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.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

Aim To investigate the effect of p-AMPK activity on autophagy in different subtypes of MDA-MB-231(triple-negative breast cancer cells)and MCF-7(estrogen receptor-positive cells)and its regulatory mechanism.Methods MDA-MB-231 cells were trea-ted with EBSS,Baf-A1,and EBSS+Baf-A1 for four hours,and MCF-7 cells for eight hours.The effects of autophagy on cell proliferation and apoptosis were ob-served,mitochondrial morphology was examined,and the expression of autophagy markers LC3B,P62,LAMP1,TOM20,AMPK,p-AMPK,ULK1,and Bec-lin1/VPS34 proteins was detected.The autophagy pathway was validated by inhibiting AMPK activity.Results Breast cancer cells underwent autophagy af-ter starvation induction(EBSS),with inconsistent au-tophagy processes observed in different subtypes of breast cancer cells.Autophagy inhibited cell prolifera-tion.In MDA-MB-231 cells,autophagy led to an in-crease in p-AMPK levels and a decrease in ULK1 lev-els,initiating autophagy through p-AMPK activation of ULK1.In MCF-7 cells,both p-AMPK and ULK1 levels decreased after autophagy,suggesting that autophagy might not be mediated by p-AMPK activation.Conclu-sions MDA-MB-231 cells primarily initiate autophagy by directly activating ULK1 by p-AMPK,independent of the MTOR pathway.In MCF-7 cells autophagy might be triggered by inhibiting MTOR through AMPK activity or directly activating MTOR through other up-stream factors.Regulating p-AMPK activity based on the autophagy pathways in different cell subtypes could enable more precise targeting and treatment of different types of breast cancer.

Objective:To evaluate the clinical rehabilitation effect of external counterpulsation(ECP)on patients with coronary heart disease(CHD)by meta-analysis.Methods:We searched the databases of CNKI,WanFang,VIP,CBM,PubMed,Web of Science,Cochrane Library and Embase for randomized controlled trials(RCTs)and prospective cohort studies upon rehabilitative effect of ECP on CHD patients before May 2024.And meta-analysis was conducted to calculate the pooled MD and 95％CI using the random(P＜0.5 or I2≥50％)or fixed effect models(other situations).Results:13 eligible literatures were finally included in the meta-analysis.Compared with participants in control group,those in trial group had significant higher left ventricular ejection fraction(MD=4.15,95％CI 2.55～5.76,P＜0.001),stroke volume(MD=9.11,95％CI 7.59～10.64,P＜0.001),peak oxygen uptake(MD=5.42,95％CI 2.53～8.32,P＜0.001),6-min walking distance(MD=31.14,95％CI 24.89～37.40,P＜0.001),metabolic equiv-alent(MD=0.58,95％CI 0.45～0.71,P＜0.001),exercise duration time(SMD=0.77,95％CI 0.55～0.99,P＜0.001),oxygen pulse(MD=0.88,95％CI 0.68～1.09,P＜0.001),and significant lower left ventricular end-diastolic diameter(MD=-3.19,95％CI-5.20～-2.61,P＜0.001).Conclusion:This study showed that ECP could effectively improve heart function,exercise capacity and tolerance of CHD patients.

At present,breast cancer is still the first place in the global incidence and mortality of female cancer.Searching for reliable biological markers plays an extremely important role in clarifying the early diagnosis of breast cancer and improving the long-term survival rate and prognosis of breast cancer patients.In recent years,long non-coding RNA HOTAIR(LncRNA HOTAIR)is still the focus of research by many scholars,and HOTAIR is closely related to the occurrence and development of a variety of malignant tumors.The expression of HOTAIR is particularly obvious in breast cancer patients.More and more studies have shown that HOTAIR is highly expressed in both peripheral blood and breast cancer tissues of breast cancer patients,and is closely related to the proliferation,metastasis and drug resistance of breast cancer.HOTAIR may become an important biomarker for the early diagnosis of breast cancer and a target for breast cancer treatment.

Chronic kidney disease is characterized by complex pathophysiology. In recent years, research has indicated that gut microbiota dysbiosis plays a key role in the progression of chronic kidney disease. In patients with chronic kidney disease, the intestinal barrier function is compromised, allowing enteric metabolic toxins and bacterial translocation into the systemic circulation, which exacerbates the systemic inflammatory response associated with chronic kidney disease. Probiotics, as active microorganisms that regulate gut microbiota, have gradually attracted attention for their potential role in the treatment of chronic kidney disease. This review focuses on the research progress on probiotics for the treatment of chronic kidney disease.

At present,breast cancer is still the first place in the global incidence and mortality of female cancer.Searching for reliable biological markers plays an extremely important role in clarifying the early diagnosis of breast cancer and improving the long-term survival rate and prognosis of breast cancer patients.In recent years,long non-coding RNA HOTAIR(LncRNA HOTAIR)is still the focus of research by many scholars,and HOTAIR is closely related to the occurrence and development of a variety of malignant tumors.The expression of HOTAIR is particularly obvious in breast cancer patients.More and more studies have shown that HOTAIR is highly expressed in both peripheral blood and breast cancer tissues of breast cancer patients,and is closely related to the proliferation,metastasis and drug resistance of breast cancer.HOTAIR may become an important biomarker for the early diagnosis of breast cancer and a target for breast cancer treatment.

To achieve the national objectives of improving medical quality and safety,the Shanghai Shenkang Hospital Development Center has formulated a list of major targets,tasks,and key results based onthe Objective and Key Results (OKR) method.The primary approaches adopted include establishing an organizational structure to advance medical quality and safety supervision,setting up a series of quantitative indicators for medical quality and safety targets,formulating standardized management systems,building an information platform,and strengthening supervision.It argues that the adoption of OKR can effectively promote the implementation of national target management for improving medical quality and safety,establish a cross-institutional management network for medical quality and safety,strengthen process management,and effectively drive continuous improvement in medical quality and safety.