Deconstructing \u27Just and Proper\u27: Arguments in Favor of Adopting the \u27Remedial Purpose\u27 Approach to Section 10(J) Labor Injunctions

Congress, through the 1947 addition of section 10(j) to the National Labor Relations Act, authorized district courts to grant preliminary injunctive relief for unfair labor practices if they deem such relief just and proper. To this day a circuit split persists over the correct interpretation of this just and proper standard. Some circuits interpret just and proper to require application of the traditional equitable principles approach that normally governs preliminary injunctions. Other circuits interpret just and proper to require an analysis of whether injunctive relief is necessary to preserve the National Labor Relations Board\u27s remedial power This Note examines the justifications behind these two interpretations in light of section 10(j)\u27s statutory structure-most notably, the use of the just and proper standard in two other provisions of the National Labor Relations Act. It also considers the legislative history of section 10(j) and the public policy consequences underlying Congress\u27s mandate granting the Board exclusive jurisdiction to seek injunctive relief in court under section 10(j). This Note argues that an examination of these factors reveals that Congress intended for courts to focus their section 10(j) analysis on the preservation of the National Labor Relations Board\u27s remedial power rather than on traditional equitable principles

Data consistency in the English Hospital Episodes Statistics database

BACKGROUND: To gain maximum insight from large administrative healthcare datasets it is important to understand their data quality. Although a gold standard against which to assess criterion validity rarely exists for such datasets, internal consistency can be evaluated. We aimed to identify inconsistencies in the recording of mandatory International Statistical Classification of Diseases and Related Health Problems, tenth revision (ICD-10) codes within the Hospital Episodes Statistics dataset in England. METHODS: Three exemplar medical conditions where recording is mandatory once diagnosed were chosen: autism, type II diabetes mellitus and Parkinson's disease dementia. We identified the first occurrence of the condition ICD-10 code for a patient during the period April 2013 to March 2021 and in subsequent hospital spells. We designed and trained random forest classifiers to identify variables strongly associated with recording inconsistencies. RESULTS: For autism, diabetes and Parkinson's disease dementia respectively, 43.7%, 8.6% and 31.2% of subsequent spells had inconsistencies. Coding inconsistencies were highly correlated with non-coding of an underlying condition, a change in hospital trust and greater time between the spell with the first coded diagnosis and the subsequent spell. For patients with diabetes or Parkinson's disease dementia, the code recording for spells without an overnight stay were found to have a higher rate of inconsistencies. CONCLUSIONS: Data inconsistencies are relatively common for the three conditions considered. Where these mandatory diagnoses are not recorded in administrative datasets, and where clinical decisions are made based on such data, there is potential for this to impact patient care

Paracrine Induction of HIF by Glutamate in Breast Cancer: EglN1 Senses Cysteine

The HIF transcription factor promotes adaptation to hypoxia and stimulates the growth of certain cancers, including triple-negative breast cancer (TNBC). The HIFα subunit is usually prolyl-hydroxylated by EglN family members under normoxic conditions, causing its rapid degradation. We confirmed that TNBC cells secrete glutamate, which we found is both necessary and sufficient for the paracrine induction of HIF1α in such cells under normoxic conditions. Glutamate inhibits the xCT glutamate-cystine antiporter, leading to intracellular cysteine depletion. EglN1, the main HIFα prolyl-hydroxylase, undergoes oxidative self-inactivation in the absence of cysteine both in biochemical assays and in cells, resulting in HIF1α accumulation. Therefore, EglN1 senses both oxygen and cysteine

SIMULTANEOUS OBSERVATIONS of GIANT PULSES from the CRAB PULSAR, with the MURCHISON WIDEFIELD ARRAY and PARKES RADIO TELESCOPE: IMPLICATIONS for the GIANT PULSE EMISSION MECHANISM

We report on observations of giant pulses from the Crab pulsar performed simultaneously with the Parkes radio telescope and the incoherent combination of the Murchison Widefield Array (MWA) antenna tiles. The observations were performed over a duration of approximately one hour at a center frequency of 1382 MHz with 340 MHz bandwidth at Parkes, and at a center frequency of 193 MHz with 15 MHz bandwidth at the MWA. Our analysis has led to the detection of 55 giant pulses at the MWA and 2075 at Parkes above a threshold of 3.5σ and 6.5σ, respectively. We detected 51% of the MWA giant pulses at the Parkes radio telescope, with spectral indices in the range of -3.6 > α > -4.9 (Sv ∝ vα). We present a Monte Carlo analysis supporting the conjecture that the giant pulse emission in the Crab is intrinsically broadband, the less than 100% correlation being due to the relative sensitivities of the two instruments and the width of the spectral index distribution. Our observations are consistent with the hypothesis that the spectral index of giant pulses is drawn from normal distribution of standard deviation 0.6, but with a mean that displays an evolution with frequency from -3.00 at 1382 MHz, to -2.85 at 192 MHz

Metabolic profiling of aortic stenosis and hypertrophic cardiomyopathy identifies mechanistic contrasts in substrate utilization

Open Access via the Wiley Agreement UKRI | Medical Research Council (MRC), Grant/Award Number: MR/ P011705/1, MC_UP_A090_1006 and MR/S010483; British Heart Foundation (BHF); NIHR | NIHR Oxford Biomedical Research Centre (OxBRC)Peer reviewe

Sloan Digital Sky Survey Imaging of Low Galactic Latitude Fields: Technical Summary and Data Release

The Sloan Digital Sky Survey (SDSS) mosaic camera and telescope have obtained five-band optical-wavelength imaging near the Galactic plane outside of the nominal survey boundaries. These additional data were obtained during commissioning and subsequent testing of the SDSS observing system, and they provide unique wide-area imaging data in regions of high obscuration and star formation, including numerous young stellar objects, Herbig-Haro objects and young star clusters. Because these data are outside the Survey regions in the Galactic caps, they are not part of the standard SDSS data releases. This paper presents imaging data for 832 square degrees of sky (including repeats), in the star-forming regions of Orion, Taurus, and Cygnus. About 470 square degrees are now released to the public, with the remainder to follow at the time of SDSS Data Release 4. The public data in Orion include the star-forming region NGC 2068/NGC 2071/HH24 and a large part of Barnard's loop.Comment: 31 pages, 9 figures (3 missing to save space), accepted by AJ, in press, see http://photo.astro.princeton.edu/oriondatarelease for data and paper with all figure

Variability in COVID-19 in-hospital mortality rates between national health service trusts and regions in England: A national observational study for the Getting It Right First Time Programme

Background A key first step in optimising COVID-19 patient outcomes during future case-surges is to learn from the experience within individual hospitals during the early stages of the pandemic. The aim of this study was to investigate the extent of variation in COVID-19 outcomes between National Health Service (NHS) hospital trusts and regions in England using data from March–July 2020. Methods This was a retrospective observational study using the Hospital Episode Statistics administrative dataset. Patients aged ≥ 18 years who had a diagnosis of COVID-19 during a hospital stay in England that was completed between March 1st and July 31st, 2020 were included. In-hospital mortality was the primary outcome of interest. In secondary analysis, critical care admission, length of stay and mortality within 30 days of discharge were also investigated. Multilevel logistic regression was used to adjust for covariates. Findings There were 86,356 patients with a confirmed diagnosis of COVID-19 included in the study, of whom 22,944 (26.6%) died in hospital with COVID-19 as the primary cause of death. After adjusting for covariates, the extent of the variation in-hospital mortality rates between hospital trusts and regions was relatively modest. Trusts with the largest baseline number of beds and a greater proportion of patients admitted to critical care had the lowest in-hospital mortality rates. Interpretation There is little evidence of clustering of deaths within hospital trusts. There may be opportunities to learn from the experience of individual trusts to help prepare hospitals for future case-surges

Bias correction and Bayesian analysis of aggregate counts in SAGE libraries

<p>Abstract</p> <p>Background</p> <p>Tag-based techniques, such as SAGE, are commonly used to sample the mRNA pool of an organism's transcriptome. Incomplete digestion during the tag formation process may allow for multiple tags to be generated from a given mRNA transcript. The probability of forming a tag varies with its relative location. As a result, the observed tag counts represent a biased sample of the actual transcript pool. In SAGE this bias can be avoided by ignoring all but the 3' most tag but will discard a large fraction of the observed data. Taking this bias into account should allow more of the available data to be used leading to increased statistical power.</p> <p>Results</p> <p>Three new hierarchical models, which directly embed a model for the variation in tag formation probability, are proposed and their associated Bayesian inference algorithms are developed. These models may be applied to libraries at both the tag and aggregate level. Simulation experiments and analysis of real data are used to contrast the accuracy of the various methods. The consequences of tag formation bias are discussed in the context of testing differential expression. A description is given as to how these algorithms can be applied in that context.</p> <p>Conclusions</p> <p>Several Bayesian inference algorithms that account for tag formation effects are compared with the DPB algorithm providing clear evidence of superior performance. The accuracy of inferences when using a particular non-informative prior is found to depend on the expression level of a given gene. The multivariate nature of the approach easily allows both univariate and joint tests of differential expression. Calculations demonstrate the potential for false positive and negative findings due to variation in tag formation probabilities across samples when testing for differential expression.</p

Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

Data quality and autism : issues and potential impacts

Introduction Large healthcare datasets can provide insight that has the potential to improve outcomes for patients. However, it is important to understand the strengths and limitations of such datasets so that the insights they provide are accurate and useful. The aim of this study was to identify data inconsistencies within the Hospital Episodes Statistics (HES) dataset for autistic patients and assess potential biases introduced through these inconsistencies and their impact on patient outcomes. The study can only identify inconsistencies in recording of autism diagnosis and not whether the inclusion or exclusion of the autism diagnosis is the error. Methods Data were extracted from the HES database for the period 1st April 2013 to 31st March 2021 for patients with a diagnosis of autism. First spells in hospital during the study period were identified for each patient and these were linked to any subsequent spell in hospital for the same patient. Data inconsistencies were recorded where autism was not recorded as a diagnosis in a subsequent spell. Features associated with data inconsistencies were identified using a random forest classifiers and regression modelling. Results Data were available for 172,324 unique patients who had been recorded as having an autism diagnosis on first admission. In total, 43.7 % of subsequent spells were found to have inconsistencies. The features most strongly associated with inconsistencies included greater age, greater deprivation, longer time since the first spell, change in provider, shorter length of stay, being female and a change in the main specialty description. The random forest algorithm had an area under the receiver operating characteristic curve of 0.864 (95 % CI [0.862 – 0.866]) in predicting a data inconsistency. For patients who died in hospital, inconsistencies in their final spell were significantly associated with being 80 years and over, being female, greater deprivation and use of a palliative care code in the death spell. Conclusions Data inconsistencies in the HES database were relatively common in autistic patients and were associated a number of patient and hospital admission characteristics. Such inconsistencies have the potential to distort our understanding of service use in key demographic groups