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COVID-19 caused devastating effects of human loss and suffering along with disruption in clinical research, forcing reconceptualization and modification of studies. buy Sodium dichloroacetate This paper attempts to outline the steps followed and detail the modifications undertaken to deal with the impacts of the pandemic on the first ongoing randomized controlled trial on effectiveness of neuropsychological rehabilitation in adult patients with drug-resistant epilepsy in India. All modifications were based on evolving guidelines and circumstantial context and were planned, reviewed and approved by important stakeholders. Results obtained from the trial need to be interpreted and analysed within this context. These modifications have implications for wider outreach of neuropsychology services in India.

The use of rosuvastatin plus colchicine and emtricitabine/tenofovir in hospitalized patients with SARS-CoV-2 disease (COVID-19) has not been assessed. The objective of this study was to assess the effectiveness and safety of rosuvastatin plus colchicine, emtricitabine/tenofovir, and their combined use in these patients.

This was a randomized, controlled, open-label, multicentre, parallel, pragmatic study conducted in six referral hospitals in Bogotá, Colombia. The study enrolled hospitalized patients over 18 years of age with a confirmed diagnosis of COVID-19 complicated with pneumonia, not on chronic treatment with the study medications, and with no contraindications for their use. Patients were assigned 1111. 1) emtricitabine with tenofovir disoproxil fumarate (FTC/TDF, 200/300 mg given orally for 10 days); 2) colchicine plus rosuvastatin (COLCH+ROSU, 0.5 mg and 40 mg given orally for 14 days); 3) emtricitabine with tenofovir disoproxil plus colchicine and rosuvastatin at the same doses and for the sameatment with this combination versus other drugs that have been shown to reduce mortality from SARS-CoV-2 infection and its usefulness in patients with chronic statin use.Inflammatory cytokines and chemokines (CC) drive COVID-19 pathology. Yet, patients with similar circulating CC levels present with different disease severity. Here, we determined 171 microRNAomes from 58 hospitalized COVID-19 patients (Cohort 1) and levels of 25 cytokines and chemokines (CC) in the same samples. Combining microRNA (miRNA) and CC measurements allowed for discrimination of severe cases with greater accuracy than using miRNA or CC levels alone. Severity group-specific associations between miRNAs and COVID-19-associated CC (e.g., IL6, CCL20) or clinical hallmarks of COVID-19 (e.g., neutrophilia, hypoalbuminemia) separated patients with similar CC levels but different disease severity. Analysis of an independent cohort of 108 patients from a different center (Cohort 2) demonstrated feasibility of CC/miRNA profiling in leftover hospital blood samples with similar severe disease CC and miRNA profiles, and revealed CCL20, IL6, IL10, and miR-451a as key correlates of fatal COVID-19. These findings highlight that systemic miRNA/CC networks underpin severe COVID-19.SARS-CoV-2, the etiologic agent of COVID-19, uses ACE2 as a cell entry receptor. Soluble ACE2 has been shown to have neutralizing antiviral activity but has a short half-life and no active transport mechanism from the circulation into the alveolar spaces of the lung. To overcome this, we constructed an ACE2-human IgG1 fusion protein with mutations in the catalytic domain of ACE2. A mutation in the catalytic domain of ACE2, MDR504, significantly increased binding to SARS-CoV-2 spike protein, as well as to a spike variant, in vitro with more potent viral neutralization in plaque assays. Parental administration of the protein showed stable serum concentrations with excellent bioavailability in the epithelial lining fluid of the lung, and ameliorated lung SARS-CoV-2 infection in vivo. These data support that the MDR504 hACE2-Fc is an excellent candidate for treatment or prophylaxis of COVID-19 and potentially emerging variants.Although some COVID-19 patients maintain SARS-CoV-2-specific serum immunoglobulin G (IgG) for more than 6 months postinfection, others eventually lose IgG levels. We assessed the persistence of SARS-CoV-2-specific B cells in 17 patients, 5 of whom had lost specific IgGs after 5-8 months. Differentiation of blood-derived B cells in vitro revealed persistent SARS-CoV-2-specific IgG B cells in all patients, whereas IgA B cells were maintained in 11. Antibodies derived from cultured B cells blocked binding of viral receptor-binding domain (RBD) to the cellular receptor ACE-2, had neutralizing activity to authentic virus, and recognized the RBD of the variant of concern Alpha similarly to the wild type, whereas reactivity to Beta and Gamma were decreased. Thus, differentiation of memory B cells could be more sensitive for detecting previous infection than measuring serum antibodies. Understanding the persistence of SARS-CoV-2-specific B cells even in the absence of specific serum IgG will help to promote long-term immunity.The SARS-CoV-2 global pandemic created an unprecedented need for rapid, sensitive, and inexpensive point-of-care (POC) diagnostic tests to treat and control the disease. Many POC SARS-CoV-2 lateral flow immunoassays (LFAs) have been developed and/or commercialized, but with only limited sensitivity (μM-fM). We created an advanced LFA based on gold nanospheres (GNSs) with comprehensive assay redesign for enhanced specific binding and thermal contrast amplification (TCA) on GNSs for signal amplification, which enabled fM-aM detection sensitivity for SARS-CoV-2 spike receptor-binding domain (RBD) proteins within 30 min. The advanced LFA can visually detect RBD proteins down to 3.6 and 28.6 aM in buffer and human nasopharyngeal wash, respectively. This is the first reported LFA achieving sensitivity comparable to that of the PCR (aM-zM) by visual reading, which was much more sensitive than traditional LFAs. We also developed a fast ( less then 1 min) TCA reading algorithm, with results showing that this TCA could distinguish 26-32% visual false negatives for clinical commercial LFAs. When our advanced LFAs were applied with this TCA, the sensitivities were further improved by eightfold to 0.45 aM (in buffer) and 3.6 aM (in the human nasopharyngeal wash) with a semiquantitative readout. Our proposed advanced LFA with a TCA diagnostic platform can help control the current SARS-CoV-2 pandemic. Furthermore, the simplicity and speed with which this assay was assembled may also facilitate preparedness for future pandemics.Digital platforms, understood as multi-sided matchmakers, have amassed huge power, reimagining the role of consumers, producers, and even ownership. They increasingly dictate the way the economy and urban life is organized. Yet, despite their influential and far-reaching role in shaping our economic as well as sociocultural world, our understanding of their embeddedness, namely how their activities are embedded in systems of social and societal relationships and how they conceptualize their main functions and actions in relation to their wider setting, remains rudimentary. Consequently, the purpose of this frontier paper is threefold. Firstly, it reveals the need to discuss and evaluate (dis-)embedding processes in platform urbanism in order to understand the underlying dynamics of platform power and urban transformation. Secondly, it aims to reveal the main reasons in regard to the difficulties in pinpointing digital platforms embeddedness. Thirdly, it seeks to propose future research unravelling the (dis-)embeddedness of the platform economy. This paper argues for three main reasons namely unawareness, unaccountability and non-transparency of digital platforms that drive the lack of embeddedness and reaffirms platform power. This is mainly based on the configuration of new commodities, platforms' strategic avoidance of labour protections and other regulatory frameworks as well as platforms' secrecy in which they operate. This frontier paper argues that transferring the concept of embeddedness to the platform economy might serve as a valuable tool to understand and pinpoint essential dynamics and relationships at play, therefore proposing embeddedness as a basis for future research on the platform economy. It strongly argues that a more detailed understanding is urgently needed, in order to be able to understand, accompany and actively influence the development of the platform economy in regulatory terms.Kitchen gardening is considered a way to reconnect with agriculture and complement the cereal-based relief food offered to refugees in East Africa. This work aimed at profiling mineral content of okra in four refugee camps and settlements located in Ethiopia and Uganda and its contribution to adequate intake (AIs) or recommended dietary allowances (RDAs) for young children and pregnant and lactating women (PLW). The study also evaluated the applicability of portable X-ray fluorescence (PXRF) as compared with inductively coupled plasma mass spectrometry (ICP-MS) for mineral profiling of okra powder samples. The contents of minerals (mg kg-1) from the ICP-MS readings were in the following ranges K (14,385-33,294), Ca (2610-14,090), P (3178-13,248), Mg (3896-7986), Cu (3.81-19.3), Fe (75.7-1243), Zn (33-141) and Mn (23.1-261). Regardless of geographic origin, at low-end consumption probability (17 g day-1 for young children and 68 g day-1 for PLW), okra could contribute ˂ 15% (2.7-12.9%) AI for macro-minerals (K and Ca). In addition, the contributions to RDA values for Fe and Zn, elements of known public health interest, ranged from 4.5 to 34.7% for young children. Interestingly, regression lines revealed strong agreement between ICP-MS and PXRF readings for Mn and Zn, with R2 values > 0.91. This information is useful in support of nutrition-sensitive kitchen gardening programs through scaling culturally important crops in refugee settings.

The online version contains supplementary material available at 10.1007/s42452-021-04898-6.

The online version contains supplementary material available at 10.1007/s42452-021-04898-6.Cyberbullying is the use of digital communication tools and spaces to inflict physical, mental, or emotional distress. This serious form of aggression is frequently targeted at, but not limited to, vulnerable populations. A common problem when creating machine learning models to identify cyberbullying is the availability of accurately annotated, reliable, relevant, and diverse datasets. Datasets intended to train models for cyberbullying detection are typically annotated by human participants, which can introduce the following issues (1) annotator bias, (2) incorrect annotation due to language and cultural barriers, and (3) the inherent subjectivity of the task can naturally create multiple valid labels for a given comment. The result can be a potentially inadequate dataset with one or more of these overlapping issues. We propose two machine learning approaches to identify and filter unambiguous comments in a cyberbullying dataset of roughly 19,000 comments collected from YouTube that was initially annotated using Amazon Mechanical Turk (AMT). Using consensus filtering methods, comments were classified as unambiguous when an agreement occurred between the AMT workers' majority label and the unanimous algorithmic filtering label. Comments identified as unambiguous were extracted and used to curate new datasets. We then used an artificial neural network to test for performance on these datasets. Compared to the original dataset, the classifier exhibits a large improvement in performance on modified versions of the dataset and can yield insight into the type of data that is consistently classified as bullying or non-bullying. This annotation approach can be expanded from cyberbullying datasets onto any classification corpus that has a similar complexity in scope.