Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal prescribing of drugs to prevent CVD and drugs that cause dependency: an evidence gap map

Rationale The early detection of risk factors for cardiovascular disease (CVD) and initiation of preventative treatment is a key part of the NHS Long Term Plan The prescribing of statins (and antihypertensives) is recommended as an effective measure to prevent CVD However evidence suggests that both the prescribing of statins and the taking of prescribed statins, are not at optimal levels It is essential to understand the factors influencing the prescription and taking of statins throughout the patient pathway in order to achieve optimisation Drugs that may cause dependency (DCD), such as benzodiazepines, z-drugs, gabapentinoids and opioids are prescribed to 1 in 4 adults in the UK Evidence suggests that many patients have been taking DCD beyond the short periods for which they are licensed Addiction to DCD is a priority area for reform, with a required focus on prescribing (and deprescribing) practices It is essential to understand the factors which may influence the prescription, review and withdrawal of DCD A systematic review is required which synthesises evidence about factors influencing the optimal prescribing and/or taking of DCD and drugs to prevent CVD. However, scoping of the literature in this area reveals an array of systematic reviews covering aspects of the overarching topic of interest. Prior to conducting a systematic review and synthesis of evidence to understand the factors that influence the prescription and/or taking of drugs to prevent CVD and DCD, there is a need to clarify the state of the systematic review evidence in the area by the production of an evidence gap map.
RNAlign2D – a rapid method for combined RNA structure and sequence-based alignment using a pseudo-amino acid substitution matrix

Background The functions of RNA molecules are mainly determined by their secondary structures. These functions can also be predicted using bioinformatic tools that enable the alignment of multiple RNAs to determine functional domains and/or classify RNA molecules into RNA families. However, the existing multiple RNA alignment tools, which use structural information, are slow in aligning long molecules and/or a large number of molecules. Therefore, a more rapid tool for multiple RNA alignment may improve the classification of known RNAs and help to reveal the functions of newly discovered RNAs. Results Here, we introduce an extremely fast Python-based tool called RNAlign2D. It converts RNA sequences to pseudo-amino acid sequences, which incorporate structural information, and uses a customizable scoring matrix to align these RNA molecules via the multiple protein sequence alignment tool MUSCLE. Conclusions RNAlign2D produces accurate RNA alignments in a very short time. The pseudo-amino acid substitution matrix approach utilized in RNAlign2D is applicable for virtually all protein aligners.
Evaluation of Genomic DNA-Extraction Methods for Molecular Analysis of Solanecio biafrae

ABSTRACT Solanecio biafrae (Oliv. & Hiern) C. Jеffrеу, an indigenous vegetable of the humid tropics, is rich in minerals and easy to cultivate, but its vegetative growth is slow, making production fall short of demand. An efficient and effective genomic DNA-extraction method is necessary for a comprehensive molecular analysis to increase leaf yield and further improve proximate and mineral contents of the vegetable. Cetyltrimethylammonium bromide (CTAB), sodium dodecyl sulfate (SDS), and Qiagen kit (QIAGEN) methods were evaluated for extraction of genomic DNA from young leaves suitable for PCR amplification for molecular analyses. Quantity and quality of the DNA were examined spectrophotometerically and with gel electrophoresis. Amplification of the DNA by PCR for molecular analysis was assessed with five inter-simple sequence repeat (ISSR) primers. The mean DNA yield using QIAGEN, CTAB, and SDS methods were 71.0, 35.4, and 38.8 µg∙µL−1∙g−1 of tissue, respectively. The mean 260/280 nm ratios of QIAGEN, CTAB, and SDS were 1.84, 1.83, and 1.79, respectively. Gel electrophoresis indicated presence of DNA free of contaminants in all samples using three methods. A total of 270 distinct bands were produced by five ISSR primers with similar patterns among three DNA-extraction methods, ranging from 200–2900 base pairs. Three methods are capable of extracting adequate genomic DNA suitable for PCR amplification. The QIAGEN method produced the highest DNA yield, which was of the same quality with DNA obtained using CTAB and SDS methods.
Biophysical insights into the regulatory and DNA-binding mechanisms of the eukaryotic transcription factors Pax5 and Ets1

Transcription factors are proteins that bind at promoter and enhancer sites to regulate gene expression. In this thesis, I used NMR spectroscopy and other methods to investigate the structural and biophysical basis of DNA binding by two eukaryotic transcription factors that are crucial in the development of lymphocytes, Pax5 and Ets1. In chapter 2, I describe how the two subdomains comprising the bipartite DNA-binding Paired domain of Pax5 cooperate to mediate transcriptional regulation. The N-terminal subdomain recognizes DNA sequences in a highly specific manner, whereas the C-terminal subdomain shows little sequence discrimination. The more rigid C-terminal subdomain binds DNA primarily though non-specific electrostatic interactions. In contrast, association with specific DNAs by the dynamic N-terminal subdomain involves relatively large and compensating changes in enthalpy and entropy that point to structural rearrangements upon binding. I propose that the distinct behaviors of the subdomains allow the Pax5 protein to rapidly scan non-specific genomic DNA while retaining specificity for functional regulatory sites. In chapter 3, I expand our understanding of the structural and thermodynamic basis of Ets1 autoinhibition. Previously it was reported that an intrinsically disordered serine-rich region (SRR) interacts transiently with the adjacent ETS domain to attenuate DNA binding. Although forming a dynamic fuzzy complex, I was able to use NMR spectroscopy and X-ray crystallography to provide a detailed mechanism for this inhibitory interaction. In particular, I exploited a trans peptide system to show that the SRR uses a combination of electrostatic and hydrophobic-driven interactions to sterically block the ETS domain DNA-binding interface. I also show how phosphorylation of the SRR strengthens its association with the ETS domain. Altogether, these results explain how the activity of Ets1 is regulated at the level of DNA binding through post-translational modifications that impinge upon the SRR.
Investigating the role of transcription factors ust1 and med1 in mating, pathogenicity and sporulation of Ustilago maydis

by NADIA CHACKO (Under the Direction of Scott Gold) ABSTRACT The plant pathogenic fungus Ustilago maydis is a model organism for the study of obligate pathogenesis. Mating, dimorphic switch, growth in planta and sporulation of U. maydis are areas of considerable interest in the context of study of pathogenicity of this fungus. In the work presented here, two transcription factors ust1 and med1 involved in these vital processes in the life cycle of U. maydis, were studied. Transcription factors ust1 and med1 are orthologs of conidiation regulators stuA and medA genes of Aspergillus nidulans. The role of Ust1 in regulation of genes differentially expressed during saprobic budding growth of U. maydis was studied using a reverse genetic approach. Several potential targets of Ust1 were identified in an earlier study of genes differentially expressed during budding growth of U. maydis. Deletion studies indicate that these genes are dispensable for mating, pathogenicity and budding growth. One exception was the thi1 gene, which was auxotrophic for thiamine in culture but dispensable for mating and pathogenicity.
Defect detection of automotive injector valve seat based on feature fusion

Automobile fuel injector seat is a device that injects gasoline into the automobile cylinder. It plays a very important role in the control of automobile fuel quantity. However, due to the small parts and susceptibility to processing technology, in the production process of automobile fuel injector seats, it is inevitable to leave scratches, defects, rust spots, white spots and other defects. This paper will use the depth detection technology to complete the flaw detection of the injector seat, the depth detection algorithm model Faster R-CNN is improved. Defect detection can be seen that when extracting features, the Faster R-CNN algorithm model only uses the features of the last layer of convolution output, and has a large loss and affects the effect of small target detection. In order to improve the detection ability and solve the problem of missing detection caused by multi-scale and small targets, we introduce the idea of multi feature fusion in the stage of feature network extraction, and compares the improved algorithm model with the original Faster R-CNN model on the data set of injector seat. It is found that the improved model can be better applied to the flaw detection of automobile injector seats.
Visualizing BDNF cell-to-cell transfer reveals astrocytes are the primary recipient of neuronal BDNF

Brain-derived neurotrophic factor (BDNF) is essential for neuronal growth, differentiation, and synaptic plasticity. Although the release and effects of BDNF have been well-studied separately, the transfer of BDNF between cells has not been investigated. Using a four-fluorophore imaging approach to identify both the cell of origin and target cells, we quantified the transfer of BDNF. Surprisingly, we found that astrocytes are the main recipient of neuronally expressed BDNF. We further found that astrocytes specifically take up mature (not pro) BDNF released by neurons. Over-expression of TrkB in neurons redirects released BDNF from astrocytes to neurons, indicating that TrkB levels determine neuronal versus astrocytic BDNF uptake. Increased neuronal activity further increased astrocytic (but not neuronal) uptake of neuronally expressed BDNF. Finally, we demonstrate that astrocytes are not simply a sink for excess BDNF, but that BDNF taken up by astrocytes mediates physiological effects on the astrocytic population by increasing astrocytic territory.
Development of arbuscular mycorrhizal spore production in hydroponic culture on leaf lettuce (Lactuca sativar var crispa L.)

This study aimed to assess the suitability of a nutrient liquid solution for the production of Glomus verruculosum on leaf lettuce, a highly-colonized horticultural crop that is a host of arbuscular mycorrhizal (AM) fungi for inoculum production. A hydroponic culture was developed to allow nursery production of an AM horticultural crop. A suitable host of leaf lettuce cultivars was selected by an initial experiment. The red-leaf variety was found to be the best host because it exhibit maximum amount of root infection. In a second experiment, 2 nutrient media; modified Long Ashton (LANS) and modified Hoagland medium (HNS) were compared for culturing AM fungi on leaf lettuce. After a pre-culture period of 4 weeks with 50 spores in sand substrate, the plants initially infected with AM fungi and irrigated with both LANS and HNS were not significantly different. At 4 weeks after transplanting in the hydroponic culture, the total percentage of root colonization was found to be significantly greater in HNS medium than in LANS medium. In a third experiment, 4 nutrient media (solution-I, solution-II, solution-III and solution-IV) of HNS were used to compare root colonization, plant growth and spore production. The solution was changed every week by a deep water culture technique. At harvest time, plants in a solution-I with containing of NO3 as the N source and insoluble Ca3PO4 and CaSO4.2H2O had a higher percentage of mycorrhizal colonization and spore population than those using other nutrient media.
Semisupervised Deep Sparse Auto-Encoder With Local and Nonlocal Information for Intelligent Fault Diagnosis of Rotating Machinery

Nowadays, the measuring and monitoring data collected from rotating machinery exists a high-dimensional and massive status in quo, but the acquisition of the valuable labeled information is difficult. To address this challenge, an intelligent fault diagnosis method of rotating machinery based on semisupervised deep sparse auto-encoder (SSDSAE) with local and nonlocal information is presented in this article. Primarily, the collected vibration spectrum signals are fed into the constructed SSDSAE algorithm to implement fault feature extraction, and after that the extracted sparse discriminant features are fed into the back-propagation (BP) classifier for fault diagnosis. Accordingly, the unlabeled samples in SSDSAE are used to define local and nonlocal structural information for the original DSAE, and then the topological regularization terms are obtained by minimizing intraclass compactness (locality) and maximizing interclass separability (nonlocality). Moreover, the weighted cross-entropy (WCE) techniques in SSDSAE are used to improve the generalization performance of the fault diagnosis model for labeled data. Eventually, the availability of the proposed method is validated with data from experimental bearing fault and industrial rotor fault, respectively.
The Upper Tail of Precipitation in Convection‐Permitting Regional Climate Models and Their Utility in Nonstationary Rainfall and Flood Frequency Analysis

Computational advances have made atmospheric modeling at convection‐permitting (≤4 km) grid spacings increasingly feasible. These simulations hold great promise in the projection of climate change impacts including rainfall and flood extremes. The relatively short model runs that are currently feasible, however, inhibit the assessment of the upper tail of rainfall and flood quantiles using conventional statistical methods. Stochastic storm transposition (SST) and process‐based flood frequency analysis are two approaches that together can help to mitigate this limitation. SST generates large numbers of extreme rainfall scenarios by temporal resampling and geospatial transposition of rainfall fields from relatively short data sets. Coupling SST with process‐based flood frequency analysis enables exploration of flood behavior at a range of spatial and temporal scales. We apply these approaches with outputs of 13‐year simulations of regional climate to examine changes in extreme rainfall and flood quantiles up to the 500‐year recurrence interval in a medium‐sized watershed in the Midwestern United States. Intensification of extreme precipitation across a range of spatial and temporal scales is identified in future climate; changes in flood magnitudes depend on watershed area, with small watersheds exhibiting the greatest increases due to their limited capacity to attenuate flood peaks. Flood seasonality and snowmelt are predicted to be earlier in the year under projected warming, while the most extreme floods continue to occur in early summer. Findings highlight both the potential and limitations of convection‐resolving climate models to help understand possible changes in rainfall and flood frequency across watershed scales.
Understanding branding is demanding…

ABSTRACT As a tribute to the African American, Latino, and Caribbean-origin global Hip-hop cultural phenomenon, the body of this paper is written as a Spoken-word RAP (Rhyme And Poetry) treatise on the current branding landscape. Grounded in rhetoric, analogies, and allegories, the aim is to present a didactic passage for discussion and reflection, that through phonaesthetics, rhythm, and rhyme is multi-layered and easier to recall. Support for this approach, the author argues, lies in the fact that branding, through image, identity, personality, and slogan creation, aims to produce attractive and memorable meaning and language-shaping cultural artefacts. Furthermore, a gestalt method to capturing the cultural zeitgeist is designed to present a variety of perspectives – in the interests of evoking thought and language in line with the speed at which brands are having to evolve their approaches, steeped in popular culture and relevance.
Innovación e improvisación en el marco de la pandemia de COVID-19: relato de una experiencia

En el presente trabajo se relata la experiencia de nuestro equipo docente en el marco de la contingencia provocada por la pandemia de COVID-19. Nuestra universidad decidió en este particular contexto ratificar su calendario académico y garantizar la continuidad pedagógica a través de la modalidad de enseñanza a distancia. Este requerimiento nos puso a los docentes de la casa a pensar y a actuar con gran celeridad, seleccionando las herramientas y metodologías que consideramos más adecuadas para garantizar el derecho a continuar estudiando a la mayoría de nuestros estudiantes. En este trabajo, queremos presentar las estrategias didácticas llevadas a cabo por nuestro equipo docente -el cual está a cargo de una comisión de la cátedra Matemática A, de la Facultad de Ingeniería de la Universidad Nacional de La Plata-, algunas de las dificultades que nos hemos encontrado en este camino y algunos resultados que nos permiten valorar positivamente la experiencia. PALABRAS CLAVE: Educación virtual de emergencia, COVID-19, Enseñanza de la Matemática, TIC y Educación
HIV p17 enhances T cell proliferation by suppressing autophagy through the p17‐OLA1‐GSK3β axis under nutrient starvation

Nutrient starvation is a common phenomenon that occurs during T cell activation. Upon pathogen infection, large amounts of immune cells migrate to infection sites, and antigen‐specific T cells are activated; this is followed by rapid proliferation through clonal expansion. The dramatic expansion of cells will commonly lead to nutrient shortage. Cellular autophagy is often upregulated as a way to sustain the body's energy requirements. During infection, human immunodeficiency virus (HIV) co‐opts a series of host cell metabolic pathways for replication. Several HIV proteins, such as Env, Nef, and Vpr, have already been reported as being involved in autophagy‐related processes. In this report, we identified that the HIV p17 protein acts as a major factor in suppressing the autophagic process in T cells, especially under glucose starvation condition. HIV p17 interacts with Obg‐like ATPase 1 (OLA1) and disrupts OLA1‐glycogen synthase kinase‐3 beta (GSK3β) complex, leading to GSK3β hyperactivation. Consequently, a prior proliferation of HIV‐infected T cells under glucose starvation will occur. The inhibition of autophagy also aids HIV replication by antagonizing the antiviral effect of autophagy. Our study shows a new cellular pathway that HIV can hijack for viral spreading by a prior proliferation of HIV‐loaded T cells and may provide new therapeutic targets for acquired immunodeficiency syndrome intervention.
Navigating Gaza’s conflict through women’s entrepreneurship

Purpose – This paper explores the extent to which women’s entrepreneurship in conflict zones is an influential catalyst for liberalizing traditionally conservative gender norms. This purpose is achieved by focusing on women entrepreneurs in Gaza and how they actively renegotiate their multiple gender roles and navigate the social order through entrepreneurship. Design/methodology/approach This paper adopts the interpretivist approach where individual in-depth interviews were conducted with sixteen Palestinian women entrepreneurs operating in Gaza. Findings The findings demonstrate that the context of conflict itself and its impact on gender norms is a prime motivator for women to engage in entrepreneurial ventures. Some gender roles were constraining and other enabling for women to initiate and sustain their ventures in order to contribute to their families’ well-being. Despite the fact that the conflict context and entrepreneurship have contributed to enhancing the agency of women and their ability to navigate the conflict and its consequences, the gendered practices and assumptions are still used as guidance for women to grant legitimacy. Originality/value This paper contributes to the gender and entrepreneurship literature by giving a greater visibility to necessity-driven women entrepreneurs in an under researched conflict context, and demonstrates how prolonged conflict instigates social and economic changes that can empower women whilst also reinforcing certain gendered norms.
Examining Developed versus Emerging Economy Online Food and Beverage Purchase Behaviour and Predictors: A Survey Comparison of Indian, Chinese, Indonesian, Japanese and United Kingdom Consumers

Aims: Consumers are increasingly using online shopping for purchasing food and beverage (F&B) products. A challenge to industry stakeholders is understanding which elements of online digital media and smart technologies are associated with higher rates of online expenditure that could be strategically targeted. Therefore, the central aims of this study are to identify predictors of online F&B expenditure, and how they differ across developed and emerging economy consumers. Study Design: This is a quantitative study based on cross-sectional survey data. Place and Duration of Study: The study is based on data collected in India, China, Indonesia, Japan and the United Kingdom in April 2016. Original Research Article Driver et al.; SAJSSE, 7(3): 26-38, 2020; Article no.SAJSSE. 59385 27 Methodology: Primary data is collected using online surveys of consumers primarily responsible for F&B grocery shopping within the household. Questionnaires focused on eliciting online expenditure rates for F&B, and associated use of relevant online digital media and smart technologies. Fractional multinomial logit modelling is used to identify statistically significant determinants of respondents’ percentage of expenditure online in each country. Results: The sample consists of 5,004 respondents: China (1,001), India (998), Indonesia (1,002), Japan (1,002), UK (1,001). In-market technology use is a stronger predictor of online F&B expenditure in emerging than in developed economy markets. The influence of digital information sourcing behaviour and demographics are weak predictors of online F&B expenditure across both developed and emerging economy markets. In general, consumers in emerging economies show greater engagement with digital media and smart technology in relation to online F&B expenditure than their developed economy counterparts. Conclusion: There is significant variation across countries in the specific determinants of online food and beverage expenditure and the uptake of associated digital media and smart technologies. These insights provide useful direction for focusing effort in targeting channel activators specific to each markets characteristics.