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Biology subjects

Rocha, J. C.

Publications and source records attributed to Rocha, J. C..

5 recordsLinked to original sources

Biosphere functional integrity for people and Planet

Defining a safe and just biosphere space requires a synthetic scaleable measure of biosphere functional integrity to secure Natures Contributions to People (NCP). Using a systematic review of 153 peer-reviewed studies we estimated the minimum level of functional integrity needed to secure multiple critical NCP, including pollination, pest and disease control, water quality regulation, soil protection, recreation and natural hazards mitigation in human-modified landscapes. We characterise functional integrity by the quantity, quality and spatial configuration of (semi-)natural habitat within any landscape. We find that at least 20-25% of structurally complex and biologically diverse (semi-)natural habitat in each 1 km2 of land area is needed to maintain the supply of multiple NCP simultaneously. Exact quantity, quality and spatial configuration required is dependent on local context, and may differ for individual NCP. Today, about 50-60% of human-modified lands have less than 10% and 20% (semi-)natural habitat per 1 km2 respectively. These areas require immediate attention to regenerate functional integrity in order to secure ecological functioning in those landscapes.

ecology↗

Gut microbiota diversity and C-Reactive Protein are predictors of disease severity in COVID-19 patients

Risk factors for COVID-19 disease severity are still poorly understood. Considering the pivotal role of gut microbiota on host immune and inflammatory functions, we investigated the association between changes in gut microbiota composition and the clinical severity of COVID-19. We conducted a multicentre cross-sectional study prospectively enrolling 115 COVID-19 patients categorized according to: 1) WHO Clinical Progression Scale - mild 19 (16.5%), moderate 37 (32.2%) or severe 59 (51.3%); and 2) location of recovery from COVID-19 - ambulatory 14 (household isolation; 12.2%), hospitalized in ward 40 (34.8%) or intensive care unit 61 (53.0%). Gut microbiota analysis was performed through 16S rRNA gene sequencing and data obtained was further related with clinical parameters of COVID-19 patients. Risk factors for COVID-19 severity were identified by univariate and multivariable logistic regression models. In comparison with mild COVID-19 patients, the gut microbiota of moderate and severe patients has: a) lower Firmicutes/Bacteroidetes ratio, b) higher abundance of Proteobacteria; and c) lower abundance of beneficial butyrate-producing bacteria such as Roseburia and Lachnospira genera. Multivariable regression analysis showed that Shannon index diversity (odds ratio [OR] 2.85 [95% CI 1.09-7.41]; p=0.032) and C-Reactive Protein (OR 3.45 [95% CI 1.33-8.91]; p=0.011) were risk factors for COVID-19 severe disease (a score of 6 or higher in WHO clinical progression scale). In conclusion, our results demonstrated that hospitalised moderate and severe COVID-19 patients have microbial signatures of gut dysbiosis and for the first time, the gut microbiota diversity is pointed out as a prognostic biomarker for COVID-19 disease severity.

microbiology↗

Distinct Sources of a Bovine Blastocyst Digital Image do not Produce the Same Classification by a Previously Trained Software using Artificial Neural Network

We develop an online graphical and intuitive interface connected to a server aiming to facilitate access to professionals worldwide that face problems with bovine blastocysts classification. The interface Blasto3Q (3Q is referred to the three qualities of the blastocyst grading) contains a description of 24 variables that are extracted from the image of the blastocyst and analyzed by three Artificial Neural Networks (ANNs) that classifies the same loaded image. The same embryo (i.e., the biological specimen) was submitted to digital image capture by the control group (inverted microscope with 40x of magnification) and to experimental group (stereomicroscope with maximum of magnification plus 4x zoom from the cell phone). The 36 images obtained from control and experimental groups were uploaded on the Blasto3Q. Each image from both sources was evaluated for segmentation and submitted (only if it could be properly or partially segmented) to the quality grade classification by the three ANNs of the Blasto3Q program. In the group control, all the images were properly segmented, whereas 38.9% (07/18) and 61.1% (11/18) of the images from the experimental group, respectively could not be segmented or were partially segmented. The percentage of agreement was calculated when the same blastocyst was evaluated by the same ANN from the two sources (control and experimental groups). On the 54 potential evaluations of the three ANNs (i.e., 18 images been evaluated by the three networks) from the experimental group only 22.2% agreed with evaluations of the control (12/54). Of the remaining 42 disagreed evaluations from experimental group, 21 were unable to be performed and 21 were wrongly processed when compared with control evaluation.

developmental biology↗

Cascading regime shifts within and across scales

Regime shifts are large, abrupt and persistent critical transitions in the function and structure of systems (1, 2). Yet it is largely unknown how these transitions will interact, whether the occurrence of one will increase the likelihood of another, or simply correlate at distant places. Here we explore two types of cascading effects: domino effects create one-way dependencies, while hidden feedbacks produce two-way interactions; and compare them with the control case of driver sharing which can induce correlations. Using 30 regime shifts described as networks, we show that 45% of the pair-wise combinations of regime shifts present at least one plausible structural interdependence. Driver sharing is more common in aquatic systems, while hidden feedbacks are more commonly found in terrestrial and Earth systems tipping points. The likelihood of cascading effects depends on cross-scale interactions, but differs for each cascading effect type. Regime shifts should not be studied in isolation: instead, methods and data collection should account for potential teleconnections.

ecology↗

Mapping Social Ecological Systems Archetypes

While sustainable development goals are by their nature global, their achievement requires local action and thus targeting and monitoring sustainable solutions tailored to different social and ecological contexts. Ostrom stressed that there are no panaceas or universal solutions to environmental problems, and developed a social-ecological systems (SES) framework -a nested multi-tier set of variables- to help diagnose problems, identify complex interactions, and solutions tailored to each SES arena. The framework has been applied to over a hundred cases, typically reflecting in-depth analysis of local case studies, but with relatively small coverage in space and time. While case studies are context rich and necessary, it can be difficult to upscale their lessons to policy making realms. Here we develop a data driven method for upscaling Ostroms SES framework and apply it to a context where data is scarce, incomplete, but also where sustainable solutions are needed. The purpose of upscaling the framework is to create a tool that facilitates decision-making on data scarce contexts such as developing countries. We mapped SES by applying the SES framework to poverty alleviation and food security issues in the Volta River basin in Ghana and Burkina Faso. We found archetypical configurations of SES in space. Given data availability, we study their change over time, and discuss where agricultural innovations such as water reservoirs might have a stronger impact at increasing food security and therefore alleviating poverty and hunger. We conclude by outlining how the method can be used in other SES comparative studies.

ecology↗