Miracle-dz/UniFAR-FTUs huggingface dataset:
Response of Wild Blueberry Yield to Spatial Variability of Soil Properties

Abstract Crop management practices within wild blueberry fields are implemented uniformly, with inadequate attention being given to substantial variations in soil properties and fruit yield. These variations emphasize the need for precise and site-specific crop management based on proper characterization and quantification of spatial soil variability. The objective of this research was to characterize and quantify the spatial patterns of variability in soil properties and fruit yield. A grid pattern of sampling points was established at each experimental site to collect soil and fruit yield samples during 2009 to 2010 at North River and Carmal sites, Nova Scotia, Canada. The soil samples were collected from 0- to 15-cm depth at each grid point. These soil samples were analyzed for soil organic matter, pH, texture, electrical conductivity, and inorganic nitrogen (N). The volumetric moisture content (&thetas;v) was recorded at each grid point using time domain reflectometry. Ground conductivity readings were also recorded using dual EM conductivity meter at same selected grid points. Fruit yield was mapped using calibrated digital color photography during the crop year. The coefficient of variation of the soil properties and fruit yield suggested moderate to high variability (coefficient of variation >15%) except for soil pH. The results of correlation analysis indicated that the values for inorganic N, soil organic matter, electrical conductivity, clay, and &thetas;v were generally higher in high-yielding areas and vice versa. The trend was opposite for sand and silt content, which were higher in low-yielding areas. Most of the soil properties had a large spatial variation with semivariogram range of 20 to 50 m and varied greatly within field. Kriged maps of soil properties and fruit yield also showed substantial variation within field. Characterization of spatial soil variability in wild blueberry fields would assist in planning future soil sampling in new fields showing soil and/or yield variability. The selection of soil sampling should be based on the sampling interval suggested by the variogram range (<20 m). Proper soil sampling can help in identifying yield-limiting soil properties and develop prescription maps for site-specific nutrient management to ameliorate unproductive areas and reduce environmental contamination.
Perspectives of bilateral thoracic sympathectomy for treatment of heart failure

Surgical neuromodulation therapies are still considered a last resort when standard therapies have failed for patients with progressive heart failure (HF). Although a number of experimental studies have provided robust evidence of its effectiveness, the lack of strong clinical evidence discourages practitioners. Thoracic unilateral sympathectomy has been extensively studied and has failed to show significant clinical improvement in HF patients. Most recently, bilateral sympathectomy effect was associated with a high degree of success in HF models, opening the perspective to be investigated in randomized controlled clinical trials. In addition, a series of clinical trials showed that bilateral sympathectomy was associated with a decreased risk of sudden death, which is an important outcome in patients with HF. These aspects indicates that bilateral sympathectomy could be an important alternative in the treatment of HF wherein pharmacological treatment barely reaches the target dose.
EZH2 Exacerbates Breast Cancer by Methylating and Activating STAT3 Directly

Breast cancer is one of the most common causes of female death globally. Numerous clinical drugs for breast cancer have been developed, but the unsatisfactory, inevitable side effects and drug resistance are the emerging threatens. Therefore, it is necessary to investigate the comprehensive mechanism of breast cancer. Enhancer of zeste homolog 2 (EZH2) is a candidate oncogenic driver in diverse cancers, such as breast cancer. The canonical role of EZH2 has been vastly investigated, but the non-canonical function of EZH2 in breast cancer remains unclear. Here, we demonstrated that EZH2 exacerbated breast cancer in non-canonical manner by methylating STAT3. EZH2 over-expressed in breast cancer patients and regulated STAT3 post-transcriptionally according to TCGA datasets. Chemical and genetic inhibition of EZH2 impeded proliferation and migration of breast cancer cells, which may be partially rescued by STAT3 over-expression. EZH2 physically interacted with STAT3 and methylated STAT3 directly, resulting in increased nuclear localization and chromatin of STAT3. Furthermore, the mutation of STAT3 methylation site, targeted by EZH2, impeded the transcriptional activity of STAT3. Eventually, disturbed STAT3 methylation by EZH2 in animal model showed decreased breast cancer growth. These data confirm that EZH2 exacerbates breast cancer by methylating STAT3 directly, and thus providing a promising therapeutic target for breast cancer.
Neprilysin Inhibition Increases Glucagon Levels in Humans and Mice With Potential Effects on Amino Acid Metabolism

Abstract Context Inhibitors of the protease neprilysin (NEP) are used for treating heart failure, but are also linked to improvements in metabolism. NEP may cleave proglucagon-derived peptides, including the glucose and amino acid (AA)-regulating hormone glucagon. Studies investigating NEP inhibition on glucagon metabolism are warranted. Objective This work aims to investigate whether NEP inhibition increases glucagon levels. Methods Plasma concentrations of glucagon and AAs were measured in eight healthy men during a mixed meal with and without a single dose of the NEP inhibitor/angiotensin II type 1 receptor antagonist, sacubitril/valsartan (194 mg/206 mg). Long-term effects of sacubitril/valsartan (8 weeks) were investigated in individuals with obesity (n = 7). Mass spectrometry was used to investigate NEP-induced glucagon degradation, and the derived glucagon fragments were tested pharmacologically in cells transfected with the glucagon receptor (GCGR). Genetic deletion or pharmacological inhibition of NEP with or without concomitant GCGR antagonism was tested in mice to evaluate effects on AA metabolism. Results In healthy men, a single dose of sacubitril/valsartan significantly increased postprandial concentrations of glucagon by 228%, concomitantly lowering concentrations of AAs including glucagonotropic AAs. Eight-week sacubitril/valsartan treatment increased fasting glucagon concentrations in individuals with obesity. NEP cleaved glucagon into 5 inactive fragments (in vitro). Pharmacological NEP inhibition protected both exogenous and endogenous glucagon in mice after an AA challenge, while NEP-deficient mice showed elevated fasting and AA-stimulated plasma concentrations of glucagon and urea compared to controls. Conclusion NEP cleaves glucagon, and inhibitors of NEP result in hyperglucagonemia and may increase postprandial AA catabolism without affecting glycemia.
Histone Deacetylase Inhibitor-Induced CDKN2B and CDKN2D Contribute to G2/M Cell Cycle Arrest Incurred by Oxidative Stress in Hepatocellular Carcinoma Cells via Forkhead Box M1 Suppression

Forkhead box protein M1 (FOXM1) is a pivotal regulator of G2/M cell cycle progression in many types of cancer. Previously, our study demonstrated that histone deacetylase inhibition (HDACi) sensitizes hepatocellular carcinoma cells (HCC) to oxidative stress through FOXM1 suppression. However, the mechanism underlying its suppression by HDACi still requires elucidation. We hypothesized that HDACi induce genes responsible for destabilizing and inactivating FOXM1. The transcriptome in the HepG2 was revealed by massive analysis of cDNA end (MACE). Expression of mRNA and proteins were analyzed by quantitative real-time PCR (qPCR) and western blot, respectively. Cell cycle was analyzed by fluorescence-activated cell sorting (FACS). Oxidative stress and HDACi suppressed CDK4/6 levels while enhancing CDK inhibitor 2B and 2D (CDKN2B and CDKN2D) expressions in HCC. Palbociclib, a specific inhibitor of CDK4/6, induced G2/M cell cycle arrest in HCC by down-regulating phosphorylation level of FOXM1, and its downstream target genes such as aurora kinase A (AURKA) and polo-like kinase 1 (PLK1). HDACi treatment increased the ubiquitination level of FOXM1 by suppressing ubiquitin-specific peptidase 21 (USP21), which deubiquitinates FOXM1. Inhibiting FOXM1 degradation with MG132 treatment affected neither palbociclib-induced G2/M cell cycle arrest nor expression of its target genes. Double knockdown of CDKN2B and CDKN2D reduced the oxidative stress and HDACi-induced G/2M cell cycle arrest. In conclusion, oxidative stress and HDACi synergistically cause G2/M cell cycle arrest via CDKN2 induction, which sequentially inhibits CDK4/6, FOXM1, and its downstream target genes AURKA, PLK1, and CCNB1 phosphorylation in HCC.
Colorectal Cancer: From Genetic Landscape to Targeted Therapy

Colorectal cancer (CRC) is the third most common cancer type and the second cause of death worldwide. The advancement in understanding molecular pathways involved in CRC has led to new classifications based on the molecular characteristics of each tumor and also improved CRC management through the integration of targeted therapy into clinical practice. In this review, we will present the main molecular pathways involved in CRC carcinogenesis, the molecular classifications. The anti-VEGF and anti-EGFR therapies currently used in CRC treatment and those under clinical investigation will also be outlined, as well as the mechanisms of primary and acquired resistance to anti-EGFR monoclonal antibodies (cetuximab and panitumumab). Targeted therapy has led to great improvement in the treatment of metastatic CRC. However, there has been variability in CRC treatment outcomes due to molecular heterogeneity in colorectal tumors, which underscores the need for identifying prognostic and predictive biomarkers for CRC-targeted drugs.
COVID-19 vaccinations are associated with reduced fatality rates: Evidence from cross-county quasi-experiments

Background Scientists have demonstrated the efficacy of vaccines against severe acute respiratory syndrome coronavirus 2 in randomized controlled trials. However, the extent to which reductions in COVID-19 case fatality ratio (CFR) are attributable to mass vaccination in the real world remains unclear. This study evaluated the association of COVID-19 vaccine coverage with CFR on a global scale. Methods The sample was a longitudinal data set of 90 countries over 25 weeks, from the first week of November 2020 to the third week of April 2021. CFR was measured in deaths per 100 COVID-19 confirmed cases; vaccine coverage was defined as the number of people who received at least one vaccine dose per 10 people in the total population. Data were retrieved from open-access databases, including Our World in Data and the Oxford COVID-19 Government Response Tracker. A country-level random effects model was used; a comprehensive set of variables for country characteristics and nonpharmaceutical interventions were included. Results A 10% increase in vaccine coverage was associated with a 7.6% reduction in the CFR (95% confidence interval (CI = -12.6 to -2.7%, P = 0.002). This association was stronger in countries with more effective governments (-8.3%; 95% CI = -13.6 to -3.1%, P = 0.002) and higher transport infrastructure quality (-8.1%; 95% CI = -13.3 to -2.9%, P = 0.002). Moreover, the vaccine coverage was associated with a reduced CFR in a dose-dependent manner. When vaccine coverage achieved 0.8 to 1.6, 1.6 to 3.2 and ≥3.2 per 10 people, the CFR reduced by 12.7% (95 CI = -21.8 to -3.6%, P = 0.006), 21.2% (95 CI = -33.9 to -8.5%, P = 0.001) and 31.3% (95 CI = -51.5 to -11.0%, P = 0.002), respectively as compared with no vaccination. Conclusions Our results provide supporting evidence that vaccination is critical to preventing deaths among infected people. Vaccination programmes have yielded significant health benefits in certain countries. However, globally, a large gap remains between observed and achievable fatality reductions. Continuous improvement in vaccine coverage will be critical to transforming efficacious vaccines into desired health outcomes.
Association between Red Blood Cell Distribution Width and Diabetic Retinopathy: A 5-Year Retrospective Case-Control Study

Purpose Red blood cell distribution width (RDW) has been regarded as an emerging biomarker of the general population and cardiovascular disease. In this study, we aimed to evaluate the association between RDW and diabetic retinopathy (DR). Methods This case-control study included 167 patients with DR, 131 patients with diabetes mellitus (DM), and 170 age- and sex-matched healthy controls from April 2014 to May 2019. Demographic data, laboratory parameters, and ocular examinations were collected. Results RDW values of the DR group were significantly higher than those of the healthy control (p < 0.001) and DM group (p=0.002). A similar trend was observed when RDW was compared among the 3 groups with respect to age and gender. Logistic regression analysis has shown the OR of RDW was 3.791 (2.33–6.168; p < 0.001) against the control group and was 1.348 (0.997–1.823; p=0.047) against the DM group. Conclusion RDW values were significantly elevated in DR patients, and an elevated RDW was associated with an increased incidence of DR in patients with DM.
Development and Validation of a Magnetic Resonance Imaging-Based Machine Learning Model for TMJ Pathologies

The purpose of this study was to propose a machine learning model and assess its ability to classify TMJ pathologies on magnetic resonance (MR) images. This retrospective cohort study included 214 TMJs from 107 patients with TMJ signs and symptoms. A radiomics platform was used to extract (Huiying Medical Technology Co., Ltd., China) imaging features of TMJ pathologies, condylar bone changes, and disc displacements. Thereafter, different machine learning (ML) algorithms and logistic regression were implemented on radiomic features for feature selection, classification, and prediction. The following radiomic features included first-order statistics, shape, texture, gray-level cooccurrence matrix (GLCM), gray-level run length matrix (GLRLM), and gray-level size zone matrix (GLSZM). Six classifiers, including logistic regression (LR), random forest (RF), decision tree (DT), k-nearest neighbors (KNN), XGBoost, and support vector machine (SVM) were used for model building which could predict the TMJ pathologies. The performance of models was evaluated by sensitivity, specificity, and ROC curve. KNN and RF classifiers were found to be the most optimal machine learning model for the prediction of TMJ pathologies. The AUC, sensitivity, and specificity for the training set were 0.89 and 1, while those for the testing set were 0.77 and 0.74, respectively, for condylar changes and disc displacement, respectively. For TMJ condylar bone changes Large-Area High-Gray-Level Emphasis, Gray-Level Nonuniformity, Long-Run Emphasis Long-Run High-Gray-Level Emphasis, Flatness, and Volume features, while for TMJ disc displacements Average Intensity, Sum Average, Spherical Disproportion, and Entropy features, were selected. This study has proposed a machine learning model by KNN and RF analysis on TMJ MR images, which can be used to classify condylar changes and TMJ disc displacements.
Correlation between tumor location and survival in stage I lung adenocarcinoma and squamous cell carcinoma: a SEER-based study

Background: Whether location mattered remained controversial in early-stage non-small cell lung cancer. Methods: We conducted a retrospective study with the Surveillance, Epidemiology, and End Results (SEER) database. Overall survival (OS) and lung cancer-specific survival (LCSS) with landmark analysis and restricted mean survival time (RMST) were compared between patients with a tumor in upper lobe and non-upper lobe. The multivariable Cox analysis was applied to evaluate multiple prognostic factors. Results: Tumor in non-upper lobe had worse OS (hazard ratio [HR]: 1.354, p < 0.001) and LCSS (HR: 1.476, p = 0.005) than the upper lobe in stage IB adenocarcinoma in 32-month landmark and IA3 (OS, HR: 1.300, p < 0.001; LCSS, HR: 1.413, p = 0.004) adenocarcinoma in 48-month landmark, but not in stage IA1 and IA2 adenocarcinoma. The results remained positive in subgroups of < 4, ≥ 4 and ≥ 11 LN examined in stage IB tumor and ≥ 4 LN examined in stage IA3 tumor. For SCC, non-upper lobar tumor had similar OS and LCSS with upper lobar tumor in all stages. The multivariate Cox analysis confirmed that the non-upper lobe was an independent risk factor in stage IA3-IB adenocarcinoma, but not in SCC. Adjuvant chemotherapy (ACT) could improve OS in stage IB adenocarcinoma (HR: 0.586, p < 0.001) and SCC (HR: 0.708, p = 0.030) located in non-upper lobe. Conclusions: Non-upper lobar adenocarcinoma in stage IA3-IB was associated with worse prognosis. ACT may improve prognosis in stage IB tumor located in non-upper lobe.
Comparison of Diagnostic Performance of Classification Trees and Hematological Discrimination Functions for Differential Diagnosis between the Two Common Hematologic Disorders: An Application of Multidimensional Scaling and Cluster Analysis

Background: Several hematological indices have been already proposed to discriminate between iron deficiency anemia (IDA) and β‐thalassemia trait (βTT). The aim of the present study was to compare the diagnostic performance of different hematological discrimination indices with statistical methods such as decision trees to discriminate IDA from βTT. Methods: Consisting of 1178 patients with hypochromic microcytic anemia (708 patients with βTT and 470 patients with IDA), this cross-sectional study intended to compare the diagnostic performance of 43 hematological discrimination indices and tree-based methods such as J48, CART, Evtree, Ctree, QUEST, CRUISE as well as GUIDE to discriminate IDA from βTT. Moreover, multidimensional scaling and cluster analysis were used to identify the homogeneous subgroups of discrimination methods with similar performances.Results: All the classification tree algorithms showed acceptable accuracy measures for discrimination between IDA and βTT in comparison with other hematological discrimination indices. The results indicated that CRUISE tree algorithm had better diagnostic performance and efficiency among other discrimination methods. In turn, this tree algorithm showed the high Youden's index (88.03%), accuracy (94.57%), diagnostic odds ratio (311.63) and F-measure (95.54%) in the differential diagnosis of IDA from βTT. In addition, AUC of this algorithm indicated more precise classification with a value of 0.94 and this model was found to have excellent diagnostic accuracy. Also, CRUISE tree algorithm showed that Mean corpuscular volume can be considered as the main variable in discrimination as it extracted six homogenous subgroups of patients.Conclusions: CRUISE tree algorithm as a powerful method in data mining techniques can be used to develop accurate differential methods along with other laboratory parameters to discriminate IDA from βTT.
Contents of Selected Nutrients and Heavy Metals in Biogas Slurry

In the present study,we analyzed basic characters,contents of nutrients and heavy metals in biogas slurry and dregs collected from Chongqing.The results showed that the pH of the slurry were either neutral or light-alkalinity.Contents of both nutrients and heavy metals were changeable and affected by raw material used.The average contents of nutrients in slurry were found to be in an order: KNP,exception of P,which in dregs was higher than K and N.The order of the average content of middle-micronutrient in slurry from high to low was Ca,Mg,Fe,Zn,Cu and Mn and in dregs was CaFe,Mg,MnCu、Zn.The average contents of heavy metals in slurry were in a range of: total AsCrCdPbHg and in dregs total CrAsPbCdHg,respectively.The contents and variation of heavy metals in the slurry fermented with pig manure were lower than others except for the content of arsenic.The contents of heavy metals exceeded limitations in the studied slurries except lead.In addition,arsenic was in highest contents.However,there was little risk for dregs in our study.
Didactic Engineering (DE) and Professional Didactics (PD): A Proposal for Historical Eesearch in Brazil on Recurring Number Sequences

The present work presents some examples of data originated from a set of investigations developed in Brazil, at the Federal Institute of Education, Science and Technology of the State of Ceará IFCE, in the context of teacher education, and the consideration of elements of a historical, mathematical, and evolutionary nature. Thus, from a perspective of theoretical complementarity involving the research elements derived from the notion of the didactic engineering for development and some assumptions of the French aspect of the professional didactics, two sets of data are discussed. The first set involved research carried out between 2017 and 2020. The second set considered involved studies still under development in Brazil, considering the period of 2020 2023. The historical landscape of investigation rests on considering the recurring number sequences of Fibonacci, Lucas, Pell, Jacobsthal, Coordonier or Padovan, Perrin, Mersenne, Oresme, Naraynna, and Leonardo. Furthermore, in a broad sense, the study aims to provide a learning scenario for the teacher, affected by a perspective of mathematical knowledge evolution, including the repercussions and applications with current technology.
Relationship between sexual harassment at workplace and subjective well-being among working women in South Punjab, Pakistan

Sexual Harassment at workplace (SHW) is a global phenomenon. However, there has been no prior research on the association of SHW and subjective well-being (SWB) of working women in Pakistan. The SWB is an umbrella term that encompasses concepts such as satisfaction with life (SWL) and subjective happiness (SbH). The 200 working women from the public and private sector organizations in Pakistan were recruited randomly. The Sexual Harassment Experience Questionnaire, The Satisfaction with Life Scale, and Subjective Happiness Scale were administered as the main measures. The study met all the ethical considerations. The data was analyzed by the Statistical Package for the Social Sciences and expressed as baseline characteristics, correlation analysis and t tests. There was statistically significant negative relationship of SHW with SWL and SbH in working women. The young age, high school or less education, single marital status, and working in private sector organization were significantly associated with the increased and decreased experience of SHW and SWB respectively. The study recommended the adoption of anti SHW laws by the working sector and the periodic screening of working women for SWB so as to reduce the phenomenon of SHW and enhance the SWL and SbH in working women. Article History Received: March 30, 2021 Last Revised: May 30, 2021 Accepted: June 18, 2021 Published: June 30, 2021