Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

NLRP3(NLR family pyrin domain containing 3)is the core of the inflammatory response,and its excessive activation involves the development of various diseases,including neurodegenerative diseases,autoimmune diseases and metabolic disorders,etc.In recent years,it has been found that natural flavonoids can extensively inhibit the diseases caused by NLRP3 inflammation overactivation via various mechanisms,including resistance to oxidative stress,promotion of autophagy,stabilization of mitochondrial function,adjustment ion channels and inhibition of NLRP3 inflammation composition.In this paper,we reviewed the relevant latest research reports,compiled the types and pathogenesis of diseases caused by excessive activation of NLRP3 inflammation,and summarized the mechanisms on the prevention and treatment of various diseases by inhibiting NLRP3 inflammation with natural flavonoids.This review provides new ideas for the development of new drugs using flavonoid components in the prevention and treatment of NLRP3 inflammatory-related diseases.

Objective:To further confirm the anti-endotoxin active parts of Lidanpaidu prescription through observing the anti-en-dotoxin intensity based on a half-in vivo method. Methods:The extracting solution of Lidanpaidu prescription was extracted by the sol-vents with different polarity to obtain the active part. The anti-endotoxin activity of the samples was determined by using the Azo color matrix method, and the amount of inactivated endotoxin was compared among the various extraction parts with different dosages. Re-sults:Compared with that of the control group, the amount of inactivated endotoxin by the rat plasma in each administration group was all higher, and the differences were statistically significant (P<0. 05). The rat plasma of the whole prescription administration groups all showed endotoxin inactivation, while the differences among the groups with various dosages were without statistical significance( P>0. 05). The rat plasma of the water soluble fraction administration groups also showed endotoxin inactivation, and the difference be-tween the high dosage group and the low dosage group was statistically significant (P<0. 05). Conclusion:The results of the half-in vivo method showed the consistent anti-endotoxin effect of the whole prescription and the water soluble fraction, furthermore, the dose-effect relationship is preliminarily appeared, suggesting that the water soluble fraction remains the effective components of the whole prescription to a great extent. Therefore, the water soluble fraction can be further confirmed as the active anti-endotoxin part of Lidan-paidu prescription.

Objective: To quantitatively analyze the content of glucose in glucose injection by near infrared spectroscopy to control the quality of the product.Methods: A quantitative model was established by near infrared reflectance spectroscopy and the injection came from pharmaceutical enterprises with different concentrations of glucose and the solution samples came from laboratories with different concentrations of glucose.The liquid sample accessories were selected, a quantitative model was established by a partial least squares method, and the effect of environmental temperature on the model was studied as well.Results: According to the quantitative model, the correlation coefficient reached up to 0.999 3, and RMS deviation (RMSECV) was 0.077 4.In the verification test, the results of various liquid formulas containing glucose were similar to those of the laboratory results.The prediction error was less than 5% within the temperature range of 20-35℃.Conclusion: The model of near-infrared partial least squares (PLS) can accurately predict the content of glucose in glucose products without sodium chloride, and can be used for the quality control of glucose intermediates and the finished products in the large infusion manufacturers

Compared with that for botanical drugs and animal-derived drugs, the identification study for mineral traditional Chi-nese medicines is relatively weak. The traditional identification methods can’ t meet the quality control requirements of mineral tradi-tional Chinese medicines, and the application of modern analysis techniques are needed urgently in the systematic research of mineral traditional Chinese medicines. In the paper, the identification of traditional methods combined with some modern analysis techniques such as X-ray diffraction, near infrared spectroscopy and Raman spectroscopy for mineral traditional Chinese medicines was summarized and analyzed to provide basic idea and methods for the systematic identification construction of mineral traditional Chinese medicines.

Objective:To assess the genetic diversity and phylogenetic relationship of Desmodium styraeifolium from fifteen regions of Guangdong and Guangxi Zhuang autonomous region. Methods:The molecular technique ISSR((inter-simple sequence repeat))was applied to investigate the genetic diversity of Desmodium styraeifolium from fifteen regions of Guangdong and Guangxi Zhuang autonomous region. The data was analyzed with Popgene 1. 32,and a cluster diagram was presented by UPGMA. Results:Totally 51 amplified fragments were obtained by 7 ISSR primers. The results analyzed by Popgene 1. 32 showed that the Shannon diversity index(I)was 0. 3,the NEI’s genetic diversity coefficient(H)was 0. 246 4,the coefficient of genetic differentiation (GST)was 0. 123 8,and the gene flow(Nm)was 3. 539 7. Conclusion:The above mentioned results exhibit that Desmodium styraeifolium from Guangdong,Guangxi and some wild herbal populations has high genetic diversity. The clustering results illustrate that the genetic distance of Desmodium styraeifolium originated from Guangdong and Guangxi is related with geographic distance.