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Human mpox (formerly monkeypox) is an emerging zoonotic disease caused by monkeypox virus (MPXV) (1,2). Since the 1970s, mpox outbreaks in humans have occurred sporadically, mainly in Africa (3). In [...]

Online learning has grown in recent years and has become popular with Massive Open Online Courses (MOOCs). The advent of the pandemic has undoubtedly made more teachers and students experience the online learning experience. Distance learning is going to grow even more in the coming years. In this article, we present our computational thinking and programming course focused on life science students. We introduce our approach for analyzing how students interact with didactic resources regarding their probability of completing the course. We discussed several insights this strategy brought us and how we can leverage the teaching of programming skills to life science students through learning analytics. We suggest that machine learning techniques will be increasingly essential for better monitoring and supporting students and for online courses improvements.

PURPOSECOVID-19 has affected cancer care worldwide. Clinical trials are an important alternative for the treatment of oncologic patients, especially in Latin America, where trials can be the only opportunity for some of them to access novel and, sometimes, standard treatments.METHODSThis was a cross-sectional study, in which a 22-question survey regarding the impact of the COVID-19 pandemic on oncology clinical trials was sent to 350 representatives of research programs in selected Latin American institutions, members of the Latin American Cooperative Oncology Group.RESULTSThere were 90 research centers participating in the survey, with 70 of them from Brazil. The majority were partly private or fully private (n = 77; 85.6%) and had confirmed COVID-19 cases at the institution (n = 57; 63.3%). Accruals were suspended at least for some studies in 80% (n = 72) of the responses, mostly because of sponsors' decision. Clinical trials' routine was affected by medical visits cancelation, reduction of patients' attendance, reduction of other specialties' availability, and/or alterations on follow-up processes. Formal COVID-19 mitigation policies were adopted in 96.7% of the centers, including remote monitoring and remote site initiation visits, telemedicine visits, reduction of research team workdays or home office, special consent procedures, shipment of oral drugs directly to patients' home, and increase in outpatient diagnostic studies. Importantly, some of these changes were suggested to be part of future oncology clinical trials' routine, particularly the ones regarding remote methods, such as telemedicine.CONCLUSIONTo our knowledge, this was the first survey to evaluate the impact of COVID-19 on Latin American oncology clinical trials. The results are consistent with surveys from other world regions. These findings may endorse improvements in clinical trials' processes and management in the postpandemic period.

Abstract Substantial COVID-19 research investment has been allocated to randomized clinical trials (RCTs) on hydroxychloroquine/chloroquine, which currently face recruitment challenges or early discontinuation. We aim to estimate the effects of hydroxychloroquine and chloroquine on survival in COVID-19 from all currently available RCT evidence, published and unpublished. We present a rapid meta-analysis of ongoing, completed, or discontinued RCTs on hydroxychloroquine or chloroquine treatment for any COVID-19 patients (protocol: https://osf.io/QESV4/ ). We systematically identified unpublished RCTs (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, Cochrane COVID-registry up to June 11, 2020), and published RCTs (PubMed, medRxiv and bioRxiv up to October 16, 2020). All-cause mortality has been extracted (publications/preprints) or requested from investigators and combined in random-effects meta-analyses, calculating odds ratios (ORs) with 95% confidence intervals (CIs), separately for hydroxychloroquine and chloroquine. Prespecified subgroup analyses include patient setting, diagnostic confirmation, control type, and publication status. Sixty-three trials were potentially eligible. We included 14 unpublished trials (1308 patients) and 14 publications/preprints (9011 patients). Results for hydroxychloroquine are dominated by RECOVERY and WHO SOLIDARITY, two highly pragmatic trials, which employed relatively high doses and included 4716 and 1853 patients, respectively (67% of the total sample size). The combined OR on all-cause mortality for hydroxychloroquine is 1.11 (95% CI: 1.02, 1.20; I² = 0%; 26 trials; 10,012 patients) and for chloroquine 1.77 (95%CI: 0.15, 21.13, I² = 0%; 4 trials; 307 patients). We identified no subgroup effects. We found that treatment with hydroxychloroquine is associated with increased mortality in COVID-19 patients, and there is no benefit of chloroquine. Findings have unclear generalizability to outpatients, children, pregnant women, and people with comorbidities.

Abstract Background Protein–peptide interactions play a fundamental role in a wide variety of biological processes, such as cell signaling, regulatory networks, immune responses, and enzyme inhibition. Peptides are characterized by low toxicity and small interface areas; therefore, they are good targets for therapeutic strategies, rational drug planning and protein inhibition. Approximately 10% of the ethical pharmaceutical market is protein/peptide-based. Furthermore, it is estimated that 40% of protein interactions are mediated by peptides. Despite the fast increase in the volume of biological data, particularly on sequences and structures, there remains a lack of broad and comprehensive protein–peptide databases and tools that allow the retrieval, characterization and understanding of protein–peptide recognition and consequently support peptide design. Results We introduce Propedia, a comprehensive and up-to-date database with a web interface that permits clustering, searching and visualizing of protein–peptide complexes according to varied criteria. Propedia comprises over 19,000 high-resolution structures from the Protein Data Bank including structural and sequence information from protein–peptide complexes. The main advantage of Propedia over other peptide databases is that it allows a more comprehensive analysis of similarity and redundancy. It was constructed based on a hybrid clustering algorithm that compares and groups peptides by sequences, interface structures and binding sites. Propedia is available through a graphical, user-friendly and functional interface where users can retrieve, and analyze complexes and download each search data set. We performed case studies and verified that the utility of Propedia scores to rank promissing interacting peptides. In a study involving predicting peptides to inhibit SARS-CoV-2 main protease, we showed that Propedia scores related to similarity between different peptide complexes with SARS-CoV-2 main protease are in agreement with molecular dynamics free energy calculation. Conclusions Propedia is a database and tool to support structure-based rational design of peptides for special purposes. Protein–peptide interactions can be useful to predict, classifying and scoring complexes or for designing new molecules as well. Propedia is up-to-date as a ready-to-use webserver with a friendly and resourceful interface and is available at: https://bioinfo.dcc.ufmg.br/propedia

Abstract Background Protein engineering has many applications for industry, such as the development of new drugs, vaccines, treatment therapies, food, and biofuel production. A common way to engineer a protein is to perform mutations in functionally essential residues to optimize their function. However, the discovery of beneficial mutations for proteins is a complex task, with a time-consuming and high cost for experimental validation. Hence, computational approaches have been used to propose new insights for experiments narrowing the search space and reducing the costs. Results In this study, we developed Proteus (an acronym for Protein Engineering Supporter), a new algorithm for proposing mutation pairs in a target 3D structure. These suggestions are based on contacts observed in other known structures from Protein Data Bank (PDB). Proteus’ basic assumption is that if a non-interacting pair of amino acid residues in the target structure is exchanged to an interacting pair, this could enhance protein stability. This trade is only allowed if the main-chain conformation of the residues involved in the contact is conserved. Furthermore, no steric impediment is expected between the proposed mutations and the surrounding protein atoms. To evaluate Proteus, we performed two case studies with proteins of industrial interests. In the first case study, we evaluated if the mutations suggested by Proteus for four protein structures enhance the number of inter-residue contacts. Our results suggest that most mutations proposed by Proteus increase the number of interactions into the protein. In the second case study, we used Proteus to suggest mutations for a lysozyme protein. Then, we compared Proteus’ outcomes to mutations with available experimental evidence reported in the ProTherm database. Four mutations, in which our results agree with the experimental data, were found. This could be initial evidence that changes in the side-chain of some residues do not cause disturbances that harm protein structure stability. Conclusion We believe that Proteus could be used combined with other methods to give new insights into the rational development of engineered proteins. Proteus user-friendly web-based tool is available at < http://proteus.dcc.ufmg.br >.

Abstract Background Interactions between proteins and non-proteic small molecule ligands play important roles in the biological processes of living systems. Thus, the development of computational methods to support our understanding of the ligand-receptor recognition process is of fundamental importance since these methods are a major step towards ligand prediction, target identification, lead discovery, and more. This article presents visGReMLIN, a web server that couples a graph mining-based strategy to detect motifs at the protein-ligand interface with an interactive platform to visually explore and interpret these motifs in the context of protein-ligand interfaces. Results To illustrate the potential of visGReMLIN, we conducted two cases in which our strategy was compared with previous experimentally and computationally determined results. visGReMLIN allowed us to detect patterns previously documented in the literature in a totally visual manner. In addition, we found some motifs that we believe are relevant to protein-ligand interactions in the analyzed datasets. Conclusions We aimed to build a visual analytics-oriented web server to detect and visualize common motifs at the protein-ligand interface. visGReMLIN motifs can support users in gaining insights on the key atoms/residues responsible for protein-ligand interactions in a dataset of complexes.

Bioinformatics is a fast-evolving research field, requiring effective educational initiatives to bring computational knowledge to Life Sciences. Since 2017, an organizing committee composed of graduate students and postdoctoral researchers from the Universidade Federal de Minas Gerais (Brazil) promotes a week-long event named Summer Course in Bioinformatics (CVBioinfo). This event aims to diffuse bioinformatic principles, news, and methods mainly focused on audiences of undergraduate students. Furthermore, as the advent of the COVID-19 global pandemic has precluded in-person events, we offered the event in online mode, using free video transmission platforms. Herein, we present and discuss the insights obtained from promoting the Online Workshop in Bioinformatics (WOB) organized in November 2020, comparing it to our experience in previous in-person editions of the same event.

Abstract The Dyson–Schwinger quark equation is solved for the quark-gluon vertex using the most recent lattice data available in the Landau gauge for the quark, gluon and ghost propagators, the full set of longitudinal tensor structures in the Ball-Chiu vertex, taking into account a recently derived normalisation for a quark-ghost kernel form factors and the gluon contribution for the tree level quark-gluon vertex identified on a recent study of the lattice soft gluon limit. A solution for the inverse problem is computed after the Tikhonov linear regularisation of the integral equation, that implies solving a modified Dyson–Schwinger equation. We get longitudinal form factors that are strongly enhanced at the infrared region, deviate significantly from the tree level results for quark and gluon momentum below 2 GeV and at higher momentum approach their perturbative values. The computed quark-gluon vertex favours kinematical configurations where the quark momentum p and the gluon momentum q are small and parallel. Further, the quark-gluon vertex is dominated by the form factors associated to the tree level vertex $$\gamma _\mu $$ γμ and to the operator $$2 \, p_\mu + q_\mu $$ 2pμ+qμ . The higher rank tensor structures provide small contributions to the vertex.

Abstract Hops is a new culture in Brazil. Tissue culture can be an important technique for rapid hop propagation. This paper aims to characterize responses from different genotypes under different growth regulators through the interrelationship of response variables important to hop in vitro growth. Three genotypes were cultivated in six culture media with different combinations of growth regulators, BAP (6-benzylaminopurine), IAA (3-indolacetic acid) and GA3 (gibberellic acid). The means were compared by orthogonal contrasts and the interrelationship of the response variables was performed by path analysis. American genotypes showed favorable root development under the BAP + IAA combination, while the use of IAA improved shoot development. The origin of genotypes was important for defining the best protocol for in vitro cultivation. The path coefficient showed that the variable number of shoots has stronger direct effect on the number of nodal segments. Additionally, in tissue culture assays, the use of a covariable and proper error distribution significantly increased experimental accuracy.

Epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase widely expressed in cervical tumors, being correlated with adverse clinical outcomes. EGFR may be activated by a diversity of mechanisms, including transactivation by G-protein coupled receptors (GPCRs). Studies have also shown that platelet-activating factor (PAF), a pro-inflammatory phospholipid mediator, plays an important role in the cancer progression either by modulating the cancer cells or the tumor microenvironment. Most of the PAF effects seem to be mediated by the interaction with its receptor (PAFR), a member of the GPCRs family. PAFR- and EGFR-evoked signaling pathways contribute to tumor biology; however, the interplay between them remains uninvestigated in cervical cancer. In this study, we employed The Cancer Genome Atlas (TCGA) and cancer cell lines to evaluate possible cooperation between EGFR, PAFR, and lysophosphatidylcholine acyltransferases (LPCATs), enzymes involved in the PAF biosynthesis, in the context of cervical cancer. It was observed a strong positive correlation between the expression of EGFR × PAFR and EGFR × LPCAT2 in 306 cervical cancer samples. The increased expression of LPCAT2 was significantly correlated with poor overall survival. Activation of EGFR upregulated the expression of PAFR and LPCAT2 in a MAPK-dependent fashion. At the same time, PAF showed the ability to transactivate EGFR leading to ERK/MAPK activation, cyclooxygenase-2 (COX-2) induction, and cell migration. The positive crosstalk between the PAF-PAFR axis and EGFR demonstrates a relevant linkage between inflammatory and growth factor signaling in cervical cancer cells. Finally, combined PAFR and EGFR targeting treatment impaired clonogenic capacity and viability of aggressive cervical cancer cells more strongly than each treatment separately. Collectively, we proposed that EGFR, LPCAT2, and PAFR emerge as novel targets for cervical cancer therapy.

Summary: Obesity has been associated with cognitive decline, atrophy of brain regions related to learning and memory, and higher risk of developing dementia. However, the molecular mechanisms underlying these neurological alterations are still largely unknown. Here, we investigate the effects of palmitate, a saturated fatty acid present at high amounts in fat-rich diets, in the brain. Palmitate is increased in the cerebrospinal fluid (CSF) of overweight and obese patients with amnestic mild cognitive impairment. In mice, intracerebroventricular infusion of palmitate impairs synaptic plasticity and memory. Palmitate induces astroglial and microglial activation in the mouse hippocampus, and its deleterious impact is mediated by microglia-derived tumor necrosis factor alpha (TNF-α) signaling. Our results establish that obesity is associated with increases in CSF palmitate. By defining a pro-inflammatory mechanism by which abnormal levels of palmitate in the brain impair memory, the results further suggest that anti-inflammatory strategies may attenuate memory impairment in obesity. : Obesity has been associated with cognitive decline. Melo et al. show that palmitate levels are increased in the CSF of overweight and obese humans. In mice, intracerebroventricular infusion of palmitate impairs synaptic plasticity and memory. Microglial-derived TNF-α mediates the deleterious actions of palmitate in the brain. Keywords: palmitate, memory impairment, obesity, brain inflammation, microglia, TNF-α, insulin signaling

ObjectiveThis study aimed to describe the demographic and clinical characteristics of cancer inpatients with COVID-19 exploring clinical outcomes.MethodsA retrospective search in the electronic medical records of cancer inpatients admitted to the Brazilian National Cancer Institute from April 30, 2020 to May 26, 2020 granted identification of 181 patients with COVID-19 confirmed by RT-PCR.ResultsThe mean age was 55.3 years (SD ± 21.1). Comorbidities were present in 110 (60.8%) cases. The most prevalent solid tumors were breast (40 [22.1%]), gastrointestinal (24 [13.3%]), and gynecological (22 [12.2%]). Among hematological malignancies, lymphoma (20 [11%]) and leukemia (10 [5.5%]) predominated. Metastatic disease accounted for 90 (49.7%) cases. In total, 63 (34.8%) had recently received cytotoxic chemotherapy. The most common complications were respiratory failure (70 [38.7%]), septic shock (40 [22.1%]) and acute kidney injury (33 [18.2%]). A total of 60 (33.1%) patients died due to COVID-19 complications. For solid tumors, the COVID-19-specific mortality rate was 37.7% (52 out of 138 patients) and for hematological malignancies, 23.5% (8 out of 34). According to the univariate analysis COVID-19-specific mortality was significantly associated with age over 75 years (P = .002), metastatic cancer (p ConclusionThis is the first Brazilian cohort of cancer patients with COVID-19. The rates of complications and COVID-19-specific death were significantly high.

Abstract The soft gluon limit of the longitudinal part of the quark-gluon vertex is studied by resorting to non-perturbative approaches to quantum chromodynamics (QCD). Based on a Slavnov–Taylor identity (STI), the longitudinal form factors is expressed in terms of the quark-ghost kernel, the quark self energy and the quark wave function. An exact relation between the non-vanishing longitudinal form factors is derived for the soft gluon limit and explored to understand the behaviour of the vertex. Within a Ball–Chiu vertex, the form factor $$\lambda _1$$ λ1 was analysed using recent lattice simulations for full QCD for the soft gluon limit. The lattice data shows that the gluon propagator resumes the momentum dependence of such component of the vertex. This connection is understood via a fully dressed one-loop Bethe–Salpeter equation. The behaviour of the remaining longitudinal form factors $$\lambda _2(p^2)$$ λ2(p2) and $$\lambda _3(p^2)$$ λ3(p2) is investigated combining both the information of lattice simulations and the derived relations based on the STI.

This report provides a detailed overview of the resurgence of DENV-3 in the state of Minas Gerais, Brazil, which is a concerning scenario in the context of dengue, a mosquito-borne viral disease. Historically, Brazil has grappled with dengue epidemics caused primarily by the DENV-1 and DENV-2 serotypes. However, in 2023, a significant shift in this pattern was observed as DENV-3 made a notable resurgence. This resurgence was characterized by the increase in DENV-3 cases within the country and the region of the Americas. Given the absence of sustained DENV-3 circulation in Brazil in previous years, this situation poses a significant risk, making the population highly susceptible to a potential novel epidemic. In November 2023, a 31-year-old male patient in Belo Horizonte exhibited symptoms of acute febrile syndrome. Multiplex RT-qPCR using the Kit Molecular ZC D-Tipagem confirmed DENV-3 infection, suggesting a likely autochthonous case, as the patient reported no travel history. To promptly assess this resurgence, we applied the nanopore sequencing technology. This allowed for the rapid characterization of the initial DENV-3 case isolated in Minas Gerais in 2023, representing a 13-year interval since the serotype's previous documented circulation in that state. This case report underscores the critical importance of proactive monitoring and the swift implementation of targeted control strategies to address the evolving dynamics of dengue, with a specific emphasis on the resurgence of DENV-3 in the state. [ABSTRACT FROM AUTHOR]

Abstract Background A huge amount of data about genomes and sequence variation is available and continues to grow on a large scale, which makes experimentally characterizing these mutations infeasible regarding disease association and effects on protein structure and function. Therefore, reliable computational approaches are needed to support the understanding of mutations and their impacts. Here, we present VERMONT 2.0, a visual interactive platform that combines sequence and structural parameters with interactive visualizations to make the impact of protein point mutations more understandable. Results We aimed to contribute a novel visual analytics oriented method to analyze and gain insight on the impact of protein point mutations. To assess the ability of VERMONT to do this, we visually examined a set of mutations that were experimentally characterized to determine if VERMONT could identify damaging mutations and why they can be considered so. Conclusions VERMONT allowed us to understand mutations by interpreting position-specific structural and physicochemical properties. Additionally, we note some specific positions we believe have an impact on protein function/structure in the case of mutation.

A proposta que norteia esta pesquisa encontra seu fundamento na crítica de Theodor Adorno aos advogados da “Indústria Cultural”. Procuramos investigar em que consiste tal crítica, dando evidência às suas principais características, bem como aos seus reflexos no corpo social, uma vez que, a arte e a cultura, que são manifestações do espírito humano, tornaram-se produtos industrializados e comercializados, perdendo a sua essência. O escopo da arte e da cultura, entendida como a libertação e a emancipação do homem, fora violado, sendo transformado em meras mercadorias descartáveis, com a finalidade de disseminar o pensamento da classe dominante através do seu sistema econômico, acarretando em uma pseudo-individualidade. O homem passou a ser objeto de manipulação da indústria que transforma tudo em mercadoria. Esta maquinaria engloba tudo, e nem mesmo alguns atos de contestação deixam de ser incorporados e diluídos pela Indústria Cultural que rapidamente procura transformá-las em produtos para comercialização, revelando que tudo aquilo que está contra o sistema é absorvido e reinterpretado, tragando a individualidade. Os homens, por sua vez, se não aderirem à forma de pensar imposta pela Indústria, soçobrarão em meio à multidão consumidora. Assim, nossa análise compreende esta Indústria como um braço do sistema capitalista, que através dos meios de comunicação de amplo acesso, exerce grande influência na difusão e disseminação da ideologia desse sistema.

This study measured levels of brain-derived neurotrophic factor (BDNF) in the prefrontal cortex (PFC) after single (S) and repetitive (R) anodal epidural DC stimulation (eDCS) over the left medial prefrontal cortex (mPFC). Male Wistar rats (n = 4 per group) received single application of sham (S-sham) or anodal eDCS (S-eDCS) (400 μA for 11 min) and had their PFC removed 15, 30, or 60 min later. For repetitive brain stimulation, rats received sham (R-sham) or anodal eDCS (R-eDCS) once a day, five consecutive days, and their PFC were removed 24 h after the last application. BDNF isoforms levels were measured by Western blot assays. It was observed that animals receiving S-eDCS showed smaller (p < 0.01) levels of BDNF 15 min after stimulation when compared to S-sham, especially in its mature form (mBDNF p < 0.001). Levels of BDNF, including mBDNF, were almost like the S-sham at 30 and 60 min intervals after stimulation, but not proBDNF, which was significantly smaller (p < 0.05) than S-sham at these intervals. After five sessions, BDNF levels were higher in the PFC of R-eDCS animals, notably the proBDNF (p < 0.01) when compared to R-sham. This study showed that levels of BDNF in the PFC, especially the proBDNF, were lower after a single and higher after repetitive anodal eDCS applied over the left mPFC when compared to sham. Therefore, changes of prefrontal BDNF levels may disclose molecular changes underlying the plasticity induced by cortical anodal DC stimulation, which may be opposite if applied in single or multiple sessions.

ABSTRACT Associations between root distribution and bean growth habit may contribute to the selection of genotypes adapted to restrictive environments. The present work aimed to relate and compare root distribution with the growth habit in beans. 10 bean genotypes of different growth habits (I, II and III) were evaluated for root distribution in two agricultural years (2014/15 and 2015/16). The genotypes responded similarly for the trait root distribution throughout the agricultural years, without any simple effect of the genotype x year interaction. The factors genotype and years were significant for the trait. The genotypes of a determinate habit showed significant differences compared to other genotypes (II and III), which were ascribed to their poor performance in the average of years. They include the Carioca Precoce, which showed a behavior similar to the other habits. It could be considered a “plastic” genotype under restrictive conditions. The contrasts revealed significant differences between the growth habits II vs I (2.87) and III vs I (3.64) for root distribution. The differences were also significant for grain yield. Thus, genotypes of indeterminate growth habit show greater root distribution than those of a determinate habit, regardless of the agricultural years. Therefore, they are promising for use in blocks of crosses, when the purpose is the selection of cultivars adapted to low input environments.

In aquaculture, activities with anesthetic compounds are usually used in order to ensure the welfare of farmed fish, allowing handling out of water with decreased trauma by stress. Presently, there is no information about anesthetic action of eugenol in early life stages of Nile tilapia (Oreochromis niloticus). The objective of this study was to evaluate different concentrations of eugenol for larvae and juveniles of Nile tilapia. Sixty animals were used for each group of weight, group I = 0.02 g; group II = 0.08 g; group III = 0.22 g; group IV = 2.62 g; and group V = 11.64 g. The eugenol concentrations tested were 50, 75, 100, 125, 150 and 175 mg L-1. No mortality was reported during the tests with eugenol. Tilapia larvae with 0.02 g and juveniles around 11.64 g can be anesthetized with eugenol concentrations between 150 and 175 mg L-1, since they determine the shortest sedation time (23 and 72 seconds, for the group of lowest and highest weights, respectively).