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Reading and music instruction can form a symbiotic relationship to positively impact lower-elementary literacy and increase student engagement. In this action research study, cross-curricular instruction between reading and music at the 2nd grade elementary level was taught by both the reading and music teacher. This study employed reading, rhythm, rhyme, instrumentation, writing, physical movement, and song to benefit students' phonemic awareness while reading. Developmental Reading Assessments (DRAs) were used to measure student growth from the start of the study to its conclusion. These DRAs were used as pre- and posttests and were bookended around instruction using reading, rhythm, rhyme, instrumentation, writing, physical movement, and song in the regular and music classrooms. This type of cross-curricular instruction between reading and music reinforced learning in both classroom settings. Results revealed that co-planning reading and music instruction have a positive impact on fluency, comprehension, and student engagement, but that DRAs are not the most accurate tools to measure phonemic awareness.

While there is a significant body of educational literature addressing the character and needs of rural communities in the Appalachian and southern regions of the US, there is a need for a better understanding of rural communities outside of this region. Existing literature focused on US rurality revolves around four main themes: the rural idyllic, isolation and deficits, rural identity, and community. The voices, experiences, and needs of future teachers of the Northern Great Plains are missing from this dominant narrative and this study begins to address this gap. This qualitative study is based on data collected from 16 semi-structured interviews with students enrolled in a preservice teacher preparation program about their experiences growing up and living in rural Northern Plains communities. Interview transcripts were transcribed, coded, and compared to the themes of the existing literature. The analysis resulted in several stable themes similar to the prevailing narratives on rural communities, with specific and nuanced differences. Specifically, participants held a nostalgic rather than idyllic view of their communities, internalized an agrarian identity even if they did not lead an agrarian lifestyle, and described communal ties as essential to their distinct lifestyle. Future research on Northern Plains rurality should seek to include non-white and Native American participants and perspectives.

Background Alzheimer’s disease (AD) is a neurodegenerative and heterogeneous disorder with complex etiology. Mild cognitive impairment (MCI) may represent an intermediate stage of AD, and the ability to identify MCI patients at greater risk of conversion to AD could guide personalized treatments. This study sought to develop a methylation risk score predictive of conversion from MCI to AD using publicly available blood DNA methylation (DNAm) data. Methods Using blood DNA methylation data from an epigenome-wide association study of AD that included 111 subjects with MCI, a methylation risk score of MCI conversion was created using an elastic-net framework. The elastic-net model was trained with a high-variance subset of the DNAm data, age and sex as predictors. Results The final model included three CpG sites: SLC6A3 (cg09892121) and TRIM62 (cg25342005), with a third (cg17292662) near the genes ATP6V1H and RGS20. A significant difference (p < 0.0001, t-test) was observed in the scores for MCI stable subjects compared with MCI converters. No statistically significant difference was observed between AD subjects and controls, suggesting specificity of the risk score for susceptibility to conversion. Conclusions The ability to identify MCI patients at greater risk of progression could inform early interventions and is a critical component in mitigation strategies for AD. This study provides insight into a potential role for epigenetics in the development of a multi-omic risk score of conversion.

Abstract 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.

Category: Basic Sciences/Biologics; Diabetes Introduction/Purpose: Diabetes mellitus is a chronic metabolic disease that leads to serious complications including bone health and wound healing. Bone fractures commonly occur in diabetic patients, and are difficultly to heal due to prolonged inflammation, which leads to a higher risk of non-union. Fully reduced high mobility group box1 (frHMGB1) can play an important role in skeletal regeneration; however, the activity can be inhibited by Metformin; which is commonly used for the treatment of diabetes. The effect of frHMGB1 and Metformin on the bone fracture healing is largely unknown. In this study, we tested the hypothesis that frHMGB1 enhances healing in a nonunion bone fracture and Metformin inhibits the healing using a diabetic rat model. Methods: Diabetic fracture rat model was created by injection of streptozotocin into total 32 Sprague Dawley rats and confirmed by blood glucose levels.An incision was performed, tibia bones were fractured, followed by the muscle and skin wound closure.The rats were divided into four groups with 8 rats per group(Fig 1): Group-1 had no additional treatment;Group-2 were injected Metformin (IP, 160 mg/kg) daily;Group-3 were injected frHMGB1 into wound area (250 µg/kg) weekly;Group-4 were injected Metformin (IP, 160 mg/kg) daily and frHMGB1 into wound area (250 µg/kg) weekly. The rats were monitored postoperatively and sacrificed on postoperative day-28 and day-90. The blood samples were collected for HMGB1 & IL-1β.Tibia samples were also collected and examined by gross inspection, micro-CT images and histological analysis. Data was analyzed by One-way ANOVA followed by Fisher’s Least significance difference test. A p-value less than 0.05 was considered to be significantly different between the groups. Results: Metformin with frHMGB1 significantly decreased HMGB1 levels and decreased the enhanced expression of IL-1β compared to frHMGB1 alone. Micro-CT images showed completely healed at day-90 post-surgery in frHMGB1 rats while Metformin inhibited frHMGB1 enhanced bone fracture healing as evidenced by the gap in the fractured bone area(Fig 2). Histology analysis indicated that frHMGB1 enhanced fractured bone healing as evidenced by high density of the cells was found in the bone fracture area (Fig. 3). Safranin O and fast green staining along with Masson’s Trichrome staining confirmed the frHMGB1 local injection promoted fractured bone healing (Fig. 4) as evidenced by high quality bone tissue formation with collagen type I (red staining) and collagen type III (blue staining) in the fractured bone wound area. Conclusion: Fully reduced HMGB1 treatment enhanced healing in a nonunion diabetic rat model. The fracture site had high density of cells, quality bone tissue, and enhanced production of collagen I and III. However, Metformin inhibited frHMGB1-induced healing enhancement. In diabetic rats, nonunion bone fracture was present with evidence of inflammation showing elevated levels of HMGB1 and IL-1β.FrHMGB1 treatment enhanced healing of nonunion bone fracture by promoting cell proliferation and migration, limited HMGB1 concentration, increased collagen production. Although Metformin injection slowed down the bone fracture healing by inhibiting frHMGB1activity, it also blocked HMGB1 release and reduced the inflammation caused by HMGB1.

Abstract 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.

Background: Alzheimer’s disease (AD) is a neurodegenerative and heterogeneous disorder with complex etiology. Mild cognitive impairment (MCI) may represent an intermediate stage of AD, and the ability to identify MCI patients at greater risk of conversion to AD could guide personalized treatments. This study sought to develop a methylation risk score predictive of conversion from MCI to AD using publicly available blood DNA methylation (DNAm) data. Methods: Using blood DNA methylation data from an epigenome-wide association study of AD that included 111 subjects with MCI, a methylation risk score of MCI conversion was created using an elastic-net framework. The elastic-net model was trained with a high-variance subset of the DNAm data, age and sex as predictors. Results: The final model included four CpG sites: PNCK (cg01231576), SLC6A3 (cg09892121), and TRIM62 (cg25342005), with a fourth (cg17292662) near the genes ATP6V1H and RGS20. A significant difference (p < 0.0001, t-test) was observed in the scores for MCI stable subjects compared with MCI converters. No statistically significant difference was observed between AD subjects and controls, suggesting specificity of the risk score for susceptibility to conversion. Conclusions: The ability to identify MCI patients at greater risk of progression could inform early interventions and is a critical component in mitigation strategies for AD. This study provides insight into a potential role for epigenetics in the development of a multi-omic risk score of conversion.

IntroductionCachexia contributes to increased mortality and reduced quality of life in Chronic Obstructive Pulmonary Disease (COPD) and may be associated with underlying gene expression changes. Our goal was to identify differential gene expression signatures associated with COPD cachexia in current and former smokers.MethodsWe analyzed whole-blood gene expression data from participants with COPD in a discovery cohort (COPDGene, N = 400) and assessed replication (ECLIPSE, N = 114). To approximate the consensus definition using available criteria, cachexia was defined as weight-loss > 5% in the past 12 months or low body mass index (BMI) ( 5% in the past 12 months or low BMI and 3/5 criteria: decreased muscle strength, anorexia, abnormal biochemistry (anemia or high c-reactive protein (> 5 mg/l)), fatigue, and low FFMI. Differential gene expression was assessed between cachectic and non-cachectic subjects, adjusting for age, sex, white blood cell counts, and technical covariates. Gene set enrichment analysis was performed using MSigDB.ResultsThe prevalence of COPD cachexia was 13.7% in COPDGene and 7.9% in ECLIPSE. Fourteen genes were differentially downregulated in cachectic versus non-cachectic COPD patients in COPDGene (FDR

Abstract 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.

Abstract Background Chronic obstructive pulmonary disease (COPD) is a leading cause of death in adults that may have origins in early lung development. It is a complex disease, influenced by multiple factors including genetic variants and environmental factors. Maternal smoking during pregnancy may influence the risk for diseases during adulthood, potentially through epigenetic modifications including methylation. Methods In this work, we explore the fetal origins of COPD by utilizing lung DNA methylation marks associated with in utero smoke (IUS) exposure, and evaluate the network relationships between methylomic and transcriptomic signatures associated with adult lung tissue from former smokers with and without COPD. To identify potential pathobiological mechanisms that may link fetal lung, smoke exposure and adult lung disease, we study the interactions (physical and functional) of identified genes using protein–protein interaction networks. Results We build IUS-exposure and COPD modules, which identify connected subnetworks linking fetal lung smoke exposure to adult COPD. Studying the relationships and connectivity among the different modules for fetal smoke exposure and adult COPD, we identify enriched pathways, including the AGE-RAGE and focal adhesion pathways. Conclusions The modules identified in our analysis add new and potentially important insights to understanding the early life molecular perturbations related to the pathogenesis of COPD. We identify AGE-RAGE and focal adhesion as two biologically plausible pathways that may reveal lung developmental contributions to COPD. We were not only able to identify meaningful modules but were also able to study interconnections between smoke exposure and lung disease, augmenting our knowledge about the fetal origins of COPD.

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. [ABSTRACT FROM AUTHOR]

Category: Midfoot/Forefoot; Bunion Introduction/Purpose: The pathology of the bunion deformity consists of deformities in the axial, coronal, and sagittal planes of the first metatarsal and its articular surface with the medial cuneiform. While weightbearing radiographs have been utilized for assessment of these deformities, such methods have limitations with regard to image magnification, patient position, and superimposition of bone alignments. With advances with weightbearing computed tomography (WBCT), evaluation of the 3- dimensional components of the first metatarsal along with its proximal articular surface can be assessed with greater precision. This study aims to observe the effect of the midshaft osteotomy on the alignment of the tarsometatarsal joint in three dimension Methods: Ten feet in 10 subjects underwent midshaft first metatarsal osteotomies. Weight-bearing (using a load equivalent to body weight) CT scans with .3mm cubic voxel size using an original loading device preoperatively and postoperatively were collected from each of the subjects in neutral standing position. Scans were segmented, and 3D renderings of the medial cuneiform, first metatarsal, and the first phalanx were also generated from the segmentations followed by definition of reference frames to evaluate changes in the metatarsal in relationship to the medial cuneiform. (Fig.1) Results: The measurements of the rotational parameters showed greater changes in the sagittal plane postoperatively with dorsiflexion of the first metatarsal relative to the medial cuneiform at the first tarsometatarsal joint (p

Abstract The human microbiome has a role in the development of multiple diseases. Individual microbiome profiles are highly personalized, though many species are shared. Understanding the relationship between the human microbiome and disease may inform future individualized treatments. We hypothesize the blood microbiome signature may be a surrogate for some lung microbial characteristics. We sought associations between the blood microbiome signature and lung-relevant host factors. Based on reads not mapped to the human genome, we detected microbial nucleic acids through secondary use of peripheral blood RNA-sequencing from 2,590 current and former smokers with and without chronic obstructive pulmonary disease (COPD) from the COPDGene study. We used the Genome Analysis Toolkit (GATK) microbial pipeline PathSeq to infer microbial profiles. We tested associations between the inferred profiles and lung disease relevant phenotypes and examined links to host gene expression pathways. We replicated our analyses using a second independent set of blood RNA-seq data from 1,065 COPDGene study subjects and performed a meta-analysis across the two studies. The four phyla with highest abundance across all subjects were Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes. In our meta-analysis, we observed associations (q-value

Chronic obstructive pulmonary disease (COPD) is a complex disease with strong environmental and genetic influences and sexually dimorphic features. Although genetic risk factors for COPD have been identified, much of the heritability remains unexplained. Sex-based genetic association studies may uncover additional COPD genetic risk factors. We studied current and former smokers from COPD case-control cohorts (COPDGene non-Hispanic whites and African Americans, Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-Points, and Genetics of Chronic Obstructive Lung Disease). COPD was defined as post-bronchodilator forced expiratory volume in 1 second/forced vital capacity less than 0.70 and forced expiratory volume in 1 second percent predicted less than 80. Testing was performed across all cohorts and combined in a meta-analysis adjusted for age, pack-years, and genetic ancestry. We first performed genome-wide single-nucleotide polymorphism (SNP)-by-sex interaction testing on the outcome of COPD affection status. We performed sex-stratified association testing for SNPs with interaction P less than 10-6. We examined over 8 million SNPs in four populations, including 6,260 subjects with COPD (40.6% female) and 5,269 smoking control subjects (47.3% female). The SNP rs9615358 in the cadherin gene CELSR1 approached genome-wide significance for an interaction with sex (P = 1.24 × 10-7). In the sex-stratified meta-analysis, this SNP was associated with COPD among females (odds ratio, 1.37 [95% confidence interval, 1.25-1.49]; P = 3.32 × 10-7) but not males (odds ratio, 0.90 [95% confidence interval, 0.79-1.01]; P = 0.06). CELSR1 is involved in fetal lung development. In a human fetal lung tissue dataset, we observed greater CELSR1 expression in female compared with male samples. This SNP-by-sex genome-wide association analysis identified the fetal lung development gene, CELSR1, as a potential sex-specific risk factor for COPD. Identifying sex-specific genetic risk factors may reveal new insights into sexually dimorphic features of COPD.

Introduction Bronchodilator response (BDR) is a measurement of acute bronchodilation in response to short-acting β2-agonists, with a heritability between 10 and 40%. Identifying genetic variants associated with BDR may lead to a better understanding of its complex pathophysiology. Methods We performed a genome-wide association study (GWAS) of BDR in six adult cohorts with participants of European ancestry (EA) and African ancestry (AA) including community cohorts and cohorts ascertained on the basis of obstructive pulmonary disease. Validation analysis was carried out in two paediatric asthma cohorts. Results A total of 10 623 EA and 3597 AA participants were included in the analyses. No single nucleotide polymorphism (SNP) was associated with BDR at the conventional genome-wide significance threshold (p

DNA barcoding has been largely successful in satisfactorily exposing levels of standing genetic diversity for a wide range of taxonomic groups through the employment of only one or a few universal gene markers. However, sufficient coverage of geographically-broad intra-specific haplotype variation within genomic databases like the Barcode of Life Data Systems (BOLD) and GenBank remains relatively sparse. As reference sequence libraries continue to grow exponentially in size, there is now the need to identify novel ways of meaningfully analyzing vast amounts of available DNA barcode data. This is an important issue to address promptly for the routine tasks of specimen identification and species discovery, which have seen broad adoption in areas as diverse as regulatory forensics and resource conservation. Here, it is demonstrated that the interpretation of DNA barcoding data is lacking in statistical rigor. To highlight this, focus is set specifically on one key concept that has become a household name in the field: the DNA barcode gap. Arguments outlined herein specifically center on DNA barcoding in animal taxa and stem from three angles: (1) the improper allocation of specimen sampling effort necessary to capture adequate levels of within-species genetic variation, (2) failing to properly visualize intra-specific and interspecific genetic distances, and (3) the inconsistent, inappropriate use, or absence of statistical inferential procedures in DNA barcoding gap analyses. Furthermore, simple statistical solutions are outlined which can greatly propel the use of DNA barcoding as a tool to irrefutably match unknowns to knowns on the basis of the barcoding gap with a high degree of confidence. Proposed methods examined herein are illustrated through application to DNA barcode sequence data from Canadian Pacific fish species as a case study.

The article focuses on examining the gene expression signature of Alpha-1 Antitrypsin Deficiency (AATD) across different lung cell types using single-cell RNA-sequencing (scRNA-seq) data. It highlights the association between AATD and proinflammatory changes in lung cells, especially in alveolar macrophages and other cell types.

Abstract Introduction Cachexia contributes to increased mortality and reduced quality of life in Chronic Obstructive Pulmonary Disease (COPD) and may be associated with underlying gene expression changes. Our goal was to identify differential gene expression signatures associated with COPD cachexia in current and former smokers. Methods We analyzed whole-blood gene expression data from participants with COPD in a discovery cohort (COPDGene, N = 400) and assessed replication (ECLIPSE, N = 114). To approximate the consensus definition using available criteria, cachexia was defined as weight-loss > 5% in the past 12 months or low body mass index (BMI) ( 5% in the past 12 months or low BMI and 3/5 criteria: decreased muscle strength, anorexia, abnormal biochemistry (anemia or high c-reactive protein (> 5 mg/l)), fatigue, and low FFMI. Differential gene expression was assessed between cachectic and non-cachectic subjects, adjusting for age, sex, white blood cell counts, and technical covariates. Gene set enrichment analysis was performed using MSigDB. Results The prevalence of COPD cachexia was 13.7% in COPDGene and 7.9% in ECLIPSE. Fourteen genes were differentially downregulated in cachectic versus non-cachectic COPD patients in COPDGene (FDR

Category: Basic Sciences/Biologics; Basic Sciences/Biologics; Sports; Other Introduction/Purpose: Recently, purposes of medicinal marijuana including analgesia and reduction in inflammation. The active component activates the CB1 and CB2 receptors, thus mimicking the action of endogenous cannabinoids. CB1 and CB2 are important regulators of bone metabollism. In particular, endocannabinoid signaling has shown to regulate proliferation and differentiation of MSCs and the activities of osteoblasts and osteoclasts. Cannabinoids may be prescribed to patients suffering bone fractures involving prolonged immobilization and discomfort. Thus, there is an important need to understand more completely the role of cannanbinoid signaling in fracture healing. In this study, we examine the influence of a synthetic cannabinoid agonist, Win-55,212-2 (Win) on adult, human MSC-derived osteoblast activity. Cell viability and osteogenic phenotype were assessed by MTS assay, RT-PCR, and alizarin red staining. Methods: With an IRB approved protocol, MSCs were isolated from healthy human bone marrow and expanded to the passage five for experimentation. Cells were then plated at 5,200 cells/cm2 (6-well plate) and osteogenically stimulated for 21 days before treatment with increasing concentrations of Win (0.01, 0.1, or 1 µM) for an additional 48 hours. The MTS assay was employed to determine the half-maximal (50%) inhibitory concentration (IC50) at different time points. The cell phenotype was assessed by real-time PCR and alizarin red staining. Results: We first used the MTS assay (for metabolism and proliferation) to test 7 doses of Win-55, from 0.001µM up to 5 µM and determined that the human osteoblast IC50 of Win-55 over 1-7 days of exposure was ~ 1.5 µM (Figure 1), a dose slightly lower than concentrations found to affect chondrocytes in a previous study. At 1µM Win-55, RT-PCR revealed that the expression of inflammatory cytokines IL-1beta and TNF-alpha was significantly reduced, while that of IL-6 and COX2 was unchanged. The expression of most osteogenic markers was unchanged by Win, but we did observe significant increases in BMP2, RUNX2 and OPN (Figure 2). Alizarin Red staining revealed increased calcium deposition and mineralization in the presence of 1µM Win, corroborating the RT-PCR results (Figure 3). Conclusion: Win-55,212-2 may be beneficial to osteogenesis. 1 µM Win enhanced the osteoblastic phenotype over control, untreated MSC-derived osteoblasts, reduced inflammatory mediators and increased calcium deposition and mineralization. This suggests that cannabidiol treatment might lead to improvements in fracture healing and provide a novel therapeutic option for the bone regeneration. Future studies are aimed at characterizing the CB-1 and CB-2 signaling associated with the changes observed here and the effects of Win on MSC-derived osteoblasts in the context of inflammation.

Category: Basic Sciences/Biologics Introduction/Purpose: Medical marijuana is reported to have potent analgesic, immunomodulatory and anti-inflammatory properties. Some recent studies have shown that cannabinoids may attenuate joint damage in animal models of arthritis. However, the underlying mechanism has not been completely elucidated. Interleukin-1β (IL-1β), a proinflammatory cytokine that can result in the degradation of cartilage, is known to be associated with the pathogenesis of osteoarthritis. We hypothesize that cannabinoids can mitigate the detrimental effect of IL-1β on cartilage, thus slowing the progression of osteoarthritis. We exposed human chondrocyte-derived engineered cartilage pellet cultures to IL-1 β for 48 hours or not and then treated the samples with a synthetic cannabinoid agonist, Win-55,212-2(Win). The tissue phenotypes were thereafter assessed by real time polymerase chain reaction (RT-PCR), histology and western blotting. Methods: Medical marijuana is reported to have potent analgesic, immunomodulatory and anti-inflammatory properties. Some recent studies have shown that cannabinoids may attenuate joint damage in animal models of arthritis. However, the underlying mechanism has not been completely elucidated. Interleukin-1β (IL-1β), a proinflammatory cytokine that can result in the degradation of cartilage, is known to be associated with the pathogenesis of osteoarthritis. We hypothesize that cannabinoids can mitigate the detrimental effect of IL-1β on cartilage, thus slowing the progression of osteoarthritis. We exposed human chondrocyte-derived engineered cartilage pellet cultures to IL-1 β for 48 hours or not and then treated the samples with a synthetic cannabinoid agonist, Win-55,212-2(Win). The tissue phenotypes were thereafter assessed by real time polymerase chain reaction (RT-PCR), histology and western blotting. Results: RT-PCR revealed persistent increase in the expression of inflammatory mediators IL-1beta, TNF-alpha and COL2 in IL1beta+ cultures over IL1beta- controls at all levels of WIN exposure. In contrast there was clear decrease in IL-6 expression at high WIN doses coincident with a downward trend the other mediators. WIN was unable to rescue IL-1beta-induced reductions in COL2 and ACN, while inducing ALP, a marker of osteogenesis and cartilage hypertrophy. Safranin O/Fast Green histology revealed progressive loss in GAG deposition with increasing doses of WIN (Figure 2). Western blots confirmed reductions in COL2 and COMP protein, persistent COX2 production, and increasing translation of the osteogenic transcription factor RUNX2 and p-SMAD1/5/8 (Figure 3). Conclusion: At doses below 1µM, Win does not impact IL-1beta-induced chondrocyte inflammation. while inhibiting chondrogenesis and stimulating osteogenesis through RUNX2 as compared to IL-1β controls. In proper context, BMP2 stimulates osteogenesis through SMAD1/5/8 and the induction of RUNX2. We did observe an apparent anti-inflammatory role of WIN at 1µM, but this dose did not rescue a loss in cartilage pellet GAG loss. Our data suggests that cannabinoids are anti-inflammatory, but are unable to rescue cartilage degeneration by IL-1β and promote an osteogenic phenotype. However, the data are not conclusive with regarding the beneficial or detrimental to arthritic bones and cartilage

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract Background Multiple gene expression studies have been performed separately in peripheral blood, lung, and airway tissues to study COPD. We performed RNA-sequencing gene expression profiling of large-airway epithelium, alveolar macrophage and peripheral blood samples from the same subset of COPD cases and controls from the COPDGene study who underwent bronchoscopy at a single center. Using statistical and gene set enrichment approaches, we sought to improve the understanding of COPD by studying gene sets and pathways across these tissues, beyond the individual genomic determinants. Methods We performed differential expression analysis using RNA-seq data obtained from 63 samples from 21 COPD cases and controls (includes four non-smokers) via the R package DESeq2. We tested associations between gene expression and variables related to lung function, smoking history, and CT scan measures of emphysema and airway disease. We examined the correlation of differential gene expression across the tissues and phenotypes, hypothesizing that this would reveal preserved and private gene expression signatures. We performed gene set enrichment analyses using curated databases and findings from prior COPD studies to provide biological and disease relevance. Results The known smoking-related genes CYP1B1 and AHRR were among the top differential expression results for smoking status in the large-airway epithelium data. We observed a significant overlap of genes primarily across large-airway and macrophage results for smoking and airway disease phenotypes. We did not observe specific genes differentially expressed in all three tissues for any of the phenotypes. However, we did observe hemostasis and immune signaling pathways in the overlaps across all three tissues for emphysema, and amyloid and telomere-related pathways for smoking. In peripheral blood, the emphysema results were enriched for B cell related genes previously identified in lung tissue studies. Conclusions Our integrative analyses across COPD-relevant tissues and prior studies revealed shared and tissue-specific disease biology. These replicated and novel findings in the airway and peripheral blood have highlighted candidate genes and pathways for COPD pathogenesis.

Abstract Background Previous studies have identified lung, sputum or blood transcriptomic biomarkers associated with the severity of airflow limitation in COPD. Yet, it is not clear whether the lung pathobiology is mirrored by these surrogate tissues. The aim of this study was to explore this question. Methods We used Weighted Gene Co-expression Network Analysis (WGCNA) to identify shared pathological mechanisms across four COPD gene-expression datasets: two sets of lung tissues (L1 n = 70; L2 n = 124), and one each of induced sputum (S; n = 121) and peripheral blood (B; n = 121). Results WGCNA analysis identified twenty-one gene co-expression modules in L1. A robust module preservation between the two L datasets was observed (86%), with less preservation in S (33%) and even less in B (23%). Three modules preserved across lung tissues and sputum (not blood) were associated with the severity of airflow limitation. Ontology enrichment analysis showed that these modules included genes related to mitochondrial function, ion-homeostasis, T cells and RNA processing. These findings were largely reproduced using the consensus WGCNA network approach. Conclusions These observations indicate that major differences in lung tissue transcriptomics in patients with COPD are poorly mirrored in sputum and are unrelated to those determined in blood, suggesting that the systemic component in COPD is independently regulated. Finally, the fact that one of the preserved modules associated with FEV1 was enriched in mitochondria-related genes supports a role for mitochondrial dysfunction in the pathobiology of COPD.

Data-independent acquisition (DIA)-based proteomics often relies on mass spectrum libraries from data-dependent acquisition experiments. Here, the authors present a method to generate DIA-based chromatogram libraries, enabling DIA-only workflows and detecting more peptides than with spectrum libraries alone.

Although the butterflies of North America have received considerable taxonomic attention, overlooked species and instances of hybridization continue to be revealed. The present study assembles a DNA barcode reference library for this fauna to identify groups whose patterns of sequence variation suggest the need for further taxonomic study. Based on 14,626 records from 814 species, DNA barcodes were obtained for 96% of the fauna. The maximum intraspecific distance averaged 1/4 the minimum distance to the nearest neighbor, producing a barcode gap in 76% of the species. Most species (80%) were monophyletic, the others were para- or polyphyletic. Although 15% of currently recognized species shared barcodes, the incidence of such taxa was far higher in regions exposed to Pleistocene glaciations than in those that were ice-free. Nearly 10% of species displayed high intraspecific variation (>2.5%), suggesting the need for further investigation to assess potential cryptic diversity. Aside from aiding the identification of all life stages of North American butterflies, the reference library has provided new perspectives on the incidence of both cryptic and potentially over-split species, setting the stage for future studies that can further explore the evolutionary dynamics of this group.

Category: Bunion; Midfoot/Forefoot Introduction/Purpose: Hallux valgus (HV) is a tri-plane deformity of the foot corresponding to a medial deviation of the first metatarsal and a lateral deviation of the hallux. Understanding key angles between bones, as well as how these deformity changes in each plane, is critical to generating pre-operative insights into the most effective surgical correction of the deformity. While two- dimenional (2D) imaging can provide some information; utilizing three-dimensional (3D) imaging can include more precise and accurate measures of hallux valgus. The purpose of this study is to evaluate the metatarsal osteotomies for correction of hallux valgus deformity in axial, coronal and sagittal plane with 2D and 3D measurements with the hypothesis that 3D measurements will provide greater accuracy of pre and post surgical changes Methods: Ten cadaveric specimens were selected and weight-bearing CT scans were taken pre operatively with an applied an axial load of 80 pounds. Midshaft osteotomies were then performed on the cadaveric specimens followed by weight-bearing CT scans taken post-operatively.3D models of the pre-operative and post-operative specimens were created and differences in pre and post operative changes were analyzed using conventional 2D and 3D models of the first metatarsal (M1), second metatarsal (M2), fifth metatarsal (M5), and proximal phalanx of the hallux (PP1) using a paired student t-test. Quantitative examination of foot and ankle offset (FAO) alignment along with congruity of first metatarsal phalangeal and first tarsometatarsal joints Results: 3D measurements of the Inter-Metatarsal (IM) Angle, was 12.3 degrees pre-opeative and 10.4 degrees post-operative with no significant differences in all three planes while the M1M5 Angle, measured between the principle axes of the first metatarsal and fifth metatarsal was 25.3 degrees pre-operative and 22.0 degrees post-operative were statistically significant with the greatest change in the axial plane. 2D measurements of the hallux valgus angle, measured the longitudineal axes of the first metatarsal and proximal phalange of the hallux was 22.6 degrees pre opereative and 21.7 degrees post opereative with no statistical difference while the metatarsal parabola, measured in two dimensions projected onto the axial plane was 157.1 degrees before and 141.5 degrees after surgery was statistical significant. Conclusion: When comparing 2D and 3D pre and post surgical hallux valgus values, the only significant differences were identified in the absolute M1M5 values in the axial plane and a significant change was also observed in the metatarsal parabola angle. While the metatarsal parabola angle are sensitive measures, these results suggest that the M1 M5 angle allows for precise, efficient measurements in axial, coronal and sagittal planes that is previously unknown through two-dimensional radiographic measurements for quantifying the effect of metatarsal osteotomies on hallux valgus

Assessing levels of standing genetic variation within species requires a robust sampling for the purpose of accurate specimen identification using molecular techniques such as DNA barcoding; however, statistical estimators for what constitutes a robust sample are currently lacking. Moreover, such estimates are needed because most species are currently represented by only one or a few sequences in existing databases, which can safely be assumed to be undersampled. Unfortunately, sample sizes of 5–10 specimens per species typically seen in DNA barcoding studies are often insufficient to adequately capture within-species genetic diversity. Here, we introduce a novel iterative extrapolation simulation algorithm of haplotype accumulation curves, called HACSim (Haplotype Accumulation Curve Simulator) that can be employed to calculate likely sample sizes needed to observe the full range of DNA barcode haplotype variation that exists for a species. Using uniform haplotype and non-uniform haplotype frequency distributions, the notion of sampling sufficiency (the sample size at which sampling accuracy is maximized and above which no new sampling information is likely to be gained) can be gleaned. HACSim can be employed in two primary ways to estimate specimen sample sizes: (1) to simulate haplotype sampling in hypothetical species, and (2) to simulate haplotype sampling in real species mined from public reference sequence databases like the Barcode of Life Data Systems (BOLD) or GenBank for any genomic marker of interest. While our algorithm is globally convergent, runtime is heavily dependent on initial sample sizes and skewness of the corresponding haplotype frequency distribution.

Abstract Background Genome-wide association studies have identified several genetic risk loci for severe chronic obstructive pulmonary disease (COPD) and emphysema. However, these studies do not fully explain disease heritability and in most cases, fail to implicate specific genes. Integrative methods that combine gene expression data with GWAS can provide more power in discovering disease-associated genes and give mechanistic insight into regulated genes. Methods We applied a recently described method that imputes gene expression using reference transcriptome data to genome-wide association studies for two phenotypes (severe COPD and quantitative emphysema) and blood and lung tissue gene expression datasets. We further tested the potential causality of individual genes using multi-variant colocalization. Results We identified seven genes significantly associated with severe COPD, and five genes significantly associated with quantitative emphysema in whole blood or lung. We validated results in independent transcriptome databases and confirmed colocalization signals for PSMA4, EGLN2, WNT3, DCBLD1, and LILRA3. Three of these genes were not located within previously reported GWAS loci for either phenotype. We also identified genetically driven pathways, including those related to immune regulation. Conclusions An integrative analysis of GWAS and gene expression identified novel associations with severe COPD and quantitative emphysema, and also suggested disease-associated genes in known COPD susceptibility loci. Trial registration NCT00608764, Registry: ClinicalTrials.gov, Date of Enrollment of First Participant: November 2007, Date Registered: January 28, 2008 (retrospectively registered); NCT00292552, Registry: ClinicalTrials.gov, Date of Enrollment of First Participant: December 2005, Date Registered: February 14, 2006 (retrospectively registered).

Abstract Background Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) significantly associated with chronic obstructive pulmonary disease (COPD). However, many genetic variants show suggestive evidence for association but do not meet the strict threshold for genome-wide significance. Integrative analysis of multiple omics datasets has the potential to identify novel genes involved in disease pathogenesis by leveraging these variants in a functional, regulatory context. Results We performed expression quantitative trait locus (eQTL) analysis using genome-wide SNP genotyping and gene expression profiling of lung tissue samples from 86 COPD cases and 31 controls, testing for SNPs associated with gene expression levels. These results were integrated with a prior COPD GWAS using an ensemble statistical and network methods approach to identify relevant genes and observe them in the context of overall genetic control of gene expression to highlight co-regulated genes and disease pathways. We identified 250,312 unique SNPs and 4997 genes in the cis(local)-eQTL analysis (5% false discovery rate). The top gene from the integrative analysis was MAPT, a gene recently identified in an independent GWAS of lung function. The genes HNRNPAB and PCBP2 with RNA binding activity and the gene ACVR1B were identified in network communities with validated disease relevance. Conclusions The integration of lung tissue gene expression with genome-wide SNP genotyping and subsequent intersection with prior GWAS and omics studies highlighted candidate genes within COPD loci and in communities harboring known COPD genes. This integration also identified novel disease genes in sub-threshold regions that would otherwise have been missed through GWAS.