Vertebral bone marrow fat, bone mineral density and diabetes : The Osteoporotic Fractures in Men (MrOS) study

Elevated vertebral bone marrow fat (BMF) among individuals with osteoporosis has been established in histomorphometric studies. Several studies have found a negative correlation between BMF and bone mineral density (BMD) at the spine in men and women across different age groups. Animal studies have also observed bone loss with increased BMF in mice with induced diabetes. Our study objective was to test the hypothesis that the association between BMF and BMD varies by diabetic status. We performed a cross-sectional study of 156 men aged 74-96years from the Osteoporotic Fractures in Men study at the Pittsburgh clinical site. All men had spine BMF scans using proton magnetic resonance spectroscopy and spine and hip BMD scans by dual-energy X-ray absorptiometry. BMF was expressed as lipid to "lipid+water" ratio (%). Men were considered diabetic if they self-reported a physician diagnosis of diabetes, diabetes medication or had a fasting glucose ≥126mg/dl. Men with diabetes (n=38) had a significantly higher spine BMF (58.9 vs. 54.6%, p=0.0035), spine BMD (1.20 vs. 1.10g/cm(2), P=0.007) and total hip BMD (1.00 vs. 0.94g/cm(2), p=0.04) than those without, while no differences were observed for body weight, body mass index or waist circumference. Pearson correlation tests showed no significant correlation of spine BMF with age or BMD in non-diabetics. Significant inverse correlations were observed between BMF and BMD (-0.30 for femoral neck and -0.39 for total hip) among diabetic men. In conclusion, men with diabetes had a higher BMF compared to non-diabetic men. The correlation between BMF and BMD differed by diabetes status. Further investigation of the association of diabetes with BMF and BMD may provide a better understanding of the high fracture rates among individuals with diabetes despite their higher BMD

Drug Adverse Event Detection in Health Plan Data Using the Gamma Poisson Shrinker and Comparison to the Tree-based Scan Statistic

Background: Drug adverse event (AE) signal detection using the Gamma Poisson Shrinker (GPS) is commonly applied in spontaneous reporting. AE signal detection using large observational health plan databases can expand medication safety surveillance. Methods: Using data from nine health plans, we conducted a pilot study to evaluate the implementation and findings of the GPS approach for two antifungal drugs, terbinafine and itraconazole, and two diabetes drugs, pioglitazone and rosiglitazone. We evaluated 1676 diagnosis codes grouped into 183 different clinical concepts and four levels of granularity. Several signaling thresholds were assessed. GPS results were compared to findings from a companion study using the identical analytic dataset but an alternative statistical method—the tree-based scan statistic (TreeScan). Results: We identified 71 statistical signals across two signaling thresholds and two methods, including closely-related signals of overlapping diagnosis definitions. Initial review found that most signals represented known adverse drug reactions or confounding. About 31% of signals met the highest signaling threshold. Conclusions: The GPS method was successfully applied to observational health plan data in a distributed data environment as a drug safety data mining method. There was substantial concordance between the GPS and TreeScan approaches. Key method implementation decisions relate to defining exposures and outcomes and informed choice of signaling thresholds

Characterizing Long COVID: Deep Phenotype of a Complex Condition.

BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or long COVID ), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. METHODS: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. FINDINGS: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. INTERPRETATION: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID. FUNDING: U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411

Expression of RNA interference triggers from an oncolytic herpes simplex virus results in specific silencing in tumour cells in vitro and tumours in vivo

<p>Abstract</p> <p>Background</p> <p>Delivery of small interfering RNA (siRNA) to tumours remains a major obstacle for the development of RNA interference (RNAi)-based therapeutics. Following the promising pre-clinical and clinical results with the oncolytic herpes simplex virus (HSV) OncoVEX^GM-CSF, we aimed to express RNAi triggers from oncolytic HSV, which although has the potential to improve treatment by silencing tumour-related genes, was not considered possible due to the highly oncolytic properties of HSV.</p> <p>Methods</p> <p>To evaluate RNAi-mediated silencing from an oncolytic HSV backbone, we developed novel replicating HSV vectors expressing short-hairpin RNA (shRNA) or artificial microRNA (miRNA) against the reporter genes green fluorescent protein (eGFP) and β-galactosidase (lacZ). These vectors were tested in non-tumour cell lines <it>in vitro </it>and tumour cells that are moderately susceptible to HSV infection both <it>in vitro </it>and in mice xenografts <it>in vivo</it>. Silencing was assessed at the protein level by fluorescent microscopy, x-gal staining, enzyme activity assay, and western blotting.</p> <p>Results</p> <p>Our results demonstrate that it is possible to express shRNA and artificial miRNA from an oncolytic HSV backbone, which had not been previously investigated. Furthermore, oncolytic HSV-mediated delivery of RNAi triggers resulted in effective and specific silencing of targeted genes in tumour cells <it>in vitro </it>and tumours <it>in vivo</it>, with the viruses expressing artificial miRNA being comprehensibly more effective.</p> <p>Conclusions</p> <p>This preliminary data provide the first demonstration of oncolytic HSV-mediated expression of shRNA or artificial miRNA and silencing of targeted genes in tumour cells <it>in vitro </it>and <it>in vivo</it>. The vectors developed in this study are being adapted to silence tumour-related genes in an ongoing study that aims to improve the effectiveness of oncolytic HSV treatment in tumours that are moderately susceptible to HSV infection and thus, potentially improve response rates seen in human clinical trials.</p

PRimary Care Opioid Use Disorders treatment (PROUD) trial protocol: a pragmatic, cluster-randomized implementation trial in primary care for opioid use disorder treatment

BACKGROUND: Most people with opioid use disorder (OUD) never receive treatment. Medication treatment of OUD in primary care is recommended as an approach to increase access to care. The PRimary Care Opioid Use Disorders treatment (PROUD) trial tests whether implementation of a collaborative care model (Massachusetts Model) using a nurse care manager (NCM) to support medication treatment of OUD in primary care increases OUD treatment and improves outcomes. Specifically, it tests whether implementation of collaborative care, compared to usual primary care, increases the number of days of medication for OUD (implementation objective) and reduces acute health care utilization (effectiveness objective). The protocol for the PROUD trial is presented here. METHODS: PROUD is a hybrid type III cluster-randomized implementation trial in six health care systems. The intervention consists of three implementation strategies: salary for a full-time NCM, training and technical assistance for the NCM, and requiring that three primary care providers have DEA waivers to prescribe buprenorphine. Within each health system, two primary care clinics are randomized: one to the intervention and one to Usual Primary Care. The sample includes all patients age 16-90 who visited the randomized primary care clinics from 3 years before to 2 years after randomization (anticipated to be \u3e 170,000). Quantitative data are derived from existing health system administrative data, electronic medical records, and/or health insurance claims ( electronic health records, [EHRs]). Anonymous staff surveys, stakeholder debriefs, and observations from site visits, trainings and technical assistance provide qualitative data to assess barriers and facilitators to implementation. The outcome for the implementation objective (primary outcome) is a clinic-level measure of the number of patient days of medication treatment of OUD over the 2 years post-randomization. The patient-level outcome for the effectiveness objective (secondary outcome) is days of acute care utilization [e.g. urgent care, emergency department (ED) and/or hospitalizations] over 2 years post-randomization among patients with documented OUD prior to randomization. DISCUSSION: The PROUD trial provides information for clinical leaders and policy makers regarding potential benefits for patients and health systems of a collaborative care model for management of OUD in primary care, tested in real-world diverse primary care settings

Primitive layered gabbros from fast-spreading lower oceanic crust

Three-quarters of the oceanic crust formed at fast-spreading ridges is composed of plutonic rocks whose mineral assemblages, textures and compositions record the history of melt transport and crystallization between the mantle and the sea floor. Despite the importance of these rocks, sampling them in situ is extremely challenging owing to the overlying dykes and lavas. This means that models for understanding the formation of the lower crust are based largely on geophysical studies and ancient analogues (ophiolites) that did not form at typical mid-ocean ridges. Here we describe cored intervals of primitive, modally layered gabbroic rocks from the lower plutonic crust formed at a fast-spreading ridge, sampled by the Integrated Ocean Drilling Program at the Hess Deep rift. Centimetre-scale, modally layered rocks, some of which have a strong layering-parallel foliation, confirm a long-held belief that such rocks are a key constituent of the lower oceanic crust formed at fast-spreading ridges. Geochemical analysis of these primitive lower plutonic rocks-in combination with previous geochemical data for shallow-level plutonic rocks, sheeted dykes and lavas-provides the most completely constrained estimate of the bulk composition of fast-spreading oceanic crust so far. Simple crystallization models using this bulk crustal composition as the parental melt accurately predict the bulk composition of both the lavas and the plutonic rocks. However, the recovered plutonic rocks show early crystallization of orthopyroxene, which is not predicted by current models of melt extraction from the mantle and mid-ocean-ridge basalt differentiation. The simplest explanation of this observation is that compositionally diverse melts are extracted from the mantle and partly crystallize before mixing to produce the more homogeneous magmas that erupt

Increased Incidence of Vestibular Disorders in Patients With SARS-CoV-2

OBJECTIVE: Determine the incidence of vestibular disorders in patients with SARS-CoV-2 compared to the control population. STUDY DESIGN: Retrospective. SETTING: Clinical data in the National COVID Cohort Collaborative database (N3C). METHODS: Deidentified patient data from the National COVID Cohort Collaborative database (N3C) were queried based on variant peak prevalence (untyped, alpha, delta, omicron 21K, and omicron 23A) from covariants.org to retrospectively analyze the incidence of vestibular disorders in patients with SARS-CoV-2 compared to control population, consisting of patients without documented evidence of COVID infection during the same period. RESULTS: Patients testing positive for COVID-19 were significantly more likely to have a vestibular disorder compared to the control population. Compared to control patients, the odds ratio of vestibular disorders was significantly elevated in patients with untyped (odds ratio [OR], 2.39; confidence intervals [CI], 2.29-2.50; CONCLUSIONS: The incidence of vestibular disorders differed between COVID-19 variants and was significantly elevated in COVID-19-positive patients compared to the control population. These findings have implications for patient counseling and further research is needed to discern the long-term effects of these findings

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.Development of the BIDS Standard has been supported by the International Neuroinformatics Coordinating Facility, Laura and John Arnold Foundation, National Institutes of Health (R24MH114705, R24MH117179, R01MH126699, R24MH117295, P41EB019936, ZIAMH002977, R01MH109682, RF1MH126700, R01EB020740), National Science Foundation (OAC-1760950, BCS-1734853, CRCNS-1429999, CRCNS-1912266), Novo Nordisk Fonden (NNF20OC0063277), French National Research Agency (ANR-19-DATA-0023, ANR 19-DATA-0021), Digital Europe TEF-Health (101100700), EU H2020 Virtual Brain Cloud (826421), Human Brain Project (SGA2 785907, SGA3 945539), European Research Council (Consolidator 683049), German Research Foundation (SFB 1436/425899996), SFB 1315/327654276, SFB 936/178316478, SFB-TRR 295/424778381), SPP Computational Connectomics (RI 2073/6-1, RI 2073/10-2, RI 2073/9-1), European Innovation Council PHRASE Horizon (101058240), Berlin Institute of Health & Foundation Charité, Johanna Quandt Excellence Initiative, ERAPerMed Pattern-Cog, and the Virtual Research Environment at the Charité Berlin – a node of EBRAINS Health Data Cloud.N