Employment Protection Legislation and Plant-Level Productivity in India

Using plant-level data from the Annual Survey of Industries (ASI) for the fiscal years from 1998-99 through 2007-08, this study provides plant-level cross-state/time-series evidence of the impact of employment protection legislation (EPL) on total factor productivity (TFP) and labor productivity in India. Identification of the effect of EPL follows from a difference-in-differences estimator inspired by Rajan and Zingales (1998) that takes advantage of the state-level variation in labor regulation and heterogeneous industry characteristics. The fundamental identification assumption is that EPL is more likely to restrict firms operating in industries with higher labor intensity and/or higher sales volatility. Our results show that firms in labor intensive or more volatile industries benefited the most from labor reforms in their states. Our point estimates indicate that, on average, firms in labor intensive industries and in flexible labor markets have TFP residuals 14% higher than those registered for their counterparts in states with more stringent labor laws. However, no important differences are identified among plants in industries with low labor intensity when comparing states with high and low levels of EPL reform. Similarly, the TFP of plants in volatile industries and in states that experienced more pro-employer reforms is 11% higher than that of firms in volatile industries and in more restrictive states; however, the TFP residuals of plants in industries with low labor intensity are 11% lower in high EPL reform states than in states with lower levels of EPL reform. In sum, the evidence presented here suggests that the high labor costs and rigidities imposed through Indian federal labor laws are lessened by labor market reforms at the state level.

A Chromosomal Deletion and New Frameshift Mutation Cause ARSACS in an African-American

Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay (ARSACS) is a rare, progressive, neurodegenerative disease characterized by ataxia, spasticity and polyneuropathy. First described in the French-Canadian population of Quebec in 1978, ARSACS has since been identified in multiple patients worldwide. In this clinical case report, we describe the evaluation of an 11-years-old African-American male who presented to neuromuscular clinic for assessment of a gait abnormality. He had a history of gross motor delay since early childhood, frequent falls and a below average IQ. Chromosomal microarray revealed a 1.422 megabase loss in the 13q12.12 region, which includes the SACS gene. Next Generation Sequencing then showed a novel, predicted to be pathogenic missense mutation (c.11824dup) of this gene. His clinical presentation and neurological imaging further confirmed the diagnosis of ARSACS. To our knowledge, this is the first reported case of this disease in the African-American population of the United States. This case report further highlights the growing trend of identifying genetic diseases previously restricted to single, ethnically isolated regions in many different ethnic groups worldwide

Extracorporeal Membrane Oxygenation in Severe Acute Eosinophilic Pneumonia

Acute Eosinophilic Pneumonia (AEP) is a potentially fatal cause of hypoxemic respiratory failure characterized by fever, diffuse bilateral pulmonary infiltrates, and pulmonary eosinophilia. Shown to be associated with a number of environmental exposures and lifestyle choices, AEP has a good prognosis when diagnosed early and treated with corticosteroids. In this clinical case report, we detail the presentation, evaluation, diagnosis, and management of a 40-year old male who presented to the emergency department with dyspnea, chills, and diaphoresis. He had a history of pulmonary embolism 8 years prior but was otherwise healthy, though he had re-started smoking cigarettes a week prior to presentation. Initial chest CT scan revealed widespread mixed groundglass and solid airspace opacities; over the next 12 hours, he rapidly decompensated and after not responding to other invasive mechanical ventilation, was emergently cannulated for veno-venous extracorporeal membrane oxygenation (V-V ECMO). Bronchoalveolar lavage later revealed pulmonary eosinophilia, and after an infectious workup was negative, a diagnosis of AEP was reached and the patient was started on corticosteroids. To our knowledge, this is one of few published cases of AEP requiring V-V ECMO for clinical stabilization, highlighting the utility of this treatment modality in severe disease

LOGISTICS IN CONTESTED ENVIRONMENTS

This report examines the transport and delivery of logistics in contested environments within the context of great-power competition (GPC). Across the Department of Defense (DOD), it is believed that GPC will strain our current supply lines beyond their capacity to maintain required warfighting capability. Current DOD efforts are underway to determine an appropriate range of platforms, platform quantities, and delivery tactics to meet the projected logistics demand in future conflicts. This report explores the effectiveness of various platforms and delivery methods through analysis in developed survivability, circulation, and network optimization models. Among other factors, platforms are discriminated by their radar cross-section (RCS), noise level, speed, cargo capacity, and self-defense capability. To maximize supply delivered and minimize the cost of losses, the results of this analysis indicate preference for utilization of well-defended convoys on supply routes where bulk supply is appropriate and smaller, and widely dispersed assets on shorter, more contested routes with less demand. Sensitivity analysis on these results indicates system survivability can be improved by applying RCS and noise-reduction measures to logistics assets.Director, Warfare Integration (OPNAV N9I)Major, Israel Defence ForcesCivilian, Singapore Technologies Engineering Ltd, SingaporeCommander, Republic of Singapore NavyCommander, United States NavyCaptain, Singapore ArmyLieutenant, United States NavyLieutenant, United States NavyMajor, Republic of Singapore Air ForceCaptain, United States Marine CorpsLieutenant, United States NavyLieutenant, United States NavyLieutenant, United States NavyLieutenant, United States NavyLieutenant, United States NavyCaptain, Singapore ArmyLieutenant Junior Grade, United States NavyCaptain, Singapore ArmyLieutenant Colonel, Republic of Singapore Air ForceApproved for public release. distribution is unlimite

Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning

Understanding the spatial organization of tissues is of critical importance for both basic and translational research. While recent advances in tissue imaging are opening an exciting new window into the biology of human tissues, interpreting the data that they create is a significant computational challenge. Cell segmentation, the task of uniquely identifying each cell in an image, remains a substantial barrier for tissue imaging, as existing approaches are inaccurate or require a substantial amount of manual curation to yield useful results. Here, we addressed the problem of cell segmentation in tissue imaging data through large-scale data annotation and deep learning. We constructed TissueNet, an image dataset containing >1 million paired whole-cell and nuclear annotations for tissue images from nine organs and six imaging platforms. We created Mesmer, a deep learning-enabled segmentation algorithm trained on TissueNet that performs nuclear and whole-cell segmentation in tissue imaging data. We demonstrated that Mesmer has better speed and accuracy than previous methods, generalizes to the full diversity of tissue types and imaging platforms in TissueNet, and achieves human-level performance for whole-cell segmentation. Mesmer enabled the automated extraction of key cellular features, such as subcellular localization of protein signal, which was challenging with previous approaches. We further showed that Mesmer could be adapted to harness cell lineage information present in highly multiplexed datasets. We used this enhanced version to quantify cell morphology changes during human gestation. All underlying code and models are released with permissive licenses as a community resource

Mapping genetic variations to three- dimensional protein structures to enhance variant interpretation: a proposed framework

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods

Phasevarions Mediate Random Switching of Gene Expression in Pathogenic Neisseria

Many host-adapted bacterial pathogens contain DNA methyltransferases (mod genes) that are subject to phase-variable expression (high-frequency reversible ON/OFF switching of gene expression). In Haemophilus influenzae, the random switching of the modA gene controls expression of a phase-variable regulon of genes (a “phasevarion”), via differential methylation of the genome in the modA ON and OFF states. Phase-variable mod genes are also present in Neisseria meningitidis and Neisseria gonorrhoeae, suggesting that phasevarions may occur in these important human pathogens. Phylogenetic studies on phase-variable mod genes associated with type III restriction modification (R-M) systems revealed that these organisms have two distinct mod genes—modA and modB. There are also distinct alleles of modA (abundant: modA11, 12, 13; minor: modA4, 15, 18) and modB (modB1, 2). These alleles differ only in their DNA recognition domain. ModA11 was only found in N. meningitidis and modA13 only in N. gonorrhoeae. The recognition site for the modA13 methyltransferase in N. gonorrhoeae strain FA1090 was identified as 5′-AGAAA-3′. Mutant strains lacking the modA11, 12 or 13 genes were made in N. meningitidis and N. gonorrhoeae and their phenotype analyzed in comparison to a corresponding mod ON wild-type strain. Microarray analysis revealed that in all three modA alleles multiple genes were either upregulated or downregulated, some of which were virulence-associated. For example, in N. meningitidis MC58 (modA11), differentially expressed genes included those encoding the candidate vaccine antigens lactoferrin binding proteins A and B. Functional studies using N. gonorrhoeae FA1090 and the clinical isolate O1G1370 confirmed that modA13 ON and OFF strains have distinct phenotypes in antimicrobial resistance, in a primary human cervical epithelial cell model of infection, and in biofilm formation. This study, in conjunction with our previous work in H. influenzae, indicates that phasevarions may be a common strategy used by host-adapted bacterial pathogens to randomly switch between “differentiated” cell types

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

Obscured AGN enhancement in galaxy pairs at cosmic noon: evidence from a probabilistic treatment of photometric redshifts

Observations of the nearby universe reveal an increasing fraction of active galactic nuclei (AGN) with decreasing projected separation for close galaxy pairs, relative to control galaxies. This implies galaxy interactions play a role in enhancing AGN activity. However, the picture at higher redshift is less established, partly due to limited spectroscopic redshifts. We combine spectroscopic surveys with photometric redshift probability distribution functions for galaxies in the CANDELS and COSMOS surveys, to produce the largest ever sample of galaxy pairs used in an AGN fraction calculation for cosmic noon ($0.5<z<3$). We present a new technique for assessing galaxy pair probability (based on line-of-sight velocities +/-1000 km/s) from photometric redshift posterior convolutions and use these to produce weighted AGN fractions. Over projected separations 5-100kpc we find no evidence for enhancement, relative to isolated control galaxies, of X-ray (L_X > 10^42 erg/s) or infrared-selected AGN in major (mass ratios up to 4:1) or minor (4:1 to 10:1) galaxy pairs. However, defining the most obscured AGN as those detected in the infrared but not in X-rays, we observe a trend of increasing obscured AGN enhancement at decreasing separations. The peak enhancement, relative to isolated controls, is a factor of 2.08+/-0.61 for separations <25kpc. Our simulations with mock data, indicates this could be a lower limit of the true enhancement. If confirmed with improved infrared imaging (e.g., with JWST) and redshifts (e.g., with forthcoming multi-object spectrograph surveys), this would suggest that galaxy interactions play a role in enhancing the most obscured black hole growth at cosmic noon.Comment: Accepted for publication in MNRA

Brief Report: PrEP Uptake, Adherence, and Discontinuation Among California YMSM Using Geosocial Networking Applications.

We investigated pre-exposure prophylaxis (PrEP) uptake, adherence, and discontinuation among young app-using men who have sex with men in California (N = 761). Approximately, 9.7% of participants had ever used PrEP; 87% of those deemed good candidates for screening (indicated by a Centers for Disease Control and Prevention risk index score ≥10) were not current or past users. PrEP use was associated with higher income [adjusted odds ratio (aOR): 4.13; confidence interval (CI): 1.87 to 9.12], receptive condomless anal sex (aOR: 3.41; CI: 1.71 to 6.78), HIV-positive sex partners (aOR: 2.87; CI: 1.53 to 5.38), popper use (aOR: 3.47; CI: 1.96 to 6.13), and recent sexually transmitted infection diagnosis (aOR: 2.90; CI: 1.64 to 5.13). Some users (41.5%) wanted help remembering to take PrEP. The top reason for discontinuation was concern about long-term side effects (33.0%). Young men who have sex with men app users are prime candidates for PrEP, despite low uptake. Apps may be useful tools for PrEP information dissemination, adherence monitoring, and support