bluuebunny/crossref_metadata_2025_split huggingface dataset:
Methodology for isolation of serum, cerebrospinal fluid, and hippocampal neuron proteins from rat and their analysis using mass spectrometry-based shotgun proteomics
Authors: Sharma Pratibha , Dhamija Rajinder K 
Published: May 2024

AbstractEmerging interests in the field of research related to diseases such as Alzheimer’s disease, Parkinson’s disease, cognition, and other mental health-related disorders have prompted a need for a common method for the isolation of serum, CSF, and hippocampus. The hippocampus is responsible for learning and memory. It can be affected by various neurological and psychiatric disorders. However, the process of collecting samples such as CSF and hippocampal neurons is challenging, especially for small animals like rats. We have presented here a method for the isolation of serum, CSF, and hippocampal neurons that can be used for its downstream applications such as proteomics. We have used high-speed centrifugation instruments and density gradient centrifugation methods, which are easy to follow. Additionally, we have tested the proteins identified through mass spectrometry. Our method enables the study of proteins in serum, CSF, and neural cells for researching protein cross-talks and neurological disorder mechanisms.
Epidemiology of Myalgic Encephalomyelitis among individuals with self-reported Chronic Fatigue Syndrome in British Columbia, Canada, and their health-related quality of life
Authors: Chuluunbaatar-Lussier Enkhzaya , Tsai Melody , Boulter Travis , Muñoz Carola , Kerr Kathleen , Nacul Luis 
Published: May 2024

ABSTRACTBackgroundThere is no accurate data on the epidemiology of Myalgic Encephalomyelitis/ Chronic Fatigue Syndrome (ME/CFS) in Canada. The aims of the study were to describe the epidemiology of confirmed ME/CFS cases and their health-related quality of life (HRQoL).MethodsThis is a cross-sectional study with British Columbia Generations Project (BCGP) participants who self-reported having CFS and population-based controls with no fatiguing illness. Participants completed the Symptoms Assessment Questionnaire, RAND 36-item Health Survey, and Phenotyping Questionnaire Short-form. These assessments enabled the identification and characterization of “confirmed cases” of ME/CFS. Those with self-reported diagnoses who did not meet study diagnosis of ME/CFS were subcategorized as “non-ME/CFS cases.”ResultsWe included 187 participants, 45.5% (n=85) self-reported cases and 54.5% (n=102) controls; 34% (n=29) of those who self-reported ME/CFS fulfilled diagnostic criteria for ME/CFS. The population prevalence rates were 1.1% and 0.4% for self-reported and confirmed ME/CFS cases respectively. Participants displayed significantly lower scores in all eight SF-36 domains compared to the other groups. Mental component scores were similar between ME/CFS and non-ME/CFS groups. The main risk factor for low HRQoL scores was fatigue severity (β = - 0.6, p<0.001 for physical health; β = -0.7, p<0.001 for mental health).ConclusionsThe majority of self-reported cases do not meet diagnostic criteria for ME/CFS, suggesting that self-reported CFS may not be a reliable indicator for a true ME/CFS diagnosis. HRQoL indicators were consistently lower in ME/CFS and non-ME/CFS cases compared to controls, with ME/CFS cases having lower scores in most domains. Having higher symptom severity scores and perceived poorer health were the significant affecting factors of lowerHRQoL. Although self-report can be used as screening to identify cases in populations, we suggest studies of ME/CFS should include appropriate medically confirmed clinical diagnosis for validity. Further large-scale population-based studies with simultaneous medical assessment are suggested to further characterize validity parameters of self-reported diagnosis.
Neurodevelopmental and psychiatric conditions in 600 Swedish Children with the ARFID phenotype
Authors: Nyholmer Manda , Wronski Marie-Louis , Hog Liv , Kuja-Halkola Ralf , Lichtenstein Paul , Lundström Sebastian , Larsson Henrik , Taylor Mark J. , Bulik Cynthia M. , Dinkler Lisa 
Published: May 2024

AbstractObjectiveAvoidant restrictive food intake disorder (ARFID) is a feeding and eating disorder characterized by extremely restricted dietary variety and/or quantity resulting in serious consequences for physical health and psychosocial functioning. ARFID often co-occurs with neurodevelopmental conditions (NDCs) and psychiatric conditions, but previous data are mostly limited to small clinical samples examining a narrow range of conditions. Here, we examined NDCs and psychiatric conditions in a large, population-based group of children with ARFID.MethodIn a sample of 30,795 children born 1992–2008 in Sweden, ARFID was assessed using parent reports and clinical diagnoses from national health registers. Parents further reported symptoms of NDCs and psychiatric conditions at child age 9 or 12 years. We conducted regressions for symptom scores and screening diagnoses (identified using validated cut offs) on ARFID and examined interactions with sex.ResultsChildren with ARFID had significantly increased odds of all 17 screening diagnoses with odds ratios ranging from 3.3 for visual hallucinations to 13.7 for autism (all p<.0001). The most common NDCs were oppositional defiant disorder (19.4%), ADHD (16.9%), tic disorders (14.8%), and autism (12.1%). Among psychiatric conditions, separation anxiety disorder (29.0%) and sleep problems (20.0%) had the highest prevalence. We did not find any sex-specific differences in co-occurring conditions.ConclusionThis study highlights the co-occurrence of a broad range of NDCs and psychiatric conditions with ARFID in a large, non-clinical cohort. Our findings underscore that children with ARFID face significant burden from multiple co-existing conditions which should be considered during assessment and treatment.
Contralateral Neck Recurrence Rates After Ipsilateral Neck Adjuvant Radiation in Head and Neck Carcinomas with a Pathologically Negative Contralateral Neck
Authors: Kiser Kendall J. , Apicelli Anthony J. , Brenneman Randall J. , Contreras Jessika A. , Gay Hiram , Moravan Michael J. , Rammohan Nikhil , Jackson Ryan S. , Pipkorn Patrik , Puram Sidharth V. , Rich Jason T. , Zevallos Jose P. , Adkins Douglas R. , Oppelt Peter , Thorstad Wade L. 
Published: May 2024

AbstractIntroductionIn 2019 we published a phase II trial of ipsilateral neck adjuvant radiation therapy in head and neck (HN) carcinoma patients with a pathologically negative (pN0) contralateral neck after bilateral neck dissection. The five-year contralateral neck recurrence rate was 3%. Here we present the recurrence rate in patients subsequently treated by this trial’s paradigm.MethodsPatients were selected who would have been eligible for our phase II trial: all had oropharynx, hypopharynx, oral cavity, or unknown primary carcinomas without prior HN cancer or major HN surgeries, underwent primary resection including bilateral neck dissection with a pN0 contralateral neck, and underwent adjuvant intensity modulated radiation therapy (IMRT) that spared the contralateral neck.ResultsFifty-five patients met cohort inclusion criteria. Thirty-nine cancers arose from the oropharynx, 11 from the oral cavity, three from the hypopharynx, and two from an unknown primary. With a median follow-up of 15 months there were nine recurrences (16%), four contralateral neck recurrences (7%), and one isolated contralateral neck recurrence (2%). No contralateral neck recurrences occurred in patients with p16+ oropharyngeal primaries despite that most (73%) arose from the base of the tongue. In contrast, three contralateral neck recurrences occurred in patients with advanced stage oral cavity primaries.ConclusionThe contralateral neck recurrence rate in HN carcinoma patients with a pN0 contralateral neck treated by adjuvant ipsilateral neck IMRT was similar to the 3% rate observed in our phase II trial. However, this paradigm may be inadequate for patients with locally advanced oral cavity primaries.
Mapping vascular network architecture in primate brain using ferumoxytol-weighted laminar MRI
Authors: Autio Joonas A. , Kimura Ikko , Ose Takayuki , Matsumoto Yuki , Ohno Masahiro , Urushibata Yuta , Ikeda Takuro , Glasser Matthew F. , Van Essen David C. , Hayashi Takuya 
Published: May 2024

AbstractMapping the vascular organization of the brain is of great importance across various domains of basic neuroimaging research, diagnostic radiology, and neurology. However, the intricate task of precisely mapping vasculature across brain regions and cortical layers presents formidable challenges, resulting in a limited understanding of neurometabolic factors influencing the brain’s microvasculature. Addressing this gap, our study investigates whole-brain vascular volume using ferumoxytol-weighted laminar-resolution multi-echo gradient-echo imaging in macaque monkeys. We validate the results with published data for vascular densities and compare them with cytoarchitecture, neuron and synaptic densities. The ferumoxytol-induced change in transverse relaxation rate (ΔR2*), an indirect proxy measure of cerebral blood volume (CBV), was mapped onto twelve equivolumetric laminar cortical surfaces. Our findings reveal that CBV varies 3-fold across the brain, with the highest vascular volume observed in the inferior colliculus and lowest in the corpus callosum. In the cerebral cortex, CBV is notably high in early primary sensory areas and low in association areas responsible for higher cognitive functions. Classification of CBV into distinct groups unveils extensive replication of translaminar vascular network motifs, suggesting distinct computational energy supply requirements in areas with varying cytoarchitecture types. Regionally, baseline R2* and CBV exhibit positive correlations with neuron density and negative correlations with receptor densities. Adjusting image resolution based on the critical sampling frequency of penetrating cortical vessels allows us to delineate approximately 30% of the arterial-venous vessels. Collectively, these results mark significant methodological and conceptual advancements, contributing to the refinement of cerebrovascular MRI. Furthermore, our study establishes a linkage between neurometabolic factors and the vascular network architecture in the primate brain.HighlightsCortical layer vascular mapping using ferumoxytol-weighted R2* MRIVascular volume is high in primary sensory areas and low in association areasCorrelation between R2* and vascular volume with neuron and receptor densitiesVascularization co-varies with densities of specific interneuron types
A foundation model for generalizable cancer diagnosis and survival prediction from histopathological images
Authors: Yang Zhaochang , Wei Ting , Liang Ying , Yuan Xin , Gao Ruitian , Xia Yujia , Zhou Jie , Zhang Yue , Yu Zhangsheng 
Published: May 2024

AbstractComputational pathology, utilizing whole slide image (WSI) for pathological diagnosis, has advanced the development of intelligent healthcare. However, the scarcity of annotated data and histological differences hinder the general application of existing methods. Extensive histopathological data and the robustness of self-supervised models in small-scale data demonstrate promising prospects for developing foundation pathology models. Due to the need for deployment, lightweight foundation models also need to be developed. In this work, we propose the BEPH (BEiT-based modelPre-training onHistopathological images), a general lightweight foundation model that leverages self-supervised learning to learn meaningful representations from 11 million unlabeled histopathological images. These representations are then efficiently adapted to various tasks, including 2 cancer patch-level recognition tasks, 3 cancer WSI-level classification tasks, and 6 cancer subtypes survival prediction tasks. Experimental results demonstrate that our model consistently outperforms several comparative models with similar parameters, even with limited training data reduced to 50%. Especially when the downstream structure is the same, the model can improve ResNet and DINO by up to a maximum increase of 8.8% and 7.2% (WSI level classification), and 6.44% and 3.28% on average (survival prediction), respectively. Therefore, BEPH offers a universal solution to enhance model performance, reduce the burden of expert annotations, and enable widespread clinical applications of artificial intelligence. The code and models can be obtained athttps://github.com/Zhcyoung/BEPH. And currently, online fine-tuning of WSI classification tasks is available for use onhttp://yulab-sjtu.natapp1.cc/BEPH.
A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds
Authors: Orlichenko Anton , Qu Gang , Zhou Ziyu , Liu Anqi , Deng Hong-Wen , Ding Zhengming , Stephen Julia M. , Wilson Tony W. , Calhoun Vince D. , Wang Yu-Ping 
Published: May 2024

AbstractObjectivefMRI and derived measures such as functional connectivity (FC) have been used to predict brain age, general fluid intelligence, psychiatric disease status, and preclinical neurodegenerative disease. However, it is not always clear that all demographic confounds, such as age, sex, and race, have been removed from fMRI data. Additionally, many fMRI datasets are restricted to authorized researchers, making dissemination of these valuable data sources challenging.MethodsWe create a variational autoencoder (VAE)-based model, DemoVAE, to decorrelate fMRI features from demographics and generate high-quality synthetic fMRI data based on user-supplied demographics. We train and validate our model using two large, widely used datasets, the Philadelphia Neurodevel-opmental Cohort (PNC) and Bipolar and Schizophrenia Network for Intermediate Phenotypes (BSNIP).ResultsWe find that DemoVAE recapitulates group differences in fMRI data while capturing the full breadth of individual variations. Significantly, we also find that most clinical and computerized battery fields that are correlated with fMRI data are not correlated with DemoVAE latents. An exception are several fields related to schizophrenia medication and symptom severity.ConclusionOur model generates fMRI data that captures the full distribution of FC better than traditional VAE or GAN models. We also find that most prediction using fMRI data is dependent on correlation with, and prediction of, demographics.SignificanceOur DemoVAE model allows for generation of high quality synthetic data conditioned on subject demographics as well as the removal of the confounding effects of demographics. We identify that FC-based prediction tasks are highly influenced by demographic confounds.
A Novel Explainable AI Method to Assess Associations between Temporal Patterns in Patient Trajectories and Adverse Outcome Risks: Analyzing Fitness as a Risk Factor of ADRD
Authors: Shao Yijun , Zamrini Edward Y. , Ahmed Ali , Cheng Yan , Nelson Stuart J. , Kokkinos Peter , Zeng-Treitler Qing 
Published: May 2024

AbstractWe present a novel explainable artificial intelligence (XAI) method to assess the associations between the temporal patterns in the patient trajectories recorded in longitudinal clinical data and the adverse outcome risks, through explanations for a type of deep neural network model called Hybrid Value-Aware Transformer (HVAT) model. The HVAT models can learn jointly from longitudinal and non-longitudinal clinical data, and in particular can leverage the time-varying numerical values associated with the clinical codes or concepts within the longitudinal data for outcome prediction. The key component of the XAI method is the definitions of two derived variables, the temporal mean and the temporal slope, which are defined for the clinical concepts with associated time-varying numerical values. The two variables represent the overall level and the rate of change over time, respectively, in the trajectory formed by the values associated with the clinical concept. Two operations on the original values are designed for changing the values of the two derived variables separately. The effects of the two variables on the outcome risks learned by the HVAT model are calculated in terms of impact scores and impacts. Interpretations of the impact scores and impacts as being similar to those of odds ratios are also provided. We applied the XAI method to the study of cardiorespiratory fitness (CRF) as a risk factor of Alzheimer’s disease and related dementias (ADRD). Using a retrospective case-control study design, we found that each one-unit increase in the overall CRF level is associated with a 5% reduction in ADRD risk, while each one-unit increase in the changing rate of CRF over time is associated with a 1% reduction. A closer investigation revealed that the association between the changing rate of CRF level and the ADRD risk is nonlinear, or more specifically, approximately piecewise linear along the axis of the changing rate on two pieces: the piece of negative changing rates and the piece of positive changing rates.
In vivosequential mutagenesis in germinal center B cells using a dual-recombinase approach: FOXO1 re-expression upon FOXO1 knockout rescues class switch recombination
Authors: Díaz Carlota Farré , Kabrani Eleni , Winkler Wiebke , Salomon Claudia , Wunderlich F. Thomas , Janz Martin , Rajewsky Klaus 
Published: May 2024

AbstractModeling complex (patho)physiological processes by sequential mutagenesis in mice is limited by the lack of optimized genetic tools and complex breeding strategies. We present a new Cre/DreERT2 dual-recombinase germinal center B-cell (GCBC)- specific strain, with co-expression of the recombinases from a single allele. This enables highly efficient Cre-mediated FOXO1 knockout followed by time-controlled, efficient Dre-mediated FOXO1 re-expression and functional rescue in GCBCs, demonstrating suitability for precise targeted sequential mutagenesisin vivo.
Glial cell activation precedes neurodegeneration in the cerebellar cortex of the YG8-800 murine model of Friedreich’s ataxia
Authors: Vicente-Acosta Andrés , Herranz-Martín Saúl , Pazos María Ruth , Galán-Cruz Jorge , Amores Mario , Loria Frida , Díaz-Nido Javier 
Published: May 2024

AbstractFriedreich’s ataxia is a hereditary neurodegenerative disorder resulting from reduced levels of the protein frataxin due to an expanded GAA repeat in theFXNgene. This deficiency causes progressive degeneration of specific neuronal populations in the cerebellum and the consequent loss of movement coordination and equilibrium, some of the main symptoms observed in affected individuals. Similar to other neurodegenerative diseases, previous studies suggest that glial cells could be involved in the neurodegenerative process and disease progression in Friedreich’s ataxia.In this work, we have followed and characterized the progression of changes in the cerebellar cortex of the latest Friedreich’s ataxia humanized mouse model, the YG8-800 (Fxnnull:YG8s(GAA)>800), which carries a humanFXNtransgene containing more than 800 GAA repeats.Comparative analyses of behavioral, histopathological, and biochemical parameters were conducted between Y47R control and YG8-800 mice at different time points. Our findings revealed that the YG8-800 mice display an ataxic phenotype, characterized by poor motor coordination, lower body weight, cerebellar atrophy, neuronal loss, and changes in synaptic proteins. Additionally, early activation of glial cells, predominantly astrocytes and microglia, was observed preceding neuronal degeneration along with an increased expression of key pro-inflammatory cytokines and downregulation of neurotrophic factors.Together, our results show how the YG8-800 mouse model exhibits a stronger phenotype than previous experimental murine models, reliably recapitulating some of the features observed in the human condition. Accordingly, this humanized model could represent a valuable tool to study Friedreich’s ataxia molecular disease mechanisms and for preclinical evaluation of possible therapies.
Developmental olfactory dysfunction and abnormal odor memory in immune-challengedDisc1+/-mice
Authors: Parbst Fiona , Kostka Johanna K. , Günther Anne , Chen Yu-Nan , Hanganu-Opatz Ileana L. , Bitzenhofer Sebastian H. 
Published: May 2024

AbstractNeuronal activity in the olfactory bulb (OB) drives coordinated activity in the hippocampal-prefrontal network during early development. Inhibiting OB output in neonatal mice disrupts functional development of the hippocampal formation as well as cognitive abilities. These impairments manifest early in life and resemble dysfunctions of the hippocampus and the prefrontal cortex that have been linked to neuropsychiatric disorders. Thus, we investigated a disease mouse model and asked whether activity in the OB might be altered, thereby contributing to the dysfunctional development of the hippocampal-prefrontal network. We addressed this question by combining in vivo electrophysiology with behavioral assessment of immune-challengedDisc1+/-mice that mimic the dual genetic-environmental etiology of neuropsychiatric disorders. In wildtype mice, we found high DISC1 expression levels in OB projection neurons during development. Furthermore, neuronal and network activity in the OB, as well as the drive from the bulb to the hippocampal-prefrontal network were reduced in immune-challengedDisc1+/-mice during early development. This early deficit did not affect odor-evoked activity and odor perception but resulted in impaired long-term odor memory. We propose that reduced endogenous activity in the developing OB contributes to altered maturation of the hippocampal-prefrontal network, leading to memory impairment in immune-challengedDisc1+/-mice.
Associated production of heavy quarkonia and
D
mesons in the improved color evaporation model with KaTie
Authors: Chernyshev A. A. , Saleev V. A. 
Published: May 2024

In this article, we study associated production of prompt J/ψ(ϒ) and D mesons in the improved color evaporation model using the high-energy factorization approach as it is realized in the Monte Carlo event generator KaTie. The modified Kimber-Martin-Ryskin-Watt model for unintegrated parton distribution functions is used. We predict cross sections for associated J/ψ(ϒ) and D meson hadroproduction via the single and double parton scattering mechanisms using the set of model parameters which has been fixed early for description of prompt single and pair heavy quarkonium production at the LHC energies. We found the results of calculations agree with the LHCb Collaboration data at the energies s=7, 8 TeV and we present theoretical predictions for the energy s=13  TeV.

Published by the American Physical Society
2024