bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of Blood-Based Exosomes as Biomarkers for Aging-Related TDP-43 pathology
Authors: Winston Charisse N. , Sukreet Sonal , Lynch Haley , Lee Virginia M.-Y. , Wilcock Donna M. , Nelson Peter T. , Rissman Robert A. 
Published: June 2022

ABSTRACTINTRODUCTIONLimbic predominant age related TDP-43 encephalopathy (LATE) is a recently characterized brain disease that mimics Alzheimer’s disease (AD) clinically. To date, LATE is difficult to diagnose antemortem using clinical information or biomarkers. Recent studies suggest concentrations of exosomal protein cargo derived from neuronal and glial cells may serve as useful diagnostic biomarkers for AD and other neurodegenerative diseases.METHODSTDP-43 was evaluated in neuronal (NDE), astrocyte (ADE), and microglial derived exosomes (MDE). Exosome preparations were isolated from the plasma of research subjects with autopsy-confirmed diagnoses, including many with LATE. Quantified TDP-43 concentrations were compared to cohort that included healthy controls, mild cognitively impairment (MCI), and AD dementia with diagnoses other than LATE.RESULTSTDP-43 was significantly elevated in plasma ADEs derived from autopsy confirmed LATE-NC subjects, with or without comorbid AD pathology. Measurable levels of TDP-43 were also detected in exosome depleted plasma; however, TDP-43 levels were not significantly different between persons with and without eventual autopsy confirmed LATE-NC. No correlation was observed between exosomal TDP-43 levels with cognition-based variables, sex, and APOE carrier status.DISCUSSIONBlood-based exosomes, specifically measuring TDP-43 accumulation in ADEs, may serve as a powerful diagnostic tool to rapidly identify subjects who are currently living with LATE-NC.
Spatial learning overshadows learning novel odors and sounds in both a predatory and a frugivorous bat
Authors: Dixon M. May , Carter Gerald , Ryan Michael J. , Page Rachel A. 
Published: June 2022

AbstractTo be efficient while foraging, animals should be selective about attending to and remembering the cues of food that best predict future meals. One hypothesis is that animals with different foraging strategies should vary in their reliance on spatial and feature cues. Animals that store food or feed on spatially stable food, like fruit or flowers, should be predisposed to learning a meal’s location, whereas predators that hunt mobile prey should instead be biased towards learning feature cues such as color or sound. Previous studies suggest that nectar- and fruit-feeding bats should rely relatively more on spatial cues, whereas predatory bats should rely more on feature cues, yet no experiment has compared these two foraging strategies under the same conditions. To test this hypothesis, we compared learning in the frugivorous bat, Artibeus jamaicensis, and the predatory bat, Lophostoma silvicolum, which hunts katydids using acoustic cues. We trained bats to find food paired with a unique odor, sound, and location. We then dissociated these cues to assess which cue each bat had learned. Rather than finding that the frugivore and predator are on opposite ends of a continuum in their relative reliance on spatial and feature cues, we found that both species learned spatial cues with no evidence that either learned the sounds or odors. We discuss interpretations of these results in the context of past work on use of spatial cues versus feature cues. Compared to feature cues, spatial cues may be fundamentally more rich, salient, or memorable.Lay SummaryWhen animals learn how to obtain food, they could attend to many possible cues—such as the associated smells, sights, sounds, or locations of the food. It has been hypothesized that natural selection has shaped animals to pay particular attention to the types of cues that are most useful for finding their typical food. In bats, this would predict that predatory species that hunt mobile, noisy insects by sound should be biased towards learning a food-associated sound, whereas bats that eat stationary and silent fruit should be biased towards learning a food’s location. We gave predatory and fruit-eating bats the opportunity to simultaneously learn food-rewarded odors, sounds, or locations.Regardless of their diets, both species of bats learned locations rather than the odors or sounds associated with food. Spatial cues may be particularly rich or salient, and when they are reliable, animals may use them for learning over other cues regardless of their typical food.
Metabolomic profiles of human glioma inform patient survival
Authors: Scott Andrew J. , Correa Luis O. , Sun Yilun , Ravikumar Visweswaran , Andren Anthony C. , Zhang Li , Srinivasan Sudharsan , Jairath Neil , Verbal Kait , Muraszko Karin , Sagher Oren , Carty Shannon A. , Hervey-Jumper Shawn , Orringer Daniel , Kim Michelle M. , Junck Larry , Umemura Yoshie , Leung Denise , Venneti Sriram , Camelo-Piragua Sandra , Lawrence Theodore S. , Ippolito Joseph E. , Al-Holou Wajd N. , Chinnaiyan Prakash , Heth Jason , Rao Arvind , Lyssiotis Costas A. , Wahl Daniel R. 
Published: June 2022

AbstractAimsTargeting tumor metabolism may improve the outcomes for patients with glioblastoma (GBM). To further preclinical efforts targeting metabolism in GBM, we tested the hypothesis that brain tumors can be stratified into distinct metabolic groups with different patient outcomes. Therefore, to determine if tumor metabolites relate to patient survival, we profiled the metabolomes of human gliomas and correlated metabolic information with clinical data.ResultsWe found that isocitrate dehydrogenase-wildtype (IDHwt) GBMs are metabolically distinguishable from IDH mutated (IDHmut) astrocytomas and oligodendrogliomas. Survival of patients with IDHmut gliomas was expectedly more favorable than those with IDHwt GBM, and metabolic signatures can stratify IDHwt GBMs subtypes with varying prognoses. Patients whose GBMs were enriched in amino acids had improved survival while those whose tumors were enriched for nucleobases and carbohydrates fared more poorly. These findings were recapitulated in validation cohorts using both metabolomic and transcriptomic data.InnovationOur results suggest the existence of metabolic subtypes of GBM with differing prognoses and further support the concept that metabolism may drive the aggressiveness of human gliomas.ConclusionsOur data show that metabolic signatures of human gliomas can inform patient survival. These findings may be used clinically to tailor novel metabolically targeted agents for GBM patients with different metabolic phenotypes.
Pronounced state-level variation in prescription cannabinoids to Medicaid patients
Authors: Liu Edward Y. , McCall Kenneth L. , Piper Brian J. 
Published: June 2022

AbstractDronabinol is approved for chemotherapy induced nausea as well as vomiting and HIV-induced anorexia, while cannabidiol is primarily approved for childhood epileptic disorders Lennox-Gastaut and Dravet syndrome. The use pattern for these prescription cannabinoids in the US is unknown. This study analyzed Medicaid claims for dronabinol and cannabidiol prescriptions from 2016-2020. Dronabinol prescriptions decreased by 25.3% from 2016 to 2020 while cannabidiol prescriptions increased by 16,272.99 % from 2018 to 2020. The spending on these drugs parallels that on their prescription trend with a 66.3% decrease in reimbursement for dronabinol ($5.7 million in 2020), whereas that of cannabidiol increased by +26,582.0% ($233.3 million in 2020). Dronabinol prescriptions in Connecticut were 136.4 times larger than New Mexico and 17 states had zero prescriptions. Idaho prescriptions, when corrected for number of enrollees, were 15.4-fold higher than Washington DC. Prescribing of dronabinol and cannabidiol did not differ significantly based on the whether the state had an active medical marijuana program. The prescriptions of pharmaceutical grade tetrahydrocannabinol were decreasing while cannabidiol was increasing. This study also identified pronounced state level variation in cannabinoid prescribing to Medicaid patients. Further research to identify the origins of these disparities is needed.
Improved Version of ChETA Promotes Aggression in the Medial Amygdala
Authors: Hu Rongfeng K. , Chen Patrick B. , Berndt André , Anderson David J. , Hong Weizhe 
Published: June 2022

AbstractThe development of optogenetic tools has significantly advanced our understanding of neural circuits and behavior. The medial amygdala, posterior dorsal subdivision (MeApd) is part of a distributed network controlling social behaviors such as mating and aggression. Previous work showed that activation of GABAergic neurons in mouse MeApd using channelrodopsin-2 (ChR2H134R) promoted aggression. In a recent study, Baleisyte et al. (2022) confirmed these findings using the same reagents (i.e. ChR2H134R), but also reported that a different ChR2 variant with faster kinetics—ChETA—inhibited rather than promoted aggression when high laser power, long duration photostimulation conditions were used. As ChETA is known to have a substantially lower photocurrent than ChR2 and other opsins, an improved version of ChETA (i.e. ChR2E123T/T159C; ChETATC) was subsequently developed. ChETATC has larger photocurrents than the original ChETA while maintaining fast kinetics and low plateau depolarization. Here we show that activating MeApd GABAergic neurons using the improved ChETATC promotes aggression, similar to ChR2H134R, suggesting that the results obtained using the original ChETA are not due to a difference in channel kinetics. Furthermore, we found that ChETATC is capable of driving a rapid onset of aggression within 200-300 milliseconds of stimulation, suggesting that this effect reflects direct activation of MeApd GABAergic neurons. We conclude that the different behavioral phenotypes observed using the original ChETA vs. ChETATC and ChR2 likely reflects the weaker photocurrents in ChETA vs. other opsins, and/or the long duration/high power photostimulation conditions used with ChETA. Consistent with this conclusion, the results obtained using ChR2 or ChETATC are complementary to findings from loss-of-functions experiments using optogenetic inhibition, chemogenetic inhibition, and neuronal ablation. These data support a positive-acting role of MeApd Vgat+ neurons in aggression. Our findings, in conjunction with studies of Berndt et al. (2011), suggest that the improved ChETATC should be used when faster kinetics than ChR2 offers are required.
A uniquely stable trimeric model of SARS-CoV-2 spike transmembrane domain
Authors: Aliper E.T. , Krylov N.A. , Nolde D.E. , Polyansky A.A. , Efremov R.G. 
Published: June 2022

ABSTRACTThe spike (S) protein of SARS-CoV-2 effectuates membrane fusion and virus entry into target cells. Its transmembrane domain (TMD) represents a homotrimer of α-helices anchoring the spike in the viral envelope. Although S-protein models available to date include the TMD, its precise configuration was given brief consideration. Understanding viral fusion entails realistic TMD models, while no reliable approaches towards predicting the 3D structure of transmembrane (TM) trimers exist. Here, we propose a comprehensive computational framework to model the spike TMD (S-TMD) based solely on its primary structure. First, we performed amino acid sequence pattern matching and compared molecular hydrophobicity potential (MHP) distribution on the helix surface against TM homotrimers with known 3D structures and thus selected the TMD of the tumour necrosis factor receptor 1 (TNFR-1) for subsequent template-based modelling. We then iteratively built an all-atom homotrimer model of S-TMD based on “dynamic MHP portraits” and residue variability motifs. In this model each helix possessed two overlapping interfaces interacting with either of the remaining helices, which include conservative residues I1216, F1220, I1227, M1229, and M1233. Finally, the stability of this and several alternative models (including a recent NMR structure) and a set of mutant forms was tested in all-atom molecular dynamics (MD) simulations in a POPC bilayer mimicking the viral envelope membrane. Unlike other configurations, our model trimer remained extraordinarily tightly packed over a microsecond-range MD and retained its stability when palmitoylated in accordance with experimental data. Palmitoylation had no significant impact on the TMD conformation nor the way in which the lipid bilayer was perturbed in the presence of the trimer. Overall, the resulting model of S-TMD conforms to known basic principles of TM helix packing and will be further used to explore the complex machinery of membrane fusion from a broader perspective beyond the TMD.
Continuous Indexing of Fibrosis (CIF): Improving the Assessment and Classification of MPN Patients
Authors: Ryou Hosuk , Sirinukunwattana Korsuk , Aberdeen Alan , Grindstaff Gillian , Stolz Bernadette , Byrne Helen , Harrington Heather A. , Sousos Nikolaos , Godfrey Anna L. , Harrison Claire N. , Psaila Bethan , Mead Adam J. , Rees Gabrielle , Turner Gareth D.H. , Rittscher Jens , Royston Daniel 
Published: June 2022

AbstractThe detection and grading of fibrosis in myeloproliferative neoplasms (MPN) is an important component of disease classification, prognostication and disease monitoring. However, current fibrosis grading systems are only semi-quantitative and fail to capture sample heterogeneity. To improve the detection, quantitation and representation of reticulin fibrosis, we developed a machine learning (ML) approach using bone marrow trephine (BMT) samples (n = 107) from patients diagnosed with MPN or a reactive / nonneoplastic marrow. The resulting Continuous Indexing of Fibrosis (CIF) enhances the detection and monitoring of fibrosis within BMTs, and aids the discrimination of MPN subtypes. When combined with megakaryocyte feature analysis, CIF discriminates between the frequently challenging differential diagnosis of essential thrombocythemia (ET) and pre-fibrotic myelofibrosis (pre-PMF) with high predictive accuracy [area under the curve = 0.94]. CIF also shows significant promise in the identification of MPN patients at risk of disease progression; analysis of samples from 35 patients diagnosed with ET and enrolled in the Primary Thrombocythemia-1 (PT-1) trial identified features predictive of post-ET myelofibrosis (area under the curve = 0.77). In addition to these clinical applications, automated analysis of fibrosis has clear potential to further refine disease classification boundaries and inform future studies of the micro-environmental factors driving disease initiation and progression in MPN and other stem cell disorders. The image analysis methods used to generate CIF can be readily integrated with those of other key morphological features in MPNs, including megakaryocyte morphology, that lie beyond the scope of conventional histological assessment.Key PointsMachine learning enables an objective and quantitative description of reticulin fibrosis within the bone marrow of patients with myeloproliferative neoplasms (MPN),Automated analysis and Continuous Indexing of Fibrosis (CIF) captures heterogeneity within MPN samples and has utility in refined classification and disease monitoringQuantitative fibrosis assessment combined with topological data analysis may help to predict patients at increased risk of progression to post-ET myelofibrosis, and assist in the discrimination of ET and pre-fibrotic PMF (pre-PMF)
The State of Household Handwashing by Mothers and Associated Risk Factors in Nepal: A Systematic Review
Authors: Dhital Shalik Ram , Chojenta Catherine , Bagade Tanmay , Loxton Deborah 
Published: June 2022

AbstractApproximately 53% of households do not use soap and water for handwashing. Mothers oversee their hygiene and are ideally placed to teach their children about handwashing with soap. This paper aims to determine the rates of household handwashing with soap by mothers in Nepal and explore the factors associated with the uptake of handwashing. A systematic literature search using PubMed/Medline, Embase, PsycINFO, CINAHL, and Grey literature was searched. Eligible articles were extracted and recorded then descriptive analysis was performed. The quality assessment of the article was done using STROBE guidelines. We screened 187 articles from database searching and 16 from additional grey literature. A total of 120 full-textt articles and records were retrieved to evaluate for inclusion in the review. We identified seven articles that met the criteria for inclusion. The included studies contained 32,010 participants from articles. Current handwashing rates by mothers were varied, ranging from 5% to 67%. The potential risk factors for a lack of handwashing were lack of knowledge, lack of handwashing facilities, and absence of regularities. The hygiene advocacy, provision of soap and water, family encouragement and support, the establishment of a handwashing strategy, and mothers’ participation in decision making are key possible solutions.
Transcriptomics Meta-Analysis Predicts Two Robust Human Biomarkers for Severe Infection with SARS-CoV-2
Authors: Clancy Jeffrey , Hoffmann Curtis S. , Pickett Brett E. 
Published: June 2022

AbstractDefining the human factors associated with severe vs mild SARS-CoV-2 infection has become of increasing interest. Mining large numbers of public gene expression datasets is an effective way to identify genes that contribute to a given phenotype. Combining RNA-sequencing data with the associated clinical metadata describing disease severity can enable earlier identification of patients who are at higher risk of developing severe COVID-19 disease. We consequently identified 358 public RNA-seq human transcriptome samples from the Gene Expression Omnibus database that had disease severity metadata. We then subjected these samples to a robust RNA-seq data processing workflow to quantify gene expression in each patient. This process involved using Salmon to map the reads to the reference transcriptomes, edgeR to calculate significant differential expression levels, and gene ontology enrichment using Camera. We then applied a machine learning algorithm to the read counts data to identify features that best differentiated samples based on COVID-19 severity phenotype. Ultimately, we produced a ranked list of genes based on their Gini importance values that includes GIMAP7 and S1PR2, which are associated with immunity and inflammation (respectively). Our results show that these two genes can potentially predict people with severe COVID-19 at up to ∼90% accuracy. We expect that our findings can help contribute to the development of improved prognostics for severe COVID-19.
COVID-19 and per capitagreen tea consumption: update
Authors: Storozhuk Maksim 
Published: June 2022

AbstractPurposeIn spite of the development of numerous vaccines for the prevention of COVID-19 and approvement of several drugs for its treatment, there is still a great need in effective and inexpensive therapy of this disease. Pharmacological evidence suggesting the therapeutic potential of green tea catechins in amelioration/treatment of COVID19 is growing rapidly, however, there are only a few epidemiological studies addressing this possibility. The aim of this study was to provide update regarding ecological study assessing this issue as of January 2021.MethodsThe methodological approach used in this report is similar to that described previously. Briefly, information about COVID-19 morbidity (defined as a total number of cases per million population) and mortality (defined as a total number of deaths per million population) for a specific date was directly obtained from Worldometers info. Coronavirus. Analysis was restricted to 134 countries or territories with at least 3 million population. Twenty-one of these countries/territories, with estimatedper/capitagreen tea consumption above 150 g (annually), were considered as a group with the high consumption. Countries/territories with the estimatedper/capitagreen tea consumption below 150 g (N=82) were considered as the group with low the consumption.ResultsPronounced differences in COVID-19 morbidity and mortality between groups of countries with high and low green tea consumption were found as of February 20, 2022. These differences were still observed in a subset of countries with HDI above 0.55. Moreover, in this restricted subset of countries, weak but statistically significant correlations between COVID-19 morbidity (or mortality) and per/capita green tea consumption were observed in a multiple regression model accounting for: population density, percentage of population aged above 65, and percentage of urban population.ConclusionThe obtained results provide additional, though indirect, support of the idea that green tea catechins can be useful for treatment/amelioration of COVID-19. These results are in line with emerging evidence from other studies, including pharmacological. Nevertheless, further research is necessary to directly validate or reject this idea.
MTaxi : A comparative tool for taxon identification of ultra low coverage ancient genomes
Authors: Atağ Gözde , Vural Kıvılcım Başak , Kaptan Damla , Özkan Mustafa , Koptekin Dilek , Sağlıcan Ekin , Doğramacı Sevcan , Köz Mevlüt , Yılmaz Ardan , Söylev Arda , Togan İnci , Somel Mehmet , Özer Füsun 
Published: June 2022

AbstractA major challenge in zooarchaeology is to morphologically distinguish closely related species’ remains, especially using small bone fragments. Shotgun sequencing aDNA from archeological remains and comparative alignment to the candidate species’ reference genomes will only apply when reference nuclear genomes of comparable quality are available, and may still fail when coverages are low. Here, we propose an alternative method, MTaxi, that uses highly accessible mitochondrial DNA (mtDNA) to distinguish between pairs of closely related species from ancient DNA sequences. MTaxi utilises mtDNA transversion-type substitutions between pairs of candidate species, assigns reads to either species, and performs a binomial test to determine the sample taxon. We tested MTaxi on sheep/goat and horse/donkey data, between which zooarchaeological classification can be challenging in ways that epitomise our case. The method performed efficiently on simulated ancient genomes down to 0.5x mitochondrial coverage for both sheep/goat and horse/donkey, with no false positives. Trials on n=18 ancient sheep/goat samples and n=10 horse/donkey samples of known species identity with mtDNA coverages 0.1x - 12x also yielded 100% accuracy. Overall, MTaxi provides a straightforward approach to classify closely related species that are compelling to distinguish through zooarchaeological methods using low coverage aDNA data, especially when similar quality reference genomes are unavailable. MTaxi is freely available athttps://github.com/goztag/MTaxi.
Long-term Antibody Release Polycaprolactone (PCL) Capsule and the Release Kinetics In Natural and Accelerated Degradation
Authors: Thomas Waterkotte , He Xingyu , Wanasathop Apipa , Li Kevin , Park Yoonjee 
Published: June 2022

AbstractAlthough therapy using monoclonal antibodies (mAbs) has been steadily successful over the last 20 years, the means of delivery of mAbs has not been optimized, especially for long-term delivery. Frequent injections or infusions have been current standard of care. In this study, we have developed a long-term antibody biodegradable implant using a porous polycaprolactone (PCL) capsule. It released Bevacizumab (Bev) slowly for 8 months to date. The Bev release kinetics fit a drug release model with experimental data of the diffusion coefficient and partition coefficient through the polymer capsule. Since screening drug release profiles for the long-term (> 6 months) is time consuming, an accelerated degradation method was used after validating characteristics of the PCL capsule in natural and accelerated degradation conditions. The correlation of time period between the natural and the accelerated degradation was determined. Overall, the study suggests mAbs can be released from a porous PCL capsule without an effect of the polymer degradation over the long period (~ 6 months) and the long-term release kinetics can be determined by the accelerated degradation within 14 days.