Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved chromatographic separation and characterization of ethanol-soluble wheat proteins

A fraction of oligomeric wheat proteins, ethanol-soluble glutenin (ESG), formerly referred to as high molecular weight (HMW) gliadin, is coextracted with low molecular weight (LMW) monomeric gliadins using 70% ethanol. ESG has several subunits that are apparently identical to LMW-glutenin subunits (40-55 kDa). The cysteine residues of these subunits may be in different locations from those of LMW-monomeric gliadins, and these locations may favor intramolecular cross-linking. This distribution of cysteine residues enables these subunits to form oligomers of two to six subunits, with molecular masses of 80-250 +- 50 kDa. Variation of these polypeptides between wheat cultivars could significantly affect mixing and baking quality. To examine such quantitative and qualitative variation, we extracted defatted flours with 70% ethanol. Solubilized proteins were separated by size-exclusion liquid chromatography into ESG and LMW monomeric gliadins. Amounts of each fraction were determined gravimetrically after lyophilization. Fractions were then analyzed by to flour-quality parameters or wheat class. Carbohydrate and amino acid analyses of fractions were also done. ESG consisted of up to 37% of among cultivars, possibly because of structural differences among proteins.
COVID-19 in Russia: Clinical and Immunological Features of the First-Wave Patients

The coronavirus disease outbreak in 2019 (COVID-19) has now achieved the level of a global pandemic and affected more than 100 million people on all five continents and caused over 2 million deaths. Russia is, needless to say, among the countries affected by SARS-CoV-2, and its health authorities have mobilized significant efforts and resources to fight the disease. The paper presents the result of a functional analysis of 155 patients in the Moscow Region who were examined at the Central Clinical Hospital of the Russian Academy of Sciences during the first wave of the pandemic (February–July, 2020). The inclusion criteria were a positive PCR test and typical, computed tomographic findings of viral pneumonia in the form of ground-glass opacities. A clinical correlation analysis was performed in four groups of patients: (1) those who were not on mechanical ventilation, (2) those who were on mechanical ventilation, and (3) those who subsequently recovered or (4) died. The correlation analysis also considered confounding comorbidities (diabetes, metabolic syndrome, hypertension, etc.). The immunological status of the patients was examined (levels of immunoglobulins of the M, A, G classes and their subclasses, as well as the total immunoglobulin level) using an original SARS-CoV-2 antibody ELISA kit. The ELISA kit was developed using linear S-protein RBD-SD1 and NTD fragments, as well as the N-protein, as antigens. These antigens were produced in the prokaryotic E. coli system. Recombinant RBD produced in the eukaryotic CHO system (RBD CHO) was used as an antigen representing conformational RBD epitopes. The immunoglobulin A level was found to be the earliest serological criterion for the development of a SARS-CoV-2 infection and it yielded the best sensitivity and diagnostic significance of ELISA compared to that of class M immunoglobulin. We demonstrated that the seroconversion rate of “early” N-protein-specific IgM and IgA antibodies is comparable to that of antibodies specific to RBD conformational epitopes. At the same time, seroconversion of SARS-CoV-2 N-protein-specific class G immunoglobulins was significantly faster compared to that of other specific antibodies. Our findings suggest that the strong immunogenicity of the RBD fragment is for the most part associated with its conformational epitopes, while the linear RBD and NTD epitopes have the least immunogenicity. An analysis of the occurrence rate of SARS-CoV-2-specific immunoglobulins of different classes revealed that RBD- and N-specific antibodies should be evaluated in parallel to improve the sensitivity of ELISA. An analysis of the immunoglobulin subclass distribution in sera of seropositive patients revealed uniform induction of N-protein-specific IgG subclasses G1–G4 and IgA subclasses A1–A2 in groups of patients with varying severity of COVID-19. In the case of the S-protein, G1, G3, and A1 were the main subclasses of antibodies involved in the immune response.
Molecular evidence of the avocado defense response to Fusarium kuroshium infection: a deep transcriptome analysis using RNA-Seq

Fusarium kuroshium is a novel member of the Ambrosia Fusarium Clade (AFC) that has been recognized as one of the symbionts of the invasive Kuroshio shot hole borer, an Asian ambrosia beetle. This complex is considered the causal agent of Fusarium dieback, a disease that has severely threatened natural forests, landscape trees, and avocado orchards in the last 8 years. Despite the interest in this species, the molecular responses of both the host and F. kuroshium during the infection process and disease establishment remain unknown. In this work, we established an in vitro pathosystem using Hass avocado stems inoculated with F. kuroshium to investigate differential gene expression at 1, 4, 7 and 14 days post-inoculation. RNA-seq technology allowed us to obtain data from both the plant and the fungus, and the sequences obtained from both organisms were analyzed independently. The pathosystem established was able to mimic Fusarium dieback symptoms, such as carbohydrate exudation, necrosis, and vascular tissue discoloration. The results provide interesting evidence regarding the genes that may play roles in the avocado defense response to Fusarium dieback disease. The avocado data set comprised a coding sequence collection of 51,379 UniGenes, from which 2,403 (4.67%) were identified as differentially expressed. The global expression analysis showed that F. kuroshium responsive UniGenes can be clustered into six groups according to their expression profiles. The biologically relevant functional categories that were identified included photosynthesis as well as responses to stress, hormones, abscisic acid, and water deprivation. Additionally, processes such as oxidation-reduction, organization and biogenesis of the cell wall and polysaccharide metabolism were detected. Moreover, we identified orthologues of nucleotide-binding leucine-rich receptors, and their possible action mode was analyzed. In F. kuroshium, we identified 57 differentially expressed genes. Interestingly, the alcohol metabolic process biological category had the highest number of upregulated genes, and the enzyme group in this category may play an important role in the mechanisms of secondary metabolite detoxification. Hydrolytic enzymes, such as endoglucanases and a pectate lyase, were also identified, as well as some proteases. In conclusion, our research was conducted mainly to explain how the vascular tissue of a recognized host of the ambrosia complex responds during F. kuroshium infection since Fusarium dieback is an ambrosia beetle-vectored disease and many variables facilitate its establishment.
Population density and basic reproductive number of COVID-19 across United States counties

The basic reproductive number (R0) is a function of contact rates among individuals, transmission probability, and duration of infectiousness. We sought to determine the association between population density and R0 of SARS-CoV-2 across U.S. counties. We conducted a cross-sectional analysis using linear mixed models with random intercept and fixed slopes to assess the association of population density and R0, and controlled for state-level effects using random intercepts. We also assessed whether the association was differential across county-level main mode of transportation percentage as a proxy for transportation accessibility, and adjusted for median household income. The median R0 among the United States counties was 1.66 (IQR: 1.35–2.11). A population density threshold of 22 people/km2 was needed to sustain an outbreak. Counties with greater population density have greater rates of transmission of SARS-CoV-2, likely due to increased contact rates in areas with greater density. An increase in one unit of log population density increased R0 by 0.16 (95% CI: 0.13 to 0.19). This association remained when adjusted for main mode of transportation and household income. The effect of population density on R0 was not modified by transportation mode. Our findings suggest that dense areas increase contact rates necessary for disease transmission. SARS-CoV-2 R0 estimates need to consider this geographic variability for proper planning and resource allocation, particularly as epidemics newly emerge and old outbreaks resurge.
Durability of VEGF Suppression With Intravitreal Aflibercept and Brolucizumab: Using Pharmacokinetic Modeling to Understand Clinical Outcomes

Purpose To investigate whether vascular endothelial growth factor (VEGF)–suppression durations contribute to our understanding of clinical trial outcomes by simulating vitreous molar concentrations (Cvm) of intravitreal aflibercept (IVT-AFL) and brolucizumab (IVT-BRO) using pharmacokinetic (PK) modeling. Methods A PK model simulated Cvm after single-dose IVT-AFL, IVT-BRO, and ranibizumab (IVT-RAN), and extrapolated intraocular VEGF-suppression thresholds and durations. Vitreous PK after multidose regimens used in studies of IVT-AFL versus IVT-BRO were simulated and compared with best-corrected visual acuity (BCVA) data. Results Cvm peaked higher (Cmax) and decreased more quickly to the VEGF-suppression threshold and minimum (Cmin) levels with IVT-BRO than with IVT-AFL, consistent with their molar doses calculated using molecular weights and vitreous half-lives (26 kDa and 115 kDa; 4.4–5.1 and 9.1–11 days, respectively). The mean VEGF suppression durations were 71 days for IVT-AFL 2 mg and 51 (48–59) days for IVT-BRO 6 mg. Based on dosing in OSPREY (matched dosing to week [w]32 for both agents; thereafter, IVT-AFL every eight weeks [q8w] and IVT-BRO q12w for the last two doses [w32→w44 and w44→w56]), IVT-BRO showed wider Cmax-Cmin fluctuations than IVT-AFL. The IVT-BRO Cmin fell below the VEGF-suppression threshold at timepoints near w56, when decreases in BCVA were also observed. The IVT-AFL vitreous Cmin remained above the suppression threshold through w56, where BCVA gains were maintained. Conclusions The PK-modeled mean VEGF-suppression duration for IVT-BRO was substantially shorter than that published for IVT-AFL and may not be sufficient to effectively suppress VEGF throughout q12w dosing. Translational Relevance The PK modeling suggests that more patients may be maintained on ≥q12w dosing with IVT-AFL than with IVT-BRO.
Intraspecific morphological variation of Bellidiastrum michelii (Asteraceae) along a 1,155 m elevation gradient in the Tatra Mountains

Plant species that inhabit large elevation gradients in mountain regions are exposed to different environmental conditions. These different conditions may influence plant morphology via plastic responses and/or via genetic adaptation to the local environment. In this study, morphological variation was examined for Bellidiastrum michelii Cass. (Asteraceae) plants growing along a 1,155 m elevation gradient in the Tatra Mountains in Central Europe. The aim was to contribute to gaining a better understanding of within-species morphological variation in a mountain species across elevation gradients. Twelve morphological traits, which were measured for 340 plants collected from 34 sites, were plotted against elevation using Generalised Additive Models. Significant variation in B. michelii morphology was found across the elevation gradient. Plant size, in the form of plant height, total aboveground mass and total leaf mass, decreased significantly with increasing elevation. Similarly, floral traits, such as flower head mass, total flower mass, individual flower mass, flower head diameter and ligulate and tubular flower length, also decreased significantly with increasing elevation. However, the changes in these floral traits were not as large as those observed for plant size traits. Interestingly, the number of flowers produced by the plant, both ligulate and tubular, did not change across the studied elevation gradient. In this study, elevation was found to be an important gradient across which significant intraspecific morphological variation occurred in a mountain plant. These morphological changes may have occurred in response to various abiotic and biotic factors that change along elevation gradients.
Designing an e-learning tool to support health practitioners caring for patients taking multiple medications

Background: Population ageing and improvements in healthcare mean the number of people living with two or more chronic conditions, or ‘multimorbidity’, is rapidly increasing. This presents a challenge to current disease-specific care delivery models. Adherence to prescribed medications appears particularly challenging for individuals living with multimorbidity, given the often-complex drug regimens required to treat multiple conditions. Poor adherence is associated with increased mortality, as well as wasted healthcare resources. Supporting medication adherence is a key priority for general practitioners (GPs) and practice nurses as they are responsible for much of the disease counselling and medication prescribing associated with chronic illnesses. Despite this, practical resources and training for health practitioners on how to promote adherence in practice is currently lacking. Informed by the principles of patient and public involvement (PPI), the aim of this research was to develop a patient informed e-learning resource to help GPs and nurses support medication adherence. Method: Utilising collective intelligence (CI) and scenario-based design (SBD) methodology, input was gathered from key stakeholders in medication adherence to gain insights into barriers to supporting people with multimorbidity who are receiving polypharmacy, strategies for overcoming these barriers, and user needs and requirements to inform the design of the e-learning tool. Results: In total, 67 barriers to supporting people who are taking multiple medications were identified across 8 barrier categories. 162 options for overcoming the identified barriers were then generated. This data was used in the design of a flexible e-learning tool for continuous professional development, that has been integrated into general practice and clinical education programmes as a supportive tool. Conclusions: Using CI and SBD methodology was an effective way of facilitating collaboration, idea-generation, and the co-creation of design solutions amongst a diverse group of stakeholders. This approach could be usefully applied to address other complex healthcare-related challenges.
MicroRNA Biomarkers of High-Grade Cervical Intraepithelial Neoplasia in Liquid Biopsy

New prevention strategies are needed to detect cervical intraepithelial neoplasia (CIN). The microRNA expression analysis has already been reported as molecular biomarkers in the early detection of cervical cancer (CC) through minimally invasive samples, such as liquid biopsy, obtained through collection using liquid-based cytology (LBC). In this study, we aimed to identify molecular signatures of microRNAs in cervical precursor lesions from LBC cervical and the molecular pathways potentially associated with the CC progression. We analyzed 31 LBC cervical samples from women who underwent colposcopy. These samples were divided into two groups: the first group was composed of samples without precursor lesions of CC, considering the control group, referred to as healthy female subjects (HFS; n = 11). The second group corresponded to women diagnosed with cervical interepithelial neoplasia grade 3 (CIN 3; n = 20). We performed microRNA and gene expression profiling using the nCounter® miRNA Expression Assays (NanoString Technology) and PanCancer Pathways (NanoString Technology), respectively. A microRNA target prediction was performed by mirDIP, and molecular pathway interaction was constructed using Cytoscape. Bidirectional in silico analyses and Pearson's correlation were performed for associated the relation between genes, and miRNAs differentially expressed related cervical cancer progression were performed. We found that the expression of nine microRNAs was significantly higher, two were downregulated (miR-381-3p and miR-4531), and seven miRNAs were upregulated (miR-205-5p, miR-130a-3p, miR-3136-3p, miR-128-2-5p, let-7f-5p, miR-202-3p, and miR-323a-5p) in CIN 3 (fold change ≥ 2 and p ≤ 0.05). The miRNA expression patterns were independent of hr-HPV infection. We identified four miRNAs (miR-205-5p, miR-130a-3p, miR-4531, and miR-381-3p) that could be used as biomarkers for CIN 3 in LBC samples through multiple logistic regression analyses. We found 16 genes differentially expressed between CIN 3 and HSF samples (fold change ≥ 2 and p ≤ 0.05). We found the correlation between miR-130a-3p and CCND1(R = −0.52; p = 0.0029), miR-205-5p and EGFR (R = 0.53; p = 0.0021), and miR-4531 and SMAD2 (R = −0.54; p = 0.0016). In addition, we demonstrated the most significant pathways of the targets associated with cervical cancer progression (FDR-corrected p < 0.001). This study demonstrated that miRNA biomarkers may distinguish healthy cervix and CIN 3 and regulate important molecular pathways of carcinogenesis.
Current COVID-19 treatments: Rapid review of the literature

Background As SARS-CoV-2 continues to spread worldwide, it has already resulted in over 110 million cases and 2.5 million deaths. Currently, there are no effective COVID-19 treatments, although numerous studies are under way. SARS-CoV-2, however, is not the first coronavirus to cause serious outbreaks. COVID-19 can be compared with previous human coronavirus diseases, such as Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), to better understand the development of treatments. Methods Databases Medline, Embase and WHO COVID-19 was systematically searched on 9 February 2021 for studies reporting on therapeutic effect of COVID-19 treatments. Clinical trials, case reports, observational studies and systematic reviews in the English language were eligible. Results 1416 studies were identified and 40 studies were included in this review. Therapies included are: remdesivir, convalescent plasma, hydroxychloroquine, lopinavir/ ritonavir, interferon, corticosteroids, cytokine storm inhibitors and monoclonal antibodies. Remdesivir, convalescent plasma and interferon seems to provide some clinical benefits such as faster recovery time and reduced mortality, but these effects are not clinically significant. Some corticosteroids are effective in reducing mortality in severe COVID-19 patients. Hydroxychloroquine do not convey any beneficial, and therapies such as cytokine storm inhibitors and monoclonal antibodies were also not effective and require further investigation. Conclusions There is no single therapy effective against COVID-19. However, a combination of therapies administered at different stages of infection may provide some benefit. This conclusion is reflected in the limited effects of these treatments in previous human coronaviruses.
Active-Ingredient Screening and Synergistic Action Mechanism of Shegan Mixture for Anti-Asthma Effects Based on Network Pharmacology in a Mouse Model of Asthma

Background Shegan Mixture (SGM) is a traditional Chinese medicine that has anti-inflammatory and therapeutic effects on asthma. However, its active ingredients and combined action mechanism have not been fully elucidated so far. The purpose of this study was to screen the effective ingredients and targets and elucidate the synergistic action mechanism of SGM in asthma mice using the network pharmacological approach. Methods A mouse model of asthma model was used in this study. Mice were orally administered SGM at three doses for 4 weeks and the effect of SGM on asthma was evaluated. The active ingredients and their targets of SGM were identiﬁed by searching databases, such as Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). The main active ingredients were selected with parameters OB and DL. The synergistic action mechanisms of SGM in asthma were studied through key active ingredient-target interaction network and verified using surface plasmon resonance assay (SPR). Results SGM exerts anti-asthmatic effects by reducing lung tissue damage and inflammatory factors (IFN-γ, IL-4, IL-5, and IL-13) in asthmatic mice. Twenty ingredients and 45 related proteins were selected as potential nodes using enrichment analysis and network analysis. Inflammation and smooth muscle regulation-related pathways were considered to be the main pharmacological mechanisms of SGM in the treatment of asthma. Especially, 5 molecule-target pairs (including 3 ingredients and 4 proteins) were well docked with each other and the SPR assay revealed that glabridin-PTGS2 had good binding with 44.5 μM Kd value. Conclusion SGM exerts the synergistic anti-asthma effects by virtue of reducing lung-tissue damage and inflammatory factors in asthmatic mice, which explains the theoretical basis for the traditional Chinese medicine, SGM, to treat asthma. Our study thus sheds light on a variety of options including Chinese medicine that could potentially be used in the clinical treatment of asthma.
Diabetic Retinopathy Detection Using Local Extrema Quantized Haralick Features with Long Short-Term Memory Network

Diabetic retinopathy is one of the leading diseases affecting eyes. Lack of early detection and treatment can lead to total blindness of the diseased eyes. Recently, numerous researchers have attempted producing automatic diabetic retinopathy detection techniques to supplement diagnosis and early treatment of diabetic retinopathy symptoms. In this manuscript, a new approach has been proposed. The proposed approach utilizes the feature extracted from the fundus image using a local extrema information with quantized Haralick features. The quantized features encode not only the textural Haralick features but also exploit the multiresolution information of numerous symptoms in diabetic retinopathy. Long Short-Term Memory network together with local extrema pattern provides a probabilistic approach to analyze each segment of the image with higher precision which helps to suppress false positive occurrences. The proposed approach analyzes the retina vasculature and hard-exudate symptoms of diabetic retinopathy on two different public datasets. The experimental results evaluated using performance matrices such as specificity, accuracy, and sensitivity reveal promising indices. Similarly, comparison with the related state-of-the-art researches highlights the validity of the proposed method. The proposed approach performs better than most of the researches used for comparison.