Deceptive learning in histopathology

AIMS

Deep learning holds immense potential for histopathology, automating tasks that are simple for expert pathologists and revealing novel biology for tasks that were previously considered difficult or impossible to solve by eye alone. However, the extent to which the visual strategies learned by deep learning models in histopathological analysis are trustworthy or not has yet to be systematically analysed. Here, we systematically evaluate deep neural networks (DNNs) trained for histopathological analysis in order to understand if their learned strategies are trustworthy or deceptive.

METHODS AND RESULTS

We trained a variety of DNNs on a novel data set of 221 whole-slide images (WSIs) from lung adenocarcinoma patients, and evaluated their effectiveness at (1) molecular profiling of KRAS versus EGFR mutations, (2) determining the primary tissue of a tumour and (3) tumour detection. While DNNs achieved above-chance performance on molecular profiling, they did so by exploiting correlations between histological subtypes and mutations, and failed to generalise to a challenging test set obtained through laser capture microdissection (LCM). In contrast, DNNs learned robust and trustworthy strategies for determining the primary tissue of a tumour as well as detecting and localising tumours in tissue.

CONCLUSIONS

Our work demonstrates that DNNs hold immense promise for aiding pathologists in analysing tissue. However, they are also capable of achieving seemingly strong performance by learning deceptive strategies that leverage spurious correlations, and are ultimately unsuitable for research or clinical work. The framework we propose for model evaluation and interpretation is an important step towards developing reliable automated systems for histopathological analysis.

Genetic and molecular architecture of complex traits

Human genetics has emerged as one of the most dynamic areas of biology, with a broadening societal impact. In this review, we discuss recent achievements, ongoing efforts, and future challenges in the field. Advances in technology, statistical methods, and the growing scale of research efforts have all provided many insights into the processes that have given rise to the current patterns of genetic variation. Vast maps of genetic associations with human traits and diseases have allowed characterization of their genetic architecture. Finally, studies of molecular and cellular effects of genetic variants have provided insights into biological processes underlying disease. Many outstanding questions remain, but the field is well poised for groundbreaking discoveries as it increases the use of genetic data to understand both the history of our species and its applications to improve human health.

Measurement of the Positive Muon Anomalous Magnetic Moment to 0.20 ppm

We present a new measurement of the positive muon magnetic anomaly, a_{μ}≡(g_{μ}-2)/2, from the Fermilab Muon g-2 Experiment using data collected in 2019 and 2020. We have analyzed more than 4 times the number of positrons from muon decay than in our previous result from 2018 data. The systematic error is reduced by more than a factor of 2 due to better running conditions, a more stable beam, and improved knowledge of the magnetic field weighted by the muon distribution, ω[over ˜]_{p}^{'}, and of the anomalous precession frequency corrected for beam dynamics effects, ω_{a}. From the ratio ω_{a}/ω[over ˜]_{p}^{'}, together with precisely determined external parameters, we determine a_{μ}=116 592 057(25)×10^{-11} (0.21 ppm). Combining this result with our previous result from the 2018 data, we obtain a_{μ}(FNAL)=116 592 055(24)×10^{-11} (0.20 ppm). The new experimental world average is a_{μ}(exp)=116 592 059(22)×10^{-11} (0.19 ppm), which represents a factor of 2 improvement in precision.

Aerosols heat up the Himalayan climate

The impact of aerosols, especially the absorbing aerosols, in the Himalayan region is important for climate. We closely examine ground-based high-quality observations of aerosol characteristics including radiative forcing from several locations in the Indo-Gangetic Plain (IGP), the Himalayan foothills and the Tibetan Plateau, relatively poorly studied regions with several sensitive ecosystems of global importance, as well as highly vulnerable large populations. This paper presents a state-of-the-art treatment of the warming that arises from these particles, using a combination of new measurements and modeling techniques. This is a first-time analysis of its kind, including ground-based observations, satellite data, and model simulations, which reveals that the aerosol radiative forcing efficiency (ARFE) in the atmosphere is clearly high over the IGP and the Himalayan foothills (80-135 Wm-2 per unit aerosol optical depth (AOD)), with values being greater at higher elevations. AOD is >0.30 and single scattering albedo (SSA) is ∼0.90 throughout the year over this region. The mean ARFE is 2-4 times higher here than over other polluted sites in South and East Asia, owing to higher AOD and aerosol absorption (i.e., lower SSA). Further, the observed annual mean aerosol-induced atmospheric heating rates (0.5-0.8 Kelvin/day), which are significantly higher than previously reported values for the region, imply that the aerosols alone could account for >50 % of the total warming (aerosols + greenhouse gases) of the lower atmosphere and surface over this region. We demonstrate that the current state-of-the-art models used in climate assessments significantly underestimate aerosol-induced heating, efficiency and warming over the Hindu Kush - Himalaya - Tibetan Plateau (HKHTP) region, indicating a need for a more realistic representation of aerosol properties, especially of black carbon and other aerosols. The significant, regionally coherent aerosol-induced warming that we observe in the high altitudes of the region, is a significant factor contributing to increasing air temperature, observed accelerated retreat of the glaciers, and changes in the hydrological cycle and precipitation patterns over this region. Thus, aerosols are heating up the Himalayan climate, and will remain a key factor driving climate change over the region.

Erratum: Global Polarization of Ξ and Ω Hyperons in Au+Au Collisions at sqrt[s_{NN}]=200 GeV [Phys. Rev. Lett. 126, 162301 (2021)]

This corrects the article DOI: 10.1103/PhysRevLett.126.162301.

Integrating sex-bias into studies of archaic introgression on chromosome X

Evidence of interbreeding between archaic hominins and humans comes from methods that infer the locations of segments of archaic haplotypes, or 'archaic coverage' using the genomes of people living today. As more estimates of archaic coverage have emerged, it has become clear that most of this coverage is found on the autosomes- very little is retained on chromosome X. Here, we summarize published estimates of archaic coverage on autosomes and chromosome X from extant human samples. We find on average 7 times more archaic coverage on autosomes than chromosome X, and identify broad continental patterns in this ratio: greatest in European samples, and least in South Asian samples. We also perform extensive simulation studies to investigate how the amount of archaic coverage, lengths of coverage, and rates of purging of archaic coverage are affected by sex-bias caused by an unequal sex ratio within the archaic introgressors. Our results generally confirm that, with increasing male sex-bias, less archaic coverage is retained on chromosome X. Ours is the first study to explicitly model such sex-bias and its potential role in creating the dearth of archaic coverage on chromosome X.

Enabling interpretable machine learning for biological data with reliability scores

Machine learning tools have proven useful across biological disciplines, allowing researchers to draw conclusions from large datasets, and opening up new opportunities for interpreting complex and heterogeneous biological data. Alongside the rapid growth of machine learning, there have also been growing pains: some models that appear to perform well have later been revealed to rely on features of the data that are artifactual or biased; this feeds into the general criticism that machine learning models are designed to optimize model performance over the creation of new biological insights. A natural question arises: how do we develop machine learning models that are inherently interpretable or explainable? In this manuscript, we describe the SWIF(r) reliability score (SRS), a method building on the SWIF(r) generative framework that reflects the trustworthiness of the classification of a specific instance. The concept of the reliability score has the potential to generalize to other machine learning methods. We demonstrate the utility of the SRS when faced with common challenges in machine learning including: 1) an unknown class present in testing data that was not present in training data, 2) systemic mismatch between training and testing data, and 3) instances of testing data that have missing values for some attributes. We explore these applications of the SRS using a range of biological datasets, from agricultural data on seed morphology, to 22 quantitative traits in the UK Biobank, and population genetic simulations and 1000 Genomes Project data. With each of these examples, we demonstrate how the SRS can allow researchers to interrogate their data and training approach thoroughly, and to pair their domain-specific knowledge with powerful machine-learning frameworks. We also compare the SRS to related tools for outlier and novelty detection, and find that it has comparable performance, with the advantage of being able to operate when some data are missing. The SRS, and the broader discussion of interpretable scientific machine learning, will aid researchers in the biological machine learning space as they seek to harness the power of machine learning without sacrificing rigor and biological insight.

Insights into Changing Dermatophyte Spectrum in India Through Analysis of Cumulative 161,245 Cases Between 1939 and 2021

Dermatophytosis is one of the most common superficial infections of the skin affecting nearly one-fifth of the world population at any given time. With nearly 30% of worldwide terbinafine-resistance cases in Trichophyton mentagrophytes/Trichophyton interdigitale and Trichophyton rubrum reported from India in recent years, there is a significant burden of the emerging drug resistance epidemic on India. Here, we carry out a comprehensive retrospective analysis of dermatophytosis in India using 1038 research articles pertaining to 161,245 cases reported from 1939 to 2021. We find that dermatophytosis is prevalent in all parts of the country despite variable climatic conditions in different regions. Our results show T. rubrum as the most prevalent until 2015, with a sudden change in dermatophyte spectrum towards T. mentagrophytes/T. interdigitale complex since then. We also carried out an 18S rRNA-based phylogenetics and an average nucleotide identity-and single nucleotide polymorphism-based analysis of available whole genomes and find very high relatedness among the prevalent dermatophytes, suggesting geographic specificity. The comprehensive epidemiological and phylogenomics analysis of dermatophytosis in India over the last 80 years, presented here, would help in region-specific prevention, control and treatment of dermatophyte infections, especially considering the large number of emerging resistance cases.

The Extra-Islet Pancreas Supports Autoimmunity in Human Type 1 Diabetes

In autoimmune Type 1 diabetes (T1D), immune cells progressively infiltrate and destroy the islets of Langerhans - islands of endocrine tissue dispersed throughout the pancreas. However, it is unclear how this process, called 'insulitis', develops and progresses within this organ. Here, using highly multiplexed CO-Detection by indEXing (CODEX) tissue imaging and cadaveric pancreas samples from pre-T1D, T1D, and non-T1D donors, we examine pseudotemporal-spatial patterns of insulitis and exocrine inflammation within large pancreatic tissue sections. We identify four sub-states of insulitis characterized by CD8 ⁺ T cells at different stages of activation. We further find that exocrine compartments of pancreatic lobules affected by insulitis have distinct cellularity, suggesting that extra-islet factors may make particular lobules permissive to disease. Finally, we identify "staging areas" - immature tertiary lymphoid structures away from islets where CD8 ⁺ T cells appear to assemble before they navigate to islets. Together, these data implicate the extra-islet pancreas in autoimmune insulitis, greatly expanding the boundaries of T1D pathogenesis.

Radiative effects of absorbing aerosol types over South Asia

A comprehensive study on classifying the aerosol types and absorbing aerosol types, and quantifying the effect of absorbing aerosols on aerosol optical and radiative properties using four years (2015-2016, 2018-2019) of high-quality Aerosol Robotic Network (AERONET) datasets over Kanpur (urban) and Gandhi College (rural) in the Indo-Gangetic Plain (IGP) region is conducted on a seasonal scale, for the first time. Biomass burning (BB), urban-industrial, and mixed aerosol types are always present, whereas dust aerosol and mostly dust absorbing aerosol types are only present in pre-monsoon and monsoon seasons. During winter and post-monsoon seasons, BB aerosols and mostly black carbon (MBC) absorbing aerosols dominate, and the contribution of aerosol optical depth (AOD) and single scattering albedo (SSA) corresponding to MBC to total AOD and SSA are higher. SSA for MBC varies over a broader range due to mixing of BC with water-soluble aerosols. During pre-monsoon and monsoon seasons, mixing of dust with anthropogenic aerosols increases the amount of mixed aerosol type. Surface cooling and atmospheric heating efficiency for mixed aerosols are higher than MBC and dust aerosols due to enhancement in aerosol absorption over both locations. Seasonal analysis of aerosol radiative properties showed that during winter and post-monsoon, MBC absorbing aerosols are the major contributor in controlling/influencing the total aerosol radiative forcing (ARF) and heating rate (HR). During the other seasons, each absorbing aerosol type significantly influences ARF depending on their AOD and SSA values. In addition to Kanpur and Gandhi College, data from seven other AERONET sites located at Karachi, Lahore, Jaipur, Lumbini, Pokhara, Bhola, and Dhaka in South Asia are analysed to conduct a regional-scale examination of aerosol optical parameters and radiative effects due to different absorbing aerosol types. As the aerosol characteristics and trends are similar over these sites, the findings from such a regional-scale analysis can be an appropriate representative for the South Asian region. The regional analysis revealed that the annual mean atmospheric ARF (ARF_ATM) and ARF efficiency (ARFE_ATM), and HR are higher for MBC, followed by mixed and MD aerosols over South Asia due to higher AOD, and higher absorbing efficiency of MBC aerosols. In comparison, mixed aerosols exhibit higher ARF_ATM over East Asia. This quantification of absorbing aerosol types over a global aerosol hotspot will be useful for an accurate quantification of climate impacts of aerosols.

Black carbon flux in terrestrial and aquatic environments of Kodaikanal in the Western Ghats, South India: Estimation, source identification, and implication

Evolving Anthropocene epoch wields significant influence in altering atmospheric carbon, which affects the carbon cycle, leading to climate change. Understanding the carbon stock, fate, and transport across ecosystems are essential in determining India's carbon budget, hitherto, unavailable. In this study, we have analysed the stock, source, distribution, flux, and the relationship between terrestrial and aquatic black carbon over a high-altitude mountainous area in the Western Ghats region using the data collected from September 2019 to February 2021. Soil Organic Carbon (SOC) and Black Carbon (BC) are the highest in the forest region (SOC:23 ± 3 g of C/kg (dry weight (dw)), BC:6 ± 3 g/kg) and are the lowest in the urban region (SOC: 13 ± 2 g of C/kg (dw), BC:2 ± 1 g/kg). SOC is labile, whereas BC is non-labile. The BC/SOC ratio represents soil carbon lability. Topsoil BC/SOC ratios vary by land use and land cover, with urban areas having greater labile carbon pools than the forests. Dissolved BC (DBC) concentrations were most strongly correlated with bulk Dissolved Organic Carbon (DOC) concentrations in midstream (R = 0.6, p < 0.05), headwater streams (R = 0.3, p < 0.05) and to the soil bulk DBC (R = 0.3, p < 0.05), indicating the presence of transfer mechanism of soil to streams. The molecular associations revealed the presence of biolabile autochthonous compounds suggesting the crucial role land use and land cover play on watersheds. A positive relationship between DOC with seasonal hydrology and gradient significantly influences the DBC flux across regional streams. Intercomparison of observed terrestrial and aquatic carbon stocks with globally modelled data indicates an overestimation of regional-scale stock. These new findings have repercussions to policy framework on regional climate change. Further, the results suggest that a consistent quantification of BC and integration of regional, and global source-to-sink process are needed in order to understand and better quantify biogeochemical process cycles and associated climatic impacts.

Quantification of organic carbon and black carbon emissions, distribution, and carbon variation in diverse vegetative ecosystems across India

Black Carbon (BC) and Organic Carbon (OC) are the principal chemical aerosol components generated during combustion, both of which play a key role in air pollution, human health and climate change. Several studies of OC and BC have been conducted over India to assess the contribution from household and fossil fuel-based sources; however, studies on their emissions and their contribution from forest and cropland fires are quite limited. To address this issue, as part of this research, we derived a vegetation burning-based inventory of BC and OC aerosols over India at a resolution of 250 m × 250 m. Using a consumed biomass technique, we estimated emissions based on updated emission factor estimates. During the fire season in India (March-June), the mean OC and BC emissions were 2.1 ± 5.2 × 10¹³ kg per year and 1.8 ± 4.4 × 10¹² kg per year, respectively. Andhra Pradesh had the highest total carbonaceous aerosol emissions during the study period. Forest fires were prevalent in the northeastern states, while agricultural fires were prevalent in Gujarat, Chhattisgarh, Odisha, Madhya Pradesh, Bihar, Tripura, Uttar Pradesh, and Andhra Pradesh. The previous inventory, conducted at a coarser resolution (25 km × 25 km), overestimated open burning by 5 Mt. Our results were highly correlated with global bottom-up model values, especially the Fire Inventory (FINN). Our analysis showed that vegetative burning contributed 80.32% of the total carbon stock, with agricultural burning being the largest source of vegetative burning. Based on these findings, measures and strategies to control agricultural burning which would reduce significantly the total emissions of BC and OC with implications to improvement in air quality, human health and climate should be planned.

Genetic structure correlates with ethnolinguistic diversity in eastern and southern Africa

African populations are the most diverse in the world yet are sorely underrepresented in medical genetics research. Here, we examine the structure of African populations using genetic and comprehensive multi-generational ethnolinguistic data from the Neuropsychiatric Genetics of African Populations-Psychosis study (NeuroGAP-Psychosis) consisting of 900 individuals from Ethiopia, Kenya, South Africa, and Uganda. We find that self-reported language classifications meaningfully tag underlying genetic variation that would be missed with consideration of geography alone, highlighting the importance of culture in shaping genetic diversity. Leveraging our uniquely rich multi-generational ethnolinguistic metadata, we track language transmission through the pedigree, observing the disappearance of several languages in our cohort as well as notable shifts in frequency over three generations. We find suggestive evidence for the rate of language transmission in matrilineal groups having been higher than that for patrilineal ones. We highlight both the diversity of variation within Africa as well as how within-Africa variation can be informative for broader variant interpretation; many variants that are rare elsewhere are common in parts of Africa. The work presented here improves the understanding of the spectrum of genetic variation in African populations and highlights the enormous and complex genetic and ethnolinguistic diversity across Africa.

Trends in the types and absorption characteristics of ambient aerosols over the Indo-Gangetic Plain and North China Plain in last two decades

The sixth assessment report released by the Intergovernmental Panel on Climate Change (IPCC) in 2021 states that our inadequate understanding of magnitudes and trends of atmospheric aerosols, particularly over Asia, is a major source of uncertainty in climate change. In this study, the climatology and trends in different types of aerosols with focus on absorbing aerosols over Kanpur located in the Indo-Gangetic Plain (IGP) in South Asia and Beijing in the North China Plain (NCP) in East Asia are derived for the first time. We perform a first analysis of high-quality time series of columnar aerosols observations over a period of nearly two-decades, along with satellite observations to provide a broader regional perspective. The satellite retrieved aerosol Ångström exponent (AE) values have increased (10-20%) suggesting an increasing contribution of fine aerosols to aerosol optical depth (AOD) over Asia in last 2-decades. Among the three aerosol types [urban-industrial (UI), biomass burning (BB), and dust (DU)], only UI and BB aerosols are present over Kanpur throughout the year, while DU is present along with UI and BB aerosols only during pre-monsoon and monsoon. Overall, there is a positive trend in BB aerosols over both Kanpur and Beijing, a positive (negative) trend in UI aerosols over Kanpur (Beijing), and positive (negative) trend in dust over Beijing (Kanpur). However, only the positive trend in BB aerosol type over Kanpur is statistically significant. Further, among the three absorbing aerosol types [mostly black carbon (MBC), mostly dust (MDU), and mixed (MIX) containing BC and dust], only MBC and MIX are present in post-monsoon and winter over IGP, and MDU is present along with MBC and MIX only during pre-monsoon and monsoon, which is in agreement with aerosol types found. Trends in MBC, MIX and MDU over Kanpur in IGP and in MIX over Beijing are statistically significant. These trends are attributed mainly to the changes in anthropogenic aerosol emissions, and not to natural and climatic factors as their changes are relatively small. These findings on hitherto unavailable climatology and trends in aerosols and absorbing aerosols over two global aerosol hotspots and identified contrasts will be crucial in model simulations to better decipher the aerosol-climate interactions over Asia.

Uncertainty quantification in variable selection for genetic fine-mapping using bayesian neural networks

In this paper, we propose a new approach for variable selection using a collection of Bayesian neural networks with a focus on quantifying uncertainty over which variables are selected. Motivated by fine-mapping applications in statistical genetics, we refer to our framework as an "ensemble of single-effect neural networks" (ESNN) which generalizes the "sum of single effects" regression framework by both accounting for nonlinear structure in genotypic data (e.g., dominance effects) and having the capability to model discrete phenotypes (e.g., case-control studies). Through extensive simulations, we demonstrate our method's ability to produce calibrated posterior summaries such as credible sets and posterior inclusion probabilities, particularly for traits with genetic architectures that have significant proportions of non-additive variation driven by correlated variants. Lastly, we use real data to demonstrate that the ESNN framework improves upon the state of the art for identifying true effect variables underlying various complex traits.

New Constraint on the Local Relic Neutrino Background Overdensity with the First KATRIN Data Runs

We report on the direct search for cosmic relic neutrinos using data acquired during the first two science campaigns of the KATRIN experiment in 2019. Beta-decay electrons from a high-purity molecular tritium gas source are analyzed by a high-resolution MAC-E filter around the end point at 18.57 keV. The analysis is sensitive to a local relic neutrino overdensity ratio of η<9.7×10^{10}/α (1.1×10^{11}/α) at a 90% (95%) confidence level with α=1 (0.5) for Majorana (Dirac) neutrinos. A fit of the integrated electron spectrum over a narrow interval around the end point accounting for relic neutrino captures in the tritium source reveals no significant overdensity. This work improves the results obtained by the previous neutrino mass experiments at Los Alamos and Troitsk. We furthermore update the projected final sensitivity of the KATRIN experiment to η<1×10^{10}/α at 90% confidence level, by relying on updated operational conditions.

Human genetic admixture through the lens of population genomics

Over the past 50 years, geneticists have made great strides in understanding how our species' evolutionary history gave rise to current patterns of human genetic diversity classically summarized by Lewontin in his 1972 paper, ‘The Apportionment of Human Diversity’. One evolutionary process that requires special attention in both population genetics and statistical genetics is admixture: gene flow between two or more previously separated source populations to form a new admixed population. The admixture process introduces ancestry-based structure into patterns of genetic variation within and between populations, which in turn influences the inference of demographic histories, identification of genetic targets of selection and prediction of complex traits. In this review, we outline some challenges for admixture population genetics, including limitations of applying methods designed for populations without recent admixture to the study of admixed populations. We highlight recent studies and methodological advances that aim to overcome such challenges, leveraging genomic signatures of admixture that occurred in the past tens of generations to gain insights into human history, natural selection and complex trait architecture.

This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.

Assessment of the coronavirus disease 2019 (COVID-19) pandemic imposed lockdown and unlock effects on black carbon aerosol, its source apportionment, and aerosol radiative forcing over an urban city in India

A nationwide lockdown was imposed in India due to the Coronavirus Disease 2019 (COVID-19) pandemic which significantly reduced the anthropogenic emissions. We examined the characteristics of equivalent black carbon (eBC) mass concentration and its source apportionment using a multiwavelength aethalometer over an urban site (Ahmedabad) in India during the pandemic induced lockdown period of year 2020. For the first time, we estimate the changes in BC, its contribution from fossil (eBC ff ) and wood (eBC wf ) fuels during lockdown (LD) and unlock (UL) periods in 2020 with respect to 2017 to 2019 (normal period). The eBC mass concentration continuously decreased throughout lockdown periods (LD1 to LD4) due to enforced and stringent restrictions which substantially reduced the anthropogenic emissions. The eBC mass concentration increased gradually during unlock phases (UL1 to UL7) due to the phase wise relaxations after lockdown. During lockdown period eBC mass concentration decreased by 35%, whereas during the unlock period eBC decreased by 30% as compared to normal period. The eBC wf concentrations were higher by 40% during lockdown period than normal period due to significant increase in the biomass burning emissions from the several community kitchens which were operational in the city during the lockdown period. The average contributions of eBC ff and eBC wf to total eBC mass concentrations were 70% and 30% respectively during lockdown (LD1 to LD4) period, whereas these values were 87% and 13% respectively during the normal period. The reductions in BC concentrations were commensurate with the reductions in emissions from transportation and industrial activities. The aerosol radiative forcing reduced significantly due to the reduction in anthropogenic emissions associated with COVID-19 pandemic induced lockdown leading to a cooling of the atmosphere. The findings in the present study on eBC obtained during the unprecedented COVID-19 induced lockdown can provide a comprehensive understanding of the BC sources and current emission control strategies, and thus can serve as baseline anthropogenic emissions scenario for future emission control strategies aimed to improve air quality and climate.

Molecular Docking and Molecular Dynamic Studies, Synthesis, Characterisation of Thiazolidine-4-One Derivatives

Background: Antibacterial, antifungal, anticancer, antitubercular, anti-HIV, analgesic, anti-inflammatory, and ulcerogenic activities have all been documented for thiazolidine derivatives. Molecular docking has become a crucial step in the drug discovery process, with the goal of predicting the binding mechanism and affinity of the protein-ligand complex. AutoDock is a popular non-commercial docking tool that successfully docks ligands to their target proteins (accurate and computationally fast). The Discovery Studio Visualizer is a free viewer that may be used to open data produced by other Discovery Studio tools. Aim: The main aim of this study is: To study the molecular docking and molecular dynamic studies of the different thiazolidine derivatives. To synthesise the compound based on the results produced in the molecular dynamics and molecular studies. To Characterise the synthesised compounds using FTIR, 1H NMR, 13C NMR and Mass Spectral studies. Procedure: In two phases, a new series of Thiazolidine-4-one derivatives was created. The production of Schiff base is the first step, followed by the condensation of Schiff base with Chloro acetyl chloride and subsequent cyclisation steps. FTIR, 1H-NMR, 13C-NMR, and Mass Spectroscopy were used to characterise the chemical structures of the produced compounds. 1BVR protein that was taken from the protein database website The structures were drawn using Chem draw Ultra 8.0 and Biovia draw 2018. Using the Smiles Online Translator, it was stored in Mol format and then converted to PDB format. The Cygwin toolings were used to log all of the files. Conclusion: The conformation was computed using a ranking system. This indicates whether the molecule has strong ligand binding energy, hydrogen bonding, and hydrophobic interaction with the receptor. According to the findings, thiazolidine-4-one derivatives have antitubercular efficacy when used in conjunction with the Enoyl-acyl carrier protein (enoyl-ACP) reductase enzyme. For the docking analysis it indicates if the compound has strong ligand binding energy, hydrogen bonding, and hydrophobic binding with the receptor shows good activity. Using Auto dock 4.2 it was found out that among the above 20 compounds (including the control compound), C2, C5, C6, C8, C11. C13, C15 and C17 directly bind with the functional domain (Casein kinase II phosphorylation site) of the amino acid (252 to 255). The above compounds bind at the 252nd position of the Chain C, where Alanine is present (The target protein, 1BVR () contains ABCDEF chains).

Synthesis, Characterisation and Evaluation of Azetidine-2-One Derivative

Antibacterial, antifungal, anticancer, antitubercular, anti-HIV, analgesic, anti-inflammatory, and ulcerogenic activities have all been documented for azetidinone derivatives. The reaction of Schiff base((Z)-N (4-dimethylamino)benzylidene)pyrimidine-2-amine) with chloroacetyl chloride yielded a novel chemical called Azetdine-2-one derivative. Fourier Transform Infrared Spectroscopy and Proton Nuclear Magnetic Resonance Spectroscopy were used to confirm the chemical structures of the produced substances. The antimicrobial activity shows that the compound showed mild Antibacterial activity against Staphylococcus aureus and Escherichia coli.

Insights into recent aerosol trends over Asia from observations and CMIP6 simulations

Aerosols continue to contribute the largest uncertainty in climate change. Over Asia, a global aerosol hotspot, spatial patterns of aerosol emissions are changing mainly because of changes in anthropogenic emissions, producing a dipole in atmospheric aerosol loading between East (decrease in emissions) and South Asia (increase in emissions). The resultant aerosol radiative effects are expected to be different as compared to the last decades of the 20^th century because of this emerging Asian aerosol dipole. The projection and assessments of radiative and climate impacts of aerosols rely on simulating accurately the aerosol properties, thus, making it imperative that current climate models involved in climate assessments including the Intergovernmental Panel on Climate Change Assessment Reports, simulate well the magnitude and trends in changing aerosol properties. For the first time, in this study we analyze trends in aerosol properties over Asia from satellite and ground-based observations, and simulations from climate models in Coupled Model Intercomparison Project Phase 6 (CMIP6) experiment with state-of-the-art treatment of aerosol chemistry, physics and meteorology. The results reveal large inter-model differences in model estimates, and discrepancies between model simulations and observations as most models are not able to capture the recent observed magnitudes and trends in aerosol optical depth (AOD) and single scattering albedo (SSA) over Asia. The absolute and the relative (percent) trends (positive and/or negative) in AOD are significantly higher than the trends in SSA. The aerosol-induced effective radiative forcing within the atmosphere simulated with three CMIP6 models show a positive (increasing) trend over Asia. A positive trend in atmospheric heating due to aerosols in model simulations is consistent with model simulated trends in AOD (positive) and SSA (negative). These results on model-observations comparison need to be taken into account while examining the projected/expected future climate impacts due to aerosols, and potential value of various mitigation measures, in particular on regional and decadal climate change in Asia which is largely uncertain. MAIN FINDING: Our analysis of satellite and ground-based observations, and simulations from climate models in CMIP6 experiment with state-of-the-art treatment of aerosol chemistry, physics and meteorology reveal large difference in model calculations, and most models are not able to capture the recent observed trends in aerosol optical depth and single scattering albedo over Asia during 2000-2018.

Prevalence of forward neck posture and influence of smartphones in physiotherapy students

Introduction and Aim: InAsia, the prevalence of forward neck posture is 66%. Forward neck posture is the anterior positioning of cervical spine. This posture is sometimes called as “scholar’s neck. Forward neck posture can lead to musculoskeletal disorders such as injuries in muscles, tendons, and peripheral vessels, vascular vessels caused by repetitive or continuous use of certain body part. In forward neck posture, the sternocleidomastoid muscle and trapezius are largely responsible for turning and nodding the head. When the head moves front, the spine follows, pulling the shoulder blades forward as well.They make contact with the upper ribs and begin to drag it forward with them.Therefore, this study aims to quantify forward neck posture in prolonged smart phone users.   Methodology:An observational study was done in smartphone using student population comparing the control group students with forward neck posture studentsfor the duration of 3weeks. This study has included 100 students with forward neck posturewho were recruited fromDr. MGR Educational & Research Institute. Goniometer, Craniovertebral angle and Plumb line were used as the outcome measure.   Results:The findings of this research exhibit there is a statistically significant changes inforward neck posture studentscompared with control group and the mean difference is 14.97 in two groups students.   Conclusion:The present study concluded that 3 weeks after assessing the students. Forward neck posture students found to have decreased craniovertebral angle and range of motion compared to normal neck posture students and also found that forward neck posture students spent 5-6 hours using smart phones per day.

Observation of D_{s}^{±}/D^{0} Enhancement in Au+Au Collisions at sqrt[s_{NN}]=200 GeV

We report on the first measurement of charm-strange meson D_{s}^{±} production at midrapidity in Au+Au collisions at sqrt[s_{NN}]=200  GeV from the STAR experiment. The yield ratio between strange (D_{s}^{±}) and nonstrange (D^{0}) open-charm mesons is presented and compared to model calculations. A significant enhancement, relative to a pythia simulation of p+p collisions, is observed in the D_{s}^{±}/D^{0} yield ratio in Au+Au collisions over a large range of collision centralities. Model calculations incorporating abundant strange-quark production in the quark-gluon plasma and coalescence hadronization qualitatively reproduce the data. The transverse-momentum integrated yield ratio of D_{s}^{±}/D^{0} at midrapidity is consistent with a prediction from a statistical hadronization model with the parameters constrained by the yields of light and strange hadrons measured at the same collision energy. These results suggest that the coalescence of charm quarks with strange quarks in the quark-gluon plasma plays an important role in D_{s}^{±}-meson production in heavy-ion collisions.

Multi-scale inference of genetic trait architecture using biologically annotated neural networks

In this article, we present Biologically Annotated Neural Networks (BANNs), a nonlinear probabilistic framework for association mapping in genome-wide association (GWA) studies. BANNs are feedforward models with partially connected architectures that are based on biological annotations. This setup yields a fully interpretable neural network where the input layer encodes SNP-level effects, and the hidden layer models the aggregated effects among SNP-sets. We treat the weights and connections of the network as random variables with prior distributions that reflect how genetic effects manifest at different genomic scales. The BANNs software uses variational inference to provide posterior summaries which allow researchers to simultaneously perform (i) mapping with SNPs and (ii) enrichment analyses with SNP-sets on complex traits. Through simulations, we show that our method improves upon state-of-the-art association mapping and enrichment approaches across a wide range of genetic architectures. We then further illustrate the benefits of BANNs by analyzing real GWA data assayed in approximately 2,000 heterogenous stock of mice from the Wellcome Trust Centre for Human Genetics and approximately 7,000 individuals from the Framingham Heart Study. Lastly, using a random subset of individuals of European ancestry from the UK Biobank, we show that BANNs is able to replicate known associations in high and low-density lipoprotein cholesterol content.

Measurement of e^{+}e^{-} Momentum and Angular Distributions from Linearly Polarized Photon Collisions

The Breit-Wheeler process which produces matter and antimatter from photon collisions is experimentally investigated through the observation of 6085 exclusive electron-positron pairs in ultraperipheral Au+Au collisions at sqrt[s_{NN}]=200  GeV. The measurements reveal a large fourth-order angular modulation of cos4Δϕ=(16.8±2.5)% and smooth invariant mass distribution absent of vector mesons (ϕ, ω, and ρ) at the experimental limit of ≤0.2% of the observed yields. The differential cross section as a function of e^{+}e^{-} pair transverse momentum P_{⊥} peaks at low value with sqrt[⟨P_{⊥}^{2}⟩]=38.1±0.9  MeV and displays a significant centrality dependence. These features are consistent with QED calculations for the collision of linearly polarized photons quantized from the extremely strong electromagnetic fields generated by the highly charged Au nuclei at ultrarelativistic speed. The experimental results have implications for vacuum birefringence and for mapping the magnetic field which is important for emergent QCD phenomena.

Converting noise into solitons: optical self-organization through intermodal nonlinearity

We experimentally demonstrate a pump-pulse-induced conversion of noise into solitons in multimode optical fibers. The process is based on the recently discovered phenomenon of soliton self-mode conversion, where a pump soliton in a higher-order spatial mode crafts another well-defined soliton, originating purely from noise, in a lower-order mode at a longer wavelength through intermodal Raman scattering. The lack of the need for any seed or cavity feedback demonstrates that soliton self-mode conversion is a fundamentally unavoidable, but nevertheless tailorable and hence useful, self-organizing nonlinear optical effect capable of turning noise into transform limited solitons.

Global Polarization of Ξ and Ω Hyperons in Au+Au Collisions at sqrt[s_{NN}]=200 GeV

Global polarization of Ξ and Ω hyperons has been measured for the first time in Au+Au collisions at sqrt[s_{NN}]=200  GeV. The measurements of the Ξ^{-} and Ξ[over ¯]^{+} hyperon polarization have been performed by two independent methods, via analysis of the angular distribution of the daughter particles in the parity violating weak decay Ξ→Λ+π, as well as by measuring the polarization of the daughter Λ hyperon, polarized via polarization transfer from its parent. The polarization, obtained by combining the results from the two methods and averaged over Ξ^{-} and Ξ[over ¯]^{+}, is measured to be ⟨P_{Ξ}⟩=0.47±0.10(stat)±0.23(syst)% for the collision centrality 20%-80%. The ⟨P_{Ξ}⟩ is found to be slightly larger than the inclusive Λ polarization and in reasonable agreement with a multiphase transport model. The ⟨P_{Ξ}⟩ is found to follow the centrality dependence of the vorticity predicted in the model, increasing toward more peripheral collisions. The global polarization of Ω, ⟨P_{Ω}⟩=1.11±0.87(stat)±1.97(syst)% was obtained by measuring the polarization of daughter Λ in the decay Ω→Λ+K, assuming the polarization transfer factor C_{ΩΛ}=1.

Measurement of the Positive Muon Anomalous Magnetic Moment to 0.46 ppm

We present the first results of the Fermilab National Accelerator Laboratory (FNAL) Muon g-2 Experiment for the positive muon magnetic anomaly a_{μ}≡(g_{μ}-2)/2. The anomaly is determined from the precision measurements of two angular frequencies. Intensity variation of high-energy positrons from muon decays directly encodes the difference frequency ω_{a} between the spin-precession and cyclotron frequencies for polarized muons in a magnetic storage ring. The storage ring magnetic field is measured using nuclear magnetic resonance probes calibrated in terms of the equivalent proton spin precession frequency ω[over ˜]_{p}^{'} in a spherical water sample at 34.7 °C. The ratio ω_{a}/ω[over ˜]_{p}^{'}, together with known fundamental constants, determines a_{μ}(FNAL)=116 592 040(54)×10^{-11} (0.46 ppm). The result is 3.3 standard deviations greater than the standard model prediction and is in excellent agreement with the previous Brookhaven National Laboratory (BNL) E821 measurement. After combination with previous measurements of both μ^{+} and μ^{-}, the new experimental average of a_{μ}(Exp)=116 592 061(41)×10^{-11} (0.35 ppm) increases the tension between experiment and theory to 4.2 standard deviations.

Natural variation in the regulation of neurodevelopmental genes modifies flight performance in Drosophila

The winged insects of the order Diptera are colloquially named for their most recognizable phenotype: flight. These insects rely on flight for a number of important life history traits, such as dispersal, foraging, and courtship. Despite the importance of flight, relatively little is known about the genetic architecture of flight performance. Accordingly, we sought to uncover the genetic modifiers of flight using a measure of flies’ reaction and response to an abrupt drop in a vertical flight column. We conducted a genome wide association study (GWAS) using 197 of the Drosophila Genetic Reference Panel (DGRP) lines, and identified a combination of additive and marginal variants, epistatic interactions, whole genes, and enrichment across interaction networks. Egfr, a highly pleiotropic developmental gene, was among the most significant additive variants identified. We functionally validated 13 of the additive candidate genes’ (Adgf-A/Adgf-A2/CG32181, bru1, CadN, flapper (CG11073), CG15236, flippy (CG9766), CREG, Dscam4, form3, fry, Lasp/CG9692, Pde6, Snoo), and introduce a novel approach to whole gene significance screens: PEGASUS_flies. Additionally, we identified ppk23, an Acid Sensing Ion Channel (ASIC) homolog, as an important hub for epistatic interactions. We propose a model that suggests genetic modifiers of wing and muscle morphology, nervous system development and function, BMP signaling, sexually dimorphic neural wiring, and gene regulation are all important for the observed differences flight performance in a natural population. Additionally, these results represent a snapshot of the genetic modifiers affecting drop-response flight performance in Drosophila, with implications for other insects.

Insect flight is a widely recognizable phenotype of many winged insects, hence the name: flies. While fruit flies, or Drosophila melanogaster, are a genetically tractable model, flight performance is a highly integrative phenotype, and therefore challenging to identify comprehensively which genetic modifiers contribute to its genetic architecture. Accordingly, we screened 197 Drosophila Genetic Reference Panel lines for their ability to react and respond to an abrupt drop. Using several computational approaches, we identified additive, marginal, and epistatic variants, as well as whole genes and altered sub-networks of gene-gene and protein-protein interaction networks that contribute to variation in flight performance. More generally, we demonstrate the benefits of employing multiple methodologies to elucidate the genetic architecture of complex traits. Many variants and genes mapped to regions of the genome that affect neurodevelopment, wing and muscle development, and regulation of gene expression. We also introduce PEGASUS_flies, a Drosophila-adapted version of the PEGASUS platform first used in human studies, to infer gene-level significance of association based on the gene’s distribution of individual variant P-values. Our results contribute to the debate over the relative importance of individual, additive factors and epistatic, or higher order, interactions, in the mapping of genotype to phenotype.

Nonmonotonic Energy Dependence of Net-Proton Number Fluctuations

Nonmonotonic variation with collision energy (sqrt[s_{NN}]) of the moments of the net-baryon number distribution in heavy-ion collisions, related to the correlation length and the susceptibilities of the system, is suggested as a signature for the quantum chromodynamics critical point. We report the first evidence of a nonmonotonic variation in the kurtosis times variance of the net-proton number (proxy for net-baryon number) distribution as a function of sqrt[s_{NN}] with 3.1  σ significance for head-on (central) gold-on-gold (Au+Au) collisions measured solenoidal tracker at Relativistic Heavy Ion Collider. Data in noncentral Au+Au collisions and models of heavy-ion collisions without a critical point show a monotonic variation as a function of sqrt[s_{NN}].

Improved multiplex TaqMan qPCR assay with universal internal control offers reliable and accurate detection of Clavibacter michiganensis

AIM

Clavibacter michiganensis (Cm) is a seed-borne plant pathogen that significantly reduces tomato production worldwide. Due to repeated outbreaks and rapid spread of the disease, seeds/transplants need to be certified free of the pathogen before planting. To this end, we developed a multiplex TaqMan qPCR assay that can accurately detect Cm in infected samples.

METHODS AND RESULTS

A specific region of Cm (clvG gene) was selected for primer design using comparative genomics approach. A fully synthetic universal internal control (UIC) was also designed to detect PCR inhibitors and false-negative results in qPCRs. The Cm primers can be used alone or in a triplex TaqMan qPCR assay with UIC and previously described Clavibacter primers. The assay was specific for Cm and detected up to 10 fg of Cm DNA in sensitivity and spiked assays. Addition of the UIC did not change the specificity or sensitivity of the multiplex TaqMan qPCR assay.

CONCLUSION

The triplex TaqMan qPCR provides a specific and sensitive diagnostic assay for Cm.

SIGNIFICANCE AND IMPACT OF THE STUDY

This assay can be used for biosecurity surveillance, routine diagnostics, estimating bacterial titres in infected material and for epidemiological studies. The UIC is fully synthetic, efficiently amplified and multiplex compatible with any other qPCR assay.

Aerosol-induced atmospheric heating rate decreases over South and East Asia as a result of changing content and composition

Aerosol emissions from human activities are extensive and changing rapidly over Asia. Model simulations and satellite observations indicate a dipole pattern in aerosol emissions and loading between South Asia and East Asia, two of the most heavily polluted regions of the world. We examine the previously unexplored diverging trends in the existing dipole pattern of aerosols between East and South Asia using the high quality, two-decade long ground-based time series of observations of aerosol properties from the Aerosol Robotic Network (AERONET), from satellites (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)), and from model simulations (Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The data cover the period since 2001 for Kanpur (South Asia) and Beijing (East Asia), two locations taken as being broadly representative of the respective regions. Since 2010 a dipole in aerosol optical depth (AOD) is maintained, but the trend is reversed—the decrease in AOD over Beijing (East Asia) is rapid since 2010, being 17% less in current decade compared to first decade of twenty-first century, while the AOD over South Asia increased by 12% during the same period. Furthermore, we find that the aerosol composition is also changing over time. The single scattering albedo (SSA), a measure of aerosol’s absorption capacity and related to aerosol composition, is slightly higher over Beijing than Kanpur, and has increased from 0.91 in 2002 to 0.93 in 2017 over Beijing and from 0.89 to 0.92 during the same period over Kanpur, confirming that aerosols in this region have on an average become more scattering in nature. These changes have led to a notable decrease in aerosol-induced atmospheric heating rate (HR) over both regions between the two decades, decreasing considerably more over East Asia (− 31%) than over South Asia (− 9%). The annual mean HR is lower now, it is still large (≥ 0.6 K per day), which has significant climate implications. The seasonal trends in AOD, SSA and HR are more pronounced than their respective annual trends over both regions. The seasonal trends are caused mainly by the increase/decrease in anthropogenic aerosol emissions (sulfate, black carbon and organic carbon) while the natural aerosols (dust and sea salt) did not change significantly over South and East Asia during the last two decades. The MERRA-2 model is able to simulate the observed trends in AODs well but not the magnitude, while it also did not simulate the SSA values or trends well. These robust findings based on observations of key aerosol parameters and previously unrecognized diverging trends over South and East Asia need to be accounted for in current state-of-the-art climate models to ensure accurate quantification of the complex and evolving impact of aerosols on the regional climate over Asia.

Fragility of a soliton's shot-to-shot coherence

We show that a soliton in a high-order spatial mode of a multi-mode fiber can completely lose its shot-to-shot coherence due to a noise seed with energy orders of magnitude below that of the soliton. The total degradation of shot-to-shot coherence is caused by a very strong recently demonstrated intermodal nonlinear effect, soliton self-mode conversion. The results indicate that the robustness of solitons against perturbations is not entirely applicable in the presence of intermodal nonlinearities, and, more generally, that certain single-mode results cannot be trivially extrapolated to multi-mode fibers.

Inter-annual and seasonal variations in columnar aerosol characteristics and radiative effects over the Pokhara Valley in the Himalayan foothills - Composition, radiative forcing, and atmospheric heating

This study reports comprehensive analysis of seasonal and inter-annual variations of aerosol properties (optical, physical and chemical) and radiative effects over Pokhara Valley in the foothills of central Himalayas in Nepal utilizing the high-quality multi-year columnar aerosol data observed recently from January 2010 to December 2017. This paper focusses on the seasonal and inter-annual variations of chemical (composition), and absorption properties of aerosols and their radiative effects. The single scattering albedo (SSA) either decreases as a function of wavelength or remains independent of wavelength. The seasonal mean aerosol absorption optical depth (AAOD) exhibits a behavior opposite to that of SSA. Carbonaceous aerosols (CA) dominate (≥60%) aerosol absorption during the whole year. Black carbon (BC) alone contributes >60% to AAOD_CA while brown carbon (BrC) shares the rest. The absorbing aerosol types are determined to be BC, and mixed (BC and dust) only. Dust as absorbing aerosol type is absent over the Himalayan foothills. The ARF_SFC is ≥ -50 Wm^-2 except in monsoon almost every year. The ARF_ATM is ≥ 50 Wm^-2 during winter and pre-monsoon in all the years. ARFE_SFC, ARFE_TOA and ARFE_ATM follow a similar pattern as that of ARF. High values of ARFE at SFC, TOA and ATM (except during monsoon when values are slightly lower) suggest that aerosols are efficient in significantly modulating the incoming solar flux throughout the year. The annual average aerosol-induced atmospheric heating rate (HR) over Pokhara is nearly 1 K day^-1 every year during 8-year observation, and is highest in 2015 (∼2.5 K day^-1). The HR is about 1 K day^-1 or more over all the locations in IGP during the year. These quantitative results can be used as inputs in global/regional climate models to assess the climate impact of aerosols, including on regional temperature, hydrological cycle and melting of glaciers and snowfields in the region.

Black carbon dominates the aerosol absorption over the Indo-Gangetic Plain and the Himalayan foothills

This study, based on new and high quality in situ observations, quantifies for the first time, the individual contributions of light-absorbing aerosols (black carbon (BC), brown carbon (BrC) and dust) to aerosol absorption over the Indo-Gangetic Plain (IGP) and the Himalayan foothill region, a relatively poorly studied region with several sensitive ecosystems of global importance, as well as highly vulnerable populations. The annual and seasonal average single scattering albedo (SSA) over Kathmandu is the lowest of all the locations. The SSA over Kathmandu is < 0.89 during all seasons, which confirms the dominance of light-absorbing carbonaceous aerosols from local and regional sources over Kathmandu. It is observed here that the SSA decreases with increasing elevation, confirming the dominance of light absorbing carbonaceous aerosols at higher elevations. In contrast, the SSA over the IGP does not exhibit a pronounced spatial variation. BC dominates (≥75%) the aerosol absorption over the IGP and the Himalayan foothills throughout the year. Higher BC concentration at elevated locations in the Himalayas leads to lower SSA at elevated locations in the Himalayas. The contribution of dust to aerosol absorption is higher throughout the year over the IGP than over the Himalayan foothills. The aerosol absorption over South Asia is very high, exceeding available observations over East Asia, and also exceeds previous model estimates. This quantification will be valuable as observational constraints to help improve regional simulations of climate change, impacts on the glaciers and the hydrological cycle, and will help to direct the focus towards BC as the main contributor to aerosol-induced warming in the region.

Circulation of Asian-I and Cosmopolitan genotypes of Dengue-2 virus in northeast India, 2016-2017

BACKGROUND & OBJECTIVES

Dengue is a major public health problem in northeast India where the majority of the cases go unreported and undiagnosed. Even though all four dengue serotypes are reported, there is a dearth of information on genetic diversity. The present cross-sectional study was undertaken during 2016-17 to determine the genetic variance of dengue virus serotype 2 (DENV-2) based on the envelope (E) glycoprotein gene.

METHODS

The serum samples collected from the northeast parts of India, as a part of hospital-based acute febrile illness surveillance, were serotyped. Viral RNA was extracted from DENV-2 serum samples using QIAquick® RNA Extraction Kit. The E gene was amplified by conventional reverse-transcriptase polymerase chain reaction (RT-PCR) and the PCR products were sequenced.

RESULTS

The E glycoprotein gene of nine serum samples with high viral RNA concentration (Ct <25) was sequenced. The E gene sequences of eight DENV-2 strains from Assam and Meghalaya aligned with genotype IV (Cosmopolitan) and one strain from Tripura segregated with Asian-I genotype.

INTERPRETATION & CONCLUSION

Ongoing laboratory-based surveillance is mandatory to understand the transmission dynamics of dengue in endemic countries. This study concluded that in northeast India, presently two distinct genotypes of DENV-2, namely genotype IVb (Cosmopolitan) and Asian-I genotype are in circulation.

Estimation of non-null SNP effect size distributions enables the detection of enriched genes underlying complex traits

Traditional univariate genome-wide association studies generate false positives and negatives due to difficulties distinguishing associated variants from variants with spurious nonzero effects that do not directly influence the trait. Recent efforts have been directed at identifying genes or signaling pathways enriched for mutations in quantitative traits or case-control studies, but these can be computationally costly and hampered by strict model assumptions. Here, we present gene-ε, a new approach for identifying statistical associations between sets of variants and quantitative traits. Our key insight is that enrichment studies on the gene-level are improved when we reformulate the genome-wide SNP-level null hypothesis to identify spurious small-to-intermediate SNP effects and classify them as non-causal. gene-ε efficiently identifies enriched genes under a variety of simulated genetic architectures, achieving greater than a 90% true positive rate at 1% false positive rate for polygenic traits. Lastly, we apply gene-ε to summary statistics derived from six quantitative traits using European-ancestry individuals in the UK Biobank, and identify enriched genes that are in biologically relevant pathways.

A junior doctor's experience of critical illness: from treating patients to becoming a patient with COVID-19

When the coronavirus disease 2019 (COVID‐19) pandemic was declared, it was clear that severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) would have far‐reaching impacts on medicine, society and everyday life. As a junior doctor working closely with patients with SARS‐CoV‐2 infection, I was aware of my personal risk of exposure to the virus. I assumed that as a fit and well 26‐year‐old with no comorbidities, if I were to become infected, it was unlikely that COVID‐19 would be severe. However, I became critically unwell following a week of clinical work, necessitating hospital admission, tracheal intubation and mechanical ventilation. I remained mechanically ventilated for 6 days and was then transferred to a medical ward 2 days later. After two further days of rehabilitation, I was discharged home. This reflection is not a junior doctor’s view of how COVID‐19 was managed by the NHS, but a personal view of my illness from ‘the other side of the curtain’. My reflections focus upon the psychological aspects of my experiences, exploring the memories that I formed around the time of critical care, how the fears that I possessed were managed with exceptional communication, and the importance of the wider healthcare team in my recovery.

Detecting Shared Genetic Architecture Among Multiple Phenotypes by Hierarchical Clustering of Gene-Level Association Statistics

Emerging large-scale biobanks pairing genotype data with phenotype data present new opportunities to prioritize shared genetic associations across multiple phenotypes for molecular validation. Past research, by our group and others, has shown gene-level tests of association produce biologically interpretable characterization of the genetic architecture of a given phenotype. Here, we present a new method, Ward clustering to identify Internal Node branch length outliers using Gene Scores (WINGS), for identifying shared genetic architecture among multiple phenotypes. The objective of WINGS is to identify groups of phenotypes, or "clusters," sharing a core set of genes enriched for mutations in cases. We validate WINGS using extensive simulation studies and then combine gene-level association tests with WINGS to identify shared genetic architecture among 81 case-control and seven quantitative phenotypes in 349,468 European-ancestry individuals from the UK Biobank. We identify eight prioritized phenotype clusters and recover multiple published gene-level associations within prioritized clusters.

First Measurement of Λ_{c} Baryon Production in Au+Au Collisions at sqrt[s_{NN}]=200 GeV

We report on the first measurement of the charmed baryon Λ_{c}^{±} production at midrapidity (|y|<1) in Au+Au collisions at sqrt[s_{NN}]=200  GeV collected by the STAR experiment at the Relativistic Heavy Ion Collider. The Λ_{c}/D^{0} [denoting (Λ_{c}^{+}+Λ_{c}^{-})/(D^{0}+D[over ¯]^{0})] yield ratio is measured to be 1.08±0.16  (stat)±0.26  (sys) in the 0%-20% most central Au+Au collisions for the transverse momentum (p_{T}) range 3<p_{T}<6  GeV/c. This is significantly larger than the pythia model calculations for p+p collisions. The measured Λ_{c}/D^{0} ratio, as a function of p_{T} and collision centrality, is comparable to the baryon-to-meson ratios for light and strange hadrons in Au+Au collisions. Model calculations including coalescence hadronization for charmed baryon and meson formation reproduce the features of our measured Λ_{c}/D^{0} ratio.

Rapid Synthesis and Characterization of Pure and Cobalt Doped Zinc Aluminate Nanoparticles via Microwave Assisted Combustion Method

Zn_1-xCo_xAl₂O₄ (0 ≤ x ≤ 0.5) nanoparticles were synthesized employing L-alanine as fuel using MACT (microwave assisted combustion technique). The synthesized samples were characterized following methods such as X-ray Diffraction, high resolution scanning electron microscopy, Energydispersive X-ray spectroscopy; UV-visible diffused reflectance spectroscopy, FT-IR and VSM. The XRD confirmed the cubic spinel structure and the average crystallite size observed lying in the range of 12-19 nm deduced using the Debye Scherrer's equation. The morphology of the Zn_1-xCo_xAl₂O₄ (0 ≤ x ≤ 0.5) nanoparticles is observed using HR-SEM. EDX analysis is opted for the elemental mapping of pure and cobalt doped zinc aluminate nanoparticles. Further band gap value was calculated using Kubelka Munk function, which was seen lying within 3.73 to 5.45 eV. The strong absorption band at 669, 556 and 500 cm^-1 was associated with the vibrations of Zn-O, Al-O and Zn-O-Al of zinc aluminate nanoparticles. The hysteresis loops exhibited conversion from diamagnetic into super paramagnetic behaviour with increase in Co doping.