Assessment of nomogram model for the prediction of esophageal variceal hemorrhage in hepatitis B-induced hepatic cirrhosis.

BACKGROUND: Esophageal variceal (EV) hemorrhage is a life-threatening consequence of portal hypertension in hepatitis B virus (HBV) -induced cirrhotic patients. Screening upper endoscopy and endoscopic variceal ligation to find EVs for treatment have complications, contraindications, and high costs. We sought to identify the nomogram models (NMs) as alternative predictions for the risk of EV hemorrhage. METHODS: In this case-control study, we retrospectively analyzed 241 HBV-induced liver cirrhotic patients treated for EVs at the Second People's Hospital of Fuyang City, China from January 2021 to April 2023. We applied univariate analysis and multivariate logistic regression to assess the accuracy of various NMs in EV hemorrhage. The area under the curve (AUC) and calibration curves of the receiver's operating characteristics were used to evaluate the predictive accuracy of the nomogram. Decision curve analysis (DCA) was used to determine the clinically relevant of nomograms. RESULTS: In the prediction group, multivariate logistic regression analysis identified platelet distribution and spleen length as independent risk factors for EVs. We applied NMs as the independent risk factors to predict EVs risk. The NMs fit well with the calibration curve and have good discrimination ability. The AUC and DCA demonstrated that NMs with a good net benefit. The above results were validated in the validation cohort. CONCLUSION: Our non-invasive NMs based on the platelet distribution width and spleen length may be used to predict EV hemorrhage in HBV-induced cirrhotic patients. NMs can help clinicians to increase diagnostic performance leading to improved treatment measures.

The impact of environmental regulation on renewable energy development in China from the perspective of spatial effects.

From a spatial perspective, this paper constructs a spatial Durbin model based on the adjacent weight matrix to analyze the impact of environmental regulation on the development of renewable energy in 30 provinces (autonomous regions and municipalities directly under the Central Government) in China from 2007 to 2020. The results show that (1) both environmental regulation and renewable energy development have positive spatial autocorrelation and form relatively similar spatial agglomeration areas, specifically showing the characteristics of "high-high" agglomeration in resource-rich areas and "low-low" agglomeration in resource-scarce areas. (2) Environmental regulation significantly promotes the development of local renewable energy and has a significant spatial spillover effect on the development of renewable energy in neighboring provinces. (3) The moderating effect results show that renewable energy installed capacity and electricity demand play an inverse moderating role between environmental regulation and renewable energy development. (4) From the perspective of different regions, the impact of environmental regulation on the development of renewable energy is heterogeneous. Based on the research conclusions, this paper finally provides corresponding policy suggestions from three aspects: regional cooperation, technical support, and differentiation.

Assessment of Non-invasive Markers for the Prediction of Esophageal Variceal Hemorrhage.

Background: Esophageal variceal (EV) hemorrhage is a life-threatening consequence of portal hypertension in cirrhotic patients. Screening upper endoscopy and endoscopic variceal ligation to identify and treat EVs have contraindications, complications, and high costs. We sought to identify non-invasive tests (NITs) as alternatives to endoscopic EV screening. Methods: In this case-control study, we retrospectively analyzed 286 cirrhotic patients treated for EVs at the Second People's Hospital of Fuyang City, China from January to December 2019. We applied ROC curve analysis to assess the accuracy of various NITs in predicting EV hemorrhage. Results: There were significant differences between the hemorrhage and non-hemorrhage groups in median serum albumin (ALB) (p < 0.001), median bilirubin (TBIL) (p < 0.046), prothrombin (PT) time (p < 0.001), Golgi protein 73 (GP73; p = 0.012) and Child-Pugh (C-P) scores (p < 0.001). For ALB (cutoff <33.2g/L), PT time (cutoff > 14.2 seconds), GP73 (cutoff > 126.4 ng/ml), and C-P scores, the areas under the ROC curves (AUCs) were 73.4% (95% CI: 67.5-79.2), 68.6% (95% CI: 62.4-74.8), 62.2% (95% CI: 52.8-71.5) and 69.8% (95%CI: 63.8-75.8), respectively, with corresponding sensitives of 71.5, 59.8, 69.8, and 92.2% and specificities of 65.6%, 70.1%, 56.5%, and 38.6%. When ALB was combined with GP73, the AUC was 74.3% (95% CI: 66.1-82.5) with a sensitivity of 65.1% and specificity of 76.5%. When ALB, PT, and C-P scores were combined, the AUC was 76.5% (95% CI: 70.9-82.1) with a sensitivity of 79.5% and specificity of 64.3%. When ALB, PT, GP73, and C-P scores were combined, the AUC was 75.2% (95% CI: 67.3-83.1) with a sensitivity of 54.0% and specificity of 86.9%. Conclusion: ALB, TBIL, GP73, and C-P scores, may be used to predict EV hemorrhage in cirrhotic patients. The combination of multiple NITs is better than a single index and can increase diagnostic performance.

Genome-Wide Assessment of Avocado Germplasm Determined from Specific Length Amplified Fragment Sequencing and Transcriptomes: Population Structure, Genetic Diversity, Identification, and Application of Race-Specific Markers.

Genomic data is a powerful tool. However, the phylogenetic relationships among different ecological races of avocado remain unclear. Here, we used the results from specific length amplified fragment sequencing (SLAF-seq) and transcriptome data to infer the population structure and genetic diversity of 21 avocado cultivars and reconstructed the phylogeny of three ecological races and two interracial hybrids. The results of the three analyses performed (unweighted pair-group methods with arithmetic means (UPGMA) cluster, Principal coordinate analysis (PCoA), and STRUCTURE) based on single nucleotide polymorphisms (SNPs) from SLAF-seq all indicated the existence of two populations based on botanical race: Mexican⁻Guatemalan and West Indian genotype populations. Our results based on SNPs from SLAF-seq indicated that the Mexican and Guatemalan races were more closely related to each other than either was to the West Indian race, which also was confirmed in the UPGMA cluster results based on SNPs from transcriptomic data. SNPs from SLAF-seq provided strong evidence that the Guatemalan, Mexican, and Guatemalan × Mexican hybrid accession possessed higher genetic diversity than the West Indian races and Guatemalan × West Indian hybrid accessions. Six race-specific Kompetitive allele specific PCR (KASP) markers based on SNPs from SLAF-seq were then developed and validated.

Assessment of l-Asparaginase Pharmacodynamics in Mouse Models of Cancer.

l-asparaginase (ASNase) is a metabolism-targeted anti-neoplastic agent used to treat acute lymphoblastic leukemia (ALL). ASNase's anticancer activity results from the enzymatic depletion of asparagine (Asn) and glutamine (Gln), which are converted to aspartic acid (Asp) and glutamic acid (Glu), respectively, in the blood. Unfortunately, accurate assessment of the in vivo pharmacodynamics (PD) of ASNase is challenging because of the following reasons: (i) ASNase is resilient to deactivation; (ii) ASNase catalytic efficiency is very high; and (iii) the PD markers Asn and Gln are depleted ex vivo in blood samples containing ASNase. To address those issues and facilitate longitudinal studies in individual mice for ASNase PD studies, we present here a new LC-MS/MS bioanalytical method that incorporates rapid quenching of ASNase for measurement of Asn, Asp, Gln, and Glu in just 10 µL of whole blood, with limits of detection (s:n ≥ 10:1) estimated to be 2.3, 3.5, 0.8, and 0.5 µM, respectively. We tested the suitability of the method in a 5-day, longitudinal PD study in mice and found the method to be simple to perform with sufficient accuracy and precision for whole blood measurements. Overall, the method increases the density of data that can be acquired from a single animal and will facilitate optimization of novel ASNase treatment regimens and/or the development of new ASNase variants with desired kinetic properties.

Toward precision medicine in neurological diseases.

Technological development has paved the way for accelerated genomic discovery and is bringing precision medicine into view. The goal of precision medicine is to deliver optimally targeted and timed interventions tailored to an individual's molecular drivers of disease. Neurological diseases are promisingly suited models for precision medicine because of the rapidly expanding genetic knowledge base, phenotypic classification, the development of biomarkers and the potential modifying treatments. Moving forward, it is crucial that through these integrated research platforms to provide analysis both for accurate personal genome analysis and gene and drug discovery. Here we describe our vision of how precision medicine can bring greater clarity to the clinical and biological complexity of neurological diseases.

Meta-analysis of modifiable risk factors for Alzheimer's disease.

BACKGROUND: The aetiology of Alzheimer's disease (AD) is believed to involve environmental exposure and genetic susceptibility. The aim of our present systematic review and meta-analysis was to roundly evaluate the association between AD and its modifiable risk factors. METHODS: We systematically searched PubMed and the Cochrane Database of Systematic Reviews from inception to July 2014, and the references of retrieved relevant articles. We included prospective cohort studies and retrospective case-control studies. RESULTS: 16,906 articles were identified of which 323 with 93 factors met the inclusion criteria for meta-analysis. Among factors with relatively strong evidence (pooled population >5000) in our meta-analysis, we found grade I evidence for 4 medical exposures (oestrogen, statin, antihypertensive medications and non-steroidal anti-inflammatory drugs therapy) as well as 4 dietary exposures (folate, vitamin E/C and coffee) as protective factors of AD. We found grade I evidence showing that one biochemical exposure (hyperhomocysteine) and one psychological condition (depression) significantly increase risk of developing AD. We also found grade I evidence indicative of complex roles of pre-existing disease (frailty, carotid atherosclerosis, hypertension, low diastolic blood pressure, type 2 diabetes mellitus (Asian population) increasing risk whereas history of arthritis, heart disease, metabolic syndrome and cancer decreasing risk) and lifestyle (low education, high body mass index (BMI) in mid-life and low BMI increasing the risk whereas cognitive activity, current smoking (Western population), light-to-moderate drinking, stress, high BMI in late-life decreasing the risk) in influencing AD risk. We identified no evidence suggestive of significant association with occupational exposures. CONCLUSIONS: Effective interventions in diet, medications, biochemical exposures, psychological condition, pre-existing disease and lifestyle may decrease new incidence of AD.