bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementation of an in-house real-time reverse transcription-PCR assay for the rapid detection of the SARS-CoV-2 Marseille-4 variant
Authors: Bedotto Marielle , Fournier Pierre-Edouard , Houhamdi Linda , Levasseur Anthony , Delerce Jeremy , Pinault Lucile , Padane Abdou , Chamieh Amanda , Tissot-Dupont Hervé , Brouqui Philippe , Sokhna Cheikh , Azar Eid , Saile Rachid , Mboup Souleymane , Bitam Idir , Colson Philippe , Raoult Didier 
Published: February 2021

ABSTRACTIntroductionThe SARS-CoV-2 pandemic has been associated with the occurrence since summer 2020 of several viral variants that overlapped or succeeded each other in time. Those of current concern harbor mutations within the spike receptor binding domain (RBD) that may be associated with viral escape to immune responses. In our geographical area a viral variant we named Marseille-4 harbors a S477N substitution in this RBD.Materials and methodsWe aimed to implement an in-house one-step real-time reverse transcription-PCR (qPCR) assay with a hydrolysis probe that specifically detects the SARS-CoV-2 Marseille-4 variant.ResultsAll 6 cDNA samples from Marseille-4 variant strains identified in our institute by genome next-generation sequencing (NGS) tested positive using our Marseille-4 specific qPCR, whereas all 32 cDNA samples from other variants tested negative. In addition, 39/42 (93%) respiratory samples identified by NGS as containing a Marseille-4 variant strain and 0/26 samples identified as containing non-Marseille-4 variant strains were positive. Finally, 1,585/2,889 patients SARS-CoV-2-diagnosed in our institute, 10/277 (3.6%) respiratory samples collected in Algeria, and none of 207 respiratory samples collected in Senegal, Morocco, or Lebanon tested positive using our Marseille-4 specific qPCR.DiscussionOur in-house qPCR system was found reliable to detect specifically the Marseille-4 variant and allowed estimating it is involved in more than half of our SARS-CoV-2 diagnoses since December 2020. Such approach allows the real-time surveillance of SARS-CoV-2 variants, which is warranted to monitor and assess their epidemiological and clinical characterics based on comprehensive sets of data.
Morphological Patterns Of Anemia Among Under Five Children On Prevention Of Mother-To-Child Transmission (PMTCT) Programmes In Masogo Sub-County Hospital, Kisumu County, Kenya
Authors: Awuor Silas O. , Eric Omwenga O. , Musyoki Stanslaus , Daud Ibrahim I. , Nyangaresi Robert O. , Mugah Peter , Mukunzi Beatrice 
Published: February 2021

AbstractBackgroundAnaemia during childhood adversely affects mental, physical and social development of the children, therefore morphological patterns of anaemia in under-five children are considered essential for classification, diagnosis and management.AimThis study aimed at assessing morphological patterns, the prevalence and associated factors of anaemia among under-five children on Prevention of Mother-To-Child Transmission (PMTCT) programmes in Masogo sub-county hospital, Kisumu County, Kenya.MethodA cross-sectional health facility-based study was conducted among 175 children aged 6 to 59 months who attended clinic for the PMTCT programme for the period of January 2020 to December 2020. Pretested and structured questionnaires were used to collect socioeconomic and demographic characteristics of the family and child. Capillary blood sample was collected from each child for malaria parasite and Peripheral Blood Film (PBF) examination.ResultComplete blood counts indicate that microcytic pattern was the most common, representing 30 (42.3%) followed by microcytic hypochromic pattern 20 (28.2%), normocytic normochromic pattern with 11 (15.5%) and lastly dimorphic pattern with 10 (14.0%). High prevalence of anaemia was observed in children who were urban dwellers (50.0%), in children whose mothers aged 18-27 years (44.0%) and had no formal education (48.1%). Besides, the high prevalence rate of anaemia was found among children with a family monthly income of less than 500 Ksh. (46.9%), early (<6 months) introduction of complementary foods (71.4%)ConclusionThis study has revealed that the prevalence of anaemia in children less than five years is high and is a severe public health problem in the study area. Therefore, the policymakers should make a strategy that can reduce poverty and increase the awareness to women on breastfeeding, nutrition, and other associated factors to reduce anaemia.
Tau-PET and in vivo Braak-staging as a prognostic marker in Alzheimer’s disease
Authors: Biel Davina , Brendel Matthias , Rubinski Anna , Buerger Katharina , Janowitz Daniel , Dichgans Martin , Franzmeier Nicolai ,   for the Alzheimer’s Disease Neuroimaging Initiative (ADNI)
Published: February 2021

ABSTRACTINTRODUCTIONTau pathology in Alzheimer’s disease tracks clinical status more closely than beta-amyloid. Thus, tau-PET may be a promising prognostic marker for cognitive decline. Here, we systematically compared tau-PET and Braak-staging vs. amyloid-PET as predictors of cognitive decline.METHODSWe included 396 cognitively normal to dementia subjects with18F-Flutemetamol/18F-Florbetapir-amyloid-PET,18F-Flortaucipir-tau-PET and ~2-year cognitive assessments. Annual cognitive change rates were calculated via linear-mixed models. We determined global amyloid-PET, global tau-PET, and tau-PET-based Braak-stage (Braak0/BraakI+/BraakI-IV+/BraakI-VI+/Braakatypical+). In bootstrapped linear regression, we assessed whether tau-PET outperformed amyloid-PET in predicting cognitive decline. Using ANCOVAs, we tested whether later Braak-stage predicted accelerated cognitive decline and determined Braak-stage-specific conversion risk to MCI or dementia.RESULTSGlobal tau-PET was a better predictor of cognitive decline than global amyloid-PET (p<0.001). Advanced Braak-stage was associated with faster cognitive decline (p<0.001) and elevated clinical conversion risk.DISCUSSIONTau-PET and Braak-staging show promise for predicting patient-specific risk of clinical AD progression.
Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning
Authors: Pelin Helena , Ising Marcus , Stein Frederike , Meinert Susanne , Meller Tina , Brosch Katharina , Winter Nils R. , Krug Axel , Leenings Ramona , Lemke Hannah , Nenadic Igor , Heilmann-Heimbach Stefanie , Forstner Andreas J. , Nöthen Markus M. , Opel Nils , Repple Jonathan , Pfarr Julia , Ringwald Kai , Schmitt Simon , Thiel Katharina , Waltemate Lena , Winter Alexandra , Streit Fabian , Witt Stephanie , Rietschel Marcella , Dannlowski Udo , Kircher Tilo , Hahn Tim , Müller-Myhsok Bertram , Andlauer Till F. M. 
Published: February 2021

AbstractPsychiatric disorders show heterogeneous clinical manifestations and disease trajectories, with current classification systems not accurately reflecting their molecular etiology. This heterogeneity impedes timely and targeted treatment. Our study aimed to identify diagnostically mixed psychiatric patient clusters that share clinical and genetic features and may profit from similar therapeutic interventions. We used unsupervised high-dimensional data clustering on deep clinical data to identify transdiagnostic groups in a discovery sample (N=1250) of healthy controls and patients diagnosed with depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other psychiatric disorders. We observed five diagnostically mixed clusters and ordered them based on severity. The least impaired cluster 0, containing most healthy controls, was characterized by general well-being. Clusters 1-3 differed predominantly regarding levels of maltreatment, depression, daily functioning, and parental bonding. Cluster 4 contained most patients diagnosed with psychotic disorders and exhibited the highest severity in many dimensions, including medication load. MDD patients were present in all clusters, indicating that we captured different disease stages or subtypes. We replicated all but the smallest cluster 1 in an independent sample (N=622). Next, we analyzed genetic differences between clusters using polygenic scores (PGS) and the psychiatric family history. These genetic variables differed mainly between clusters 0 and 4 (prediction AUC=81%; significant PGS: cross-disorder psychiatric risk, schizophrenia, and educational attainment). Our results confirm that psychiatric disorders consist of heterogeneous subtypes sharing molecular factors and symptoms. The identification of transdiagnostic clusters advances our understanding of the heterogeneity of psychiatric disorders and may support the development of personalized treatment regimes.
Using Machine Learning to Predict Mortality for COVID-19 Patients on Day Zero in the ICU
Authors: Jamshidi Elham , Asgary Amirhossein , Tavakoli Nader , Zali Alireza , Esmaily Hadi , Jamaldini Seyed Hamid , Daaee Amir , Babajani Amirhesam , Kashi Mohammad Ali Sendani , Jamshidi Masoud , Rahi Sahand Jamal , Mansouri Nahal 
Published: February 2021

AbstractRationaleGiven the expanding number of COVID-19 cases and the potential for upcoming waves of infection, there is an urgent need for early prediction of the severity of the disease in intensive care unit (ICU) patients to optimize treatment strategies.ObjectivesEarly prediction of mortality using machine learning based on typical laboratory results and clinical data registered on the day of ICU admission.MethodsWe studied retrospectively 263 COVID-19 ICU patients. To find parameters with the highest predictive values, Kolmogorov-Smirnov and Pearson chi-squared tests were used. Logistic regression and random forest (RF) algorithms were utilized to build classification models. The impact of each marker on the RF model predictions was studied by implementing the local interpretable model-agnostic explanation technique (LIME-SP).ResultsAmong 66 documented parameters, 15 factors with the highest predictive values were identified as follows: gender, age, blood urea nitrogen (BUN), creatinine, international normalized ratio (INR), albumin, mean corpuscular volume, white blood cell count, segmented neutrophil count, lymphocyte count, red cell distribution width (RDW), and mean cell hemoglobin along with a history of neurological, cardiovascular, and respiratory disorders. Our RF model can predict patients outcomes with a sensitivity of 70% and a specificity of 75%.ConclusionsThe most decisive variables in our model were increased levels of BUN, lowered albumin levels, increased creatinine, INR, and RDW along with gender and age. Complete blood count parameters were also crucial for some patients. Considering the importance of early triage decisions, this model can be a useful tool in COVID-19 ICU decision-making.
Investigation of association of rare, functional genetic variants with heavy drinking and problem drinking in exome sequenced UK Biobank participants
Authors: Curtis David 
Published: February 2021

AbstractAimsThe study aimed to identify specific genes and functional genetic variants affecting susceptibility to two alcohol related phenotypes: heavy drinking and problem drinking.MethodsPhenotypic and exome sequence data was downloaded from the UK Biobank. Reported drinks in the last 24 hours was used to define heavy drinking while responses to a mental health questionnaire defined problem drinking. Gene-wise weighted burden analysis was applied, with genetic variants which were rarer and/or had a more severe functional effect being weighted more highly. Additionally, previously reported variants of interest were analysed inidividually.ResultsOf exome sequenced subjects, for heavy drinking there were 8,166 cases and 84,461 controls while for problem drinking there were 7,811 cases and 59,606 controls. No gene was formally significant after correction for multiple testing but three genes possibly related to autism were significant at p < 0.001,FOXP1, ARHGAP33andCDH9, along withVGFwhich may also be of psychiatric interest. Well established associations with rs1229984 inADH1Band rs671 inALDH2were confirmed but previously reported variants inALDH1B1andGRM3were not associated with either phenotype.ConclusionsThis large study fails to conclusively implicate any novel genes or variants. It is possible that more definitive results will be obtained when sequence data for the remaining UK Biobank participants becomes available and/or if data can be obtained for a more extreme phenotype such as alcohol dependence disorder. This research has been conducted using the UK Biobank Resource.Short summaryTests for association of rare, functional genetic variants with heavy drinking and problem drinking confirm the known effects of variants inADH1BandALDH2but fail to implicate novel variants or genes. Results for three genes potentially related to autism suggest they might exert a protective effect.
Ventilation rate assessment by carbon dioxide levels in dental treatment rooms
Authors: Huang Qirong , Marzouk Tamer , Cirligeanu Razvan , Malmstrom Hans , Eliav Eli , Ren Yan-Fang 
Published: February 2021

AbstractObjectivesThe purpose of the present study was to monitor and evaluate CO2 levels in dental operatories using a consumer-grade CO2 sensor and determine the utility and accuracy of various methods using CO2 levels to assess ventilation rate in dental clinics. We aim to find a practical tool for dental practitioners to conveniently and accurately monitor CO2 levels and assess the ventilation rates in their office in order to devise a pragmatic and effective strategy for ventilation improvement in their work environment.MethodsMechanical ventilation rate in air change per hour (ACHVENT) of 10 dental operatories was first measured with an air velocity sensor and air flow balancing hood. CO2 levels were measured in these rooms to analyze the effects of ventilation rate and number of persons in the room on CO2 accumulation. Ventilation rates were estimated using natural steady state CO2 levels during dental treatments and experimental CO2 concentration decays by dry ice or mixing baking soda and vinegar. We compared the differences and assessed the correlations between ACHVENT and ventilation rates estimated by steady states CO2 model with low (0.3 L/min, ACHSS30) or high (0.46 L/min, ACHSS46) CO2 generation rates, by CO2 decay constants using dry ice (ACHDI) or baking soda (ACHBV), and by time needed to remove 63% of excess CO2 generated by dry ice (ACHDI63%) or baking soda (ACHBV63%).ResultsACHVENT varied from 3.9 to 35.0 with a mean of 13.2 (±10.6) in the 10 dental operatories. CO2 accumulation occurred in rooms with low ventilation (ACHVENT≤6) and more persons (n>3) but not in those with higher ventilation and less persons. ACHSS30 and ACHSS46 correlated well with ACHVENT (r=0.83, p=0.003), but ACHSS30 was more accurate for rooms with low ACHVENT. Ventilation rates could be reliably estimated using CO2 released from dry ice or baking soda. ACHVENT was highly correlated with ACHDI (r=0.99), ACHBV(r=0.98), ACHDI63%(r=0.98), and ACHBV63% (r=0.98). There were no statistically significant differences between ACHVENT and ACHDI63% or ACHBV63%.ConclusionsDental operatories with low ventilation rates and overcrowding facilitate CO2 accumulations. Ventilation rates could be reliably calculated by observing the changes in CO2 levels after a simple mixing of household baking soda and vinegar in dental settings. Time needed to remove 63% of excess CO2 generated by baking soda could be used to accurately assess the ventilation rates using a consumer-grade CO2 sensor and a basic calculator.
COVID-19 prevention behaviour over time in Australia: Patterns and long-term predictors from April to July 2020
Authors: Ayre J , Cvejic E , McCaffery K , Copp T , Cornell S , Dodd RH , Pickles K , Batcup C , Isautier JMJ , Nickel B , Dakin T , Bonner C 
Published: February 2021

AbstractBackgroundIn Australia in March 2020 a national public health directive required that non-essential workers stay at home, except for essential activities. These restrictions began easing in May 2020 as community transmission slowed.PurposeThis study investigated changes in COVID-19 prevention behaviours from April-July 2020, and psychosocial predictors of these behaviours.Methods1,843 participants in Australia completed a national COVID-19 survey in April, with monthly follow-up over four months. Principal components analysis (PCA) combined self-reported adherence across seven prevention behaviours. Multivariable regression models explored baseline (April) correlates of behaviour in June (a period of low community transmission) and July (a period of increasing community transmission).ResultsOn average, participants agreed with statements of adherence for all behaviours (means all above 4 out of 7). PCA identified two behaviour types: ‘distancing’ (e.g. staying 1.5m away) and ‘hygiene’ (e.g. washing hands), explaining 28.3% and 24.2% of variance, respectively. Distancing declined each month (p’s<.001), whereas hygiene remained relatively stable. For distancing, stronger perceptions of societal risk, self-efficacy to maintain distancing, and greater perceived social obligation at baseline were associated with adherence in June and July (p’s<0.05). For hygiene, the only significant correlate of adherence in June and July was belief that one’s actions could prevent infection of family members (p<.001).ConclusionsHigh adherence to COVID-19 prevention behaviours were reported; however, distancing behaviours tended to decrease over time. Belief in social responsibility may be an important aspect to consider in encouraging distancing behaviours. Different policy approaches may be needed for different behavioural categories.
Symptoms of COVID-19 infection and magnitude of antibody response in a large community-based study
Authors: McDade Thomas W. , Schrock Joshua M. , D’Aquila Richard , Mustanski Brian , Benbow Nanette , Vaught Lauren A. , Reiser Nina L. , Velez Matt E. , Hsieh Ryan R. , Ryan Daniel T. , Saber Rana , McNally Elizabeth M. , Demonbreun Alexis R. 
Published: February 2021

AbstractBackgroundThe majority of COVID-19 cases are asymptomatic, or minimally symptomatic with management in the home. Little is known about the frequency of specific symptoms in the general population, and how symptoms predict the magnitude of antibody response to SARS-CoV-2 infection.MethodsWe quantified IgG antibodies against the SARS-CoV-2 receptor binding domain (RBD) in home-collected dried blood spot samples from 3,365 adults participating in a community-based seroprevalence study in the city of Chicago, USA, collected between June 24 and November 11, 2020.Results17.8% of the sample was seropositive for SARS-CoV-2. A cluster of symptoms (loss of sense of smell or taste, fever, shortness of breath, muscle or body aches, cough, fatigue, diarrhea, headache) was associated with stronger anti-RBD IgG responses among the seropositives. 39.2% of infections were asymptomatic, and 2 or fewer symptoms were reported for 66.7% of infections. Total number of symptoms was positively but weakly associated with IgG response: Median anti-RBD IgG was 0.95 ug/mL for individuals with 3 or more symptoms, in comparison with 0.61 ug/mL for asymptomatic infections.ConclusionWe document high rates of asymptomatic and mild infection in a large community-based cohort, and relatively low levels of anti-SARS-CoV-2 IgG antibody in the general population of previously exposed individuals.
Assessment of Vaccination and Underreporting on COVID-19 Infections in Turkey Based On Effective Reproduction Number
Authors: Akman Yıldız Tuğba , Köse Emek , Tuncer Necibe 
Published: February 2021

AbstractIn this paper, we introduce a SEIR type COVID-19 model where the infected class is further divided into subclasses with individuals in intensive care (ICUs) and ventilation units. The model is validated with the symptomatic COVID-19 cases, deaths, and the number of patients in ICUs and ventilation units as reported by Republic of Turkey, Ministry of Health for the period March 11, 2020 through May 30, 2020 when the nationwide lockdown is in order. COVID-19 interventions in Turkey are incorporated into the model to detect the future trend of the outbreak accurately. We tested the effect of underreporting and we found that the peaks of the disease differ significantly depending on the rate of underreporting, however, the timing of the peaks remains constant.The lockdown is lifted on June 1, and the model is modified to include a time dependent transmission rate which is linked to the effective reproduction number ℛt through basic reproduction number ℛ0. The modified model captures the changing dynamics and peaks of the outbreak successfully. With the onset of vaccination on 13 January 2021, we augment the model with the vaccination class to investigate the impact of vaccination rate and efficacy. We observe that vaccination rate is a more critical parameter than the vaccine efficacy to eliminate the disease successfully.
Adaptive plasticity in development rate and genetic variance in survival increase the potential for adapting to novel environments
Authors: Walter Greg M. , Terranova Delia , la Spina Enrico , Majorana Mari , Pepe Giuseppe , du Plessis Sarah , Clark James , Cozzolino Salvatore , Cristaudo Antonia , Hiscock Simon J. , Bridle Jon R. 
Published: February 2021

ABSTRACTPlasticity in early development is expected to be crucial for helping natural populations adjust to environmental change. Where such plasticity fails to maintain fitness, genetic variance in plasticity or survival could help populations adapt to the novel conditions. To test this prediction, we used two closely related, but ecologically distinct, species of Sicilian daisy (Senecio, Asteraceae) adapted to high and low elevations on Mount Etna. Using a paternal half-sibling breeding design, we generated seeds of both species and planted them across an elevational gradient representing the native range of each species, and two intermediate elevations. We tracked mortality and measured the number of days it took seedlings to establish. We found that each species survived better at their native elevation, and better than the species from the other habitat. Genetic variance in relative survival was near zero within the native range, but increased in the novel environments for both species. Plasticity increased development time at higher elevations. At novel elevations, selection was in the direction of plasticity for the low-elevation species, but the opposite direction for the high-elevation species. Genetic variance for greater plasticity was associated with higher survival, but only for the low-elevation species. Together, these results suggest that while genetic variance in survival increased for both species, genetic variance for adaptive plasticity differs among species. Understanding adaptive potential in novel environments therefore needs to consider how species vary in their capacity and underlying genetic variation for adaptive plasticity.