Objective To explore the impact of meteorological factors on the incidence of scarlet fever in Xicheng District of Beijing, and to provide a scientific basis for formulating targeted prevention and control measures. Methods Daily scarlet fever incidence data and corresponding meteorological data from 2010 to 2019 in Xicheng District of Beijing were collected. Using year, month, and day of the week as time-stratified variables, a conditional logistic regression model with a time-stratified case-crossover design was employed to analyze the impact of different meteorological factors on the number of scarlet fever cases in Xicheng District, while controlling for long-term trends, seasonality and other confounding factors. Results From 2010 to 2019, a total of 3,195 cases of scarlet fever were reported in Xicheng District, with an average annual incidence rate of 24.17/100 000. The overall trend showed fluctuating decline, during which three incidence peaks occurred, with the highest incidence rate observed in 2011. No severe or fatal cases were reported. The incidence of scarlet fever exhibited a distinct seasonal bimodal distribution, primarily concentrated between April to June and November to January of the following year. The conditional logistic regression results showed that the average relative humidity and average temperature were positively correlated with scarlet fever cases (β=0.0203, β=0.0613, P＜0.001), while the average vapor pressure was negatively correlated with scarlet fever cases (β=-0.1468, P＜0.001). Increases average relative humidity and average temperature were risk factors for scarlet fever incidence (OR=1.0205，95%CI=1.0150 -1.0261；OR=1.0632，95%CI=1.0379 -1.0891). For every 1.00% increase in average relative humidity, the number of scarlet fever cases increased by 2.05% (1.50% –2.61%). Similarly, for every 1^。C rise in average temperature, the number of cases increased by 6.32% (3.79% – 8.91%). In contrast, an increase in average vapor pressure had a protective effect against scarlet fever (OR=0.8635,95%CI=0.8392-0.8885). For every 1 hPa increase in average vapor pressure, the number of scarlet fever cases decreased by 13.65% (11.15%–16.08%). Conclusion The average relative humidity, average temperature and average vapor pressure are the primary meteorological factors influencing the incidence of scarlet fever in Xicheng District of Beijing, and can be utilized as indicators for the prevention, control, surveillance and early warning of scarlet fever.

OBJECTIVE To prepare an intelligent responsive liposome-hydrogel nanopreparation co-loaded with gambogic acid （GA）， and characterize its antitumor activity in vitro . METHODS GA-ICG-Lip-gel was prepared by ethanol injection and cold dissolution， incorporating GA and the photosensitizer indocyanine green （ICG）. The appearance and microscopic morphology of GA-ICG-Lip-gel were observed， its encapsulation efficiency and drug loading capacity were measured， and its photothermal conversion performance， photothermal stability， and infrared imaging properties were investigated， along with the determination of its in vitro release profile. Human breast cancer MCF-7 cells were used as objects to investigate the effects of GA-ICG-Lip-gel （or with near-infrared light irradiation） on cell viability， migration ability， and the cellular uptake capacity of GA-ICG-Lip-gel. RESULTS GA-ICG-Lip-gel existed in a solution state at room temperature and transformed into a gel state at 37 ℃. Its microstructure was dense with small pores， and its encapsulation efficiency and drug loading were （96.07±0.86） % and （6.28±1.16） %， respectively. After exposure to near-infrared light， the temperature of GA-ICG-Lip-gel rose above 42 ℃， with no significant attenuation observed in the heating curve. The heating efficiency was dependent on both the irradiation time and drug concentration. Compared to media without gelatinase， the cumulative release rate of GA-ICG-Lip-gel increased in media containing gelatinase. In vitro studies showed that GA-ICG-Lip-gel could be efficiently taken up by MCF-7 cells； GA-ICG-Lip-gel significantly inhibited the viability and migration ability of MCF-7 cells （ P ＜0.05）， and this inhibitory effect was further enhanced under near-infrared light irradiation. CONCLUSIONS This study successfully prepares GA-ICG-Lip-gel， which exhibits favorable photothermal conversion properties and temperature/enzyme dual-responsive drug release characteristics， and demonstrates significant inhibitory effects on the proliferation and migration of breast cancer cells.

Objective To compare the epidemic characteristics of seasonal influenza in Xicheng District, Beijing, between 2018-2019 and 2023-2024. Methods The present study was a cross-sectional study. The influenza cases and etiological surveillance data of Xicheng District, Beijing in 2018-2019 and 2023-2024, respectively, were analyzed to study the differences in the incidence rate of influenza cases in different ages, regions, occupations, and etiological detection results during the four years. Results There were significant differences in the incidence rates of influenza (χ²=37 038.65，P＜0.05) and the interval between visits (Z=468.692, P < 0.05) in 2018, 2019, 2023 and 2024. There were statistically significant differences in the incidence rates of influenza among different age groups, streets, and occupations during the four years (Z=75.646, 209.276, 72.132, 361.176, 43.570, all P < 0.05). Compared with 2018-2019, the growth rate of influenza in Xicheng District, Beijing in 2023-2024 was the highest in the 15-24 year-old group, Tianqiao Street, and housework and unemployed people. The difference in the interval between influenza visits among people of different age groups during these 4 years was statistically significant (P < 0.05). The growth rate of the interval between influenza visits in Xicheng District, Beijing in 2023-2024 was the highest in the 15-24 year-old group, while it showed a decrease in the 0-4 year-old group. The etiology in 2018-2019 was mainly H1N1 and H3N2 subtypes, and in 2023-2024 it was mainly H3N2 subtype and influenza B, and the peak values of H1N1, H3N2 subtype and influenza B in 2023-2024 were all higher than those in 2018-2019. Conclusion During the epidemic period, non-medical interventions have changed the transmission mode, seasonal peak and subtype distribution of influenza virus. As the epidemic has eased, the pattern of influenza has gradually rebounded.

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

BACKGROUND:The sports medicine community has widely called for the use of machine learning technology to efficiently process the huge and complicated sports data resources,and construct intelligent sports injury prediction models,enabling accurate early warning of sports injuries.It is of great significance to comprehensively summarize and review such research results so as to grasp the direction of early warning model improvement and to guide the construction of sports injury prediction models in China. OBJECTIVE:To systematically review and analyze relevant research on sports injury prediction models based on machine learning technology,thereby providing references for the development of sports injury prediction models in China. METHODS:Literature search was conducted on CNKI,Web of Science and EBSCO databases,which mainly searched for literature related to machine learning techniques and sports injuries.Finally,61 articles related to sports injury prediction models were included for analysis. RESULTS AND CONCLUSION:(1)In terms of external risk feature indicators,there is a lack of competition scenario indicators,and the inclusion of related feature indicators needs to be further improved to further enrich the dimensions of the dataset for model training.In addition,the inclusion feature weighting methods of the sports injury prediction model are mainly based on filtering methods and the use of embedding and wrapping weighting methods needs to be strengthened in order to enhance the analysis of the interaction effects of multiple risk factors.(2)In terms of model body training,supervised learning algorithms become the mainstream choice.Such algorithms have higher requirements for the completeness of sample labeling information,and the application scenarios are easily limited.Therefore,the application of unsupervised and semi-supervised algorithms can be increased in the later stage.(3)In terms of model performance evaluation and optimization,the current studies mainly adopt two verification methods:HoldOut crossover and k-crossover.The range of AUC values is(0.76±0.12),the range of sensitivity is(75.92±11.03)%,the range of specificity is(0.03±4.54)%,the range of F1 score is(80.60±10.63)%,the range of accuracy is(69.96±13.10)%,and the range of precision is(70±14.71)%.Data augmentation and feature optimization are the most common model optimization operations.The accuracy and precision of the current sports injury prediction model are about 70%,and the early warning effect is good.However,the model optimization operation is relatively single,and data augmentation methods are often used to improve model performance.Further adjustments to the model algorithm and hyperparameters are needed to further improve model performance.(4)In terms of model feature extraction,most of the internal risk profile indicators included are mainly based on anthropometrics,training load,years of training,and injury history,but there is a lack of sports recovery and physical function indicators.

Objective To explore the mediating role of activities of daily living (ADL) in pain and depressive symptoms in the elderly in China. Methods Utilizing the data from 2020 China Health and Retirement Longitudinal Study, 4403 Chinese elderly individuals aged ≥ 60 years old were selected as the research subjects. Depression Scale (CES-D 10) of the Center for Epidemiological Survey and ADL scale were used in the study. The PROCESS4.1 macro was used to test the mediating effect of daily living activities between pain and depressive symptoms, and the Bootstrap method was applied for verification of the mediating variables. Results A total of 2368 cases of depressive symptoms were detected in the elderly in China, with a detection rate of 53.78%. Pain was positively correlated with depressive symptoms (r=0.27, P<0.01), and activities of daily living were negatively correlated with pain and depressive symptoms (r=-0.27, -0.337, P<0.01). The results showed that the total effect value of pain on depressive symptoms was 0.33, the direct effect value was 0.24, and the mediating effect value of daily living activities was 0.09, accounting for 27.27%. Conclusion Pain and activities of daily living are important factors influencing depressive symptoms in the elderly, and activities of daily living play a partial mediating role in the relationship between pain and depressive symptoms in the elderly.

Objective To understand the distribution of M protein gene (emm) of group A streptococcus (GAS) infections among children in Xicheng District of Beijing. Methods Throat swab samples from scarlet fever and pharyngeal infection cases were collected in sentinel hospitals of Xicheng District, Beijing from 2011 to 2024. GAS strains were isolated and identified, and emm gene was amplified and sequenced by PCR to determine the genotype. The differences in emm genotype between different groups were compared. Results A total of 3 130 throat swab samples were collected, and 400 GAS strains were isolated, with a positive rate of 12.78%. The highest positive rate was 19.93% in 2011. The positive rate of scarlet fever (45.71%) was higher than that of pharyngeal infection (6.14%) (P<0.001). There were 391 emm gene positive strains, and the differences in the positive rate of emm gene among different cases were statistically significant (P<0.001). A total of 7 genotypes and 27 gene subtypes were detected. Among different groups, the emm genotypes were mainly emm12 and emm1. The emm gene subtypes were mainly emm12.00 and emm1.00. Except for some years, the genotypes and their subtypes were dominated by emm12 and emm12.00, and the distribution differences of the two major genotypes and their subtypes were statistically significant from 2011 to 2019 (P<0.001). There were differences in genotypes and subtypes among different age groups (P=0.002). Conclusion The dominant types of emm genes in group A streptococcus infections among children were emm12 and emm1 in Xicheng District of Beijing from 2011 to 2024, and the dominant gene subtypes were emm12.00 and emm1.00. It is necessary to comprehensively strengthen the monitoring of the epidemic situation and genotype, timely grasp the distribution and variation of emm gene.

Cardiac fibrosis is characterized by an elevated amount of extracellular matrix (ECM) within the heart. However, the persistence of cardiac fibrosis ultimately diminishes contractility and precipitates cardiac dysfunction. Circular RNAs (circRNAs) are emerging as important regulators of cardiac fibrosis. Here, we elucidate the functional role of a specific circular RNA CELF1 in cardiac fibrosis and delineate a novel feedback loop mechanism. Functionally, circ-CELF1 was involved in enhancing fibrosis-related markers' expression and promoting the proliferation of cardiac fibroblasts (CFs), thereby exacerbating cardiac fibrosis. Mechanistically, circ-CELF1 reduced the ubiquitination-degradation rate of BRPF3, leading to an elevation of BRPF3 protein levels. Additionally, BRPF3 acted as a modular scaffold for the recruitment of histone acetyltransferase KAT7 to facilitate the induction of H3K14 acetylation within the promoters of the Celf1 gene. Thus, the transcription of Celf1 was dramatically activated, thereby inhibiting the subsequent response of their downstream target gene Smad7 expression to promote cardiac fibrosis. Moreover, Celf1 further promoted Celf1 pre-mRNA transcription and back-splicing, thereby establishing a feedback loop for circ-CELF1 production. Consequently, a novel feedback loop involving CELF1/circ-CELF1/BRPF3/KAT7 was established, suggesting that circ-CELF1 may serve as a potential novel therapeutic target for cardiac fibrosis.

This study established the HPLC fingerprints and a multi-component content determination method for Bidens pilosa var. radiata and B. pilosa and conducted comprehensive evaluation by integrating fingerprint similarity comparison, cluster analysis(CA), and principal component analysis(PCA), aiming to provide a reference for the establishment of quality standards for Bidentis Herba. HPLC was launched on an Agilent Poroshell 120 EC-C_(18) chromatographic column(4.6 mm×250 mm, 4 μm) by gradient elution with a mobile phase of 0.1% aqueous phosphoric acid-acetonitrile at a flow rate of 0.7 mL·min~(-1), detection wavelength of 270 nm, column temperature of 25 ℃, and an injection volume of 5 μL. The fingerprint similarity of 20 batches of Bidentis Herba ranged from 0.775 to 0.979. A total of 20 common peaks were identified, and seven components were confirmed through comparison with reference substances: neochlorogenic acid, chlorogenic acid, isochlorogenic acid A, isochlorogenic acid B, isochlorogenic acid C, rutin, and hyperoside. These seven components exhibited good linearity within the ranges of 3.4-67.4, 33.0-660.3, 26.6-531.2, 3.5-70.5, 6.2-124.9, 2.4-48.3, and 4.6-91.5 μg·mL~(-1), respectively, with correlation coefficients(r) greater than 0.999. The average recovery rates ranged from 96.47% to 104.6%. CA and PCA classified the 20 batches of Bidentis Herba into two categories. PCA yielded two principal components, with a cumulative variance contribution rate of 80.557%. The established HPLC fingerprints and multi-component content determination method are simple and accurate, providing a scientific basis for the quality control and quality standard formulation of Bidentis Herba.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Chemometrics/methods* ; Bidens/chemistry* ; Principal Component Analysis

This study established the HPLC fingerprints, characteristic chromatograms, and a multi-component content determination method for Bidens bipinnata and B. biternata. The chemical pattern recognition analysis was then employed to clarify the characteristic indexes of quality differences between the two original plants of Bidentis Herba, providing a reference for establishing the quality standards of Bidentis Herba. HPLC was launched on an Agilent Poroshell 120 EC-C_(18) chromatographic column(4.6 mm×250 mm, 4 μm) by gradient elution with a mobile phase of 0.1% aqueous phosphoric acid-acetonitrile at a flow rate of 0.7 mL·min~(-1), detection wavelength of 270 nm, column temperature of 25 ℃, and an injection volume of 5 μL. The similarity between the fingerprints of 18 batches of Bidentis Herba samples and the common pattern(R) ranged from 0.572 to 0.933. A total of 23 chromatographic peaks were calibrated. Through comparison with the reference substances, six components(neochlorogenic acid, chlorogenic acid, isochlorogenic acid A, isochlorogenic acid B, rutin, and hyperoside) were identified and subjected to quantitative analysis. The characteristic fingerprints of B. bipinnata and B. biternata were calibrated with 20 and 17 characteristic peaks, respectively. Among them, peaks 8, 9, 22, and 23 were the characteristic peaks of B. bipinnata, and peak 7 was the characteristic peak of B. biternata, which can be used to distinguish the two original plants of Bidentis Herba. The relative standard deviation of the content of the above-mentioned six components ranged from 36% to 123%. The cluster analysis, principal component analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) classified the 18 batches of Bidentis Herba samples into two categories. Additionally, through the analysis of variable importance in projection(VIP) under OPLS-DA, three characteristic indexes, rutin, isochlorogenic acid A, and isochlorogenic acid B, were identified. The analytical method established in this study can comprehensively evaluate the consistency of Bidentis Herba samples derived from different original plants, specifically identify the differential components between them, and effectively distinguish the two original plants of Bidentis Herba, providing a basis for the differentiation between different original plants and the quality control of Bidentis Herba.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Bidens/chemistry*