Linear Size Research Articles

Vertical variation in prokaryotic community composition and co-occurrence patterns in sediments of the Three Gorges Reservoir, China

Archaea and bacteria are distributed throughout the sediment; however, our understanding of their biodiversity patterns, community composition, and interactions is primarily limited to the surface horizons (0–20 cm). In this research, sediment samples were collected from three vertical sediment profiles (depths of 0–295 cm) in the Three Gorges Reservoir (TGR), one of the largest reservoirs in the world. Through 16S rRNA sequencing, it was shown that sediment microbial diversity did not significantly vary across the sediment. Nevertheless, a decline in the similarity of archaeal and bacterial communities over distance along sediment vertical profiles was noted. Nonmetric multidimensional scaling (NMDS) analysis revealed that archaeal and bacterial communities could be clearly separated into two groups, located in the upper sediments (0–135 cm) and deep sediments (155–295 cm). Meanwhile, at the fine-scale of the vertical section, noteworthy variations were observed in the relative abundance of prominent archaea (e.g., Euryarchaeota) and bacteria (e.g., Proteobacteria). The linear discriminant analysis effect size (LEfSe) demonstrated that twenty-four bacterial and twenty-six archaeal biomarker microbes exist in the upper and deep sediment layers. Each layer exhibited distinctive microbial divisions, suggesting that microbes with diverse biological functions are capable of thriving and propagating along the sediment profile. Co-occurrence network analysis further indicated that the microbial network in the upper sediments was more complex than that in the deep sediments. Additionally, the newly discovered anaerobic methanotrophic archaeon Candidatus Methanoperedens was identified as the most abundant keystone archaeal taxon in both sediment layers, highlighting the significance of methane oxidation in material cycling within the TGR ecosystem. In summary, our study examined the biodiversity and coexistence patterns of benthic microbial communities throughout the vertical sediment profile, providing detailed insights into the vertical geography of archaeal and bacterial communities in typical deep-water reservoir ecosystems.

Salivary and fecal microbiota: potential new biomarkers for early screening of colorectal polyps.

Gut microbiota plays an important role in colorectal cancer (CRC) pathogenesis through microbes and their metabolites, while oral pathogens are the major components of CRC-associated microbes. Multiple studies have identified gut and fecal microbiome-derived biomarkers for precursors lesions of CRC detection. However, few studies have used salivary samples to predict colorectal polyps. Therefore, in order to find new noninvasive colorectal polyp biomarkers, we searched into the differences in fecal and salivary microbiota between patients with colorectal polyps and healthy controls. In this case-control study, we collected salivary and fecal samples from 33 patients with colorectal polyps (CP) and 22 healthy controls (HC) between May 2021 and November 2022. All samples were sequenced using full-length 16S rRNA sequencing and compared with the Nucleotide Sequence Database. The salivary and fecal microbiota signature of colorectal polyps was established by alpha and beta diversity, Linear discriminant analysis Effect Size (LEfSe) and random forest model analysis. In addition, the possibility of microbiota in identifying colorectal polyps was assessed by Receiver Operating Characteristic Curve (ROC). In comparison to the HC group, the CP group's microbial diversity increased in saliva and decreased in feces (p < 0.05), but there was no significantly difference in microbiota richness (p > 0.05). The principal coordinate analysis revealed significant differences in β-diversity of salivary and fecal microbiota between the CP and HC groups. Moreover, LEfSe analysis at the species level identified Porphyromonas gingivalis, Fusobacterium nucleatum, Leptotrichia wadei, Prevotella intermedia, and Megasphaera micronuciformis as the major contributors to the salivary microbiota, and Ruminococcus gnavus, Bacteroides ovatus, Parabacteroides distasonis, Citrobacter freundii, and Clostridium symbiosum to the fecal microbiota of patients with polyps. Salivary and fecal bacterial biomarkers showed Area Under ROC Curve of 0.8167 and 0.8051, respectively, which determined the potential of diagnostic markers in distinguishing patients with colorectal polyps from controls, and it increased to 0.8217 when salivary and fecal biomarkers were combined. The composition and diversity of the salivary and fecal microbiota were significantly different in colorectal polyp patients compared to healthy controls, with an increased abundance of harmful bacteria and a decreased abundance of beneficial bacteria. A promising non-invasive tool for the detection of colorectal polyps can be provided by potential biomarkers based on the microbiota of the saliva and feces.

Alterations of the salivary microbiota in gastroesophageal reflux disease

ObjectivesGastroesophageal reflux disease (GERD) is among the most prevalent gastrointestinal disorders. The oral microbiota plays an important role in human health and may be altered by the presence of GERD. Here, we aimed to investigate the alterations of salivary microbiota in GERD patients. MethodsWe collected clinical information and salivary samples from 60 individuals. All participants underwent combined pH/impedance monitoring measurement and submitted samples for salivary microbiota sequencing. According to acid exposure time and DeMeester score, participants were divided into two groups: GERD + (Group G) and GERD – (Group C). ResultsThere was no significant difference in alpha diversity between study groups. Regarding beta diversity, principal coordinate analysis plots indicated that the microbiota composition data of the participants were grouped within partial overlapping clusters. The statistical analysis of the distance matrices was performed using the Adonis test (p = 0.017). Based on linear discriminant analysis effect size, the relative abundances of the phylum Bacteroidetes, class Bacteroidia, order Bacteroidales, family Prevotellaceae, and genus unidentified_Prevotellaceae were enriched in Group G. Compared with Group C, the phylum Actinobacteria, classes unidentified_Actinobacteria and Bacilli, orders Micrococcales and Lactobacillales, families Micrococcaceae and Streptococcaceae, and genuses Rothia and Streptococcus were decreased in Group G. At the genus level, the abundances of Streptococcus and Rothia were negatively correlated with DeMeester score and acid exposure time. ConclusionsThis study revealed alterations of the salivary microbiota in GERD patients, suggesting that acid reflux changes the oral ecosystem.

Superdiffusion-like behavior in zero-temperature coarsening of the d=3 Ising model

One key aspect of coarsening following a quench below the critical temperature is domain growth. For the non-conserved Ising model a power-law growth of domains of like spins with exponent alpha = 1/2 is predicted. Including recent work, it was not possible to clearly observe this growth law in the special case of a zero-temperature quench in the three-dimensional model. Instead a slower growth with alpha <1/2 was reported. We attempt to clarify this discrepancy by running large-scale Monte Carlo simulations on simple-cubic lattices with linear lattice sizes up to L=2048 employing an efficient GPU implementation. Indeed, at late times we measure domain sizes compatible with the expected growth law—but surprisingly, at still later times domains even grow superdiffusively, i.e., with alpha > 1/2. We argue that this new problem is possibly caused by sponge-like structures emerging at early times.

Fecal microbial biomarkers combined with multi-target stool DNA test improve diagnostic accuracy for colorectal cancer.

Colorectal cancer (CRC) is a major global health burden. The current diagnostic tests have shortcomings of being invasive and low accuracy. To explore the combination of intestinal microbiome composition and multi-target stool DNA (MT-sDNA) test in the diagnosis of CRC. We assessed the performance of the MT-sDNA test based on a hospital clinical trial. The intestinal microbiota was tested using 16S rRNA gene sequencing. This case-control study enrolled 54 CRC patients and 51 healthy controls. We identified biomarkers of bacterial structure, analyzed the relationship between different tumor markers and the relative abundance of related flora components, and distinguished CRC patients from healthy subjects by the linear discriminant analysis effect size, redundancy analysis, and random forest analysis. MT-sDNA was associated with Bacteroides. MT-sDNA and carcinoembryonic antigen (CEA) were positively correlated with the existence of Parabacteroides, and alpha-fetoprotein (AFP) was positively associated with Faecalibacterium and Megamonas. In the random forest model, the existence of Streptococcus, Escherichia, Chitinophaga, Parasutterella, Lachnospira, and Romboutsia can distinguish CRC from health controls. The diagnostic accuracy of MT-sDNA combined with the six genera and CEA in the diagnosis of CRC was 97.1%, with a sensitivity and specificity of 98.1% and 92.3%, respectively. There is a positive correlation of MT-sDNA, CEA, and AFP with intestinal microbiome. Eight biomarkers including six genera of gut microbiota, MT-sDNA, and CEA showed a prominent sensitivity and specificity for CRC prediction, which could be used as a non-invasive method for improving the diagnostic accuracy for this malignancy.

Characterization of the follicular fluid microbiota based on culturomics and sequencing analysis.

Introduction. The human oocyte microenvironment is follicular fluid, which is important for follicle growth, ovulation and maturation of the oocyte. The micro-organisms present in follicular fluid could be a predictor of in vitro fertilization outcomes.Hypothesis/Gap Statement. Women with follicular fluid colonized with micro-organisms can be asymptomatic, but the presence of some genera in the follicular fluid correlates with in vitro fertilization.Aim. To confirm the existence of micro-organisms in follicular fluid, and to profile the micro-organisms present in follicular fluid sampled from women undergoing in vitro fertilization with different outcomes.Methodology. Women undergoing in vitro fertilization (n=163) were divided into different subgroups according to their in vitro fertilization outcomes. Their follicular fluid samples were collected, and among them, 157 samples were analysed by 16S rDNA sequencing, and 19 samples were analysed using culturomics.Results. The culturomics results suggested that the 19 follicular fluid samples were not sterile. The isolation rates for Streptococcus, Finegoldia and Peptoniphilus were >50 % in the 19 samples. Linear discriminant analysis effect size analysis showed differential bacteria abundance according to the pregnancy rate, the rate of normal fertilization, the rate of high-quality embryos and the rate of available oocytes. The sequencing results showed that micro-organisms could be detected in all 157 samples. Pseudomonas, Lactobacillus, Comamonas, Streptococcus and Acinetobacter were detected in all of the samples, but with a wide range of relative abundance. Pseudomonas, Lactobacillus, Ralstonia and Vibrio constituted a notable fraction of the microbiota.Conclusions. Follicular fluid is not sterile. Micro-organisms in follicular fluid could be a predictor of in vitro fertilization outcomes.

Influence of ammonia nitrogen management strategies on microbial communities in biofloc-based aquaculture systems

Controlling ammonia nitrogen is very important in intensive aquaculture. This study evaluated how different management strategies, i.e., chemoautotrophic (control), heterotrophic bacterial enhancement using carbon in glucose or polyhydroxy butyrate-hydroxy valerate (PHBV), and mature biofloc application, affect water quality and microbial community structure and composition. The management strategies were examined during the domestication and fish culture stages. In the domestication stage, the average NO2−-N concentration, pH, and DO in the glucose-added groups were significantly lower than those in the control and PHBV groups. All water quality parameters differed significantly among treatment groups in the culture stage. Carbon additions decreased both bacterial richness and diversity in the fish culture stage. Both principal coordinate analysis and hierarchical cluster analysis grouped the 33 bacteria community samples from the two stages into four clusters, which were closely related to management strategy. The dominant taxa of the clusters were identified using linear discriminant analysis effect size (LEfSe). The biomarkers of Cluster I included Marinomonas, Photobacterium, and Vibrio. Porticoccus and Clade-1a were identified as the biomarkers of Cluster II. Marivia, Leucothrix, and Phaeodactylibacter were identified as the biomarkers of Cluster IV. The Cluster I biomarkers were positively correlated with NO2−-N, while those of Cluster IV were positively correlated with NO3−-N. The redundancy analysis showed that the bacterial communities and biomarkers were influenced by water quality parameters. Quantitative real-time PCR analysis revealed significant differences in the abundances of the amoA and nxrB genes among treatments and between the two stages. The abundance of the amoA gene was higher in the control group than in the carton-added treatments at the ends of both stages. This study provides an important theoretical basis for the selection of efficient ammonia nitrogen control strategies in aquaculture systems.

First insights into diversity and potential metabolic pathways of bacterial and fungal communities in the rhizosphere of Argemonemexicana L. (Papaveraceae) from the water-level-fluctuation zone of Wudongde Reservoir of the upper Yangtze river, China.

The water-level fluctuation zone (WLFZ) of Wudongde reservoir of the upper Yangtze river is a completely new aquatic-terrestrial transitional zone, and its plant degenerate issue is attracting global concerns. Uncovering the unknown rhizosphere microbiome of dominant plants of this zone is helpful in understanding the plant-microbe interactions and their growth under the largely varying environment. Here, a first exploration of the rhizosphere bacterial and fungal communities of wilted (JB) and unwilted (JA) Argemonemexicana L. individuals from the WLFZ of Wudongde reservoir was carried out using high-throughput sequencing and MetaCyc metabolic pathway analyses. The results showed that rhizosphere of wilted A.mexicana L individuals exhibited a higher microbial richness and diversity than the unwilted ones, irrespective of the bacterial and fungal communities. It was noted that 837 common bacterial amplicon sequence variants (ASV) and 92 common fungal ASV were presented in both JA and JB with 3108 bacteria and 212 fungi unique to JA, and 3569 bacteria and 693 fungi unique to JB. Linear discriminant analysis effect Size (LEfSe) analyses indicated that the taxa that had the most contribution to observed differences between both JA and JB was Proteobacteria, Actinobacteria and Ascomycota for JA, and Bacteroidetes, Firmicutes, Verrucomicrobia, Basidiomycota and Ascomycota for JB. Organic compound conversion pathway (degradation/reduction/oxidation) was consistently highly represented in the rhizosphere microbiomes of both JA and JB. Overall, this study provides insights into the rhizosphere microbiome composition, diversity and metabolic pathways of both wilted and unwilted A.mexicana L. individuals in the WLFZ of Wudongde reservoir, and the results give valuable clues for manipulating microbes to support plant growth in such a recently-formed WLFZ under a dry-hot valley environment.

The association between nasal mucosa bacteria and serum metals in children with nasal diseases

Allergic rhinitis (AR) and adenoid hypertrophy (AH) are common nasal diseases in children. Studies have shown that heavy metals are environmental risk factors for nasal diseases, and the pathogenic mechanisms may be related to dysregulation of nasal mucosal microbiota. However, it is unclear how heavy metal exposure relates to the nasal mucosal microbiota in nasal diseases. Therefore, we explored serum metal exposure levels and nasal mucosal microbiota composition in children with different nasal disease, and further studied the potential correlation between metal exposure and disease-related taxa. There were 64 children recruited for this study. The 23 metals concentrations in serum were measured by inductively coupled plasma mass spectrometry, and nasal mucosal bacteria was identified by 16S rRNA sequencing. Nasal diseases (AR and AH) in children were associated with alterations in the abundance and diversity of the nasal mucosal microbiota. The nasal microbiota of children with AR showed lower diversity, while the microbiota of children with AH showed higher diversity. Linear discriminant analysis Effect Size showed 108 differentially abundant taxa between AR and control groups, 35 differentially abundant taxa among large adenoid, moderate adenoid and small adenoid groups. The serum zinc concentration was negatively correlated with Pielou's eveness index and Simpson's Index in children classified by adenoid size. The spearman correlation analysis showed that multiple disease-related taxa were closely associated with metal concentrations in serum. Our findings may support a link between metal exposure and the diversity and composition of nasal bacteria in children with nasal disease, which present new evidence for the effects of metals on children health.

Fecal microbiota of the synanthropic golden jackal (Canis aureus)

The golden jackal (Canis aureus), is a medium canid carnivore widespread throughout the Mediterranean region and expanding into Europe. This species thrives near human settlements and is implicated in zoonoses such as rabies. This study explores for the first time, the golden jackal fecal microbiota. We analyzed 111 fecal samples of wild golden jackals using 16S rRNA amplicon sequencing the connection of the microbiome to animal characteristics, burden of pathogens and geographic and climate characteristics. We further compared the fecal microbiota of the golden jackal to the black-backed jackal and domestic dog. We found that the golden jackal fecal microbiota is dominated by the phyla Bacteroidota, Fusobacteriota and Firmicutes. The golden jackal fecal microbiota was associated with different variables, including geographic region, age-class, exposure to rabies oral vaccine, fecal parasites and toxoplasmosis. A remarkable variation in the relative abundance of different taxa was also found associated with different variables, such as age-class. Linear discriminant analysis effect size (LEfSe) analysis found abundance of specific taxons in each region, Megasphaera genus in group 1, Megamonas genus in group 2 and Bacteroides coprocola species in group 3. We also found a different composition between the fecal microbiota of the golden jackal, blacked-backed jackal and the domestic dog. Furthermore, LEfSe analysis found abundance of Fusobacterium and Bacteroides genera in the golden jackal, Clostridia class in blacked-backed jackal and Megamonas genus in domestic dog. The golden jackal fecal microbiota is influenced by multiple factors including host traits and pathogen burden. The characterization of the microbiota of this thriving species may aid in mapping its spread and proximity to human settlements. Moreover, understanding the jackal microbiota could inform the study of potential animal and human health risks and inform control measures.

Novel Microbial Signatures in the Faecal Microbiome Associated with Severe Alcoholic Hepatitis: Bacteroides Finegoldii and Veillonella Dispar

Background: Alcoholic hepatitis is associated with dysbiosis, resulting in compositional changes in the gut microbiome, endotoxin transfer to the portal vein, and activation of inflammatory signalling pathways in the liver. However, the microbiome signature of severe alcoholic hepatitis (AH) patients of Indian origin is unknown. Aim: To investigate the microbiome diversity of Indian AH patients in comparison to non-alcoholic healthy controls (HC). Methods: 16S rRNA amplicon-based metagenomics analysis of faecal samples at the time of AH diagnosis (n=12) was compared with HC (n=6), and correlation with survival status, co-occurrence networking, Linear Discriminant Analysis Effect Size (LEfSe), and the relationship between diet – microbiome were performed. Results: 16S rDNA data showed a significant abundance of the Enterobacteriaceae family belonging to the phylum Proteobacteria and a depletion of the phylum Firmicutes in AH. A species-level classification identified Klebsiella pneumonia, Klebsiella variicola, and Parabacteroides distasonis as having the highest predictive performance value with reference to mortality at 60 days. Apart from this, a unique finding was the abundance of Bacteroides finegoldii and Veillonella dispar in AH patients. Moreover, the co-occurrence networking analysis revealed a higher level of connectivity and complexity within the microbial community of AH patients compared to HC. Thus, indicating the significant positive association (Spearman r &gt; 0.7, p &lt; 0.01) among members of the Firmicutes, Bacteroidetes, and Proteobacteria phyla in AH. Wilcoxon-Rank Sum test (p &lt; 0.01) identified Firmicutes phyla occurrence associated with high carbohydrate intake and Actinobacteria phyla with low protein intake. Conclusion: The findings provide the baseline occurrence profile of the gut microbiome signature of liver damage and the diet-microbiome relationship in patients with severe AH. The study demonstrated an abundance of Proteobacteria phyla, indicating their role in inflammatory conditions, and further identified Bacteroides finegoldii and Veillonella dispar in severe AH patients. Additionally, Klebsiella pneumonia, Klebsiella variicola, and Parabacteroides distasonis were identified as mortality-predictive risk biomarkers.

Multiquanta flux jumps in superconducting fractal

We study the magnetic field response of millimeter scale fractal Sierpinski gaskets (SG) assembled of superconducting equilateral triangular patches. Directly imaged quantitative induction maps reveal hierarchical periodic filling of enclosed void areas with multiquanta magnetic flux, which jumps inside the voids in repeating bundles of individual flux quanta Φ0. The number Ns of entering flux quanta in different triangular voids of the SG is proportional to the linear size s of the void, while the field periodicity of flux jumps varies as 1/s. We explain this behavior by modeling the triangular voids in the SG with effective superconducting rings and by calculating their response following the London analysis of persistent currents, Js, induced by the applied field Ha and by the entering flux. With changing Ha, Js reaches a critical value in the vertex joints that connect the triangular superconducting patches and allows the giant flux jumps into the SG voids through phase slips or multiple Abrikosov vortex transfer across the vertices. The unique flux behavior in superconducting SG patterns, may be used to design tunable low-loss resonators with multi-line high-frequency spectrum for microwave technologies.

Coupled Fredkin and Motzkin chains from quantum six- and nineteen-vertex models

We generalize the area-law violating models of Fredkin and Motzkin spin chains into two dimensions by building quantum six- and nineteen-vertex models with correlated interactions. The Hamiltonian is frustration free, and its projectors generate ergodic dynamics within the subspace of height configuration that are non negative. The ground state is a volume- and color-weighted superposition of classical bi-color vertex configurations with non-negative heights in the bulk and zero height on the boundary. The entanglement entropy between subsystems has a phase transition as the qq-deformation parameter is tuned, which is shown to be robust in the presence of an external field acting on the color degree of freedom. The ground state undergoes a quantum phase transition between area- and volume-law entanglement phases with a critical point where entanglement entropy scales as a function L\log LLlogL of the linear system size LL. Intermediate power law scalings between L\log LLlogL and L^2L2 can be achieved with an inhomogeneous deformation parameter that approaches 1 at different rates in the thermodynamic limit. For the q&amp;gt;1q&gt;1 phase, we construct a variational wave function that establishes an upper bound on the spectral gap that scales as q^{-L^3/8}q−L3/8.

Characteristics of gut microbiota in male periadolescent rats with irritable bowel syndrome

Irritable bowel syndrome (IBS) is a prevalent functional gastrointestinal disorder, however, its effect on gut microbiota during the periadolescent period remains unclear. In this study, our objective was to investigate the characteristics of gut microbiota in male periadolescent rats with IBS induced by neonatal maternal separation (NMS). We evaluated visceral sensitivity by electromyography (EMG), analyzed gut microbiota composition using 16S rDNA gene sequencing, and examined intestinal pathological changes between control and IBS-like groups. The IBS-like group had significantly higher discharge amplitude of the external oblique muscle of the abdomen during colorectal distension (CRD) at 40- and 60 mmHg pressures. We observed differences in gut microbiota composition, with an increase in Bacteroidetes abundance and a decrease in Firmicutes in IBS-like rats. Beta-diversity analysis revealed the gut microbiota of the IBS-like group displayed higher consistent, while that of the control group exhibited substantial variation. Linear discriminant analysis effect size (LEfSe) detected 10 bacterial taxonomic clades showing statistically significant differences (7 increased and 3 decreased) in the IBS-like group. Functional analysis revealed that aminoacyl-tRNA biosynthesis and fatty acid biosynthesis were significantly altered, leading to changes in gene expression. Our findings demonstrate a definite correlation between gut microbiota dysbiosis and IBS during the male periadolescent period, with Alloprevotella and Bacteroide positively associated with high risk of IBS. The effects of specific bacterial genera may provide new insights for the development of treatments for IBS.

Local-Global Context Aware Transformer for Language-Guided Video Segmentation.

We explore the task of language-guided video segmentation (LVS). Previous algorithms mostly adopt 3D CNNs to learn video representation, struggling to capture long-term context and easily suffering from visual-linguistic misalignment. In light of this, we present Locater (local-global context aware Transformer), which augments the Transformer architecture with a finite memory so as to query the entire video with the language expression in an efficient manner. The memory is designed to involve two components - one for persistently preserving global video content, and one for dynamically gathering local temporal context and segmentation history. Based on the memorized local-global context and the particular content of each frame, Locater holistically and flexibly comprehends the expression as an adaptive query vector for each frame. The vector is used to query the corresponding frame for mask generation. The memory also allows Locater to process videos with linear time complexity and constant size memory, while Transformer-style self-attention computation scales quadratically with sequence length. To thoroughly examine the visual grounding capability of LVS models, we contribute a new LVS dataset, A2D-S +, which is built upon A2D-S dataset but poses increased challenges in disambiguating among similar objects. Experiments on three LVS datasets and our A2D-S + show that Locater outperforms previous state-of-the-arts. Further, we won the 1st place in the Referring Video Object Segmentation Track of the 3rd Large-scale Video Object Segmentation Challenge, where Locater served as the foundation for the winning solution.

Analysis of Fecal Microbial Changes in Young Calves Following Bovine Rotavirus Infection.

The objective of the present study was to identify changes in fecal microbiota and predict the functional features of healthy calves and those infected with rotavirus over time. Six Holstein calves (average body weight 43.63 ± 1.19 kg, age-matched within 5-7 d) were randomly selected and distributed into two groups which contained three calves each. Fecal samples were taken 3 days before inoculation and on days 1 and 7 post-inoculation. The 16S rRNA gene amplicon sequencing was performed. Bacterial diversity tended to decrease in the rota group, as indicated by the alpha (evenness, p = 0.074 and Shannon, p = 0.055) and beta (Bray-Curtis dissimilarity, p = 0.099) diversity at 1 day post-inoculation. Differences in the bacterial taxa between healthy and rota-infected calves were detected using a linear discriminant analysis effect size (LDA > 2.0, p < 0.05). Rota calves had a higher abundance of certain bacterial taxa, such as Enterococcus, Streptococcus, and Escherichia-Shigella, and a lower abundance of bacteria that contribute to the production of short-chain fatty acids, such as Alistipes, Faecalibacterium, Pseudoflavonifractor, Subdoligranulum, Alloprevotella, Butyricicoccus, and Ruminococcus, compared to the healthy calves. The observed changes in the fecal microbiota of the rota-infected group compared to the healthy group indicated potential dysbiosis. This was further supported by significant differences in the predicted functional metagenomic profiles of these microbial communities. We suggest that calves infected with bovine rotavirus had bacterial dysbiosis, which was characterized by lower diversity and fewer observed genera than the fecal microbiota of healthy calves.

Safe reuse of wastewater: Effect of disinfection methods on microbial community

Performic acid (PFA), a new generation of disinfectant, has shown outstanding performance for wastewater treatment. However, the effect of PFA on wastewater microbial community changes as well as the differences in comparison to the commonly disinfectants used are poorly documented. We provide an overview of the PFA effect and that of chlorine and UV, two commonly used disinfectants, on microbial community diversity and structure. The study was performed using wastewaters from three municipal wastewater treatment plants (WWTPs) processed by activated sludge, lagoon and reed beds, and biofilter. We focused on disinfection of pathogen microorganisms, identifying sensitive and resistant bacteria to disinfectants that can serve as biomarkers for evaluating the disinfectant performances. As well, we investigated the modifications of microbial functions after treatment by functional predictive analysis. The more efficient E. coli inactivation was obtained with initial concentration of 4 mg/L of PFA with 15 min disinfectant contact time that achieved 95.71–99.99% inactivation efficiency. Although the origin of wastewater was the main factor determining the microbial community diversity and composition, the microbial communities were specific to the disinfectant used. Linear discriminant analysis Effect Size (LEfSe) identified 18 and 10 biomarkers, including pathogenic microorganisms affiliated to Chromobacterium, Flavobacterium, Aeromonas, Enterobacteriaceae, Escherichia_Shigella and Fusobacteriaceae, which were sensitive to PFA, while being resistant to chlorine and/or UV. Consistently, the predicted bacterial functional patterns diverged according to the wastewater origin and the disinfectant used. Pathogen microorganisms were more sensitive to PFA than the other treatments, demonstrating its potential for implementing a safe reuse of wastewater.

LXGB: a machine learning algorithm for estimating the discharge coefficient of pseudo-cosine labyrinth weir

One of the practical and financial solutions to increase the efficiency of weirs is to modify the geometry of the plan and increase the length of the weir to a specific width. This increases the discharge coefficient (Cd) of the weir. In this study, a new weir referred to pseudo-cosine labyrinth weir (PCLW) was introduced. A hybrid machine learning LXGB algorithm was introduced to estimate the Cd of the PCLW. The LXGB is a combination of the linear population size reduction history-based adaptive differential evolution (LSHADE) and extreme gradient boosting (XGB) algorithm. Seven different input scenarios were presented to estimate the discharge coefficient of the PCLW weir. To train and test the proposed method, 132 data series, including geometric and hydraulic parameters from PCLW1 and PCLW2 models were used. The root mean square error (RMSE), relative root mean square error (RRMSE), and Nash–Sutcliffe model efficiency coefficient (NSE) indices were used to evaluate the proposed approach. The results showed that the input variables were the ratio of the radius to the weir height (R/W), the ratio of the length of the weir to the weir height (L/W), and the ratio of the hydraulic head to the weir height (H/W), with the average values of RMSE = 0.009, RRMSE = 0.010, and NSE = 0.977 provided better results in estimating the Cd of PCLW1 and PCLW2 models. The improvement compared to SAELM, ANFIS-FFA, GEP, and ANN in terms of R2 is 2.06%, 3.09%, 1.03%, and 5.15%. In general, intelligent hybrid approaches can be introduced as the most suitable method for estimating the Cd of PCLW weirs.

Comparative analysis of the gut microbiota of wild wintering whooper swans (Cygnus Cygnus), captive black swans (Cygnus Atratus), and mute swans (Cygnus Olor) in Sanmenxia Swan National Wetland Park of China.

The gastrointestinal microbiota, a complex ecosystem, is involved in the physiological activities of hosts and the development of diseases. Birds occupy a critical ecological niche in the ecosystem, performing a variety of ecological functions and possessing a complex gut microbiota composition. However, the gut microbiota of wild and captive birds has received less attention in the same region. We profiled the fecal gut microbiome of wild wintering whooper swans (Cygnus Cygnus; Cyg group, n = 25), captive black swans (Cygnus Atratus; Atr group, n = 20), and mute swans (Cygnus Olor;Olor group, n = 30) using 16S rRNA gene sequencing to reveal differences in the gut microbial ecology. The results revealed that the three species of swans differed significantly in terms of the alpha and beta diversity of their gut microbiota, as measured by ACE, Chao1, Simpson and Shannon indices, principal coordinates analysis (PCoA) and non-metricmulti-dimensional scaling (NMDS) respectively. Based on the results of the linear discriminant analysis effect size (LEfSe) and random forest analysis, we found that there were substantial differences in the relative abundance of Gottschalkia, Trichococcus, Enterococcus, and Kurthia among the three groups. Furthermore, an advantageous pattern of interactions between microorganisms was shown by the association network analysis. Among these, Gottschalkia had the higher area under curve (AUC), which was 0.939 (CI = 0.879-0.999), indicating that it might be used as a biomarker to distinguish between wild and captive black swans. Additionally, PICRUSt2 predictions indicated significant differences in gut microbiota functions between wild and captive trumpeter swans, with the gut microbiota functions of Cyg group focusing on carbohydrate metabolism, membrane transport, cofactor, and vitamin metabolism pathways, the Atr group on lipid metabolism, and the Olor group on cell motility, amino acid metabolism, and replication and repair pathways. These findings showed that the gut microbiota of wild and captive swans differed, which is beneficial to understand the gut microecology of swans and to improve regional wildlife conservation strategies.

Oral and gut microbial biomarkers of susceptibility to respiratory tract infection in adults: A feasibility study

We conducted a feasibility cohort study which aimed to recruit and retain adults from the community to collect saliva (oral) and stool (gut) samples at three time points, at the start of the study (baseline), during a respiratory tract infection (RTI) and post-RTI. Community RTIs place a huge burden on health care services, and a non-invasive microbial diagnostic tool to predict the most vulnerable to respiratory infection would be ideal. To this aim, we analysed oral-gut baseline samples comparing those who reported RTI symptoms to those who remained healthy throughout the study for microbial biomarkers of respiratory susceptibility. Amplicon sequence variants (ASV) were identified by 16S sequence profiling to reveal oral-gut microbes. Reverse transcriptase-polymerase chain reaction (RT-PCR) was applied to target common respiratory microbes. Two general practices were recruited, and the participant recruitment rate was 1.3%. A total of 40 adult participants were retained, of which 19 acquired an RTI whereas 21 remained healthy. In healthy baseline oral and gut samples, ASVs from participants with RTI symptoms compared to those who remained healthy were similar with a high relative abundance of Streptococcus sp., and Blautia sp., respectively. Linear discriminant analysis effect size (LEfSe) revealed baseline oral microbes differed, indicating participants who suffered RTI symptoms had enhanced Streptococcus sobrinus and Megamonas sp., and depletion of Lactobacillus salivarius, Synergistetes, Verrucomicrobia and Dethiosulfovibrio. Furthermore, a random forest model ranked Streptococcus (4.13) as the highest mean decrease in accuracy (MDA) and RT-PCR showed a higher level of carriage of coagulase-negative Staphylococcus. Baseline core gut microbes were similar in both participant groups whereas LEfSe analysis revealed enhanced Veillonella, Rikenellaceae, Enhydobacteria, Eggerthella and Xanthomonsdales and depleted Desulfobulbus and Coprobacillus. Sutterella (4.73) had a high MDA value. Overall, we demonstrated the feasibility of recruiting and retaining adult participants from the community to provide multiple biological samples for microbial profiling. Our analyses identified potential oral-gut microbial biomarkers of respiratory infection susceptibility in otherwise healthy participants.