For each example, we review both the empirical evidence and the existing theoretical frameworks developed to identify the causes and consequences of patterning. Finally, we trace qualitative similarities across systems and propose possible ways of developing a more quantitative understanding of how self-organization operates across systems and observational scales in ecology.Naive CD4 and CD8 T cells are cornerstones of adaptive immunity, but the dynamics of their establishment early in life and how their kinetics change as they mature following release from the thymus are poorly understood. Further, due to the diverse signals implicated in naive T cell survival, it has been a long-held and conceptually attractive view that they are sustained by active homeostatic control as thymic activity wanes. Here we use multiple modelling and experimental approaches to identify a unified model of naive CD4 and CD8 T cell population dynamics in mice, across their lifespan. We infer that both subsets divide rarely, and progressively increase their survival capacity with cell age. Strikingly, this simple model is able to describe naive CD4 T cell dynamics throughout life. In contrast, we find that newly generated naive CD8 T cells are lost more rapidly during the first 3-4 weeks of life, likely due to increased recruitment into memory. We find no evidence for elevated division rates in neonates, or for feedback regulation of naive T cell numbers at any age. We show how confronting mathematical models with diverse datasets can reveal a quantitative and remarkably simple picture of naive T cell dynamics in mice from birth into old age.Fragment molecular orbital (FMO) method is a powerful computational tool for structure-based drug design, in which protein-ligand interactions can be described by the inter-fragment interaction energy (IFIE) and its pair interaction energy decomposition analysis (PIEDA). Here, we introduced a dynamically averaged (DA) FMO-based approach in which molecular dynamics simulations were used to generate multiple protein-ligand complex structures for FMO calculations. To assess this approach, we examined the correlation between the experimental binding free energies and DA-IFIEs of six CDK2 inhibitors whose net charges are zero. The correlation between the experimental binding free energies and snapshot IFIEs for X-ray crystal structures was R2 = 0.75. Using the DA-IFIEs, the correlation significantly improved to 0.99. When an additional CDK2 inhibitor with net charge of -1 was added, the DA FMO-based scheme with the dispersion energies still achieved R2 = 0.99, whereas R2 decreased to 0.32 employing all the energy terms of PIEDA.

The aim was to provide updated evidence on the association of male body mass index (BMI) with outcomes of assisted reproduction technology (ART).

PubMed, Embase, and Scopus databases were systematically searched. The review included observational studies in patients undergoing ART, that is, either in-vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) and compared rate of clinical pregnancy and live birth based on different categories of male BMI. Quality of the pooled findings was assessed using the GRADE criteria.

A total of 19 studies were included in the review. Among subjects undergoing IVF, there were no significant differences in the rates of clinical pregnancy among overweight (odds ratio [OR] 1.38, 95% confidence interval [CI] 0.65, 2.96) and obese (OR 1.86, 95% CI 0.75, 4.58) BMI, compared to normal male BMI. Similarly, there were no significant differences in the rates of live birth among overweight (OR 1.04, 95% CI 0.97, 1.13) and obese BMI (OR 0.90, 95% CI 0.69, 1.18) when compared to males with normal BMI. Further, among those undergoing ICSI, there were no significant differences in the odds of clinical pregnancy among overweight (OR 0.98, 95% CI 0.73, 1.33) and obese (OR 0.89, 95% CI 0.62, 1.29). The odds of live births among overweight (OR 0.97, 95% CI 0.89, 1.05) and obese (OR 0.95, 95% CI 0.84, 1.07) male BMI were statistically similar to males with normal BMI undergoing ICSI.

The low to very low-quality findings suggest no significant association of overweight and obese BMI with clinical pregnancy and live birth rates among couples undergoing either IVF or ICSI.

The low to very low-quality findings suggest no significant association of overweight and obese BMI with clinical pregnancy and live birth rates among couples undergoing either IVF or ICSI.Metal organic frameworks (MOFs) have drawn broad attention as a novel stationary phase due to their highly porous structure, modifiable pores, large specific surface areas, and satisfactory stability. In this paper, histidine-zeolitic imidazolate framework-8 (His-ZIF-8) synthesized at room temperature was physically coated to the internal surface of the capillary column and the carboxymethyl-β-cyclodextrin (CM-β-CD) as the chiral selector was chemically bonded to the His-ZIF-8@capillary column. The prepared CM-β-CD@His-ZIF-8@capillary column was used for the enantioseparation of amlodipine, propranolol, and atenolol in capillary electrochromatography. In contrast to the CM-β-CD@capillary column without His-ZIF-8, the CM-β-CD@His-ZIF-8@capillary column reveals significantly improved enantiodiscrimination performance for amlodipine (Rs 0 → 2.29), propranolol (Rs 0 → 1.69), and atenolol (Rs 0 → 0.79). His-ZIF-8 concentration, buffer pH, buffer concentration, and the proportion of organic modifier were evaluated in detail with enantiomerically separating chiral molecules. The repeatability of intraday, day-to-day, and column-to-column have been discussed; the result was preferable, and the relative standard deviation (RSD) of separation parameters was less then 6.7%.

This study conducted in rural Tanzania examined the effects of a midwife-led prenatal group program on (1) improvement of knowledge of the physiological symptoms of pregnancy; (2) promotion of pregnancy-related empowerment; (3) enhancement of intention to self-care behaviors for safer childbirth; and (4) gaining satisfaction with antenatal care visits.

This work was a quasi-experimental study with a control group using a pre-post study design conducted in two district hospitals in Tanzania. Data were collected from 108 analyzed pregnant women from the prenatal group program (n=54) and control program (n=54) using questionnaires before (baseline) and after (endline) the program. The program consisted of lecture, sharing, and review sessions. The control program consisted of the same lectures. The contents of both programs included physiological symptoms of pregnancy and self-care behaviors. The primary outcome was knowledge of common symptoms of pregnancy. The secondary outcomes were Pregnancy-Related Empowerment Scale score, intention to self-care behaviors, and satisfaction.

The primary outcome of knowledge of common symptoms of pregnancy was significantly increased in the intervention group compared with the control group (t=2.677, p=.009). The secondary outcome of one of the Pregnancy-Related Empowerment Scale statements about midwife’s respectful attitude toward women’s decision was significantly increased in the intervention group compared with the control group (U=2.076, p=.038).

The interventional prenatal group program during pregnancy was effective in increasing knowledge of common symptoms of pregnancy and in identifying favorable midwife connectedness.

The interventional prenatal group program during pregnancy was effective in increasing knowledge of common symptoms of pregnancy and in identifying favorable midwife connectedness.The technological inference in procedures applied to healthcare is frequently investigated in order to understand the real contribution to decision-making and clinical improvement. In this context, the theoretical field of machine learning has suitably presented itself. The objective of this research is to identify the main machine learning algorithms used in healthcare through the methodology of a systematic literature review. Considering the time frame of the last twenty years, 173 studies were mined based on established criteria, which allowed the grouping of algorithms into typologies. Supervised Learning, Unsupervised Learning, and Deep Learning were the groups derived from the studies mined, establishing 59 works employed. We expect that this research will stimulate investigations towards machine learning applications in healthcare.Cell surface proteins form a major fraction of the druggable proteome and can be used for tissue-specific delivery of oligonucleotide/cell-based therapeutics. Surface protein isoforms are regulated by alternative splicing, which drives subcellular localization and transmembrane (TM) topology thereby shaping cell type specific signatures. Current advances in multiomic approaches have developed interest in discovery of tissue-specific alternatively spliced or novel surface protein isoforms. However, there exists a need for bioinformatic approaches for rapidly benchmarking the large number of isoforms identified by these approaches. To address this gap, we have developed, surfaltr, an R package which takes user input isoforms, pairs them with the known principal isoform of the gene, predicts TM topologies, and generates a customizable graphical output. Further, surfaltr facilitates prioritization of topologically diverse isoform pairs through incorporation of three different ranking metrics and through protein alignment functions. Here, we demonstrate the utility of our R package by evaluating the mouse retina-specific novel surface protein isoforms identified in Ray et al. 2020. surfaltr is freely available through Bioconductor (https//bioconductor.org/packages/surfaltr) and the vignette provides extensive instructions for implementation.The insulin signaling pathway controls cell growth and metabolism, thus its deregulation is associated with both cancer and diabetes. Phosphatidylinositol 3-kinase (PI3K) contributes to the cascade of phosphorylation events occurring in the insulin pathway by activating the protein kinase B (PKB/AKT), which phosphorylates several substrates, including those involved in glucose uptake and storage. PI3K inactivating mutations are associated with insulin resistance while activating mutations are identified in human cancers. Here we show that RNAi-induced depletion of the Drosophila PI3K catalytic subunit (Dp110) results in diabetic phenotypes such as hyperglycemia, body size reduction, and decreased glycogen content. Interestingly, we found that hyperglycemia produces chromosome aberrations (CABs) triggered by the accumulation of advanced glycation end-products and reactive oxygen species. Rearing PI3KRNAi flies in a medium supplemented with pyridoxal 5′-phosphate (PLP; the catalytically active form of vitamin B6) rescues DNA damage while, in contrast, treating PI3KRNAi larvae with the PLP inhibitor 4-deoxypyridoxine strongly enhances CAB frequency. Interestingly, PLP supplementation rescues also diabetic phenotypes. Taken together, our results provide a strong link between impaired PI3K activity and genomic instability, a crucial relationship that needs to be monitored not only in diabetes due to impaired insulin signaling but also in cancer therapies based on PI3K inhibitors. In addition, our findings confirm the notion that vitamin B6 is a good natural remedy to counteract insulin resistance and its complications.