Evaluation of Tissue-engineered Tendon Enthesis Polymer Constructs

Both scientists and clinicians have proposed tissue engineering as the future of medicine. The possibilities for tissue engineering, that is, fabrication of tissues and organs in the laboratory and their translation to patients, appear to be endless, and many believe that this new approach in medicine will result in abolishing many common ailments, injuries, and congenital defects. Injuries to a tendon enthesis, the normal tissue connection between tendon and bone, are of particular concern to clinicians because of their frequency and failure to repair as a result of surgery. While these injuries may not be life threatening, they can certainly limit mobility and reduce the quality of life in those affected individuals. Fabrication of a tendon enthesis by tissue engineering would offer an alternative to the routine of surgery now performed and present potential for treatment and healing of the tissue now unavailable. In the current prospective study, polymer scaffolds created using polycaprolactone (PCL), poly-L lactide (PLLA), or nano-polyglycolic acid (nPGA) were seeded with chondrocytes, tenocytes, and periosteum for the development of cartilage, tendon and bone, respectively, and then implanted into six athymic nude mice for a period of 10 weeks. One group of constructs (scaffolds and cells or tissue together) was tethered to the mice 2 in order to determine if mechanical forces improved or were required for tendon enthesis formation compared to a group of identical implanted constructs that were not tethered. Analysis by histology illustrated a noticeable increase in tissue formation around the area of anticipated enthesis in tethered constructs when compared to constructs that were not tethered. Based on these data, it is believed that mechanical tension (tethering) is required for the formation of a tendon enthesi

The disruption of proteostasis in neurodegenerative diseases

Cells count on surveillance systems to monitor and protect the cellular proteome which, besides being highly heterogeneous, is constantly being challenged by intrinsic and environmental factors. In this context, the proteostasis network (PN) is essential to achieve a stable and functional proteome. Disruption of the PN is associated with aging and can lead to and/or potentiate the occurrence of many neurodegenerative diseases (ND). This not only emphasizes the importance of the PN in health span and aging but also how its modulation can be a potential target for intervention and treatment of human diseases.info:eu-repo/semantics/publishedVersio

Predicting the risk of Chronic Kidney Disease in Men and Women in England and Wales: prospective derivation and external validation of the QKidney® Scores

<p>Abstract</p> <p>Background</p> <p>Chronic Kidney Disease is a major cause of morbidity and interventions now exist which can reduce risk. We sought to develop and validate two new risk algorithms (the QKidney^®Scores) for estimating (a) the individual 5 year risk of moderate-severe CKD and (b) the individual 5 year risk of developing End Stage Kidney Failure in a primary care population.</p> <p>Methods</p> <p>We conducted a prospective open cohort study using data from 368 QResearch^®general practices to develop the scores. We validated the scores using two separate sets of practices - 188 separate QResearch^®practices and 364 practices contributing to the THIN database.</p> <p>We studied 775,091 women and 799,658 men aged 35-74 years in the QResearch^®derivation cohort, who contributed 4,068,643 and 4,121,926 person-years of observation respectively.</p> <p>We had two main outcomes (a) moderate-severe CKD (defined as the first evidence of CKD based on the earliest of any of the following: kidney transplant; kidney dialysis; diagnosis of nephropathy; persistent proteinuria; or glomerular filtration rate of < 45 mL/min) and (b) End Stage Kidney Failure.</p> <p>We derived separate risk equations for men and women. We calculated measures of calibration and discrimination using the two separate validation cohorts.</p> <p>Results</p> <p>Our final model for moderate-severe CKD included: age, ethnicity, deprivation, smoking, BMI, systolic blood pressure, diabetes, rheumatoid arthritis, cardiovascular disease, treated hypertension, congestive cardiac failure; peripheral vascular disease, NSAID use and family history of kidney disease. In addition, it included SLE and kidney stones in women. The final model for End Stage Kidney Failure was similar except it did not include NSAID use.</p> <p>Each risk prediction algorithms performed well across all measures in both validation cohorts. For the THIN cohort, the model to predict moderate-severe CKD explained 56.38% of the total variation in women and 57.49% for men. The D statistic values were high with values of 2.33 for women and 2.38 for men. The ROC statistic was 0.875 for women and 0.876 for men.</p> <p>Conclusions</p> <p>These new algorithms have the potential to identify high risk patients who might benefit from more detailed assessment, closer monitoring or interventions to reduce their risk.</p

Identifying quality improvement intervention publications - A comparison of electronic search strategies

Abstract Background The evidence base for quality improvement (QI) interventions is expanding rapidly. The diversity of the initiatives and the inconsistency in labeling these as QI interventions makes it challenging for researchers, policymakers, and QI practitioners to access the literature systematically and to identify relevant publications. Methods We evaluated search strategies developed for MEDLINE (Ovid) and PubMed based on free text words, Medical subject headings (MeSH), QI intervention components, continuous quality improvement (CQI) methods, and combinations of the strategies. Three sets of pertinent QI intervention publications were used for validation. Two independent expert reviewers screened publications for relevance. We compared the yield, recall rate, and precision of the search strategies for the identification of QI publications and for a subset of empirical studies on effects of QI interventions. Results The search yields ranged from 2,221 to 216,167 publications. Mean recall rates for reference publications ranged from 5% to 53% for strategies with yields of 50,000 publications or fewer. The 'best case' strategy, a simple text word search with high face validity ('quality' AND 'improv*' AND 'intervention*') identified 44%, 24%, and 62% of influential intervention articles selected by Agency for Healthcare Research and Quality (AHRQ) experts, a set of exemplar articles provided by members of the Standards for Quality Improvement Reporting Excellence (SQUIRE) group, and a sample from the Cochrane Effective Practice and Organization of Care Group (EPOC) register of studies, respectively. We applied the search strategy to a PubMed search for articles published in 10 pertinent journals in a three-year period which retrieved 183 publications. Among these, 67% were deemed relevant to QI by at least one of two independent raters. Forty percent were classified as empirical studies reporting on a QI intervention. Conclusions The presented search terms and operating characteristics can be used to guide the identification of QI intervention publications. Even with extensive iterative development, we achieved only moderate recall rates of reference publications. Consensus development on QI reporting and initiatives to develop QI-relevant MeSH terms are urgently needed

Chronic kidney disease and use of dental services in a united states public healthcare system: a retrospective cohort study

<p>Abstract</p> <p>Background</p> <p>As several studies have shown an association between periodontal disease and chronic kidney disease (CKD), regular dental care may be an important strategy for reducing the burden of CKD. Access to dental care may be limited in the US public health system.</p> <p>Methods</p> <p>In this retrospective cohort study of 6,498 adult patients with (n = 2,235) and without (n = 4,263) CKD and at least 12 months of follow-up within the San Francisco Department of Public Health Community Health Network clinical databases, we examined the likelihood of having a dental visit within the observation period (2005-2010) using Cox proportional hazards models. To determine whether dental visits reflected a uniform approach to preventive service use in this setting, we similarly examined the likelihood of having an eye visit among those with diabetes, for whom regular retinopathy screening is recommended. We defined CKD status by average estimated glomerular filtration rate based on two or more creatinine measurements ≥ 3 months apart (no CKD, ≥ 60 ml/min/1.73 m²; CKD, < 60 ml/min/1.73 m²).</p> <p>Results</p> <p>Only 11.0% and 17.4% of patients with and without CKD, respectively, had at least one dental visit. Those with CKD had a 25% lower likelihood of having a dental visit [HR = 0.75, 95% CI (0.64-0.88)] than those without CKD after adjustment for confounders. Among the subgroup of patients with diabetes, 11.8% vs. 17.2% of those with and without CKD had a dental visit, while 58.8% vs. 57.8% had an eye visit.</p> <p>Conclusions</p> <p>Dental visits, but not eye visits, in a US public healthcare setting are extremely low, particularly among patients with CKD. Given the emerging association between oral health and CKD, addressing factors that impede dental access may be important for reducing the disparate burden of CKD in this population.</p

Linear low-dose extrapolation for noncancer health effects is the exception, not the rule

The nature of the exposure-response relationship has a profound influence on risk analyses. Several arguments have been proffered as to why all exposure-response relationships for both cancer and noncarcinogenic end-points should be assumed to be linear at low doses. We focused on three arguments that have been put forth for noncarcinogens. First, the general “additivity-to-background” argument proposes that if an agent enhances an already existing disease-causing process, then even small exposures increase disease incidence in a linear manner. This only holds if it is related to a specific mode of action that has nonuniversal properties—properties that would not be expected for most noncancer effects. Second, the “heterogeneity in the population” argument states that variations in sensitivity among members ofthe target population tend to “flatten out and linearize” the exposure-response curve, but this actually only tends to broaden, not linearize, the dose-response relationship. Third, it has been argued that a review of epidemiological evidence shows linear or no-threshold effects at low exposures in humans, despite nonlinear exposure-response in the experimental dose range in animal testing for similar endpoints. It is more likely that this is attributable to exposure measurement error rather than a true non-threshold association. Assuming that every chemical is toxic at high exposures and linear at low exposures does not comport to modern-day scientific knowledge of biology. There is no compelling evidence-based justification for a general low-exposure linearity; rather, case-specific mechanistic arguments are needed

Network analysis of sea turtle movements and connectivity: A tool for conservation prioritization

This is the final version. Available on open access from Wiley via the DOI in this recordData availability statement: The data that support the findings of this study are available in the Supplementary Material of this article and Zenodo (https://doi.org/10.5281/zenodo.5898578). Details for all animals included in this study are provided in Appendices S1 and S2. Data used to create the spatial networks are listed in the Appendices S3 and S4. The geospatial files for all networks are available on the Migratory Connectivity in the Ocean Project website (https://mico.eco) and Dryad (https://doi.org/10.5061/dryad.j3tx95xg9). Additional data that support the findings of this study are available from the corresponding author upon reasonable request.Aim Understanding the spatial ecology of animal movements is a critical element in conserving long-lived, highly mobile marine species. Analyzing networks developed from movements of six sea turtle species reveals marine connectivity and can help prioritize conservation efforts. Location Global. Methods We collated telemetry data from 1235 individuals and reviewed the literature to determine our dataset's representativeness. We used the telemetry data to develop spatial networks at different scales to examine areas, connections, and their geographic arrangement. We used graph theory metrics to compare networks across regions and species and to identify the role of important areas and connections. Results Relevant literature and citations for data used in this study had very little overlap. Network analysis showed that sampling effort influenced network structure, and the arrangement of areas and connections for most networks was complex. However, important areas and connections identified by graph theory metrics can be different than areas of high data density. For the global network, marine regions in the Mediterranean had high closeness, while links with high betweenness among marine regions in the South Atlantic were critical for maintaining connectivity. Comparisons among species-specific networks showed that functional connectivity was related to movement ecology, resulting in networks composed of different areas and links. Main conclusions Network analysis identified the structure and functional connectivity of the sea turtles in our sample at multiple scales. These network characteristics could help guide the coordination of management strategies for wide-ranging animals throughout their geographic extent. Most networks had complex structures that can contribute to greater robustness but may be more difficult to manage changes when compared to simpler forms. Area-based conservation measures would benefit sea turtle populations when directed toward areas with high closeness dominating network function. Promoting seascape connectivity of links with high betweenness would decrease network vulnerability.International Climate Initiative (IKI)German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU

A Brain Region-Specific Predictive Gene Map for Autism Derived by Profiling a Reference Gene Set

Molecular underpinnings of complex psychiatric disorders such as autism spectrum disorders (ASD) remain largely unresolved. Increasingly, structural variations in discrete chromosomal loci are implicated in ASD, expanding the search space for its disease etiology. We exploited the high genetic heterogeneity of ASD to derive a predictive map of candidate genes by an integrated bioinformatics approach. Using a reference set of 84 Rare and Syndromic candidate ASD genes (AutRef84), we built a composite reference profile based on both functional and expression analyses. First, we created a functional profile of AutRef84 by performing Gene Ontology (GO) enrichment analysis which encompassed three main areas: 1) neurogenesis/projection, 2) cell adhesion, and 3) ion channel activity. Second, we constructed an expression profile of AutRef84 by conducting DAVID analysis which found enrichment in brain regions critical for sensory information processing (olfactory bulb, occipital lobe), executive function (prefrontal cortex), and hormone secretion (pituitary). Disease specificity of this dual AutRef84 profile was demonstrated by comparative analysis with control, diabetes, and non-specific gene sets. We then screened the human genome with the dual AutRef84 profile to derive a set of 460 potential ASD candidate genes. Importantly, the power of our predictive gene map was demonstrated by capturing 18 existing ASD-associated genes which were not part of the AutRef84 input dataset. The remaining 442 genes are entirely novel putative ASD risk genes. Together, we used a composite ASD reference profile to generate a predictive map of novel ASD candidate genes which should be prioritized for future research

Knowledge-Driven Multi-Locus Analysis Reveals Gene-Gene Interactions Influencing HDL Cholesterol Level in Two Independent EMR-Linked Biobanks

Genome-wide association studies (GWAS) are routinely being used to examine the genetic contribution to complex human traits, such as high-density lipoprotein cholesterol (HDL-C). Although HDL-C levels are highly heritable (h2∼0.7), the genetic determinants identified through GWAS contribute to a small fraction of the variance in this trait. Reasons for this discrepancy may include rare variants, structural variants, gene-environment (GxE) interactions, and gene-gene (GxG) interactions. Clinical practice-based biobanks now allow investigators to address these challenges by conducting GWAS in the context of comprehensive electronic medical records (EMRs). Here we apply an EMR-based phenotyping approach, within the context of routine care, to replicate several known associations between HDL-C and previously characterized genetic variants: CETP (rs3764261, p = 1.22e-25), LIPC (rs11855284, p = 3.92e-14), LPL (rs12678919, p = 1.99e-7), and the APOA1/C3/A4/A5 locus (rs964184, p = 1.06e-5), all adjusted for age, gender, body mass index (BMI), and smoking status. By using a novel approach which censors data based on relevant co-morbidities and lipid modifying medications to construct a more rigorous HDL-C phenotype, we identified an association between HDL-C and TRIB1, a gene which previously resisted identification in studies with larger sample sizes. Through the application of additional analytical strategies incorporating biological knowledge, we further identified 11 significant GxG interaction models in our discovery cohort, 8 of which show evidence of replication in a second biobank cohort. The strongest predictive model included a pairwise interaction between LPL (which modulates the incorporation of triglyceride into HDL) and ABCA1 (which modulates the incorporation of free cholesterol into HDL). These results demonstrate that gene-gene interactions modulate complex human traits, including HDL cholesterol