Modeling the Winter–to–Summer Transition of Prokaryotic and Viral Abundance in the Arctic Ocean

One of the challenges in oceanography is to understand the influence of environmental factors on the abundances of prokaryotes and viruses. Generally, conventional statistical methods resolve trends well, but more complex relationships are difficult to explore. In such cases, Artificial Neural Networks (ANNs) offer an alternative way for data analysis. Here, we developed ANN-based models of prokaryotic and viral abundances in the Arctic Ocean. The models were used to identify the best predictors for prokaryotic and viral abundances including cytometrically-distinguishable populations of prokaryotes (high and low nucleic acid cells) and viruses (high- and low-fluorescent viruses) among salinity, temperature, depth, day length, and the concentration of Chlorophyll-a. The best performing ANNs to model the abundances of high and low nucleic acid cells used temperature and Chl-a as input parameters, while the abundances of high- and low-fluorescent viruses used depth, Chl-a, and day length as input parameters. Decreasing viral abundance with increasing depth and decreasing system productivity was captured well by the ANNs. Despite identifying the same predictors for the two populations of prokaryotes and viruses, respectively, the structure of the best performing ANNs differed between high and low nucleic acid cells and between high- and low-fluorescent viruses. Also, the two prokaryotic and viral groups responded differently to changes in the predictor parameters; hence, the cytometric distinction between these populations is ecologically relevant. The models imply that temperature is the main factor explaining most of the variation in the abundances of high nucleic acid cells and total prokaryotes and that the mechanisms governing the reaction to changes in the environment are distinctly different among the prokaryotic and viral populations.     

Birth spacing and infant mortality in Brazil

The effects of birth spacing on neonatal and post-neonatal mortality in Brazil were found to be very consistent with models based on data from other South American countries. The model for neonatal mortality simplified to three significant variables, whereas the model for post-neonatal mortality included four significant interactions.     

Interleukin‐37 improves T‐cell‐mediated immunity and chimeric antigen receptor T‐cell therapy in aged backgrounds

Aging‐associated declines in innate and adaptive immune responses are well documented and pose a risk for the growing aging population, which is predicted to comprise greater than 40 percent of the world''s population by 2050. Efforts have been made to improve immunity in aged populations; however, safe and effective protocols to accomplish this goal have not been universally established. Aging‐associated chronic inflammation is postulated to compromise immunity in aged mice and humans. Interleukin‐37 (IL‐37) is a potent anti‐inflammatory cytokine, and we present data demonstrating that IL‐37 gene expression levels in human monocytes significantly decline with age. Furthermore, we demonstrate that transgenic expression of interleukin‐37 (IL‐37) in aged mice reduces or prevents aging‐associated chronic inflammation, splenomegaly, and accumulation of myeloid cells (macrophages and dendritic cells) in the bone marrow and spleen. Additionally, we show that IL‐37 expression decreases the surface expression of programmed cell death protein 1 (PD‐1) and augments cytokine production from aged T‐cells. Improved T‐cell function coincided with a youthful restoration of Pdcd1, Lat, and Stat4 gene expression levels in CD4⁺ T‐cells and Lat in CD8⁺ T‐cells when aged mice were treated with recombinant IL‐37 (rIL‐37) but not control immunoglobin (Control Ig). Importantly, IL‐37‐mediated rejuvenation of aged endogenous T‐cells was also observed in aged chimeric antigen receptor (CAR) T‐cells, where improved function significantly extended the survival of mice transplanted with leukemia cells. Collectively, these data demonstrate the potency of IL‐37 in boosting the function of aged T‐cells and highlight its therapeutic potential to overcome aging‐associated immunosenescence.     

Role of methyl groups in dynamics and evolution of biomolecules

Recent studies have discovered strong differences between the dynamics of nucleic acids (RNA and DNA) and proteins, especially at low hydration and low temperatures. This difference is caused primarily by dynamics of methyl groups that are abundant in proteins, but are absent or very rare in RNA and DNA. In this paper, we present a hypothesis regarding the role of methyl groups as intrinsic plasticizers in proteins and their evolutionary selection to facilitate protein dynamics and activity. We demonstrate the profound effect methyl groups have on protein dynamics relative to nucleic acid dynamics, and note the apparent correlation of methyl group content in protein classes and their need for molecular flexibility. Moreover, we note the fastest methyl groups of some enzymes appear around dynamical centers such as hinges or active sites. Methyl groups are also of tremendous importance from a hydrophobicity/folding/entropy perspective. These significant roles, however, complement our hypothesis rather than preclude the recognition of methyl groups in the dynamics and evolution of biomolecules.