CENP-meta, an essential kinetochore kinesin required for the maintenance of metaphase chromosome alignment in Drosophila.

CENP-meta has been identified as an essential, kinesin-like motor protein in Drosophila. The 257-kD CENP-meta protein is most similar to the vertebrate kinetochore-associated kinesin-like protein CENP-E, and like CENP-E, is shown to be a component of centromeric/kinetochore regions of Drosophila chromosomes. However, unlike CENP-E, which leaves the centromere/kinetochore region at the end of anaphase A, the CENP-meta protein remains associated with the centromeric/kinetochore region of the chromosome during all stages of the Drosophila cell cycle. P-element-mediated disruption of the CENP-meta gene leads to late larval/pupal stage lethality with incomplete chromosome alignment at metaphase. Complete removal of CENP-meta from the female germline leads to lethality in early embryos resulting from defects in metaphase chromosome alignment. Real-time imaging of these mutants with GFP-labeled chromosomes demonstrates that CENP-meta is required for the maintenance of chromosomes at the metaphase plate, demonstrating that the functions required to establish and maintain chromosome congression have distinguishable requirements

Fetal exome sequencing for isolated increased nuchal translucency: should we be doing it?

Objective: To evaluate the utility of prenatal exome sequencing (ES) for isolated increased nuchal translucency (NT) and investigate factors which increase diagnostic yield. Design: Retrospective analysis of data from two prospective cohort studies. Setting: Fetal medicine centres in the UK and USA. Population: Fetuses with increased NT ≥3.5mm at 11-14 weeks’ gestation recruited to the Prenatal Assessment of Genomes and Exomes (PAGE) and Columbia fetal WES studies (n = 213). Methods: We grouped cases based on (i) the presence of additional structural abnormalities at presentation in the first trimester or later in pregnancy, and (ii) NT measurement at presentation. We compared diagnostic rates between groups using Fisher exact test. Main Outcome Measures: Detection of diagnostic genetic variants considered to have caused the observed fetal structural anomaly. Results: Diagnostic variants were detected in 12 (22.2%) of 54 fetuses presenting with non-isolated increased NT, 12 (32.4%) of 37 fetuses with isolated increased NT in the first trimester and additional abnormalities later in pregnancy, and 2 (1.8%) of 111 fetuses with isolated increased NT in the first trimester and no other abnormalities on subsequent scans. Diagnostic rate also increased with increasing size of NT. Conclusions: The diagnostic yield of prenatal ES is low for fetuses with isolated increased NT but significantly higher where there are additional structural anomalies. Prenatal ES may not be appropriate for truly isolated increased NT but timely, careful ultrasound scanning to identify other anomalies emerging later can direct testing to focus where there is a higher likelihood of diagnosis

Automatic construction of rule-based ICD-9-CM coding systems

Background: In this paper we focus on the problem of automatically constructing ICD-9-CM coding systems for radiology reports. ICD-9-CM codes are used for billing purposes by health institutes and are assigned to clinical records manually following clinical treatment. Since this labeling task requires expert knowledge in the field of medicine, the process itself is costly and is prone to errors as human annotators have to consider thousands of possible codes when assigning the right ICD-9-CM labels to a document. In this study we use the datasets made available for training and testing automated ICD-9-CM coding systems by the organisers of an International Challenge on Classifying Clinical Free Text Using Natural Language Processing in spring 2007. The challenge itself was dominated by entirely or partly rule-based systems that solve the coding task using a set of hand crafted expert rules. Since the feasibility of the construction of such systems for thousands of ICD codes is indeed questionable, we decided to examine the problem of automatically constructing similar rule sets that turned out to achieve a remarkable accuracy in the shared task challenge. Results: Our results are very promising in the sense that we managed to achieve comparable results with purely hand-crafted ICD-9-CM classifiers. Our best model got a 90.26 % F measure on the training dataset and an 88.93 % F measure on the challenge test dataset, using the micro-averaged Fβ=1 measure, the official evaluatio

Visualizing the Feature Importance for Black Box Models

In recent years, a large amount of model-agnostic methods to improve the transparency, trustability and interpretability of machine learning models have been developed. We introduce local feature importance as a local version of a recent model-agnostic global feature importance method. Based on local feature importance, we propose two visual tools: partial importance (PI) and individual conditional importance (ICI) plots which visualize how changes in a feature affect the model performance on average, as well as for individual observations. Our proposed methods are related to partial dependence (PD) and individual conditional expectation (ICE) plots, but visualize the expected (conditional) feature importance instead of the expected (conditional) prediction. Furthermore, we show that averaging ICI curves across observations yields a PI curve, and integrating the PI curve with respect to the distribution of the considered feature results in the global feature importance. Another contribution of our paper is the Shapley feature importance, which fairly distributes the overall performance of a model among the features according to the marginal contributions and which can be used to compare the feature importance across different models.Comment: To Appear in Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10 to 14, 2018, Proceedings, Part

Acute kidney disease and renal recovery : consensus report of the Acute Disease Quality Initiative (ADQI) 16 Workgroup

Consensus definitions have been reached for both acute kidney injury (AKI) and chronic kidney disease (CKD) and these definitions are now routinely used in research and clinical practice. The KDIGO guideline defines AKI as an abrupt decrease in kidney function occurring over 7 days or less, whereas CKD is defined by the persistence of kidney disease for a period of > 90 days. AKI and CKD are increasingly recognized as related entities and in some instances probably represent a continuum of the disease process. For patients in whom pathophysiologic processes are ongoing, the term acute kidney disease (AKD) has been proposed to define the course of disease after AKI; however, definitions of AKD and strategies for the management of patients with AKD are not currently available. In this consensus statement, the Acute Disease Quality Initiative (ADQI) proposes definitions, staging criteria for AKD, and strategies for the management of affected patients. We also make recommendations for areas of future research, which aim to improve understanding of the underlying processes and improve outcomes for patients with AKD

Interoception in functional motor symptoms and functional seizures: Preliminary evidence of intact accuracy alongside reduced insight and altered sensibility

Altered interoception may be a pathophysiological mechanism in functional neurological disorder (FND). However, findings have been inconsistent across interoceptive dimensions in FND including functional motor symptoms (FMS) and seizures (FS). Here, individuals with FMS/FS (n = 17) and healthy controls (HC, n = 17) completed measures of interoceptive accuracy and insight (adapted heartbeat tracking task [HTT] with confidence ratings), a time estimation control task (TET) and the Multidimensional Assessment of Interoceptive Awareness-2 (MAIA-2) to assess interoceptive sensibility. The groups did not differ in interoceptive accuracy (p = 1.00, g = 0.00) or confidence (p = .99, g = 0.004), although the FMS/FS group displayed lower scores on the "Not-Distracting" (p < .001, g = 1.42) and "Trusting" (p = .005, g = 1.17) MAIA-2 subscales, relative to HCs. The groups did not differ in TET performance (p = .82, g = 0.08). There was a positive relationship between HTT accuracy and confidence (insight) in HCs (r = .61, p = .016) but not in FMS/FS (r = 0.11, p = .69). HTT confidence was positively correlated with MAIA-2 "Self-Regulation" (r = 0.77, p = .002) and negatively correlated with FND symptom severity (r = -0.84, p < .001) and impact (r = -0.86, p < .001) in FMS/FS. Impaired interoceptive accuracy may not be a core feature in FMS/FS, but reduced insight and altered sensibility may be relevant. Reduced certainty in self-evaluations of bodily experiences may contribute to the pathogenesis of FND symptoms

Elemental analysis of lung tissue particles and intracellular iron content of alveolar macrophages in pulmonary alveolar proteinosis

<p>Abstract</p> <p>Background</p> <p>Pulmonary alveolar proteinosis (PAP) is a rare disease occurred by idiopathic (autoimmune) or secondary to particle inhalation. The in-air microparticle induced X-ray emission (in-air micro-PIXE) system performs elemental analysis of materials by irradiation with a proton microbeam, and allows visualization of the spatial distribution and quantitation of various elements with very low background noise. The aim of this study was to assess the secondary PAP due to inhalation of harmful particles by employing in-air micro-PIXE analysis for particles and intracellular iron in parafin-embedded lung tissue specimens obtained from a PAP patient comparing with normal lung tissue from a non-PAP patient. The iron inside alveolar macrophages was stained with Berlin blue, and its distribution was compared with that on micro-PIXE images.</p> <p>Results</p> <p>The elements composing particles and their locations in the PAP specimens could be identified by in-air micro-PIXE analysis, with magnesium (Mg), aluminum (Al), silicon (Si), phosphorus (P), sulfur (S), scandium (Sc), potassium (K), calcium (Ca), titanium (Ti), chromium (Cr), copper (Cu), manganase (Mn), iron (Fe), and zinc (Zn) being detected. Si was the major component of the particles. Serial sections stained by Berlin blue revealed accumulation of sideromacrophages that had phagocytosed the particles. The intracellular iron content of alveolar macrophage from the surfactant-rich area in PAP was higher than normal lung tissue in control lung by both in-air micro-PIXE analysis and Berlin blue staining.</p> <p>Conclusion</p> <p>The present study demonstrated the efficacy of in-air micro-PIXE for analyzing the distribution and composition of lung particles. The intracellular iron content of single cells was determined by simultaneous two-dimensional and elemental analysis of paraffin-embedded lung tissue sections. The results suggest that secondary PAP is associated with exposure to inhaled particles and accumulation of iron in alveolar macrophages.</p

Positive Clinical Neuroscience: Explorations in Positive Neurology

Disorders of the brain and its sensory organs have traditionally been associated with deficits in movement, perception, cognition, emotion, and behavior. It is increasingly evident, however, that positive phenomena may also occur in such conditions, with implications for the individual, science, medicine, and for society. This article provides a selective review of such positive phenomena – enhanced function after brain lesions, better-than-normal performance in people with sensory loss, creativity associated with neurological disease, and enhanced performance associated with aging. We propose that, akin to the well-established field of positive psychology and the emerging field of positive clinical psychology, the nascent fields of positive neurology and positive neuropsychology offer new avenues to understand brain-behavior relationships, with both theoretical and therapeutic implications

Objective and subjective neurocognitive functioning in functional motor symptoms and functional seizures: preliminary findings

INTRODUCTION: This study aimed to provide a preliminary assessment of objective and subjective neurocognitive functioning in individuals with functional motor symptoms (FMS) and/or functional seizures (FS). We tested the hypotheses that the FMS/FS group would display poorer objective attentional and executive functioning, altered social cognition, and reduced metacognitive accuracy. METHOD: Individuals with FMS/FS (n = 16) and healthy controls (HCs, n = 17) completed an abbreviated CANTAB battery, and measures of intellectual functioning, subjective cognitive complaints, performance validity, and comorbid symptoms. Subjective performance ratings were obtained to assess local metacognitive accuracy. RESULTS: The groups were comparable in age (p = 0.45), sex (p = 0.62), IQ (p = 0.57), and performance validity (p-values = 0.10-0.91). We observed no impairment on any CANTAB test in this FMS/FS sample compared to HCs, although the FMS/FS group displayed shorter reaction times on the Emotional Bias task (anger) (p = 0.01, np2 = 0.20). The groups did not differ in subjective performance ratings (p-values 0.15). Whilst CANTAB attentional set-shifting performance (total trials/errors) correlated with subjective performance ratings in HCs (p-values<0.005, rs = -0.85), these correlations were non-significant in the FMS/FS sample (p-values = 0.10-0.13, rs-values = -0.46-0.50). The FMS/FS group reported more daily cognitive complaints than HCs (p = 0.006, g = 0.92), which were associated with subjective performance ratings on CANTAB sustained attention (p = 0.001, rs = -0.74) and working memory tests (p < 0.001, rs = -0.75), and with depression (p = 0.003, rs = 0.70), and somatoform (p = 0.003, rs = 0.70) and psychological dissociation (p-values<0.005, rs-values = 0.67-0.85). CONCLUSIONS: These results suggest a discordance between objective and subjective neurocognitive functioning in this FMS/FS sample, reflecting intact test performance alongside poorer subjective cognitive functioning. Further investigation of neurocognitive functioning in FND subgroups is necessary

Utilizing electronic health records to predict acute kidney injury risk and outcomes: Workgroup statements from the 15^th ADQI Consensus Conference

The data contained within the electronic health record (EHR) is "big" from the standpoint of volume, velocity, and variety. These circumstances and the pervasive trend towards EHR adoption have sparked interest in applying big data predictive analytic techniques to EHR data. Acute kidney injury (AKI) is a condition well suited to prediction and risk forecasting; not only does the consensus definition for AKI allow temporal anchoring of events, but no treatments exist once AKI develops, underscoring the importance of early identification and prevention. The Acute Dialysis Quality Initiative (ADQI) convened a group of key opinion leaders and stakeholders to consider how best to approach AKI research and care in the "Big Data" era. This manuscript addresses the core elements of AKI risk prediction and outlines potential pathways and processes. We describe AKI prediction targets, feature selection, model development, and data display