bluuebunny/crossref_metadata_2025_split huggingface dataset:
Vehicle pollution is associated with elevated insect damage to street trees
Authors: Meineke Emily K. , Eng David S. , Karban Richard 
Published: June 2022

AbstractVehicle pollution is a pervasive aspect of anthropogenic change across rural and urban habitats. The most common emissions are carbon- or nitrogen-based pollutants that may impact diverse interactions between plants and insect herbivores. However, the effects of vehicle pollution on plant-insect interactions are poorly understood.Here, we combine a city-wide experiment across the Sacramento Metropolitan Area and a laboratory experiment to determine how vehicle emissions affect insect herbivory and leaf nutritional quality.We demonstrate that leaf damage to a native oak species (Quercus lobata) commonly planted across the western US is substantially elevated on trees exposed to vehicle emissions. In the laboratory, caterpillars preferred leaves from highway-adjacent trees and performed better on leaves from those same trees.Synthesis and applications. Together, our studies demonstrate that the heterogeneity in vehicle emissions across cities may explain highly variable patterns of insect herbivory on street trees. Our results also indicate that trees next to highways are particularly vulnerable to multiple stressors, including insect damage. To combat these effects, urban foresters may consider installing trees that are less susceptible to insect herbivory along heavily traveled roadways.
‘A Generalized Reinforcement Learning-Based Deep Neural Network (GRL-DNN) Agent Model for Diverse Cognitive Constructs
Authors: Nair Sandeep S. , Muddapu Vignayanandam R. , Vigneswaran C , Balasubramani Pragathi P. , Ramanathan Dhakshin S. , Mishra Jyoti , Chakravarthy V. Srinivasa 
Published: June 2022

ABSTRACTHuman cognition is characterized by a wide range of capabilities including goal-oriented selective attention, distractor suppression, decision making, response inhibition, and working memory. Much research has focused on studying these individual components of cognition in isolation, whereas in several translational applications for cognitive impairment, multiple cognitive functions are altered in a given individual. Hence it is important to study multiple cognitive abilities in the same subject or, in computational terms, model them using a single model. To this end, we propose a unified, reinforcement learning-based agent model comprising of systems for representation, memory, value computation and exploration. We successfully modelled the aforementioned cognitive tasks and show how individual performance can be mapped to model meta-parameters. This model has the potential to serve as a proxy for cognitively impaired conditions, and can be used as a clinical testbench on which therapeutic interventions can be simulated first before delivering to human subjects.
Threshold-awareness in adaptive cancer therapy
Authors: Wang MingYi , Scott Jacob G. , Vladimirsky Alexander 
Published: June 2022

AbstractAlthough adaptive cancer therapy shows promise in integrating evolutionary dynamics into treatment scheduling, the stochastic nature of cancer evolution has seldom been taken into account. Various sources of random perturbations can impact the evolution of heterogeneous tumors, making performance metrics of any treatment policy random as well. In this paper, we propose an efficient method for selecting optimal adaptive treatment policies under randomly evolving tumor dynamics. The goal is to improve the cumulative “cost” of treatment, a combination of the total amount of drugs used and the total treatment time. As this cost also becomes random in any stochastic setting, we maximize the probability of reaching the treatment goals (tumor stabilization or eradication) without exceeding a pre-specified threshold (or a “budget”). We use a novel Stochastic Optimal Control formulation and Dynamic Programming to find such “threshold-aware” optimal treatment policies. Our approach enables an efficient algorithm to compute these policies for a range of threshold values simultaneously. Compared to treatment plans shown to be optimal in a deterministic setting, the new “threshold-aware” policies significantly improve the chances of the therapy succeeding under the budget, which is correlated with a lower general drug usage. We illustrate this method using two specific examples, but our approach is far more general and provides a new tool for optimizing adaptive therapies based on a broad range of stochastic cancer models.Author SummaryTumor heterogeneities provide an opportunity to improve therapies by leveraging complex (often competitive) interactions of different types of cancer cells. These interactions are usually stochastic due to both individual cell differences and random events affecting the patient as a whole. The new generation of cancer models strive to account for this inherent stochasticity, andadaptivetreatment plans need to reflect it as well. In optimizing such treatment, the most common approach is to maximize the probability of eventually stabilizing or eradicating the tumor. In this paper, we consider a more nuanced version of success, maximizing the probability of reaching these therapy goals before the cumulative burden from the disease and treatment exceed a chosen threshold. Importantly, our method allows computing such optimal treatment plans efficiently and for a range of thresholds at once. If used on a high-fidelity personalized model, our general approach could potentially be used by clinicians to choose the most suitable threshold after a detailed discussion of a specific patient’s goals (e.g., to include the trade-offs between toxicity and quality of life).
NRX-101, A RAPID-ACTING ANTI-DEPRESSANT, DOES NOT CAUSE NEUROTOXICITY FOLLOWING KETAMINE ADMINISTRATION IN PRECLINICAL MODELS
Authors: Jordan William , Siegel Richard , Kumar Rajendra , Javitt Jonathan 
Published: June 2022

ABSTRACTBackgroundNMDA (N-Methyl-D aspartate) receptor antagonists have gained increasing attention as rapid-acting antidepressants. However, their use has been limited by potential neurotoxicity (Olney Lesions) and recent FDA guidance requires demonstration of safety on histologic parameters prior to initiation of human studies. D-cycloserine is a mixed NMDA agonist/antagonist awarded Breakthrough Therapy Designation and currently in clinical trials for the treatment of bipolar depression with suicidal ideation. The current study was designed to investigate the neurologic safety profile of D-cycloserine by itself and in combination with ketamine and lurasidone.MethodsSprague Dawley female rats (n=106) were randomly divided into 7 study groups. Ketamine was administered via tail vein infusion. D-cycloserine and lurasidone were administered via oral gavage in escalating doses to a maximum of 2000 mg/kg DCS. To ascertain toxicity, dose escalation with three different doses of D-cycloserine/lurasidone was given in combination with ketamine. MK-801, a known neurotoxic NMDA antagonist, was administered as a positive control. Brain tissue was sectioned and stained with H&E and Fluorojade stains.ResultsNo fatalities were observed in any group. No microscopic abnormalities were found in the brain of animal subjects given ketamine, ketamine followed by DCS/lurasidone, or DCS/lurasidone alone. Neuronal necrosis, as expected, was seen in the MK-801 positive control group.ConclusionNRX-101, a fixed-dose combination of D-cycloserine/lurasidone, when administered with or without prior infusion of IV ketamine was tolerated and did not induce neurotoxicity, even at maximum-tolerated doses of D-cycloserine.HIGHLIGHTSNRX-101, a fixed dose combination of D-cycloserine and lurasidone does not exhibit histologic neurotoxicity, even at maximum-tolerated doses
Novel Rickettsia spp. in two common overwintering North American passerines
Authors: Becker Daniel J. , Byrd Allison , Smiley Tara M. , Marques Mariana Fernandes , Nunez Julissa Villegas , Talbott Katherine M. , Atwell Jonathan W. , Volokhov Dmitriy V. , Ketterson Ellen D. , Jahn Alex E. , Clark Kerry L. 
Published: June 2022

AbstractAmerican robins and dark-eyed juncos migrate across North America, but their contributions to arthropod-borne disease remain poorly characterized. We identified novel Rickettsia spp. in one wintering migrant per bird species related to bellii, transitional, and spotted fever group rickettsiae and suggest spring migration could disperse these pathogens hundreds-to-thousands of kilometers.
Conservation management strategy impacts inbreeding and mutation load in scimitar-horned oryx
Authors: Humble Emily , Stoffel Martin A , Dicks Kara , Ball Alex D , Gooley Rebecca M , Chuven Justin , Pusey Ricardo , Remeithi Mohammed Al , Koepfli Klaus-Peter , Pukazhenthi Budhan , Senn Helen , Ogden Rob 
Published: June 2022

AbstractIn an age of habitat loss and overexploitation, small populations, both captive and wild, are increasingly facing the effects of isolation and inbreeding. Genetic management has therefore become a vital tool for ensuring population viability. However, little is known about how the type and intensity of intervention shape the genomic landscape of inbreeding and mutation load. We address this using whole genome sequence data of scimitar-horned oryx (Oryx dammah), an iconic antelope that has been subject to contrasting management strategies since it was declared extinct in the wild. We show that unmanaged populations are enriched for long runs of homozygosity (ROH) and have significantly higher inbreeding coefficients than managed populations. Additionally, despite the total number of deleterious alleles being similar across management strategies, the burden of homozygous deleterious genotypes was consistently higher in unmanaged groups. These findings emphasise the risks associated with deleterious mutations through multiple generations of inbreeding. As wildlife management strategies continue to diversify, our study reinforces the importance of maintaining genome-wide variation in vulnerable populations and has direct implications for one of the largest reintroduction attempts in the world.Significance statementConservation genetic management is becoming increasingly important for safeguarding and restoring wildlife populations. Understanding how the intensity of intervention influences genomic components of fitness is therefore essential for supporting species viability. We investigate the impact of contrasting management strategies on the genomic landscape of inbreeding and mutation load in captive populations of scimitar-horned oryx. We reveal how several decades of management have prevented the formation of long runs of homozygosity and masked the expression of deleterious mutations. Our findings highlight the dynamics between inbreeding, mutation load and population size and have direct implications for future management of threatened species.
multEvol: An interactive pipeline for multitrait evolutionary analysis in a phylogenetic framework
Authors: Basu Dipendra Nath , Bhaumik Vaishali , Kunte Krushnamegh 
Published: June 2022

ABSTRACTComparative phylogenetic studies based on 2D image data can reveal macroevolutionary patterns and processes by integrating phylogenetic and ecological analyses. The advent of high-throughput imaging facilities has led to the accumulation of large image datasets; however, large-scale data extraction and analysis using these resources can be labour- and computation-intensive. Moreover, there are few standardized methods to analyse multitrait image-based data in a phylogenetic framework. Several packages in the R statistical environment offer utilities for processing and analysing large-scale image data. Techniques for the comparative phylogenetic analysis of multitrait data have also been introduced in other packages. However, most of these approaches are specialized for discrete purposes, and there is a lack of streamlined and efficient methodological pipelines integrating features across packages. Here, we present multEvol, an interactive pipeline for the extraction and phylogenetic analysis of shape and colour pattern data from 2D images in the R statistical computing environment. Using this pipeline, shape outlines and colour pattern data for multiple colours can be extracted, visualised, and compared in a phylogenetic framework. Using various utilities provided in the phytools, RNiftyReg, Momocs, patternize, convevol, and geiger packages, we introduce an interactive interface that allows user inputs for iterative data extraction. This pipeline provides an efficient method for the bulk processing of images of biological specimens from museum collections. As such, it has potential applications in the large-scale morphometric analysis of museum specimens to reveal macroevolutionary patterns in ecology, evolution and integrative biology.
Pyramidal neuron morphogenesis requires a septin network that stabilizes filopodia and suppresses lamellipodia during neurite initiation
Authors: Radler Megan R. , Liu Xiaonan , Peng Megan , Doyle Brenna , Toyo-Oka Kazuhito , Spiliotis Elias T. 
Published: June 2022

SummaryPyramidal neurons are the major cell type of the forebrain, consisting of a pyramidally shaped soma with axonal and apicobasal dendritic processes. It is poorly understood how the neuronal soma morphs from a sphere to pyramid, while generating neurites of the proper shape and orientation. Here, we discovered that the spherical somata of immature neurite-less neurons possess a circumferential wreath-like network of septin filaments, which promotes myosin II localization and suppresses Arp2/3 activity at the base of filopodial actin bundles. The septin network facilitates neurite formation by stabilizing nascent filopodia, which mature to neurites, and concomitantly maintains a consolidated soma by suppressing the extension of lamellipodia. We show that this septin function is critical for the morphogenesis and spatial orientation of pyramidal somata and their neurites in vitro and in vivo. Therefore, the somatic septin cytoskeleton provides a key morphogenetic mechanism for neuritogenesis and the development of pyramidal neurons.Highlights- A septin wreath-like network controls the shape of neuronal somata and nascent neurites- Septins promote and suppress filopodial and lamellipodial protrusions, respectively- Septins scaffold myosin II and exclude Arp2/3 at the base of filopodial actin- Development of pyramidally shaped neurons requires septins in vitro and in vivoeTOC SummaryRadler et al report a new morphogenetic mechanism in the development of pyramidal neurons, which is mediated by a septin wreath-like cytoskeleton in the soma of immature spherical neurons. The septin network stabilizes somatic filopodia and suppresses lamellipodia by differentially controlling the localization of myosin II and Arp2/3.
An insight into cellulolytic capacity of the Trichoderma harzianum P49P11 revealed by omics approaches
Authors: Codima Carla Aloia , Tomazetto Geizecler , Persinoti Gabriela Felix , Riano-Pachon Diego M. , Squina Fábio Marcio , da Cruz Pradella José Geraldo , da Silva Delabona Priscila 
Published: June 2022

AbstractCellulases are a group of enzymes with several applications in biofuel production, and the paper, food, pharmaceutical, and chemical industries. Trichoderma harzianum P49P11 secrete all cellulases with high efficiency, representing an alternative to the current filamentous fungi in biotechnological industries. In this study, the cellulolytic mechanisms employed by the strain P49P11 to degrade crystalline cellulose in batch fermentation culture mode were elucidated by combining genome and secretome analysis. The strain P49P11 encodes nineteen cellulase genes from five different CAZyme families (GH5, GH6, GH7, GH12, and GH45), followed by several enzyme families for hemicellulose, pectin, and alpha-and beta-glucans degradation. The diverse CAZymes were also observed in the secretome, including cellulases, hemicellulases, and glucanases. In addition, β-glucosidases and xylanase activities detected during the fermentation process validated our secretome analysis. Taken together, our results revealed all enzymatic machinery used by the T. harzianum P49P11 to degrade cellulose in batch fermentation mode.HighlightsWe described a high-quality genome assembly and annotation of the T. harzianum P49P11.The T. harzianum P49P11 genome possesses a complete set of genes for lignocellulose degradation.The first report on T. harzianum P49P11 secretome obtained from batch fermentation strategy.T. harzianum P49P11 produced cellulases, lignocellulases, and auxiliary enzymes produced in response to crystalline cellulose.
Identification of potential natural compound inhibitors and drug like molecules against human METTL3 by docking and molecular dynamics simulation
Authors: Manna Shibambika , Samal Pragati , Basak Rohini , Mitra Anushka , Roy Arijit Kumar , Kundu Raima , Ahir Amrita , Roychowdhury Amlan , Hazra Ditipriya 
Published: June 2022

AbstractNucleotide level chemical modification in transcriptome is critical in regulating different cellular processes, including cancer. The most investigated epitranscriptomic modification is methylation at the N6-position of adenosine (m6A). This dynamic modification process is carried out by: writer, reader and eraser proteins. Writers are methyltransferases, METTL3 is the major writer that works in association with METTL14, an accessory protein. Extensive study revealed that cancer progression for acute myeloid leukaemia, gastric cancer, colorectal cancer, hepatocellular carcinoma, and lung cancer is directly contributed by irregular expression of METTL3. Targeting METTL3, has opened a new window in the development of new inhibitors/drugs. In this study, 80 commercially available compounds were found from an unbiased screening by molecular docking, showing better score when compared with the existing substrate/substrate-analogue and the inhibitor bound crystal structures in terms of docking score and binding energy calculation. Among this pool of compounds, the best seven small molecules, AMF, RAD, JNJ, MEH, ECP, MHN, SGI, have been selected and further validated by different computational tools like binding energy calculation, molecular dynamics simulation etc. The novel hits found in this study can function as lead compounds which can be developed into inhibitors as well as drugs, specific against METTL3.
Characterising patterns of COVID-19 and long COVID symptoms: Evidence from nine UK longitudinal studies
Authors: Bowyer Ruth C. E. , Huggins Charlotte , Toms Renin , Shaw Richard J. , Hou Bo , Thompson Ellen J. , Kwong Alex , Williams Dylan , Kibble Milla , Ploubidis George B. , Timpson Nic , Sterne Jonathan , Chaturvedi Nish , Steves Claire J. , Tilling Kate , Silverwood Richard J. 
Published: June 2022

ABSTRACTMultiple studies across global populations have established the primary symptoms characterising COVID-19 (Coronavirus Disease 2019) and long COVID. However, as symptoms may also occur in the absence of COVID-19, a lack of appropriate controls has often meant that specificity of symptoms to acute COVID-19 or long COVID could not be examined. We aimed to characterise patterns of COVID-19 and long COVID symptoms across nine UK longitudinal studies, totalling over 42,000 participants. Conducting latent class analyses separately in three groups (‘no COVID-19’, ‘COVID-19 in last 12 weeks’, ‘COVID-19 > 12 weeks ago’), the data did not support the presence of more than two distinct symptom patterns, representing high and low symptom burden, in each group. Comparing the high symptom burden classes between the ‘COVID-19 in last 12 weeks’ and ‘no COVID-19’ groups we identified symptoms characteristic of acute COVID-19, including loss of taste and smell, fatigue, cough, shortness of breath and muscle pains or aches. Comparing the high symptom burden classes between the ‘COVID-19 > 12 weeks ago’ and ‘no COVID-19’ groups we identified symptoms characteristic of long COVID, including fatigue, shortness of breath, muscle pain or aches, difficulty concentrating and chest tightness. The identified symptom patterns among individuals with COVID-19 > 12 weeks ago were strongly associated with self-reported length of time unable to function as normal due to COVID-19 symptoms, suggesting that the symptom pattern identified corresponds to long COVID. Building the evidence base regarding typical long COVID symptoms will improve diagnosis of this condition and the ability to elicit underlying biological mechanisms, leading to better patient access to treatment and services.
Complementary coding of behaviors in striatal pathways supports a dual selection-suppression function
Authors: Varin Christophe , Cornil Amandine , Houtteman Delphine , Bonnavion Patricia , de Kerchove d’Exaerde Alban 
Published: June 2022

ABSTRACTThe basal ganglia are known to control actions and modulate movements. Neuronal activity in the two efferent pathways of the dorsal striatum, a major input to the basal ganglia, is critical for appropriate behavioral control. Previous evidence has led to divergent conclusions on the respective engagement of both pathways during actions. We used calcium imaging to evaluate how neurons in the direct and indirect pathways in the dorsal striatum encode behaviors during self-paced spontaneous explorations in an open field. We observed that the two striatal pathways exhibit distinct tuning properties during spontaneous behaviors. We applied supervised learning algorithms and found that direct pathway neurons encode behaviors through their activation, whereas indirect pathway neurons exhibit behavior-specific silencing. These properties remain stable for weeks. Our findings highlight a complementary encoding of behaviors in the two striatal pathways that supports an updated model, reconciling previous conflicting conclusions on motor encoding in the striatum.
Quality standards, crime management and the efficiency of manufacturing firms in middle-income economies
Authors: Boamah Nicholas Addai , Ofori-Yeboah Francis , Asare Nicholas 
Published: June 2022

PurposeThis study investigates the ability of crime management expenses, recognised external quality certification and ownership structure to describe the cross-sectional changes in the capital and labour efficiencies of manufacturing firms in middle income economies. It controls for the potential effects of graft incidence and firm age on firm-level efficiency.Design/methodology/approachThe study adopts a state space model approach within the context of cross-sectional regressions. Data for the study are obtained from the World Bank Enterprise Survey for 2006, 2009, 2013, 2016 and 2019.FindingsThe study provides evidence that crime management expenses impact labour efficiency negatively. Also, its effect on capital efficiency is positive in 2019 and negative in 2013 and 2016 eras. Additionally, external auditor services and internationally recognised quality certification increase labour and capital efficiencies. Graft incidence exerts negative and positive effect on capital efficiency in the recent and earlier periods respectively. In addition, older firms tend to have higher labour efficiency, whilst younger firms have higher capital efficiency. There is evidence of firm size and export orientation effects in the drivers of efficiency.Originality/valuePolicies aimed at creating graft and crime-free business environment will enhance the efficiency and growth of firms' particularly for small firms. Also, the market rewards recognised quality assurance and good reputation.