Selective Covalent Basal Plane Modification as a Probe of Hydroxide Ion Conduction Pathways in Magnesium Aluminum Layered Double Hydroxides.

Understanding ionic conduction in layered double hydroxides (LDHs) is a crucial step towards utilizing them as solid, hydroxide ion-conducting electrolytes in energy conversion applications. We selectively modified the interlayer and external surfaces of MgAl LDHs with tris(hydroxymethyl)aminomethane (TRIS) ligands. By adjusting the concentration of the TRIS surface modifier, the LDH basal plane surfaces could be functionalized everywhere (internally and externally) or only externally. External modification resulted in loss of OH-conductivity compared to pristine LDHs, confirming that external platelet surfaces are the primary ion conduction pathway.

Delimiting Species with Single-Locus DNA Sequences.

DNA sequences are increasingly used for large-scale biodiversity inventories. Because these genetic data avoid the time-consuming initial sorting of specimens based on their phenotypic attributes, they have been recently incorporated into taxonomic workflows for overlooked and diverse taxa. Major statistical developments have accompanied this new practice, and several models have been proposed to delimit species with single-locus DNA sequences. However, proposed approaches to date make different assumptions regarding taxon lineage history, leading to strong discordance whenever comparisons are made among methods. Distance-based methods, such as Automatic Barcode Gap Discovery (ABGD) and Assemble Species by Automatic Partitioning (ASAP), rely on the detection of a barcode gap (i.e., the lack of overlap in the distributions of intraspecific and interspecific genetic distances) and the associated threshold in genetic distances. Network-based methods, as exemplified by the REfined Single Linkage (RESL) algorithm for the generation of Barcode Index Numbers (BINs), use connectivity statistics to hierarchically cluster-related haplotypes into molecular operational taxonomic units (MOTUs) which serve as species proxies. Tree-based methods, including Poisson Tree Processes (PTP) and the General Mixed Yule Coalescent (GMYC), fit statistical models to phylogenetic trees by maximum likelihood or Bayesian frameworks.Multiple webservers and stand-alone versions of these methods are now available, complicating decision-making regarding the most appropriate approach to use for a given taxon of interest. For instance, tree-based methods require an initial phylogenetic reconstruction, and multiple options are now available for this purpose such as RAxML and BEAST. Across all examined species delimitation methods, judicious parameter setting is paramount, as different model parameterizations can lead to differing conclusions. The objective of this chapter is to guide users step-by-step through all the procedures involved for each of these methods, while aggregating all necessary information required to conduct these analyses. The "Materials" section details how to prepare and format input files, including options to align sequences and conduct tree reconstruction with Maximum Likelihood and Bayesian inference. The Methods section presents the procedure and options available to conduct species delimitation analyses, including distance-, network-, and tree-based models. Finally, limits and future developments are discussed in the Notes section. Most importantly, species delimitation methods discussed herein are categorized based on five indicators: reliability, availability, scalability, understandability, and usability, all of which are fundamental properties needed for any approach to gain unanimous adoption within the DNA barcoding community moving forward.

A Measure of the DNA Barcode Gap for Applied and Basic Research.

DNA barcoding has largely established itself as a mainstay for rapid molecular taxonomic identification in both academic and applied research. The use of DNA barcoding as a molecular identification method depends on a "DNA barcode gap"-the separation between the maximum within-species difference and the minimum between-species difference. Previous work indicates the presence of a gap hinges on sampling effort for focal taxa and their close relatives. Furthermore, both theory and empirical work indicate a gap may not occur for related pairs of biological species. Here, we present a novel evaluation approach in the form of an easily calculated set of nonparametric metrics to quantify the extent of proportional overlap in inter- and intraspecific distributions of pairwise differences among target species and their conspecifics. The metrics are based on a simple count of the number of overlapping records for a species falling within the bounds of maximum intraspecific distance and minimum interspecific distance. Our approach takes advantage of the asymmetric directionality inherent in pairwise genetic distance distributions, which has not been previously done in the DNA barcoding literature. We apply the metrics to the predatory diving beetle genus Agabus as a case study because this group poses significant identification challenges due to its morphological uniformity despite both relative sampling ease and well-established taxonomy. Results herein show that target species and their nearest neighbor species were found to be tightly clustered and therefore difficult to distinguish. Such findings demonstrate that DNA barcoding can fail to fully resolve species in certain cases. Moving forward, we suggest the implementation of the proposed metrics be integrated into a common framework to be reported in any study that uses DNA barcoding for identification. In so doing, the importance of the DNA barcode gap and its components for the success of DNA-based identification using DNA barcodes can be better appreciated.

Computational Deconvolution of Cell Type-Specific Gene Expression in COPD and IPF Lungs Reveals Disease Severity Associations.

RATIONALE: Chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) are debilitating diseases associated with divergent histopathological changes in the lungs. At present, due to cost and technical limitations, profiling cell types is not practical in large epidemiology cohorts (n>1000). Here, we used computational deconvolution to identify cell types in COPD and IPF lungs whose abundances and cell type-specific gene expression are associated with disease diagnosis and severity. METHODS: We analyzed lung tissue RNA-seq data from 1026 subjects (COPD, n=465; IPF, n=213; control, n=348) from the Lung Tissue Research Consortium. We performed RNA-seq deconvolution, querying thirty-eight discrete cell-type varieties in the lungs. We tested whether deconvoluted cell-type abundance and cell type-specific gene expression were associated with disease severity. RESULTS: The abundance score of twenty cell types significantly differed between IPF and control lungs. In IPF subjects, eleven and nine cell types were significantly associated with forced vital capacity (FVC) and diffusing capacity for carbon monoxide (DLCO), respectively. Aberrant basaloid cells, a rare cells found in fibrotic lungs, were associated with worse FVC and DLCO in IPF subjects, indicating that this aberrant epithelial population increased with disease severity. Alveolar type 1 and vascular endothelial (VE) capillary A were decreased in COPD lungs compared to controls. An increase in macrophages and classical monocytes was associated with lower DLCO in IPF and COPD subjects. In both diseases, lower non-classical monocytes and VE capillary A cells were associated with increased disease severity. Alveolar type 2 cells and alveolar macrophages had the highest number of genes with cell type-specific differential expression by disease severity in COPD and IPF. In IPF, genes implicated in the pathogenesis of IPF, such as matrix metallopeptidase 7, growth differentiation factor 15, and eph receptor B2, were associated with disease severity in a cell type-specific manner. CONCLUSION: Utilization of RNA-seq deconvolution enabled us to pinpoint cell types present in the lungs that are associated with the severity of COPD and IPF. This knowledge offers valuable insight into the alterations within tissues in more advanced illness, ultimately providing a better understanding of the underlying pathological processes that drive disease progression.

Special Considerations in Podiatric Science: Translational Research, Cadavers, Gait Analysis, Dermatology, and Databases.

The objective of this article is to provide a brief overview of the critical analysis and design of unique and perhaps less common methodologies in podiatric science. These include basic science translational designs, cadaveric investigations, gait analyses, dermatologic studies, and database analysis. The relative advantages, disadvantages, and inherent limitations are reviewed with an intention to improve the interpretation of results and advance future foot and ankle scientific endeavors.

A gentle introduction to computer vision-based specimen classification in ecological datasets.

Classifying specimens is a critical component of ecological research, biodiversity monitoring and conservation. However, manual classification can be prohibitively time-consuming and expensive, limiting how much data a project can afford to process. Computer vision, a form of machine learning, can help overcome these problems by rapidly, automatically and accurately classifying images of specimens. Given the diversity of animal species and contexts in which images are captured, there is no universal classifier for all species and use cases. As such, ecologists often need to train their own models. While numerous software programs exist to support this process, ecologists need a fundamental understanding of how computer vision works to select appropriate model workflows based on their specific use case, data types, computing resources and desired performance capabilities. Ecologists may also face characteristic quirks of ecological datasets, such as long-tail distributions, 'unknown' species, similarity between species and polymorphism within species, which impact the efficacy of computer vision. Despite growing interest in computer vision for ecology, there are few resources available to help ecologists face the challenges they are likely to encounter. Here, we present a gentle introduction for species classification using computer vision. In this manuscript and associated GitHub repository, we demonstrate how to prepare training data, basic model training procedures, and methods for model evaluation and selection. Throughout, we explore specific considerations ecologists should make when training classification models, such as data domains, feature extractors and class imbalances. With these basics, ecologists can adjust their workflows to achieve research goals and/or account for uncertainty in downstream analysis. Our goal is to provide guidance for ecologists for getting started in or improving their use of machine learning for visual classification tasks.

2023 International Consensus Meeting on musculoskeletal infection: Summary from the treatment workgroup and consensus on treatment in preclinical models.

In vitro and in vivo studies are critical for the preclinical efficacy assessment of novel therapies targeting musculoskeletal infections (MSKI). Many preclinical models have been developed and applied as a prelude to evaluating safety and efficacy in human clinical trials. In performing these studies, there is both a requirement for a robust assessment of efficacy, as well as a parallel responsibility to consider the burden on experimental animals used in such studies. Since MSKI is a broad term encompassing infections varying in pathogen, anatomical location, and implants used, there are also a wide range of animal models described modeling these disparate infections. Although some of these variations are required to adequately evaluate specific interventions, there would be enormous value in creating a unified and standardized criteria to animal testing in the treatment of MSKI. The Treatment Workgroup of the 2023 International Consensus Meeting on Musculoskeletal Infection was responsible for questions related to preclinical models for treatment of MSKI. The main objective was to review the literature related to priority questions and estimate consensus opinion after voting. This document presents that process and results for preclinical models related to (1) animal model considerations, (2) outcome measurements, and (3) imaging.

Returning incidentally discovered Hepatitis C RNA-seq results to COPDGene study participants.

The consequences of returning infectious pathogen test results identified incidentally in research studies have not been well-studied. Concerns include identification of an important health issue for individuals, accuracy of research test results, public health impact, potential emotional distress for participants, and need for IRB permissions. Blood RNA-sequencing analysis for non-human RNA in 3984 participants from the COPDGene study identified 228 participants with evidence suggestive for hepatitis C virus (HCV) infection. We hypothesized that incidentally discovered HCV results could be effectively returned to COPDGene participants with attention to the identified concerns. In conjunction with a COPDGene Participant Advisory Panel, we developed and obtained IRB approval for a process of returning HCV research results and an HCV Follow-Up Study questionnaire to capture information about previous HCV diagnosis and treatment information and participant reactions to return of HCV results. During phone calls following the initial HCV notification letter, 84 of 124 participants who could be contacted (67.7%) volunteered that they had been previously diagnosed with HCV infection. Thirty-one of these 124 COPDGene participants were enrolled in the HCV Follow-Up Study. Five of the 31 HCV Follow-Up Study participants did not report a previous diagnosis of HCV. For four of these participants, subsequent clinical HCV testing confirmed HCV infection. Thus, 30/31 Follow-Up Study participants had confirmed HCV diagnoses, supporting the accuracy of the HCV research test results. However, the limited number of participants in the Follow-Up Study precludes an accurate assessment of the false-positive and false-negative rates of the research RNA sequencing evidence for HCV. Most HCV Follow-Up Study participants (29/31) were supportive of returning HCV research results, and most participants found the process for returning HCV results to be informative and not upsetting. Newly diagnosed participants were more likely to be pleased to learn about a potentially curable infection (p = 0.027) and showed a trend toward being more frightened by the potential health risks of HCV (p = 0.11). We conclude that HCV results identified incidentally during transcriptomic research studies can be successfully returned to research study participants with a carefully designed process.

Racial and Ethnic Disparities in the Management of Diabetic Feet.

PURPOSE OF REVIEW: Diabetes mellitus is a chronic medical condition affecting many individuals worldwide and leads to billions of dollars spent within the healthcare system for its treatment and complications. Complications from diabetes include diabetic foot conditions that can have a devasting impact on quality of life. Diabetic foot ulcers and amputations occur in minority individuals at an increased rate compared to Caucasian individuals. This review provides an update examining the racial and ethnic disparities in the management of diabetic foot conditions and the differences in rates of amputation. RECENT FINDINGS: Current research continues to show a disparity as it relates to diabetic foot management. There are novel treatment options for diabetic foot ulcers that are currently being explored. However, there continues to be a lack in racial diversity in new treatment studies conducted in the USA. Individuals from racial and ethnic minority groups have diabetes at higher rates compared to Caucasian individuals, and are also more likely to develop diabetic foot ulcers and receive amputations. Over the last few years, more efforts have been made to improve health disparities. However, there needs to be an improvement in increasing racial diversity when investigating new therapies for diabetic foot ulcers.

Crowd-sourced observations of a polyphagous moth reveal evidence of allochronic speciation varying along a latitudinal gradient.

Allochronic speciation, where reproductive isolation between populations of a species is facilitated by a difference in reproductive timing, depends on abiotic factors such as seasonality and biotic factors such as diapause intensity. These factors are strongly influenced by latitudinal trends in climate, so we hypothesized that there is a relationship between latitude and divergence among populations separated by life history timing. Hyphantria cunea (the fall webworm), a lepidopteran defoliator with red and black colour morphs, is hypothesized to be experiencing an incipient allochronic speciation. However, given their broad geographic range, the strength of allochronic speciation may vary across latitude. We annotated >11,000 crowd-sourced observations of fall webworm to model geographic distribution, phenology, and differences in colour phenotype between morphs across North America. We found that red and black morph life history timing differs across North America, and the phenology of morphs diverges more in warmer climates at lower latitudes. We also found some evidence that the colour phenotype of morphs also diverges at lower latitudes, suggesting reduced gene flow between colour morphs. Our results demonstrate that seasonality in lower latitudes may increase the strength of allochronic speciation in insects, and that the strength of sympatric speciation can vary along a latitudinal gradient. This has implications for our understanding of broad-scale speciation events and trends in global biodiversity.

Blood Gene Expression and Immune Cell Subtypes Associated with Chronic Obstructive Pulmonary Disease Exacerbations.

Rationale: Acute exacerbations of chronic obstructive pulmonary disease (AE-COPDs) are associated with a significant disease burden. Blood immune phenotyping may improve our understanding of a COPD endotype at increased risk of exacerbations. Objective: To determine the relationship between the transcriptome of circulating leukocytes and COPD exacerbations. Methods: Blood RNA sequencing data (n = 3,618) from the COPDGene (Genetic Epidemiology of COPD) study were analyzed. Blood microarray data (n = 646) from the ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) study were used for validation. We tested the association between blood gene expression and AE-COPDs. We imputed the abundance of leukocyte subtypes and tested their association with prospective AE-COPDs. Flow cytometry was performed on blood in SPIROMICS (Subpopulations and Intermediate Outcomes in COPD Study) (n = 127), and activation markers for T cells were tested for association with prospective AE-COPDs. Measurements and Main Results: Exacerbations were reported 4,030 and 2,368 times during follow-up in COPDGene (5.3 ± 1.7 yr) and ECLIPSE (3 yr), respectively. We identified 890, 675, and 3,217 genes associated with a history of AE-COPDs, persistent exacerbations (at least one exacerbation per year), and prospective exacerbation rate, respectively. In COPDGene, the number of prospective exacerbations in patients with COPD (Global Initiative for Chronic Obstructive Lung Disease stage ⩾2) was negatively associated with circulating CD8+ T cells, CD4+ T cells, and resting natural killer cells. The negative association with naive CD4+ T cells was replicated in ECLIPSE. In the flow-cytometry study, an increase in CTLA4 on CD4+ T cells was positively associated with AE-COPDs. Conclusions: Individuals with COPD with lower circulating lymphocyte counts, particularly decreased CD4+ T cells, are more susceptible to AE-COPDs, including persistent exacerbations.

Identifying chronic obstructive pulmonary disease from integrative omics and clustering in lung tissue.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a highly morbid and heterogenous disease. While COPD is defined by spirometry, many COPD characteristics are seen in cigarette smokers with normal spirometry. The extent to which COPD and COPD heterogeneity is captured in omics of lung tissue is not known. METHODS: We clustered gene expression and methylation data in 78 lung tissue samples from former smokers with normal lung function or severe COPD. We applied two integrative omics clustering methods: (1) Similarity Network Fusion (SNF) and (2) Entropy-Based Consensus Clustering (ECC). RESULTS: SNF clusters were not significantly different by the percentage of COPD cases (48.8% vs. 68.6%, p = 0.13), though were different according to median forced expiratory volume in one second (FEV1) % predicted (82 vs. 31, p = 0.017). In contrast, the ECC clusters showed stronger evidence of separation by COPD case status (48.2% vs. 81.8%, p = 0.013) and similar stratification by median FEV1% predicted (82 vs. 30.5, p = 0.0059). ECC clusters using both gene expression and methylation were identical to the ECC clustering solution generated using methylation data alone. Both methods selected clusters with differentially expressed transcripts enriched for interleukin signaling and immunoregulatory interactions between lymphoid and non-lymphoid cells. CONCLUSIONS: Unsupervised clustering analysis from integrated gene expression and methylation data in lung tissue resulted in clusters with modest concordance with COPD, though were enriched in pathways potentially contributing to COPD-related pathology and heterogeneity.

Integrating Genetics, Transcriptomics, and Proteomics in Lung Tissue to Investigate Chronic Obstructive Pulmonary Disease.

The integration of transcriptomic and proteomic data from lung tissue with chronic obstructive pulmonary disease (COPD)-associated genetic variants could provide insight into the biological mechanisms of COPD. Here, we assessed associations between lung transcriptomics and proteomics with COPD in 98 subjects from the Lung Tissue Research Consortium. Low correlations between transcriptomics and proteomics were generally observed, but higher correlations were found for COPD-associated proteins. We integrated COPD risk SNPs or SNPs near COPD-associated proteins with lung transcripts and proteins to identify regulatory cis-quantitative trait loci (QTLs). Significant expression QTLs (eQTLs) and protein QTLs (pQTLs) were found regulating multiple COPD-associated biomarkers. We investigated mediated associations from significant pQTLs through transcripts to protein levels of COPD-associated proteins. We also attempted to identify colocalized effects between COPD genome-wide association studies and eQTL and pQTL signals. Evidence was found for colocalization between COPD genome-wide association study signals and a pQTL for RHOB and an eQTL for DSP. We applied weighted gene co-expression network analysis to find consensus COPD-associated network modules. Two network modules generated by consensus weighted gene co-expression network analysis were associated with COPD with a false discovery rate lower than 0.05. One network module is related to the catenin complex, and the other module is related to plasma membrane components. In summary, multiple cis-acting determinants of transcripts and proteins associated with COPD were identified. Colocalization analysis, mediation analysis, and correlation-based network analysis of multiple omics data may identify key genes and proteins that work together to influence COPD pathogenesis.

Hepatitis C and HIV detection by blood RNA-sequencing in cohort of smokers.

Detection of viruses by RNA and DNA sequencing has improved the understanding of the human virome. We sought to identify blood viral signatures through secondary use of RNA-sequencing (RNA-seq) data in a large study cohort. The ability to reveal undiagnosed infections with public health implications among study subjects with available sequencing data could enable epidemiologic surveys and may lead to diagnosis and therapeutic interventions, leveraging existing research data in a clinical context. We detected viral RNA in peripheral blood RNA-seq data from a COPD-enriched population of current and former smokers. Correlation between viral detection and both reported infections and relevant disease outcomes was evaluated. We identified Hepatitis C virus RNA in 228 subjects and HIV RNA in 30 subjects. Overall, we observed 31 viral species, including Epstein-Barr virus and Cytomegalovirus. We observed an enrichment of Hepatitis C and HIV infections among subjects reporting liver disease and HIV infections, respectively. Higher interferon expression scores were observed in the subjects with Hepatitis C and HIV infections. Through secondary use of RNA-seq from a cohort of current and former smokers, we detected peripheral blood viral signatures. We identified HIV and Hepatitis C virus (HCV), highlighting potential public health implications for the approach described this study. We observed correlations with reported infections, chronic infection outcomes and the host transcriptomic response, providing evidence to support the validity of the approach.

VLF: An R package for the analysis of very low frequency variants in DNA sequences.

Here, we introduce VLF, an R package to determine the distribution of very low frequency variants (VLFs) in nucleotide and amino acid sequences for the analysis of errors in DNA sequence records. The package allows users to assess VLFs in aligned and trimmed protein-coding sequences by automatically calculating the frequency of nucleotides or amino acids in each sequence position and outputting those that occur under a user-specified frequency (default of p = 0.001). These results can then be used to explore fundamental population genetic and phylogeographic patterns, mechanisms and processes at the microevolutionary level, such as nucleotide and amino acid sequence conservation. Our package extends earlier work pertaining to an implementation of VLF analysis in Microsoft Excel, which was found to be both computationally slow and error prone. We compare those results to our own herein. Results between the two implementations are found to be highly consistent for a large DNA barcode dataset of bird species. Differences in results are readily explained by both manual human error and inadequate Linnean taxonomy (specifically, species synonymy). Here, VLF is also applied to a subset of avian barcodes to assess the extent of biological artifacts at the species level for Canada goose (Branta canadensis), as well as within a large dataset of DNA barcodes for fishes of forensic and regulatory importance. The novelty of VLF and its benefit over the previous implementation include its high level of automation, speed, scalability and ease-of-use, each desirable characteristics which will be extremely valuable as more sequence data are rapidly accumulated in popular reference databases, such as BOLD and GenBank.

Elamipretide effects on the skeletal muscle phosphoproteome in aged female mice.

The age-related decline in skeletal muscle mass and function is known as sarcopenia. Sarcopenia progresses based on complex processes involving protein dynamics, cell signaling, oxidative stress, and repair. We have previously found that 8-week treatment with elamipretide improves skeletal muscle function, reverses redox stress, and restores protein S-glutathionylation changes in aged female mice. This study tested whether 8-week treatment with elamipretide also affects global phosphorylation in skeletal muscle consistent with functional improvements and S-glutathionylation. Using female 6-7-month-old mice and 28-29-month-old mice, we found that phosphorylation changes did not relate to S-glutathionylation modifications, but that treatment with elamipretide did partially reverse age-related changes in protein phosphorylation in mouse skeletal muscle.

Basal Plane Functionalization of Niobium Disulfide Nanosheets with Cyclopentadienyl Manganese(I) Dicarbonyl.

Basal plane-functionalized NbS2 nanosheets were obtained using in situ photolysis to generate the coordinatively unsaturated organometallic fragment cyclopentadienyl manganese(I) dicarbonyl (CpMn(CO)2). Under UV irradiation, a labile carbonyl ligand dissociates from the tricarbonyl complex, creating an open coordination site for bonding between the Mn atom and the electron-rich sulfur atoms on the surface of the NbS2 nanosheets. In contrast, no reaction is observed with 2H-MoS2 nanosheets under the same reaction conditions. This difference in reactivity is consistent with the electronic structure calculations, which indicate stronger bonding of the organometallic fragment to electron-poor, metallic NbS2 than to semiconducting, electron-rich MoS2. X-ray photoelectron spectroscopy (XPS), Fourier-transform infrared (FTIR) spectroscopy, and powder X-ray diffraction (PXRD) were used to characterize the bonding between Mn and S atoms on the surface-functionalized nanosheets.