A high-performance liquid chromatography method using pre-column derivatization with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate was developed to determine the content of 15 amino acids in the medicinal snakes Bungarus Parvus, Agkistrodon, and Zaocys. The results showed that the total amino acid(TAA) content ranged from 277.13 to 515.05 mg·g~(-1), with the top four amino acids in all three species being glutamic acid(Glu), glycine(Gly), aspartic acid(Asp), and lysine(Lys). The essential amino acid(EAA) content ranged from 74.56 to 203.94 mg·g~(-1), with Agkistrodon exhibiting the highest content. The non-essential amino acid(NEAA), semi-essential amino acid(semi-EAA), and medicinal amino acid(MAA) content ranged from 189.06 to 318.23, 12.89 to 33.53, and 179.83 to 342.33 mg·g~(-1), respectively, with Zaocys having the highest content in these categories. Amino acid nutritional value was evaluated using the amino acid ratio(RAA), amino acid ratio coefficient(RCAA), and amino acid ratio coefficient score(SRCAA), and the results indicated that all three medicinal snakes possessed good nutritional value. The amino acid composition was similar across the species, though significant differences in content were observed. Based on these differences, an orthogonal partial least squares-discriminant analysis(OPLS-DA) model was established, which could clearly distinguish between the three medicinal snake species. The key differences in amino acid content included Gly, tyrosine(Tyr), Glu, and serine(Ser), which may be related to the observed clinical application differences among the species. Further research into the mechanisms of these differential amino acids is expected to provide more insights into the clinical application disparities of these three medicinal snake species.
Amino Acids/chemistry* ; Animals ; Nutritive Value ; Chromatography, High Pressure Liquid ; Snakes/classification* ; Bungarus

OBJECTIVE: To analyze the effect of COVID-19 infection on the mobilization and collection of autologous peripheral blood stem cells in patients with multiple myeloma. METHODS: The general baseline data, treatment factors before mobilization collection, collection status, and treatment overview after collection of autologous peripheral blood stem cells at Beijing Chaoyang Hospital affiliated with Capital Medical University from January 1, 2020 to July 15, 2023 were analyzed. RESULTS: 269 patients underwent mobilization and collection of autologous peripheral blood stem cells. Among them, 32 cases with COVID-19 infection history (COVID-19 group) and 237 cases without COVID-19 infection history (non-COVID-19 group). In the COVID-19 group, 17 cases were treated with chemotherapy (etoposide)+G-CSF, and 15 cases were treated with plerixafor +G-CSF. In the non-COVID-19 group, 214 cases were treated with chemotherapy +G-CSF, 17 cases were treated with plerixafor +G-CSF, and 6 cases were treated with chemotherapy + plerixafor +G-CSF. The number of CD34⁺ cells, collection success rate, and excellence rate in the COVID-19 group and the non-COVID-19 group were ［5.52 (0.94-26.87) vs 4.80 (0.53-37.20)］×10⁶/kg (P =0.610), (93.8% vs 85.2%) (P =0.275), (62.5% vs 49.4%) (P =0.190), respectively. Among 113 patients mobilized with etoposide +G-CSF, the number of CD34⁺ cells, success rate, and excellence rate collected from COVID-19 infection (17 cases) and non-COVID-19 infection (96 cases) were ［7.54 (2.66-26.87) vs 7.78 (2.26-37.20)］×10⁶/kg (P =0.847), (100.0% vs 100.0%) (no P value), (82.4% vs 86.5%) (P =0.655), respectively. Among 32 patients mobilized by plerixafor +G-CSF, the number of CD34⁺ cells, success rate and excellence rate of COVID-19 infection (15 cases) and non-COVID-19 infection (17 cases) were ［3.82 (0.94-7.27) vs 4.11 (0.53-9.05)］×10⁶/kg (P =0.821), (86.7% vs 88.2%) (P =0.893), (40.0% vs 35.3%) (P =0.784), respectively. In 32 patients with COVID-19 infection, the number of CD34⁺ cells collected by etoposide +G-CSF (17 cases) and plerixafor +G-CSF (15 cases), as well as the success rate and excellence rate were ［7.54 (2.66-26.87) vs 3.82(0.94-7.27)］×10⁶/kg (P =0.004), (100.0% vs 86.7%) (P =0.120), (82.4% vs 40.0%) (P =0.014), respectively. By 2023.7.31, 232 patients (86.2%, 232/269) had received transplantation, including 24 patients in the COVID-19 group and 208 patients in the non-COVID-19 group. The median number of CD34⁺ cells infused in the two groups was ［3.67 (2.50-13.44) vs 3.11(1.12-19.89)］×10⁶/kg (P =0.058), the median days of neutrophil engraftment ［11(9-13) vs 11(9-17)］ (P =0.674), the median days of platelet engraftment ［11(0-23), 12(0-43)］ (P =0.279), respectively. CONCLUSION The history of COVID-19 infection did not affect the PBSC mobilization, collection and transplantation of patients with myeloma. In patients with COVID-19 infection, the results of chemotherapy mobilization with etoposide seems to be better than that of plerixafor mobilization, but further research is needed to clarify.
Humans ; COVID-19/complications* ; Multiple Myeloma/complications* ; Hematopoietic Stem Cell Mobilization ; Transplantation, Autologous ; Granulocyte Colony-Stimulating Factor/therapeutic use* ; Peripheral Blood Stem Cell Transplantation ; SARS-CoV-2 ; Middle Aged ; Peripheral Blood Stem Cells ; Male ; Female ; Cyclams ; Benzylamines

[This corrects the article DOI: 10.1016/j.apsb.2018.08.009.].

OBJECTIVE: To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis (TB) in the Guangdong Province between 2010 and 2019. METHOD: Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering. Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive (ST-CAR) model. RESULTS: Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000 in 2019. Spatial hotspots were found in northeastern Guangdong, particularly in Heyuan, Shanwei, and Shantou, while Shenzhen, Dongguan, and Foshan had the lowest rates in the Pearl River Delta. The ST-CAR model showed that the TB risk was lower with higher per capita Gross Domestic Product (GDP) [Relative Risk ( RR), 0.91; 95% Confidence Interval ( CI): 0.86-0.98], more the ratio of licensed physicians and physician ( RR, 0.94; 95% CI: 0.90-0.98), and higher per capita public expenditure ( RR, 0.94; 95% CI: 0.90-0.97), with a marginal effect of population density ( RR, 0.86; 95% CI: 0.86-1.00). CONCLUSION The incidence of TB in Guangdong varies spatially and temporally. Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection. Strategies focusing on equitable health resource distribution and economic development are the key to TB control.
Humans ; China/epidemiology* ; Incidence ; Bayes Theorem ; Spatio-Temporal Analysis ; Tuberculosis/epidemiology* ; Socioeconomic Factors

OBJECTIVE: Patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection frequently develop central nervous system damage, yet the mechanisms driving this pathology remain unclear. This study investigated the primary pathways and key factors underlying brain tissue damage induced by the SARS-CoV-2 beta variant (lineage B.1.351). METHODS: K18-hACE2 and C57BL/6 mice were intranasally infected with the SARS-CoV-2 beta variant. Viral replication, pathological phenotypes, and brain transcriptomes were analyzed. Gene Ontology (GO) analysis was performed to identify altered pathways. Expression changes of host genes were verified using reverse transcription-quantitative polymerase chain reaction and Western blot. RESULTS: Pathological alterations were observed in the lungs of both mouse strains. However, only K18-hACE2 mice exhibited elevated viral RNA loads and infectious titers in the brain at 3 days post-infection, accompanied by neuropathological injury and weight loss. GO analysis of infected K18-hACE2 brain tissue revealed significant dysregulation of genes associated with innate immunity and antiviral defense responses, including type I interferons, pro-inflammatory cytokines, Toll-like receptor signaling components, and interferon-stimulated genes. Neuroinflammation was evident, alongside activation of apoptotic and pyroptotic pathways. Furthermore, altered neural cell marker expression suggested viral-induced neuroglial activation, resulting in caspase 4 and lipocalin 2 release and disruption of neuronal molecular networks. CONCLUSION These findings elucidate mechanisms of neuropathogenicity associated with the SARS-CoV-2 beta variant and highlight therapeutic targets to mitigate COVID-19-related neurological dysfunction.
Animals ; COVID-19/genetics* ; Mice ; Brain/metabolism* ; Apoptosis ; Mice, Inbred C57BL ; SARS-CoV-2/physiology* ; Pyroptosis ; Gene Expression Profiling ; Transcriptome ; Male ; Female

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.

Objective:To develop habitat radiomics models to predict early treatment responses to the hepatic arterial infusion chemotherapy (HAIC) combined with targeted therapy or immunotherapy in advanced hepatocellular carcinoma (HCC) patients, and to guide clinical diagnosis and treatment.Methods:From October 2021 to Decemeber 2023, at Army Characteristic Medical Center of PLA (Chongqing Daping Hospital) and the First Affiliated Hospital of Chongqing Medical University, 94 patients with advanced HCC who received HAIC combined with targeted therapy or immunotherapy were retrospectively enrolled. According to the treatment results, the patients were divided into response group and non-response group. Univariate and multivariate logistic regression were performed to analyze the clinical data of the patients. Based on contrast-enhanced CT images, tumor habitats were delineated and habitat features were extracted with k-means clustering, and the imaging features of arterial and venous phases were also extracted. The least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. Feature selection was performed using LASSO to reduce dimensions, and then the selected features were further refined through stepwise logistic regression analysis.Binary logistic regression models were conducted to develop the habitat radiomics model, arterial phase radiomics model (APRM), venous phase radiomics model (VPRM), clinical data model, as well as the combination of radiomics model and clinical data model to predict early treatment (after 2 treatment cycles) response. Receiver operating characteristic curves (ROC) were plotted, and model performance was evaluated by the area under the curve (AUC), calibration curves, and decision curve. The models were validated through Bootstrap methods (1 000 times). DeLong test was used to compare AUC values.Results:The results of cluster analysis identified 3 characteristic habitats in HCC imaging: low-, medium-, and high-enhancement tumor habitats. The proportion of high-enhancement habitats was higher than that in the non-response group. A predictive model was established based on the proportions of these 3 habitats. Based on the proportion of low-, medium-, and high-enhancement habitats within the tumor, a habitat radiomics model was constructed. After LASSO selection and logistic regression analysis, 3 arterial phase and 3 venous phase radiomic features were selected to build the APRM and VPRM, respectively. Logistic regression analysis identified the following factors for the clinical data model: comorbidities ( OR=0.275, P=0.031), maximum tumor diameter ( OR=1.149, P=0.019), red blood cell count ( OR=0.463, P=0.022), alpha fetoprotein >400 μg/L ( OR=3.452, P=0.017), and tyrosine kinase inhibitor therapy ( OR=3.072, P=0.048). Among the single predictive model′s comparison, the AUC of habitat radiomics model was 0.860 (95% confidence interval(95% CI): 0.789 to 0.932), while those of the APRM、VPRM and clinical data model were 0.850 (95% CI: 0.773 to 0.926), 0.855 (95% CI: 0.782 to 0.928), and 0.774 (95% CI: 0.681 to 0.867), respectively, and there were no statistically significant among these models (all P>0.05). Among the combination models, the AUC of the habitat rediomic-clinical data combination model was 0.881 (95% CI: 0.814 to 0.947); the AUC of arterial phase rediomic-clinical data combination model was 0.897 (95% CI: 0.833 to 0.961); and the AUC of venous phase rediomic-clinical data combination model was 0.888 (95% CI: 0.826 to 0.951), but there were no statistically significant among the 3 models (all P>0.05). The calibration curve showed that the habitat rediomic-clinical data combination model had the most accurate predictive probability. Internal validation showed that the AUC of habitat rediomic-clinical data combination model was 0.848 (95% CI: 0.772 to 0.922), and the predictive performance was better than that of the clinical-data model (0.733 (95% CI: 0.670 to 0.863)). Conclusion:The habitat radiomics model based on enhanced CT can effectively predict early treatment responses to the HAIC combined with targeted therapy or immunotherapy in advanced HCC patients, which provides theoretical basis for individualized treatment in advanced HCC.

The epidemiological and spatiotemporal clustering characteristics of dengue fever in Fujian Province were ana-lyzed,to provide a scientific basis for dengue fever prevention and control.Descriptive epidemiology,spatial autocorrelation a-nalysis,and spatiotemporal scanning were used to analyze dengue fever cases in Fujian Province from 2011 to 2023.In this peri-od,a total of 3 586 cases of dengue fever were reported in Fujian Province,including 2 360 local cases,1 134 imported cases from abroad,and 92 imported cases from China.Cases were reported in ten prefectures and cities of the province,and 81 out of 88 counties reported cases.Imported cases were reported throughout the year in Fujian Province,but the occurrence of local ca-ses showed clear seasonality.Local cases and domestic imports were concentrated in August to October,whereas overseas im-ports occurred primarily from June to October.The imported cases were mainly from Southeast Asian countries,but a trend of spreading from Southeast Asian countries to South Asia,Africa,the Americas,and other regions,was observed.Spatio-tem-poral clustering of dengue fever was found in Fujian Province(Moran's I value 0.14-0.66,P＜0.05),and the high-high ag-gregation areas were distributed primarily in Fuzhou,Quanzhou,and Putian.Spatio-temporal scanning detected three aggrega-tion areas:one main and two secondary.The aggregation time was from the end of July to October,and the distribution was primarily in Fuzhou,Quanzhou,Putian,Zhangzhou,and Xiamen.The distribution of dengue fever in Fujian Province showed clear spatial and temporal clustering from the end of July to October,and the distribution was primarily in Fuzhou,Quanzhou,Putian,Zhangzhou,and Xiamen.For high concentration areas,national health campaigns,mosquito prevention and control,epidemic surveillance,medical personnel training,and other relevant measures could be carried out in advance before local cases appear every year.Reduce local transmission of dengue fever due to importation.

The epidemiological and spatiotemporal clustering characteristics of dengue fever in Fujian Province were ana-lyzed,to provide a scientific basis for dengue fever prevention and control.Descriptive epidemiology,spatial autocorrelation a-nalysis,and spatiotemporal scanning were used to analyze dengue fever cases in Fujian Province from 2011 to 2023.In this peri-od,a total of 3 586 cases of dengue fever were reported in Fujian Province,including 2 360 local cases,1 134 imported cases from abroad,and 92 imported cases from China.Cases were reported in ten prefectures and cities of the province,and 81 out of 88 counties reported cases.Imported cases were reported throughout the year in Fujian Province,but the occurrence of local ca-ses showed clear seasonality.Local cases and domestic imports were concentrated in August to October,whereas overseas im-ports occurred primarily from June to October.The imported cases were mainly from Southeast Asian countries,but a trend of spreading from Southeast Asian countries to South Asia,Africa,the Americas,and other regions,was observed.Spatio-tem-poral clustering of dengue fever was found in Fujian Province(Moran's I value 0.14-0.66,P＜0.05),and the high-high ag-gregation areas were distributed primarily in Fuzhou,Quanzhou,and Putian.Spatio-temporal scanning detected three aggrega-tion areas:one main and two secondary.The aggregation time was from the end of July to October,and the distribution was primarily in Fuzhou,Quanzhou,Putian,Zhangzhou,and Xiamen.The distribution of dengue fever in Fujian Province showed clear spatial and temporal clustering from the end of July to October,and the distribution was primarily in Fuzhou,Quanzhou,Putian,Zhangzhou,and Xiamen.For high concentration areas,national health campaigns,mosquito prevention and control,epidemic surveillance,medical personnel training,and other relevant measures could be carried out in advance before local cases appear every year.Reduce local transmission of dengue fever due to importation.