Abundance Analysis Research Articles

Insights into the early-life chemical exposome of Nigerian infants and potential correlations with the developing gut microbiome

Early-life exposure to natural and synthetic chemicals can impact acute and chronic health conditions. Here, a suspect screening workflow anchored on high-resolution mass spectrometry was applied to elucidate xenobiotics in breast milk and matching stool samples collected from Nigerian mother-infant pairs (n = 11) at three time points. Potential correlations between xenobiotic exposure and the developing gut microbiome, as determined by 16S rRNA gene amplicon sequencing, were subsequently explored. Overall, 12,192 and 16,461 features were acquired in the breast milk and stool samples, respectively. Following quality control and suspect screening, 562 and 864 features remained, respectively, with 149 of these features present in both matrices. Taking advantage of 242 authentic reference standards measured for confirmatory purposes of food bio-actives and toxicants, 34 features in breast milk and 68 features in stool were identified and semi-quantified. Moreover, 51 and 78 features were annotated with spectral library matching, as well as 416 and 652 by in silico fragmentation tools in breast milk and stool, respectively. The analytical workflow proved its versatility to simultaneously determine a diverse panel of chemical classes including mycotoxins, endocrine-disrupting chemicals (EDCs), antibiotics, plasticizers, perfluorinated alkylated substances (PFAS), and pesticides, although it was originally optimized for polyphenols. Spearman rank correlation of the identified features revealed significant correlations between chemicals of the same classification such as polyphenols. One-way ANOVA and differential abundance analysis of the data obtained from stool samples revealed that molecules of plant-based origin elevated as complementary foods were introduced to the infants’ diets. Annotated compounds in the stool, such as tricetin, positively correlated with the genus Blautia. Moreover, vulgaxanthin negatively correlated with Escherichia-Shigella. Despite the limited sample size, this exploratory study provides high-quality exposure data of matched biospecimens obtained from mother-infant pairs in sub-Saharan Africa and shows potential correlations between the chemical exposome and the gut microbiome.

Prediction of TNFRSF9 expression and molecular pathological features in thyroid cancer using machine learning to construct Pathomics models.

The TNFRSF9 molecule is pivotal in thyroid carcinoma (THCA) development. This study utilizes Pathomics techniques to predict TNFRSF9 expression in THCA tissue and explore its molecular mechanisms. Transcriptome data, pathology images, and clinical information from the cancer genome atlas (TCGA) were analyzed. Image segmentation and feature extraction were performed using the OTSU's algorithm and pyradiomics package. The dataset was split for training and validation. Features were selected using maximum relevance minimum redundancy recursive feature elimination (mRMR_RFE) and modeling conducted with the gradient boosting machine (GBM) algorithm. Model evaluation included receiver operating characteristic curve (ROC) analysis. The Pathomics model output a probabilistic pathomics score (PS) for gene expression prediction, with its prognostic value assessed in TNFRSF9 expression groups. Subsequent analysis involved gene set variation analysis (GSVA), immune gene expression, cell abundance, immunotherapy susceptibility, and gene mutation analysis. High TNFRSF9 expression correlated with worsened progression-free interval (PFI) and acted as an independent risk factor [hazard ratio (HR) = 2.178, 95% confidence interval (CI) 1.045-4.538, P = 0.038]. Nine pathohistological features were identified. The GBM Pathomics model demonstrated good prediction efficacy [area under the curve (AUC) 0.819 and 0.769] and clinical benefits. High PS was a PFI risk factor (HR = 2.156, 95% CI 1.047-4.440, P = 0.037). Patients with high PS potentially exhibited enriched pathways, increased TIGIT gene expression, Tregs infiltration (P < 0.0001), and higher rates of gene mutations (BRAF, TTN, TG). The GBM Pathomics model constructed based on the pathohistological features of H&E-stained sections well predicted the expression level of TNFRSF9 molecules in THCA.

Development of MetaXplore: An Interactive Tool for Targeted Metagenomic Analysis.

Over the last decades, the analysis of complex microbial communities by high-throughput sequencing of marker gene amplicons has become routine work for many research groups. However, the main challenges faced by scientists who want to make use of the generated sequencing datasets are the lack of expertise to select a suitable pipeline and the need for bioinformatics or programming skills to apply it. Here, we present MetaXplore, an interactive, user-friendly platform that enables the discovery and visualization of amplicon sequencing data. Currently, it provides a set of well-documented choices for downstream analysis, including alpha and beta diversity analysis, taxonomic composition, differential abundance analysis, identification of the core microbiome within a population, and biomarker analysis. These features are presented in a user-friendly format that facilitates easy customization and the generation of publication-quality graphics. MetaXplore is implemented entirely in the R language using the Shiny framework. It can be easily used locally on any system with R installed, including Windows, Mac OS, and most Linux distributions, or remotely via a web server without bioinformatic expertise. It can also be used as a framework for advanced users who can modify and expand the tool.

The R-Process Alliance: Analysis of limited-r stars

In recent years, the $R$-Process Alliance (RPA) has conducted a successful search for stars that are enhanced in elements produced by the rapid neutron-capture ($r$-)process. In particular, the RPA has uncovered a number of stars that are strongly enriched in light $r$-process elements, such as Sr, Y, and Zr. These so-called limited-$r$ stars were investigated to explore the astrophysical production site(s) of these elements. We investigate the possible formation sites for light neutron-capture elements by deriving detailed abundances for neutron-capture elements from high-resolution spectra with a high signal-to-noise ratio of three limited-$r$ stars. We conducted a kinematic analysis and a 1D local thermodynamic equilibrium spectroscopic abundance analysis of three stars. Furthermore, we calculated the lanthanide mass fraction ($ X_ La $) of our stars and of limited-$r$ stars from the literature. We found that the abundance pattern of neutron-capture elements of limited-$r$ stars behaves differently depending on their $ Ba/Eu $ ratios, and we suggest that this should be taken into account in future investigations of their abundances. Furthermore, we found that the $ X_ La $ of limited-$r$ stars is lower than that of the kilonova AT2017gfo. The latter seems to be in the transition zone between limited-$r$ $ X_ La $ and that of $r$-I and $r$-II stars. Finally, we found that unlike $r$-I and $r$-II stars, the current sample of limited-$r$ stars is largely born in the Galaxy and is not accreted.

Non‐destructive quantitative analysis of melt inclusions in extraterrestrial samples: Case study of chassignite via nanoscale X‐ray computed tomography

AbstractEstimation of the composition of planetary rocks and minerals is crucial for understanding their formation processes. In this study, we present the application of X‐ray nano‐computed tomography (nano‐XCT) for non‐destructive three‐dimensional (3‐D) phase analysis and estimation of phase abundances in rare Martian meteorite samples, specifically chassignite Northwest Africa (NWA) 2737. We determined the most suitable laser power for minimizing artifacts and maximizing phase contrast. By utilizing nano‐XCT, we successfully identified and segmented primary phases in the bulk meteorite sample. Additionally, we were able to locate and segment crystallized silicate melt inclusions within the meteorite. The phase abundances in bulk NWA 2737 and within melt inclusions calculated using nano‐XCT were in good agreement with previous studies that used thin section calculations, demonstrating the reliability of nano‐XCT as a non‐destructive alternative for estimating bulk phase abundances in rare samples. This study develops a benchmarking protocol and demonstrates the efficacy of nano‐XCT as a non‐destructive technique for generating an overview of phase distribution and assemblages of melt inclusions within rare samples. Future research can benefit from combining non‐destructive 3‐D phase assemblage estimations with non‐destructive 3‐D chemical analysis techniques to achieve a fully non‐destructive parental magma composition estimation of rare cumulate samples.

M3DIS - A grid of 3D radiation-hydrodynamics stellar atmosphere models for stellar surveys. I. Procedure, validation, and the Sun

Large-scale stellar surveys, such as SDSS-V, 4MOST, WEAVE, and PLATO, require accurate atmospheric models and synthetic spectra of stars for accurate analyses of fundamental stellar parameters and chemical abundances. The primary goal of our work is to develop a new approach to solve radiation-hydrodynamics (RHD) and generate model stellar spectra in a self-consistent and highly efficient framework. We build upon the Copenhagen legacy RHD code, the MULTI3D non-local thermodynamic equilibrium (NLTE) code, and the DISPATCH high-performance framework. The new approach allows us to calculate 3D RHD models of stellar atmospheres on timescales of a few thousand CPU hours and to perform subsequent spectrum synthesis in local thermodynamic equilibrium (LTE) or NLTE for the desired physical conditions within the parameter space of FGK-type stars. We compare the 3D RHD solar model with other available models and validate its performance against solar observations, including the centre-to-limb variation of intensities and key solar diagnostic lines of H and Fe. We show that the performance of the new code allows to overcome the main bottleneck in 3D NLTE spectroscopy and enables calculations of multi-dimensional grids of synthetic stellar observables for comparison with modern astronomical observations.

Comparative characterization of supragingival plaque microbiomes in malocclusion adult female patients undergoing orthodontic treatment with removable aligners or fixed appliances: a descriptive cross-sectional study.

This study aimed to explore the effects of removable aligners and fixed appliances on the supragingival bacterial communities in adult female patients undergoing orthodontic treatment. Supragingival plaque samples from 48 female individuals underwent microbiome analysis (16S rRNA gene sequencing) using PacBio Sequel sequencing. The study included 13 adults without orthodontic treatment needs as the control group (Group C), and 35 patients with comparable initial orthodontic conditions who received treatment at a university clinic in Beijing, China. The treatment involved either traditional fixed brackets (Group B, n = 17) or Invisalign® aligners (Group AT, n = 18). Bioinformatics methods were used for data analysis. From the 48 plaque samples, a total of 334,961 valid reads were obtained, averaging 6,978 sequences per sample. The 16S rDNA sequences were classified into 25,727 amplicon sequence variants (ASVs). Significant variances in alpha and beta diversity among the groups were noted. Group B microbiome exhibited an increased presence of Gram-negative bacteria. At the phylum level, Actinobacteriota was significantly more prevalent in Group C samples, while Bacteroidota was enriched in Group B samples. Family-level relative abundance analysis showed a notable increase in Saccharibacteria (formerly TM7) and Prevotellaceae in Group B. Genus-level analysis revealed a significant rise in Lautropia in Group AT. Fixed orthodontic appliances were linked to oral microbiome changes, notably an enhanced relative abundance of anaerobes, including periodontal pathogens. The observation points to the impact of orthodontic appliance on the oral microbial community, highlighting the difference between traditional braces (Group B) and clear aligners (Group AT)in terms of the predominance of anaerobic and gram negative bacteria. This emphasizes the importance of considering the microbiological effects when choosing orthodontic appliance and underscores the need for tailored oral hygiene practices for individuals undergoing these treatments. This research might provide insights that could assist in the development of innovative cleaning techniques and antibacterial materials.

Nitrogen functional profiles of microbiomes in diverse agricultural and forest soils and its driver at continental scale in China

Functional characteristics of microbiomes are good predictors of nitrogen (N) biogeochemistry, but soil microbial N-functional profiles under different land use practices and their dominant drivers at continental scale remain unclear. For this study, we selected soils having a broad range of edaphic factors across different land use practices and soil types in China and used metagenomic sequencing to investigate N-functional profiles of microbiomes. The N-pathway frequencies were highest in paddy soils, and the composition of N-cycling genes in paddy soils significantly diverged from upland and forest soils. Differential abundance analysis showed that genes associated with nitrogen dissimilatory pathways exhibited enrichment in paddy soils, whereas those linked to assimilatory pathways were enriched in forest soils. Aggregated boosted tree analysis revealed that the frequencies of N-pathways and relative abundances of N-cycling genes were mainly explained by soil moisture and pH. Partial Mantel and redundancy analysis consistently showed that N-functional composition correlated strongest with moisture and pH. Overall, our results demonstrated that soil moisture and pH were vital drivers of microbial N-functional profiles, providing novel evidence for soil moisture and pH’s role in driving whole nitrogen cycling. Considering the large fluctuations in moisture over time, soil pH, with minor seasonality, could be used as indicators to reflect microbial N-functional profiles at the continental scale.

Nondestructive determination of isotopic abundance using multi-energy nuclear resonance fluorescence driven by laser Compton scattering source

We report on the quantitative nondestructive analysis of the natural isotopic abundances of hafnium and tungsten elements using nuclear resonance fluorescence. Metallic samples of hafnium and tungsten were irradiated to six quasi-monochromatic γ-ray beams generated by laser Compton scattering in the energy range of 2.4–3.2 MeV. Multiple nuclei were simultaneously excited at each of the six γ-ray beam energies. A high-purity germanium detector array detected deexcitations of the nuclei. In total, 51 transitions were unprecedentedly employed to estimate the isotopic abundances of heavy elements nondestructively. The estimated abundances of three hafnium isotopes and three tungsten isotopes are consistent with standard known natural abundances within the experimental uncertainties. The deviation from the standard values ranges from 0.18% to 1.36%.

Mibianto: ultra-efficient online microbiome analysis through k-mer based metagenomics.

Quantifying microbiome species and composition from metagenomic assays is often challenging due to its time-consuming nature and computational complexity. In Bioinformatics, k-mer-based approaches were long established to expedite the analysis of large sequencing data and are now widely used to annotate metagenomic data. We make use of k-mer counting techniques for efficient and accurate compositional analysis of microbiota from whole metagenome sequencing. Mibianto solves this problem by operating directly on read files, without manual preprocessing or complete data exchange. It handles diverse sequencing platforms, including short single-end, paired-end, and long read technologies. Our sketch-based workflow significantly reduces the data volume transferred from the user to the server (up to 99.59% size reduction) to subsequently perform taxonomic profiling with enhanced efficiency and privacy. Mibianto offers functionality beyond k-mer quantification; it supports advanced community composition estimation, including diversity, ordination, and differential abundance analysis. Our tool aids in the standardization of computational workflows, thus supporting reproducibility of scientific sequencing studies. It is adaptable to small- and large-scale experimental designs and offers a user-friendly interface, thus making it an invaluable tool for both clinical and research-oriented metagenomic studies. Mibianto is freely available without the need for a login at: https://www.ccb.uni-saarland.de/mibianto.

The oldest stars with low neutron-capture element abundances and origins in ancient dwarf galaxies

ABSTRACT We present a detailed chemical abundance and kinematic analysis of six extremely metal-poor (−4.2 ≤ [Fe/H] ≤−2.9) halo stars with very low neutron-capture abundances ([Sr/H] and [Ba/H]) based on high-resolution Magellan/MIKE spectra. Three of our stars have [Sr/Ba] and [Sr/H] ratios that resemble those of metal-poor stars in ultra-faint dwarf galaxies (UFDs). Since early UFDs may be the building blocks of the Milky Way, extremely metal-poor halo stars with low, UFD-like Sr and Ba abundances may thus be ancient stars from the earliest small galactic systems that were accreted by the proto-Milky Way. We label these objects as Small Accreted Stellar System (SASS) stars, and we find an additional 61 similar ones in the literature. A kinematic analysis of our sample and literature stars reveals them to be fast-moving halo objects, all with retrograde motion, indicating an accretion origin. Because SASS stars are much brighter than typical UFD stars, identifying them offers promising ways towards detailed studies of early star formation environments. From the chemical abundances of SASS stars, it appears that the earliest accreted systems were likely enriched by a few supernovae whose light element yields varied from system to system. Neutron-capture elements were sparsely produced and/or diluted, with r-process nucleosynthesis playing a role. These insights offer a glimpse into the early formation of the Galaxy. Using neutron-capture elements as a distinguishing criterion for early formation, we have access to a unique metal-poor population that consists of the oldest stars in the universe.

Bacterial dysbiosis in newly diagnosed treatment naïve pediatric ulcerative colitis in Saudi Arabia.

The role of microbiota in the pathogenesis of ulcerative colitis (UC) has been increasingly recognized. However, most of the reports are from Western populations. In Middle Eastern countries, including Saudi Arabia, little is known about the role of microbiota. Therefore, our aim was to describe the bacterial microbiota profile and signature in pediatric UC in Saudi Arabia. Twenty children with UC and 20 healthy controls enrolled in the study gave stool samples. Twenty rectal mucosal samples were taken from UC and 20 from non-UC controls. Inclusion criteria included newly diagnosed and untreated children and lack of antibiotic exposure for at least 6 months before stool collection was required for children with UC and controls. Bacterial deoxyribonucleic acid was extracted and sequenced using shotgun metagenomic analysis. Statistical analysis included Shannon alpha diversity metrics, Bray-Curtis dissimilarity, DESeq2, and biomarker discovery. The demographic characteristics were similar in children with UC and controls. There was a significant reduction in alpha diversity (P = 0.037) and beta diversity in samples from children with UC (P = 0.001). Many taxa were identified with log2 abundance analysis, revealing 110 and 102 species significantly depleted and enriched in UC, respectively. Eleven bacterial species' signatures were identified. In Saudi Arabian children with UC, we demonstrate a dysbiosis similar to reports from Western populations, possibly related to changes of lifestyle. Microbial signature discovery in this report is an important contribution to research, leading to the development of adjunctive non-invasive diagnostic options in unusual cases of UC.

Bacterial peptidoglycan drives synovial inflammation in osteoarthritis

Abstract Peptidoglycan (PG) is a potent inflammatory mediator. We have previously demonstrated that PG is present in the synovial tissue of osteoarthritis (OA) patients but its role in OA inflammation remains unknown. We hypothesized that PG in synovial tissue drives inflammation in OA. Intraoperative synovial tissue and synovial fluid samples were obtained from 56 consecutive patients with OA, with no prior history of infection. PG in synovial tissue was detected by immunohistochemical (IHC) staining of serial sections of 10 mm2 of tissue with anti-PG antiserum. PG was found in 33/56 (59%) of the tissue samples using IHC, with a median of eight PG occurrences per 10 mm2 in PG-positive samples. Tissue inflammation and fibrosis were assessed by histopathology. Cellular localization was further characterized in three PG-positive tissue samples by immunofluorescent microscopy (IFM). PG was localized to cells demonstrating mononuclear and fibroblastic morphology primarily in and around areas of vascularization and inflammation. CD68+ macrophages and to a lesser degree CD90+ synovial sublining fibroblasts. In multiplex assay analysis of synovial fluid cytokine levels, IL-6 and PG abundance were positively correlated. Fibroblasts and macrophages stimulated with PG in vitro secreted high levels of innate cytokines, paricularly IL-6 when measured by supernatant cytokine quantification. Together these data support the hypothesis that PG in synovial tissue drives joint inflammation in OA.

Comprehensive profiling of endocrine metabolism identifies a novel signature with robust predictive value in ovarian cancer.

The cell endocrine pathway is a critical physiological process composed of the endoplasmic reticulum, Golgi apparatus and associated vesicles. Loss of enzymes or proteins can cause dysfunction of endoplasmic reticulum and Golgi apparatus and affect secretion pathways leading to a variety of human diseases, including cancer. The single-cell RNA sequencing and single nucleotide variant principal component analysis data of ovarian cancer were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus (GEO) datasets. Eighty-four genes from SECRETORY_PATHWAYs were obtained from the gene set enrichment analysis (GSEA) website. Univariate cox regression analyses and ConsensusClusterPlus were used to identify prognostic genes and molecular subtypes, which were validated using the tumor immune dysfunction and exclusion (i.e. TIDE) analysis and gene mutation analysis. A prognosis model was established by randomForestSRC. Abundant infiltrated immune cells and pathway enrichment analyses were carried out, respectively, through ssGSEA, ESTIMATE, MCP-counter and GSEA. The drug sensitive analysis was performed using pRRophetic package. Immunotherapy datasets and pan-carcinoma analysis were used to examine the performance of prognostic model. Eighteen prognostic genes from SECRETORY_PATHWAYs were found in both TCGA and GEO datasets. Next, two clusters (C1 and C2) were determined, for which C1 with a poor prognosis had higher immune infiltration. Tumor-related pathways, such as PATHWAYS_IN_CANCER and B_CELL_RECEPTOR_SIGNALING_PATHWAY, were enriched in C1. Moreover, C2 was suitable for immunotherapy. A four-gene (DNAJA1, NDRG3, LUZP1 and ZCCHC24) signature was developed and successfully validated. RiskScore of higher levels were significantly associated with worse prognoses. An enhanced immune infiltration, increased pathways score and inappropriate immunotherapy were observed in the high RiskScore group. The high- and low-RiskScore groups had different drug sensitivities. Immunotherapy datasets and pan-carcinoma analysis indicated that the low RiskScore group may benefit from immunotherapy. Based on the perspective of the secretory signaling pathway, a robust prognostic signature with great performances was determined, which may provide clues for clinical precision treatment of ovarian cancer.

Characteristics of Gut Microbiota in Rosacea Patients-A Cross-Sectional, Controlled Pilot Study.

Recent studies have suggested a possible connection between rosacea and patients' gut microbiota. To investigate the differences in fecal microbial profiles between patients with rosacea and healthy controls. Gut microbiota of 54 rosacea patients (RP) were analyzed using MiSeq 16S rRNA sequencing. Enterotypes, the Firmicutes/Bacteroides (F/B) ratio, the significance of alpha and beta diversity, and differential abundance analysis (DAA) were calculated and compared with age- and gender-matched controls (CP, n = 50). Significant changes in the enterotypes and F/B ratio were observed between the RP and CP (p = 0.017 and p = 0.002, respectively). The RP showed a decreased microbial richness and diversity compared to the CP (Shannon p = 0.012, inverse Simpson p = 0.034). Beta diversity also differed between both groups (PERMANOVA, p = 0.006). Fourteen significantly different taxa were detected according to DAA. Faecalibacterium prausnitzii (coef. -0.0800, p = 0.008), Lachnoospiraceae ND 3007 group sp. (coef. -0.073, p < 0.001), and Ruminococcaceae (coef. -0.072, p = 0.015) were significantly decreased; Oscillobacter sp. (coef. 0.023, p = 0.031), Flavonifractor plautii (coef. 0.011, p = 0.037), and Ruminococccaceae UBA 1819 (coef. 0.010, p = 0.031) were significantly increased in the RP compared to the CP. Significant alterations in gut microbiota were present in the RP. Taxonomic shifts and reduced richness and diversity were observed when compared to the CP. Larger prospective studies are needed to investigate correlations with clinical features and to translate these findings into future therapeutic approaches.

Euclid preparation

The Euclid photometric survey of galaxy clusters stands as a powerful cosmological tool, with the capacity to significantly propel our understanding of the Universe. Despite being subdominant to dark matter and dark energy, the baryonic component of our Universe holds substantial influence over the structure and mass of galaxy clusters. This paper presents a novel model that can be used to precisely quantify the impact of baryons on the virial halo masses of galaxy clusters using the baryon fraction within a cluster as a proxy for their effect. Constructed on the premise of quasi-adiabaticity, the model includes two parameters, which are calibrated using non-radiative cosmological hydrodynamical simulations, and a single large-scale simulation from the Magneticum set, which includes the physical processes driving galaxy formation. As a main result of our analysis, we demonstrate that this model delivers a remarkable 1% relative accuracy in determining the virial dark matter-only equivalent mass of galaxy clusters starting from the corresponding total cluster mass and baryon fraction measured in hydrodynamical simulations. Furthermore, we demonstrate that this result is robust against changes in cosmological parameters and against variation of the numerical implementation of the subresolution physical processes included in the simulations. Our work substantiates previous claims regarding the impact of baryons on cluster cosmology studies. In particular, we show how neglecting these effects would lead to biased cosmological constraints for a Euclid-like cluster abundance analysis. Importantly, we demonstrate that uncertainties associated with our model arising from baryonic corrections to cluster masses are subdominant when compared to the precision with which mass–observable (i.e. richness) relations will be calibrated using Euclid and to our current understanding of the baryon fraction within galaxy clusters.

Mi-Mic: a novel multi-layer statistical test for microbiota-disease associations.

mi-Mic, a novel approach for microbiome differential abundance analysis, tackles the key challenges of such statistical tests: a large number of tests, sparsity, varying abundance scales, and taxonomic relationships. mi-Mic first converts microbial counts to a cladogram of means. It then applies a priori tests on the upper levels of the cladogram to detect overall relationships. Finally, it performs a Mann-Whitney test on paths that are consistently significant along the cladogram or on the leaves. mi-Mic has much higher true to false positives ratios than existing tests, as measured by a new real-to-shuffle positive score.

Distinct anal microbiome is correlated with anal cancer precursors in MSM with HIV.

Anal cancer risk is elevated in MSM with HIV (MSMWH). Anal high-risk human papillomavirus (hr-HPV) infection is necessary but insufficient to develop high-grade squamous intraepithelial lesion (HSIL), the anal cancer precursor, suggesting additional factors. We sought to determine whether the microbiome of the anal canal is distinct by comparing it with the microbiome of stool. We also sought to determine whether changes in the anal microbiome are associated with HSIL among MSMWH. Cross-sectional comparison of the microbiome of the anal canal with the microbiome of stool in MSMWH and cross-sectional comparison of the anal microbiome of MSMWH with anal HSIL with the anal microbiome of MSMWH without anal HSIL. Sterile swabs were used to sample the anus of MSMWH for microbiome and HPV testing, followed by high-resolution anoscopy. Stool samples were mailed from home. 16S sequencing was used for bacterial identification. Measures of alpha diversity, beta diversity, and differential abundance analysis were used to compare samples. One hundred sixty-six anal samples and 103 matching stool samples were sequenced. Beta diversity showed clustering of stool and anal samples. Of hr-HPV-positive MSMWH, 31 had HSIL and 13 had no SIL. Comparison of the microbiome between these revealed 28 different species. The highest-fold enrichment among MSMWH/hr-HPV/HSIL included pro-inflammatory and carcinogenic Prevotella, Parasuterella, Hungatella, Sneathia, and Fusobacterium species. The anti-inflammatory Anaerostipes caccae showed the greatest reduction among MSMWH/hr-HPV/HSIL. The anal microbiome is distinct from stool. A pro-inflammatory and carcinogenic environment may be associated with anal HSIL.

Influence of ongoing discharge from multiple wastewater treatment plants on microplastic patterns in small-scale receiving rivers

As widely acknowledged, wastewater treatment plants (WWTPs) stand as significant contributors to the presence of microplastics in surface water. Nonetheless, there exists a notable research gap regarding the extent of potential pollution resulting from the concurrent and uninterrupted discharges originating from multiple WWTPs into small-scale receiving water bodies. This study endeavors to address this knowledge deficit by conducting a thorough investigation into the prevalence of microplastics in surface water. The research encompasses seven distinct locations within the Changzhou section of the Beijing-Hangzhou Grand Canal and the effluent of three WWTPs situated along the tributary. The results indicate differences in the distribution of microplastics in surface waters of mainstream and tributaries. While the microplastic abundance and composition showed little variation along the main stream, the tributaries displayed an overall increasing trend in microplastic abundance from upstream to downstream. Notably, the major contributors to this increase were fragments, fiber particles, and microplastics with particle sizes ranging from 100 to 300 μm. Considering that the primary distinction between the tributaries and the mainstream is the presence of the three WWTPs along the tributaries, the study conducted a correlation analysis between river surface water and effluents from these plants. The results indicated a stronger correlation between the tributaries and the effluents, suggesting that WWTPs are one of the primary factors contributing to the elevated levels of microplastics in the tributaries. Finally, a comparative analysis of microplastic abundance in the Beijing-Hangzhou Grand Canal's Changzhou section and other regions was conducted. The findings revealed that the microplastic pollution level in the Beijing-Hangzhou Grand Canal's Changzhou section is higher than that in most other rivers. Therefore, the issue of microplastic pollution in the Beijing-Hangzhou Grand Canal's Changzhou section warrants our attention, particularly with regard to the effectiveness of microplastic removal by the WWTPs along its course.

Abundant discrete localized wave solutions and related dynamic analysis for the coupled Ablowitz–Ladik equation with a time-dependent coefficient

Abundant discrete localized wave solutions and related dynamic analysis for the coupled Ablowitz–Ladik equation with a time-dependent coefficient