The role of flow velocity combined with habitat complexity as a top–down regulator in seagrass meadows

Large‐scale losses of seagrass areas have been associated with eutrophication events, which have led to an overproduction of photosynthetic organisms including epiphytes. Grazers that feed on epiphytes can exert a significant top–down control in the system, but the effects of physical factors on grazing activity and feeding behaviour have been rarely examined. We addressed the combination of hydrodynamic regime and seagrass shoot density can alter the feeding and foraging behaviours of mesograzers. A full factorial experiment, with flow velocity (high, medium and low) and shoot density (high versus low) as main factors, was conducted in a racetrack flume using artificial seagrass plots. The results showed that when high flow velocity conditions were combined with low shoot density, consumption of epiphytes by mesograzers was strongly reduced. In contrast, when flow velocity was low or shoot density was high, mesograzers exhibited high feeding rates and vigorous swimming behaviour. These results clearly indicate that hydrodynamic stress reduces the time that mesograzers can spend feeding, since it inhibits their swimming behaviour, and thus indirectly affecting to the density of epiphytes. Therefore, the triggering of trophic cascade effects in seagrass communities under these experimental conditions depended on the interrelationship and feedbacks among shoot density, abiotic (flow velocity) and biotic (epiphytes and mesograzers) compartments, with flow velocity exerting a top–down control on seagrass ecosystems.     

Influence of Socioeconomic Factors on the Knowledge and Consumption of Firewood in the Atlantic Forest of Northeast Brazil

Economic Botany - We aim to evaluate whether socioeconomic factors influence the knowledge, use, preference, and consumption of firewood in a rural community in Northeast Brazil. We conducted...     

Biology of Bactrocera carambolae (Diptera: Tephritidae) on four hosts

Bactrocera carambolae is a quarantine pest found in Brazil, restricted to the states of Amapá, Pará and Roraima. This fruit fly can potentially cause extensive socioeconomic and environmental damage in the country, if it disperse into areas where fruit is grown for exporting. The objective of this work was to study the biology of B. carambolae on fruits of Averrhoa carambola L. (Oxalidaceae), Psidium guajava L. (Myrtaceae), Spondias mombin L. (Anacardiaceae) and Eugenia stipitata McVaugh (Myrtaceae). The following parameters were investigated: duration of egg-larva, pupal, egg-adult, pre-oviposition, oviposition and post-oviposition periods, pupal weight and viability, sex ratio, fecundity, fertility and longevity. All parameters except pupal weight, oviposition and post-oviposition period, egg fertility and sex ratio were influenced by the host plant on which the larvae were reared. The carambola fruit fly completes its development on all those hosts studied here, with the highest fecundities on A. carambola and P. guajava.     

The double-stranded RNA-binding protein,Staufen1, is an IRES-transacting factor regulating HIV-1 cap-independent translation initiation

Translation initiation of the viral genomic mRNA (vRNA) of human immunodeficiency virus-type 1 (HIV-1) can be mediated by a cap- or an internal ribosome entry site (IRES)-dependent mechanism. A previous report shows that Staufen1, a cellular double-stranded (ds) RNA-binding protein (RBP), binds to the 5’untranslated region (5′UTR) of the HIV-1 vRNA and promotes its cap-dependent translation. In this study, we now evaluate the role of Staufen1 as an HIV-1 IRES-transacting factor (ITAF). We first confirm that Staufen1 associates with both the HIV-1 vRNA and the Gag protein during HIV-1 replication. We found that in HIV-1-expressing cells, siRNA-mediated depletion of Staufen1 reduces HIV-1 vRNA translation. Using dual-luciferase bicistronic mRNAs, we show that the siRNA-mediated depletion and cDNA-mediated overexpression of Staufen1 acutely regulates HIV-1 IRES activity. Furthermore, we show that Staufen1-vRNA interaction is required for the enhancement of HIV-1 IRES activity. Interestingly, we find that only Staufen1 harboring an intact dsRNA-binding domain 3 (dsRBD3) rescues HIV-1 IRES activity in Staufen1 CRISPR-Cas9 gene edited cells. Finally, we show that the expression of Staufen1-dsRBD3 alone enhances HIV-1 IRES activity. This study provides evidence of a novel role for Staufen1 as an ITAF promoting HIV-1 vRNA IRES activity.     

In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes

The human immune system consists of a highly intelligent network of billions of independent, self-organized cells that interact with each other. Machine learning (ML) is an artificial intelligence (AI) tool that automatically processes huge amounts of image data. Immunotherapies have revolutionized the treatment of blood cancer. Specifically, one such therapy involves engineering immune cells to express chimeric antigen receptors (CAR), which combine tumor antigen specificity with immune cell activation in a single receptor. To improve their efficacy and expand their applicability to solid tumors, scientists optimize different CARs with different modifications. However, predicting and ranking the efficacy of different "off-the-shelf" immune products (e.g., CAR or Bispecific T-cell Engager [BiTE]) and selection of clinical responders are challenging in clinical practice. Meanwhile, identifying the optimal CAR construct for a researcher to further develop a potential clinical application is limited by the current, time-consuming, costly, and labor-intensive conventional tools used to evaluate efficacy. Particularly, more than 30 years of immunological synapse (IS) research data demonstrate that T cell efficacy is not only controlled by the specificity and avidity of the tumor antigen and T cell interaction, but also it depends on a collective process, involving multiple adhesion and regulatory molecules, as well as tumor microenvironment, spatially and temporally organized at the IS formed by cytotoxic T lymphocytes (CTL) and natural killer (NK) cells. The optimal function of cytotoxic lymphocytes (including CTL and NK) depends on IS quality. Recognizing the inadequacy of conventional tools and the importance of IS in immune cell functions, we investigate a new strategy for assessing CAR-T efficacy by quantifying CAR IS quality using the glass-support planar lipid bilayer system combined with ML-based data analysis. Previous studies in our group show that CAR-T IS quality correlates with antitumor activities in vitro and in vivo. However, current manually quantified IS quality data analysis is time-consuming and labor-intensive with low accuracy, reproducibility, and repeatability. In this study, we develop a novel ML-based method to quantify thousands of CAR cell IS images with enhanced accuracy and speed. Specifically, we used artificial neural networks (ANN) to incorporate object detection into segmentation. The proposed ANN model extracts the most useful information to differentiate different IS datasets. The network output is flexible and produces bounding boxes, instance segmentation, contour outlines (borders), intensities of the borders, and segmentations without borders. Based on requirements, one or a combination of this information is used in statistical analysis. The ML-based automated algorithm quantified CAR-T IS data correlates with the clinical responder and non-responder treated with Kappa-CAR-T cells directly from patients. The results suggest that CAR cell IS quality can be used as a potential composite biomarker and correlates with antitumor activities in patients, which is sufficiently discriminative to further test the CAR IS quality as a clinical biomarker to predict response to CAR immunotherapy in cancer. For translational research, the method developed here can also provide guidelines for designing and optimizing numerous CAR constructs for potential clinical development.Trial Registration: ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00881920","term_id":"NCT00881920"}}NCT00881920.