and alcohol-soluble extracts of wild and cultivated GF were detected by hot immersion method under the general rule 2201 in volume Ⅳ of the 2020 edition of the Pharmacopoeia of the People's Republic of China， the starch content was measured by anthrone colorimetric method， the content of total polysaccharides was determined by phenol-sulfuric acid colorimetric method， the sucrose content was determined by high performance liquid chromatography coupled with evaporative light scattering detection（HPLC-ELSD）， and the contents of representative components in them were measured by ultra-performance liquid chromatography（UPLC）. Finally， correlation analysis was conducted between quality traits and phenotypic traits， combined with multivariate statistical analysis methods such as principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， key differential components between wild and cultivated GF were screened. ResultsIn terms of traits， the wild GF fruits were smaller， exhibiting reddish yellow or brownish red hues with significant variation between batches. While the cultivated GF fruits are larger， displaying deeper orange-red or brownish red. The diameter and individual fruit weight of cultivated GF were significantly greater than those of wild GF， while the blue-yellow value（b^*） of wild GF was significantly higher than that of cultivated GF. In the microstructure， the mesocarp of wild GF contained numerous scattered calcium oxalate cluster crystals， while the endocarp contained stone cell class round， polygonal or tangential prolongation， undeveloped seeds were visible within the fruit. In contrast， the mesocarp of cultivated GF contained few calcium oxalate cluster crystals， or some batches exhibited extremely numerous cluster crystals. The stone cells in the endocarp were predominantly round-like， with the innermost layer arranged in a grid pattern. Seeds were basically mature， and only a few immature seeds existed in some batches. Regarding primary metabolite content， wild GF exhibited significantly higher total polysaccharide level than cultivated GF（P<0.01）. In category-specific component content， wild GF exhibited significantly higher levels of total flavonoids and total polyphenols compared to cultivated GF（P<0.01）. Analysis of 12 secondary metabolites revealed that wild GF exhibited significantly higher levels of Shanzhiside， deacetyl asperulosidic acid methyl ester， gardenoside and chlorogenic acid compared to cultivated GF（P<0.01）. Conversely， the contents of genipin 1-gentiobioside， geniposide and genipin were significantly lower in wild GF（P<0.01）. ConclusionThere are significant differences between wild and cultivated GF in terms of traits， microstructure， and contents of primary and secondary metabolites. At present， the quality evaluation system of cultivated GF remains incomplete， and this study provides a reference for guiding the production of high-quality GF medicinal materials.

Background: Influenza A virus (IAV) is a negative-sense RNA virus of the Orthomyxoviridae family and is the etiological agent of a highly contagious acute respiratory disease that can lead to acute lung injury. Objective: To elucidate the molecular mechanisms of IAV infection, an integrative research approach combining gene expression profiling, multinetwork analysis, and in vivo experimental validations was employed. Methods: First, a series of network-based analyses were performed, including protein-protein interaction network construction, weighted gene co-expression network analysis, and subsequent gene set enrichment analysis, to identify the major underlying mechanisms of IAV infection. Following gene expression analysis, core targets, both direct and indirect regulators, were screened. An IAV (H1N1) strain A/PR/8/34-induced acute lung injury mouse model was constructed for in vivo validations. Batch one included two groups to evaluate findings from the multi-network analysis: Mock (n = 10; 5 males and 5 females) and IAV (n = 10; 5 males and 5 females). Batch two included three groups to assess the role of toll-like receptor 3 (TLR3) in IAV infection: Mock (n = 6; 3 males and 3 females), IAV (n = 6; 3 males and 3 females), and TLR3 inhibitor (n = 6; 3 males and 3 females). Body weight was measured on days 0, 3, and 5 after infection. On day 5, lung tissues were collected to assess viral load and histopathological changes. Key targets were examined using enzyme-linked immunosorbent assay, Western blotting, and immunofluorescence staining, both in sera and lung tissues. Results: IAV infection was significantly associated with dysregulation of the immune-inflammation system, such as the LTR, nucle-otide-binding oligomerization domain-(NOD) like receptor, retinoic acid-inducible gene I-like receptor, and nuclear factor kappa-B signaling pathways. Gene set enrichment analysis further indicated that the TLR and necroptosis signaling pathways played crucial roles in the progression of IAV infection (TLR signaling pathway normalized enrichment score = 2.3941, P = 1.00 × 10 ⁻¹⁰; necroptosis normalized enrichment score = 1.9421, P = 6.21 × 10 ⁻⁷). Among the core targets, TLR3 and mixed lineage kinase domain-like protein (MLKL) may regulate gene expression at the transcriptional level (all P < 0.05). In vivo validation using an IAV (PR8) infected acute lung injury mouse model demonstrated increased viral load and lung index, alveolar structural damage, and inflammatory cell infiltration. Immunofluorescence staining exhibited large gaps in Lamin B1 staining and breaches in Emerin signals following IAV-PR8 infection. Expression levels of TLR3, p-receptor-interacting serine/threonine-protein kinase 3 (RIPK3)/RIPK3, and p-mixed lineage kinase domain-like protein (MLKL)/MLKL proteins in lung tissues, as well as proinflammatory factors and mediators in sera, were significantly elevated after IAV infection. Moreover, enhanced neutrophil infiltration (myeloperoxidase) and citrullinated histone H3 (a neutrophil extracellular trap-specific marker), both established indicators of neutrophil extracellular trap formation, were observed. Notably, treatment with a TLR3 inhibitor significantly ameliorated IAV-induced acute lung injury by regulating necroptosis-related targets. Conclusion: Our study provides network-based in vivo evidence that TLR3-receptor-interacting serine/threonine-protein kinase 3-MLKL-mediated necroptosis may underlie IAV-induced acute lung injury and could serve as a potential therapeutic target in severe influenza cases.

Objective To develop and validate a prediction model for in-hospital recurrent intensive care unit (ICU) admission in critically ill patients with ischemic stroke (IS) based on machine learning (ML) algorithms. Methods Clinical data from 2 929 IS patients were included from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Least absolute shrinkage and selection operator (LASSO) regression was used to identify predictive factors, and the synthetic minority over-sampling technique (SMOTE) was employed to create a derivation cohort comprising 2 583 patients. These patients were randomly divided into a training set (n=2 066) and a test set (n=517) at an 8:2 ratio. Five ML algorithms, including decision tree, random forest, adaptive boosting (AdaBoost), gradient boosting decision tree (GBDT), and support vector machine (SVM), were performed to construct prediction models. Five-fold cross-validation was used to evaluate the performance of the model in the training set. The area under the receiver operating characteristic curve (ROC-AUC) and decision curve analysis (DCA) were used to assess and compare the models in the testing set. The best-performing model was interpreted by shapley additive explanations (SHAP). Results Among the 2 929 patients included, 704 (24.0%) experienced in-hospital recurrent ICU admission. Among the five ML models, the random forest model demonstrated the best predictive performance, with an AUC of 0.839 (95%CI 0.801–0.877). Feature importance analysis identified five most significant features affecting model prediction, including APS Ⅲ score, albumin, age, heart rate, and SOFA score. Conclusions ML-based models can effectively predict the risk of in-hospital recurrent ICU admission in critically ill patients with IS. The random forest model showed superior predictive performance, which may have potential applications in early clinical risk stratification and intervention.

ObjectiveTo analyze the current status of traditional Chinese medicine （TCM） prediction model research for emerging acute infectious diseases， in order to provide reference for subsequent model construction and optimization. MethodsEight databases， including PubMed， Cochrane Library， and Embase， were systematically searched to comprehensively collect Chinese and English literature on TCM prediction models for emerging acute infectious diseases. The search period ranged from database inception to July 5， 2024. Reporting quality compliance was evaluated using the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis—Traditional Chinese Medicine （TRIPOD-TCM） guideline. Risk of bias and applicability were assessed using the Prediction Model Risk of Bias Assessment Tool （PROBAST）. ResultsA total of 21 studies were included， comprising 11 early warning model studies， 5 diagnostic model studies， 3 prognostic model studies， and 2 prescription prediction model studies， involving 84 models in total. The diseases involved were mainly viral infectious diseases such as coronavirus disease 2019 （COVID-19） and hepatitis B. The most frequently applied TCM theory was the "five movements and six climates" theory. The most commonly used modeling method was neural network-based approaches. The most frequently reported predictive factors were meteorological variables， including daily mean temperature， wind speed， precipitation， relative humidity， and vapor pressure. In terms of reporting quality， the included studies showed poor item-level compliance， with only 13 sub-items achieving compliance rates above 50%. Overall compliance ranged from 27% to 59% across studies. Although the included studies showed relatively good applicability， all were assessed as having a high risk of bias. The main sources of bias included inappropriate handling of missing data， absence of calibration methods， and unreasonable validation strategies， indicating deficiencies across multiple stages of model development. ConclusionCurrent research on TCM prediction models for emerging acute infectious diseases exhibits distinctive modeling characteristics. These models are based on traditional TCM theories such as the "five movements and six climates"， incorporate TCM-specific features as predictive variables， and use TCM syndromes as outcomes. However， they generally suffer from low reporting compliance and a high risk of bias. Future studies should systematically design model development and validation processes， adhere to TRIPOD-TCM reporting standards， and apply PROBAST or develop dedicated bias risk assessment tools for TCM prediction models to improve methodological quality and promote their translation into clinical practice.

Objective To genetically investigate the protective effects of statins on breast cancer. Methods Instrumental variables for the statin target gene HMGCR and five other cholesterol-regulated genes (LDLR, PCSK9, ABCG8, APOB, and NPC1L1) were obtained from previous expression quantitative trait locus (eQTL) studies. Cholesterol-regulated genes predicted by these instrumental variables served as the exposure factors. Mendelian randomization based on pooled data (SMR) was conducted to explore the genetic effects of exposure factors on the incidence risk of all breast cancers, ER+ breast cancer, and ER-breast cancer. Instrumental variables for total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and non-high-density lipoprotein cholesterol (non-HDL-C) were derived from a previous human genome-wide association study and restricted to be chromosomally located within 100 kb of the above cholesterol regulatory genes; the instrumental variables could predict TC, LDL-C, or non-HDL-C levels under the regulation of the abovementioned cholesterol-associated genes which were used as exposure factors. Two-sample Mendelian randomization (IVW, MR-PRESSO, and MR-Egger) was used to explore the genetic effects of exposure factors on the risk of all breast cancers, ER+ breast cancer, and ER− breast cancer. Results SMR analysis reported that elevated HMGCR expression was significantly associated with the increased incidence risk of all breast cancers and ER+ breast cancer (P=0.044 and P=0.039, respectively) but not with the change in incidence risk of ER− breast cancer (P=0.190); the other five regulatory genes were not significantly correlated with the change in incidence risk of all breast cancers, ER+ breast cancer, and ER− breast cancer (all P>0.05). IVW analysis reported that under the regulation of HMGCR, elevated levels of peripheral TC, LDL-C, and non-HDL-C significantly increased the incidence risk of all breast cancers (P=1.160e-05, P=1.248e-05, and P=1.869e-05) and the incidence risk of ER+ breast cancer (P=3.181e-04, P=2.231e-04, and P=3.520e-04), but they were not associated with a change in the incidence risk of ER− breast cancer (P=0.062, P=0.133, and P=0.055). The results of MR-PRESSO and MR-Egger analyses supported the IVW results. Conclusion Statins could reduce the incidence risk of ER+ breast cancer at the genetic level, but there is no such protective effects on ER− breast cancer.

Ecological cultivation is an important way for the sustainable production of traditional Chinese medicine in the context of the carbon peaking and carbon neutrality goals. Facility cultivation and simulative habitat cultivation modes have been developed and applied to develop the endangered Dendrobium huoshanense on the basis of protection. However, the differences in the greenhouse gas emissions and global warming potential of these cultivation modes remain unexplored, which limits the accurate assessment of carbon-friendly ecological cultivation modes of D. huoshanense. Greenhouse gas emission flux monitoring based on the static chamber method provides an effective way to solve this problem. Therefore, this study conducted a field experiment in the facility cultivation and simulative habitat cultivation modes at a D. huoshanense cultivation base in Dabie Mountains, Anhui Province. From April 2023 to March 2024, samples of greenhouse gases were collected every month, and the concentrations of CO_2, CH_4, and N_2O of the samples were then detected by gas chromatography. The greenhouse gas emission fluxes, cumulative emissions, and global warming potential were further calculated, and the following results were obtained.(1)The two cultivation modes of D. huoshanense showed significant differences in greenhouse gas emission fluxes, especially the CO_2 emission flux, with a pattern of facility cultivation>simulative habitat cultivation [(35.60±11.70)mg·m~(-2)·h~(-1) vs(2.10±4.59)mg·m~(-2)·h~(-1)].(2) The annual cumulative CO_2 emission flux in the case of facility cultivation was significantly higher than that of simulative habitat cultivation[(3 077.00±842.00)kg·hm~(-2) vs(221.00±332.00)kg·hm~(-2)], while no significant difference was found in annual cumulative CH_4 and N_2O emission fluxes.(3) The facility cultivation mode had a significantly higher global warming potential than the simulative habitat cultivation mode [(3 053.00±847.00)kg·hm~(-2) vs(196.00±362.00)kg·hm~(-2)]. Overall, the simulative habitat cultivation of D. huoshanense has obvious carbon-friendly characteristics compared with facility cultivation, which is in line with the concept of ecological cultivation of medicinal plants. This study is of great reference significance for the implementation and promotion of the ecological cultivation mode of D. huoshanense under carbon peaking and carbon neutrality goals.
Dendrobium/chemistry* ; Greenhouse Gases/metabolism* ; Carbon/analysis* ; Ecosystem ; Carbon Dioxide/metabolism* ; China ; Global Warming

Diterpenoid ferruginol is a key intermediate in biosynthesis of active ingredients such as tanshinone and carnosic acid.However, the traditional process of obtaining ferruginol from plants is often cumbersome and inefficient. In recent years, the increasingly developing gene editing technology has been gradually applied to the heterologous production of natural products, but the production of ferruginol in microbe is still very low, which has become an obstacle to the efficient biosynthesis of downstream chemicals, such as tanshinone. In this study, miltiradiene was produced by integrating the shortened diterpene synthase fusion protein,and the key genes in the MVA pathway were overexpressed to improve the yield of miltiradiene. Under the shake flask fermentation condition, the yield of miltiradiene reached about(113. 12±17. 4)mg·L~(-1). Subsequently, this study integrated the ferruginol synthase Sm CYP76AH1 and Sm CPR1 to reconstruct the ferruginol pathway and thereby realized the heterologous synthesis of ferruginol in Saccharomyces cerevisiae. The study selected the best ferruginol synthase(Il CYP76AH46) from different plants and optimized the expression of pathway genes through redox partner engineering to increase the yield of ferruginol. By increasing the copy number of diterpene synthase, CYP450, and CPR, the yield of ferruginol reached(370. 39± 21. 65) mg·L~(-1) in the shake flask, which was increased by 21. 57-fold compared with that when the initial ferruginol strain JMLT05 was used. Finally, 1 083. 51 mg·L~(-1) ferruginol was obtained by fed-batch fermentation, which is the highest yield of ferruginol from biosynthesis so far. This study provides not only research ideas for other metabolic engineering but also a platform for the construction of cell factories for downstream products.
Saccharomyces cerevisiae/genetics* ; Diterpenes/metabolism* ; Metabolic Engineering ; Fermentation ; Abietanes

Sophorae Flavescentis Radix is one of the commonly used traditional Chinese medicine in China, and a large amount of pharmaceutical residue generated during its processing and production is discarded as waste, which not only wastes resources but also pollutes the environment. Therefore, elucidating the chemical composition of the residue of Sophorae Flavescentis Radix and the differences between the residue and Sophorae Flavescentis Radix itself is of great significance for the comprehensive utilization of the residue. This study, based on ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS) technology combined with multivariate statistical methods, provides a thorough characterization, identification, and differential analysis of the overall components of Sophorae Flavescentis Radix and its residue. Firstly, 61 compounds in Sophorae Flavescentis Radix were rapidly identified based on their precise molecular weight, fragment ions, and compound abundance, using a self-constructed compound database. Among them, 41 compounds were found in the residue, mainly alkaloids and flavonoids. Secondly, through principal component analysis(PCA) and orthogonal partial least squares discriminant analysis(OPLS-DA), 15 key compounds differentiating Sophorae Flavescentis Radix from its residue were identified. These included highly polar alkaloids, such as oxymatrine and oxysophocarpine, which showed significantly reduced content in the residue, and less polar flavonoids, such as kurarinone and kuraridin, which were more abundant in the residue. In summary, this paper clarifies the overall composition, structure, and content differences between Sophorae Flavescentis Radix and its residue, suggesting that the residue of Sophorae Flavescentis Radix can be used as a raw material for the extraction of its high-activity components, with promising potential for development and application in cosmetics and daily care. This research provides a scientific basis for the future comprehensive utilization of Sophorae Flavescentis Radix and its residue.
Drugs, Chinese Herbal/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Mass Spectrometry/methods* ; Sophora/chemistry* ; Flavonoids/chemistry* ; Alkaloids/chemistry*

With the vigorous development of computers and internet, the construction of the information management system for Occupational Health Technical Service (OHTS) institutions in China has achieved impressive progress. But for the management of OHTS institutions, there are relatively few systems that can fully explore and utilize OHTS information. Base on this background, in light of the actual situation of the OHTS institution in Henan Province, an OHTS Information Management System was developed under the Java Spring Boot framework, with a MySQL database and a B/S multi-tier architecture. The platform integrates a vertical three-level network of ″provincial-municipal-county/district″ and a horizontal network involving health commissions, disease prevention and control bureaus, Centers for Disease Control and Prevention (occupational disease prevention and treatment institutes), and OHTS institutions. The system includes five core modules: dynamic management of institutional and personnel qualifications, full-process project supervision (including five categories of technical services such as pre-evaluation and control-effectiveness evaluation), multidimensional decision analysis (including eight statistical indicators of institutional distribution, equipment allocation, and occupational hazard factors), rapid generation and automated submission of various reports, and early warning and intelligent supervision. The system has been implemented in 61 OHTS institutions in Henan Province, improving the ″off-site supervision rate″ of supervision department and promoting the standardization and digital transformation of occupational health services.

Cardiac surgery patients often present with multiple comorbidities,the risk of periop-erative complications and the complexity of postoperative rehabilitation have significantly increased,posing higher demands on comprehensive perioperative management.Preoperative exercise pre-reha-bilitation,as a multidisciplinary collaborative intervention strategy,has been demonstrated to signifi-cantly improve the clinical prognosis of patients undergoing elective cardiac surgery by enhancing their cardiopulmonary function,muscle strength,and overall physiological functional reserve,thereby in-creasing the body's tolerance to surgical stress.Although phase-specific research achievements have been made domestically and internationally in the field of exercise pre-rehabilitation,its standardized implementation and clinical translation on a global scale still face numerous obstacles,necessitating systematic review and in-depth exploration.Therefore,this study aimed to conduct a systematic re-view of the intervention protocols,clinical efficacy,safety,and feasibility of preoperative exercise pre-rehabilitation in patients undergoing elective cardiac surgery,with the goal of providing theoretical evidence and practical references for optimizing perioperative management pathways and promoting the implementation of enhanced recovery after surgery concepts.