bluuebunny/crossref_metadata_2025_split huggingface dataset:
Towards implementing artificial intelligence post-processing in weather and climate: proposed actions from the Oxford 2019 workshop
Authors: Haupt Sue Ellen , Chapman William , Adams Samantha V. , Kirkwood Charlie , Hosking J. Scott , Robinson Niall H. , Lerch Sebastian , Subramanian Aneesh C. 
Published: February 2021

The most mature aspect of applying artificial intelligence (AI)/machine learning (ML) to problems in the atmospheric sciences is likely post-processing of model output. This article provides some history and current state of the science of post-processing with AI for weather and climate models. Deriving from the discussion at the 2019 Oxford workshop on Machine Learning for Weather and Climate, this paper also presents thoughts on medium-term goals to advance such use of AI, which include assuring that algorithms are trustworthy and interpretable, adherence to FAIR data practices to promote usability, and development of techniques that leverage our physical knowledge of the atmosphere. The coauthors propose several actionable items and have initiated one of those: a repository for datasets from various real weather and climate problems that can be addressed using AI. Five such datasets are presented and permanently archived, together with Jupyter notebooks to process them and assess the results in comparison with a baseline technique. The coauthors invite the readers to test their own algorithms in comparison with the baseline and to archive their results.This article is part of the theme issue ‘Machine learning for weather and climate modelling’.
Domain-driven models yield better predictions at lower cost than reservoir computers in Lorenz systems
Authors: Pyle Ryan , Jovanovic Nikola , Subramanian Devika , Palem Krishna V. , Patel Ankit B. 
Published: February 2021

Recent advances in computing algorithms and hardware have rekindled interest in developing high-accuracy, low-costsurrogatemodels for simulating physical systems. The idea is to replace expensive numerical integration of complex coupled partial differential equations at fine time scales performed on supercomputers, with machine-learned surrogates that efficiently and accurately forecast future system states using data sampled from the underlying system. One particularly popular technique being explored within the weather and climate modelling community is theecho state network(ESN), an attractive alternative to other well-known deep learning architectures. Using the classical Lorenz 63 system, and the three tier multi-scale Lorenz 96 system (Thornes T, Duben P, Palmer T. 2017Q. J. R. Meteorol. Soc.143, 897–908. (doi:10.1002/qj.2974)) as benchmarks, we realize that previously studied state-of-the-art ESNs operate in two distinct regimes, corresponding to low and high spectral radius (LSR/HSR) for the sparse, randomly generated, reservoir recurrence matrix. Using knowledge of the mathematical structure of the Lorenz systems along with systematic ablation and hyperparameter sensitivity analyses, we show that state-of-the-art LSR-ESNs reduce to a polynomial regression model which we call Domain-Driven Regularized Regression (D2R2). Interestingly, D2R2 is a generalization of the well-known SINDy algorithm (Brunton SL, Proctor JL, Kutz JN. 2016Proc. Natl Acad. Sci. USA113, 3932–3937. (doi:10.1073/pnas.1517384113)). We also show experimentally that LSR-ESNs (Chattopadhyay A, Hassanzadeh P, Subramanian D. 2019 (http://arxiv.org/abs/1906.08829)) outperform HSR ESNs (Pathak J, Hunt B, Girvan M, Lu Z, Ott E. 2018Phys. Rev. Lett.120, 024102. (doi:10.1103/PhysRevLett.120.024102)) while D2R2 dominates both approaches. A significant goal in constructing surrogates is to cope with barriers to scaling in weather prediction and simulation of dynamical systems that are imposed by time and energy consumption in supercomputers.Inexact computinghas emerged as a novel approach to helping with scaling. In this paper, we evaluate the performance of three models (LSR-ESN, HSR-ESN and D2R2) by varying the precision or word size of the computation as our inexactness-controlling parameter. For precisions of 64, 32 and 16 bits, we show that, surprisingly, the least expensive D2R2 method yields the most robust results and the greatest savings compared to ESNs. Specifically, D2R2 achieves 68 × in computational savings, with an additional 2 × if precision reductions are also employed, outperforming ESN variants by a large margin.This article is part of the theme issue ‘Machine learning for weather and climate modelling’.
The genetic code is not optimized for resource conservation
Authors: Xu Haiqing , Zhang Jianzhi 
Published: February 2021

AbstractShenhav and Zeevi conclude in a recent article (Science370:683-687) that the universal genetic code (UGC) is optimized for resource conservation because mutations are less likely to increase proteomic nitrogen and carbon uses under the UGC than under random genetic codes (RGCs). Their finding results from miscalculating mutational effects and benchmarking against biased RGCs. Our reanalysis refutes their conclusion.
Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19
Authors: Feyaerts Dorien , Hédou Julien , Gillard Joshua , Chen Han , Tsai Eileen S. , Peterson Laura S. , Ando Kazuo , Manohar Monali , Do Evan , Dhondalay Gopal K.R. , Fitzpatrick Jessica , Artandi Maja , Chang Iris , Snow Theo T. , Chinthrajah R. Sharon , Warren Christopher M. , Wittman Rich , Meyerowitz Justin G. , Ganio Edward A. , Stelzer Ina A. , Han Xiaoyuan , Verdonk Franck , Gaudillière Dyani K. , Mukherjee Nilanjan , Tsai Amy S. , Rumer Kristen K. , Jiang Sizun , Ferrer Sergio Iván Valdés , Kelly J. Daniel , Furman David , Aghaeepour Nima , Angst Martin S. , Boyd Scott D. , Pinsky Benjamin A. , Nolan Garry P. , Nadeau Kari C. , Gaudillière Brice , McIlwain David R. 
Published: February 2021

AbstractThe biological determinants of the wide spectrum of COVID-19 clinical manifestations are not fully understood. Here, over 1400 plasma proteins and 2600 single-cell immune features comprising cell phenotype, basal signaling activity, and signaling responses to inflammatory ligands were assessed in peripheral blood from patients with mild, moderate, and severe COVID-19, at the time of diagnosis. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identified and independently validated a multivariate model classifying COVID-19 severity (multi-class AUCtraining= 0.799, p-value = 4.2e-6; multi-class AUCvalidation= 0.773, p-value = 7.7e-6). Features of this high-dimensional model recapitulated recent COVID-19 related observations of immune perturbations, and revealed novel biological signatures of severity, including the mobilization of elements of the renin-angiotensin system and primary hemostasis, as well as dysregulation of JAK/STAT, MAPK/mTOR, and NF-κB immune signaling networks. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for the prevention of COVID-19 progression.SummaryFeyaerts et al. demonstrate that an integrated analysis of plasma and single-cell proteomics differentiates COVID-19 severity and reveals severity-specific biological signatures associated with the dysregulation of the JAK/STAT, MAPK/mTOR, and NF-κB immune signaling networks and the mobilization of the renin-angiotensin and hemostasis systems.
An analysis of school absences in England during the Covid-19 pandemic
Authors: Southall Emma , Holmes Alex , Hill Edward M. , Atkins Benjamin D. , Leng Trystan , Thompson Robin N. , Dyson Louise , Keeling Matt J. , Tildesley Michael J. 
Published: February 2021

AbstractThe introduction of SARS-CoV-2, the virus that causes COVID-19 infection, in the UK in early 2020, resulted in the UK government introducing several control policies in order to reduce the spread of disease. As part of these restrictions, schools were closed to all pupils in March (except for vulnerable and key worker children), before re-opening to certain year groups in June. Finally all school children returned to the classroom in September. In this paper, we analyse the data on school absences from September 2020 to December 2020 as a result of COVID-19 infection and how that varied through time as other measures in the community were introduced. We utilise data from the Educational Settings database compiled by the Department for Education and examine how pupil and teacher absences change in both primary and secondary schools.Our results show that absences as a result of COVID-19 infection rose steadily following the re-opening of schools in September. Cases in teachers were seen to decline during the November lockdown, particularly in those regions that had previously been in tier 3, the highest level of control at the time. Cases in secondary school pupils increased for the first two weeks of the November lockdown, before decreasing. Since the introduction of the tier system, the number of absences owing to confirmed infection in primary schools was observed to be significantly lower than in secondary schools across all regions and tiers.In December, we observed a large rise in the number of absences per school in secondary school settings in the South East and Greater London, but such rises were not observed in other regions or in primary school settings. We conjecture that the increased transmissibility of the new variant in these regions may have contributed to this rise in cases in secondary schools. Finally, we observe a positive correlation between cases in the community and cases in schools in most regions, with weak evidence suggesting that cases in schools lag behind cases in the surrounding community. We conclude that there is not significant evidence to suggest that schools are playing a significant role in driving spread in the community and that careful monitoring may be required as schools re-open to determine the effect associated with open schools upon community incidence.
Cytokine response following perturbation of the cervicovaginal milieu during HPV genital infection
Authors: Selinger Christian , Rahmoun Massilva , Murall Carmen Lia , Bernat Claire , Boué Vanina , Bonneau Marine , Graf Christelle , Grasset Sophie , Groc Soraya , Reynes Jacques , Hirtz Christophe , Jacobs Nathalie , Alizon Samuel 
Published: February 2021

AbstractHuman papillomaviruses (HPVs) are the most oncogenic viruses known to human, causing nearly all cervical cancers worldwide. Highly prevalent in young, sexually active women, most HPV infections are cleared within 3 years, and only a minority of those infections persist and lead to cancer later in life. To better characterize the immuno-modulatory impact of early HPV infection and more generally perturbations of the cervicovaginal milieu, we measured changes in a panel of 20 cytokines, known as highly dynamic effector molecules implicated in cell signaling. We analyzed 92 cervicovaginal samples collected from young, sexually active women who were tested for or diagnosed with HPV, chlamydia, and bacterial vaginosis. Also, symptoms associated with genital inflammation and infection were collected through self-reporting.Following a parsimonious multi-factor modeling approach, our statistical analyses revealed that increased IL-1Alpha and IL-12/IL-23p40 concentrations were associated with HPV infection. Cytokine network analysis further highlighted the role of IL-1Alpha and macrophage inflammatory proteins (MIP-3Alpha) in HPV-associated immuno-modulation.
Exposure to per- and polyfluoroalkyl substances associates with altered lipid profile of breast milk
Authors: Lamichhane Santosh , Siljander Heli , Duberg Daniel , Honkanen Jarno , Virtanen Suvi M. , Orešič Matej , Knip Mikael , Hyötyläinen Tuulia 
Published: February 2021

AbstractBackgroundChemical composition of human breast milk is highly variable inter- and intra-individually. Environmental factors are suspected to partly explain the compositional variation, however, their impact on breast milk composition is currently poorly understood.ObjectivesWe sought (1) to define the impact of maternal exposure to per- and polyfluoroalkyl substances (PFAS) on lipid composition of human breast milk, and (2) to study the combined impact of maternal PFAS exposure and breast milk lipid composition on the growth of the infants.MethodsIn a mother-infant study (n=44) we measured the levels of PFAS and lipids in maternal serum and conducted lipidomics analysis of breast milk at birth and at 3 months of infant age, by using ultra high performance liquid chromatography combined with quadrupole-time-of-flight mass spectrometry. Maternal diet was studied by a validated food frequency questionnaire.ResultsPFAS levels were inversely associated with total lipid levels in the breast milk collected at birth. In the high exposure group, the ratio of acylated saturated and polyunsaturated fatty acids in triacylglycerols was increased. Moreover, high exposure to PFAS associated with the altered phospholipid composition, which was indicative of unfavorable increase in the size of milk fat globules. These changes in the milk lipid composition were further associated with slower infant growth and with elevated intestinal inflammatory markers.DiscussionOur data suggest that the maternal exposure to PFAS impacts the nutritional quality of the breast milk, which, in turn, may have detrimental impact on the health and growth of the children later in life.
Treatment of irritant contact dermatitis in healthcare settings during the COVID19 pandemic: The emollient Dermol 500 exhibits virucidal activity against influenza A virus and SARS-CoV-2
Authors: Styles Christine T. , Oever Michael Vanden , Brown Jonathan , Rai Sweta , Walsh Sarah , Ryan Finola M. , Barclay Wendy S. , Edgar Rachel S. 
Published: February 2021

ABSTRACTObjectivesTo investigate whether the antimicrobial emollient Dermol 500 and its active components, benzalkonium chloride (BAK) and chlorhexidine dihydrochloride (CD), exhibit virucidal activity thus informing whether Dermol 500 is a suitable soap substitute for use during the COVID19 pandemic, to combat the increased incidence of work-related contact dermatitis in clinical settings that we report here.MethodsInactivation of influenza A virus and SARS-CoV-2 by Dermol 500 and the independent and combined virucidal activity of the Dermol 500 components BAK and CD was assessed by influenza A virus and SARS-CoV-2 infectivity assays. Viruses were treated with concentrations of BAK and CD comparable to Dermol 500, and lower, and infectivity of the viruses assessed by titration.ResultsDermol 500 exhibits comparable virucidal activity to alcohol-based sanitisers against influenza A virus and SARS-CoV-2. In addition, the Dermol 500 components BAK and CD exhibit independent and synergistic virucidal activity against influenza A virus and SARS-CoV-2, the causative agent of COVID19.ConclusionsThe synergistic virucidal activity of the Dermol 500 components BAK and CD makes Dermol 500 suitable as a soap substitute to treat and prevent work-related contact dermatitis in healthcare settings.KEY MESSAGESWhat is already known about this subject?Work-related contact dermatitis is a prominent issue among healthcare workers, and likely exacerbated by the enhanced hand hygiene and personal protective equipment required to control infection during the COVID19 pandemic.The antimicrobial lotion Dermol 500 is frequently prescribed as an emollient and soap substitute to help prevent and treat dermatitis, but its use during the COVID19 pandemic was not advised as its capacity to inactivate viruses was unknown.What are the new findings?Increased incidence of irritant contact dermatitis was recorded amongst healthcare workers at King’s College Hospital NHS Foundation Trust in 2020 compared to 2019.Dermol 500 lotion and its antimicrobial components, benzalkonium chloride (BAK) and chlorhexidine dihydrochloride (CD), exhibit virucidal activity against influenza A virus and SARS-CoV-2, the virus responsible for COVID19 pandemic.How might this impact policy or clinical practice in the foreseeable future?Our results demonstrate that Dermol 500 can be safely used as a soap substitute to treat work-related contact dermatitis in clinical care settings during the COVID19 pandemic.Employers can meet their obligations under COSHH to eliminate workplace exposure to a harmful substance and substitute with an alternative product for hand hygiene.
Severe COVID-19 pneumonia and barotrauma: From the frying pan into the fire
Authors: Kalpakam Hariprasad , Bansal Sameer , Suresh Nithya , Kade Samson , Thorbole Anmol , Mehta Ravindra M 
Published: February 2021

AbstractAimCOVID-19 pneumonia with ARDS (C-ARDS) has a high mortality. Preliminary reports indicate a higher incidence of barotrauma in patients with C-ARDS[1] both on invasive mechanical ventilation (iMV) and non-invasive ventilation (NIV) This study examines the incidence and risk factors for barotrauma and change in outcomes after barotrauma in patients with severe C-ARDS on positive pressure respiratory support (PPRS).Methods and materialsThis is a retrospective study of C-ARDS associated barotrauma over 5 months in patients on PPRS in a tertiary COVID care center. The type of barotrauma, intervention, related factors, such as type of respiratory support (iMV vs NIV), airway pressure prior to the occurrence of barotrauma, and post-barotrauma outcomes were analyzed.ResultsA total of 38/410 (9.3%) C-ARDS patients on PPRS [mean age 57.82 ± 13.3 years, 32 males (84.2%)] developed barotrauma. Of these, 20 patients (52.6%) were on NIV and 18 (47.4%) patients were iMV on standard recommended settings. The median P/F ratio of patients on MV at the time of barotrauma was 116.4 (IQR 72.4, 193.25). The details of barotrauma were as follows: 24 patients had pneumothorax (PTX), 2 had pneumo-mediastinum and 12 had subcutaneous emphysema. Overall, 24/38 (63.2%) patients, including 15/18 (83.3%) on MV succumbed to their illness. The barotrauma happened a median of 6.5 days (IQR 4.75,13) after admission and 15 days (IQR 10.25,18.0) from symptom onset. The median duration from barotrauma to death was 7 days (IQR 2.25, 8.0) and barotrauma to discharge (for survivors) was 12.5 days (IQR 8.0, 21.25). All patients received steroids and 11/38 (28.9%) received additional immunosuppression with tocilizumab.ConclusionA high incidence of barotrauma was seen in this large series of severe C-ARDS patients on PPRS. Barotrauma led to further deterioration in the clinical status leading to a fatal outcome in the majority of the MV patients, despite prompt treatment.
Patient and physician shared decision making behaviors in oncology: Evidence on adequate measurement properties of the iSHARE questionnaires
Authors: Bomhof-Roordink Hanna , Stiggelbout Anne M. , Gärtner Fania R. , Portielje Johanneke E.A. , de Kroon Cor D. , Peeters Koen C.M.J. , Neelis Karen J. , Dekker Jan Willem T. , van der Weijden Trudy , Pieterse Arwen H. ,   for the iSHARE study group
Published: February 2021

AbstractObjectivesWe have developed two questionnaires to assess the shared decision making (SDM) process in oncology; the iSHAREpatient and iSHAREphysician. In this study, we aimed to determine: scores, construct validity, test-retest agreement (iSHAREpatient), and inter-rater (iSHAREpatient-iSHAREphysician) agreement.MethodsPhysicians from seven Dutch hospitals recruited cancer patients, and completed the iSHAREphysician and SDM-Questionnaire–physician version. Their patients completed the: iSHAREpatient, 9-item SDM-Questionnaire, Decisional Conflict Scale, Combined Outcome Measure for Risk communication And treatment Decision making Effectiveness, and Perceived Efficacy in Patient-Physician Interactions. We formulated, respectively, one (iSHAREphysician) and 10 (iSHAREpatient) a priori hypotheses regarding correlations between the iSHARE questionnaires and questionnaires assessing related constructs. To assess test-retest agreement patients completed the iSHAREpatient again 1-2 weeks later.ResultsIn total, 151 treatment decision making processes with unique patients were rated. Dimension and total iSHARE scores were high both in patients and physicians. The hypothesis on the iSHAREphysician and 9/10 hypotheses on the iSHAREpatient were confirmed. Test-retest and inter-rater agreement were >.60 for most items.ConclusionsThe iSHARE questionnaires show high scores, have good construct validity, substantial test-retest agreement, and moderate inter-rater agreement.Practice implicationsResults from the iSHARE questionnaires can inform both physician- and patient-directed efforts to improve SDM in clinical practice.
SARS-CoV-2 incidence and risk factors in a national, community-based prospective cohort of U.S. adults
Authors: Nash Denis , Rane Madhura S. , Chang Mindy , Kulkarni Sarah Gorrell , Zimba Rebecca , You William , Berry Amanda , Mirzayi Chloe , Kochhar Shivani , Maroko Andrew , Robertson McKaylee M. , Westmoreland Drew A. , Parcesepe Angela M. , Waldron Levi , Grov Christian 
Published: February 2021

ABSTRACTBackgroundEpidemiologic risk factors for incident SARS-CoV-2 infection as determined via prospective cohort studies greatly augment and complement information from case-based surveillance and cross-sectional seroprevalence surveys.MethodsWe estimated the incidence of SARS-CoV-2 infection and risk factors in a well-characterized, national prospective cohort of 6,738 U.S. adults, enrolled March-August 2020, a subset of whom (n=4,510) underwent repeat serologic testing between May 2020 and January 2021. We examined the crude associations of sociodemographic factors, epidemiologic risk factors, and county-level community transmission with the incidence of seroconversion. In multivariable Poisson models we examined the association of social distancing and a composite score of several epidemiologic risk factors with the rate of seroconversion.FindingsAmong the 4,510 individuals with at least one serologic test, 323 (7.3%, 95% confidence interval [CI] 6.5%-8.1%) seroconverted by January 2021. Among 3,422 participants seronegative in May-September 2020 and tested during November 2020-January 2021, we observed 161 seroconversions over 1,646 person-years of follow-up (incidence rate of 9.8 per 100 person-years [95%CI 8.3-11.5]). In adjusted models, participants who reported always or sometimes social distancing with people they knew (IRRalways vs. never0.43, 95%CI 0.21-1.0; IRRsometimes vs. never0.47, 95%CI 0.22-1.2) and people they did not know (IRRalways vs. never0.64, 95%CI 0.39-1.1; IRRsometimes vs. never0.60, 95%CI 0.38-0.97) had lower rates of seroconversion. The rate of seroconversion increased across tertiles of the composite score of epidemiologic risk (IRRmedium vs. low1.5, 95%CI 0.92-2.4; IRRhigh vs. low3.0, 95%CI 2.0-4.6). Among the 161 observed seroconversions, 28% reported no symptoms of COVID-like illness (i.e., were asymptomatic), and 27% reported a positive SARS-CoV-2 diagnostic test. Ultimately, only 29% reported isolating and 19% were asked about contacts.InterpretationModifiable epidemiologic risk factors and poor reach of public health strategies drove SARS-CoV-2 transmission across the U.S during May 2020-January 2021.FundingU.S. National Institutes of Allergy and Infectious Diseases (NIAID).