Objective:To assess the fall risk of hospitalized patients with cardiovascular diseases, analyze the related influencing factors, and construct a prediction model based on machine learning technology, so as to provide a basis for the fall management of hospitalized patients with cardiovascular diseases.Methods:This study was a retrospective cohort study. A total of 450 patients admitted to the Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University from June 2017 to June 2024 were selected as the research objects by convenience sampling method. By reviewing electronic medical records, trained nurses extracted the patients' general information and Activities of Daily Living Scale (ADL) scores during hospitalization. Lasso regression was used to screen risk factors, and machine learning libraries were used to construct support vector machine (SVM), decision tree, XGBoost, and neural network models. Bootstrap resampling method and area under the curve (AUC) were used to verify the model performance.Results:Among the 450 patients, there were 261 males and 189 females, with a mean age of (66.0 ± 8.4) years. Among them, 90 patients fell during hospitalization and 360 patients did not fall. The results of Lasso regression showed that ADL score ≤60 points, use of hypnotics, hypokalemia, nighttime toilet visits≥2 times, use of antihypertensive drugs, no caregiver, and history of atrial fibrillation were all risk factors for falls in hospitalized patients with cardiovascular diseases (regression coefficients ranging from 0.61 to 1.20, all P<0.01). Among the machine learning models, XGBoost had the best comprehensive performance (AUC=0.98), which was better than decision tree (AUC=0.66), SVM (AUC=0.95), and neural network (AUC=0.87). Conclusions:The fall risk of hospitalized patients with cardiovascular diseases is jointly affected by physiological, medication and behavioral factors, and the XGBoost model can effectively identify high-risk groups. In actual clinical work, nursing strategies can be optimized in combination with risk factors, and the application of intelligent fall prediction and assessment tools can be promoted.

Objective:To assess the fall risk of hospitalized patients with cardiovascular diseases, analyze the related influencing factors, and construct a prediction model based on machine learning technology, so as to provide a basis for the fall management of hospitalized patients with cardiovascular diseases.Methods:This study was a retrospective cohort study. A total of 450 patients admitted to the Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University from June 2017 to June 2024 were selected as the research objects by convenience sampling method. By reviewing electronic medical records, trained nurses extracted the patients' general information and Activities of Daily Living Scale (ADL) scores during hospitalization. Lasso regression was used to screen risk factors, and machine learning libraries were used to construct support vector machine (SVM), decision tree, XGBoost, and neural network models. Bootstrap resampling method and area under the curve (AUC) were used to verify the model performance.Results:Among the 450 patients, there were 261 males and 189 females, with a mean age of (66.0 ± 8.4) years. Among them, 90 patients fell during hospitalization and 360 patients did not fall. The results of Lasso regression showed that ADL score ≤60 points, use of hypnotics, hypokalemia, nighttime toilet visits≥2 times, use of antihypertensive drugs, no caregiver, and history of atrial fibrillation were all risk factors for falls in hospitalized patients with cardiovascular diseases (regression coefficients ranging from 0.61 to 1.20, all P<0.01). Among the machine learning models, XGBoost had the best comprehensive performance (AUC=0.98), which was better than decision tree (AUC=0.66), SVM (AUC=0.95), and neural network (AUC=0.87). Conclusions:The fall risk of hospitalized patients with cardiovascular diseases is jointly affected by physiological, medication and behavioral factors, and the XGBoost model can effectively identify high-risk groups. In actual clinical work, nursing strategies can be optimized in combination with risk factors, and the application of intelligent fall prediction and assessment tools can be promoted.

OBJECTIVE To identify the chemical components of Shenbai Jiedu Decoction(SBJDD),a traditional Chinese medi-cine(TCM)prescription clinically used for the treatment of colorectal adenoma(CRA),and explore the potential mechanism of SBJDD preventing and treating CRA carcinogenesis.METHODS An ultra-high performance liquid chromatography-time of flight-mass spectrometry(UPLC-Q-TOF-MS)method was established to detect the chemical components in the decoction of SBJDD and the plas-ma samples of rats after administration with SBJDD.Based on the network pharmacological method,SBJDD was screened for the poten-tial active ingredients at different stages of CRA carcinogenesis,and the mechanism of the anti-cancer effect of SBJDD was explored.In vitro experiments were also carried out to verify the mechanism of anti-colorectal cancer(CRC)action of SBJDD.RE-SULTS The detection data of UPLC-Q-TOF-MS showed that 152 components were found from SBJDD water extraction.41 chemical compounds were identified in plasma samples from rats administrated with SBJDD.Network pharmacology analysis indicated that during the CREI stage,the potential active ingredients in SBJDD,including epiberberine,and kushenol H,might affect target proteins such as PIK3CA,MAPK3 and PIK3CB.This,in turn,can influence signaling pathways like PI3K-AKT and Ras signaling pathways,and regulate biological processes like protein phosphorylation,and signal transduction.During the CRA stage,the potential active ingredi-ents from SBJDD,such as 3,7-dihydroxycoumarin,palmatine,and kushenol A,might affect target proteins such as AKT and EGFR.This can regulate the negative regulation of apoptotic process,and positive regulation of cell proliferation,and modify HIF-1,and Rap1 signaling pathways.During the progression of CRA carcinogenesis,potential active ingredients such as 3,7-dihydroxycouma-rin may interact with TP53,and impact the PI3K-AKT,and Thyroid hormone signaling pathways to regulate biological processes,in-cluding positive regulation of transcription from RNA polymerase Ⅱ promoter,and negative regulation of apoptotic process.In the CRC stage,core ingredients like p-coumaric acid may bind with proteins such as PRKCB.This binding may impact the signaling pathways that negatively affect EGFR tyrosine kinase inhibitor resistance,and PI3K-AKT signaling pathways.Additionally,it may regulate bio-logical processes,including negative regulation of apoptotic process,signal transduction,and protein phosphorylation.In vitro experi-ment results indicated that SBJDD inhibited the proliferation of HT29 cells and suppressed the expression of EGFR and PKC proteins.CONCLUSION The UPLC-Q-TOF-MS method is established to effectively separate the chemical constituents in SBJDD,which are mainly composed of alkaloids,organic acids and flavonoids components.Components from SBJDD dock with different targets during the carcinogenesis process of CRA and regulate cancer-related signaling pathways to exert therapeutic effects.

Objective:To study the effects of broad-spectrum antibiotics and induced antibiotic-resistant bacteria on the efficacy of 5-fluorouracil (5-FU) chemotherapy for mice with colon cancer and to investigate the underlying mechanisms associated with anti-tumor immune responses.Methods:BALB/c mice were subcutaneously injected with CT26 colon cancer cells and randomized into four groups: tumor-bearing control group, antibiotic group treated with ampicillin, streptomycin and colistin, 5-FU group and anitibiotic+ 5-FU group. Tumor volumes and body weights were measured and recorded. Seven days after the last 5-FU treatment, the percentages of splenic immune cell subpopulations and proliferated CD8 + T cells after co-culturing with CT26 were analyzed by flow cytometry. Gut microbiota composition was detected by 16S rRNA sequencing and the bacteria in mesenteric lymph nodes (mLN) were isolated and cultured. Bone marrow-derive macrophages were stimulated with identified bacteria and the expression of M1 and M2 polarization markers were assessed by quantitative PCR. The proliferation of CD8 + T cells co-cultured with bacteria-treated macrophages was analyzed by flow cytometry. In addition, tumor-bearing mice were treated with 5-FU and oral gavage of bacteria isolated from antibiotic+ 5-FU group or PBS. Tumor volumes, gut microbiota composition and the percentages of proliferated CD8 + T cells co-cultured with CT26 were assessed. Results:Tumor volumes were larger and body weights were lower in the antibiotic+ 5-FU group than in the 5-FU group. The percentages of CD4 + T cells, CD8 + T cells and neutrophils did not varied significantly after using antibiotics, however, the percentage of monocytes was increased in the antibiotic group. The percentage of proliferated tumor-specific CD8 + T cells in the antibiotic+ 5-FU group was decreased compared with that in the 5-FU group. Compared with the control group and 5-FU group, antibiotic usage was associated with the changes in gut microbiota composition with decreased α diversity indexes. Escherichia coli, Klebsiella pneumonia, and Proteus mirabilis were isolated from mLNs of the antibiotic group, 5-FU group and antibiotic+ 5-FU group, respectively. Bone marrow-derived macrophages stimulated with Proteus mirabilis expressed arginase at a high level, which was a M2 polarization marker of macrophage, and associated with the decreased percentage of proliferated CD8 + T cells after co-culturing. Bacteria of the genus Proteus were enriched in the gut microbiota of 5-FU-treated tumor-bearing mice with the oral gavage of Proteus mirabilis. Although no significant inhibitory effect on tumor growth was observed, the oral gavage of Proteus mirabilis was associated with the decreased percentage of proliferated tumor-specific CD8 + T cells in vitro. Conclusions:Broad-spectrum antibiotics inhibited the efficacy of chemotherapy and the proliferation of tumor-specific CD8 + T cells, in which antibiotic-resistant bacteria might be involved.

Objective: To understand literacy development of school-aged children of grade 2-5 and its influencing factors in Guangzhou,and to provide a reference for the reform of the teaching of Chinese subject. Methods: By using cluster sampling method, 1 661 school-age children from grade 2 to grade 5 from 5 primary schools in Guangzhou were selected. The self-designed questionnaire was used to obtain demographic data of the participants. The Primary School Literacy Assessment Scale and the Pupil Rating Scale Revised Screening for Learning Disabilities was used to evaluate the literacy and the cognitive characteristics of participants. Results: The average literacy of children of grade 2 to grade 5 in Guangzhou was as follows: grade 2 was (1 159±295), grade 3 was (1 919±394), grade 4 was (2 599±365), grade 5 was (2 947±303), higher than the norm(P<0.01). The average literacy of grade 2 students was lower than the national curriculum requirements while students of grade 3 to grade 5 met the requirements. Univariate analysis found differences in literacy among school-age children based on gender, reading experience before age 6, and parental education background (P<0.01). Multiple linear regression analysis revealed that grade (β=607.04), preschool reading experience (β=109.89), father’s education (β=27.14), language factor (β=27.21), social behavior (β=16.03) was positively correlated with literacy in boys (P<0.05). Grade (β=603.53), auditory comprehension and memory (β=29.39), language factor (β=16.74) was positively correlated with the literacy of girls (P<0.05), while time and orientation judgments were negatively correlated with the literacy of both boys (β=-18.95) and girls (β=-21.93) (P<0.05). Conclusion The literacy level of school-age children in grade 2 to 5 in Guangzhou has reached the national literacy requirements with students in grade 2 being relatively lower. Literacy is related to grade, preschool reading experience, father’s education, and child’s cognitive characteristics. Factors affecting literacy in boys and girls are different. Literacy education should vary according to gender.

Objective: This study aims to explore the influence of birth order and age difference on the emotional and behavioral problems among children from two-child family, so as to provide advice on parenting. Methods: A total of 482 students in grades 2 to 5 from the 5 primary schools in Guangzhou were selected, all of whom came from two-child families (excluding twin children). Emotional and behavioral problems were investigated by using the Conner’s Parental Symptom Questionnaire (PSQ). Results: Among children from two-child families, higher prevalence of behavioral problems, learning problems, impulsive hyperactivity and hyperactivity index in older compared with younger children (β=-0.09，-0.16，-0.09，-0.10,P<0.05). The scores of behavioral problems and hyperactivity index were significantly higher among those of children who were 6-9 years older than young siblings, compared to those who were 0-3 years older than younger siblings(β=0.20,0.21,P<0.05). No similar pattern was found among the younger siblings(P>0.05). Conclusion Among school-age children from two-child families, emotional and behavioral problems of the elder ones were more serious than the younger ones’. Age difference between siblings shows impact on the emotional and behavioral development among elder children, however no significant impact is noticed among the younger ones.

Objective:To study the compatibility and stability of coenzyme A for injection, adenosine disodium triphosphate and inosine injection. Methods:By simulating the clinical medication, the three drugs and 5% glucose injection were mixed together. The contents and relative substances of coenzyme A, adenosine disodium triphosphate and inosine were measured by HPLC. The changes in appearance, pH and insoluble particles were observed or tested at ambient temperature. Results:The mixed solution showed no signifi-cant changes in appearance, pH, number of insoluble particles, contents and relative substances of coenzyme A, adenosine disodium triphosphate and inosine in 4 h, while the mixed solution became turbid and the pH, number of insoluble particles and contents of the three drugs showed significant changes after 24-h storage. Conclusion:The mixed solution of coenzyme A for injection, adenosine dis-odium triphosphate and inosine injection in 5% glucose injection should be used up in 4 h at ambient temperature.

Objective To improve the quality standard for Compound Belladonna Mixture.Methods TLC was used for the qualitative identification of morphine.HPLC was used for the content of morphine in the Compound Belladonna Mixture.Results Morphine could be identified by TLC.A good linear correlation of morphine was observed within the range of 0.525~10.5 μg/ml (r=0.999 9).The average recovery was 99.44% with RSD of 0.23% (n=9).Conclusion This method is simple,accurate and quick, which could be used for determination and quality control of Compound Belladonna Mixture with good selectivity and repeatability.

Objective: To determine total phenylethanoid glycoside and acteoside in Plantago Herba to provide reference for evaluating the quality of medicinal materials.Methods: With acteoside as the control sample, a UV visible spectrophotometric method was used to determine total phenylethanoid glycosides in Plantago Herba.An HPLC method was applied to determine acteoside in Plantago Herba , and the conditions were as follows: an ODS2 C 18 (150 mm× 4.6 mm ,5 μm) chromatographic column was used with acetonitrile-0.1% formic acid (13∶87) as the mobile phase at a flow rate of 1.0 ml·min-1 , the detection wavelength was 332nm, the column temperature was 30℃, and the sample volume was 10 μl.Results: The reference solution and the sample solution had the maximum absorption at 332 nm, and the linear relationship was good within the range of 0.003 1-0.155 0 mg·ml-1 (r=0.999 5).The content of total benzene alcohol glycosides in 3 batches of samples was 2.73% , 2.61% and 2.84% , respectively;acteoside over the range of 0.000 6-0.155 0 mg·ml-1 (r=0.999 1) showed a good linear relationship with peak area,the sample recovery was 98.5% and the RSD was 1.6% (n =6), and the acteoside content in 3 batches of samples respectively was 0.54% , 0.51% and 0.56%.Conclusion: The method is simple, accurate and reproducible, and can be used for the determination of total phenylethanoid glycosides and acteoside in Plantago Herba.

Objective To establish a method for determination of phenylethanoid glycoside and acteoside in Plantago Herba. Methods UV-visible spectrophotometric method was used for the determination of the content of phenylethanoid glycosides compounds in Plantago Herba. HPLC method was used for the determination of acteoside in Plantago Herba. Chromatographic column with C18 ODS2 (4.6 mm × 150 mm, 5 μm) was used. Acetonitrile-0.1%formic acid (13:87) was as mobile phase; the flow rate was 1 mL/min; the detection wavelength was 332 nm; the column temperature was 30 ℃; the sample volume was 10 μL. Results The contents of phenylethanoid glycoside in Plantago Herba from different producing areas were among 1.03%–3.47%. Acteoside with peak area over the 0.0062–1.55 mg range showed a good linear relationship; the sample recovery rate was 98.9%, and the RSD was 1.6%. The contents of acteoside in Plantago Herba from different producing areas was among 0.18%–0.56%. Conclusion The method is simple, stable and reproducible, which can be used for the determination of phenylethanoid glycoside and acteoside in Plantago Herba from different producing areas and provide experimental basis for quality control of Plantago Herba.