bluuebunny/crossref_metadata_2025_split huggingface dataset:
Guide to veterinary care of small rodents
Authors: Keeble Emma 
Published: October 2021

Background: Rodents comprise the largest order of mammals, with novel species still being discovered worldwide. This article concentrates on the Myomorph suborder (mouse‐like rodents) containing the families Muridae (true mice: rats and mice) and Cricetidae (burrowing rodents: gerbils and hamsters). Most information available for these species originates from their use in laboratory research as animal models for disease, or associated with disease transfer, acting as reservoir hosts for many infectious diseases. This field of veterinary medicine is rapidly evolving, with more publications on pet rodent medicine available to veterinary practitioners and a greater client expectation for the diagnosis and treatment of their pet rodents in veterinary practice.Aim of the article: This article reviews the basic biology and husbandry of the commonly seen small rodent species in veterinary practice (rats, mice, hamsters and gerbils), and discusses how to take a thorough history and perform a clinical examination, including handling techniques. It also covers common clinical techniques, diagnostic procedures, hospitalisation requirements and small rodent emergency and critical care, and provides an overview of common clinical problems, including diagnosis and treatment of these conditions. This article is a useful guide for all veterinarians, whether treating small rodents rarely or as a regular occurrence in veterinary practice.
Nutritional status and skeletal muscle status in patients with head and neck cancer: Impact on outcomes
Authors: Findlay Merran , White Kathryn , Brown Chris , Bauer Judith D. 
Published: October 2021

AbstractBackgroundComputed tomography (CT)‐defined skeletal muscle depletion and malnutrition are demonstrated as poor prognostic factors in patients with head and neck cancer (HNC), however to date, have only been explored in isolation. We aimed to describe body composition profile and examine the impact of nutritional status as well as independently and concurrently occurring body composition features on overall survival, treatment completion, unplanned admissions and length of stay (LOS) in patients undergoing radiotherapy (RT) or chemoradiotherapy (CRT) of curative intent for HNC.MethodsThis work is a retrospective, observational study of patients who had completed treatment of curative intent for HNC. Scored Patient‐Generated Subjective Global Assessment (PG‐SGA) was used to determine nutritional status. Tissue‐density data were derived at the third lumbar vertebra (L3) with sarcopenia and myosteatosis defined by published, sex‐specific threshold values stratified by body mass index for skeletal muscle index (cm2/m2) and skeletal muscle radiodensity (SMR, Hounsfield Unit).ResultsPre‐treatment data (n = 277: 78% male, mean (SD) age 60 (13) years) revealed the prevalence of malnutrition (24.9%), sarcopenia (52.3%), myosteatosis (82.3%), and concurrently occurring sarcopenia and myosteatosis (39.7%). Malnutrition was independently associated with reduced OS for patients with moderate [hazard ratio (HR) 2.57; 95% confidence interval (CI) 1.45–4.55, P = 0.001] and severe (HR 3.19; 95% CI 1.44–7.07, P = 0.004) malnutrition on multivariable analysis but not sarcopenia (HR 1.09; 95% CI 0.70–1.71), P = 0.700 or myosteatosis (HR 1.28; 95% CI 0.57–2.84), P = 0.500). Malnutrition was associated with treatment discontinuation (P < 0.001), not completing RT as planned (P < 0.001), unplanned hospital admission (P = 0.021), and greater LOS (P < 0.001). Skeletal muscle status features were associated with unplanned hospital admissions for those with no features (32%), with sarcopenia only (50%), myosteatosis only (25%), and concurrent sarcopenia and myosteatosis (50%), P < 0.001. Similarly, a clinically relevant greater median (Q1, Q3) LOS was observed for those with sarcopenia only [5 (3, 32)], myosteatosis only [10 (5, 30)], concurrent sarcopenia, and myosteatosis [14 (4, 33)] days vs. those with no features [3 (2, 11)] days, P = 0.2.ConclusionsMalnutrition was a more powerful prognostic indicator than CT‐defined skeletal muscle depletion and was independently associated with reduced OS in patients undergoing RT or CRT of curative intent for HNC. CT‐defined skeletal muscle depletion studies should recognize the multifaceted nature of human body composition and also measure nutritional status using validated methods in order to move towards developing a typology of high risk criteria for this complex patient group.
Choosing an engineering major: A conceptual model of student pathways into engineering
Authors: Main Joyce B. , Griffith Amanda L. , Xu Xinrui , Dukes Alexandra M. 
Published: October 2021

AbstractBackgroundIncreasing interest and participation in engineering is vital if the United States is to create the larger technological and scientific labor force it needs to meet the challenges of the 21st century. Students' pathways into the different engineering majors provide important information for this effort.PurposeThis study addresses which factors across life stages (pre‐high school, high school, and early college) are associated with engineering major choice. The quantitative analysis identifies which demographic characteristics and academic achievement variables are correlated with engineering major choice, whereas the qualitative analysis examines when and why students choose a specific engineering major.MethodsInformed by the life course perspective, this convergent mixed methods research study applies Logit regression and thematic analysis. Data sets include more than 20,000 observations of student‐level academic records (2001–2015) as well as interviews conducted with 20 students at a large, research‐intensive university in the Midwest.ResultsQuantitative results indicate that student demographic factors and measures of academic achievement—including passing scores on advanced placement tests, scholastic aptitude test scores, and high school and college first‐year grade point averages—are associated with engineering major choice. Qualitative findings show that across the life stages, the source of social influence in engineering major choice varies; while family and teachers play larger roles before and during high school, peers and university personnel play larger roles in early college.ConclusionThe conceptual model comprehensively synthesizes the key factors associated with engineering major choice, highlighting the importance of demographic factors, academic achievement, social networks, and access to role models from pre‐high school, high school, and early college.
Assessing the impact of magnetic resonance treatment simulation (MRSIM) on target volume delineation and dose to organs at risk for oropharyngeal radiotherapy
Authors: Richardson Haylea , Kumar Mahesh , Tieu Minh Thi , Parker Joel , Dowling Jason A. , Arm Jameen , Best Leah , Greer Peter B. , Clapham Matthew , Oldmeadow Christopher , O’Connor Laura , Wratten Chris 
Published: October 2021

AbstractIntroductionAssessing the use of a radiation therapy (RT) planning MRI performed in the treatment position (pMRI) on target volume delineation and effect on organ at risk dose for oropharyngeal cancer patients planned with diagnostic MRI (dMRI) and CT scan.MethodsDiagnostic MRI scans were acquired for 26 patients in a neutral patient position using a 3T scanner (dMRI). Subsequent pMRI scans were acquired on the same scanner with a flat couch top and the patient in their immobilisation mask. Each series was rigidly registered to the patients planning CT scan and volumes were first completed with the CT/dMRI. The pMRI was then made available for volume modification. For the group with revised volumes, two IMRT plans were developed to demonstrate the impact of the modification. Image and registration quality was also evaluated.ResultsThe pMRI registration led to the modification of target volumes for 19 of 26 participants. The pMRI target volumes were larger in absolute volume resulting in reduced capacity for organ sparing. Predominantly, modifications occurred for the primary gross tumour volume (GTVp) with a mean Dice Similarity Coefficient (DSC) of 0.7 and the resulting high risk planning target volume, a mean DSC of 0.89. Both MRIs scored similarly for image quality, with the pMRI demonstrating improved registration quality and efficiency.ConclusionsA pMRI provides improvement in registration efficiency, quality and a higher degree of oncologist confidence in target delineation. These results have led to a practice change within our department, where a pMRI is acquired for all eligible oropharyngeal cancer patients.
Effects of short environmental enrichment on early‐life adversity induced cognitive alternations in adolescent rats
Authors: Joushi Sara , Esmaeilpour Khadijeh , Masoumi‐Ardakani Yaser , Esmaeili‐Mahani Saeed , Sheibani Vahid 
Published: October 2021

AbstractEarly‐life experiences, including parental care, affect cognitive performance later in life. Being exposed to early‐life maternal separation (MS) increases susceptibility to stress‐related psychopathology. Previous studies suggest that MS could induce learning and memory impairments. Since enriched environment (EE) provides more opportunities for exploration and social interaction, in the present study we evaluated the effects of a short EE paradigm with a duration of 13 days on cognitive abilities of maternally separated rats (MS; 180 min/day, postnatal day (PND) 1–21) during adolescence in four experimental groups: Control, Control+EE, MS, and MS+EE. Plasma corticosterone (CORT) and brain‐derived neurotrophic factor (BDNF) levels were also measured in experimental animals. We also studied the induction of long‐term potentiation (LTP) in the slices of hippocampal CA1 area. The behavioral and electrophysiological assessments were started at PND 35. MS caused higher basal CORT levels in plasma and impaired spatial learning, memory, and social interaction. LTP induction was also impaired in MS rats and plasma BDNF levels were reduced in these animals. MS also induced more anxiety‐like behavior. Short EE reduced plasma CORT levels had the potential to improve locomotor activity and anxiety‐like behavior in MS+EE rats and reversed MS‐induced impairments of spatial learning, memory, and social behavior. LTP induction and plasma BDNF levels were also enhanced in MS+EE rats. We concluded that short EE might be considered as a therapeutic strategy for promoting cognition.
Machine Learning for Prediction of Drug Targets in Microbe Associated Cardiovascular Diseases by Incorporating Host‐pathogen Interaction Network Parameters
Authors: Singh Nirupma , Bhatnagar Sonika 
Published: October 2021

AbstractHost‐pathogen interactions play a crucial role in invasion, infection, and induction of immune response in humans. In this work, four machine learning algorithms, namely Logistic regression, K‐nearest neighbor, Support Vector Machine, and Random Forest were implemented for the classification of drug targets. The algorithms were trained using 3400 hosts and 3800 pathogen drug and non‐drug target proteins as learning instances. For each protein, 68 pathogen and 73 host features were computed that included sequence, structure, biological and host‐pathogen network centrality characteristics. The Random Forest classifier model achieved the best accuracy after 10‐fold cross‐validation. 99 % accuracy was achieved with a ROC‐AUC score of 0.99±0.01 for both pathogen and host training sets. The Eigenvector Centrality of host‐pathogen interactions and host‐host interactions was the top feature in performing classification of pathogen and host targets respectively. Other features important for classification were the presence of catalytic and binding sites, low instability/aliphatic index, and cellular location. The Random Forest classifier was then used for prediction of drug targets involved in Microbe Associated Cardiovascular Diseases. 331 host and 743 pathogen proteins were predicted as drug targets by the random forest model and can be validated experimentally for therapeutic intervention in Microbe Associated Cardiovascular Diseases.
SoxE group transcription factor Sox8 promotes astrocytic differentiation of neural stem/precursor cells downstream of Nfia
Authors: Takouda Jun , Katada Sayako , Imamura Takuya , Sanosaka Tsukasa , Nakashima Kinichi 
Published: October 2021

AbstractThe brain consists of three major cell types: neurons and two glial cell types (astrocytes and oligodendrocytes). Although they are generated from common multipotent neural stem/precursor cells (NS/PCs), embryonic NS/PCs cannot generate all of the cell types at the beginning of brain development. NS/PCs first undergo extensive self‐renewal to expand their pools, and then acquire the potential to produce neurons, followed by glial cells. Astrocytes are the most frequently found cell type in the central nervous system (CNS), and play important roles in brain development and functions. Although it has been shown that nuclear factor IA (Nfia) is a pivotal transcription factor for conferring gliogenic potential on neurogenic NS/PCs by sequestering DNA methyltransferase 1 (Dnmt1) from astrocyte‐specific genes, direct targets of Nfia that participate in astrocytic differentiation have yet to be completely identified. Here we show that SRY‐box transcription factor 8 (Sox8) is a direct target gene of Nfia at the initiation of the gliogenic phase. We found that expression of Sox8 augmented leukemia inhibitory factor (LIF)‐induced astrocytic differentiation, while Sox8 knockdown inhibited Nfia‐enhanced astrocytic differentiation of NS/PCs. In contrast to Nfia, Sox8 did not induce DNA demethylation of an astrocyte‐specific marker gene, glial fibrillary acidic protein (Gfap), but instead associated with LIF downstream transcription factor STAT3 through transcriptional coactivator p300, explaining how Sox8 expression further facilitated LIF‐induced Gfap expression. Taken together, these results suggest that Sox8 is a crucial Nfia downstream transcription factor for the astrocytic differentiation of NS/PCs in the developing brain.
Enzymatic and Acidic Hydrolysis of Cull Potatoes for Production of Fermentable Sugars
Authors: Bansal Riya , Katyal Priya , Jain Deepali 
Published: October 2021

AbstractCull potato is an under‐utilized biomass being produced in different states of India. Using cull potatoes as a substrate for bioethanol production can overcome the post‐harvest losses as well as making the process economical. In the present study, comparative hydrolysis of cull potatoes is carried out using enzymes and hydrochloric acid to study the effect of variables on saccharification efficiency. For enzymatic hydrolysis, samples are liquefied using crude enzyme from Bacillus sp. and then saccharification of liquefied samples is optimized using central composite rotatable design (CCRD) in Response surface methodology (RSM) w.r.t pH (4–7), temperature (25–40 °C) and incubation period (15–60 min) at 5% substrate concentration with glucoamylase of Aspergillus niger. Acidic hydrolysis is performed at different acid concentration, i.e., 1–5 (v/v) at variable time intervals (15–60 min) with 1–5% substrate concentration at 90 °C. Highest saccharification efficiency is observed with acidic hydrolysis 85.2% at substrate concentration of (4%) and at acid concentration (4% v/v) after 45 min of incubation, while with enzymatic hydrolysis it is very close to acidic hydrolysis, i.e., 83.2% at 25 °C temperature and at pH 4 after 30 min of incubation.
Strong-coupling results for $$ \mathcal{N} $$ = 2 superconformal quivers and holography
Authors: Billò M. , Frau M. , Galvagno F. , Lerda A. , Pini A. 
Published: October 2021

Abstract
We consider $$ \mathcal{N} $$
N
= 2 superconformal quiver gauge theories in four dimensions and evaluate the chiral/anti-chiral correlators of single-trace operators. We show that it is convenient to form particular twisted and untwisted combinations of these operators suggested by the dual holographic description of the theory. The various twisted sectors are orthogonal and the correlators in each sector have always the same structure, as we show at the lowest orders in perturbation theory with Feynman diagrams. Using localization we then map the computation to a matrix model. In this way we are able to obtain formal expressions for the twisted correlators in the planar limit that are valid for all values of the ‘t Hooft coupling λ, and find that they are proportional to 1/λ at strong coupling. We successfully test the correctness of our extrapolation against a direct numerical evaluation of the matrix model and argue that the 1/λ behavior qualitatively agrees with the holographic description.
Inflation and supersymmetry breaking in Higgs-R2 supergravity
Authors: Aoki Shuntaro , Lee Hyun Min , Menkara Adriana G. 
Published: October 2021

Abstract
We propose a new construction of the supergravity inflation as an UV completion of the Higgs-R2 inflation. In the dual description of R2-supergravity, we show that there appear dual chiral superfields containing the scalaron or sigma field in the Starobinsky inflation, which unitarizes the supersymmetric Higgs inflation with a large non-minimal coupling up to the Planck scale. We find that a successful slow-roll inflation is achievable in the Higgs-sigma field space, but under the condition that higher curvature terms are introduced to cure the tachyonic mass problems for spectator singlet scalar fields. We also discuss supersymmetry breaking and its transmission to the visible sector as a result of the couplings of the dual chiral superfields and the non-minimal gravity coupling of the Higgs fields.
Molecular Genetics Diversity of Primary Hemophagocytic Lymphohistiocytosis among Polish Pediatric Patients
Authors: Bąbol-Pokora Katarzyna , Wołowiec Magdalena , Popko Katarzyna , Jaworowska Aleksandra , Bryceson Yenan T. , Tesi Bianca , Henter Jan-Inge , Młynarski Wojciech , Badowska Wanda , Balwierz Walentyna , Drabko Katarzyna , Kałwak Krzysztof , Maciejka-Kembłowska Lucyna , Pieczonka Anna , Sobol-Milejska Grażyna , Kołtan Sylwia , Malinowska Iwona ,   for the Polish Pediatric Hematology, Oncology Society
Published: October 2021

AbstractHemophagocytic lymphohistiocytosis (HLH) is a clinical syndrome of life-threatening inflammation caused by an excessive, prolonged and ineffective immune response. An increasing number of HLH cases is recognized in Poland, but the genetic causes of familial HLH (FHL) have not been reported. We investigated the molecular genetics and associated outcomes of pediatric patients who met HLH criteria. We studied 54 patients with HLH, 36 of whom received genetic studies. Twenty-five patients were subjected to direct sequencing of the PRF1, UNC13D, STX11, XIAP and SH2D1A genes. Additionally, 11 patients were subjected to targeted next-generation sequencing. In our study group, 17 patients (31%) were diagnosed with primary HLH, with bi-allelic FHL variants identified in 13 (36%) patients whereas hemizygous changes were identified in 4 patients with X-linked lymphoproliferative diseases. In addition, one patient was diagnosed with X-linked immunodeficiency with magnesium defect, Epstein–Barr virus infection and neoplasia due to a hemizygous MAGT1 variant; another newborn was diagnosed with auto-inflammatory syndrome caused by MVK variants. The majority (65%) of FHL patients carried UNC13D pathogenic variants, whereas PRF1 variants occurred in two patients. Novel variants in UNC13D, PRF1 and XIAP were detected. Epstein–Barr virus was the most common trigger noted in 23 (65%) of the patients with secondary HLH. In three patients with secondary HLH, heterozygous variants of FHL genes were found. Overall survival for the entire study group was 74% with a median of 3.6 years of follow-up. Our results highlight the diversity of molecular causes of primary HLH in Poland.
From internal models toward metacognitive AI
Authors: Kawato Mitsuo , Cortese Aurelio 
Published: October 2021

AbstractIn several papers published in Biological Cybernetics in the 1980s and 1990s, Kawato and colleagues proposed computational models explaining how internal models are acquired in the cerebellum. These models were later supported by neurophysiological experiments using monkeys and neuroimaging experiments involving humans. These early studies influenced neuroscience from basic, sensory-motor control to higher cognitive functions. One of the most perplexing enigmas related to internal models is to understand the neural mechanisms that enable animals to learn large-dimensional problems with so few trials. Consciousness and metacognition—the ability to monitor one’s own thoughts, may be part of the solution to this enigma. Based on literature reviews of the past 20 years, here we propose a computational neuroscience model of metacognition. The model comprises a modular hierarchical reinforcement-learning architecture of parallel and layered, generative-inverse model pairs. In the prefrontal cortex, a distributed executive network called the “cognitive reality monitoring network” (CRMN) orchestrates conscious involvement of generative-inverse model pairs in perception and action. Based on mismatches between computations by generative and inverse models, as well as reward prediction errors, CRMN computes a “responsibility signal” that gates selection and learning of pairs in perception, action, and reinforcement learning. A high responsibility signal is given to the pairs that best capture the external world, that are competent in movements (small mismatch), and that are capable of reinforcement learning (small reward-prediction error). CRMN selects pairs with higher responsibility signals as objects of metacognition, and consciousness is determined by the entropy of responsibility signals across all pairs. This model could lead to new-generation AI, which exhibits metacognition, consciousness, dimension reduction, selection of modules and corresponding representations, and learning from small samples. It may also lead to the development of a new scientific paradigm that enables the causal study of consciousness by combining CRMN and decoded neurofeedback.