bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Systematic Review of Mutations Associated with Isoniazid Resistance Points to Lower Diagnostic Sensitivity for Common Mutations and Increased Incidence of Uncommon Mutations in Clinical Strains of Mycobacterium tuberculosis
Authors: Valafar Siavash J. 
Published: June 2020

ABSTRACTMolecular testing is rapidly becoming integral to the global tuberculosis (TB) control effort. Uncommon mechanisms of resistance can escape detection by these platforms and lead to the development of Multi-Drug Resistant (MDR) strains. This article is a systematic review of published articles that reported isoniazid (INH) resistance-conferring mutations between September-2013 and December-2019. The aims were to catalogue mutations associated with INH resistance, estimate their global prevalence and co-occurrence, and their utility in molecular diagnostics. The genes commonly associated with INH resistance, katG, inhA, fabG1, and the intergenic region oxyR’-ahpC were considered in this review. In total, 52 articles were included describing 5,632 INHR clinical isolates from 31 countries. The three most frequently mutated loci continue to be katG315 (4,100), inhA-15 (786), and inhA-8 (105). However, the diagnostic value of inhA-8 is far lower than previously thought, only appearing in 25 (0.4%) INHR isolates that lacked a mutation at the first two loci. Importantly, of the four katG loci recommended by the previous systematic review for diagnostics, only katG315 was observed in our INHR isolates. This indicates continued evolution and regional differences in INH resistance. We have identified 58 loci (common to both systematic reviews) in three genomic regions as a reliable basis for molecular diagnostics. We also catalogue mutations at 49 new loci associated with INH resistance. Including all observed mutations provides a cumulative sensitivity of 85.1%. The most disconcerting is the remaining 14.9% of isolates that harbor an unknown mechanism of resistance, will escape molecular detection, and likely convert to MDR-TB, further complicating treatment. Integrating the information cataloged in this and other similar studies into current diagnostic tools is essential for combating the emergence of MDR-TB. Exclusion of this information will lead to an “unnatural” selection which will result in eradication of the common but propagation of the uncommon mechanisms of resistance, leading to ineffective global published articles that reported isoniazid (INH) resistance-conferring mutations between describing 5,632 INHR clinical isolates from 31 countries. The three most frequently mutated treatment policy and a need for region-specific regiments. Finally, the observance of many low-frequency resistance-conferring mutations point to an advantage of platforms that consider regions rather than specific loci for detection of resistance.
The Chest CT Features of Coronavirus Disease 2019 (COVID-19) in China: A Meta-analysis of 19 Trials
Authors: Yang Haitao , Lan Yuzhu , Yao Xiujuan , Lin Sheng , Xie Baosong 
Published: June 2020

AbstractObjectiveThis study aimed to summarize the characteristics of chest CT imaging in Chinese patients with Coronavirus Disease 2019 (COVID-19) to provide reliable evidence for further guiding clinical routine.MethodsPubMed, Embase and Web of Science databases were thoroughly searched to identified relevant articles involving the features of chest CT imaging in Chinese patients with COVID-19. All data were analyzed utilizing R software version i386 4.0.0. Random-effects models were employed to calculate pooled mean differences.Results19 trials incorporating 1332 cases were included in the study. The results demonstrated that the incidence of ground-glass opacities (GGO) was 0.79, consolidation was 0.34; mixed GGO and consolidation was 0.46; air bronchogram sign was 0.41; crazy paving pattern was 0.32; interlobular septal thickening was 0.55; reticulation was 0.30; bronchial wall thickening was 0.24; vascular enlargement was 0.74. subpleural linear opacity was 0.28; intrathoracic lymph node enlargement was 0.03; pleural effusions was 0.03. The distribution in lung: the incidence of central was 0.05; peripheral was 0.74; peripheral involving central was 0.38; diffuse was 0.19; unifocal involvement was 0.09; multifocal involvement was 0.57; unilateral was 0.16; bilateral was 0.83; The incidence of lobes involved (>2) was 0.70; lobes involved (≦2) was 0.35.ConclusionGGO, vascular enlargement, interlobular septal thickening more frequently occurred in patients with COVID-19. Peripheral, bilateral, involved lobes >2 might be the features of COVID-19 in the distribution aspect. Therefore, based on the aboved features of COVID-19 in chest CT imaging, it might be a promising means for identifying COVID-19.
Clinical identification of malignant pleural effusions
Authors: Jia Jianlong , Marazioti Antonia , Voulgaridis Apostolos , Psallidas Ioannis , Lamort Anne-Sophie , Iliopoulou Marianthi , Krontira Anthi C. , Lilis Ioannis , Asciak Rachelle , Kanellakis Nikolaos I. , Rahman Najib M. , Karkoulias Kyriakos , Spiropoulos Konstantinos , Liu Ruonan , Kaiser Jan-Christian , Stathopoulos Georgios T. 
Published: June 2020

ABSTRACTImportancePleural effusions frequently signal disseminated cancer. Diagnostic markers of pleural malignancy at presentation that would assess cancer risk and would streamline diagnostic decisions remain unidentified.ObjectiveThe present study aimed at identifying and validating predictors of malignant pleural effusion at patient presentation.DESIGN, SETTING, AND PARTICIPANTSA consecutive cohort of 323 patients with pleural effusion (PE) from different etiologies were recruited between 2013-2017 and was retrospectively analyzed. Data included history, chest X-ray, and blood/pleural fluid cell counts and biochemistry. Group comparison, receiver-operator characteristics, unsupervised hierarchical clustering, binary logistic regression, and random forests were used to develop the malignant pleural effusion detection (MAPED) score. MAPED was validated in an independent retrospective UK cohort (n= 238).Main Outcomes and MeasuresThe outcome was diagnostic of pleural effusion in patients, and the clinical and laboratory indicators available of the patient were measured.ResultsFive variables showed significant diagnostic power and were incorporated into the 5-point MAPED score. Age > 55 years, effusion size > 50% of the most affected lung field, pleural neutrophil count < 2,500/mm3, effusion protein > 3.5 g/dL, and effusion lactate dehydrogenase > 250 U/L, each scoring one point, predicted underlying cancer with the area under curve(AUC) = 0.819 (sensitivity=82%, specificity=74%,P< 10-15) in the derivation cohort. The AUC and net reclassification improvement (NRI) of MAPED score and cytology were not significantly different. However, the integrated discrimination improvement (IDI) of The MAPED score displayed a slight increment(P<0.001). The calibration curves of the cytology model were slightly better than The MAPED score. Decision curve analysis (DCA) indicated that The MAPED score generated net clinical benefit. In the validation dataset, the results were generally consistent with the above findings, with an AUC of 0.723 (sensitivity=76%, specificity=62%, P =3*10-9) for The MAPED score. Interestingly, MAPED correctly identified 33/42(79%) of cytology-negative patients that indeed had cancer. The MAPED score is used to create nomogram so clinicians can predict the probability of malignant pleural effusions.ConclusionsThe MAPED score identifies malignant pleural effusions with satisfactory accuracy and can be used complementary to cytology to streamline diagnostic procedures.
Covid-19 and Population Age Structure
Authors: Haridas Ajit , Prathap Gangan 
Published: June 2020

AbstractEpidemiological studies suggest that age distribution of a population has a non-trivial effect on how morbidity rates, mortality rates and case fatality rates (CFR) vary when there is an epidemic or pandemic. We look at the empirical evidence from a large cohort of countries to see the sensitivity of Covid-19 data to their respective median ages. The insights that emerge could be used to control for age structure effects while investigating other factors like cross-protection, comorbidities, etc.
A Projection Model of COVID-19 Pandemic for Belgium
Authors: Ruzhansky Michael , Tokmagambetov Niyaz , Torebek Berikbol T. 
Published: June 2020

AbstractWe consider a simple model for the COVID-19 pandemic to analyse the relative effectiveness of several stages of the lockdown in Belgium, as well as of several phases of its relaxation. We also make a future projection of different types of measures relative to different stages of the already experienced lockdown.
Model Based Covid-19 Case Studies in the UK, the USA and India
Authors: Basu Santanu 
Published: June 2020

ABSTRACTTime dependent spread of Covid-19 among the population of the UK, the USA and India is analyzed using a recently developed mathematical model [1-3]. Results of model predictions of case growth in these countries during the next six weeks are also presented. The model is applicable to case studies and near term predictions for other countries and regions.
Roadmap to Help Develop Personalized Targeted Treatments for Autism as a Disorder of the Nervous Systems
Authors: Torres Elizabeth B 
Published: June 2020

AbstractThere is a disconnect between the clinical behavioral definition of autism and the genomic science that this definition largely informs and steers. But the digital sensor revolution paired with open access to genomics data has the potential to bridge the gap between these two layers of knowledge. Here we use the SFARI genes module and interrogate the human genome upon removing those genes. We then compare the remaining genes’ expression on tissues responsible for brain, heart and organs function to its counterpart in well-known neurological disorders of genetic origins. Despite clinical criteria emphasizing a behavioral definition of Autism, over a neurological one, here we find convergence between Autism and the neurological disorders. Tissues involved in motor control, emotions and memory are the most affected by the removal of the SFARI Autism genes. Congruent with this picture, the Ataxias, Parkinson’s disease and Fragile X share 76.9% of the most affected tissues, including those related to motor control and autonomic function, while mitochondria disorder share 61.5% with autism. Together, these results offer a new roadmap to help diagnosis and personalized targeted treatments of autism. They underscore Autism as an objectively quantifiable disorder of the nervous systems.
Inhibition of Angiotensin II Dependent AT1a Receptor Stimulation Attenuates Thoracic Aortic Pathology in Fibrillin-1C1041G/+Mice
Authors: Chen Jeff Z. , Sawada Hisashi , Moorleghen Jessica J. , Franklin Michael K. , Howatt Deborah A. , Sheppard Mary B. , Mullick Adam E. , Lu Hong S. , Daugherty Alan 
Published: June 2020

AbstractGraphic AbstractObjectiveA cardinal feature of Marfan syndrome is thoracic aortic aneurysm (TAA). The contribution of ligand-dependent stimulation of angiotensin II receptor type 1a (AT1aR) to TAA progression remains controversial because the beneficial effects of angiotensin receptor blockers have been ascribed to off-target effects. This study used genetic and pharmacologic modes of attenuating angiotensin receptor and ligand, respectively, to determine their roles on TAA in mice with fibrillin-1 haploinsufficiency (Fbn1C1041G/+).Approach and ResultsTAA in Fbn1C1041G/+mice were determined in both sexes and found to be strikingly sexual dimorphic. Males displayed progressive dilation over 12 months while ascending aortic dilation in Fbn1C1041G/+females did not differ significantly from wild type mice. To determine the role of AT1aR, Fbn1C1041G/+mice that were either +/+ or −/− for AT1aR were generated. AT1aR deletion reduced progressive expansion of ascending aorta and aortic root diameter from 1 to 12 months of age in males. Medial thickening and elastin fragmentation were attenuated. An antisense oligonucleotide against angiotensinogen (AGT-ASO) was administered to male Fbn1C1041G/+mice to determine the effects of angiotensin II depletion. AGT-ASO administration, at doses that markedly reduced plasma AGT concentrations, attenuated progressive dilation of the ascending aorta and aortic root. AGT-ASO also reduced medial thickening and elastin fragmentation.ConclusionsGenetic approaches to delete AT1aR and deplete AngII production exerted similar effects in attenuating pathology in the proximal thoracic aorta of male Fbn1C1041G/+mice. These data are consistent with ligand (AngII) dependent stimulation of AT1aR being responsible for aortic disease progression.HighlightsProfound sexual dimorphism of aortic disease occurs in Fbn1C1041G/+mice, with female mice being more resistant and male mice being more susceptible.Inhibition of the AngII-AT1aR axis attenuates aortic pathology in male Fbn1C1041G/+mice.Antisense oligonucleotides targeting angiotensinogen deplete plasma angiotensinogen and attenuate thoracic aortic aneurysms.
“Estimating abundance and phenology from transect count data with GLMs”
Authors: Edwards Collin , Crone Elizabeth E. 
Published: June 2020

AbstractEstimating population abundance is central to population ecology. With increasing concern over declining insect populations, estimating trends in abundance has become even more urgent. At the same time, there is an emerging in interest in quantifying phenological patterns, in part because phenological shifts are one of the most conspicuous signs of climate change. Existing techniques to fit activity curves (and thus both abundance and phenology) to repeated transect counts of insects (a common form of data for these taxa) frequently fail for sparse data, and often require advanced knowledge of statistical computing. These limitations prevent us from understanding both population trends and phenological shifts, especially in the at-risk species for which this understanding is most vital. Here we present a method to fit repeated transect count data with Gaussian curves using linear models, and show how robust abundance and phenological metrics can be obtained using standard regression tools. We then apply this method to eight years of Baltimore checkerspot data using generalized linear models (GLMs). This case study illustrates the ability of our method to fit even years with only a few non-zero survey counts, and identifies a significant negative relationship between population size and annual variation in thermal environment (in growing degree days). We believe our new method provides a key tool to unlock previously-unusable sparse data sets, and may provide a useful middle ground between ad hoc metrics of abundance and phenology and custom-coded mechanistic models.
Prefrontal and Parietal Attractor Networks Mediate Working Memory Judgments
Authors: Li Sihai , Constantinidis Christos , Qi Xue-Lian 
Published: June 2020

ABSTRACTThe dorsolateral prefrontal cortex plays a critical role in spatial working memory and its activity predicts behavioral responses in delayed response tasks. Here we addressed whether this predictive ability extends to categorical judgments based on information retained in working memory, and is present in other brain areas. We trained monkeys in a novel, Match-Stay, Nonmatch-Go task, which required them to observe two stimuli presented in sequence with an intervening delay period between them. If the two stimuli were different, the monkeys had to saccade to the location of the second stimulus; if they were the same, they held fixation. Neurophysiological recordings were performed in areas 8a and 46 of the dlPFC and 7a and lateral intraparietal cortex (LIP) of the PPC. We hypothesized that random drifts causing the peak activity of the network to move away from the first stimulus location and towards the location of the second stimulus would result in categorical errors. Indeed, for both areas, when the first stimulus appeared in a neuron’s preferred location, the neuron showed significantly higher firing rates in correct than in error trials. When the first stimulus appeared at a nonpreferred location and the second stimulus at a preferred, activity in error trials was higher than in correct. The results indicate that the activity of both dlPFC and PPC neurons is predictive of categorical judgments of information maintained in working memory, and the magnitude of neuronal firing rate deviations is revealing of the contents of working memory as it determines performance.SIGNIFICANCE STATEMENTThe neural basis of working memory and the areas mediating this function is a topic of controversy. Persistent activity in the prefrontal cortex has traditionally been thought to be the neural correlate of working memory, however recent studies have proposed alternative mechanisms and brain areas. Here we show that persistent activity in both the dorsolateral prefrontal cortex and posterior parietal cortex predicts behavior in a working memory task that requires a categorical judgement. Our results offer support to the idea that a network of neurons in both areas act as an attractor network that maintains information in working memory, which informs behavior.
Physiological noise modeling in fMRI based on the pulsatile component of photoplethysmograph
Authors: Kassinopoulos Michalis , Mitsis Georgios D. 
Published: June 2020

AbstractThe blood oxygenation level-dependent (BOLD) contrast mechanism allows the noninvasive monitoring of changes in deoxyhemoglobin content. As such, it is commonly used in functional magnetic resonance imaging (fMRI) to study brain activity since levels of deoxyhemoglobin are indirectly related to local neuronal activity through neurovascular coupling mechanisms. However, the BOLD signal is severely affected by physiological processes as well as motion. Due to this, several noise correction techniques have been developed to correct for the associated confounds. The present study focuses on cardiac pulsatility fMRI confounds, aiming to refine model-based techniques that utilize the photoplethysmograph (PPG) signal. Specifically, we propose a new technique based on convolution filtering, termed cardiac pulsatility model (CPM) and compare its performance with the cardiac-related RETROICOR (Card-RETROICOR), which is a technique commonly used to model fMRI fluctuations due to cardiac pulsatility. Further, we investigate whether variations in the amplitude of the PPG pulses (PPG-Amp) covary with variations in amplitude of pulse-related fMRI fluctuations, as well as with the systemic low frequency oscillations (SLFOs) component of the fMRI global signal (GS – defined as the mean signal across all gray matter voxels). Capitalizing on 3T fMRI data from the Human Connectome Project, CPM was found to explain a significantly larger fraction of the fMRI signal variance compared to Card-RETROICOR, particularly for subjects with larger heart rate variability during the scan. The amplitude of the fMRI pulse-related fluctuations did not covary with PPG-Amp; however, PPG-Amp explained significant variance in the GS that was not attributed to variations in heart rate or breathing patterns. Our results suggest that the proposed approach can model high-frequency fluctuations due to pulsation as well as low-frequency physiological fluctuations more accurately compared to model-based techniques commonly employed in fMRI studies.
TeamTree analysis: a new approach to evaluate scientific production
Authors: Pfrieger Frank W. 
Published: June 2020

AbstractAdvances in science and technology depend on the work of research teams and the publication of results through peer-reviewed articles representing a growing socio-economic resource. Current methods to mine the scientific literature regarding a field of interest focus on content, but the workforce credited by authorship remains largely unexplored, and appropriate measures of scientific production are debated. Here, a new bibliometric approach named TeamTree analysis is introduced that visualizes the development and composition of the workforce driving a field. A new citation-independent measure that scales with the H index estimates impact based on publication record, genealogical ties and collaborative connections. This author-centered approach complements existing tools to mine the scientific literature and to evaluate research across disciplines.
Relatedness and genetic structure of big brown bat (Eptesicus fuscus) maternity colonies in an urban-wildland interface provides insight into rabies transmission dynamics
Authors: Walker Faith M. , Sobek Colin J. , Platts-McPharlin Camille E. , Chambers Carol L. 
Published: June 2020

AbstractBig brown bats (Eptesicus fuscus) are the bat species most frequently found to be rabid in North America and are a key source of sylvatic rabies in wildlife. Females can form summer maternity colonies in urban areas, often using access holes in the exterior of buildings to roost in relatively large numbers. In Flagstaff, Arizona, these roosts are commonly found in houses adjacent to golf courses, where habitat quality (food, water, shelter) is high for bats and for mesocarnivores such as striped skunks (Mephitis mephitis) and gray foxes (Urocyon cinereoargenteus). Periodic rabies outbreaks in Flagstaff involving all three of these mammals are primarily caused by anE. fuscusvariant of the disease. However, little is known aboutE. fuscussocial behavior during the summer months and how it may drive space use and hence disease exposure to conspecifics and mesocarnivores. To address this knowledge gap, we collected 88 unique genetic samples via buccal swabs fromE. fuscuscaptured at four maternity roosts surrounding a golf course during summer of 2013. We used 7 microsatellite loci to estimate genetic relatedness among individuals and genetic structure within and among colonies in order to infer whether females selected roosts based on kinship, and used genetics and radio telemetry to determine the frequency of roost switching. We found roost switching through genetics (two mother and adult daughter pairs at the same and different roosts) and telemetry, and no evidence of elevated genetic relatedness within colonies or genetic structure between colonies. These results have important implications for disease transmission dynamics in that social cohesion based on relatedness does not act to constrain the virus to a particular roost area. Instead, geographic mobility may increase disease exposure to neighboring areas. We discuss mitigating actions for bat conservation and public health.