bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical profile and factors associated with COVID-19 in Cameroon: a prospective cohort study
Authors: Mbarga Nicole Fouda , Emilienne Epee , Mbarga Marcel , Ouamba Patrick , Nanda Herwin , Kengni Aristide , Joseph Guekeme , Eyong Justin , Tossoukpe Sylvie , Sosso Noumedem Sauvia , Engelbert Ngono Ngono , Lazare Mbala Ntsama , Landry Bonyomo , Patrick Tchatchoua , Vogue Noel , Metomb Steve , Ale Franck , Ousman Moussa , Job Dorian , Charlotte Moussi , Tamakloe Modeste , Haberer Jessica E. , Atanga Ndesoh , Halle-Ekane Gregory , Boum Yap 
Published: February 2021

AbstractObjectivesThis study explores the clinical profiles and factors associated with COVID-19 in Cameroon.Research design and methodsIn this prospective cohort study, we followed patients admitted for suspicion of COVID-19 at Djoungolo Hospital between 01st April and 31st July 2020. Patients were categorised by age groups and disease severity: mild (symptomatic without clinical signs of pneumonia pneumonia), moderate (with clinical signs of pneumonia without respiratory distress) and severe cases (clinical signs of pneumonia and respiratory distress not requiring invasive ventilation). Demographic information and clinical features were summarised. Multivariable analysis was performed to predict risk.ResultsA total of 323 patients were admitted during the study period; 262 were confirmed cases of COVID-19 by Polymerase Chain Reaction (PCR). Among the confirmed cases, the male group aged 40 to 49 years (13.9%) was predominant. Disease severity ranged from mild (77%; N=204) to moderate (15%; N=40) to severe (7%; N=18); the case fatality rate was 1% (N=4). Dysgusia (46%; N=111) and hyposmia/anosmia (39%; N=89) were common features of COVID-19. Nearly one-third of patients had comorbidities (29%; N=53), of which hypertension was the most common (20%; N=48). Participation in a mass gathering (OR=5.47; P=0.03) was a risk factor for COVID-19. Age groups 60 to 69 (OR=7.41; P=0.0001), 50 to 59 (OR=4.09; P=0.03), 40 to 49 (OR=4.54; P=0.01), male gender (OR=2.53; P=0.04), diabetes (OR= 4.05; P= 0.01), HIV infection (OR=5.57; P=0.03), lung disease (OR= 6.29; P=0.01), dyspnoea (OR=3.70; P=0.008) and fatigue (OR=3.35; P=0.02) significantly predicted COVID-19 severity.ConclusionUnlike many high-income settings, most COVID-19 cases in this study were benign with low fatality. Such findings may guide public health decision-making.
An MRI-based Deep Learning Model to Predict Parkinson’s Disease Stages
Authors: Mozhdehfarahbakhsh Azadeh , Chitsazian Saman , Chakrabarti Prasun , Chakrabarti Tulika , Kateb Babak , Nami Mohammad 
Published: February 2021

AbstractParkinson’s disease (PD) is amongst the relatively prevalent neurodegenerative disorders with its course of progression classified as prodromal, stage1, 2, 3 and sever conditions. With all the shortcomings in clinical setting, it is often challenging to identify the stage of PD severity and predict its progression course. Therefore, there appear to be an ever-growing need need to use supervised and unsupervised artificial intelligence and machine learning methods on clinical and paraclinical datasets to accurately diagnose PD, identify its stage and predict its course. In today’s neuro-medicine practices, MRI-related data are regarded beneficial in detecting various pathologies in the brain. In addition, the field has recently witnessed a growing application of deep learning methods in image processing often with outstanding results. Here, we applied Convolutional Neural Networks (CNN) to propose a model helping to distinguish different stages of PD. The results showed that our current MRI-based CNN model may potentially be employed as a suitable method for the distinction of PD stages at a high accuracy rate (0.94).
Artificial Intelligence for Advance Requesting of Immunohistochemistry in Diagnostically Uncertain Prostate Biopsies
Authors: Chatrian Andrea , Colling Richard T , Browning Lisa , Alham Nasullah Khalid , Sirinukunwattana Korsuk , Malacrino Stefano , Haghighat Maryam , Aberdeen Alan , Monks Amelia , Moxley-Wyles Benjamin , Rakha Emad , Snead David R J , Rittscher Jens , Verrill Clare 
Published: February 2021

ABSTRACTThe use of immunohistochemistry in the reporting of prostate biopsies is an important adjunct when the diagnosis is not definite on haematoxylin and eosin (H&E) morphology alone. The process is however inherently inefficient with delays while waiting for pathologist review to make the request and duplicated effort reviewing a case more than once. In this study, we aimed to capture the workflow implications of immunohistochemistry requests and demonstrate a novel artificial intelligence tool to identify cases in which immunohistochemistry (IHC) is required and generate an automated request.We conducted audits of the workflow for prostate biopsies in order to understand the potential implications of automated immunohistochemistry requesting and collected prospective cases to train a deep neural network algorithm to detect tissue regions that presented ambiguous morphology on whole slide images. These ambiguous foci were selected on the basis of the pathologist requesting immunohistochemistry to aid diagnosis. A gradient boosted trees classifier was then used to make a slide level prediction based on the outputs of the neural network prediction. The algorithm was trained on annotations of 219 immunohistochemistry-requested and 80 control images, and tested by 3-fold cross-validation. Validation was conducted on a separate validation dataset of 212 images.Non IHC-requested cases were diagnosed in 17.9 minutes on average, while IHC-requested cases took 33.4 minutes over multiple reporting sessions. We estimated 11 minutes could be saved on average per case by automated IHC requesting, by removing duplication of effort. The tool attained 99% accuracy and 0.99 Area Under the Curve (AUC) on the test data. In the validation, the average agreement with pathologists was 0.81, with a mean AUC of 0.80.We demonstrate the proof-of-principle that an AI tool making automated immunohistochemistry requests could create a significantly leaner workflow and result in pathologist time savings.
Impact of the COVID-19 pandemic on the mental health of Greek adults: a cross-sectional survey
Authors: Dragotis Efthimios , Atsopardi Korina , Barbouni Anastasia , Poulas Konstantinos , Farsalinos Konstantinos 
Published: February 2021

AbstractObjectivesThe coronavirus disease 2019 (COVID-19) pandemic and mitigation measures based on social distancing are expected to have serious adverse effects on mental health. This cross-sectional study aimed to examine self-reported changes in the mental health status of Greek adults.Study designThe current study is a primary research conducted on Greek adults during the first wave of the epidemic (March to April 2020).MethodsA total of 527 individuals participated in an online survey using a validated questionnaire (State-Trait Anxiety Inventory-STAI and DASS-21).ResultsThe respondents had a moderate mental health status based on the following scores: STAI-S, 45.8; STAI-T, 40.7; depression, 4.6; anxiety, 3.1; and stress, 6.1. Women, younger respondents, those from lower income households, and those living in smaller apartments experienced increased depression, anxiety, and stress. Additionally, infection control practices during the COVID-19 pandemic such as the use of masks, gloves, and antiseptic can drastically decrease the prevalence of mental health illnesses.ConclusionsThese findings can be used by the Greek State to reduce the effects of COVID-19 on the mental health of the population and protect socially vulnerable groups.
Does Subthalamic Deep Brain Stimulation Impact Asymmetry and Dyscoordination of Gait in Parkinson’s Disease?
Authors: Ravi Deepak K , Baumann Christian R , Bernasconi Elena , Gwerder Michelle , König Ignasiak Niklas , Uhl Mechtild , Stieglitz Lennart , Taylor William R , Singh Navrag B 
Published: February 2021

AbstractBackgroundSubthalamic deep brain stimulation is an effective treatment for selected Parkinson’s disease patients. Axial deficits including postural stability and gait characteristics are often altered after surgery, but quantitative gait-related therapeutic effects are poorly described.ObjectiveThe goal of this study was to systematically investigate modifications in asymmetry and dyscoordination of gait six-months post-operatively in patients with Parkinson’s disease, and compare the outcomes with preoperative baseline and to asymptomatic controls.MethodsThirty-two patients with Parkinson’s disease (19 with postural instability and gait disorder type, 13 with tremor-dominant disease) and 51 asymptomatic controls participated. Parkinson patients were tested prior to the surgery in both OFF and ON medication states, and six months post-operatively in the ON stimulation condition. Clinical outcome parameters and medication were compared to preoperative conditions. Asymmetry ratios, phase coordination index, and walking speed were assessed.ResultsPatients’ clinical outcomes as assessed by standard clinical parameters at six-months improved significantly, and levodopa-equivalent daily dosages were significantly decreased. STN-DBS increased step time asymmetry (hedges’ g effect sizes [confidence intervals] between pre- and post-surgery: 0.27 [-0.13,0.73]) and phase coordination index (0.29 [-0.08,0.67]). These effects were higher in the Postural Instability and Gait Disorder subgroup than the Tremor Dominant (step time asymmetry: 0.38 [-0.06,0.90] vs. 0.09 [-0.83,1.0] and phase coordination index: 0.39 [-0.04,0.84] vs. 0.13 [-0.76,0.96]).ConclusionThis study provides objective evidence of how subthalamic deep brain stimulation increases asymmetry and dyscoordination of gait in patients with Parkinson’s disease, and suggests motor subtypes-associated differences in the treatment response.
Controlling the first wave of the COVID–19 pandemic in Malawi: results from a panel study
Authors: Banda Jethro , Dube Albert N. , Brumfield Sarah , Crampin Amelia C. , Reniers Georges , Amoah Abena S. , Helleringer Stéphane 
Published: February 2021

ABSTRACTMany African countries have experienced a first wave of the COVID–19 pandemic between June and August of 2020. According to case counts reported daily by epidemiological surveillance systems, infection rates remained low in most countries. This defied early models of the potential impact of COVID–19 on the continent, that projected large outbreaks and massive strain on health systems. Theories proposed to explain the apparently limited spread of the novel coronavirus in most African countries have emphasized 1) early actions by health authorities (e.g., border closures) and 2) biological or environmental determinants of the transmissibility of SARS-CoV-2 (e.g., warm weather, cross-immunity). In this paper, we explored additional factors that might contribute to the low recorded burden of COVID–19 in Malawi, a low-income country in Southeastern Africa. To do so, we used 4 rounds of panel data collected among a sample of adults during the first 6 months of the pandemic in the country. Our analyses of survey data on SARS-CoV-2 testing and COVID-related symptoms indicate that the size of the outbreak that occurred in June-August 2020 might be larger than recorded by surveillance systems that rely on RT-PCR testing. Our data also document the widespread adoption of physical distancing and mask use in response to the outbreak, whereas most measured patterns of social contacts remained stable during the course of the panel study. These findings will help better project, and respond to, future waves of the pandemic in Malawi and similar settings.
A cross-sectional study of socioeconomic status and treatment interruption among Japanese workers during the COVID-19 pandemic
Authors: Fujimoto Kenji , Ishimaru Tomohiro , Tateishi Seiichiro , Nagata Tomohisa , Tsuji Mayumi , Eguchi Hisashi , Ogami Akira , Matsuda Shinya , Fujino Yoshihisa ,   for the CORoNaWork Project
Published: February 2021

AbstractBackgroundThe COVID-19 pandemic has caused interruptions to chronic disease and non-emergency treatment. The purpose of this study is to examine which socioeconomic status groups are most at risk of treatment interruption.MethodsThis cross-sectional internet monitor study was conducted on December 22–26, 2020, when Japan experienced its third wave of COVID-19 infection. Out of a total of 33,302 participants in the survey, 9510 (5392 males and 4118 females) who responded that they required regular treatment or hospital visits were included in the analysis. A multilevel logistic model nested in the prefecture of residence was used to estimate the odds ratio (OR) for treatment disruption. We examined separate multivariate models for socioeconomic factors, health factors, and lifestyle factors.ResultsDuring a period of rapid COVID-19 infection, about 11% of Japanese workers who required regular treatment experienced interruptions to their treatment. The OR of treatment interruption associated with not being married compared to being married was 1.44; manual labor work compared to desk work was 1.30; loss of employment when the COVID-19 pandemic started and continued unemployment compared to being employed over the entire pandemic period was 1.62 and 2.57, respectively; and feeling financially unstable was 2.92.ConclusionTreatment interruption is a new health inequality brought about by COVID-19 with possible medium- and long-term effects, including excess mortality, morbidity, and productivity loss due to increased presenteeism. Efforts are needed to reduce treatment interruptions among workers who require regular treatment.
Estimating the spreading and dominance of SARS-CoV-2 VOC 202012/01 (lineage B.1.1.7) across Europe
Authors: Gozzi Nicolò , Chinazzi Matteo , Davis Jessica T. , Mu Kunpeng , y Piontti Ana Pastore , Ajelli Marco , Perra Nicola , Vespignani Alessandro 
Published: February 2021

AbstractWe develop a two strain, age-structured, compartmental model to assess the spreading potential of the B.1.1.7 variant across several European metropolitan areas and countries. The model accounts for B.1.1.7 introductions from the UK and different locations, as well as local mitigation policies in the time period 2020/09 − 2021/02. In the case of an increase of transmissibility of 50%, the B.1.1.7 variant has the potential to become dominant in all investigated areas by the end of March 2021.
Bone mechanoregulation allows subject-specific load estimation based on time-lapsed micro-CT and HR-pQCTin vivo
Authors: Walle Matthias , Marques Francisco C. , Ohs Nicholas , Blauth Michael , Müller Ralph , Collins Caitlyn J. 
Published: February 2021

AbstractPatients at high risk of fracture due to metabolic diseases frequently undergo long-term antiresorptive therapy. However, in some patients treatment is unsuccessful in preventing fractures or causes severe adverse health outcomes. Understanding load driven bone remodelling, i.e. mechanoregulation, is critical to understand which patients are at risk for progressive bone degeneration and may enable better patient selection or adaptive therapeutic intervention strategies. Bone microarchitecture assessment using high-resolution peripheral quantitative computed tomography (HR-pQCT) combined with computed mechanical loads has successfully been used to investigate bone mechanoregulation at the trabecular level. To obtain the required mechanical loads that induce local variances in mechanical strain and cause bone remodelling, estimation of physiological loading is essential. Yet, current models homogenise strain patterns throughout the bone to estimate load distributionin vivo, which may be a flawed assumption for investigating alterations in bone mechanoregulation. By further utilising available spatiotemporal information of time-lapsed bone imaging studies, we developed a mechanoregulation-based load estimation algorithm (MR). MR calculates organ scale loads by scaling and superimposing a set of predefined independent unit loads to optimise measured bone formation in high, quiescence in medium and resorption in low strain regions. We benchmarked our algorithm against a previously published load history algorithm (LH) using synthetic data, micro-CT images of murine vertebrae under defined experimentalin vivoloadings and HR-pQCT images from seven patients. Our algorithm consistently outperformed LH in all three datasets.In silicogenerated time evolutions of distal radius geometries (n = 5) indicated significantly higher sensitivity, specificity, and accuracy for MR than LH (p < 0.01). This increased performance led to substantially better discrimination between physiological and extra-physiological loading in mice (n = 8). Moreover, a significantly (p < 0.01) higher association between remodelling events and computed local mechanical signals were found using MR (CCR = 0.42) than LH (CCR = 0.38) to estimate human distal radius loading. Future applications of MR may enable clinicians to link subtle changes in bone strength to changes in day-to-day loading, identifying weak spots in the bone micro-structure for local intervention and personalised treatment approaches.
Heterogeneity and excitability ofBRAFV600E-induced tumors is determined by PI3K/mTOR-signaling state andTrp53-loss
Authors: Cases-Cunillera Silvia , van Loo Karen M. J. , Pitsch Julika , Quatraccioni Anne , Sivalingam Sugirthan , Salomoni Paolo , Dietrich Dirk , Schoch Susanne , Becker Albert J. 
Published: February 2021

AbstractBackgroundDevelopmental brain tumors harboringBRAFV600Esomatic mutation are diverse. Here, we describe molecular factors that determineBRAFV600E-induced tumor biology and function.MethodsIntraventricularin uteroelectroporation in combination with the piggyBac transposon system is employed as a tool to generate developmental brain neoplasms.In vivotumor growth is monitored by using the infrared fluorescent protein (iRFP). Lineage inference is carried out by using the Brainbow transgene. Neural activity from tumor slices is assessed by multielectrode array. RNA sequencing is exploited to analyze the induced neoplasms at the transcriptomic level.ResultsBRAFV600Ein murine neural progenitors only in concert with active PI3K/mTOR-signaling through constitutively phosphorylated Akt-kinase (pAkt) elicits benign neoplasms composed of enlarged dysmorphic neurons and neoplastic astroglia recapitulating ganglioglioma (GG). Purely glial tumors partially resembling polymorphous low-grade neuroepithelial tumors of the young (PLNTYs) emerge fromBRAFV600Ealone. Additional somaticTrp53-loss is sufficient to induce anaplastic GGs (aGGs) with glioneuronal clonality. Functionally, onlyBRAFV600E/pAkt tumors intrinsically generate substantial neuronal activity and show enhanced relay to adjacent tissue conferring high epilepsy propensity. In contrast, PLNTY- and aGG-models lack significant spike activity, which appears in line with the glial differentiation of the former and a dysfunctional tissue structure combined with reduced neuronal transcript signatures in the latter.ConclusionmTOR-signaling andTrp53-loss critically determine the biological diversity and electrical activity ofBRAFV600E-induced tumors.Key pointsIUE of BRAFV600Eand activation of mTOR leads to ganglioglioma (GG)-like tumors, while BRAFV600Ealone give rise to PLNTY-like neoplasms.Anaplastic GGs depend on the Trp53 deletion in combination to BRAFV600Eand PI3K-mTOR signaling cascade.Importance of the StudyGlioneuronal tumors are challenging with respect to biological behavior and seizure emergence. WhileBRAFV600Ein murine neural precursors induces oligoid tumors, it requires an overactivation of PI3K/mTOR-signaling for the development of hyperexcitable gangliogliomas and additionalTrp53-loss for anaplastic transformation.
E. colichemotaxis is information-limited
Authors: Mattingly H.H. , Kamino K. , Machta B.B. , Emonet T. 
Published: February 2021

AbstractOrganisms must acquire and use environmental information to guide their behaviors. However, it is unclear whether and how information quantitatively limits behavioral performance. Here, we relate information to behavioral performance inEscherichia colichemotaxis. First, we derive a theoretical limit for the maximum achievable gradient-climbing speed given a cell’s information acquisition rate. Next, we measure cells’ gradient-climbing speeds and the rate of information acquisition by the chemotaxis pathway. We find thatE. colimake behavioral decisions with much less than the 1 bit required to determine whether they are swimming up-gradient. However, they use this information efficiently, performing near the theoretical limit. Thus, information can limit organisms’ performance, and sensory-motor pathways may have evolved to efficiently use information from the environment.
Effect of Initial pH and Organic Matter Concentration on Production of Volatile Organic Acids Through Acidogenesis of Sugarcane Vinasse
Authors: Martins Juliana , de Araújo Hugo Valença , Mockaitis Gustavo , da Silva Ariovaldo José 
Published: February 2021

ABSTRACTSugarcane vinasse is an industrial liquid waste generated in great amounts in Brazilian ethanol industries. Nowadays its main use occurs at sugarcane crops, where vinasse is applied as a nutrient source for fertirrigation. However, continued use of vinasse in soil can cause several environmental impacts. So, aiming to provide a more environmentally friendly destination to the effluent, the goal of this work was to investigate the acidogenesis using a synthetic vinasse as substrate, focusing on the effects of initial pH and Chemical Oxygen Demand (COD) on short chain organic acids (SCOAs) concentrations. Synthetic vinasse was prepared at laboratory taking some real sugarcane vinasse composition given in previous works as references. So, major contribution presented here is the investigation on obtaining high added-value SCOAs from a simulated effluent. Cattle manure sludge was utilized as inoculum to promote the conversion of carbohydrate (sucrose, Suc) in synthetic vinasse into SCOAs in batch reactors during a total incubation time of 72 h. Acidogenesis profiles have shown that concentration of lactic acid (HLa) was prevailing among all metabolites, indicating that process followed through an essentially lactic route. Furthermore, considerable concentrations of propionic, acetic and isobutyric acids were also verified at some specific operation times, while solventogenesis was not detected at all. The greatest peak of lactate content was 4.96 g HLa L−1, observed under initial pH 6.0 and 25 g COD L−1, at 16 h. Maximum of lactate productivity was 332.10 g HLa L−1h−1at 8 h, associated to a yield of 189.14 g HLa (g Suc)−1, under initial pH 7.5 and 20 g COD L−1.
The G2-phase enriched lncRNASNHG26is necessary for proper cell cycle progression and proliferation
Authors: Samdal Helle , Hegre Siv A. , Chawla Konika , Liabakk Nina-Beate , Aas Per A. , Sporsheim Bjørnar , Sætrom Pål 
Published: February 2021

AbstractLong noncoding RNAs (lncRNAs) are involved in the regulation of cell cycle, although only a few have been functionally characterized. By combining RNA sequencing and ChIP sequencing of cell cycle synchronized HaCaT cells we have previously identified lncRNAs highly enriched for cell cycle functions. Based on a cyclic expression profile and an overall high correlation to histone 3 lysine 4 trimethylation (H3K4me3) and RNA polymerase II (Pol II) signals, the lncRNASNHG26was identified as a top candidate. In the present study we report that downregulation ofSNHG26affects mitochondrial stress, proliferation, cell cycle phase distribution, and gene expression incis- and intrans, and that this effect is reversed by upregulation ofSNHG26. We also find that the effect on cell cycle phase distribution is cell type specific and stable over time. Results indicate an oncogenic role ofSNHG26, possibly by affecting cell cycle progression through the regulation of downstream MYC-responsive genes.