In situ short-term responses of Amazonian understory plants to elevated CO2

The response of plants to increasing atmospheric CO2 depends on the ecological context where the plants are found. Several experiments with elevated CO2 (eCO2) have been done worldwide, but the Amazonian forest understory has been neglected. As the central Amazon is limited by light and phosphorus, understanding how understory responds to eCO2 is important for foreseeing how the forest will function in the future. In the understory of a natural forest in the Central Amazon, we installed four open-top chambers as control replicates and another four under eCO2 (+250 ppm above ambient levels). Under eCO2, we observed increases in carbon assimilation rate (67%), maximum electron transport rate (19%), quantum yield (56%), and water use efficiency (78%). We also detected an increase in leaf area (51%) and stem diameter increment (65%). Central Amazon understory responded positively to eCO2 by increasing their ability to capture and use light and the extra primary productivity was allocated to supporting more leaf and conducting tissues. The increment in leaf area while maintaining transpiration rates suggests that the understory will increase its contribution to evapotranspiration. Therefore, this forest might be less resistant in the future to extreme drought, as no reduction in transpiration rates were detected.

Resource availability and disturbance frequency shape evolution of plant life forms in Neotropical habitats

Organisms use diverse strategies to thrive in varying habitats. While life history theory partly explains these relationships, the combined impact of resource availability and disturbance frequency on life form strategy evolution has received limited attention. We use Chamaecrista species, a legume plant lineage with a high diversity of plant life forms in the Neotropics, and employ ecological niche modeling and comparative phylogenetic methods to examine the correlated evolution of plant life forms and environmental niches. Chamaephytes and phanerophytes have optima in environments characterized by moderate water and nutrient availability coupled with infrequent fire disturbances. By contrast, annual plants thrive in environments with scarce water and nutrients, alongside frequent fire disturbances. Similarly, geophyte species also show increased resistance to frequent fire disturbances, although they thrive in resource-rich environments. Our findings shed light on the evolution of plant strategies along environmental gradients, highlighting that annuals and geophytes respond differently to high incidences of fire disturbances, with one enduring it as seeds in a resource-limited habitat and the other relying on reserves and root resprouting systems in resource-abundant habitats. Furthermore, it deepens our understanding of how organisms evolve associated with their habitats, emphasizing a constraint posed by low-resource and high-disturbance environments.

Multiple horizontal gene transfer events have shaped plant glycosyl hydrolase diversity and function

Plant glycosyl hydrolases (GHs) play a crucial role in selectively breaking down carbohydrates and glycoconjugates during various cellular processes, such as reserve mobilization, pathogen defense, and modification/disassembly of the cell wall. In this study, we examined the distribution of GH genes in the Archaeplastida supergroup, which encompasses red algae, glaucophytes, and green plants. We identified that the GH repertoire expanded from a few tens of genes in early archaeplastidians to over 400 genes in modern angiosperms, spanning 40 GH families in land plants. Our findings reveal that major evolutionary transitions were accompanied by significant changes in the GH repertoire. Specifically, we identified at least 23 GH families acquired by green plants through multiple horizontal gene transfer events, primarily from bacteria and fungi. We found a significant shift in the subcellular localization of GH activity during green plant evolution, with a marked increase in extracellular-targeted GH proteins associated with the diversification of plant cell wall polysaccharides and defense mechanisms against pathogens. In conclusion, our study sheds light on the macroevolutionary processes that have shaped the GH repertoire in plants, highlighting the acquisition of GH families through horizontal transfer and the role of GHs in plant adaptation and defense mechanisms.

NMDA glutamate receptor antagonist MK-801 induces proteome changes in adult human brain slices which are partially counteracted by haloperidol and clozapine

Deciphering the molecular pathways associated with N-methyl-D-aspartate receptor (NMDAr) hypofunction and its interaction with antipsychotics is necessary to advance our understanding of the basis of schizophrenia, as well as our capacity to treat this disease. In this regard, the development of human brain-derived models that are amenable to studying the neurobiology of schizophrenia may contribute to filling the gaps left by the widely employed animal models. Here, we assessed the proteomic changes induced by the NMDA glutamate receptor antagonist MK-801 on human brain slice cultures obtained from adult donors submitted to respective neurosurgery. Initially, we demonstrated that MK-801 diminishes NMDA glutamate receptor signaling in human brain slices in culture. Next, using mass-spectrometry-based proteomics and systems biology in silico analyses, we found that MK-801 led to alterations in proteins related to several pathways previously associated with schizophrenia pathophysiology, including ephrin, opioid, melatonin, sirtuin signaling, interleukin 8, endocannabinoid, and synaptic vesicle cycle. We also evaluated the impact of both typical and atypical antipsychotics on MK-801-induced proteome changes. Interestingly, the atypical antipsychotic clozapine showed a more significant capacity to counteract the protein alterations induced by NMDAr hypofunction than haloperidol. Finally, using our dataset, we identified potential modulators of the MK-801-induced proteome changes, which may be considered promising targets to treat NMDAr hypofunction in schizophrenia. This dataset is publicly available and may be helpful in further studies aimed at evaluating the effects of MK-801 and antipsychotics in the human brain.

Cortical folding correlates to aging and Alzheimer's Disease's cognitive and CSF biomarkers

This manuscript presents the quantification and correlation of three aspects of Alzheimer's Disease evolution, including structural, biochemical, and cognitive assessments. We aimed to test a novel structural biomarker for neurodegeneration based on a cortical folding model for mammals. Our central hypothesis is that the cortical folding variable, representative of axonal tension in white matter, is an optimal discriminator of pathological aging and correlates with altered loadings in Cerebrospinal Fluid samples and a decline in cognition and memory. We extracted morphological features from T1w 3T MRI acquisitions using FreeSurfer from 77 Healthy Controls (age = 66 ± 8.4, 69% females), 31 Mild Cognitive Impairment (age = 72 ± 4.8, 61% females), and 13 Alzheimer's Disease patients (age = 77 ± 6.1, 62% females) of recruited volunteers in Brazil to test its discriminative power using optimal cut-point analysis. Cortical folding distinguishes the groups with reasonable accuracy (Healthy Control-Alzheimer's Disease, accuracy = 0.82; Healthy Control-Mild Cognitive Impairment, accuracy = 0.56). Moreover, Cerebrospinal Fluid biomarkers (total Tau, A[Formula: see text]1-40, A[Formula: see text]1-42, and Lipoxin) and cognitive scores (Cognitive Index, Rey's Auditory Verbal Learning Test, Trail Making Test, Digit Span Backward) were correlated with the global neurodegeneration in MRI aiming to describe health, disease, and the transition between the two states using morphology.

Western diet consumption by host vertebrate promotes altered gene expression on Aedes aegypti reducing its lifespan and increasing fertility following blood feeding

BACKGROUND

The high prevalence of metabolic syndrome in low- and middle-income countries is linked to an increase in Western diet consumption, characterized by a high intake of processed foods, which impacts the levels of blood sugar and lipids, hormones, and cytokines. Hematophagous insect vectors, such as the yellow fever mosquito Aedes aegypti, rely on blood meals for reproduction and development and are therefore exposed to the components of blood plasma. However, the impact of the alteration of blood composition due to malnutrition and metabolic conditions on mosquito biology remains understudied.

METHODS

In this study, we investigated the impact of whole-blood alterations resulting from a Western-type diet on the biology of Ae. aegypti. We kept C57Bl6/J mice on a high-fat, high-sucrose (HFHS) diet for 20 weeks and followed biological parameters, including plasma insulin and lipid levels, insulin tolerance, and weight gain, to validate the development of metabolic syndrome. We further allowed Ae. aegypti mosquitoes to feed on mice and tracked how altered host blood composition modulated parameters of vector capacity.

RESULTS

Our findings identified that HFHS-fed mice resulted in reduced mosquito longevity and increased fecundity upon mosquito feeding, which correlated with alteration in the gene expression profile of nutrient sensing and physiological and metabolic markers as studied up to several days after blood ingestion.

CONCLUSIONS

Our study provides new insights into the overall effect of alterations of blood components on mosquito biology and its implications for the transmission of infectious diseases in conditions where the frequency of Western diet-induced metabolic syndromes is becoming more frequent. These findings highlight the importance of addressing metabolic health to further understand the spread of mosquito-borne illnesses in endemic areas.

Fractal basins as a mechanism for the nimble brain

An interesting feature of the brain is its ability to respond to disparate sensory signals from the environment in unique ways depending on the environmental context or current brain state. In dynamical systems, this is an example of multi-stability, the ability to switch between multiple stable states corresponding to specific patterns of brain activity/connectivity. In this article, we describe chimera states, which are patterns consisting of mixed synchrony and incoherence, in a brain-inspired dynamical systems model composed of a network with weak individual interactions and chaotic/periodic local dynamics. We illustrate the mechanism using synthetic time series interacting on a realistic anatomical brain network derived from human diffusion tensor imaging. We introduce the so-called vector pattern state (VPS) as an efficient way of identifying chimera states and mapping basin structures. Clustering similar VPSs for different initial conditions, we show that coexisting attractors of such states reveal intricately "mingled" fractal basin boundaries that are immediately reachable. This could explain the nimble brain's ability to rapidly switch patterns between coexisting attractors.

Fragmented imaginary-time evolution for early-stage quantum signal processors

Simulating quantum imaginary-time evolution (QITE) is a significant promise of quantum computation. However, the known algorithms are either probabilistic (repeat until success) with unpractically small success probabilities or coherent (quantum amplitude amplification) with circuit depths and ancillary-qubit numbers unrealistically large in the mid-term. Our main contribution is a new generation of deterministic, high-precision QITE algorithms that are significantly more amenable experimentally. A surprisingly simple idea is behind them: partitioning the evolution into a sequence of fragments that are run probabilistically. It causes a considerable reduction in wasted circuit depth every time a run fails. Remarkably, the resulting overall runtime is asymptotically better than in coherent approaches, and the hardware requirements are even milder than in probabilistic ones. Our findings are especially relevant for the early fault-tolerance stages of quantum hardware.

A molecular landscape of quiescence and proliferation highlights the role of Pten in mammary gland acinogenesis

Cell context is key for cell state. Using physiologically relevant models of laminin-rich extracellular matrix (lrECM) induction of mammary epithelial cell quiescence and differentiation, we provide a landscape of the key molecules for the proliferation-quiescence decision, identifying multiple layers of regulation at the mRNA and protein levels. Quiescence occurred despite activity of Fak (also known as PTK2), Src and phosphoinositide 3-kinases (PI3Ks), suggesting the existence of a disconnecting node between upstream and downstream proliferative signalling. Pten, a lipid and protein phosphatase, fulfils this role, because its inhibition increased proliferation and restored signalling via the Akt, mTORC1, mTORC2 and mitogen-activated protein kinase (MAPK) pathways. Pten and laminin levels were positively correlated in developing murine mammary epithelia, and Pten localized apicolaterally in luminal cells in ducts and near the nascent lumen in terminal end buds. Consistently, in three-dimensional acinogenesis models, Pten was required for triggering and sustaining quiescence, polarity and architecture. The multilayered regulatory circuitry that we uncovered provides an explanation for the robustness of quiescence within a growth-suppressive microenvironment, which could nonetheless be disrupted by perturbations in master regulators such as Pten.

Transcriptomics-Guided In Silico Drug Repurposing: Identifying New Candidates with Dual-Stage Antiplasmodial Activity

In tropical and subtropical areas, malaria stands as a profound public health challenge, causing an estimated 247 million cases worldwide annually. Given the absence of a viable vaccine, the timely and effective treatment of malaria remains a critical priority. However, the growing resistance of parasites to currently utilized drugs underscores the critical need for the identification of new antimalarial therapies. Here, we aimed to identify potential new drug candidates against Plasmodium falciparum, the main causative agent of malaria, by analyzing the transcriptomes of different life stages of the parasite and identifying highly expressed genes. We searched for genes that were expressed in all stages of the parasite's life cycle, including the asexual blood stage, gametocyte stage, liver stage, and sexual stages in the insect vector, using transcriptomics data from publicly available databases. From this analysis, we found 674 overlapping genes, including 409 essential ones. By searching through drug target databases, we discovered 70 potential drug targets and 75 associated bioactive compounds. We sought to expand this analysis to similar compounds to known drugs. So, we found a list of 1557 similar compounds, which we predicted as actives and inactives using previously developed machine learning models against five life stages of Plasmodium spp. From this analysis, two compounds were selected, and the reactions were experimentally evaluated. The compounds HSP-990 and silvestrol aglycone showed potent inhibitory activity at nanomolar concentrations against the P. falciparum 3D7 strain asexual blood stage. Moreover, silvestrol aglycone exhibited low cytotoxicity in mammalian cells, transmission-blocking potential, and inhibitory activity comparable to those of established antimalarials. These findings warrant further investigation of silvestrol aglycone as a potential dual-acting antimalarial and transmission-blocking candidate for malaria control.

Contrasting patterns of foraging behavior in neotropical stingless bees using pollen and honey metabarcoding

Stingless bees are major flower visitors in the tropics, but their foraging preferences and behavior are still poorly understood. Studying stingless bee interactions with angiosperms is methodologically challenging due to the high tropical plant diversity and inaccessibility of upper canopy flowers in forested habitats. Pollen DNA metabarcoding offers an opportunity of assessing floral visitation efficiently and was applied here to understand stingless bee floral resources spectra and foraging behavior. We analyzed pollen and honey from nests of three distantly related stingless bee species, with different body size and social behavior: Melipona rufiventris, Scaptotrigona postica and Tetragonisca angustula. Simultaneously, we evaluate the local floristic components through seventeen rapid botanical surveys conducted at different distances from the nests. We discovered a broad set of explored floral sources, with 46.3 plant species per bee species in honey samples and 53.67 in pollen samples. Plant families Myrtaceae, Asteraceae, Euphorbiaceae, Melastomataceae and Malpighiaceae dominated the records, indicating stingless bee preferences for abundant resources that flowers of these families provide in the region. Results also reinforce the preference of stingless bees for forest trees, even if only available at long distances. Our high-resolution results encourage future bee-plant studies using pollen and honey metabarcoding in hyper-diverse tropical environments.

Non-target molecular network and putative genes of flavonoid biosynthesis in Erythrina velutina Willd., a Brazilian semiarid native woody plant

Erythrina velutina is a Brazilian native tree of the Caatinga (a unique semiarid biome). It is widely used in traditional medicine showing anti-inflammatory and central nervous system modulating activities. The species is a rich source of specialized metabolites, mostly alkaloids and flavonoids. To date, genomic information, biosynthesis, and regulation of flavonoids remain unknown in this woody plant. As part of a larger ongoing research goal to better understand specialized metabolism in plants inhabiting the harsh conditions of the Caatinga, the present study focused on this important class of bioactive phenolics. Leaves and seeds of plants growing in their natural habitat had their metabolic and proteomic profiles analyzed and integrated with transcriptome data. As a result, 96 metabolites (including 43 flavonoids) were annotated. Transcripts of the flavonoid pathway totaled 27, of which EvCHI, EvCHR, EvCHS, EvCYP75A and EvCYP75B1 were identified as putative main targets for modulating the accumulation of these metabolites. The highest correspondence of mRNA vs. protein was observed in the differentially expressed transcripts. In addition, 394 candidate transcripts encoding for transcription factors distributed among the bHLH, ERF, and MYB families were annotated. Based on interaction network analyses, several putative genes of the flavonoid pathway and transcription factors were related, particularly TFs of the MYB family. Expression patterns of transcripts involved in flavonoid biosynthesis and those involved in responses to biotic and abiotic stresses were discussed in detail. Overall, these findings provide a base for the understanding of molecular and metabolic responses in this medicinally important species. Moreover, the identification of key regulatory targets for future studies aiming at bioactive metabolite production will be facilitated.

A SARS-CoV-2 Negative Antigen Rapid Diagnostic in RT-qPCR Positive Samples Correlates With a Low Likelihood of Infectious Viruses in the Nasopharynx

Severe acute respiratory syndrome-related coronavirus (SARS-CoV-2) transmission occurs even among fully vaccinated individuals; thus, prompt identification of infected patients is central to control viral circulation. Antigen rapid diagnostic tests (Ag-RDTs) are highly specific, but sensitivity is variable. Discordant RT-qPCR vs. Ag-RDT results are reported, raising the question of whether negative Ag-RDT in positive RT-qPCR samples could imply the absence of infectious viruses. To study the relationship between negative Ag-RDT results with virological, molecular, and serological parameters, we selected a cross-sectional and a follow-up dataset and analyzed virus culture, subgenomic RNA quantification, and sequencing to determine infectious viruses and mutations. We demonstrated that RT-qPCR positive while SARS-CoV-2 Ag-RDT negative discordant results correlate with the absence of infectious virus in nasopharyngeal samples. A decrease in sgRNA detection together with an expected increase in detectable anti-S and anti-N IgGs was also verified in these samples. The data clearly demonstrate that a negative Ag-RDT sample is less likely to harbor infectious SARS-CoV-2 and, consequently, has a lower transmissible potential.

Establishing a Baseline for Human Cortical Folding Morphological Variables: A Multisite Study

Differences in the way human cerebral cortices fold have been correlated to health, disease, development, and aging. However, to obtain a deeper understanding of the mechanisms that generate such differences, it is useful to derive one's morphometric variables from the first principles. This study explores one such set of variables that arise naturally from a model for universal self-similar cortical folding that was validated on comparative neuroanatomical data. We aim to establish a baseline for these variables across the human lifespan using a heterogeneous compilation of cross-sectional datasets as the first step to extending the model to incorporate the time evolution of brain morphology. We extracted the morphological features from structural MRI of 3,650 subjects: 3,095 healthy controls (CTL) and 555 patients with Alzheimer's Disease (AD) from 9 datasets, which were harmonized with a straightforward procedure to reduce the uncertainty due to heterogeneous acquisition and processing. The unprecedented possibility of analyzing such a large number of subjects in this framework allowed us to compare CTL and AD subjects' lifespan trajectories, testing if AD is a form of accelerated aging at the brain structural level. After validating this baseline from development to aging, we estimate the variables' uncertainties and show that Alzheimer's Disease is similar to premature aging when measuring global and local degeneration. This new methodology may allow future studies to explore the structural transition between healthy and pathological aging and may be essential to generate data for the cortical folding process simulations.

Socioecological vulnerability and the risk of zoonotic disease emergence in Brazil

In developing countries, outbreaks of zoonotic diseases (ZDs) result from intertwined ecological, socioeconomic, and demographic processes that shape conditions for (i) increased contact between vulnerable human population and wildlife in areas undergoing environmental degradation and (ii) the rapid geographic spread of infections across socially vulnerable regions. In Brazil, recent increases in environmental and social vulnerabilities, amplified by economic and political crises, are potential triggers for outbreaks. We discuss Brazilian features that favor outbreaks and show a novel quantitative method for zoonotic risk assessment. Using data on nine ZDs from 2001 to 2019, we found that the most significant causal variables were vegetation cover and city remoteness. Furthermore, 8 of 27 states presented low-level risk of ZD outbreaks. Given the ZD-bushmeat connection, we identified central hunted mammals that should be surveilled to prevent spillover events. The current challenge is to coordinate intersectoral collaboration for effective One Health management in megadiverse countries with high social vulnerability and growing environmental degradation like Brazil.

Experimental test of quantum causal influences

Since Bell's theorem, it is known that local realism fails to explain quantum phenomena. Bell inequality violations manifestly show the incompatibility of quantum theory with classical notions of cause and effect. As recently found, however, the instrumental scenario-a pivotal tool in causal inference-allows for nonclassicality signatures going beyond this paradigm. If we are not limited to observational data and can intervene in our setup, then we can witness quantum violations of classical bounds on the causal influence among the involved variables even when no Bell-like violation is possible. That is, through interventions, the quantum behavior of a system that would seem classical can be demonstrated. Using a photonic setup-faithfully implementing the instrumental causal structure and switching between observation and intervention run by run-we experimentally witness such a nonclassicality. We also test quantum bounds for the causal influence, showing that they provide a reliable tool for quantum causal modeling.

Ecological and environmental factors affecting transmission of sylvatic yellow fever in the 2017-2019 outbreak in the Atlantic Forest, Brazil

BACKGROUND

Yellow fever virus (YFV) is an arbovirus that, despite the existence of a safe and effective vaccine, continues to cause outbreaks of varying dimensions in the Americas and Africa. Between 2017 and 2019, Brazil registered un unprecedented sylvatic YFV outbreak whose severity was the result of its spread into zones of the Atlantic Forest with no signals of viral circulation for nearly 80 years.

METHODS

To investigate the influence of climatic, environmental, and ecological factors governing the dispersion and force of infection of YFV in a naïve area such as the landscape mosaic of Rio de Janeiro (RJ), we combined the analyses of a large set of data including entomological sampling performed before and during the 2017-2019 outbreak, with the geolocation of human and nonhuman primates (NHP) and mosquito infections.

RESULTS

A greater abundance of Haemagogus mosquitoes combined with lower richness and diversity of mosquito fauna increased the probability of finding a YFV-infected mosquito. Furthermore, the analysis of functional traits showed that certain functional groups, composed mainly of Aedini mosquitoes which includes Aedes and Haemagogus mosquitoes, are also more representative in areas where infected mosquitoes were found. Human and NHP infections were more common in two types of landscapes: large and continuous forest, capable of harboring many YFV hosts, and patches of small forest fragments, where environmental imbalance can lead to a greater density of the primary vectors and high human exposure. In both, we show that most human infections (~ 62%) occurred within an 11-km radius of the finding of an infected NHP, which is in line with the flight range of the primary vectors.

CONCLUSIONS

Together, our data suggest that entomological data and landscape composition analyses may help to predict areas permissive to yellow fever outbreaks, allowing protective measures to be taken to avoid human cases.

Water tank and swimming pool detection based on remote sensing and deep learning: Relationship with socioeconomic level and applications in dengue control

Studies have shown that areas with lower socioeconomic standings are often more vulnerable to dengue and similar deadly diseases that can be spread through mosquitoes. This study aims to detect water tanks installed on rooftops and swimming pools in digital images to identify and classify areas based on the socioeconomic index, in order to assist public health programs in the control of diseases linked to the Aedes aegypti mosquito. This study covers four regions of Campinas, São Paulo, characterized by different socioeconomic contexts. With mosaics of images obtained by a 12.1 MP Canon PowerShot S100 (5.2 mm focal length) carried by unmanned aerial vehicles, we developed deep learning algorithms in the scope of computer vision for the detection of water tanks and swimming pools. An object detection model, which was initially created for areas of Belo Horizonte, Minas Gerais, was enhanced using the transfer learning technique, and allowed us to detect objects in Campinas with fewer samples and more efficiency. With the detection of objects in digital images, the proportions of objects per square kilometer for each region studied were estimated by adopting a Chi-square distribution model. Thus, we found that regions with low socioeconomic status had more exposed water tanks, while regions with high socioeconomic levels had more exposed pools. Using deep learning approaches, we created a useful tool for Ae. aegypti control programs to utilize and direct disease prevention efforts. Therefore, we concluded that it is possible to detect objects directly related to the socioeconomic level of a given region from digital images, which encourages the practicality of this approach for studies aimed towards public health.

Is there a place for mesenchymal stromal cell-based therapies in the therapeutic armamentarium against COVID-19?

The COVID-19 pandemic, caused by the rapid global spread of the novel coronavirus (SARS-CoV-2), has caused healthcare systems to collapse and led to hundreds of thousands of deaths. The clinical spectrum of COVID-19 is not only limited to local pneumonia but also represents multiple organ involvement, with potential for systemic complications. One year after the pandemic, pathophysiological knowledge has evolved, and many therapeutic advances have occurred, but mortality rates are still elevated in severe/critical COVID-19 cases. Mesenchymal stromal cells (MSCs) can exert immunomodulatory, antiviral, and pro-regenerative paracrine/endocrine actions and are therefore promising candidates for MSC-based therapies. In this review, we discuss the rationale for MSC-based therapies based on currently available preclinical and clinical evidence of safety, potential efficacy, and mechanisms of action. Finally, we present a critical analysis of the risks, limitations, challenges, and opportunities that place MSC-based products as a therapeutic strategy that may complement the current arsenal against COVID-19 and reduce the pandemic's unmet medical needs.

High prevalence of symptoms among Brazilian subjects with antibodies against SARS-CoV-2

Since the beginning of the pandemic of COVID-19, there has been a widespread assumption that most infected persons are asymptomatic. Using data from the recent wave of the EPICOVID19 study, a nationwide household-based survey including 133 cities from all states of Brazil, we estimated the proportion of people with and without antibodies for SARS-CoV-2 who were asymptomatic, which symptoms were most frequently reported, number of symptoms and the association with socio-demographic characteristics. We tested 33,205 subjects using a rapid antibody test previously validated. Information was collected before participants received the test result. Out of 849 (2.7%) participants positive for SARS-CoV-2 antibodies, only 12.1% (95% CI 10.1-14.5) reported no symptoms, compared to 42.2% (95% CI 41.7-42.8) among those negative. The largest difference between the two groups was observed for changes in smell/taste (56.5% versus 9.1%, a 6.2-fold difference). Changes in smell/taste, fever and body aches were most likely to predict positive tests as suggested by recursive partitioning tree analysis. Among individuals without any of these three symptoms, only 0.8% tested positive, compared to 18.3% of those with both fever and changes in smell or taste. Most subjects with antibodies against SARS-CoV-2 are symptomatic, even though most present only mild symptoms.

Reboot: a straightforward approach to identify genes and splicing isoforms associated with cancer patient prognosis

Nowadays, the massive amount of data generated by modern sequencing technologies provides an unprecedented opportunity to find genes associated with cancer patient prognosis, connecting basic and translational research. However, treating high dimensionality of gene expression data and integrating it with clinical variables are major challenges to perform these analyses. Here, we present Reboot, an integrative approach to find and validate genes and transcripts (splicing isoforms) associated with cancer patient prognosis from high dimensional expression datasets. Reboot innovates by using a multivariate strategy with penalized Cox regression (LASSO method) combined with a bootstrap approach, in addition to statistical tests and plots to support the findings. Applying Reboot on data from 154 glioblastoma patients, we identified a three-gene signature (IKBIP, OSMR, PODNL1) whose increased derived risk score was significantly associated with worse patients' prognosis. Similarly, Reboot was able to find a seven-splicing isoforms signature related to worse overall survival in 177 pancreatic adenocarcinoma patients with elevated risk scores after uni- and multivariate analyses. In summary, Reboot is an efficient, intuitive and straightforward way of finding genes or splicing isoforms signatures relevant to patient prognosis, which can democratize this kind of analysis and shed light on still under-investigated cancer-related genes and splicing isoforms.

Water constraints drive allometric patterns in the body shape of tree frogs

The origin of morphological diversity is a critical question in evolutionary biology. Interactions between the environment and developmental processes have determining roles in morphological diversity, creating patterns through space and over time. Also, the shape of organisms tends to vary with increasing size as a result of those developmental processes, known as allometry. Several studies have demonstrated that the body sizes of anurans are associated with hydric conditions in their environments and that localities with high water stress tend to select for larger individuals. However, how environmental conditions alter those patterns of covariance between size and shape is still elusive. We used 3D geometric morphometric analyses, associated with phylogenetic comparative methods, to determine if the morphological variations and allometric patterns found in Arboranae (Anura) is linked to water conservation mechanisms. We found effects of the hydric stress on the shape of Arboranae species, favouring globular shapes. Also, the allometric patterns varied in intensity according to the water stress gradient, being particularly relevant for smaller frogs, and more intense in environments with higher water deficits. Our study provides empirical evidence that more spherical body shapes, especially among smaller species, reflect an important adaptation of anurans to water conservation in water-constrained environments.

Nucleosome landscape reflects phenotypic differences in Trypanosoma cruzi life forms

Trypanosoma cruzi alternates between replicative and nonreplicative life forms, accompanied by a shift in global transcription levels and by changes in the nuclear architecture, the chromatin proteome and histone posttranslational modifications. To gain further insights into the epigenetic regulation that accompanies life form changes, we performed genome-wide high-resolution nucleosome mapping using two T. cruzi life forms (epimastigotes and cellular trypomastigotes). By combining a powerful pipeline that allowed us to faithfully compare nucleosome positioning and occupancy, more than 125 thousand nucleosomes were mapped, and approximately 20% of them differed between replicative and nonreplicative forms. The nonreplicative forms have less dynamic nucleosomes, possibly reflecting their lower global transcription levels and DNA replication arrest. However, dynamic nucleosomes are enriched at nonreplicative regulatory transcription initiation regions and at multigenic family members, which are associated with infective-stage and virulence factors. Strikingly, dynamic nucleosome regions are associated with GO terms related to nuclear division, translation, gene regulation and metabolism and, notably, associated with transcripts with different expression levels among life forms. Finally, the nucleosome landscape reflects the steady-state transcription expression: more abundant genes have a more deeply nucleosome-depleted region at putative 5' splice sites, likely associated with trans-splicing efficiency. Taken together, our results indicate that chromatin architecture, defined primarily by nucleosome positioning and occupancy, reflects the phenotypic differences found among T. cruzi life forms despite the lack of a canonical transcriptional control context.

Photobiomodulation drives pericyte mobilization towards skin regeneration

Photobiomodulation is being widely applied for improving dermal or mucosal wound healing. However, the underlying cellular and molecular processes that directly contribute to its effects remain poorly understood. Pericytes are relevant cells involved in the wound microenvironment and could be one of the main targets of photobiomodulation due to their plasticity and perivascular localization. Herein, we investigate tissue repair under the photobiomodulation stimulus using a pericyte labeled (or reporter) transgenic mice. Using a model of two contralateral back wounds, one the control and the other photoactivated daily (660 nm, 20 mW, 0.71 W/cm2, 5 J/cm2, 7 s, 0.14 J), we showed an overall influx of immune and undifferentiated cells and higher mobilization of a potent pericyte subpopulation (Type-2 pericytes) in the photoactivated wounds in comparison to the controls. Doppler analysis showed a significant increase in the blood flow in the photoactivated wounds, while marked vascular supply was observed histologically. Histochemical analysis has indicated more advanced stages of tissue repair after photoactivation. These data suggest that photobiomodulation significantly accelerates tissue repair through its vascular effects with direct recruitment of pericytes to the injury site.

Novel xylose transporter Cs4130 expands the sugar uptake repertoire in recombinant Saccharomyces cerevisiae strains at high xylose concentrations

BACKGROUND

The need to restructure the world's energy matrix based on fossil fuels and mitigate greenhouse gas emissions stimulated the development of new biobased technologies for renewable energy. One promising and cleaner alternative is the use of second-generation (2G) fuels, produced from lignocellulosic biomass sugars. A major challenge on 2G technologies establishment is the inefficient assimilation of the five-carbon sugar xylose by engineered Saccharomyces cerevisiae strains, increasing fermentation time. The uptake of xylose across the plasma membrane is a critical limiting step and the budding yeast S. cerevisiae is not designed with a broad transport system and regulatory mechanisms to assimilate xylose in a wide range of concentrations present in 2G processes.

RESULTS

Assessing diverse microbiomes such as the digestive tract of plague insects and several decayed lignocellulosic biomasses, we isolated several yeast species capable of using xylose. Comparative fermentations selected the yeast Candida sojae as a potential source of high-affinity transporters. Comparative genomic analysis elects four potential xylose transporters whose properties were evaluated in the transporter null EBY.VW4000 strain carrying the xylose-utilizing pathway integrated into the genome. While the traditional xylose transporter Gxf1 allows an improved growth at lower concentrations (10 g/L), strains containing Cs3894 and Cs4130 show opposite responses with superior xylose uptake at higher concentrations (up to 50 g/L). Docking and normal mode analysis of Cs4130 and Gxf1 variants pointed out important residues related to xylose transport, identifying key differences regarding substrate translocation comparing both transporters.

CONCLUSIONS

Considering that xylose concentrations in second-generation hydrolysates can reach high values in several designed processes, Cs4130 is a promising novel candidate for xylose uptake. Here, we demonstrate a novel eukaryotic molecular transporter protein that improves growth at high xylose concentrations and can be used as a promising target towards engineering efficient pentose utilization in yeast.

Data-driven study of the COVID-19 pandemic via age-structured modelling and prediction of the health system failure in Brazil amid diverse intervention strategies

In this work we propose a data-driven age-structured census-based SIRD-like epidemiological model capable of forecasting the spread of COVID-19 in Brazil. We model the current scenario of closed schools and universities, social distancing of people above sixty years old and voluntary home quarantine to show that it is still not enough to protect the health system by explicitly computing the demand for hospital intensive care units. We also show that an urgent intense quarantine might be the only solution to avoid the collapse of the health system and, consequently, to minimize the quantity of deaths. On the other hand, we demonstrate that the relaxation of the already imposed control measures in the next days would be catastrophic.

The Brazilian Reproducibility Initiative

Most efforts to estimate the reproducibility of published findings have focused on specific areas of research, even though science is usually assessed and funded on a regional or national basis. Here we describe a project to assess the reproducibility of findings in biomedical science published by researchers based in Brazil. The Brazilian Reproducibility Initiative is a systematic, multicenter effort to repeat between 60 and 100 experiments: the project will focus on a set of common methods, repeating each experiment in three different laboratories from a countrywide network. The results, due in 2021, will allow us to estimate the level of reproducibility of biomedical science in Brazil, and to investigate what aspects of the published literature might help to predict whether a finding is reproducible.