EUS-Guided Cholecystoduodenostomy for a Poor Surgical Candidate With Chronic Octreotide-Associated Gallstones From Metastatic Neuroendocrine Tumor.

Chronic octreotide use has been associated with gallstone formation. Historically, cholecystectomy has been the defining treatment for those who have gallstone-related disease. For those who are poor surgical candidates, percutaneous and endoscopic approaches have been used. We describe the endoscopic management of a 74-year-old man with significant gallstone burden and associated sequelae because of chronic octreotide for metastatic neuroendocrine tumor through endoscopic ultrasound-guided cholecystoduodenostomy with gallstone extraction using lumen-apposing metal stents.

Molecular assessment of intratumoral immune cell subsets and potential mechanisms of resistance to odronextamab, a CD20×CD3 bispecific antibody, in patients with relapsed/refractory B-cell non-Hodgkin lymphoma.

BACKGROUND: Patients with relapsed/refractory B-cell non-Hodgkin lymphoma (R/R B-NHL) have a significant need for effective treatment options. Odronextamab is an Fc-silenced, human, CD20×CD3 bispecific antibody that targets CD20-expressing cells via T-cell-mediated cytotoxicity independent of T-cell/major histocompatibility complex interaction. Phase I results in patients with R/R B-NHL demonstrated that odronextamab monotherapy could achieve deep and durable responses with a generally manageable safety profile (ELM-1; NCT02290951). As part of a biomarker analysis of the same study, we investigated potential biomarkers and mechanisms of resistance to odronextamab. METHODS: Patients with R/R B-NHL enrolled in ELM-1 received one time per week doses of intravenous odronextamab for 4×21 day cycles, then doses every 2 weeks thereafter. Patient tumor biopsies were obtained at baseline, on-treatment, and at progression. Immune cell markers were analyzed by immunohistochemistry, flow cytometry, single-cell RNA sequencing, and whole genome sequencing. RESULTS: Baseline tumor biopsies showed that almost all patients had high proportions of B cells that expressed the CD20 target antigen, whereas expression of other B-cell surface antigens (CD19, CD22, CD79b) was more variable. Responses to odronextamab in patients with diffuse large B-cell lymphoma were not related to the relative level of baseline CD20 expression, cell of origin, or high-risk molecular subtype. A potential link was observed between greater tumor programmed cell death-ligand 1 expression and increased likelihood of response to odronextamab. Similarly, a trend was observed between clinical response and increased levels of CD8 T cells and regulatory T cells at baseline. We also identified an on-treatment pharmacodynamic shift in intratumoral immune cell subsets. Finally, loss of CD20 expression through inactivating gene mutations was identified as a potential mechanism of resistance in patients who were treated with odronextamab until progression, as highlighted in two detailed patient cases reported here. CONCLUSIONS: This biomarker analysis expands on clinical findings of odronextamab in patients with R/R B-NHL, providing verification of the suitability of CD20 as a therapeutic target, as well as evidence for potential mechanisms of action and resistance.

Computational analysis followed by in vitro studies to explore cytokines (TNF-α, IL-6 and IL-1ß) inhibition potential of the new natural molecule polonilignan.

Targeting pro-inflammatory cytokines and their production is found to be of therapeutic benefit for the regulation of inflammation in various chronic autoimmune diseases. Our continued efforts to discover small molecular-weight pro-inflammatory cytokine inhibitors resulted in identifying a novel natural lignan molecule named polonilignan, isolated from the culture broth extract of an endophytic fungus Penicillium polonicum. An in silico study (molecular docking, ADME predictions, binding free energy calculation and molecular dynamics simulation) of the polonilignan over the pro-inflammatory cytokines proteins TNF-α, IL-6 and IL-1ß was performed using Schrodinger LLC software to understand the binding interactions, drug-like properties, and stability of the ligand-protein complex. Further, in-vitro testing of inhibition of TNF-α, IL-6 and IL-1ß by polonilignan was carried out using ELISA and RT-PCR on LPS-induced RAW 264.7 cell lines along with the testing of nitrite production effect (Griess assay) and cytotoxicity (MTT) analysis. Under the computational study, polonilignan revealed good docking scores, binding interactions, and stability under MDS and desirable in silico ADME results over the proteins TNF-α, IL-1ß and IL-6. Poloniligan showed significant inhibition of IL-1ß, IL-6 and TNF-α with IC50 values of 2.01 µM, 6.59 µM and 42.10 µM, respectively. Also, it reduced the translocation of the NF-κB subunit p65 to the nucleus (confocal microscopy). The mRNA expression levels of pro-inflammatory markers IL-1ß, TNF-α and IL-6 levels were lowered significantly (p < .001) by the compound, and the diminution was higher with IL-1ß. Further, the lignan was non-cytotoxic and effective in attenuating nitrite release (IC50 48.56 µM). Thus, polonilignan has been identified as a new pan-cytokine and NO inhibitor, it is recommended to optimise a method for the synthesis of this small molecular weight lignan and explore its pharmacokinetic characteristics, toxicity and therapeutic effect under various chronic inflammatory disease models.

Bifunctional Amorphous Transition-Metal Phospho-Boride Electrocatalysts for Selective Alkaline Seawater Splitting at a Current Density of 2A cm-2.

Hydrogen production by direct seawater electrolysis is an alternative technology to conventional freshwater electrolysis, mainly owing to the vast abundance of seawater reserves on earth. However, the lack of robust, active, and selective electrocatalysts that can withstand the harsh and corrosive saline conditions of seawater greatly hinders its industrial viability. Herein, a series of amorphous transition-metal phospho-borides, namely Co-P-B, Ni-P-B, and Fe-P-B are prepared by simple chemical reduction method and screened for overall alkaline seawater electrolysis. Co-P-B is found to be the best of the lot, requiring low overpotentials of ≈270 mV for hydrogen evolution reaction (HER), ≈410 mV for oxygen evolution reaction (OER), and an overall voltage of 2.50 V to reach a current density of 2 A cm-2 in highly alkaline natural seawater. Furthermore, the optimized electrocatalyst shows formidable stability after 10,000 cycles and 30 h of chronoamperometric measurements in alkaline natural seawater without any chlorine evolution, even at higher current densities. A detailed understanding of not only HER and OER but also chlorine evolution reaction (ClER) on the Co-P-B surface is obtained by computational analysis, which also sheds light on the selectivity and stability of the catalyst at high current densities.

ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization.

Antibiotic resistance is of crucial interest to both human and animal medicine. It has been recognized that increased environmental monitoring of antibiotic resistance is needed. Metagenomic DNA sequencing is becoming an attractive method to profile antibiotic resistance genes (ARGs), including a special focus on pathogens. A number of computational pipelines are available and under development to support environmental ARG monitoring; the pipeline we present here is promising for general adoption for the purpose of harmonized global monitoring. Specifically, ARGem is a user-friendly pipeline that provides full-service analysis, from the initial DNA short reads to the final visualization of results. The capture of extensive metadata is also facilitated to support comparability across projects and broader monitoring goals. The ARGem pipeline offers efficient analysis of a modest number of samples along with affordable computational components, though the throughput could be increased through cloud resources, based on the user's configuration. The pipeline components were carefully assessed and selected to satisfy tradeoffs, balancing efficiency and flexibility. It was essential to provide a step to perform short read assembly in a reasonable time frame to ensure accurate annotation of identified ARGs. Comprehensive ARG and mobile genetic element databases are included in ARGem for annotation support. ARGem further includes an expandable set of analysis tools that include statistical and network analysis and supports various useful visualization techniques, including Cytoscape visualization of co-occurrence and correlation networks. The performance and flexibility of the ARGem pipeline is demonstrated with analysis of aquatic metagenomes. The pipeline is freely available at https://github.com/xlxlxlx/ARGem.

Hydrothermal topotactic epitaxy of SrTiO3 on Bi4Ti3O12 nanoplatelets: understanding the interplay of lattice mismatch and supersaturation.

The engineering of epitaxial, two-dimensional (2D) nano-heterostructures has stimulated great interest owing to an expectation of better functional properties (e.g., photocatalytic, piezoelectric). Hydrothermal topotactic epitaxy is one of the promising synthetic approaches for their preparation, particularly the formation of a highly ordered, epitaxial interface and possibilities for the preparation of anisotropic nanostructures of symmetrical materials. The present study highlights the key parameters when steering the alkaline, hydrothermal, topochemical conversion process from Bi4Ti3O12 nanoplatelets to the intermediate, epitaxial, SrTiO3/Bi4Ti3O12 nano-heterostructures and the final SrTiO3 nanoplatelets by balancing the lattice mismatch and the supersaturation. An atomic-scale examination revealed the formation of an ordered epitaxial SrTiO3/Bi4Ti3O12 interface with the presence of dislocations. The SrTiO3 grows in islands for a stoichiometric amount of Sr (Sr/Ti = 1) and the growth resembles a layer-by-layer mode for surplus Sr content (Sr/Ti ≥ 12). The latter enables SrTiO3 overgrowth of the Bi4Ti3O12 basal surface planes, protecting them against dissolution from the top and consequently ensuring the preservation of the platelet morphology during the entire transformation process, the kinetics of which is controlled by the base concentration. A developed understanding of this particular transformation provides the guiding principles and ideas for designing other defined or complex epitaxial heterostructures and structures under low-temperature hydrothermal conditions.

mobileOG-db: a Manually Curated Database of Protein Families Mediating the Life Cycle of Bacterial Mobile Genetic Elements.

Bacterial mobile genetic elements (MGEs) encode functional modules that perform both core and accessory functions for the element, the latter of which are often only transiently associated with the element. The presence of these accessory genes, which are often close homologs to primarily immobile genes, incur high rates of false positives and, therefore, limits the usability of these databases for MGE annotation. To overcome this limitation, we analyzed 10,776,849 protein sequences derived from eight MGE databases to compile a comprehensive set of 6,140 manually curated protein families that are linked to the "life cycle" (integration/excision, replication/recombination/repair, transfer, stability/transfer/defense, and phage-specific processes) of plasmids, phages, integrative, transposable, and conjugative elements. We overlay experimental information where available to create a tiered annotation scheme of high-quality annotations and annotations inferred exclusively through bioinformatic evidence. We additionally provide an MGE-class label for each entry (e.g., plasmid or integrative element), and assign to each entry a major and minor category. The resulting database, mobileOG-db (for mobile orthologous groups), comprises over 700,000 deduplicated sequences encompassing five major mobileOG categories and more than 50 minor categories, providing a structured language and interpretable basis for an array of MGE-centered analyses. mobileOG-db can be accessed at mobileogdb.flsi.cloud.vt.edu/, where users can select, refine, and analyze custom subsets of the dynamic mobilome. IMPORTANCE The analysis of bacterial mobile genetic elements (MGEs) in genomic data is a critical step toward profiling the root causes of antibiotic resistance, phenotypic or metabolic diversity, and the evolution of bacterial genera. Existing methods for MGE annotation pose high barriers of biological and computational expertise to properly harness. To bridge this gap, we systematically analyzed 10,776,849 proteins derived from eight databases of MGEs to identify 6,140 MGE protein families that can serve as candidate hallmarks, i.e., proteins that can be used as "signatures" of MGEs to aid annotation. The resulting resource, mobileOG-db, provides a multilevel classification scheme that encompasses plasmid, phage, integrative, and transposable element protein families categorized into five major mobileOG categories and more than 50 minor categories. mobileOG-db thus provides a rich resource for simple and intuitive element annotation that can be integrated seamlessly into existing MGE detection pipelines and colocalization analyses.

Demonstrating a Comprehensive Wastewater-Based Surveillance Approach That Differentiates Globally Sourced Resistomes.

Wastewater-based surveillance (WBS) for disease monitoring is highly promising but requires consistent methodologies that incorporate predetermined objectives, targets, and metrics. Herein, we describe a comprehensive metagenomics-based approach for global surveillance of antibiotic resistance in sewage that enables assessment of 1) which antibiotic resistance genes (ARGs) are shared across regions/communities; 2) which ARGs are discriminatory; and 3) factors associated with overall trends in ARGs, such as antibiotic concentrations. Across an internationally sourced transect of sewage samples collected using a centralized, standardized protocol, ARG relative abundances (16S rRNA gene-normalized) were highest in Hong Kong and India and lowest in Sweden and Switzerland, reflecting national policy, measured antibiotic concentrations, and metal resistance genes. Asian versus European/US resistomes were distinct, with macrolide-lincosamide-streptogramin, phenicol, quinolone, and tetracycline versus multidrug resistance ARGs being discriminatory, respectively. Regional trends in measured antibiotic concentrations differed from trends expected from public sales data. This could reflect unaccounted uses, captured only by the WBS approach. If properly benchmarked, antibiotic WBS might complement public sales and consumption statistics in the future. The WBS approach defined herein demonstrates multisite comparability and sensitivity to local/regional factors.

Declining Colectomy Rates for Nonmalignant Colorectal Polyps in a Large, Ethnically Diverse, Community-Based Population.

INTRODUCTION: Despite studies showing improved safety, efficacy, and cost-effectiveness of endoscopic resection for nonmalignant colorectal polyps, colectomy rates for nonmalignant colorectal polyps have been increasing in the United States and Europe. Given this alarming trend, we aimed to investigate whether colectomy rates for nonmalignant colorectal polyps are increasing or declining in a large, integrated, community-based healthcare system with access to advanced endoscopic resection procedures. METHODS: We identified all individuals aged 50-85 years who underwent a colonoscopy between 2008 and 2018 and were diagnosed with a nonmalignant colorectal polyp(s) at the Kaiser Permanente Northern California integrated healthcare system. Among these individuals, we identified those who underwent a colectomy for nonmalignant colorectal polyps within 12 months after the colonoscopy. We calculated annual colectomy rates for nonmalignant colorectal polyps and stratified rates by age, sex, and race and ethnicity. Changes in rates over time were tested by the Cochran-Armitage test for a linear trend. RESULTS: Among 229,730 patients who were diagnosed with nonmalignant colorectal polyps between 2008 and 2018, 1,611 patients underwent a colectomy. Colectomy rates for nonmalignant colorectal polyps decreased significantly from 125 per 10,000 patients with nonmalignant polyps in 2008 to 12 per 10,000 patients with nonmalignant polyps in 2018 (P < 0.001 for trend). When stratified by age, sex, and race and ethnicity, colectomy rates for nonmalignant colorectal polyps also significantly declined from 2008 to 2018. DISCUSSION: In a large, ethnically diverse, community-based population in the United States, we found that colectomy rates for nonmalignant colorectal polyps declined significantly over the past decade likely because of the establishment of advanced endoscopy centers, improved care coordination, and an organized colorectal cancer screening program.

Data Analytics for Environmental Science and Engineering Research.

The advent of new data acquisition and handling techniques has opened the door to alternative and more comprehensive approaches to environmental monitoring that will improve our capacity to understand and manage environmental systems. Researchers have recently begun using machine learning (ML) techniques to analyze complex environmental systems and their associated data. Herein, we provide an overview of data analytics frameworks suitable for various Environmental Science and Engineering (ESE) research applications. We present current applications of ML algorithms within the ESE domain using three representative case studies: (1) Metagenomic data analysis for characterizing and tracking antimicrobial resistance in the environment; (2) Nontarget analysis for environmental pollutant profiling; and (3) Detection of anomalies in continuous data generated by engineered water systems. We conclude by proposing a path to advance incorporation of data analytics approaches in ESE research and application.

Integrated Metagenomic Assessment of Multiple Pre-harvest Control Points on Lettuce Resistomes at Field-Scale.

An integrated understanding of factors influencing the occurrence, distribution, and fate of antibiotic resistance genes (ARGs) in vegetable production systems is needed to inform the design and development of strategies for mitigating the potential for antibiotic resistance propagation in the food chain. The goal of the present study was to holistically track antibiotic resistance and associated microbiomes at three distinct pre-harvest control points in an agroecosystem in order to identify the potential impacts of key agricultural management strategies. Samples were collected over the course of a single growing season (67 days) from field-scale plots amended with various organic and inorganic amendments at agronomic rates. Dairy-derived manure and compost amendment samples (n = 14), soil samples (n = 27), and lettuce samples (n = 12) were analyzed via shotgun metagenomics to assess multiple pre-harvest factors as hypothetical control points that shape lettuce resistomes. Pre-harvest factors of interest included manure collection during/post antibiotic use, manure composting, and soil amended with organic (stockpiled manure/compost) versus chemical fertilizer. Microbial community resistome and taxonomic compositions were unique from amendment to soil to lettuce surface according to dissimilarity analysis. The highest resistome alpha diversity (i.e., unique ARGs, n = 642) was detected in amendment samples prior to soil application, while the composted manure had the lowest total ARG relative abundance (i.e., 16S rRNA gene-normalized). Regardless of amendment type, soils acted as an apparent ecological buffer, i.e., soil resistome and taxonomic profiles returned to background conditions 67 d-post amendment application. Effects of amendment conditions surprisingly re-emerged in lettuce phyllosphere resistomes, with the highest total ARG relative abundances recovered on the surface of lettuce plants grown in organically-fertilized soils (i.e., compost- and manure-amended soils). Co-occurrence analysis identified 55 unique ARGs found both in the soil amendments and on lettuce surfaces. Among these, arnA and pmrF were the most abundant ARGs co-occurring with mobile genetic elements (MGE). Other prominent ARG-MGE co-occurrences throughout this pre-harvest lettuce production chain included: TetM to transposon (Clostridiodies difficile) in the manure amendment and TriC to plasmid (Ralstonia solanacearum) on the lettuce surfaces. This suggests that, even with imposing manure management and post-amendment wait periods in agricultural systems, ARGs originating from manure can still be found on crop surfaces. This study demonstrates a comprehensive approach to identifying key control points for the propagation of ARGs in vegetable production systems, identifying potential ARG-MGE combinations that could inform future surveillance. The findings suggest that additional pre-harvest and potentially post-harvest interventions may be warranted to minimize risk of propagating antibiotic resistance in the food chain.

Evaluation of Metagenomic-Enabled Antibiotic Resistance Surveillance at a Conventional Wastewater Treatment Plant.

Wastewater treatment plants (WWTPs) receive a confluence of sewage containing antimicrobials, antibiotic resistant bacteria, antibiotic resistance genes (ARGs), and pathogens and thus are a key point of interest for antibiotic resistance surveillance. WWTP monitoring has the potential to inform with respect to the antibiotic resistance status of the community served as well as the potential for ARGs to escape treatment. However, there is lack of agreement regarding suitable sampling frequencies and monitoring targets to facilitate comparison within and among individual WWTPs. The objective of this study was to comprehensively evaluate patterns in metagenomic-derived indicators of antibiotic resistance through various stages of treatment at a conventional WWTP for the purpose of informing local monitoring approaches that are also informative for global comparison. Relative abundance of total ARGs decreased by ∼50% from the influent to the effluent, with each sampling location defined by a unique resistome (i.e., total ARG) composition. However, 90% of the ARGs found in the effluent were also detected in the influent, while the effluent ARG-pathogen taxonomic linkage patterns identified in assembled metagenomes were more similar to patterns in regional clinical surveillance data than the patterns identified in the influent. Analysis of core and discriminatory resistomes and general ARG trends across the eight sampling events (i.e., tendency to be removed, increase, decrease, or be found in the effluent only), along with quantification of ARGs of clinical concern, aided in identifying candidate ARGs for surveillance. Relative resistome risk characterization further provided a comprehensive metric for predicting the relative mobility of ARGs and likelihood of being carried in pathogens and can help to prioritize where to focus future monitoring and mitigation. Most antibiotics that were subject to regional resistance testing were also found in the WWTP, with the total antibiotic load decreasing by ∼40-50%, but no strong correlations were found between antibiotics and corresponding ARGs. Overall, this study provides insight into how metagenomic data can be collected and analyzed for surveillance of antibiotic resistance at WWTPs, suggesting that effluent is a beneficial monitoring point with relevance both to the local clinical condition and for assessing efficacy of wastewater treatment in reducing risk of disseminating antibiotic resistance.

AgroSeek: a system for computational analysis of environmental metagenomic data and associated metadata.

BACKGROUND: Metagenomics is gaining attention as a powerful tool for identifying how agricultural management practices influence human and animal health, especially in terms of potential to contribute to the spread of antibiotic resistance. However, the ability to compare the distribution and prevalence of antibiotic resistance genes (ARGs) across multiple studies and environments is currently impossible without a complete re-analysis of published datasets. This challenge must be addressed for metagenomics to realize its potential for helping guide effective policy and practice measures relevant to agricultural ecosystems, for example, identifying critical control points for mitigating the spread of antibiotic resistance. RESULTS: Here we introduce AgroSeek, a centralized web-based system that provides computational tools for analysis and comparison of metagenomic data sets tailored specifically to researchers and other users in the agricultural sector interested in tracking and mitigating the spread of ARGs. AgroSeek draws from rich, user-provided metagenomic data and metadata to facilitate analysis, comparison, and prediction in a user-friendly fashion. Further, AgroSeek draws from publicly-contributed data sets to provide a point of comparison and context for data analysis. To incorporate metadata into our analysis and comparison procedures, we provide flexible metadata templates, including user-customized metadata attributes to facilitate data sharing, while maintaining the metadata in a comparable fashion for the broader user community and to support large-scale comparative and predictive analysis. CONCLUSION: AgroSeek provides an easy-to-use tool for environmental metagenomic analysis and comparison, based on both gene annotations and associated metadata, with this initial demonstration focusing on control of antibiotic resistance in agricultural ecosystems. Agroseek creates a space for metagenomic data sharing and collaboration to assist policy makers, stakeholders, and the public in decision-making. AgroSeek is publicly-available at https://agroseek.cs.vt.edu/ .

Next generation sequencing approaches to evaluate water and wastewater quality.

The emergence of next generation sequencing (NGS) is revolutionizing the potential to address complex microbiological challenges in the water industry. NGS technologies can provide holistic insight into microbial communities and their functional capacities in water and wastewater systems, thus eliminating the need to develop a new assay for each target organism or gene. However, several barriers have hampered wide-scale adoption of NGS by the water industry, including cost, need for specialized expertise and equipment, challenges with data analysis and interpretation, lack of standardized methods, and the rapid pace of development of new technologies. In this critical review, we provide an overview of the current state of the science of NGS technologies as they apply to water, wastewater, and recycled water. In addition, a systematic literature review was conducted in which we identified over 600 peer-reviewed journal articles on this topic and summarized their contributions to six key areas relevant to the water and wastewater fields: taxonomic classification and pathogen detection, functional and catabolic gene characterization, antimicrobial resistance (AMR) profiling, bacterial toxicity characterization, Cyanobacteria and harmful algal bloom identification, and virus characterization. For each application, we have presented key trends, noteworthy advancements, and proposed future directions. Finally, key needs to advance NGS technologies for broader application in water and wastewater fields are assessed.

Alkaline Water Oxidation Using a Bimetallic Phospho-Boride Electrocatalyst.

New oxygen evolution reaction (OER) electrocatalysts based on low-cost elements, which set new benchmark levels of activity, are vital if water electrolysis is to be applied on a global scale. Herein, a low-cost bimetallic phospho-boride catalyst was developed that showed outstanding OER activity of approximately 195 mV to achieve 10 mA cm-2 in alkaline water electrolysis, with a minimal catalyst loading of 0.3 mg cm-2 . The contrasting electron transfer property of the metal borides and phosphides when combined in phospho-boride modulated the electron density of the Co atom, yielding highly active CoOOH species at lower potentials. The addition of Mo at low levels further enhanced the activity by increasing the surface area and by formation of nano-crystalline domains. The combined contributions from each of the components resulted in a new benchmark mass activity of 666 A g-1 at 300 mV overpotential. This work presents a new avenue towards fabricating electrode materials with exceptional performances.

Applications of Dynamic Covalent Chemistry Concept towards Tailored Covalent Organic Framework Nanomaterials: A Review.

Covalent organic frameworks (COFs) are a rapidly developing class of materials that has been of immense research interest during the last ten years. Numerous reviews have been devoted to summarizing the synthesis and applications of COFs. However, the underlying dynamic covalent chemistry (DCC), which is the foundation of COFs synthesis, has never been systematically reviewed in this context. Dynamic covalent chemistry is the practice of using thermodynamic equilibriums to molecular assemblies. This Critical Review will cover the state-of-the-art use of DCC to both synthesize COFs and expand the applications of COFs. Five synthetic strategies for COF synthesis are rationalized, namely: modulation, mixed linker/linkage, sub-stoichiometric reaction, framework isomerism, and linker exchange, which highlight the dynamic covalent chemistry to regulate the growth and to modify the properties of COFs. Furthermore, the challenges in these approaches and potential future perspectives in the field of COF chemistry are also provided.

Predictors of Disease Recurrence after Venoplasty and Stent Placement for May-Thurner Syndrome.

PURPOSE: To identify factors independently associated with disease recurrence after venoplasty and stent placement for May-Thurner syndrome (MTS). MATERIALS AND METHODS: Fifty-nine consecutive patients (age, 47 y ± 15; 93% female) were identified who had undergone endovascular stent placement for MTS. Patient charts were reviewed for demographic data, risk factors for venous thrombosis, comorbidities, and venous inflow or outflow at first follow-up (3 wk to 6 mo after treatment). Logistic regression was used to identify independent predictors of symptom recurrence or repeat intervention, and multivariate analysis of variance and receiver operator characteristic curve analysis were used to assess relationships between degrees of in-stent stenosis and other variables in the 73% of patients with available cross-sectional imaging. Median follow up was 20.7 months (interquartile range, 4.7-49.5 mo). RESULTS: All procedures were technically successful. Disease recurrence, defined as symptom recurrence following initial postprocedural resolution, was observed in 38% of patients. No preprocedural variable was found to be independently predictive of disease recurrence; however, poor venous inflow or outflow were both strongly associated with recurrent disease, with adjusted odds ratios and 95% confidence intervals of 38.02 (3.76-384.20; P = .002) and 7.00 (1.15-42.71; P = .04), respectively. Higher degrees of in-stent stenosis were also associated with symptom recurrence, with an area under the curve of 0.93 (P = .000002) and 39%-41% stenosis being 78%-83% sensitive and 88%-92% specific for symptom recurrence. CONCLUSIONS: These results suggest that cross-sectional imaging can help differentiate patients in whom closer follow-up may be warranted after venoplasty and stent placement for MTS and also guide counseling regarding prognosis.

Identification of discriminatory antibiotic resistance genes among environmental resistomes using extremely randomized tree algorithm.

BACKGROUND: The interconnectivities of built and natural environments can serve as conduits for the proliferation and dissemination of antibiotic resistance genes (ARGs). Several studies have compared the broad spectrum of ARGs (i.e., "resistomes") in various environmental compartments, but there is a need to identify unique ARG occurrence patterns (i.e., "discriminatory ARGs"), characteristic of each environment. Such an approach will help to identify factors influencing ARG proliferation, facilitate development of relative comparisons of the ARGs distinguishing various environments, and help pave the way towards ranking environments based on their likelihood of contributing to the spread of clinically relevant antibiotic resistance. Here we formulate and demonstrate an approach using an extremely randomized tree (ERT) algorithm combined with a Bayesian optimization technique to capture ARG variability in environmental samples and identify the discriminatory ARGs. The potential of ERT for identifying discriminatory ARGs was first evaluated using in silico metagenomic datasets (simulated metagenomic Illumina sequencing data) with known variability. The application of ERT was then demonstrated through analyses using publicly available and in-house metagenomic datasets associated with (1) different aquatic habitats (e.g., river, wastewater influent, hospital effluent, and dairy farm effluent) to compare resistomes between distinct environments and (2) different river samples (i.e., Amazon, Kalamas, and Cam Rivers) to compare resistome characteristics of similar environments. RESULTS: The approach was found to readily identify discriminatory ARGs in the in silico datasets. Also, it was not found to be biased towards ARGs with high relative abundance, which is a common limitation of feature projection methods, and instead only captured those ARGs that elicited significant profiles. Analyses of publicly available metagenomic datasets further demonstrated that the ERT approach can effectively differentiate real-world environmental samples and identify discriminatory ARGs based on pre-defined categorizing schemes. CONCLUSIONS: Here a new methodology was formulated to characterize and compare variances in ARG profiles between metagenomic data sets derived from similar/dissimilar environments. Specifically, identification of discriminatory ARGs among samples representing various environments can be identified based on factors of interest. The methodology could prove to be a particularly useful tool for ARG surveillance and the assessment of the effectiveness of strategies for mitigating the spread of antibiotic resistance. The python package is hosted in the Git repository: https://github.com/gaarangoa/ExtrARG.

Ag loaded B-doped-g C3N4 nanosheet with efficient properties for photocatalysis.

Three material engineering strategies in the form of doping (Boron-doping), nanostructuring (nanosheet (NS) formation) and decorating with plasmonic nanoparticles (loading with Ag metal), were integrated to improve the photocatalytic activity of graphitic carbon nitride (gC3N4). Concentrations of B-doping and Ag-loading were optimized to maximize the catalytic performance in the final nanocomposite of Ag-loaded B-doped gC3N4 NS. Combined effect of all three strategies successfully produced over 5 times higher rate towards degradation of organic dye pollutant, when compared to unmodified bulk gC3N4. Detailed characterization results revealed that incorporation of B in gC3N4 matrix reduces the band gap to increase the visible light absorption, while specific surface area is significantly enhanced upon formation of NS. Decoration of Ag nanoparticles (NPs) on B-doped gC3N4 NS assists in fast transfer of photogenerated electrons from gC3N4 to Ag NPs owing to the interfacial electric field across the junctions and thus reduces the recombination process. Investigations on individual strategies revealed that decoration of Ag NPs to induce better charge separation, is the most effective route for enhancing the photocatalytic activity.