Evaluating Helium Varations By Modeling Red Giant Branch Bump of Large Magellanic Cluster NGC 1978

Many evidence show that the Multiple Population (MP) features ex- ist not only in the old Galactic globular clusters but also in the intermediate-age clusters in the Megallanic Clouds (MCs), which are characterized by star-to-star abundance scatter of several elements, including Helium (He). The photometric properties of the red giant branch bump (RGBB) are proved to be related to the variation in helium abundances of the member stars of the star clusters. We use the “Modules for Experiments in Stellar Astrophysics” (MESA) stellar evolution code to calculate the evolution sequences of stars along the red giant branch with changing helium content. Following the RGB sequences, we then generate a lu- minosity function of the RGB stars within the grid of input helium abundances, which are compared with the observational data of an intermediate-age MC cluster NGC 1978. The result of the current study reveals that the star to star helium abundance variation is 0.03.

The Relationship Between Gut Microbiome Features and Chemotherapy Response in Gastrointestinal Cancer

ObjectiveThe prognosis of advanced gastrointestinal cancer is poor. There are studies indicating that gut microbes might have the predictive ability to evaluate the outcome of cancer therapy, especially immunotherapy. There is limited evidence to date on the influence of microbes on chemotherapeutic response.DesignIn total, 130 patients with advanced or metastatic esophageal (n=40), gastric (n=46), and colorectal cancer (n=44) were enrolled. We included 147 healthy people as controls and used 16S rRNA sequencing to analyze the fecal microbiota.ResultsSignificant differences in the abundance of fecal microbiota between patients with gastrointestinal cancer and controls were identified. The abundance of Bacteroides fragilis, Escherichia coli, Akkermansia muciniphila, Clostridium hathewayi, and Alistipes finegoldii were significantly increased in the patient group. Faecalibacterium prausnitzii, Roseburia faecis, Clostridium clostridioforme, Blautia producta, Bifidobacterium adolescent, and Butyricicoccus pullicaecorum taxa were significantly more abundant in the controls. The amount of R. faecis in non-responders (NR) was more likely to decrease significantly after chemotherapy, while the amount mostly increased in responders (R) (P=0.040). The optimal abundance variation of R. faecis may be a predictor for distinguishing patients with PD from those with non-PD in all patients with gastrointestinal cancer, with a sensitivity of 75.0% and a specificity of 93.9%.ConclusionThe gut microbiome of patients with esophageal cancer, gastric cancer, and colorectal cancer differs from those of healthy people. The abundance alteration of R. faecis in patients with GI cancer might be a predictor of chemotherapy efficacy.

Temporal variability in quantitative human gut microbiome profiles and implications for clinical research

While clinical gut microbiota research is ever-expanding, extending reference knowledge of healthy between- and within-subject gut microbiota variation and its drivers remains essential; in particular, temporal variability is under-explored, and a comparison with cross-sectional variation is missing. Here, we perform daily quantitative microbiome profiling on 713 fecal samples from 20 Belgian women over six weeks, combined with extensive anthropometric measurements, blood panels, dietary data, and stool characteristics. We show substantial temporal variation for most major gut genera; we find that for 78% of microbial genera, day-to-day absolute abundance variation is substantially larger within than between individuals, with up to 100-fold shifts over the study period. Diversity, and especially evenness indicators also fluctuate substantially. Relative abundance profiles show similar but less pronounced temporal variation. Stool moisture, and to a lesser extent diet, are the only significant host covariates of temporal microbiota variation, while menstrual cycle parameters did not show significant effects. We find that the dysbiotic Bact2 enterotype shows increased between- and within-subject compositional variability. Our results suggest that to increase diagnostic as well as target discovery power, studies could adopt a repeated measurement design and/or focus analysis on community-wide microbiome descriptors and indices.

Spatial distribution of sediment archaeal and bacterial communities relates to the source of organic matter and hypoxia – a biogeographical study on Lake Remoray (France)

Bottom waters hypoxia spreads in many lakes worldwide causing severe consequences on whole lakes trophic network. Here, we aimed at understanding the origin of organic matter stored in the sediment compartment and the related diversity of sediment microbial communities in a lake with deoxygenated deep water layers. We used a geostatistical approach to map and compare both the variation of organic matter and microbial communities in sediment. Spatialisation of C/N ratio and δ13C signature of sediment organic matter suggested that Lake Remoray was characterized by an algal overproduction which could be related to an excess of nutrient due to the close lake-watershed connectivity. Three spatial patterns were observed for sediment microbial communities after the hypoxic event, each characterized by specific genetic structure, microbial diversity and composition. The relative abundance variation of dominant microbial groups across Lake Remoray such as Cyanobacteria, Gammaproteobacteria, Deltaproteobacteria and Chloroflexi provided us important information on the lake areas where hypoxia occurs. The presence of methanogenic species in the deeper part of the lake suggests important methane production during hypoxia period. Taken together, our results provide an extensive picture of microbial communities' distribution related to quantity and quality of organic matter in a seasonally hypoxic lake.

Completeness of rapid assessments of medium and large mammal diversity in the northwestern Amazon in Colombia

ABSTRACT Rapid assessments are the most common information source on biodiversity in the northwestern Amazon in Colombia due to limited resources and logistic constraints. These assessments are essential for decision-making on environmental policies in this region, that has been strongly impacted by the transformation of its natural ecosystems. Several local camera-trapping rapid assessments of medium and large-sized mammals (MLM) have been conducted in the Colombian Amazon, but they are difficult to compare. We analyzed information of 16 of these rapid assessments of MLM to provide the first list of MLM in the northwestern Amazon in Colombia. We also evaluated the accuracy of four estimators (ICE, Chao-2, Jackknife-1, and Jackknife-2), and the minimum sampling effort for the estimation of MLM richness in local surveys in the region. We report 26 species of MLM for the Colombian Amazon (between five and 13 species per locality), which is an underestimation of MLM richness in the region. The best estimator of MLM richness was the Jackknife-1, due to its precision and the lower influence of singletons. We recommend a minimum sampling effort of 350 camera trap-days. Although rapid assessments do not allow a robust estimation of MLM richness, they record the most common species (or core species) per locality and their abundance variation. The evaluation of the effect of habitat transformation on MLM and the estimation of population parameters of rare species require more intensive studies.

The Identification and Prediction in Abundance Variation of Atlantic Cod via Long Short-Term Memory With Periodicity, Time–Frequency Co-movement, and Lead-Lag Effect Across Sea Surface Temperature, Sea Surface Salinity, Catches, and Prey Biomass From 1919 to 2016

The population of Atlantic cod significantly contributes to the prosperity of fishery production in the world. In this paper, we quantitatively investigate the global abundance variation in Atlantic cod from 1919 to 2016, in favor of spatiotemporal interactions over manifold impact factors at local observation sites, and propose to explore the predictive mechanism with the help of its periodicity, time–frequency co-movement, and lead-lag effects, via long short-term memory (LSTM). We first integrate evidences yielded from wavelet coefficients, to suggest that the abundance variation potentially follows a 36-year major cycle and 24-year secondary cycle at the time scales of 55 years and 37 years. We further evaluate the responses of Atlantic cod abundance to the external impact factors, including sea surface temperature (SST), catches, prey biomass, and sea surface salinity (SSS), in aid of the wavelet coherence and phase difference, which allows us to identify the dominantly correlative factors and capture the leading roles along the time domain and then divide the responses around the recent 60 years into three stages: before 1985, 1985–1995, and after 1995. At the first stage, the reason for the decline in abundance could be mainly attributed to the rapid rise of fish catches. At the second stage, the impact of SST and SSS also provides significant indices, besides overfishing; meanwhile, the mortality of primary producers and forced migration of fish species indirectly cause the decline. At the third stage, warming SST and growing SSS directly led to the decrease of abundance. Finally, we establish one ensemble of LSTM-SAE architecture to comprehensively reflect the predictive patterns at each stage. It has been demonstrated from experimental results that the models behaved better when intentionally feeding with the dominantly correlative multivariate inputs, instead of either all factors or only the abundance. The proposed scheme provides opportunities to symmetrically identify the underlying predictive attributes of Atlantic cod abundance and potentially perform as the quantitative references in reasonably making fishing decision. With the rapid development in deep learning capabilities, it is hopeful to expect better predictions of the responses to global changes, not only for Atlantic cod but also for other fish species and the ecosystem as a whole.

EORNA, a barley gene and transcript abundance database

A high-quality, barley gene reference transcript dataset (BaRTv1.0), was used to quantify gene and transcript abundances from 22 RNA-seq experiments, covering 843 separate samples. Using the abundance data we developed a Barley Expression Database (EORNA*) to underpin a visualisation tool that displays comparative gene and transcript abundance data on demand as transcripts per million (TPM) across all samples and all the genes. EORNA provides gene and transcript models for all of the transcripts contained in BaRTV1.0, and these can be conveniently identified through either BaRT or HORVU gene names, or by direct BLAST of query sequences. Browsing the quantification data reveals cultivar, tissue and condition specific gene expression and shows changes in the proportions of individual transcripts that have arisen via alternative splicing. TPM values can be easily extracted to allow users to determine the statistical significance of observed transcript abundance variation among samples or perform meta analyses on multiple RNA-seq experiments. * Eòrna is the Scottish Gaelic word for Barley.

Spatio-Temporal Variation of the Bacterial Communities along a Salinity Gradient within a Thalassohaline Environment (Saline di Tarquinia Salterns, Italy)

The “Saline di Tarquinia” salterns have been scarcely investigated regarding their microbiological aspects. This work studied the structure and composition of their bacterial communities along the salinity gradient (from the nearby sea through different ponds). The communities showed increasing simplification of pond bacterial diversity along the gradient (particularly if compared to those of the sea). Among the 38 assigned phyla, the most represented were Proteobacteria, Actinobacteria and Bacteroidetes. Differently to other marine salterns, where at the highest salinities Bacteroidetes dominated, preponderance of Proteobacteria was observed. At the genus level the most abundant taxa were Pontimonas, Marivita, Spiribacter, Bordetella, GpVII and Lentibacter. The α-diversity analysis showed that the communities were highly uneven, and the Canonical Correspondence Analysis indicated that they were structured by various factors (sampling site, sampling year, salinity, and sampling month). Moreover, the taxa abundance variation in relation to these significant parameters were investigated by Generalized Linear Models. This work represents the first investigation of a marine saltern, carried out by a metabarcoding approach, which permitted a broad vision of the bacterial diversity, covering both a wide temporal span (two years with monthly sampling) and the entire salinity gradient (from the nearby sea up to the crystallisation ponds).

MiR-26a-5p as a Reference to Normalize MicroRNA qRT-PCR Levels in Plasma Exosomes of Pediatric Hematological Malignancies

Plasma exosomal microRNAs (miRNAs) are considered as valid circulating biomarkers for cancer diagnosis and prognosis. Quantitative real-time polymerase chain reaction (qRT-PCR), the most commonly used technique to assess circulating miRNA levels, requires a normalization step involving uniformly expressed endogenous miRNAs. However, there is still no consensus on reference miRNAs for plasma exosomal miRNA abundance normalization. In this study, we identified a panel of miRNAs with stable abundance by analyzing public plasma exosome RNA-seq data and selected miR-486-5p, miR-26a-5p, miR-423-5p and miR191-5p as candidate normalizers. Next, we tested the abundance variation of these miRNAs by qRT-PCR in plasma exosomes of healthy donors and pediatric patients with anaplastic large cell lymphoma, Burkitt lymphoma, Hodgkin lymphoma and mature B-cell acute lymphoblastic leukemia. MiR-486-5p and miR-26a-5p showed the most stable levels, both between healthy controls and patients and among the malignancies analyzed. In light of previous reports on miRNA stability in different exosome isolation methods, our data indicated that miR-26a-5p is a bona fide reference miRNA for qRT-PCR normalization to evaluate miRNA abundance from circulating plasma exosomes in studies of hematological malignancies.