bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using Explainable AI to understand frailty indicators
Authors: Mohsen Attayeb , Yamamoto Masaki , Martin-Morales Agustin , Watanabe Daiki , Nishi Nobuo , Nakagata Takashi , Yoshida Tsukasa , Miyachi Motohiko , Mizuguchi Kenji , Araki Michihiro 
Published: June 2023

AbstractIntroductionThe prevalence of frailty is on the rise with the aging population and increasing life expectancy, which often is accompanied by comorbidities. Frailty can be effectively detected using Frailty index such as KCL index. Early detection of frailty allows applying measures that reduce the conversion rate to frail, and improve the quality of life in the frail people. Therefore, to facilitate the screening of frailty status at the primary care level, we suggest to produce a shorter version of the KCL questionnaire.AimTo understand the importance of KCL components in the decision making process for frailty and use machine learning approach to shorten the Questionnaire while maintaining reasonable accuracy, making it easier to screen for frailty in primary care.MethodsWe developed an automated framework of three steps: Feature importance determination using Shap values, testing models with Cross-validation with increased addition of selected features. Moreover, we validated the reliability of KCL to detect frailty by comparing the results of KCL criteria with the unsupervised clustering of the data.ResultsOur approach allowed us to identify the most important questions in the KCL questionnaire and demonstrate its performance using a short version with only four questions (4) Do you visit homes of friends?, (6) Are you able to go upstairs without using handrails or the wall for support? (10) Do you feel anxious about falling when you walk?, and (25) (In the past two weeks) Have you felt exhausted for no apparent reason?). We also showed that the data clustering corresponds well with the results of KCL criteria.Discussion and ConclusionWhile it is difficult to predict pre-frail status using shorter KCL questionnaire, it was shown to be fairly accurate in predicting frail status using only four questions.
Human Rhinoviruses: a novel class of oncolytic virus
Authors: Burnett William J , Cluff Amber , Reeves Melissa , Parkman Gennie L , Hart Chase , Ramstead Andrew , Holmen Sheri , Williams Matthew A , VanBrocklin Matthew W 
Published: June 2023

AbstractWhile continuing to develop new and improved OVs, researchers have been vigilant in optimizing their ability to safely infect, replicate, and induce an immune response within tumors. There are currently two crucial limitations in OV development, however: modification of viruses often negatively impact their ability to infect, and induction of strong immune responses also promotes rapid viral clearance. In this study, we investigate wild-type HRVs as a novel class of OV. Multiple HRV serotypes were propagated in human melanoma cell lines to produce highly oncolytic populations of virus. A large panel of cancer types were infected, with cytotoxicity evaluated using flow cytometry and real time live imaging. Pro-inflammatory signaling was assessed by cytokine multiplexing. Tumor responses to HRV were assessed in human xenograft and in syngeneic, immune-competent mouse tumor models. We find that HRVs are capable of infecting and killing a wide variety of human cancer cell linesin vitroandin vivo, inducing pro-inflammatory responses and, ultimately, tumor regression. We propose that the natural safety profile of these viruses, coupled with their anti-tumor efficacy and multivalent potential seen in our preclinical model systems, make HRVs ideal candidates for development as oncolytic viruses for clinical testing.Simple SummaryThe idea of utilizing viruses to combat cancer has been around for over a century, yet in practice has seen relatively modest therapeutic success following decades of strategic design to improve safety, efficacy, and tumor selectivity. Engagement of an immune response is critical to have lasting tumor regression upon treatment, but many patients are unable to mount a sufficient response to standard-of-care immunotherapy alone. Oncolytic viruses (OVs) have been shown to synergize with such therapies to accomplish this goal to varying degrees. The purpose of this study is to investigate human rhinoviruses (HRVs) to establish their efficacy as a novel class of anti-cancer agents. We aim to use HRVs to promote longer lasting and more effective immune responses to tumors by fostering viral persistence and immune evasion, in addition to developing multivalent treatment strategies that enhance tumor regression by preventing tumor escape from viral infection.
High-resolution Dynamic Human Brain Neural Activity Recording Using 3T MRI
Authors: Zhang Yifei , Sun Kaibao , Ren Jianxun , Hu Qingyu , Wang Yezhe , Li Shiyi , Chen Tienzheng , Xu Na , Guo Ning , Fu Xiaoxuan , Liu Xuan , Cao Zhenen , Gao Jia-hong , Liu Hesheng 
Published: June 2023

AbstractDespite extensive research over decades, a non-invasive technique capable of capturing neural activities in the human brain with high spatiotemporal resolution is still lacking. The recently proposed direct imaging of neuronal activity (DIANA) using ultrahigh-field magnetic resonance imaging (MRI) has shown promise, but the translation from anesthetized mice to awake humans poses a significant challenge. Here we present Time Resolved ImaGing of Global Electroneurophysiological Record (TRIGGER), a novel technique that enables the direct detection of neural activity in the awake human brain using 3T MRI. In 18 participants, visual responses were captured at 5-mm spatial resolution and 1.4-ms temporal resolution. Importantly, the delay in stimulus presentation reliably corresponded to the latency of neural responses on a millisecond scale. Furthermore, when stimuli were presented to one visual field, the responses in two hemispheres exhibited the expected time difference. This non-invasive mapping approach holds the potential to elucidate neural dynamics underlying human brain function and disorders.
GeneToCN: an alignment-free method for gene copy number estimation directly from next-generation sequencing reads
Authors: Pajuste Fanny-Dhelia , Remm Maido 
Published: June 2023

ABSTRACTGenomes exhibit large regions with segmental copy number variation, many of which include entire genes and are multiallelic. We have developed a computational method GeneToCN that counts the frequencies of gene-specifick-mers in FASTQ files and uses this information to infer copy number of the gene. We validated the copy number predictions for amylase genes (AMY1, AMY2A, AMY2B) using experimental data from digital droplet PCR (ddPCR) on 39 individuals and observed a strong correlation (R=0.99) between GeneToCN predictions and experimentally determined copy numbers. We further tested the method on three different genomic regions (SMN, NPY4R, and LPA Kringle IV-2 domain). Predicted copy number distributions of these genes in a set of 500 individuals from the Estonian Biobank were in good agreement with the previously published studies. In addition, we investigated the possibility to use GeneToCN on sequencing data generated by different technologies by comparing copy number predictions from Illumina, PacBio, and Oxford Nanopore data of the same sample. Despite the differences in variability ofk-mer frequencies, all three sequencing technologies give similar predictions with GeneToCN.
Chronotate: An open-source tool for manual timestamping and quantification of animal behavior
Authors: Philipsberg Paul A. , Christenson Wick Zoé , Diego Keziah S. , Vaughan Nick , Galas Angelina , Jurkowski Albert , Feng Yu , Vetere Lauren M. , Chen Lingxuan , Cai Denise J. , Shuman Tristan 
Published: June 2023

ABSTRACTA core necessity to behavioral neuroscience research is the ability to accurately measure performance on behavioral assays, such as the novel object location and novel object recognition tasks. These tasks are widely used in neuroscience research and measure a rodent’s instinct for investigating novel features as a proxy to test their memory of a previous experience. Automated tools for scoring behavioral videos can be cost prohibitive and often have difficulty distinguishing between active investigation of an object and simply being in close proximity to an object. As such, many experimenters continue to rely on hand scoring interactions using stopwatches which makes it difficult to review scoring after-the-fact and results in the loss of temporal information. Here, we introduce Chronotate, a free, open-source tool to aid in manually scoring novel object behavior videos. The software consists of an interactive video player with keyboard integration for marking timestamps of behavioral events during video playback, making it simple to quickly score and review bouts of rodent-object interaction. In addition, Chronotate outputs detailed interaction bout data, allowing for nuanced behavioral performance analyses. Using this detailed temporal information, we demonstrate that novel object location performance peaks within the first 3 seconds of interaction time and preference for the novel location becomes reduced across the test session. Thus, Chronotate can be used to determine the temporal structure of interactions on this task and can provide new insight into the memory processes that drive this behavior. Chronotate is available for download at:https://github.com/ShumanLab/Chronotate.
Impairment of autophagy-lysosomal activity near the chronically implanted microelectrodes
Authors: Chen Keying , Padilla Camila Garcia , Kiselyov Kirill , Kozai Takashi 
Published: June 2023

AbstractIntracortical microelectrodes that can record and stimulate brain activity have become a valuable technique for basic science research and clinical applications. However, long-term implantation of these microelectrodes can lead to progressive neurodegeneration in the surrounding microenvironment, characterized by elevation in disease-associated markers. Dysregulation of autophagy-lysosomal degradation, a major intracellular waste removal process, is considered a key factor in the onset and progression of neurodegenerative diseases. It is plausible that similar dysfunctions in autophagy-lysosomal degradation contribute to tissue degeneration following implantation-induced focal brain injury, ultimately impacting recording performance. To understand how the focal, persistent brain injury caused by long-term microelectrode implantation impairs the autophagy-lysosomal pathway, we employed two-photon microscopy and immunohistology. This investigation focused on the spatiotemporal characterization of autophagy-lysosomal activity near the chronically implanted microelectrode. We observed an aberrant accumulation of immature autophagy vesicles near the microelectrode over the chronic implantation period. Additionally, we found deficits in autophagy-lysosomal clearance proximal to the chronic implant, which was associated with an accumulation of autophagy cargo and a reduction in lysosomal protease level during the chronic period. Furthermore, our evidence suggests astrocytes contribute to the clearance of myelin debris via autophagy-lysosomal degradation near the implanted microelectrode. Together, this study sheds light on the process of brain tissue degeneration caused by long-term microelectrode implantation, with a specific focus on impaired intracellular waste degradation.
Machine Learning Classification of Alzheimer’s Disease Pathology Reveals Diffuse Amyloid as a Major Predictor of Cognitive Impairment in Human Hippocampal Subregions
Authors: Stephen T.L. , Korobkova L. , Breningstall B. , Nguyen K. , Mehta S. , Pachicano M. , Jones K.T. , Hawes D. , Cabeen R.P. , Bienkowski M.S. 
Published: June 2023

AbstractAnalyzing Alzheimer’s disease (AD) pathology within anatomical subregions is a significant challenge, often carried out by pathologists using a standardized, semi-quantitative approach. To augment traditional methods, a high-throughput, high-resolution pipeline was created to classify the distribution of AD pathology within hippocampal subregions. USC ADRC post-mortem tissue sections from 51 patients were stained with 4G8 for amyloid, Gallyas for neurofibrillary tangles (NFTs) and Iba1 for microglia. Machine learning (ML) techniques were utilized to identify and classify amyloid pathology (dense, diffuse and APP (amyloid precursor protein)), NFTs, neuritic plaques and microglia. These classifications were overlaid within manually segmented regions (aligned with the Allen Human Brain Atlas) to create detailed pathology maps. Cases were separated into low, intermediate, or high AD stages. Further data extraction enabled quantification of plaque size and pathology density alongside ApoE genotype, sex, and cognitive status.Our findings revealed that the increase in pathology burden across AD stages was driven mainly by diffuse amyloid. The pre and para-subiculum had the highest levels of diffuse amyloid while NFTs were highest in the A36 region in high AD cases. Moreover, different pathology types had distinct trajectories across disease stages. In a subset of AD cases, microglia were elevated in intermediate and high compared to low AD. Microglia also correlated with amyloid pathology in the Dentate Gyrus. The size of dense plaques, which may represent microglial function, was lower in ApoE4 carriers. In addition, individuals with memory impairment had higher levels of both dense and diffuse amyloid.Taken together, our findings integrating ML classification approaches with anatomical segmentation maps provide new insights on the complexity of disease pathology in AD progression. Specifically, we identified diffuse amyloid pathology as being a major driver of AD in our cohort, regions of interest and microglial responses that might advance AD diagnosis and treatment.
Cortical high-frequency oscillations (≈ 110 Hz) in cats are state-dependent and enhanced by a subanesthetic dose of ketamine
Authors: Castro-Zaballa Santiago , González Joaquín , Cavelli Matías , Mateos Diego , Pascovich Claudia , Tort Adriano , Hunt Mark Jeremy , Torterolo Pablo 
Published: June 2023

AbstractKetamine is an NMDA receptor antagonist that has both antidepressant and anesthetic properties. At subanesthetic doses, ketamine can cause transient psychosis in humans, and is used to model psychosis in experimental animals. In rodents, subanesthetic doses of ketamine increase the power of high-frequency oscillations (HFO, 100-180 Hz) in the electroencephalogram and field potentials, a frequency band linked to cognitive functions. However, the effects of ketamine in higher mammals, with more translatable relevance, are poorly investigated. Here, we have examined cortical HFO during wakefulness, sleep, and after administering a sub-anesthetic dose of ketamine (15 mg/kg), utilizing the cat as an animal model. Four cats were implanted with cortical electrodes for chronic polysomnographic recordings. HFO power, connectivity, information flow directionality, and their relationships with respiratory activity were analyzed. During wakefulness, but not during sleep, we found that HFO were coupled with the inspiratory phase of the respiration. After ketamine administration, HFO were enhanced significantly and remained associated with the inspiratory phase. The analysis of the information flow after ketamine suggest that HFO originate from the olfactory bulb and stream towards the prefrontal cortex. Accordingly, occluding the nostrils significantly reduced HFO power in both the olfactory bulb and prefrontal cortex. In contrast, auditory stimulation did not affect HFO. In conclusion, spontaneous cortical HFO show certain state-dependent features in cats, and enhancement of this rhythm by ketamine may disrupt cortical information processing, which could contribute to some of the neuropsychiatric manifestations associated with ketamine.HighlightsKetamine is used to model psychosis in humans and experimental animalsSubanesthetic doses of ketamine increase the power of high-frequency oscillationsHigh-frequency oscillations are coupled with the inspiratory phase of respirationThese oscillations originate in the olfactory bulb and stream to the neocortexNostril occlusion lowers high-frequency activity in the olfactory bulb and neocortexGraphical abstract
Home food procurement associated with improved food security during the COVID-19 pandemic
Authors: Niles Meredith T. , McCarthy Ashley C. , Malacarne Jonathan , Bliss Sam , Belarmino Emily H. , Laurent Jennifer , Merrill Scott C. , Nowak Sarah A. , Schattman Rachel E. 
Published: June 2023

AbstractHome food procurement (HFP), including gardening, is associated with food security and improved health behaviors and outcomes. In the beginning of the COVID-19 pandemic, HFP increased in many high-income countries; yet little evidence has demonstrated what impact HFP had on food security. Furthermore, existing HFP studies are largely qualitative from unrepresentative samples, limiting population-level understanding of HFP engagement and impact. Using data from a representative sample of residents (n=988) in northern New England in the United States conducted in Spring/Summer 2021, we explore the relationship between HFP engagement in the first year of the pandemic and changes in food security status. We employ matching techniques to compare food security outcomes in households with observably similar demographic and social characteristics, and examine food security outcomes in three periods among households who do and do not participate in HFP. Our results show that nearly 60% of respondents engaged in at least one kind of HFP in the first year of the COVID-19 pandemic, with food insecure households being more likely to do HFP. Food insecure households (both newly and chronically food insecure) were also more likely to do HFP activities for the first time or more intensely than they had previously. Newly food insecure households were the most likely to engage in HFP overall, especially gardening. Furthermore, HFP engagement early in the COVID-19 pandemic is associated with improved food security for food insecure households in the 9-12 months after the start of the pandemic, though these improvements were primarily associated with newly, not chronically, food insecure households. Future research about HFP should continue to explore multiple HFP strategies and their potentially myriad relationships to food security, diet, and health outcomes.
Caregiving burden and associated factors among family caregivers of individuals with schizophrenia in Bangladesh: A cross-sectional study
Authors: Tabassum Tahsin Tasneem , Rahman Nur-A-Safrina , Shakhawat Hossain S M , Abdullah Faisal , Nawar Lubaba Tasneem , Lima Fahmida Islam , Gupta Mridul , Kona Suraiya Parveen , Podder Vivek 
Published: June 2023

AbstractBackgroundSchizophrenia is a severe mental disorder affecting millions worldwide. Family caregivers play a vital role in patient treatment and recovery, but their responsibilities can be physically and emotionally exhausting. There is limited research on caregiver burden in Bangladesh.PurposeThis study to identify factors associated with the burden among caregivers of schizophrenic individuals.MethodsThis cross-sectional study collected data from 175 caregivers from January to December 2020 in Dhaka, Bangladesh. A semi-structured questionnaire and validated Bangla version of the Zarit Interview Burden scale were used to assess the burden of primary caregivers and associated factors in caring for patients with schizophrenia.ResultsParticipants’ mean age was 34.02±10.45 years, with 26.9% in the 34-41 age group. 49.1% were housewives, with most earning 5000 to 15000 taka monthly. Spouses accounted for 28.6% of caregivers. Most patients had an illness duration of less than five years (66.3%). Mean ZBI score was 49.49±12.06, indicating moderate to severe burden. Factors significantly associated with caregiver burden included age, gender, occupation, income, marital status, house condition, relationship with patients, illness stage, and duration.ConclusionThis study highlights the burden experienced by caregivers of schizophrenic patients in Bangladesh and identifies factors associated with the burden. It recommends community interventions and psychosocial provisions to address this issue and inform targeted interventions to reduce caregiver burden. These findings provide insights for a comprehensive plan to manage such cases in the future.
Octopamine integrates the status of internal energy supply into the formation of food-related memories
Authors: Berger Michael , Fraatz Michèle , Auweiler Katrin , Dorn Katharina , Khadrawe Tanna El , Scholz Henrike 
Published: June 2023

SummaryThe brain regulates food intake in response to internal energy demands and food availability. However, can internal energy storage influence the type of memory that is formed? We show that the duration of starvation determines whetherDrosophila melanogasterforms appetitive short-term or longer-lasting intermediate memories. The internal glycogen storage in the muscles and adipose tissue influences how intensely sucrose associated information is stored. Insulin-like signaling in octopaminergic reward neurons integrates internal energy storage into memory formation. Octopamine, in turn, suppresses the formation of long-term memory. Octopamine is not required for short-term memory, because octopamine-deficient mutants can form appetitive short-term memory for sucrose and to other nutrients depending on the internal energy status. The reduced positive reinforcing effect of sucrose at high internal glycogen levels combined with the increased stability of food-related memories due to prolonged periods of starvation could lead to increased food intake.
Aberrant functional brain network organization is associated with relapse during 1-year follow-up in alcohol-dependent patients
Authors: Böhmer Justin , Reinhardt Pablo , Garbusow Maria , Marxen Michael , Smolka Michael N. , Zimmermann Ulrich S. , Heinz Andreas , Bzdok Danilo , Friedel Eva , Kruschwitz Johann D. , Walter Henrik 
Published: June 2023

AbstractAlcohol dependence (AD) is a debilitating disease associated with high relapse rates even after long periods of abstinence. Thus, elucidating neurobiological substrates of relapse risk is fundamental for the development of novel targeted interventions that could promote long-lasting abstinence. In the present study, we analyzed resting-state functional magnetic resonance imaging (rsfMRI) data from a sample of recently detoxified AD patients (n= 93) who were followed-up for 12 months after rsfMRI assessment. Specifically, we employed graph theoretic analyses to compare functional brain network topology and functional connectivity between future relapsers (REL,n= 59), future abstainers (ABS,n= 28) and age and gender matched controls (CON,n= 83). Our results suggest increased whole-brain network segregation, decreased global network integration and overall blunted connectivity strength in REL compared to CON. Conversely, we found evidence for a comparable network architecture in ABS relative to CON. At the nodal level, REL exhibited decreased integration and decoupling between multiple brain systems compared to CON, encompassing regions associated with higher-order executive functions, sensory and reward processing. Among AD patients, increased coupling between nodes implicated in reward valuation and salience attribution constitutes a particular risk factor for future relapse. Importantly, aberrant network organization in REL was consistently associated with shorter abstinence duration during follow-up, portending to a putative neural signature of relapse risk in AD. Future research should further evaluate the potential diagnostic value of the identified changes in network topology and functional connectivity for relapse prediction at the individual subject level.