bluuebunny/crossref_metadata_2025_split huggingface dataset:
Decoding Clinical Biomarker Space of COVID-19: Exploring Matrix Factorization-based Feature Selection Methods
Authors: Saberi-Movahed Farshad , Mohammadifard Mahyar , Mehrpooya Adel , Rezaei-Ravari Mohammad , Berahmand Kamal , Rostami Mehrdad , Karami Saeed , Najafzadeh Mohammad , Hajinezhad Davood , Jamshidi Mina , Abedi Farshid , Mohammadifard Mahtab , Farbod Elnaz , Safavi Farinaz , Dorvash Mohammadreza , Vahedi Shahrzad , Eftekhari Mahdi , Saberi-Movahed Farid , Tavassoly Iman 
Published: July 2021

AbstractOne of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients’ characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 patients that are predictive of poor prognosis and morbidity. Our approach consists of two interconnected schemes: Feature Selection and Prognosis Classification. The former is based on different Matrix Factorization (MF)-based methods, and the latter is performed using Random Forest algorithm. Our model reveals that Arterial Blood Gas (ABG) O2Saturation and C-Reactive Protein (CRP) are the most important clinical biomarkers determining the poor prognosis in these patients. Our approach paves the path of building quantitative and optimized clinical management systems for COVID-19 and similar diseases.
Ethnicity, migration, and weight misperception: a Born in Bradford study
Authors: Yang Tiffany C , Truesdale Kimberly P , Kelly Brian , Rasgado Marena Ceballos , Bryant Maria J 
Published: July 2021

AbstractBackgroundWeight perception may differ by ethnicity but is not well-understood, particularly among migrants to the United Kingdom (UK). It is also unknown whether a figure rating scale (FRS) or perceived weight question (PWQ) is more accurate for assessing body weight perception.MethodsAt 24-months postpartum, women in the Born in Bradford cohort (Bradford, UK) completed the 9-item Stunkard FRS and a 7-category PWQ. Both scales were condensed to weight categories representing the World Health Organisation cut-offs. Weighted kappa statistics assessed agreement between measured and perceived weight categories. χ2 and Fisher’s exact tests assessed categories of misperception by ethnicity and migration and logistic regression was used to examine odds of underestimation.ResultsThirty percent of white British and 23% of Pakistani-origin women had obesity. Agreement between measured and perceived weight categories were similar for white British women using either a visual scale or weight question (FRS: κ [95%CI]: 0.61 [0.56, 0.65]; PWQ: 0.61 [0.55, 0.68)]. Overall agreement was lower for Pakistani-origin women with the visual scale performing better (FRS (0.58 [0.52, 0.63]) vs PWQ (0.47 [0.40, 0.54]). Pakistani-origin women, particularly those born outside the UK, were more likely to underestimate their body weight compared to white British women; this was greater with the PWQ (18% vs 10%; p<0.001) than FRS (14% vs 6%; p<0.001). Pakistani-origin women were 154% more likely to underestimate their body weight compared to white British women with the FRS and 111% more likely to underestimate when using the PWQ.ConclusionWe observed ethnic differences in weight misperception with Pakistani-origin women more likely to underestimate their weight compared to white British women. Our findings suggest visual scales, rather than perceived weight questions, are more appropriate for the self-assessment of body weight.
The influence of CYP2D6 and CYP2C19 genetic variation on diabetes mellitus risk in people taking antidepressants and antipsychotics
Authors: Austin-Zimmerman Isabelle , Wronska Marta , Wang Baihan , Irizar Haritz , Thygesen Johan Hilge , Bhat Anjali , Denaxas Spiros , Fatemifar Ghazaleh , Finan Chris , Harju-Seppänen Jasmine , Giannakopoulou Olga , Kuchenbaecker Karoline , Zartaloudi Eirini , McQuillin Andrew , Bramon Elvira 
Published: July 2021

AbstractBackgroundCYP2D6 and CYP2C19 enzymes are essential in the metabolism of antidepressants and antipsychotics. Genetic variation in these genes may increase risk of adverse drug reactions. Antidepressants and antipsychotics have previously been associated with risk of diabetes. We examined whether individual genetic differences in CYP2D6 and CYP2C19 contribute to these effects.MethodsWe identified 31,579 individuals taking antidepressants and 2,699 taking antipsychotics within UK Biobank. Participants were classified as poor, intermediate or normal metabolisers of CYP2D6, and as poor, intermediate, normal, rapid and ultra-rapid metabolisers of CYP2C19. Risk of diabetes mellitus represented by HbA1c level was examined in relation to the metabolic phenotypes. We analysed drugs either individually (where sample size permitted) or grouped by class.ResultsCYP2D6 poor metabolisers taking paroxetine had higher Hb1Ac than normal metabolisers (mean difference: 2.29mmol/mol; p < 0.001). Among participants with diabetes who were taking venlafaxine, CYP2D6 poor metabolisers had higher HbA1c levels compared to normal metabolisers (mean differences: 10.15 mmol/mol; p < 0.001. Among participants with diabetes who were taking fluoxetine, we observe that CYP2D6 intermediate metabolisers and decreased HbA1c, compared to normal metabolisers (mean difference - 7.74mmol/mol; p=0.017). We did not observe any relationship between CYP2D6 or CYP2C19 metabolic status and HbA1c levels in participants taking antipsychotic medication.ConclusionOur results indicate that the impact of genetic variation in CYP2D6 differs depending on diabetes status. Although our findings support existing clinical guidelines, further research is essential to inform pharmacogenetic testing for people taking antidepressants and antipsychotics.
COVID-19 Serology Control Panel Using the Dried Tube Specimen Method
Authors: Windsor William J. , Knight Vijaya , Merkel Patricia A. , Lamb Molly M. , Santiago Mario L. , McCarthy Mary K. , Morrison Thomas E. , Kedl Ross M. , Frazer-Abel Ashley , Guo Kejun , Andersen Gillian , Huey Leah , Barrett Bradley S. , Colón-Franco Jessica M. , Chu May C. 
Published: July 2021

AbstractWe used the dried tube specimen (DTS) procedure to develop the COVID-19 Serology Control Panel (CSCP). The CSCP contains five well-characterized SARS-CoV-2 pooled plasma samples made available for labs around the world to compare test kits, use for external quality assurance, harmonize laboratory testing, and train laboratory workers.Article Summary LineThe dried tube specimen system is a highly effective and resilient way to provide laboratories with well-characterized serology materials. The CSCP can help clinical laboratories inform their choice of diagnostic test to supplement clinical diagnoses of SARS-CoV-2 infection.
Myeloid-derived suppressor cells in the blood of Iranian COVID-19 patients
Authors: Mortaz Esmaeil , Movasaghi Mehrnaz , Basiri Ali , Dezfuli Neda K. , Roofchayee Neda Dalil , Jamaati Hamidreza , Garssen Johan , Adcock Ian M. 
Published: July 2021

AbstractBackgroundA cytokine storm and lymphopenia are reported in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection associated with coronavirus disease 2019 (COVID-19). Myeloid-derived suppressive cells (MDSCs) exist in two different forms, granulocyte (G-MDSCs) and monocytic (M-MDSCs) that both suppress T-cell function. Serum IL-6 and IL-8 levels seem to correlate with the number of blood MDSCs.ObjectiveTo determine the frequency of MDSCs in severe COVID-19 patients from Iran and their correlations with serum IL-8 levels.Methods37 severe (8 on ventilation, 29 without ventilation) and 13 moderate COVID-19 patients together with 8 healthy subjects were enrolled at the Masih Daneshvari Hospital, Tehran-Iran between 10th April 2020-9th March 2021. Clinical and biochemical features, serum and whole blood were obtained. CD14, CD15, CD11b and HLA-DR expression on MDSCs was measured by flow cytometry.ResultsM-MDSCs (P≤0.0001) and G-MDSCs (P≤0.0001) frequency were higher in Iranian COVID-19 patients compared to healthy subjects. M-MDSC frequency was higher in non-ventilated compared to moderate COVID-19 subjects (P=0.004). Serum IL-8 levels were higher in patients with COVID-19 than in normal healthy subjects (P=0.03). IL8 level was significant difference in ventilated, non-ventilated and moderate patients (P=0.005). The frequency of G-MDSCs correlated negatively with INR (r=-0.39, P=0.02).ConclusionSerum IL-8 levels did not correlate with the number of systemic MDSCs in COVID-19 patients. The highest levels of M-MDSCs were seen in the blood of severe non-ventilated patients. MDSC frequency in blood in the current study did not predict the survival and severity of COVID-19 patients.
Modulating amygdala activation to traumatic memories with a single ketamine infusion
Authors: Duek Or , Li Yutong , Kelmendi Ben , Amen Shelley , Gordon Charles , Milne Madison , Krystal John H. , Levy Ifat , Harpaz-Rotem Ilan 
Published: July 2021

AbstractNMDA receptor antagonists have a vital role in extinction, learning, and reconsolidation processes. During the reconsolidation window, memories are activated into a labile state and can be stored in an altered form. This concept might have significant clinical implications in treating PTSD. Using amygdala activity as a major biomarker of fear response, we tested the potential of a single subanesthetic intravenous infusion of ketamine (NMDA receptor antagonist) to enhance post-retrieval extinction of PTSD trauma memories. Post-extinction, ketamine recipients (vs midazolam) showed a lower amygdala and hippocampus reactivation to trauma memories. Post-retrieval ketamine administration was also associated with decreased connectivity between the amygdala and hippocampus, with no change in amygdala-vmPFC connectivity, which suggests that ketamine may enhance post-retrieval extinction of PTSD trauma memory in humans. These findings demonstrate the capacity to rewrite human traumatic memories and to modulate the fear response for at least 30 days post-extinction.
Lung function from school age to adulthood in primary ciliary dyskinesia
Authors: Halbeisen Florian S , Goutaki Myrofora , Pedersen Eva S L , Spycher Ben D , Amirav Israel , Boon Mieke , Malena Cohen-Cymberknoh , Crowley Suzanne , Emiralioglu Nagehan , Haarman Eric G , Karadag Bulent , Koerner-Rettberg Cordula , Latzin Philipp , Loebinger Michael R. , Lucas Jane S , Mazurek Henryk , Morgan Lucy , Marthin June , Pohunek Petr , Santamaria Francesca , Schwerk Nicolaus , Thouvenin Guillaume , Yiallouros Panayiotis , Nielsen Kim G , Kuehni Claudia E 
Published: July 2021

AbstractPrimary ciliary dyskinesia (PCD) presents with symptoms early in life and the disease course may be progressive, but longitudinal data on lung function are scarce. This multinational cohort study describes lung function trajectories in children, adolescents, and young adults with PCD. We analysed data from 486 patients with repeated lung function measurements obtained between the age of 6 and 24 years from the international PCD Cohort (iPCD) and calculated z-scores for forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) using the Global Lung Function Initiative 2012 references. We described baseline lung function and change of lung function over time and described their associations with possible determinants in mixed-effects linear regression models. Overall, FEV1 and FVC z-scores declined over time (average crude annual FEV1 decline was -0.07 z-scores) but not at the same rate for all patients. FEV1 z-scores improved over time in 21% of patients, remained stable in 40% and declined in 39%. Low BMI was associated with poor baseline lung function and with further decline. Results differed by country and ultrastructural defect, but we found no evidence of differences by sex, calendar year of diagnosis, age at diagnosis, diagnostic certainty, or laterality defect. Our study shows that on average lung function in PCD declines throughout the entire period of lung growth, from childhood to young adult age, even among patients treated in specialized centres. It is essential to develop strategies to reverse this tendency and improve prognosis.Take home messageLung function in children with PCD is reduced by age 6 years and further declines during the growth period. It is essential to develop strategies to improve prognosis.
RISK OF ON JOB NON COMPLIANCE TOWARDS VARIOUS COVID-19 STANDARD & TRANSMISSION BASED INFECTION PREVENTION & CONTROL MEASURES/PRECAUTIONS AMONG THE HEALTHCARE WORKS WORKING IN OPD SETTINGs OF PUBLIC SECTOR TERTIORY CARE HOSPITALS OF QUETTA BALOCHISTAN
Authors: Arif Muhammad , Abdullah Muhammad , Chaudhary Ambreen , Hussain Zakir , Larik Ehsan 
Published: July 2021

ABSTRACTBackgroundCOVID-19 Pandemic is still circulating within the human population and proving to be a deadlier disease with mortality rate ranging from 0.5 to 7%8. Since COVID-19 is a highly transmissible disease; there is always a probability for its out ward spread towards general public and community from the hospitals and healthcare facilities where they come to seek treatment.MethodologyA prospective cohort study design was used, considering the limited available resources and time __ A total of 200 healthcare workers (Including Doctors, Nurses, Para-Medical staff, Janitorial staff, Reception staff & Pharmacists) working in the OPDs of the two major Public sector hospitals of Quetta were made part of this study. The study participants were selected using simple random sampling technique. The study participants from “Hospital-A” were first of all educated and trained on various COVID-19 IPC measures later on various COVID-19-IEC materials; written in simple Urdu language, were displayed clearly everywhere in the OPD. Similarly hand washing station along with Hand sanitizers/Soaps and surgical face masks were also made available free of cost for all the study participants of Hospital-A. More over the importance and effectiveness of COVID-19 IPC measures were continuously announced in the OPD gallery of Hospital-A, these announcements used Simple wording in local languages (i.e. Urdu, Pashto, Balochi & Brahvi). On the other hand in the OPD of “Hospital-B” no such interventions were made. The study participants of both the hospitals were followed for one month and observations like-which group showed more on-job non compliance towards various COVID-19 IPC measures were recorded. The data was recorded on daily bases (From 1stMay-to-31stMay 2021) after observing the study participants and checklist was used for recording various findings. Lastly all the data was analyzed using Microsoft Excel 2007 version.ResultsThe major findings of this study are almost in line with the set objectives, the study results are clearly showing the Risk ratio (R.R) as 0.27, indicating that the intervention group participants were only 27% as likely to develop On-job non-compliance for various COVID-19 IPC measures compare to the non-intervention group.ConclusionThe best suggestion and intervention for the developing countries that could at least address the spread of COVID-19 in a cost effective manner at health facility levels remains to be adoption of various Standard and Transmission based non-pharmacological measures of Infection prevention and Control (IPC)5.
In silico proof of principle of machine learning-based antibody design at unconstrained scale
Authors: Akbar Rahmad , Robert Philippe A. , Weber Cédric R. , Widrich Michael , Frank Robert , Pavlović Milena , Scheffer Lonneke , Chernigovskaya Maria , Snapkov Igor , Slabodkin Andrei , Mehta Brij Bhushan , Miho Enkelejda , Lund-Johansen Fridtjof , Andersen Jan Terje , Hochreiter Sepp , Haff Ingrid Hobæk , Klambauer Günter , Sandve Geir Kjetil , Greiff Victor 
Published: July 2021

AbstractGenerative machine learning (ML) has been postulated to be a major driver in the computational design of antigen-specific monoclonal antibodies (mAb). However, efforts to confirm this hypothesis have been hindered by the infeasibility of testing arbitrarily large numbers of antibody sequences for their most critical design parameters: paratope, epitope, affinity, and developability. To address this challenge, we leveraged a lattice-based antibody-antigen binding simulation framework, which incorporates a wide range of physiological antibody binding parameters. The simulation framework enables both the computation of antibody-antigen 3D-structures as well as functions as an oracle for unrestricted prospective evaluation of the antigen specificity of ML-generated antibody sequences. We found that a deep generative model, trained exclusively on antibody sequence (1D) data can be used to design native-like conformational (3D) epitope-specific antibodies, matching or exceeding the training dataset in affinity and developability variety. Furthermore, we show that transfer learning enables the generation of high-affinity antibody sequences from low-N training data. Finally, we validated that the antibody design insight gained from simulated antibody-antigen binding data is applicable to experimental real-world data. Our work establishes a priori feasibility and the theoretical foundation of high-throughput ML-based mAb design.HighlightsA large-scale dataset of 70M [3 orders of magnitude larger than the current state of the art] synthetic antibody-antigen complexes, that reflect biological complexity, allows the prospective evaluation of antibody generative deep learningCombination of generative learning, synthetic antibody-antigen binding data, and prospective evaluation shows that deep learning driven antibody design and discovery at an unconstrained level is feasibleTransfer learning (low-N learning) coupled to generative learning shows that antibody-binding rules may be transferred across unrelated antibody-antigen complexesExperimental validation of antibody-design conclusions drawn from deep learning on synthetic antibody-antigen binding dataGraphical abstractWe leverage large synthetic ground-truth data to demonstrate the (A,B) unconstrained deep generative learning-based generation of native-like antibody sequences, (C) the prospective evaluation of conformational (3D) affinity, paratope-epitope pairs, and developability. (D) Finally, we show increased generation quality of low-N-based machine learning models via transfer learning.
Loss of TREM2 reduces hyperactivation of progranulin deficient microglia but not lysosomal pathology
Authors: Reifschneider Anika , Robinson Sophie , van Lengerich Bettina , Gnörich Johannes , Logan Todd , Heindl Steffanie , Vogt Miriam A , Weidinger Endy , Riedl Lina , Wind Karin , Zatcepin Artem , Haberl Sophie , Nuscher Brigitte , Kleinberger Gernot , Klimmt Julien , Götzl Julia K , Liesz Arthur , Bürger Katharina , Brendel Matthias , Levin Johannes , Diehl-Schmid Janine , Suh Jung , Di Paolo Gilbert , Lewcock Joseph W , Monroe Kathryn M , Paquet Dominik , Capell Anja , Haass Christian 
Published: July 2021

AbstractGRNhaploinsufficiency causes frontotemporal lobar degeneration and results in microglial hyperactivation, lysosomal dysfunction and TDP-43 deposition. To understand the contribution of microglial hyperactivation to pathology we evaluated genetic and pharmacological approaches suppressing TREM2 dependent transition of microglia from a homeostatic to a disease associated state.Trem2deficiency inGrnKO mice led to a reduction of microglia activation. To explore antibody-mediated pharmacological modulation of TREM2-dependent microglial states, we identified antagonistic TREM2 antibodies. Treatment of macrophages fromGRN-FTLD patients with these antibodies allowed a complete rescue of elevated levels of TREM2 together with increased shedding and reduction of TREM2 signaling. Furthermore, antibody-treated PGRN deficient hiMGL showed dampened microglial hyperactivation, reduced TREM2 signaling and phagocytic activity, however, lack of rescue of lysosomal dysfunction. Similarly, lysosomal dysfunction, lipid dysregulation and glucose hypometabolism ofGrnKO mice were not rescued by TREM2 ablation. Furthermore, NfL, a biomarker for neurodegeneration, was elevated in theGrn/Trem2KO. These findings suggest that microglia hyperactivation is not necessarily contributing to neurotoxicity, and instead demonstrates that TREM2 exhibits neuroprotective potential in this model.
Microbiome divergence of marine gastropod species separated by the Isthmus of Panama
Authors: Neu Alexander T. , Torchin Mark E. , Allen Eric E. , Roy Kaustuv 
Published: July 2021

AbstractThe rise of the Isthmus of Panama ~3.5 mya separated populations of many marine organisms, which then diverged into new geminate sister species currently living in the Eastern Pacific Ocean and Caribbean Sea. However, we know very little about how such evolutionary divergences of host species have shaped their microbiomes. Here, we compared the microbiomes of whole-body and shell-surface samples of geminate species of marine gastropods in the genera Cerithium and Cerithideopsis to those of congeneric outgroups. Our results show that the effects of the Isthmus on microbiome composition varied among host genera and between sample types within the same hosts. In the whole-body samples, microbiome compositions of geminate species pairs in the focal genera tended to be similar, likely due to host filtering, although the strength of this relationship varied among the two groups and across similarity metrics. Shell-surface communities showed contrasting patterns, with co-divergence between the host taxa and a small number of microbial clades evident in Cerithideopsis, but not Cerithium. These results suggest that (i) the rise of the Isthmus of Panama affected microbiomes of geminate hosts in a complex and clade-specific manner and (ii) host-associated microbial taxa respond differently to vicariance events than the hosts themselves.
Unraveling patterns of disrupted gene expression across a complex tissue
Authors: Hunnicutt Kelsie E. , Good Jeffrey M. , Larson Erica L. 
Published: July 2021

ABSTRACTWhole tissue RNASeq is the standard approach for studying gene expression divergence in evolutionary biology and provides a snapshot of the comprehensive transcriptome for a given tissue. However, whole tissues consist of diverse cell types differing in expression profiles, and the cellular composition of these tissues can evolve across species. Here, we investigate the effects of different cellular composition on whole tissue expression profiles. We compared gene expression from whole testes and enriched spermatogenesis populations in two species of house mice, Mus musculus musculus and M. m. domesticus, and their sterile and fertile F1 hybrids, which differ in both cellular composition and regulatory dynamics. We found that cellular composition differences skewed expression profiles and differential gene expression in whole testes samples. Importantly, both approaches were able to detect large-scale patterns such as disrupted X chromosome expression although whole testes sampling resulted in decreased power to detect differentially expressed genes. We encourage researchers to account for histology in RNASeq and consider methods that reduce sample complexity whenever feasible. Ultimately, we show that differences in cellular composition between tissues can modify expression profiles, potentially altering inferred gene ontological processes, insights into gene network evolution, and processes governing gene expression evolution.