Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Estimation of Winter Wheat Nitrogen Status Using Random Forest by Integrating Multi-Source Data Across Different Agro-Ecological Zones

Timely and accurate estimation of plant nitrogen (N) status is crucial to the successful implementation of precision N management. It has been a great challenge to non-destructively estimate plant N status across different agro-ecological zones (AZs). The objective of this study was to use random forest regression (RFR) models together with multi-source data to improve the estimation of winter wheat (Triticum aestivum L.) N status across two AZs. Fifteen site-year plot and farmers' field experiments involving different N rates and 19 cultivars were conducted in two AZs from 2015 to 2020. The results indicated that RFR models integrating climatic and management factors with vegetation index (R2 = 0.72–0.86) outperformed the models by only using the vegetation index (R2 = 0.36–0.68) and performed well across AZs. The Pearson correlation coefficient-based variables selection strategy worked well to select 6–7 key variables for developing RFR models that could achieve similar performance as models using full variables. The contributions of climatic and management factors to N status estimation varied with AZs and N status indicators. In higher-latitude areas, climatic factors were more important to N status estimation, especially water-related factors. The addition of climatic factors significantly improved the performance of the RFR models for N nutrition index estimation. Climatic factors were important for the estimation of the aboveground biomass, while management variables were more important to N status estimation in lower-latitude areas. It is concluded that integrating multi-source data using RFR models can significantly improve the estimation of winter wheat N status indicators across AZs compared to models only using one vegetation index. However, more studies are needed to develop unmanned aerial vehicles and satellite remote sensing-based machine learning models incorporating multi-source data for more efficient monitoring of crop N status under more diverse soil, climatic, and management conditions across large regions.
Hydrographic Feature Variation Caused Pronounced Differences in Planktonic Ciliate Community in the Pacific Arctic Region in the Summer of 2016 and 2019

Planktonic ciliates are an important component of microzooplankton, but there is limited understanding of their responses to changing environmental conditions in the Pacific Arctic Region. We investigated the variations of ciliate community structure and their relationships with environmental features in the Pacific Arctic Region in the summer of 2016 and 2019. The Pacific water was warmer and more saline in 2019 than in 2016. The abundance and biomass of total ciliate and aloricate ciliate were significantly higher in 2019 than those in 2016, while those of tintinnid were significantly lower. The dominant aloricate ciliate changed from large size-fraction (> 30 μm) in 2016 to small size-fraction (10–20 μm) in 2019. More tintinnid species belonging to cosmopolitan genera were found in 2019 than in 2016, and the distribution of tintinnid species (Codonellopsis frigida, Ptychocylis obtusa, and Salpingella sp.1) in 2019 expanded by 5.9, 5.2, and 8.8 degrees further north of where they occurred in 2016. The environmental variables that best-matched tintinnid distributions were temperature and salinity, while the best match for aloricate ciliate distributions was temperature. Therefore, the temperature might play a key role in ciliate distribution. These results provide basic data on the response of the planktonic ciliate community to hydrographic variations and implicate the potential response of microzooplankton to Pacification as rapid warming progresses in the Pacific Arctic Region.
Antibody-Mediated LILRB2-Receptor Antagonism Induces Human Myeloid-Derived Suppressor Cells to Kill Mycobacterium tuberculosis

Tuberculosis is a leading cause of death in mankind due to infectious agents, and Mycobacterium tuberculosis (Mtb) infects and survives in macrophages (MФs). Although MФs are a major niche, myeloid-derived suppressor cells (MDSCs) are an alternative site for pathogen persistence. Both MФs and MDSCs express varying levels of leukocyte immunoglobulin-like receptor B (LILRB), which regulate the myeloid cell suppressive function. Herein, we demonstrate that antagonism of LILRB2 by a monoclonal antibody (mab) induced a switch of human MDSCs towards an M1-macrophage phenotype, increasing the killing of intracellular Mtb. Mab-mediated antagonism of LILRB2 alone and its combination with a pharmacological blockade of SHP1/2 phosphatase increased proinflammatory cytokine responses and phosphorylation of ERK1/2, p38 MAPK, and NF-kB in Mtb-infected MDSCs. LILRB2 antagonism also upregulated anti-mycobacterial iNOS gene expression and an increase in both nitric oxide and reactive oxygen species synthesis. Because genes associated with the anti-mycobacterial function of M1-MФs were enhanced in MDSCs following mab treatment, we propose that LILRB2 antagonism reprograms MDSCs from an immunosuppressive state towards a pro-inflammatory phenotype that kills Mtb. LILRB2 is therefore a novel therapeutic target for eradicating Mtb in MDSCs.
The Association Between Route of Post-menopausal Estrogen Administration and Blood Pressure and Arterial Stiffness in Community-Dwelling Women

Background Postmenopausal hormone therapy (HT) is associated with increased cardiovascular risk. Although the route of estrogen administration may play a role in mediating risk, previous studies have not controlled for concomitant progestin use. Objective To investigate the association between the route of estrogen therapy (oral or non-oral) HT use, without concomitant progestin, and blood pressure and arterial stiffness in postmenopausal women. Methods Systolic blood pressure [SBP], diastolic blood pressure [DBP]), arterial stiffness (aortic pulse wave velocity [aPWV] and augmentation index at 75 beats per minute [AIx]) were measured using a validated automated brachial cuff-based oscillometric approach (Mobil-O-Graph) in a community-dwelling sample of 328 women. Results Fifty-five participants (16.8%) were ever users (current and past use) of estrogen-only HT (oral [n = 16], transdermal [n = 20], vaginal [n = 19]), and 223 were never HT users (control). Ever use of oral estrogen was associated with increased SBP and DBP (Oral: SBP: 137 ± 4 mmHg, DBP: 79 ± 2 mmHg) compared to use of non-oral estrogen (transdermal: SBP: 118 ± 2 mmHg, DBP: 73 ± 1 mmHg; p < 0.01 & p = 0.012, respectively; vaginal: SBP: 123 ± 2 mmHg DBP: 73 ± 2 mmHg; p = 0.02 & p = 0.01, respectively.) and controls (SBP: 124 ± 1 mmHg, DBP: 74 ± 1 mmHg, p = 0.03, p = 0.02, respectively) after adjustment for covariates. aPWV was higher in oral estrogen ever users (9.9 ± 1 m/s) compared to non-oral estrogen (transdermal: 8.6 ± 0.3 m/s, p < 0.01; vaginal: 8.8 ± 0.7 m/s, p = 0.03) and controls (8.9 ± 0.5 m/s, p = 0.03) but these associations were no longer significant after adjustment for covariates. AIx was higher in oral estrogen (29 ± 2 %) compared to non-oral estrogen (transdermal: 16 ± 2 %; vaginal: 22 ± 1.7 %) but this association was no longer significant after adjustment for covariates (p = 0.92 vs. non-oral; p = 0.74 vs. control). Conclusion Ever use of oral estrogen was associated with increased SBP and DBP compared to non-oral estrogen use and no use. Given the cardiovascular risk associated with both menopause and increased blood pressure, further studies are required exploring the potential benefits of non-oral estrogen in postmenopausal women.
The Impact of Financial Literacy on Entrepreneurial Intention: The Mediating Role of Saving Behavior

This study explored the impact of financial literacy (financial awareness) on potential entrepreneurs' intent in Saudi Arabia. It also examined saving behavior as a mediator in the relationship between financial literacy and entrepreneurial intention. The study's data were collected by an online questionnaire sent to a sample of 270 potential entrepreneurs at Abqaiq Applied College, affiliated with King Faisal University. Data analysis was done using partial least squares structural equation modeling (PLS-SEM). According to the findings, there is no direct relationship between financial literacy and entrepreneurial intent. However, it has been reported that saving behavior can mediate between financial literacy and entrepreneurial intent.
Serum Proteomic Analysis Identifies SAA1, FGA, SAP, and CETP as New Biomarkers for Eosinophilic Granulomatosis With Polyangiitis

Background Eosinophilic granulomatosis with polyangiitis (EGPA) is characterized by asthma-like attacks in its early stage, which is easily misdiagnosed as severe asthma. Therefore, new biomarkers for the early diagnosis of EGPA are needed, especially for differentiating the diagnosis of asthma. Objectives To identify serum biomarkers that can be used for early diagnosis of EGPA and to distinguish EGPA from severe asthma. Method Data-independent acquisition (DIA) analysis was performed to identify 45 healthy controls (HC), severe asthma (S-A), and EGPA patients in a cohort to screen biomarkers for early diagnosis of EGPA and to differentiate asthma diagnosis. Subsequently, parallel reaction monitoring (PRM) analysis was applied to a validation cohort of 71 HC, S-A, and EGPA patients. Result Four candidate biomarkers were identified from DIA and PRM analysis—i.e., serum amyloid A1 (SAA1), fibrinogen-α (FGA), and serum amyloid P component (SAP)—and were upregulated in the EGPA group, while cholesteryl ester transfer protein (CETP) was downregulated in the EGPA group compared with the S-A group. Receiver operating characteristics analysis shows that, as biomarkers for early diagnosis of EGPA, the combination of SAA1, FGA, and SAP has an area under the curve (AUC) of 0.947, a sensitivity of 82.35%, and a specificity of 100%. The combination of SAA1, FGA, SAP, and CETP as biomarkers for differential diagnosis of asthma had an AUC of 0.921, a sensitivity of 78.13%, and a specificity of 100%, which were all larger than single markers. Moreover, SAA1, FGA, and SAP were positively and CETP was negatively correlated with eosinophil count. Conclusion DIA-PRM combined analysis screened and validated four previously unexplored but potentially useful biomarkers for early diagnosis of EGPA and differential diagnosis of asthma.
A Neuropsychological Rehabilitation Framework to Address Cognitive and Neurobehavioral Impairments After Strokes to the Anterior Communicating Artery

Patients with strokes to the Anterior Communicating Artery (ACoA) pose an important challenge to rehabilitation teams due to a particular mix of cognitive and behavioral impairments (anosognosia, anterograde amnesia, prospective memory problems, and executive dysfunction). These deficits often compromise engagement with rehabilitation, learning and generalization. The goal of this article is to describe the long-term presentation of a patient with an ACoA stroke (Mrs. B, a 60-year-old electric engineer) as well as her rehabilitation needs and the many challenges experienced by the rehabilitation team when attempting to facilitate functional, vocational and psychosocial recovery. Based on this case, and the existing literature, a neuropsychological rehabilitation framework to understand and address the specific problems and needs of this population is proposed. This framework demands rehabilitation teams to consider: the slow pattern of recovery of this population, the interaction between cognitive and behavioral impairments, the relevance of physical and social environments, the value of personal projects and the need to include psychological and relational interventions.
Identifying Alcohol Use Disorder With Resting State Functional Magnetic Resonance Imaging Data: A Comparison Among Machine Learning Classifiers

Alcohol use disorder (AUD) is a burden to society creating social and health problems. Detection of AUD and its effects on the brain are difficult to assess. This problem is enhanced by the comorbid use of other substances such as nicotine that has been present in previous studies. Recent machine learning algorithms have raised the attention of researchers as a useful tool in studying and detecting AUD. This work uses AUD and controls samples free of any other substance use to assess the performance of a set of commonly used machine learning classifiers detecting AUD from resting state functional network connectivity (rsFNC) derived from independent component analysis. The cohort used included 51 alcohol dependent subjects and 51 control subjects. Despite alcohol, none of the 102 subjects reported use of nicotine, cannabis or any other dependence or habit formation substance. Classification features consisted of whole brain rsFNC estimates undergoing a feature selection process using a random forest approach. Features were then fed to 10 different machine learning classifiers to be evaluated based on their classification performance. A neural network classifier showed the highest performance with an area under the curve (AUC) of 0.79. Other good performers with similar AUC scores were logistic regression, nearest neighbor, and support vector machine classifiers. The worst results were obtained with Gaussian process and quadratic discriminant analysis. The feature selection outcome pointed to functional connections between visual, sensorimotor, executive control, reward, and salience networks as the most relevant for classification. We conclude that AUD can be identified using machine learning classifiers in the absence of nicotine comorbidity.
Hallmarks of Severe COVID-19 Pathogenesis: A Pas de Deux Between Viral and Host Factors

Two years into Coronavirus Disease 2019 (COVID-19) pandemic, a comprehensive characterization of the pathogenesis of severe and critical forms of COVID-19 is still missing. While a deep dysregulation of both the magnitude and functionality of innate and adaptive immune responses have been described in severe COVID-19, the mechanisms underlying such dysregulations are still a matter of scientific debate, in turn hampering the identification of new therapies and of subgroups of patients that would most benefit from individual clinical interventions. Here we review the current understanding of viral and host factors that contribute to immune dysregulation associated with COVID-19 severity in the attempt to unfold and broaden the comprehension of COVID-19 pathogenesis and to define correlates of protection to further inform strategies of targeted therapeutic interventions.
High-Density Mapping of Quantitative Trait Loci Controlling Agronomically Important Traits in Quinoa (Chenopodium quinoa Willd.)

Quinoa is a pseudocereal originating from the Andean regions. Despite quinoa’s long cultivation history, genetic analysis of this crop is still in its infancy. We aimed to localize quantitative trait loci (QTL) contributing to the phenotypic variation of agronomically important traits. We crossed the Chilean accession PI-614889 and the Peruvian accession CHEN-109, which depicted significant differences in days to flowering, days to maturity, plant height, panicle length, and thousand kernel weight (TKW), saponin content, and mildew susceptibility. We observed sizeable phenotypic variation across F2 plants and F3 families grown in the greenhouse and the field, respectively. We used Skim-seq to genotype the F2 population and constructed a high-density genetic map with 133,923 single nucleotide polymorphism (SNPs). Fifteen QTL were found for ten traits. Two significant QTL, common in F2 and F3 generations, depicted pleiotropy for days to flowering, plant height, and TKW. The pleiotropic QTL harbored several putative candidate genes involved in photoperiod response and flowering time regulation. This study presents the first high-density genetic map of quinoa that incorporates QTL for several important agronomical traits. The pleiotropic loci can facilitate marker-assisted selection in quinoa breeding programs.
Processing Attenuating NPIs in Indicative and Counterfactual Conditionals

Both indicative and counterfactual conditionals are known to be licensing contexts for negative polarity items (NPIs). However, a recent theoretical account suggests that the licensing of attenuating NPIs like English all that in the conditional antecedent is sensitive to pragmatic differences between various types of conditionals. We conducted three behavioral experiments in order to test key predictions made by that proposal. In Experiment 1, we tested hypothetical indicative and counterfactual conditionals with the English NPI all that, finding that the NPI is degraded in the former compared to the latter. In Experiment 2, we compared hypothetical indicative conditionals and premise conditionals with the same NPI, again finding a degradation only for the former. Both results align with theoretically derived predictions purporting that hypothetical indicative conditionals are degraded due to their susceptibility to conditional perfection. Finally, Experiment 3 provides empirical evidence that comprehenders readily strengthen counterfactual conditionals to biconditionals, in line with theoretical analyses that assume that conditional perfection and counterfactual inferences are compatible. Their ability to still host attenuating NPIs in the conditional antecedent, by contrast, falls into place via the antiveridical inference to the falsity of the antecedent. Altogether, our study sheds light on the interplay between NPI licensing and the semantic and pragmatic properties of various types of conditionals. Moreover, it provides a novel perspective on the processing of different kinds of conditionals in context, in particular, with regard to their (non)veridicality properties.
The Effects of Combined Verbal Encouragement and Technical Instruction on Technical Skills and Psychophysiological Responses During Small-Sided Handball Games Exercise in Physical Education

To examine the effects of combined positive verbal encouragement and general technical guidelines on technical and psychophysiological parameters in pupils during a small-sided handball passing game. Twenty secondary school pupils (age, 16 ± 1 years; body mass, 55.3 ± 6.6 kg; body height, 1.77 ± 0.13 m; BMI, 22.6 ± 2.2 kg m−1) performed small-sided games (2 × 10 min) with three conditions: small-sided game (1) with combined verbal encouragement and technical instruction; (2) with technical instruction; (3) without any instruction (control) in which the passes for each pupil in each set was measured together with the rate of perceived exertion (RPE) and feeling mood after the first and second set. Results: A two-way analysis of variance demonstrated that the combined condition resulted in more passes compared to the technical instruction and control conditions, while the number of passes increased in set 2 for all conditions. RPE and the feeling mood were also differently between the conditions. Combined verbal encouragement and technical instruction during handball exercise were more beneficial for optimal passing numbers, positive mood with less perception of physical effort compared to only technical instruction and a control condition. The results evidenced positive acute effects of combined verbal encouragement and technical instruction during handball, indicating the usefulness of these training methods for optimal passing numbers, positive mood with less perception of physical effort in physical education pupils. Future studies should evaluate the applicability combined verbal encouragement and technical skills in the training of other conditioning capacities and the individual responsiveness of players toward verbal encouragement tasks.
Association of Self-Leadership With Acute Stress Responses and Acute Stress Disorders in Chinese Medics During the COVID-19 Pandemic: A Cross-Sectional Study

Background The outbreak of the highly infectious coronavirus disease 2019 (COVID-19) renders a huge physical and psychological risk to the public, especially to the medics. Additionally, self-leadership has proven to improve self-efficacy and mediate tension, such as nervousness and depression. Therefore, a cross-sectional survey was conducted to explore the association of self-leadership with acute stress responses (ASRs) and acute stress disorders (ASDs) in medics during the COVID-19 epidemic. Methods Self-reported online questionnaires were administered, and 627 participants were finally included. The data were analyzed using the univariate analysis and the logistical regression model to identify whether self-leadership and sociodemographic and epidemic characteristics were associated with mental health, including ASRs and ASDs. Results Initially, 790 medics responded. Of these, 627 remained after excluding for invalid questionnaires and those with a substantial amount of missing data. Therefore, the participation validity rate was 79.37%. Frontline medical staff (β = 0.338; p < 0.001), possibility of infection among people around the medic being mild (β = 0.141; p < 0.001), subjective estimation of epidemic duration being 3–6 months (β = 0.074; p < 0.05), self-sets (β = −0.022; p < 0.001), self-punishment (β = 0.229; p < 0.001), belief hypothesis and evaluation (β = −0.147; p < 0.05), and successful foresight (β = 0.105; p < 0.05) were statistically significant with ASRs. Marital status [adjusted odds ratio (AOR) =1.813; 95% CI (1.141, 2.881); p = 0.012], being a frontline worker [AOR = 25.760; 95% CI (14.220, 46.667); p < 0.001], visiting Hubei in the previous 14 days [AOR = 3.656; 95% CI (1.500, 8.911); p = 0.004], self-punishment [AOR = 1.352; 95% CI (1.180, 1.548); p < 0.001], and self-dialogue [AOR = 1.256; 95% CI (11.063, 1.483); p = 0.007] were the risk factors for ASD. Conversely, having frontline medical staff in one's family [AOR = 0.523; 95% CI (0.297, 0.923); p = 0.025], self-sets [AOR = 0.814; 95% CI (0.715, 0.826); p = 0.002], and belief hypothesis and evaluation [AOR = 0.796; 95% CI (0.672, 0.943); p = 0.038] were the protective factors. Conclusion The special working environment of the COVID-19 epidemic resulted in ASR and ASD. Notably, findings revealed a positive association between ASR symptoms and frontline medical staff, the subjective estimation of epidemic duration, self-punishment, and successful foresight. Nevertheless, marital status, having visited Hubei in the previous 14 days, and self-dialogue were the risk factors accounting for ASD symptoms. Surprisingly, having frontline medical staff in one's family, self-sets, and belief hypothesis and evaluation had potential benefits for ASD symptoms.