Oxidative stress in pregnancy and fertility pathologies

Oxidative stress designates the state of imbalance between reactive oxygen species (ROS) production and antioxidant levels. In a healthy placenta, there is an increase in ROS production, due to formation of new tissues and inherent metabolism, but this is balanced by higher levels of antioxidants. However, this balance is lost in some situations, with a consequent increase in oxidative stress levels. Oxidative stress has been implicated in several placental disorders and pregnancy pathologies. The present review intends to summarize what is known about the relationship between oxidative stress and well-known pregnancy disorders

Comparative phylogenetic methods and the cultural evolution of medicinal plant use

Human life depends on plant biodiversity and the ways in which plants are used are culturally determined. Whilst anthropologists have used phylogenetic comparative methods (PCMs) to gain an increasingly sophisticated understanding of the evolution of political, religious, social, and material culture, plant use has been almost entirely neglected. Medicinal plants are of special interest because of their role in maintaining people’s health across the world. PCMs in particular, and cultural evolutionary theory in general, provide a framework in which to study the diversity of medicinal plant applications cross-culturally, and to infer changes in plant use through time. These methods can be applied to single medicinal plants as well as the entire set of plants used by a culture for medicine, and they account for the non-independence of data when testing for floristic, cultural or other drivers of plant use. With cultural, biological, and linguistic diversity under threat, gaining a deeper and broader understanding of the variation of medicinal plant use through time and space is pressing

Plant DNA barcodes and assessment of phylogenetic community structure of a tropical mixed dipterocarp forest in Brunei Darussalam (Borneo)

DNA barcoding is a fast and reliable tool to assess and monitor biodiversity and, via community phylogenetics, to investigate ecological and evolutionary processes that may be responsible for the community structure of forests. In this study, DNA barcodes for the two widely used plastid coding regions rbcL and matK are used to contribute to identification of morphologically undetermined individuals, as well as to investigate phylogenetic structure of tree communities in 70 subplots (10 × 10m) of a 25-ha forest-dynamics plot in Brunei (Borneo, Southeast Asia). The combined matrix (rbcL + matK) comprised 555 haplotypes (from ≥154 genera, 68 families and 25 orders sensu APG, Angiosperm Phylogeny Group, 2016), making a substantial contribution to tree barcode sequences from Southeast Asia. Barcode sequences were used to reconstruct phylogenetic relationships using maximum likelihood, both with and without constraining the topology of taxonomic orders to match that proposed by the Angiosperm Phylogeny Group. A third phylogenetic tree was reconstructed using the program Phylomatic to investigate the influence of phylogenetic resolution on results. Detection of non-random patterns of community assembly was determined by net relatedness index (NRI) and nearest taxon index (NTI). In most cases, community assembly was either random or phylogenetically clustered, which likely indicates the importance to community structure of habitat filtering based on phylogenetically correlated traits in determining community structure. Different phylogenetic trees gave similar overall results, but the Phylomatic tree produced greater variation across plots for NRI and NTI values, presumably due to noise introduced by using an unresolved phylogenetic tree. Our results suggest that using a DNA barcode tree has benefits over the traditionally used Phylomatic approach by increasing precision and accuracy and allowing the incorporation of taxonomically unidentified individuals into analyses

Fishmeal supplementation during ovine pregnancy and lactation protects against maternal stress-induced programming of the offspring immune system

BACKGROUND: Prenatally stressed offspring exhibit increased susceptibility to inflammatory disorders due to in utero programming. Research into the effects of n-3 PUFAs shows promising results for the treatment and prevention of these disorders. The purpose of this study was to investigate whether maternal fishmeal supplementation during pregnancy and lactation protects against programming of the offspring’s immune response following simulated maternal infection. METHODS: In order to accomplish this, 53 ewes were fed a diet supplemented with fishmeal (FM; rich in n-3 PUFA) or soybean meal (SM; rich in n-6 PUFAs) from day 100 of gestation (gd 100) through lactation. On gd135, half the ewes from each dietary group were challenged with either 1.2 μg/kg Escherichia coli lipopolysaccharide (LPS) endotoxin to simulate a bacterial infection, or saline as the control. At 4.5 months of age the offspring’s dermal immune response was assessed by cutaneous hypersensitivity testing with ovalbumin (OVA) and candida albicans (CAA) 21 days after sensitization. Skinfold measurements were taken and serum blood samples were also collected to assess the primary and secondary antibody immune response. RESULTS: Offspring born to SM + LPS mothers had a significantly greater change in skinfold thickness in response to both antigens as well as a greater secondary antibody response to OVA compared to all treatments. CONCLUSIONS: Supplementation during pregnancy with FM appears to protect against adverse fetal programming that may occur during maternal infection and this may reduce the risk of atopic disease later in life

Multifaceted roles of peroxisome proliferator-activated receptors (PPARs) at the cellular and whole organism levels.

Chronic disorders, such as obesity, diabetes, inflammation, non-alcoholic fatty liver disease and atherosclerosis, are related to alterations in lipid and glucose metabolism, in which peroxisome proliferator-activated receptors (PPAR)α, PPARβ/δ and PPARγ are involved. These receptors form a subgroup of ligand-activated transcription factors that belong to the nuclear hormone receptor family. This review discusses a selection of novel PPAR functions identified during the last few years. The PPARs regulate processes that are essential for the maintenance of pregnancy and embryonic development. Newly found hepatic functions of PPARα are the mediation of female-specific gene repression and the protection of the liver from oestrogen induced toxicity. PPARα also controls lipid catabolism and is the target of hypolipidaemic drugs, whereas PPARγ controls adipocyte differentiation and regulates lipid storage; it is the target for the insulin sensitising thiazolidinediones used to treat type 2 diabetes. Activation of PPARβ/δ increases lipid catabolism in skeletal muscle, the heart and adipose tissue. In addition, PPARβ/δ ligands prevent weight gain and suppress macrophage derived inflammation. In fact, therapeutic benefits of PPAR ligands have been confirmed in inflammatory and autoimmune diseases, such as encephalomyelitis and inflammatory bowel disease. Furthermore, PPARs promote skin wound repair. PPARα favours skin healing during the inflammatory phase that follows injury, whilst PPARβ/δ enhances keratinocyte survival and migration. Due to their collective functions in skin, PPARs represent a major research target for our understanding of many skin diseases. Taken altogether, these functions suggest that PPARs serve as physiological sensors in different stress situations and remain valuable targets for innovative therapies

Streamlining Science: Recreating Systematic Literature Reviews with AI-Powered Decision Tools

In recent years there has been an explosion of new information technologies that use artificial intelligence (AI) to improve decision-making in scientific research. However, the pace of innovation has far exceeded the capacity of researchers to evaluate such technologies. This project evaluates two new AI-powered research assistant tools for decision-making in literature review: Elicit, which uses GPT, and Research Rabbit, which uses a snowballing algorithm and natural language processing. Using a database search as a control, this project will evaluate overlap of records retrieved, proportion of records missed, time savings, and usability for each tool. The goal is to ascertain the technologies’ reliability, efficiency, and acceptance. Such thorough evaluation is necessary to establish trust in these tools’ performance and therefore to promote their adoption. This is the first known assessment of AI tools that operate by iteratively employing user’s decisions as feedback for retrieving information for literature review