bluuebunny/crossref_metadata_2025_split huggingface dataset:
The World Is Completely Unprepared For Detecting Emerging Viruses/Bacteria In The Air
Authors: Srikrishna Devabhaktuni 
Published: August 2022

AbstractThere is an immediate need for efficient networks to detect and control novel/emerging bioaerosol threats. In 2022, the Pentagon Force Protection Agency (PFPA) found detection of emerging bioaerosol threats to be “not feasible for daily operations” due to cost of reagents used for metagenomics, cost of sequencing instruments, and time/cost for labor (subject matter expertise) to analyze bioinformatics. If the Pentagon experiences these operational difficulties, they may also extend to many of the 280,000 buildings (2.3 billion square feet) at 5000 secure US DoD military sites, 250 US Navy ships, and beyond in civilian buildings around the world. These economic barriers can still be addressed in a threat-agnostic manner by dynamically pooling samples from a network of dry filter units (DFUs) to detect spatio-temporally correlated “spikes” in novel pathogen concentrations, termed Spike Triggered Virtualization (STV). In STV, pooling and sequencing depth are automatically modulated in the next cycle in response to novel potential biothreats in the sequencing output of the previous sequencing cycle. By running at a high pooling factor and lower depth unless triggered by a potential pathogen spike, average daily and annual cost per DFU can be reduced by one to two orders of magnitude depending on chosen trigger thresholds. Artificial intelligence (AI) can further enhance sensitivity of STV triggers. Risk of infection remains during the 12-24 hour window between a bioaerosol incident and its detection, but can in some cases be reduced by 80% or potentially more with high-speed indoor air cleaning exceeding 10 air changes per hour (10 ACH) similar to passenger airplanes (Airbus A319, A321 and a Boeing 737-Max8/9) that were tested in flight. Costs of 4 ACH or higher are expected to rise non-linearly with ACH using central HVAC systems and be cost-prohibitive. Whereas 10 ACH or more can be achieved economically by recycling the air in rooms with low-noise, portable air filtration systems tested herein for which costs scale linearly with ACH. For typical ceiling heights (< 10 ‘), the cost per square foot cost for low-noise air filtration exceeding 10 ACH was found to be approximately $0.5 to $1 for Do-It-Yourself (DIY) and $2 to $5 for HEPA.
An observational study on imported COVID-19 cases in Hong Kong during mandatory on-arrival hotel quarantine
Authors: Martín-Sánchez Mario , Wu Peng , Adam Dillon C. , Yang Bingyi , Lim Wey Wen , Lin Yun , Lau Eric H. Y. , Sullivan Sheena G. , Leung Gabriel M. , Cowling Benjamin J. 
Published: August 2022

ABSTRACTBackgroundHong Kong has enforced stringent travel restrictions particularly for inbound travellers since the emergence of SARS-CoV-2. Understanding the characteristics of imported COVID-19 cases is important for establishing evidence-based control measures.MethodsWe conducted a retrospective cohort study to summarise the characteristics of cases classified as imported cases that were detected on or soon after arrival into Hong Kong from 13 November 2020 through to 31 January 2022, when all arriving persons were required to quarantine in a hotel or a designated quarantine facility. We analysed individual demographics, and clinical information including symptoms and disease severity, virus variants, and Ct values.ResultsThere were 2269 imported COVID-19 cases aged 0-85 years identified in Hong Kong. Almost half (48.6%) of the imported cases were detected on arrival. A shorter median delay from arrival to isolation was observed in Delta and Omicron cases (3 days) than cases infected with the ancestral strain and other variants (12 days; p<0.001) while lower Ct values at isolation were observed in cases infected with Omicron than the ancestral strain or other variants. No Omicron cases were detected beyond 14 days after arrival, and the cases (n=58, 2.6%) detected after 14 days of quarantine more frequently presented without symptoms at isolation and had a higher RT-PCR Ct-value during isolation. At least some of these cases were post-arrival infections.ConclusionsTesting inbound travellers at arrival and during on-arrival quarantine can detect imported cases early although it may not be sufficient to prevent all introductions of COVID-19 into the community. Public health measures should be adjusted in responses to the emergence of new variants of SARS-CoV-2 based on the epidemiologic evidence from continuous surveillance.
Fair Reinforcement Learning for Maternal Sepsis Treatment
Authors: Carey Siân , McInerney Ciarán , Lawton Tom , Habli Ibrahim , Johnson Owen , Fahel Leila , Kotzé Alwyn , de Kamps Marc 
Published: August 2022

ABSTRACTObjectivesReinforcement Learning is a branch of artificial intelligence (AI) which has the potential to support significant improvement in patient care. There is concern that such approaches may reinforce existing biases within patient groups. Understanding discrimination in AI models is important for building trust and ensuring fair and safe use. We explore the fairness of a published reinforcement learning model, used to suggest drug dosages for sepsis treatment of patients in critical care, on whether it safe to use with maternal sepsis patients.MethodsWe evaluate the current model using by a) comparing the results for a group of patients with maternal sepsis against a matched control group and b) using random forests to explore feature importance in the model.ResultsOur results show that the original clinicians’ decisions and model suggestions were similar across cohorts. Our feature importance ranking shows high variance for many of the features.DiscussionIn medical settings, different subgroups may have specific clinical needs and require different treatment however, in the absence of a clinical consensus on the most appropriate treatment, AI algorithms that give consistent treatment to patients regardless of subgroup could be judged as the safest and fairest option.ConclusionOur experiments showed that the evaluated model gave the same treatment to maternal and non-maternal sepsis patients. The methods developed for evaluating fair reinforcement learning may be more generally applicable to understanding how clinical AI tools can be used for safely and fairly.What is already known on this topicThe use of reinforcement learning to suggest drug dosages for sepsis patients in critical care is a well-researched area, with multiple open-source models available. It has not previously been considered whether these models can be used on maternal sepsis patients.What this study addsThe model studied behaves consistently on maternal and non-maternal sepsis patients, and appears to suggest an increased use of vasopressors compared with historical actions.How this study might affect research, practice or policyThis study shows that it is possible to design models which are consistent across maternal and non-maternal sepsis patients, suggesting that a single model may be appropriate across a variety of patients with sepsis.
Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images
Authors: An Jeehye , Wendt Leo , Wiese Georg , Herold Tom , Rzepka Norman , Mueller Susanne , Koch Stefan Paul , Hoffmann Christian J. , Harms Christoph , Boehm-Sturm Philipp 
Published: August 2022

ABSTRACTMagnetic resonance imaging (MRI) is widely used for ischemic stroke lesion detection in mice. A challenge is that lesion segmentation often relies on manual tracing by trained experts, which is labor-intensive, time-consuming, and prone to inter- and intra-rater variability. Here, we present a fully automated ischemic stroke lesion segmentation method for mouse T2-weighted MRI data. As an end-to-end deep learning approach, the automated lesion segmentation requires very little preprocessing and works directly on the raw MRI scans. We randomly split a large dataset of 382 MRI scans into a subset (n = 293) to train the automated lesion segmentation and a subset (n = 89) to evaluate its performance. We compared Dice coefficients and accuracy of lesion volume against manual segmentation, as well as its performance on an independent dataset from an open repository with different imaging characteristics. The automated lesion segmentation produced segmentation masks with a smooth, compact, and realistic appearance that are in high agreement with manual segmentation.
Labeled lines for fat and sugar reward combine to promote overeating
Authors: McDougle Molly , de Araujo Alan , Vergara Macarena , Yang Mingxin , Singh Arashdeep , Braga Isadora , Urs Nikhil , Warren Brandon , de Lartigue Guillaume 
Published: August 2022

AbstractFood is a powerful natural reinforcer that guides feeding decisions. The vagus nerve conveys internal sensory information from the gut to the brain about nutritional value; however, the cellular and molecular basis of macronutrient-specific reward circuits are poorly understood. Here, we monitor in vivo calcium dynamics to provide direct evidence of independent vagal sensing pathways for detection of dietary fats and sugars. Using activity-dependent genetic capture of nutrient-specific vagal neurons activated in response gut infusions, we demonstrate the existence of separate hard-wired reward circuits for fat and sugar that are necessary and sufficient for nutrient-specific reinforcement. Even when controlling for calories, combined activation of fat and sugar circuits increases overeating compared to fat or sugar alone. This work provides new insight on the complex sensory circuitry that mediates motivated behavior and suggests that a subconscious internal drive to consume obesogenic diets (e.g., those high in both fat and sugar) may impede conscious dieting efforts.
Distinct encoding and post-encoding representational formats contribute to episodic sequence memory formation
Authors: Wu Xiongbo , Fuentemilla Lluís 
Published: August 2022

AbstractIn episodic encoding, an unfolding experience is rapidly transformed into a memory representation that binds separate episodic elements into a memory form to be later recollected. However, it is unclear how brain activity changes over time to accommodate the encoding of incoming information. This study aimed to investigate the dynamics of the representational format that contributed to memory formation of sequential episodes. We combined Representational Similarity Analysis and multivariate decoding approaches on EEG data to compare whether “category-level” or “item-level” representations supported memory formation during the online encoding of a picture triplet sequence and offline, in the period that immediately followed encoding. The findings revealed a gradual integration of category-level representation during the online encoding of the picture sequence and a rapid item-based neural reactivation of the encoded sequence at the episodic offset. However, we found that only memory reinstatement at episodic offset was associated with successful memory retrieval from long term memory. These results suggest that post-encoding memory reinstatement is crucial for the rapid formation of unique memory for episodes that unfold over time. Overall, the study sheds light on the dynamics of representational format changes that take place during the formation of episodic memories.
metGWAS 1.0: An R workflow for network-driven over-representation analysis between independent metabolomic and meta-genome wide association studies
Authors: Khan Saifur R. , Obersterescu Andreea , Gunderson Erica P. , Wheeler Michael B. , Cox Brian J. 
Published: August 2022

ABSTRACTBackgroundMany diseases may result from disrupted metabolic regulation. Metabolite-GWAS studies assess the association of polymorphic variants with metabolite levels in body fluids. While these studies are successful, they have a high cost and technical expertise burden due to combining the analytical biochemistry of metabolomics with the computational genetics of GWAS. Currently, there are 100s of standalone metabolomics and GWAS studies related to similar diseases or phenotypes. A method that could statically evaluate these independent studies to find novel metabolites-genes association is of high interest. Although such an analysis is limited to genes with known metabolite interactions due to the unpaired nature of the data sets, any discovered associations may represent biomarkers and druggable targets for treatment and prevention.MethodsWe developed a bioinformatics tool, metGWAS 1.0, that generates and statistically compares metabolic and genomic gene sets using a hypergeometric test. Metabolic gene sets are generated by mapping disease-associated metabolites to interacting proteins (genes) via online databases. Genomic gene sets are identified from a network representation of the GWAS Catalog comprising 100s of studies.ResultsThe metGWAS 1.0 tool was evaluated using standalone metabolomics datasets extracted from two metabolomics-GWAS case studies. In case-study 1, a cardiovascular disease association study, we identified nine genes (APOA5, PLA2G5, PLA2G2D, PLA2G2E, PLA2G2F, LRAT, PLA2G2A, PLB1, and PLA2G7) that interact with metabolites in the KEGG glycerophospholipid metabolism pathway and contain polymorphic variants associated with cardiovascular disease (P < 0.005). The gene APOA5 was matched from the original metabolomics-GWAS study. In case study 2, a urine metabolome study of kidney metabolism in healthy subjects, we found marginal significance (P = 0.10 and P = 0.13) for glycine, serine, and threonine metabolism and alanine, aspartate, and glutamate metabolism pathways to GWAS data relating to kidney disease.ConclusionThe metGWAS 1.0 platform provides insight into developing methods that bridge standalone metabolomics and disease and phenotype GWAS data. We show the potential to reproduce findings of paired metabolomics-GWAS data and provide novel associations of gene variation and metabolite expression.
The phosphatase Glc7 controls eisosomal response to starvation via posttranslational modification of Pil1
Authors: Paine Katherine M. , Laidlaw Kamilla M. E. , Evans Gareth J. O. , MacDonald Chris 
Published: August 2022

ABSTRACTThe yeast plasma membrane (PM) is organised into specific subdomains that regulate surface membrane proteins. Surface transporters actively uptake nutrients in particular regions of the PM where they are also susceptible to substrate induced endocytosis. However, transporters also diffuse into distinct subdomains termed eisosomes, where they are protected from endocytosis. Although most nutrient transporter populations are downregulated in the vacuole following glucose starvation, a small pool is retained in eisosomes to provide efficient recovery from starvation. We find the core eisosome subunit Pil1, a Bin, Amphiphysin and Rvs (BAR) domain protein required for eisosome biogenesis, is phosphorylated primarily by the kinase Pkh2. In response to acute glucose starvation, Pil1 is rapidly dephosphorylated. Enzyme localisation and activity screens implicate the phosphatase Glc7 is the primary enzyme responsible for Pil1 dephosphorylation. Both depletion ofGLC7and phospho-ablative or phospho-mimetic mutations of Pil1 correlate with Pil1 phosphorylation status, failure to properly retain transporters in eisosomes, and results in defective starvation recovery. We propose precise posttranslational control of Pil1 modulates nutrient transporter retention within eisosomes depending on extracellular nutrient levels, to maximise recovery following starvation.
Ligands tune the local and global motions of neurotensin receptor 1 (NTS1): a DFT-guided solution NMR analysis
Authors: Bumbak Fabian , Pons Miquel , Inoue Asuka , Paniagua Juan Carlos , Yan Fei , Wu Hongwei , Robson Scott A. , Bathgate Ross A. D. , Scott Daniel J. , Gooley Paul R. , Ziarek Joshua J. 
Published: August 2022

SummaryUnlike many signaling proteins that function as binary switches between ‘on and off’ states, G protein-coupled receptors (GPCRs) exhibit basal activity that can be increased or decreased by numerous ligands. A given receptor can recognize multiple ligands, allosteric modulators, and transducers to create a complex free energy landscape. Many of the lowest energy states have been captured by static structural techniques while detailing the wells’ widths, metastable states, and the transition between them, is still in its infancy. Nuclear magnetic resonance (NMR) spectroscopy can monitor the structure and dynamics of GPCR ensembles across fifteen orders-of-magnitude, but technical challenges have limited its application to super-microsecond timescales. Focusing on a prototypical peptide-binding GPCR, the neurotensin receptor 1 (NTS1), we employed NMR and density functional theory (DFT) to probe global sub-nanosecond motions. The near random coil chemical shifts of the apo receptor produced a poor correlation with theoretical predictions that may indicate a high degree of conformational averaging in solution, a crystallization artifact, or both. Whereas orthosteric agonists and antagonists both rigidified the receptor, but to varying degrees, which suggests conformational entropy differentially contributes to their respective pharmacology. The strong correlations of observed and theoretical chemical shifts lend confidence to interpreting spectra in terms of local structure, methyl dihedral angle geometry, and pico-second timescale transitions. Together, our results suggest a role for sub-nanosecond dynamics and conformational entropy in GPCR ligand discrimination.
Immunogenicity of an additional mRNA-1273 SARS-CoV-2 vaccination in people living with HIV with hyporesponse after primary vaccination
Authors: Jongkees Marlou J. , Geers Daryl , Hensley Kathryn S. , Huisman Wesley , GeurtsvanKessel Corine H. , Bogers Susanne , Gommers Lennert , Papageorgiou Grigorios , Jochems Simon P. , den Hollander Jan G. , Schippers Emile F. , Ammerlaan Heidi S.M. , Bierman Wouter F.W. , van der Valk Marc , Berrevoets Marvin A.H. , Soetekouw Robert , Langebeek Nienke , Bruns Anke H.W. , Leyten Eliane M.S. , Sigaloff Kim C.E. , van Vonderen Marit G.A. , Delsing Corine E. , Branger Judith , Katsikis Peter D. , Mueller Yvonne M. , de Vries Rory D. , Rijnders Bart J.A. , Brinkman Kees , Rokx Casper , Roukens Anna H.E. 
Published: August 2022

AbstractBackgroundThe COVIH study is a prospective SARS-CoV-2 vaccination study in people living with HIV (PLWH). Of the 1154 PLWH enrolled, 14% showed a reduced or absent antibody response after a primary vaccination regimen. As the response to an additional vaccination in PLWH with hyporesponse is unknown, we evaluated whether an additional vaccination boosts immune responses in these hyporesponders.MethodsConsenting hyporesponders received an additional 100 µg of mRNA-1273. Hyporesponse was defined as ≤300 spike(S)-specific binding antibody units [BAU]/mL. The primary endpoint was the increase in antibodies 28 days after the additional vaccination. Secondary endpoints were the correlation between patient characteristics and antibody response, levels of neutralizing antibodies, S-specific T-cell and B-cell responses, and reactogenicity.ResultsOf the 75 PLWH enrolled, five were excluded as their antibody level had increased to >300 BAU/mL at baseline, two for a SARS-CoV-2 infection before the primary endpoint evaluation and two were lost to follow-up. Of the 66 remaining participants, 40 previously received ChAdOx1-S, 22 BNT162b2, and four Ad26.COV2.S. The median age was 63 [IQR:60-66], 86% were male, pre-vaccination and nadir CD4+ T-cell counts were 650/μL [IQR:423-941] and 230/μL [IQR:145-345] and 96% had HIV-RNA <50 copies/ml. The mean antibody level before the additional vaccination was 35 BAU/mL (SEM 5.4) and 45/66 (68%) were antibody negative. After the additional mRNA-1273 vaccination, antibodies were >300 BAU/mL in 64/66 (97%) with a mean increase of 4282 BAU/mL (95%CI:3241-5323). No patient characteristics correlated with the magnitude of the antibody response nor did the primary vaccination regimen. The additional vaccination significantly increased the proportion of participants with detectable ancestral S-specific B-cells (p=0.016) and CD4+ T-cells (p=0.037).ConclusionAn additional mRNA-1273 vaccination induced a robust serological response in 97% of the PLWH with a hyporesponse after a primary vaccination regimen. This response was observed regardless of the primary vaccination regimen or patient characteristics.
Genome-wide association study of treatment resistant depression highlights shared biology with metabolic traits
Authors: Kang JooEun , Castro Victor M. , Ripperger Michael , Venkatesh Sanan , Burstein David , Linnér Richard Karlsson , Rocha Daniel B. , Hu Yirui , Wilimitis Drew , Morley Theodore , Han Lide , Kim Rachel Youngjung , Feng Yen-Chen Anne , Ge Tian , Heckers Stephan , Voloudakis Georgios , Chabris Christopher , Roussos Panos , McCoy Thomas H , Walsh Colin G. , Perlis Roy H. , Ruderfer Douglas M. 
Published: August 2022

AbstractTreatment resistant depression (TRD), often defined by absence of symptomatic remission following at least two adequate treatment trials, occurs in roughly a third of all individuals with major depressive disorder (MDD). Prior work has suggested a significant common variant genetic component of liability to TRD, with heritability estimates of 8% when comparing to non-treatment resistant MDD. Despite this evidence of heritability, no replicated genetic loci have been identified and the genetic architecture of TRD remains unclear. A key barrier to this work has been the paucity of adequately powered cohorts for investigation, largely because of the challenge in prospectively investigating this phenotype. Using electroconvulsive therapy (ECT) as a surrogate for TRD, we applied standard machine learning methods to electronic health record (EHR) data to derive predicted probabilities of receiving ECT. We applied these probabilities as a quantitative trait in a genome-wide association study (GWAS) over 154,433 genotyped patients across four large biobanks. With this approach, we demonstrate heritability ranging from 2% to 4.2% and significant genetic overlap with cognition, attention deficit hyperactivity disorder, schizophrenia, alcohol and smoking traits and body mass index. We identify two genome-wide significant loci, both previously implicated in metabolic traits, suggesting shared biology and potential pharmacological implications. This work provides support for the utility of estimation of disease probability for genomic investigation and provides insights into the genetic architecture and biology of TRD.
Multiple-region Gray Matter Atrophy contribute to freezing of gait in Parkinson’s Disease
Authors: Zhang Song , Huang Jie , Liu Dongzhen , Yin Yating , He Hua , Hu Kejia 
Published: August 2022

AbstractObjectiveThe aim of our study was to detect the localization of gray matter atrophy in FOG PD patients compared with nFOG PD patients.MethodsA total of 155 PD patients (110 men and 45 women) were included in the current study. Forty-five patients were classified as FOG and one hundred and ten patients were classified as nFOG. A voxel-based morphometry approach was used to investigate the atrophy area of voxel clusters in the gray matter which is associated with FOG.ResultsFOG and nFOG PD patients were not significantly different in gender, average age, educational years, disease duration or UPDRS-part I. Compared with nFOG PD patients, FOG patients showed gray matter atrophy in right Inferior frontal gyrus (opercular part), left Superior frontal gyrus, left Superior temporal gyrus, left Amygdala, left Insula, left Medial superior frontal gyrus and left Medial frontal gyrus (orbital gyrus).ConclusionOur study identified new gray matter atrophy areas in FOG PD patients compared with nFOG patients.