Analysis of transient characteristics and design improvement of the passive residual heat removal system of NHR-200-II

NHR-200-II is a small integrated pressurized water reactor with 200 MW core thermal power. The core heat is transferred to two independent intermediate circuits via fourteen in-vessel primary heat exchangers (PHE), and the heat in the intermediate circuits is transferred to feedwater by two steam generators (SG) in the two intermediate circuits respectively. A passive residual heat removal (PRHR) branch is connected to each intermediate circuit to remove core decay heat under postulated accidents. During normal operation, PRHR branches are isolated by valves while SG branches in intermediate circuits are open. The valves in PRHR branches will be opened and the isolation valves of SG branches will be closed during decay heat removal scenarios. The decay heat removal capacity of NHR-200-II PRHRS could be seriously deteriorated once the isolation valves for SG branches fail to close, which was confirmed in a scaled integral test loop previously. Current understanding of PRHRS’s thermal-hydraulic characteristics with possible isolation failure in SG branches is limited. In this paper, the NHR-200-II PRHRS is modeled with RELAP5 considering the case of success and fail to isolate SG branches. A series of numerical simulations are carried out to study the impact of various parameters, such as the initial temperature, the size of the intermediate circuits’ header, and the initial flow direction in the intermediate circuits. Oscillatory flow is found when SG branches fail to be isolated under certain parameters combinations. An improved PRHRS design is purposed to eliminate possible flow oscillations, and the purposed improved design are tested by numerical simulations

Crosstalk of disulfidptosis-related subtypes, establishment of a prognostic signature and immune infiltration characteristics in bladder cancer based on a machine learning survival framework

BackgroundBladder cancer (BLCA) is the most common malignancy of the urinary tract. On the other hand, disulfidptosis, a mechanism of disulfide stress-induced cell death, is closely associated with tumorigenesis and progression. Here, we investigated the impact of disulfidptosis-related genes (DRGs) on the prognosis of BLCA, identified various DRG clusters, and developed a risk model to assess patient prognosis, immunological profile, and treatment response.MethodsThe expression and mutational characteristics of four DRGs were first analyzed in bulk RNA-Seq and single-cell RNA sequencing data, IHC staining identified the role of DRGs in BLCA progression, and two DRG clusters were identified by consensus clustering. Using the differentially expressed genes (DEGs) from these two clusters, we transformed ten machine learning algorithms into more than 80 combinations and finally selected the best algorithm to construct a disulfidptosis-related prognostic signature (DRPS). We based this selection on the mean C-index of three BLCA cohorts. Furthermore, we explored the differences in clinical characteristics, mutational landscape, immune cell infiltration, and predicted efficacy of immunotherapy between high and low-risk groups. To visually depict the clinical value of DRPS, we employed nomograms. Additionally, we verified whether DRPS predicts response to immunotherapy in BLCA patients by utilizing the Tumour Immune Dysfunction and Rejection (TIDE) and IMvigor 210 cohorts.ResultsIn the integrated cohort, we identified several DRG clusters and DRG gene clusters that differed significantly in overall survival (OS) and tumor microenvironment. After the integration of clinicopathological features, DRPS showed robust predictive power. Based on the median risk score associated with disulfidptosis, BLCA patients were divided into low-risk (LR) and high-risk (HR) groups, with patients in the LR group having a better prognosis, a higher tumor mutational load and being more sensitive to immunotherapy and chemotherapy.ConclusionOur study, therefore, provides a valuable tool to further guide clinical management and tailor the treatment of BLCA patients, offering new insights into individualized treatment

Impact of meteorological factors on the COVID-19 transmission: A multicity study in China

The purpose of the present study is to explore the associations between novel coronavirus disease 2019 (COVID- 19) case counts and meteorological factors in 30 provincial capital cities of China. We compiled a daily dataset including confirmed case counts, ambient temperature (AT), diurnal temperature range (DTR), absolute humidity (AH) and migration scale index (MSI) for each city during the period of January 20th to March 2nd, 2020. First, we explored the associations between COVID-19 confirmed case counts, meteorological factors, and MSI using non-linear regression. Then, we conducted a two-stage analysis for 17 cities with more than 50 confirmed cases. In the first stage, generalized linear models with negative binomial distribution were fitted to estimate city-specific effects of meteorological factors on confirmed case counts. In the second stage, the meta-analysis was conducted to estimate the pooled effects. Our results showed that among 13 cities that have less than 50 confirmed cases, 9 cities locate in the Northern China with average AT below0 °C, 12 cities had average AHbelow4 g/m3, and one city (Haikou) had the highest AH (14.05 g/m3). Those 17 cities with 50 and more cases accounted for 90.6% of all cases in our study. Each 1 °C increase in AT and DTR was related to the decline of daily confirmed case counts, and the corresponding pooled RRs were 0.80 (95% CI: 0.75, 0.85) and 0.90 (95% CI: 0.86, 0.95), respectively. For AH, the association with COVID-19 case counts were statistically significant in lag 07 and lag 014. In addition,we found the all these associations increased with accumulated time duration up to 14 days. In conclusions, meteorological factors play an independent role in the COVID-19 transmission after controlling population migration. Local weather condition with low temperature, mild diurnal temperature range and low humidity likely favor the transmission

Current aspects of small extracellular vesicles in pain process and relief

Abstract Small extracellular vesicles (sEVs) have been identified as a noteworthy paracrine mechanism of intercellular communication in diagnosing and managing neurological disorders. Current research suggests that sEVs play a pivotal role in the pathological progression of pain, emphasizing their critical function in the pathological progression of pain in acute and chronic pain models. By facilitating the transfer of diverse molecules, such as proteins, nucleic acids, and metabolites, sEVs can modulate pain signaling transmission in both the central and peripheral nervous systems. Furthermore, the unique molecules conveyed by sEVs in pain disorders indicate their potential as diagnostic biomarkers. The application of sEVs derived from mesenchymal stem cells (MSCs) in regenerative pain medicine has emerged as a promising strategy for pain management. Moreover, modified sEVs have garnered considerable attention in the investigation of pathological processes and therapeutic interventions. This review presents a comprehensive overview of the current knowledge regarding the involvement of sEVs in pain pathogenesis and treatment. Nevertheless, additional research is imperative to facilitate their clinical implementation. Graphical Abstract Schematic diagram of sEVs in the biogenesis, signal transmission, diagnosis, and treatment of pain disorders. Small extracellular vesicles (sEVs) are secreted by multiple cells, loading with various biomolecules, such as miRNAs, transmembrane proteins, and amino acids. They selectively target other cells and regulating pain signal transmission. The composition of sEVs can serve as valuable biomarkers for pain diagnosis. In particular, mesenchymal stem cell-derived sEVs have shown promise as regenerative medicine for managing multiple pain disorders. Furthermore, by modifying the structure or contents of sEVs, they could potentially be used as a potent analgesic method

Association between weight-adjusted-waist index and chronic kidney disease: a cross-sectional study

Abstract Aims We aimed to investigate the potential association between weight-adjusted-waist index (WWI) and chronic kidney disease (CKD). Design and methods This research examined data collected from the National Health and Nutrition Examination Survey (NHANES) spanning from 1999 to 2020. CKD was defined as the low estimated glomerular filtration rate (eGFR) or the existence of albuminuria (urinary albumin-to-creatinine ratio (ACR) ≥ 30mg/g). Low-eGFR was described as eGFR < 60 mL/min/1.73m2. The associations between WWI with CKD, albuminuria, and low-eGFR were examined using generalized additive models and weighted multivariable logistic regression models. We also analyzed the associations of other obesity indicators with CKD, albuminuria, and low-eGFR, including body mass index (BMI), waist-to-height ratio (WHtR), waist circumference(WC), height, and weight. The receiver operating characteristic (ROC) curves were used to assess and compare their diagnostic abilities. Results Males made up 48.26% of the total 40,421 individuals that were recruited. The prevalences of CKD, albuminuria, and low-eGFR were 16.71%, 10.97%, and 7.63%, respectively. WWI was found to be positively linked with CKD (OR = 1.42; 95% CI: 1.26, 1.60). A nonlinear connection between WWI and CKD was found using smooth curve fitting. Additionally, a higher prevalence of albuminuria is linked to a higher level of WWI (OR = 1.60; 95% CI: 1.40, 1.82). Different stratifications did not substantially influence the connection between WWI and CKD, albuminuria, and low-eGFR, according to subgroup analysis and interaction tests. We observed higher height was related to higher low-eGFR prevalence (OR = 1.05; 95% CI: 1.03, 1.06). ROC analysis revealed that WWI had the best discrimination and accuracy for predicting CKD and albuminuria compared to other obesity indicators (BMI, WHTR, WC, height and weight). In addition, height had the highest area under the curve (AUC) value for predicting low-eGFR. Conclusion WWI is the best obesity indicator to predict CKD and albuminuria compared to other obesity indicators (BMI, WHTR, WC, height, and weight). WWI and CKD and albuminuria were found to be positively correlated. Furthermore, height had the strongest ability to predict low-eGFR. Therefore, the importance of WWI and height in assessing kidney health in US adults should be emphasized

Aging-Induced Reduction in Safflower Seed Germination via Impaired Energy Metabolism and Genetic Integrity Is Partially Restored by Sucrose and DA-6 Treatment

Seed storage underpins global agriculture and the seed trade and revealing the mechanisms of seed aging is essential for enhancing seed longevity management. Safflower is a multipurpose oil crop, rich in unsaturated fatty acids that are at high risk of peroxidation as a contributory factor to seed aging. However, the molecular mechanisms responsible for safflower seed viability loss are not yet elucidated. We used controlled deterioration (CDT) conditions of 60% relative humidity and 50 °C to reduce germination in freshly harvested safflower seeds and analyzed aged seeds using biochemical and molecular techniques. While seed malondialdehyde (MDA) and fatty acid content increased significantly during CDT, catalase activity and soluble sugar content decreased. KEGG analysis of gene function and qPCR validation indicated that aging severely impaired several key functional and biosynthetic pathways including glycolysis, fatty acid metabolism, antioxidant activity, and DNA replication and repair. Furthermore, exogenous sucrose and diethyl aminoethyl hexanoate (DA-6) treatment partially promoted germination in aged seeds, further demonstrating the vital role of impaired sugar and fatty acid metabolism during the aging and recovery processes. We concluded that energy metabolism and genetic integrity are impaired during aging, which contributes to the loss of seed vigor. Such energy metabolic pathways as glycolysis, fatty acid degradation, and the tricarboxylic acid cycle (TCA) are impaired, especially fatty acids produced by the hydrolysis of triacylglycerols during aging, as they are not efficiently converted to sucrose via the glyoxylate cycle to provide energy supply for safflower seed germination and seedling growth. At the same time, the reduced capacity for nucleotide synthesis capacity and the deterioration of DNA repair ability further aggravate the damage to DNA, reducing seed vitality

Table2_Association between monocyte-to-lymphocyte ratio and prostate cancer in the U.S. population: a population-based study.DOCX

Introduction:Monocyte-to-lymphocyte ratio (MLR) is a convenient and noninvasive inflammatory biomarker, and inflammation has been reported to be associated with prostate cancer (PCa). Our objective was to ascertain any possible correlation between PCa and MLR.Methods:We utilized data from the 1999–2020 cycles of the National Health and Nutrition Examination Survey (NHANES) regarding MLR and PCa. The independent associations of MLR and other inflammatory biomarkers (platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), system inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI)) with PCa was investigated using weighted multivariate logistic regression and generalized additive models. Receiver operating characteristic (ROC) curves were conducted to evaluate and contrast their diagnostic capabilities.Results:The analysis we conducted comprised 25,367 persons in total. The mean MLR was 0.31 ± 0.14. The prevalence of PCa was 3.1%. A positive association was found between MLR and PCa (OR = 2.28; 95% CI: 1.44, 3.62). According to the interaction tests, age, body mass index (BMI), hypertension, diabetes, and smoking status did not significantly impact the relationship between MLR and PCa (all p for interaction >0.05). ROC analysis showed that MLR had a stronger discriminative ability and accuracy in predicting PCa than other inflammatory biomarkers (NLR, SII, AISI, PLR, and SIRI).Conclusion:MLR might be better than other inflammatory biomarkers (NLR, SIRI, AISI, PLR, and SII) in predicting PCa. American adults who have elevated levels of MLR, NLR, PLR, SII, and AISI should be aware that they have a greater risk of PCa.</p

Vertical deformation and tectonic activity in Tianjin area

Vertical deformation in Tianjin area during 1992–2008 was calculated from leveling data. The effect of large surface subsidence caused by extensive groundwater pumping was removed by fitting the data along each survey line with a polynomial function. The results are fitted with crustal blocks individually in this area. Vertical deformation rates are mapped, vertical rates of the main fault zones were calculated, and the activities of the blocks and fault zones were investigated. The observed vertical deformation shows that some of the blocks tilted and some blocks rose or subsided as a whole. The vertical rates at fault zones in the area vary within the range of 0.13-0.48 mm/a, with an average value of 0.29 mm/a

Table1_Association between monocyte-to-lymphocyte ratio and prostate cancer in the U.S. population: a population-based study.DOCX

Introduction:Monocyte-to-lymphocyte ratio (MLR) is a convenient and noninvasive inflammatory biomarker, and inflammation has been reported to be associated with prostate cancer (PCa). Our objective was to ascertain any possible correlation between PCa and MLR.Methods:We utilized data from the 1999–2020 cycles of the National Health and Nutrition Examination Survey (NHANES) regarding MLR and PCa. The independent associations of MLR and other inflammatory biomarkers (platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), system inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI)) with PCa was investigated using weighted multivariate logistic regression and generalized additive models. Receiver operating characteristic (ROC) curves were conducted to evaluate and contrast their diagnostic capabilities.Results:The analysis we conducted comprised 25,367 persons in total. The mean MLR was 0.31 ± 0.14. The prevalence of PCa was 3.1%. A positive association was found between MLR and PCa (OR = 2.28; 95% CI: 1.44, 3.62). According to the interaction tests, age, body mass index (BMI), hypertension, diabetes, and smoking status did not significantly impact the relationship between MLR and PCa (all p for interaction >0.05). ROC analysis showed that MLR had a stronger discriminative ability and accuracy in predicting PCa than other inflammatory biomarkers (NLR, SII, AISI, PLR, and SIRI).Conclusion:MLR might be better than other inflammatory biomarkers (NLR, SIRI, AISI, PLR, and SII) in predicting PCa. American adults who have elevated levels of MLR, NLR, PLR, SII, and AISI should be aware that they have a greater risk of PCa.</p

Image1_Association between monocyte-to-lymphocyte ratio and prostate cancer in the U.S. population: a population-based study.TIF

Introduction:Monocyte-to-lymphocyte ratio (MLR) is a convenient and noninvasive inflammatory biomarker, and inflammation has been reported to be associated with prostate cancer (PCa). Our objective was to ascertain any possible correlation between PCa and MLR.Methods:We utilized data from the 1999–2020 cycles of the National Health and Nutrition Examination Survey (NHANES) regarding MLR and PCa. The independent associations of MLR and other inflammatory biomarkers (platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), system inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI)) with PCa was investigated using weighted multivariate logistic regression and generalized additive models. Receiver operating characteristic (ROC) curves were conducted to evaluate and contrast their diagnostic capabilities.Results:The analysis we conducted comprised 25,367 persons in total. The mean MLR was 0.31 ± 0.14. The prevalence of PCa was 3.1%. A positive association was found between MLR and PCa (OR = 2.28; 95% CI: 1.44, 3.62). According to the interaction tests, age, body mass index (BMI), hypertension, diabetes, and smoking status did not significantly impact the relationship between MLR and PCa (all p for interaction >0.05). ROC analysis showed that MLR had a stronger discriminative ability and accuracy in predicting PCa than other inflammatory biomarkers (NLR, SII, AISI, PLR, and SIRI).Conclusion:MLR might be better than other inflammatory biomarkers (NLR, SIRI, AISI, PLR, and SII) in predicting PCa. American adults who have elevated levels of MLR, NLR, PLR, SII, and AISI should be aware that they have a greater risk of PCa.</p