Objective To analyze dynamic contrast-enhanced MRI (DCE-MRI) radiomic features using machine learning algorithms, and to develop and validate a predictive model for HER-2 status in breast cancer. Methods The DCE-MRI images of 272 treatment-naive female patients with breast cancer between 2020 and 2022 were included in this study. Regions of interest (ROIs) were manually segmented using 3d-Slicer software, and radiomic features were extracted. All patients were randomly divided into training sets or validation sets at a ratio of 4∶1. The least absolute shrinkage and selection operator (LASSO) algorithm was used for feature screening on the training set, followed by the development of predictive models using six machine learning algorithms. Internal cross-validation was performed to compare the performance differences between the models. The best-performing model was selected, trained on the training set, and evaluated on the validation set. Evaluation metrics included area under the curve (AUC), sensitivity, specificity, precision, and recall rate. Results The clinical data of patients in the training set and validation set showed no significant differences. Five features were identified by the LASSO algorithm. With these features, six machine learning models were developed on the training set, and their predictive performance was internally cross-validated using the bagging method. XGBoost model had the highest mean AUC (0.696), followed by RF model (0.690); XGBoost model had the highest mean precision (0.756), followed by LR and RF models. Therefore, XGBoost was the optimal model. An HER-2 predictive model was built using the XGBoost algorithm on the training set and applied to the validation set. The AUC, precision, sensitivity, and specificity of the predictive model on the validation set were calculated, and ROC curves, precision-recall curves, calibration curves, and decision-making curves were plotted. Conclusion This study constructed and evaluated different DCE-MRI radiomics-based machine learning models for predicting HER-2 status in breast cancer. Among them, XGBoost algorithm performed the best and has the potential to become a new non-invasive method for preoperative prediction of HER-2 status, providing reliable evidence for personalized clinical diagnosis and treatment.

ObjectiveTo observe the effects of Coptidis Rhizoma-Fermentum Rubrum on non-alcoholic fatty liver disease （NAFLD） in mice and explore its possible mechanisms. MethodSixty male SPF C57BL/6J mice were randomly divided into six groups： control group， model group， low-， medium-， and high-dose Coptidis Rhizoma-Fermentum Rubrum group （0.75， 1.5， 3 g·kg^-1）， and metformin group （0.075 g·kg^-1）， with 10 mice in each group. NAFLD mouse models were induced by high-fat diet feeding for 24 weeks. The low， medium， and high-dose Coptidis Rhizoma-Fermentum Rubrum groups were administered corresponding doses of Coptidis Rhizoma-Fermentum Rubrum by gavage， while the control and model groups received an equivalent amount of saline for four weeks. Serum total cholesterol （TC）， triglycerides （TG）， free fatty acids （FFA）， and liver function markers including alanine aminotransferase （ALT） and aspartate aminotransferase （AST） were measured using an automatic biochemical analyzer. Hematoxylin-eosin （HE） and oil red O staining were used to detect liver lipid deposition， and Prussian blue staining was used to measure liver ferrous ion levels. Western blot was performed to detect the expression of key proteins in the nuclear factor erythroid-2-related factor 2 （Nrf2）-glutathione peroxidase 4 （GPX4） axis. ResultAfter 24 weeks of high-fat feeding， compared with the control group， the model group showed significant increases in body weight， liver weight and liver index， and serum lipid levels （P<0.01）， as well as substantial hepatic lipid deposition with marked steatosis. Compared with the model group， Coptidis Rhizoma-Fermentum Rubrum intervention reduced body weight （P<0.01）， liver weight and liver index （P<0.01）， and serum lipid levels （P<0.05， P<0.01）， improved liver function （P<0.01）， and decreased hepatic lipid deposition， with the low-dose Coptidis Rhizoma-Fermentum Rubrum group showing the best effect. Western blot results showed that compared with those in the control group， the expression levels of Nrf2， heme oxygenase-1 （HO-1）， kelch-like ECH-associated protein 1（Keap1）， and GPX4 proteins in the model group were decreased （P<0.05， P<0.01）. Compared with the model group， Coptidis Rhizoma-Fermentum Rubrum increased the expression levels of these proteins （P<0.05， P<0.01）. ConclusionCoptidis Rhizoma-Fermentum Rubrum can alleviate fatty liver in mice， improve liver function， and reduce hepatic lipid deposition， possibly by regulating the Nrf2/GPX4 ferroptosis axis.

Fungal keratitis is a serious blinding eye disease. The development of fungal infections depends primarily on the interaction of fungal virulence with host immune defense factors. The cornea is considered an immune-privileged organ, and resident macrophages are the main immune cells that respond to the heterogeneity exhibited by the microenvironment with their polarization. In the early stage of infection, macrophages polarize towards M1, which promotes inflammation and facilitates fungal clearance but produces a cellular storm that exacerbates immune damage; in the late stage of infection, macrophages polarize towards M2, which suppresses the inflammatory response and facilitates tissue repair, but may be immunosuppressed or even immune escape to the detriment of pathogen clearance. The balance between pro-inflammatory and anti-inflammatory responses is key to maintaining the functional integrity of the cornea. Current antifungal drug therapy is limited, so it is particularly important to find a therapeutic target for the inflammatory response triggered by the immune response in addition to antifungal therapy. In this review, the functional and phenotypic characterization of macrophage subsets associated with fungal keratitis was reviewed, more in-depth research is needed to explore the specific mechanisms by which macrophage polarization and their impact on fungal keratitis. Targeted regulation of macrophage differentiation based on their phenotype and function could be an effective approach to treat and manage fungal keratitis in the future.

Adjuvant chemoradiotherapy,molecular targeted therapy,and immunotherapy are frequently employed to extend the survival of patients with advanced gastric cancer(GC).However,most of these treatments have toxic side effects,drug resistance,and limited improvements in survival and quality of life.Therefore,it is crucial to discover and develop new medications targeting GC that are highly effective and have minimal toxicity.In previous studies,the total terpene extract from the stem of Celastrus orbiculatus demonstrated anti-GC activity;however,the specific mechanism was unclear.Our research utilising co-immunoprecipitation-mass spectrometry(Co-IP-MS),polypyrimidine tract binding protein 1(ptbp1)clustered regularly interspaced short palindromic repeat-associated protein 9(Cas9)-knockout(KO)mouse model,tissue microarray,and functional experiments suggests that alpha actinin-4(ACTN4)could be a significant biomarker of GC.PTBP1 influences actin cytoskeleton restructuring in GC cells by interacting with ACTN4.Celastrus orbiculatus stem extract(COE)may directly target ACTN4 and affect the interaction between PTBP1 and ACTN4,thereby exerting anti-GC effects.

Syndrome differentiation and treatment is a unique mode of diagnosis in traditional Chinese medicine （TCM）. The establishment of scientific and standardized syndrome diagnosis standards is an important link to evaluate the clinical efficacy of TCM objectively and systematically， and also a prerequisite for the promotion and development of TCM to obtain international recognition. This article reviewed the basic modes and existed problems of the current syndrome diagnosis criteria， and proposed to construct a multidimensional core information set integrating the minimized core symptoms， the artificial intelligence signs， the multi-modal laboratory indicators， and multi-omics specific markers， so as to present syndrome characteristics from multiple perspectives systematically. This paper also described the basic mode， constructure， as well as the process and methodology to be adopted in the establishment of the standardized diagnostic research method. The core information set of diagnostic symptoms not only took into account the specificity of the disease， but also improved the inconsistency due to the complexity and subjectivity of the syndrome differentiation， thereby providing a methodological basis for the standardization of TCM syndrome differentiation in clinical research.

5-aminovalanoic acid (5AVA) can be used as the precursor of new plastics nylon 5 and nylon 56, and is a promising platform compound for the synthesis of polyimides. At present, the biosynthesis of 5-aminovalanoic acid generally is of low yield, complex synthesis process and high cost, which hampers large-scale industrial production. In order to achieve efficient biosynthesis of 5AVA, we developed a new pathway mediated by 2-keto-6-aminohexanoate. By combinatory expression of L-lysine α-oxidase from Scomber japonicus, α-ketoacid decarcarboxylase from Lactococcus lactis and aldehyde dehydrogenase from Escherichia coli, the synthesis of 5AVA from L-lysine in Escherichia coli was achieved. Under the initial conditions of glucose concentration of 55 g/L and lysine hydrochloride of 40 g/L, the final consumption of 158 g/L glucose and 144 g/L lysine hydrochloride, feeding batch fermentation to produce 57.52 g/L of 5AVA, and the molar yield is 0.62 mol/mol. The new 5AVA biosynthetic pathway does not require ethanol and H₂O₂, and achieved a higher production efficiency as compared to the previously reported Bio-Chem hybrid pathway mediated by 2-keto-6-aminohexanoate.
Nylons ; Lysine/metabolism* ; Hydrogen Peroxide/metabolism* ; Metabolic Engineering ; Plastics/metabolism* ; Fermentation ; Escherichia coli/metabolism* ; Aminocaproates/metabolism*

Objective:To explore changes in high-risk sexual behaviors and associated factors in HIV-infected men who have sex with men (MSM) in industrial workers, and provide evidence for designing behavioral interventions for this population.Methods:In this observational study, HIV-infected MSM were recruited in industrial workers using convenient sampling during August to September 2021. The sample size was estimated to be 530. A questionnaire was used and combined with routine follow-up to collect socio-demographic characteristics, high-risk sexual behaviors, partner notification, viral load testing and history of sexually transmitted diseases before and after diagnosis of HIV infection. The χ2 test was used to analyze the changes in high-risk sexual behaviors before and after diagnosis and logistic regression was conducted to identify factors associated with high-risk sexual behaviors. Results:A total of 560 HIV-infected MSM in industrial workers were recruited in this study. Of whom, 32.1% (180/560) had unprotected anal intercourse (UAI) within 12 months after diagnosis . The proportions of those having UAI with casual, commercial and regular same-sex partners significantly decreased from 73.4% (381/519), 75.1% (187/249) and 69.5% (207/298) within 12 months before diagnosis to 36.2% (146/403), 40.2% (86/214) and 34.2% (67/196) within 12 months after diagnosis , respectively. Educational level of college or above (a OR=0.41, 95% CI:0.23-0.71), passive anal sex (a OR=0.40, 95% CI:0.19-0.85), both active and passive anal sex after diagnosis (a OR=0.40, 95% CI:0.20-0.83) and no unprotected oral sex (a OR=0.02, 95% CI:0.01-0.05) were negatively associated with UAI within 12 months after diagnosis. Whereas, not considering necessary to use condom consistently after having repeated undetectable viral load (a OR=3.02, 95% CI:1.37-6.69) was positively associated with UAI within 12 months after diagnosis. Conclusions:Compared with that before diagnosis of HIV infection, although the prevalence of UAI seemed to decrease in HIV-infected MSM in industrial workers after diagnosis, nearly one third of them had high-risk sexual behaviors. Therefore, relevant interventions should be strengthened to reduce high-risk sexual behaviors.

Objective: To investigate the diagnostic value of serum α-enolase (ENO1) in the primary hepatocellular carcinoma. Methods: From May 2012 to March 2017, 163 cases with liver diseases who met the inclusion and exclusion criteria were admitted to the Infectious Diseases Department of the General Hospital of Ningxia Medical University. Among them, 28 cases were of chronic hepatitis B (CHB), 31 cases with liver cirrhosis (LC), 104 cases with hepatocellular carcinoma (HCC), and 18 healthy volunteers (NC). Patient data and serum samples were collected and liver disease related indicators were measured to detect ENO1 levels with enzyme-linked immunosorbent assay (ELISA). The measured indicators were expressed in median. Mann-Whitney U nonparametric test was used to analyze the differences between the data. A Spearman’s correlation analysis was used for bivariate correlation analysis. The sensitivity and specificity of ENO1 and alpha-fetoprotein in the diagnosis of liver cancer were analyzed by ROC curve. Results: Serum level of ENO1 in CHB group, LC group and HCC group was significantly higher than normal group. Serum level of ENO1 in HCC group was higher than CHB group (P = 0.001) and LC group (P < 0.01). Area under the curve (AUC) for serum ENO1 and alpha-fetoprotein were 0.782 (cut-off value 75.96, P = 0.000 1) and 0.800 (cut-off value 27.02, P = 0.000 1), respectively. There was a positive correlation between ENO1 and AFP (P = 0.001). The combined detection had significantly improved the detection efficiency (AUC = 0.835). Serum ENO1 was statistically significant (P < 0.05) in HCC tumor size (AUC = 0.663), tumor metastasis (AUC = 0.681), TNM stage (AUC = 0.710, stage I vs. II), and Edmondson grade (AUC = 0.685) (P < 0.05) and the elevated levels of ENO1 had significantly reduced (P < 0.05) the survival time. Conclusion ENO1 can be a new candidate marker for the diagnosis of early stage HCC and its progression.

This study aimed to optimize the ultrasonic extraction of gardenia oils from Gardenia jasminoides Ellis.by response surface analysis methodology (RSM).The duration of extraction,ratio of liquid to materials and extracting times were selected as impact factors based on single-factor experiment.RSM was adopted to learn the effects of the three factors on the extraction rate of Gardenia oil from Gardeniajasminoides Ellis.As a result,it was found that the duration of extraction was 28.7 min,while the ratio of liquid to materials was 11.62:1,and the number of extracting times were 3.36.Under this extracting condition,the average extraction rate of the oil was 13.5％ according to three validation experiments,fitting the predicted value well.In conclusion,it was demonstrated that the ultrasonic extraction method effectively improved the extraction rate of gardenia oil,providing a certain basis for the development and utilization of gardenia oil.

The National Excellent Course of Gynecology of Chinese Medicine is a main clinical subject of TCM,which puts emphasis on clinical application.The non-medical doctoral students are lack of the knowledge of traditional Chinese medicine and clinical experience,and the existing classroom teaching has the problem of the basic theory of traditional Chinese medicine being out of line with the clinical application,which has become the hindering factors of TCM gynecology teaching.By designing and perfecting the process of preparation before class-classroom teaching-discussion teaching-clinical probation-after class feedback,the related teaching teachers better improve the non medical doctoral students' ability to put the traditional Chinese medicine gynecology basic knowledge into clinical practice,which is well received by the students.