The macroscale routing mechanism of structural brain connectivity related to body mass index.

Understanding the brain's mechanisms in individuals with obesity is important for managing body weight. Prior neuroimaging studies extensively investigated alterations in brain structure and function related to body mass index (BMI). However, how the network communication among the large-scale brain networks differs across BMI is underinvestigated. This study used diffusion magnetic resonance imaging of 290 young adults to identify links between BMI and brain network mechanisms. Navigation efficiency, a measure of network routing, was calculated from the structural connectivity computed using diffusion tractography. The sensory and frontoparietal networks indicated positive associations between navigation efficiency and BMI. The neurotransmitter association analysis identified that serotonergic and dopaminergic receptors, as well as opioid and norepinephrine systems, were related to BMI-related alterations in navigation efficiency. The transcriptomic analysis found that genes associated with network routing across BMI overlapped with genes enriched in excitatory and inhibitory neurons, specifically, gene enrichments related to synaptic transmission and neuron projection. Our findings suggest a valuable insight into understanding BMI-related alterations in brain network routing mechanisms and the potential underlying cellular biology, which might be used as a foundation for BMI-based weight management.

Differences in cortical microstructure according to body mass index in neurologically healthy populations using structural magnetic resonance imaging.

Associations between brain structure and body mass index (BMI) are increasingly gaining attention. Although BMI-related regional alterations in brain morphology have been previously reported, the effect of BMI on the microstructural profiles, which provide information on the proxy of neuronal density within the cortex, is unexplored. In this study, we investigated the links between cortical layer-specific microstructural profiles and BMI in 302 neurologically healthy young adults. Using the microstructure-sensitive proxy based on the T1-and T2-weighted ratio, we estimated microstructural profile covariance (MPC) by calculating linear correlations of cortical depth-wise intensity profiles between different brain regions. Then, low-dimensional gradients of the MPC matrix were estimated using dimensionality reduction techniques, and the gradients were associated with BMI. Significant effects in the heteromodal association areas were observed. The BMI-gradient association map was related to the geodesic distance along the cortical surface, curvature, and sulcal depth, suggesting that the microstructural alterations occurred along the cortical topology. The BMI-gradient association map was further linked to cognitive states related to negative emotions. Our findings may provide insights into understanding the atypical cortical microstructure associated with BMI.

Shifts in structural connectome organization in the limbic and sensory systems of patients with episodic migraine.

Migraine is a complex neurological condition characterized by recurrent headaches, which is often accompanied by various neurological symptoms. Magnetic resonance imaging (MRI) is a powerful tool for investigating whole-brain connectivity patterns; however, systematic assessment of structural connectome organization has rarely been performed. In the present study, we aimed to examine the changes in structural connectivity in patients with episodic migraines using diffusion MRI. First, we computed structural connectivity using diffusion MRI tractography, after which we applied dimensionality reduction techniques to the structural connectivity and generated three low-dimensional eigenvectors. We subsequently calculated the manifold eccentricity, defined as the Euclidean distance between each data point and the center of the data in the manifold space. We then compared the manifold eccentricity between patients with migraines and healthy controls, revealing significant between-group differences in the orbitofrontal cortex, temporal pole, and sensory/motor regions. Between-group differences in subcortico-cortical connectivity further revealed significant changes in the amygdala, accumbens, and caudate nuclei. Finally, supervised machine learning effectively classified patients with migraines and healthy controls using cortical and subcortical structural connectivity features, highlighting the importance of the orbitofrontal and sensory cortices, in addition to the caudate, in distinguishing between the groups. Our findings confirmed that episodic migraine is related to the structural connectome changes in the limbic and sensory systems, suggesting its potential utility as a diagnostic marker for migraine.

Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass index.

Body mass index (BMI) is an indicator of obesity, and recent neuroimaging studies have demonstrated that inter-individual variations in BMI are associated with altered brain structure and function. However, the mechanism underlying the alteration of structure-function correspondence according to BMI is under-investigated. In this study, we studied structural and functional connectivity derived from diffusion MRI tractography and inter-regional correlations of functional MRI time series, respectively. We combined the structural and functional connectivity information using the Riemannian optimization approach. First, the low-dimensional principal eigenvectors (i.e., gradients) of the structural connectivity were generated by applying diffusion map embedding with varying diffusion times. A transformation was identified so that the structural and functional embeddings share the same coordinate system, and subsequently, the functional connectivity matrix was simulated. Then, we generated gradients from the simulated functional connectivity matrix. We found the most apparent cortical hierarchical organization differentiating between low-level sensory and higher-order transmodal regions in the middle of the diffusion time, indicating that the hierarchical organization of the brain may reflect the intermediate mechanisms of mono- and polysynaptic communications. Associations between the functional gradients and BMI were strongest when the hierarchical structure was the most evident. Moreover, the gradient-BMI association map was related to the microstructural features, and the findings indicated that the BMI-related structure-function coupling was significantly associated with brain microstructure, particularly in higher-order transmodal areas. Finally, transcriptomic association analysis revealed the potential biological underpinnings specifying gene enrichment in the striatum, hypothalamus, and cortical cells. Our findings provide evidence that structure-function correspondence is strongly coupled with BMI when hierarchical organization is the most apparent and that the associations are related to the multiscale properties of the brain, leading to an advanced understanding of the neural mechanisms related to BMI.

GAN-MAT: Generative adversarial network-based microstructural profile covariance analysis toolbox.

Multimodal magnetic resonance imaging (MRI) provides complementary information for investigating brain structure and function; for example, an in vivo microstructure-sensitive proxy can be estimated using the ratio between T1- and T2-weighted structural MRI. However, acquiring multiple imaging modalities is challenging in patients with inattentive disorders. In this study, we proposed a comprehensive framework to provide multiple imaging features related to the brain microstructure using only T1-weighted MRI. Our toolbox consists of (i) synthesizing T2-weighted MRI from T1-weighted MRI using a conditional generative adversarial network; (ii) estimating microstructural features, including intracortical covariance and moment features of cortical layer-wise microstructural profiles; and (iii) generating a microstructural gradient, which is a low-dimensional representation of the intracortical microstructure profile. We trained and tested our toolbox using T1- and T2-weighted MRI scans of 1,104 healthy young adults obtained from the Human Connectome Project database. We found that the synthesized T2-weighted MRI was very similar to the actual image and that the synthesized data successfully reproduced the microstructural features. The toolbox was validated using an independent dataset containing healthy controls and patients with episodic migraine as well as the atypical developmental condition of autism spectrum disorder. Our toolbox may provide a new paradigm for analyzing multimodal structural MRI in the neuroscience community and is openly accessible at https://github.com/CAMIN-neuro/GAN-MAT.

Flavivirga spongiicola sp. nov. and Flavivirga abyssicola sp. nov., Isolated from Marine Environments.

Two novel Gram-stain-negative, strictly-aerobic, rod-shaped (1.2 ± 3.4 µm × 0.3 ± 0.7 µm), and non-motile marine bacterial species, designated MEBiC05379T and MEBiC07777T, were isolated from a marine sponge Pseudaxinella sp. in Gangneung City and deep-sea sediments of the Ulleung basin in the East Sea of Korea, respectively. The 16S rRNA gene sequence analysis revealed high levels of similarities between these strains and members of the genus Flavivirga (97.0-98.4% sequence identities). Both novel strains revealed as mesophilic, neutrophilic in pH and slightly halophilic. Similar to those of other Flavivirga members, the primary cellular fatty acids of both strains were iso-C15:0, iso-C15:1 G, iso-C15:03-OH, and iso-C17:0 3-OH, with MEBiC05379T and MEBiC07777T containing relatively higher proportions of C12:0 and summed feature 3 (C16:1ω7c and/or C16:1ω6c). In both taxa, the major isoprenoid quinone was MK-6. The DNA G + C contents of MEBiC05379T and MEBiC07777T genomes were 32.62 and 32.46 mol%, respectively. Compared to other members of Flavivirga, both strains exhibited similar DNA G + C ratio and fatty acids pattern, yet enzyme expression and carbon sources utilization pattern were different. Genomes of the genus Flavivirga showed enzyme preferences to fucoidan and sulfated galactans. Considering the monophyly rule, AAI values delineate the genus Flavivirga from adjacent genera calculated to be 76.0-78.7%. Based on the phenotypic, genomic and biochemical data, strains for MEBiC05379T and MEBiC07777T thus represent two novel species in the genus Flavivirga, for which the names Flavivirga spongiicola sp. nov. (MEBiC05379T [= KCTC 92527 T = JCM 16662 T]), and Flavivirga abyssicola sp. nov. (MEBiC07777T [= KCTC 92563 T = JCM 36477 T]) are proposed.

Does quorum quenching matter to microbial community dynamics in long-term membrane bioreactor operation?

Quorum quenching (QQ) has effectively prevented biofouling in membrane bioreactors (MBRs) employing isolated QQ bacterial strains. However, the influence of QQ on the microbial population still needs to be fully understood. This research aims to analyze the microbial population in MBRs over an extended period (>250 days) under different conditions, such as varying aeration intensities and doses of QQ bacteria, QQ media, and types of feed. Results show that no significant changes occurred in the structure and diversity of the microbial community in the mixed liquor and biofilm due to QQ treatment. Canonical correspondence analysis did reveal that the microbial communities were strongly influenced by feed types and phases. The microbial community composition varied between bacterial habitats (i.e., mixed liquor and biofilm), showing the two dominant phyla Proteobacteria and Bacteroidota in the former and Proteobacteria and Chloroflexi in the latter. The co-occurrence network analysis indicated that the biofilm (with 163 edges) in the MBR fed with real wastewater exhibited a more intricate network than the biofilm (with 53 edges) in the MBR fed with synthetic wastewater. With QQ, the biofilm exhibited more positive edges than negative ones. The phylogenetic investigation of communities showed that QQ barely affects functional gene-related quorum sensing (e.g., bacterial chemotaxis, motility proteins, and secretion) in mixed liquor but in biofilms at relatively large QQ doses (> 75 mg/L BH4). This research sheds light on the bacterial QQ's role in reducing MBR biofouling and provides crucial insights into its underlying mechanisms.

Thermococcus argininiproducens sp. nov., an arginine biosynthesis archaeal species isolated from the Central Indian Ocean ridge.

A strictly anaerobic hyperthermophilic archaeon, designated strain IOH2T, was isolated from a deep-sea hydrothermal vent (Onnuri vent field) area on the Central Indian Ocean Ridge. Strain IOH2T showed high 16S rRNA gene sequence similarity to Thermococcus sibiricus MM 739T (99.42 %), Thermococcus alcaliphilus DSM 10322T (99.28 %), Thermococcus aegaeus P5T (99.21 %), Thermococcus litoralis DSM 5473T (99.13 %), 'Thermococcus bergensis' T7324T (99.13 %), Thermococcus aggregans TYT (98.92 %) and Thermococcus prieurii Bio-pl-0405IT2T (98.01 %), with all other strains showing lower than 98 % similarity. The average nucleotide identity and in silico DNA-DNA hybridization values were highest between strain IOH2T and T. sibiricus MM 739T (79.33 and 15.00 %, respectively); these values are much lower than the species delineation cut-offs. Cells of strain IOH2T were coccoid, 1.0-1.2 µm in diameter and had no flagella. Growth ranges were 60-85 °C (optimum at 80 °C), pH 4.5-8.5 (optimum at pH 6.3) and 2.0-6.0 % (optimum at 4.0 %) NaCl. Growth of strain IOH2T was enhanced by starch, glucose, maltodextrin and pyruvate as a carbon source, and elemental sulphur as an electron acceptor. Through genome analysis of strain IOH2T, arginine biosynthesis related genes were predicted, and growth of strain IOH2T without arginine was confirmed. The genome of strain IOH2T was assembled as a circular chromosome of 1 946 249 bp and predicted 2096 genes. The DNA G+C content was 39.44 mol%. Based on the results of physiological and phylogenetic analyses, Thermococcus argininiproducens sp. nov. is proposed with type strain IOH2T (=MCCC 4K00089T=KCTC 25190T).

Spinach (Spinacia oleracea) as green manure modifies the soil nutrients and microbiota structure for enhanced pepper productivity.

Spinach has been suggested as a potential rotation crop for increasing crop yield by enhancing beneficial fungal microbes in continuous monocropping. However, no research on the use of spinach as a green manure has been reported. Thus, we tested the effects of spinach and Korean mustard cultivars (green and red mustards) (10 g pot -1) as green manure on soil chemical properties, pepper productivity, and soil microbiome of long-year pepper-monocropped soil. Spinach improved the soil nutrition (e.g., pH, SOM, TN, NH4+, and K), weed suppression, and pepper growth. Spinach had by far the highest fruit yield, over 100% pepper fruit yield increment over the mustard green manures and control. Our study showed that the major influencing factors to cause a shift in both bacterial and fungal community assemblies were soil pH, TC TN, and K. Following green manure amendment Bacillota, especially Clostridium, Bacillus and Sedimentibacter, were enriched, whereas Chloroflexi and Acidobacteriota were reduced. In addition, spinach highly reduced the abundance of Leotiomycetes and Fusarium but enriched Papiliotrema. FAPROTAX and FUNGuild analysis revealed that predicted functional profiles of bacterial and fungal communities in spinach-amended soil were changed. Spinach-treated soil was differentially abundant in function related to hydrocarbon degradation and functional guilds of symbiotrophs and ectomycorrhizal. This study contributes significantly to our understanding of how the soil fertility and soil microbiome alteration via spinach green manure application as a pre-plant soil treatment might help alleviate continuous cropping obstacles.

Dietary regulations for microbiota dysbiosis among post-menopausal women with type 2 diabetes.

Type 2 diabetes (T2D) and T2D-associated comorbidities, such as obesity, are serious universally prevalent health issues among post-menopausal women. Menopause is an unavoidable condition characterized by the depletion of estrogen, a gonadotropic hormone responsible for secondary sexual characteristics in women. In addition to sexual dimorphism, estrogen also participates in glucose-lipid homeostasis, and estrogen depletion is associated with insulin resistance in the female body. Estrogen level in the gut also regulates the microbiota composition, and even conjugated estrogen is actively metabolized by the estrobolome to maintain insulin levels. Moreover, post-menopausal gut microbiota is different from the pre-menopausal gut microbiota, as it is less diverse and lacks the mucolytic Akkermansia and short-chain fatty acid (SCFA) producers such as Faecalibacterium and Roseburia. Through various metabolites (SCFAs, secondary bile acid, and serotonin), the gut microbiota plays a significant role in regulating glucose homeostasis, oxidative stress, and T2D-associated pro-inflammatory cytokines (IL-1, IL-6). While gut dysbiosis is common among post-menopausal women, dietary interventions such as probiotics, prebiotics, and synbiotics can ease post-menopausal gut dysbiosis. The objective of this review is to understand the relationship between post-menopausal gut dysbiosis and T2D-associated factors. Additionally, the study also provided dietary recommendations to avoid T2D progression among post-menopausal women.

Review of the Current State of Freely Accessible Web Tools for the Analysis of 16S rRNA Sequencing of the Gut Microbiome.

Owing to the emergence and improvement of high-throughput technology and the associated reduction in costs, next-generation sequencing (NGS) technology has made large-scale sampling and sequencing possible. With the large volume of data produced, the processing and downstream analysis of data are important for ensuring meaningful results and interpretation. Problems in data analysis may be encountered if researchers have little experience in using programming languages, especially if they are clinicians and beginners in the field. A strategy for solving this problem involves ensuring easy access to commercial software and tools. Here, we observed the current status of free web-based tools for microbiome analysis that can help users analyze and handle microbiome data effortlessly. We limited our search to freely available web-based tools and identified MicrobiomeAnalyst, Mian, gcMeta, VAMPS, and Microbiome Toolbox. We also highlighted the various analyses that each web tool offers, how users can analyze their data using each web tool, and noted some of their limitations. From the abovementioned list, gcMeta, VAMPS, and Microbiome Toolbox had several issues that made the analysis more difficult. Over time, as more data are generated and accessed, more users will analyze microbiome data. Thus, the availability of free and easily accessible web tools can enable the easy use and analysis of microbiome data, especially for those users with less experience in using command-line interfaces.

Bioconversion of CO to formate by artificially designed carbon monoxide:formate oxidoreductase in hyperthermophilic archaea.

Ferredoxin-dependent metabolic engineering of electron transfer circuits has been developed to enhance redox efficiency in the field of synthetic biology, e.g., for hydrogen production and for reduction of flavoproteins or NAD(P)+. Here, we present the bioconversion of carbon monoxide (CO) gas to formate via a synthetic CO:formate oxidoreductase (CFOR), designed as an enzyme complex for direct electron transfer between non-interacting CO dehydrogenase and formate dehydrogenase using an electron-transferring Fe-S fusion protein. The CFOR-introduced Thermococcus onnurineus mutant strains showed CO-dependent formate production in vivo and in vitro. The maximum formate production rate from purified CFOR complex and specific formate productivity from the bioreactor were 2.2 ± 0.2 µmol/mg/min and 73.1 ± 29.0 mmol/g-cells/h, respectively. The CO-dependent CO2 reduction/formate production activity of synthetic CFOR was confirmed, indicating that direct electron transfer between two unrelated dehydrogenases was feasible via mediation of the FeS-FeS fusion protein.

Microbiome dataset of spontaneously fermented Ethiopian honey wine, Tej.

This dataset contains raw and analyzed microbial data for the samples of spontaneously fermented Ethiopian honey wine, Tej, collected from three locations of Ethiopia. It was generated using culture independent amplicon sequencing technique. To gain a better understanding of microbial community variance and similarity across Tej samples from the same and different locations, the raw sequenced data obtained from the Illumina Miseq sequencer was subjected to a bioinformatics analysis. Lower diversity and richness of both bacterial and fungal communities were observed for all of the Tej samples. Besides, samples collected from Debre Markos area showed a significant discriminating tax for both bacterial and fungal communities. In nutshell, this amplicon sequencing dataset provides a useful collection of data for modernizing this spontaneous fermentation into a directed inoculated fermentation. Detail discussion on microbiome of Tej samples is given in [1].

Physicochemical properties, antioxidant activities and microbial communities of Ethiopian honey wine, Tej.

Ethiopian honey wine, Tej, is spontaneously fermented traditional alcoholic beverage, usually made from honey and "gesho" (Rhamnus prinoides). Till now, limited amount of information is available on the characterization of Tej. Thus, the aim of this paper is to reveal the microbiological diversity and physicochemical properties of Tej samples collected from different areas of Ethiopia. High-throughput sequencing, electrochemical and chromatographic techniques, and spectrophotometric methods were used to achieve these objectives. Although there was a statistical difference in the exact values of physicochemical properties between the collected Tej samples, the pH and titratable acidity values of the samples ranged from 2.8 to 3.8 and from 1.81 to 8.65 g/L, respectively. Similarly, the alcohol and sugar contents of the samples were in the range of 6.36-11.34 g/100 mL and from 0.37 to 31.6 g/L, respectively. Moreover, the 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 3-ethylbenzothiazoline-6-sulfonic acid diammonium salt (ABTS) values of the samples were in the range of 37.9-81.0% and 27.4-73.1%, respectively. Furthermore, microbial community structure was predominated by a few fermentative microorganisms. Specifically, the bacterial community structure was dominated by the genera of Lactobacillus (53.15%) and Zymomonas (38.41%). Whereas, the fungal community structure was exclusively dominated by genus of Saccharomyces (99.66%). Additionally, Lactobacillus, Zymomonas and Saccharomyces were the detected core microbiome for the collected Tej samples. Both bacterial and fungal communities had shown no statistically significant differences in alpha diversity analysis based on the area of sample collection. However, the bacterial communities had a statically significant difference in Unweighted Unifrac beta diversity analysis. Generally, the observed shared physicochemical characteristic features and the dominance by certain group of microorganisms might be seen as a boon for the development of direct fermentation system to this traditional alcoholic beverage.

Bacterial Profiles of Brain in Downer Cattle with Unknown Etiology.

Downer cow can be caused by muscular paralysis, neurological damage, metabolic disorder, and/or the complication of microbial infection. However, downer cow with unknown etiology is issued because of the non-detection of its bacterial etiological agent. In this study, differences in the bacterial community in brain tissues between downer cattle with unknown etiology and healthy slaughtered cattle are investigated. Bacterial diversity and representative genera between downer and normal cattle were significantly different (p < 0.05). There are significant differences in representative genera of downer and normal cattle, especially the significance, fold change, and area under the receiver operating characteristic curve score (p < 0.05). Furthermore, the prediction of functional genes in brain microbiota between the downer and normal cattle revealed differences in the cluster of orthologous gene categories, such as lipid transport and metabolism, secondary metabolite biosynthesis, and signal transduction (p < 0.05). This study revealed a significant difference in microbiota between the downer and normal cattle. Thus, we demonstrate that representative genera from downer cattle through 16S rRNA gene amplicon sequencing and microbiota analysis have the potential as candidates for bacterial etiological agents for downer cow.

Photolytic quorum quenching effects on the microbial communities and functional gene expressions in membrane bioreactors.

Photolytic quorum quenching by ultraviolet A (UVA) irradiation is an effective strategy for controlling membrane bioreactor (MBR) biofouling; however, its effects on MBR microbial communities and functional genes have not yet been explored. Here, we report on the effects of the UVA irradiation, which mitigates membrane biofouling, on the microbial community structures, alpha and beta diversities, and functional gene expressions in the MBR mixed liquor and biocake (membrane fouling layer) for the first time. The results show that the microbial communities become less diversified when alternating UVA is applied to the MBRs. The changes in the community structure are highly influenced by spatiotemporal factors, such as microbial habitats (mixed liquor and biocake) and reactor operation time, although UVA irradiation also has some impacts on the community. The relative abundance of the Sphingomonadaceae family, which can decompose the furan ring of autoinducer-2 (AI-2) signal molecules, becomes greater with continuous UVA irradiation. Xanthomonadaceae, which produces biofilm-degrading enzymes, is also more abundant with UVA photolysis than without it. Copies of monooxygenase and hydroxylase enzyme-related genes increase in the MBR with longer UVA exposures (i.e., continuous UVA). These enzymes seem to be inducible by UVA, enhancing the AI-2 inactivation. In conclusion, UVA irradiation alters the microbial community and the metabolism in the MBR, contributing to the membrane biofouling mitigation.

Effect of a bioconverted product of Lotus corniculatus seed on the axillary microbiome and body odor.

The skin microbiome, especially the axillary microbiome, consists of odor-causing bacteria that decompose odorless sweat into malodor compounds, which contributes to the formation of body odor. Plant-derived products are a cheap source of bioactive compounds that are common ingredients in cosmetics. Microbial bioconversion of natural products is an ecofriendly and economical method for production of new or improved biologically active compounds. Therefore, in this study, we tested the potential of a Lactobacillus acidophilus KNU-02-mediated bioconverted product (BLC) of Lotus corniculatus seed to reduce axillary malodor and its effect on the associated axillary microbiota. A chemical profile analysis revealed that benzoic acid was the most abundant chemical compound in BLC, which increased following bioconversion. Moreover, BLC treatment was found to reduce the intensity of axillary malodor. We tested the axillary microbiome of 18 study participants, divided equally into BLC and placebo groups, and revealed through 16S rRNA gene sequencing that Staphylococcus, Corynebacterium, and Anaerococcus were the dominant taxa, and some of these taxa were significantly associated with axillary malodor. After one week of BLC treatment, the abundance of Corynebacterium and Anaerococcus, which are associated with well-known odor-related genes that produce volatile fatty acids, had significantly reduced. Likewise, the identified odor-related genes decreased after the application of BLC. BLC treatment enhanced the richness and network density of the axillary microbial community. The placebo group, on the other hand, showed no difference in the microbial richness, odor associated taxa, and predicted functional genes after a week. The results demonstrated that BLC has the potential to reduce the axillary malodor and the associated odor-causing bacteria, which makes BLC a viable deodorant material in cosmetic products.

Alteration of the Soil Microbiota in Ginseng Rusty Roots: Application of Machine Learning Algorithm to Explore Potential Biomarkers for Diagnostic and Predictive Analytics.

Conceptualization to utilize microbial composition as a prediction tool has been widely applied in human cohorts, yet the potential capacity of soil microbiota as a diagnostic tool to predict plant phenotype remains unknown. Here, we collected 130 soil samples which are 54 healthy controls and 76 ginseng rusty roots (GRRs). Alpha diversities including Shannon, Simpson, Chao1, and phylogenetic diversity were significantly decreased in GRR (P < 0.05). Moreover, we identified 30 potential biomarkers. The optimized markers were obtained through fivefold cross-validation on a support vector machine and yielded a robust area under the curve of 0.856. Notably, evaluation of multi-index classification performance including accuracy, F1-score, and Kappa coefficient also showed robust discriminative capability (90.99%, 0.903, and 0.808). Taken together, our results suggest that the disease affects the microbial community and offers the potential ability of soil microbiota to identifying farms at the risk of GRR.

Use of Opioids and Outcomes of Pneumonia: Results From the US Nationwide Inpatient Sample.

BACKGROUND: Opioids have been shown to increase risk of pneumonia among susceptible population. However, the effect of opioid abuse on the outcome of pneumonia has not been evaluated at the population level. We aimed to compare the outcomes of pneumonia among patients with opioid use disorder and patients without substance use disorder using a large population database. METHODS: We assembled a pneumonia cohort composed of 11,186,564 adult patients from the National Inpatient Sample (NIS; 2005-2014). Patients with opioid disorder were identified using the International Classification of Diseases, 9th Revision, Clinical Modification codes. We compared health-related and economic outcomes between patients with and without opioid disorders using propensity score matching (PSM) analysis to balance baseline differences. The survival differences between two groups of patients were assessed using a Cox proportional hazard model. We further explored the possibility of effect modification by interaction analyses in different populations. RESULTS: After PSM, patients with opioid use disorder were at increased risk of ventilator use (odds ratio [OR]: 1.22, 95% confidence interval [CI]: 1.08 to 1.38, p = 0.0014) and associated with increased length of hospital stay by 0.59 days (95% CI: 0.35 to 0.83, p < 0.001), compared with those without substance use disorder. Patients with opioid use also had higher daily (228.00 USD, 95% CI: 180.51 to 275.49, p < 0.001) and total (1,875.72 USD, 95% CI: 1,259.63 to 2,491.80, p < 0.001) medical costs. Subgroup analyses showed similar results. CONCLUSIONS: Compared with patients without any drug dependence, patients with opioid use disorders had increased risk of complications and resource utilization. This study adds evidence for increased risk for pneumonia complications in the growing patients with opioid use disorders.

Vaginal Microbiome-Based Bacterial Signatures for Predicting the Severity of Cervical Intraepithelial Neoplasia.

Although emerging evidence revealed that the gut microbiome served as a tool and as biomarkers for predicting and detecting specific cancer or illness, it is yet unknown if vaginal microbiome-derived bacterial markers can be used as a predictive model to predict the severity of CIN. In this study, we sequenced V3 region of 16S rRNA gene on vaginal swab samples from 66 participants (24 CIN 1-, 42 CIN 2+ patients) and investigated the taxonomic composition. The vaginal microbial diversity was not significantly different between the CIN 1- and CIN 2+ groups. However, we observed Lactobacillus amylovorus dominant type (16.7%), which does not belong to conventional community state type (CST). Moreover, a minimal set of 33 bacterial species was identified to maximally differentiate CIN 2+ from CIN 1- in a random forest model, which can distinguish CIN 2+ from CIN 1- (area under the curve (AUC) = 0.952). Among the 33 bacterial species, Lactobacillus iners was selected as the most impactful predictor in our model. This finding suggests that the random forest model is able to predict the severity of CIN and vaginal microbiome may play a role as biomarker.