Performance indicators for clinical practice management in primary care in Portugal : consensus from a Delphi study

Early OnlineBackground: Performance indicators assessing the quality of medical care and linked to pay for performance may cause disagreement. Portuguese indicators included in recent health care reform are controversial. Objectives: To obtain consensus from opinion leaders in family medicine regarding the performance indicators for practice management used in the evaluation of Family Health Units in Portugal. Methods: Eighty-nine specialists in primary care were invited to answer the following question in an online Delphi study: 'Which performance indicators should be assessed regarding the organization and management of clinical practice in primary care in Portugal?' A Likert scale was used to evaluate validity, reliability, feasibility and sensitivity to change. Twenty-seven experts participated in the second round and achieved a high degree of consensus. Eight categories were created for analysis. Results: The experts suggested the use of existing indicators as well as new indicators. Thirty-nine indicators suggested by the experts are currently in use in Portugal. The assessment of the number of clinical acts performed, the number of administrative acts, and evaluation of the clinical demographic profile achieved a high degree of consensus. The expert panel suggested fifty new indicators. Five categories of these new indicators had a high degree of consensus, and three categories had a low degree of consensus. Conclusion: The expert panel recommended that performance indicators of practice management should first assess the quantity of clinical and administrative activities undertaken. These indicators must take into account the human and financial resources available to the clinic and its demographic context

Variants of the Matrix Metalloproteinase-2 but not the Matrix Metalloproteinase-9 genes significantly influence functional outcome after stroke

<p>Abstract</p> <p>Background</p> <p>Multiple lines of evidence suggest that genetic factors contribute to stroke recovery. The matrix metalloproteinases -2 (MMP-2) and -9 (MMP-9) are modulators of extracellular matrix components, with important regulatory functions in the Central Nervous System (CNS). Shortly after stroke, MMP-2 and MMP-9 have mainly damaging effects for brain tissue. However, MMPs also have a beneficial activity in angiogenesis and neurovascular remodelling during the delayed neuroinflammatory response phase, thus possibly contributing to stroke functional recovery.</p> <p>Methods</p> <p>In the present study, the role of <it>MMP-2 </it>and <it>MMP-9 </it>genetic variants in stroke recovery was investigated in 546 stroke patients. Functional outcome was assessed three months after a stroke episode using the modified Rankin Scale (mRS), and patients were classified in two groups: good recovery (mRS ≤ 1) or poor recovery (mRS>1). Haplotype tagging single nucleotide polymorphisms (SNPs) in the <it>MMP-2 </it>(N = 21) and <it>MMP-9 </it>(N = 4) genes were genotyped and tested for association with stroke outcome, adjusting for significant non-genetic clinical variables.</p> <p>Results</p> <p>Six SNPs in the <it>MMP-2 </it>gene were significantly associated with stroke outcome (0.0018<<it>P </it>< 0.0415), two of which survived the Bonferroni correction for multiple testing. In the subset of ischemic stroke patients, association of five of these SNPs remained positive (0.0042<<it>P </it>< 0.0306). No significant associations were found for the <it>MMP-9 </it>gene.</p> <p>Conclusions</p> <p>The results presented strongly indicate that <it>MMP-2 </it>genetic variants are an important mediator of functional outcome after stroke.</p

Genetic variants for head size share genes and pathways with cancer

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.</p

EXD2 governs germ stem cell homeostasis and lifespan by promoting mitoribosome integrity and translation

Mitochondria are subcellular organelles critical for meeting the bioenergetic and biosynthetic needs of the cell. Mitochondrial function relies on genes and RNA species encoded both in the nucleus and mitochondria, as well as their coordinated translation, import and respiratory complex assembly. Here we describe the characterization of exonuclease domain like 2 (EXD2), a nuclear encoded gene that we show is targeted to the mitochondria and prevents the aberrant association of mRNAs with the mitochondrial ribosome. The loss of EXD2 resulted in defective mitochondrial translation, impaired respiration, reduced ATP production, increased reactive oxygen species and widespread metabolic abnormalities. Depletion of EXD2/CG6744 in D.melanogaster caused developmental delays and premature female germline stem cell attrition, reduced fecundity and a dramatic extension of lifespan that could be reversed with an anti-oxidant diet. Our results define a conserved role for EXD2 in mitochondrial translation that influences development and aging

Normal radial migration and lamination are maintained in dyslexia-susceptibility candidate gene homolog Kiaa0319 knockout mice

AbstractDevelopmental dyslexia is a common disorder with a strong genetic component, but the underlying molecular mechanisms are still unknown. Several candidate dyslexia-susceptibility genes, including KIAA0319, DYX1C1, and DCDC2, have been identified in humans. RNA interference experiments targeting these genes in rat embryos have shown impairments in neuronal migration, suggesting that defects in radial cortical migration could be involved in the disease mechanism of dyslexia. Here we present the first characterisation of a Kiaa0319 knockout mouse line. Animals lacking KIAA0319 protein do not show anatomical abnormalities in any of the layered structures of the brain. Neurogenesis and radial migration of cortical projection neurons are not altered, and the intrinsic electrophysiological properties of Kiaa0319-deficient neurons do not differ from those of wild-type neurons. Kiaa0319 overexpression in cortex delays radial migration, but does not affect final neuronal position. However, knockout animals show subtle differences suggesting possible alterations in anxiety-related behaviour and in sensorimotor gating. Our results do not reveal a migration disorder in the mouse model, adding to the body of evidence available for Dcdc2 and Dyx1c1 that, unlike in the rat in utero knockdown models, the dyslexia-susceptibility candidate mouse homolog genes do not play an evident role in neuronal migration. However, KIAA0319 protein expression seems to be restricted to the brain, not only in early developmental stages but also in adult mice, indicative of a role of this protein in brain function. The constitutive and conditional knockout lines reported here will be useful tools for further functional analyses of Kiaa0319

Soft windowing application to improve analysis of high-throughput phenotyping data.

MOTIVATION: High-throughput phenomic projects generate complex data from small treatment and large control groups that increase the power of the analyses but introduce variation over time. A method is needed to utlize a set of temporally local controls that maximizes analytic power while minimizing noise from unspecified environmental factors. RESULTS: Here we introduce \u27soft windowing\u27, a methodological approach that selects a window of time that includes the most appropriate controls for analysis. Using phenotype data from the International Mouse Phenotyping Consortium (IMPC), adaptive windows were applied such that control data collected proximally to mutants were assigned the maximal weight, while data collected earlier or later had less weight. We applied this method to IMPC data and compared the results with those obtained from a standard non-windowed approach. Validation was performed using a resampling approach in which we demonstrate a 10% reduction of false positives from 2.5 million analyses. We applied the method to our production analysis pipeline that establishes genotype-phenotype associations by comparing mutant versus control data. We report an increase of 30% in significant P-values, as well as linkage to 106 versus 99 disease models via phenotype overlap with the soft-windowed and non-windowed approaches, respectively, from a set of 2082 mutant mouse lines. Our method is generalizable and can benefit large-scale human phenomic projects such as the UK Biobank and the All of Us resources. AVAILABILITY AND IMPLEMENTATION: The method is freely available in the R package SmoothWin, available on CRAN http://CRAN.R-project.org/package=SmoothWin. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Genetic Variants For Head Size Share Genes and Pathways With Cancer

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer

Open X-Embodiment:Robotic learning datasets and RT-X models

Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for many applications. Can such a consolidation happen in robotics? Conventionally, robotic learning methods train a separate model for every application, every robot, and even every environment. Can we instead train "generalist" X-robot policy that can be adapted efficiently to new robots, tasks, and environments? In this paper, we provide datasets in standardized data formats and models to make it possible to explore this possibility in the context of robotic manipulation, alongside experimental results that provide an example of effective X-robot policies. We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). We show that a high-capacity model trained on this data, which we call RT-X, exhibits positive transfer and improves the capabilities of multiple robots by leveraging experience from other platforms. The project website is robotics-transformer-x.github.io