Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Objective To investigate the factors involved in the development of thyroid nodules and the correlation between homocysteine(Hcy)and albumin-globulin ratio(AGR)and thyroid autoantibodies in adults.Methods As a retrospective study,a total of 1 427 people who received physical examination at the Second Hospital Affilia-ted to Hebei North College from October 2019 to August 2020 and the clinical data of the subjects who fulfilled the criteria of NAR were selected for analysis by simple random sampling.All of subjects underwent thyroid color ultrasound scanning and were divided into a control group(without thyroid nodules,n=52)and an observation group(with thyroid nodules,n=48).The general clinical data of the two study groups were compared,and the correlation between Hey and AGR and thyroid autoantibodies was analyzed.Confunding factors affecting the inci-dence of thyroid nodules were screened using multifactorial unconditional logistic regression analysis.Results The observation group showed statistically significant differences in gender,age,diastolic blood pressure,systolic blood pressure,Hey,AGR,TGAb,and TPOAb as compared to the control group(P＜0.05);Using adult Hcy as the dependent variable and Spearman's correlation analysis of AGR,TGAb and TPOAb,adult Hcy was nega-tively correlated with AGR(r=-0.384,P＜0.05)and TGAb and TPOAb were positively correlated(r=0.218,0.224,P＜0.05);Using age,sex,diastolic blood pressure,systolic blood pressure,Hcy,AGR TGAb and TPOAb as independent variables and thyroid nodules as dependent variables,a multifactor logistic regression analysis was performed in 100 subjects who experienced physical check.The analysis showed that age ≥40 years and female were relevant factors for the development of thyroid nodules factors(P＜0.05),Hcy,AGR,TGAb and TPOAb were correlated with thyroid nodules(P＜0.05).Conclusions Thyroid nodules are more common in middle-aged women,and there is a correlation between Hcy,AGR,TGAb,and TPOAb levels and thyroid nod-ules.Regular thyroid screening examination should be carried out based on the above indicators.

Objective To mine adverse drug event(ADE)signals of doxycycline using the U.S.Food and Drug Administration Adverse Event Reporting System(FAERS)database,and provide scientific evidence for clinical medication safety.Methods The data from the FAERS database between the first quarter of 2004 and the first quarter of 2024 were extracted.After data cleaning and standardization,ADE reports with doxycycline as the main suspected drug were screened.The system organ class(SOC)of ADE was performed using MedDRA,and the reporting odds ratio method and Medicines and Healthcare products Regulatory Agency method were used to mine ADE signals.The information component method was also used to evaluate signal strength.Results A total of 43 126 ADE reports with doxycycline as the primary suspected drug were collected,involving 14 642 patients,with a higher proportion of female patients(57.32％).There were 555 related ADE signals involving 26 SOC,with the top 5 SOC being gastrointestinal disorders,skin and subcutaneous tissue disorders,injuries,poisonings,and procedural complications,psychiatric disorders,and infections and infestations.The top 5 ADE signals with the highest signal intensity were Hatch reaction,sclerosing cholangitis,esophageal ulcer,gastrointestinal mucosal necrosis,and gastrointestinal injury.Among the ADE signals with the strongest signal strength not listed in the package insert,the top five were sclerosing cholangitis,nephrogenic diabetes insipidus,minimal change glomerular nephritis,diabetes insipidus and Sixth cranial nerve paralysis.Conclusion In clinical practice,particular attention should be paid to the frequent ADEs caused by doxycycline,as well as those not yet documented in the package insert,which involve multiple SOC such as renal and urinary disorders,hepatobiliary diseases,blood and lymphatic system disorders,and endocrine disorders.Therefore,clinical pharmacists should play a key role in assisting clinicians to develop and implement prevention plans for ADEs,thereby improving the safety of doxycycline in clinical use.

Objective:To establish a method of serum detection by Raman spectroscopy for the diagnosis of gastric cancer.Methods:Between April and November 2019, 110 patients with gastric cancer [73 males, 37 females, age (57.4±10.3) years] and 74 patients with colorectal cancer [48 males and 26 females, aged (58.3±12.2) years] were collected at the First Affiliated Hospital of Army Military Medical University, along with 100 healthy subjects [59 males and 41 females, aged (55.6±10.61) years] during the same period. Fasting venous blood serum samples were collected from the subjects. A Raman spectrometer XploRA PLUS was used in this experiment, with an excitation light source of 532 nm, a field of view of 100 times, and a spectrum range of 200-2 000 cm -1, etc. The serum samples were detected by nondestructive and non-contact rapid detection, and the Raman spectra of serum samples were collected. Using the Raman spectrum acquisition and processing supporting software LabSpec6 to smooth, baseline, and normalize the obtained Raman spectrum. Multivariate statistical analysis software SIMCA14.1 were applied to import and analyze the obtained Raman spectrum data by principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), and other methods for statistical analysis. An operating characteristic curve (ROC) was constructed to evaluate the model analysis effect between serum samples of healthy people and those with gastric cancer. Serum samples from the colorectal cancer group were used to verify the reliability of the model. Results:Six Raman peaks with good repeatability were detected in serum samples in health and gastric cancer group, and peaks were located at 1 001.17, 1 154.63, 1 337.89, 1 446.85, 1 515.33, and 1 658.34 cm -1, respectively. Raman intensities at six Raman peaks were significantly different between healthy and gastric cancer groups. At the displacement of 1 001.17, 1 154.63, and 1 515.33 cm -1, the Raman intensity in the healthy group was higher than that in the gastric cancer group. At 1 337.89, 1 446.85, and 1 658.34 cm -1 displacement, the Raman intensity of the gastric cancer group was higher than that of the healthy group. An OPLS-DA model was constructed to analyze the serum samples of the healthy group and the gastric cancer group. In the model, R 2 is the fitting power, and Q 2 is the predictive ability. The closer the values of R 2 and Q 2 are to 1, the better the performance of the model, and the obtained model's R 2X(cum)=0.809, R 2Y(cum)=0.819, Q 2(cum)=0.758. ROC characteristic curve was drawn based on the OPLS-DA model. The area under the curve (AUC) of the gastric cancer group was 0.998. Six peaks with good repeatability were detected in the serum Raman spectra of gastric cancer stage Ⅰ, Ⅱ, Ⅲ, and Ⅳ, which were located at the displacement of 1 001.85, 1 155.07, 1 338.36, 1 445.75, 1 515.92, and 1 657.68 cm -1, respectively, and at the displacement of 1 155.07 and 1 515.92 cm -1. The Raman intensity of gastric cancer stage Ⅳwas significantly higher than that of gastric cancer stages Ⅰ, Ⅱ, and Ⅲ. Conclusions:According to the model reliability verification, the healthy group, gastric cancer group and colorectal cancer group can also be effectively separated based on OPLS-DA results; it showed a good performance in separating the healthy group from the gastric cancer group. It is possible to detect serum samples from healthy people and gastric cancer patients unlabeled by combining Raman spectroscopy and the OPLS-DA method in multivariate statistics.

OBJECTIVE：To optim ize the ultrafiltration technology of enzymatic hydrolysate from Eucommia ulmoides peel. METHODS：The single factor test was adopted to investigate the effects of molecular weight of ultrafiltration membrane ，liquid temperature，operating pressure ，operating frequency ，membrane filtration time ，liquid concentration and pH on transfer rates of aucubin，geniposide and chlorogenic acid as well as solid removal rate in enzymatic hydrolysate from E. ulmoides peel. Setting the molecular cut off of fixed ultrafiltration membrane of 100 000，liquid concentration of 7 g/L，and pH value of 7，the ultrafiltration technology was optimized by Box-Behnken design response-surface methodology and validated with liquid temperature ，operating pressure，operating frequency and membrane passing time as factors ，using comprehensive scores calculated from transfer rates of aucubin，geniposide and chlorogenic acid as well as solid removal rate as indexes. RESULTS ：The optimal ultrafiltration technology of enzymatic hydrolysate from E. ulmoides peel was as follows as liquid temperature of 35 ℃，operating pressure of 0.5 MPa，operating frequency of 35 Hz and membrane passing time of 42 min. Results of validation tests showed that the comprehensive scores of the transfer rates of aucubin ，geniposide and chlorogenic acid as well as solid removal rate in enzymatic hydrolysate from E. ulmoides peel was 78.06％（RSD＝1.43％，n＝3），and its relative error with the predicted value （77.18％） was 1.14％. CONCLUSIONS ：The optimized ultrafiltration technology is stable and reliable ，and can be used for the ultrafiltration purification of enzymatic hydrolysate from E. ulmoides peel.

Objective:To retrieve and summarize the evidence of implementation and management of oral nutrition supplement in patients with malignant tumors, and provide reference and guidance for the intervention of oral nutrition supplement in clinical patients.Methods:China National Knowledge Infrastructure (CNKI) , Wanfang, Chinese Biological Medical Disc, Chinese Society for Parenteral and Enteral Nutrition, MedSci website, UpTo Date, BMJ Best Practice, Cochrane Library, OVID Evidence-based Database, JBI Evidence-based Health Care Database, PubMed, Web of Science, Embase Database, The National Guideline Clearinghouse of the USA, European Society for Parenteral and Enteral Nutrition website and American Society for Parenteral and Enteral Nutrition Web were searched and the retrieval time was from the establishment of the database to March 5, 2020. Literature was screened based on the "6S" model of evidence-based medicine, and the quality of different types of literature was evaluated.Results:A total of 10 articles were screened, including 3 guidelines, 3 expert consensus, 2 systematic reviews, 1 clinical decision, and 1 randomized controlled study.The evidence was summarized from 6 aspects, including nutrition screening and assessment before the use of oral nutrition supplement, application scope, risk assessment of use, preparation selection, key points of clinical implementation, clinical efficacy and evaluation, and the best 25 pieces of evidence were summarized.Conclusions:Clinical medical staff need to pay attention to the implementation and management of oral nutritional supplement. Oral nutritional supplement interventions should be carried out according to the actual conditions of the patients to give full play to the value of oral nutritional supplement and benefit patients.

OBJECTIVE：To study the toxicity mechanism of lipid-soluble alkaloids of Aconitum carmichaeli to adjuvant-induced arthritis （AIA） model rats. METHODS： Totally 40 rats were randomly divided into blank group （ultrapure water）， model group （ultrapure water） and A. carmichaeli lipid-soluble alkaloids low-dose and high-dose groups （12.5， 35 mg/kg）， with 10 rats in each group. Except for blank group， rats in other groups were given complete Freund’s adjuvant 0.1 mL on the right hind paw to induce AIA model. 19 d after modeling， they were given relevant medicine intragastrically， once a day. After 14 d of administration， endogenous metabolites were separated and identified from plasma by UPLC-LTQ/Orbitrap MS. Then， the collected data were analyzed by principal component analysis （PCA） and partial least squares-discriminant analysis （PLS-DA）. Variable importance projection （VIP）＞1 and P value （＜0.05） were used to screen differential metabolites in plasma. Retrieving the database of Kyoto Encyclopedia of Genes and Genomes according to the differential metabolites，the toxic mechanism of A. carmichaeli liposoluble alkaloids to AIA rats were speculated. RESULTS： A total of 57 plasma metabolites were indentified， and 11 differential metabolites such as L-proline， 6-hydroxynicotinic acid and adenosine were identified. After inducing AIA model， the plasma contents of L-proline and uridylic acid were decreased significantly （P＜0.05 or P＜0.01）， and the content of deoxycytidine was increased significantly （P＜0.01）. Low dose of A. carmichaeli lipid-soluble alkaloids could decrease the plasma contents of adenosine and L-proline in rats （P＜0.05 or P＜0.01）， while the plasma contents of deoxycholic acid was increased significantly （P＜0.05）. High dose of A. carmichaeli lipid-soluble alkaloids could decrease the plasma contents of 6-hydroxynicotinic acid， adenosine， carnitine， L-proline， N-formylaminobenzoic acid were decreased significantly （P＜0.05 or P＜0.01）， while the plasma contents of deoxycholic acid， L-arginine， deoxycytidine and L-lysine were increased significantly （P＜0.05 or P＜0.01）. CONCLUSIONS： The toxicity of low-dose of A. carmichaeli lipid-soluble alkaloids to AIA model rats is less； the toxicity of high-dose of A. carmichaeli lipid-soluble alkaloids to AIA model rats may be related to abnormal bile secretion， lysine biosynthesis and metabolic disorders of purine， pyrimidine， tryptophan， proline and arginine.

OBJECTIVE： To establish a method for content determination of aflatoxin （AF） G2， G1， B2 and B1 in Qinghuo tablets （capsules）， and to evaluate the safety of the preparation. METHODS： HPLC-post-column photochemical derivatization was adopted， and 266 batches of Qinghuo tablets （capsules） from 37 manufacturers as sample. The determination was performed on Agilent C18 column with mobile phase consisted of water-acetonitrile-methanol （V/V/V， gradient elution） at the flow rate of 1.0   mL/min. The column temperature was set at 40 ℃. Excitation wavelength and emission wavelength of fluorescence detector were 360 and 450 nm. RESULTS： The linear ranges of AF G2， AF G1， AF B2 and AF B1 were 10.197-101.97 （r＝0.999 7）， 10.197-101.97 （r＝0.999 6）， 9.958 6-99.586 （r＝0.999 1）， 9.999 0-99.990 （r＝0.998 3） pg， respectively. RSDs of precision （n＝6）， reproducibility （n＝6） and stability tests （12 h， n＝5） were all lower than 3.0％. The detection limits were 0.80， 4.00， 0.80 and 4.00 pg， respectively. The quantitation limits were 1.60， 8.00， 1.60 and 8.00 pg， respectively. The recoveries were 85％-90％， 85％-90％， 55％-65％， 65％-75％ （RSD＝1.8％-4.7％， n＝6）. AF G2， AF G1， AF B2 and AF B1 were not detected in 266 batches of samples. CONCLUSIONS： This method is suitable for the determination of AF in Qinghuo tablets （capsules）. Although AF was not detected in the sample， it is advisable to add the determination of AF so as to improve its safety.