Interplay between Inflammaging, Frailty and Nutrition in Covid-19: Preventive and Adjuvant Treatment Perspectives.

As humans age, their immune system undergoes modifications, including a low-grade inflammatory status called inflammaging. These changes are associated with a loss of physical and immune resilience, amplifying the risk of being malnourished and frail. Under the COVID-19 scenario, inflammaging increases the susceptibility to poor prognostics. We aimed to bring the current concepts of inflammaging and its relationship with frailty and COVID-19 prognostic; highlight the importance of evaluating the nutritional risk together with frailty aiming to monitor older adults in COVID-19 scenario; explore some compounds with potential to modulate inflammaging in perspective to manage the COVID-19 infection. Substances such as probiotics and senolytics can help reduce the high inflammatory status. Also, the periodic evaluation of nutrition risk and frailty will allow interventions, assuring the appropriate care.

Glypican-3 reexpression regulates apoptosis in murine adenocarcinoma mammary cells modulating PI3K/Akt and p38MAPK signaling pathways.

Glypican-3 (GPC3) is a proteoglycan involved in proliferation and cell survival. Several reports demonstrated that GPC3 is downregulated in some tumors, such as breast cancer. Previously, we determined that GPC3 reexpression in the murine mammary adenocarcinoma LM3 cells induced an impairment of their invasive and metastatic capacities, associated with a decrease of their motility and an increase of their cell death. We demonstrated that GPC3 inhibits canonical Wnt signaling, as well as it activates non canonical pathway. Now, we identified signaling pathways responsible for the pro-apoptotic role of GPC3 in LM3 cells. We found for the first time that GPC3 inhibits the PI3K/Akt anti-apoptotic pathway while it stimulates the p38MAPK stress-activated one. We report a concomitant modulation of CDK inhibitors as well as of pro- and anti-apoptotic molecules. Our results provide new clues regarding the mechanism involved in the modulation induced by GPC3 of mammary tumor cell growth and survival.

NUCEL (Cell and Molecular Therapy Center): a multidisciplinary center for translational research in Brazil.

Social and economical development is closely associated with technological innovation and a well-developed biotechnological industry. In the last few years, Brazil's scientific production has been steadily increasing; however, the number of patents is lagging behind, with technological and translational research requiring governmental incentive and reinforcement. The Cell and Molecular Therapy Center (NUCEL) was created to develop activities in the translational research field, addressing concrete problems found in biomedical and veterinary areas and actively searching for solutions by employing a genetic engineering approach to generate cell lines over-expressing recombinant proteins to be transferred to local biotech companies, aiming at furthering the development of a national competence for local production of biopharmaceuticals of widespread use and of life-saving importance. To this end, mammalian cell engineering technologies were used to generate cell lines over-expressing several different recombinant proteins of biomedical and biotechnological interest, namely, recombinant human Amylin/IAPP for diabetes treatment, human FVIII and FIX clotting factors for hemophilia, human and bovine FSH for fertility and reproduction, and human bone repair proteins (BMPs). Expression of some of these proteins is also being sought with the baculovirus/insect cell system (BEVS) which, in many cases, is able to deliver high-yield production of recombinant proteins with biological activity comparable to that of mammalian systems, but in a much more cost-effective manner. Transfer of some of these recombinant products to local Biotech companies has been pursued by taking advantage of the São Paulo State Foundation (FAPESP) and Federal Government (FINEP, CNPq) incentives for joint Research Development and Innovation partnership projects.

Time-varying modeling of gene expression regulatory networks using the wavelet dynamic vector autoregressive method.

MOTIVATION: A variety of biological cellular processes are achieved through a variety of extracellular regulators, signal transduction, protein-protein interactions and differential gene expression. Understanding of the mechanisms underlying these processes requires detailed molecular description of the protein and gene networks involved. To better understand these molecular networks, we propose a statistical method to estimate time-varying gene regulatory networks from time series microarray data. One well known problem when inferring connectivity in gene regulatory networks is the fact that the relationships found constitute correlations that do not allow inferring causation, for which, a priori biological knowledge is required. Moreover, it is also necessary to know the time period at which this causation occurs. Here, we present the Dynamic Vector Autoregressive model as a solution to these problems. RESULTS: We have applied the Dynamic Vector Autoregressive model to estimate time-varying gene regulatory networks based on gene expression profiles obtained from microarray experiments. The network is determined entirely based on gene expression profiles data, without any prior biological knowledge. Through construction of three gene regulatory networks (of p53, NF-kappaB and c-myc) for HeLa cells, we were able to predict the connectivity, Granger-causality and dynamics of the information flow in these networks. SUPPLEMENTARY INFORMATION: Additional figures may be found at http://mariwork.iq.usp.br/dvar/.

CaSPredictor: a new computer-based tool for caspase substrate prediction.

MOTIVATION: In vitro studies have shown that the most remarkable catalytic features of caspases, a family of cysteineproteases, are their stringent specificity to Asp (D) in the S1 subsite and at least four amino acids to the left of scissile bound. However, there is little information about the substrate recognition patterns in vivo. The prediction and characterization of proteolytic cleavage sites in natural substrates could be useful for uncovering these structural relationships. RESULTS: PEST-like sequences rich in the amino acids Ser (S), Thr (T), Pro (P), Glu or Asp (E/D), including Asn (N) and Gln (Q) are adjacent structural/sequential elements in the majority of cleavage site regions of the natural caspase substrates described in the literature, supporting its possible implication in the substrate selection by caspases. We developed CaSPredictor, a software which incorporated a PEST-like index and the position-dependent amino acid matrices for prediction of caspase cleavage sites in individual proteins and protein datasets. The program predicted successfully 81% (111/137) of the cleavage sites in experimentally verified caspase substrates not annotated in its internal data file. Its accuracy and confidence was estimated as 80% using ROC methodology. The program was much more efficient in predicting caspase substrates when compared with PeptideCutter and PEPS software. Finally, the program detected potential cleavage sites in the primary sequences of 1644 proteins in a dataset containing 9986 protein entries. AVAILABILITY: Requests for software should be made to Dr José E. Belizário SUPPLEMENTARY INFORMATION: Supplementary information is available for academic users at site http://icb.usp.br/~farmaco/Jose/CaSpredictorfiles.