bluuebunny/crossref_metadata_2025_split huggingface dataset:
Glucose-loaded dopamine transporter is associated with mood altering effect of sweet foods and control over eating sweets
Authors: Pak Kyoungjune , Kim Jihyun , Kim Keunyoung , Seo Seongho , Lee Myung Jun 
Published: April 2024

ABSTRACTDopamine transporter (DAT) mediates reuptake of extracellular dopamine into presynaptic neurons. We investigated the effects of glucose loading on striatal DAT in healthy young adults who underwent18F-FP-CIT positron emission tomography (PET) scans, and sweet taste questionnaire (STQ). Thirty-five healthy subjects were enrolled in this study. Each subject visited the institution three times, for three brain PET scans (two18F-FP-CIT PET scans after the infusion of glucose or placebo and one18F-Fluorodeoxyglucose PET scan). All subjects underwent STQ, 12-item self-reporting to evaluate subjects’ reactions to eating sweets, craving for sweets and degree of control over eating sweet foods (STQ 1: sensitivity to mood altering effect of sweets, and STQ 2: impaired control over eating sweet foods). We created Bayesian models separately with STQ 1, and STQ 2 as predictors, with DAT availability and brain glucose uptake as a dependent variable. From caudate, glucose-loaded DAT availability was significantly higher than placebo-loaded DAT availability, and from putamen, glucose-loaded DAT availability showed the higher trend than placebo-loaded DAT availability. STQ was positively associated with glucose-loaded DAT availability. The effect of STQ markedly overlapped with zero on placebo-loaded DAT availability, and brain glucose uptake. In conclusion, the change of striatal DAT availability after glucose loading is associated with the vulnerability to sweet foods. This may indicate that individuals with higher DAT availability after glucose loading experience a rapid clearance of synaptic dopamine after consuming sweet foods, potentially leading to a desire for additional sweet foods.
Magnetomyography: A novel modality for non-invasive muscle sensing
Authors: Yun Richy , Gonzalez Gabriel , Gerrard Isabel , Csaky Richard , Dash Debadatta , Kittle Evan , Deka Nishita , Labanowski Dominic 
Published: April 2024

AbstractThe measurement of magnetic fields generated by skeletal muscle activity, called magnetomyography (MMG), has seen renewed interest from the academic community in recent years. Although studies have demonstrated complex models of MMG and experiments classifying between different movements using MMG, there has yet to be time frequency analysis of MMG as well as concurrent recordings of MMG and its electrical counterpart, surface electromyography (sEMG). Here, we aim to better understand MMG in the context of sEMG by simultaneously recording both modalities during various muscle contraction tasks. We found that, similar to sEMG, MMG shows highly linearly correlated power to the degree of muscle contraction, has a unimodal distribution in spectral power, and can detect changes in muscle fatigue via changes in the spectral distribution. One main difference we found was that MMG typically has more high frequency content compared to sEMG, even when accounting for the filtering induced by the size of the sEMG electrodes. We additionally demonstrate empirically the decrease in MMG power due to distance from the arm and show MMG decreases slower than the inverse square law and can be measured up to 50 mm from the surface of the skin. Finally, we were able to capture MMG with non-OPM sensors showing that sensor technology has made great strides towards enabling MMG applications.
Pharmacological inhibition of astrocytic transglutaminase 2 facilitates the expression of a neurosupportive astrocyte reactive phenotype in association with increased histone acetylation
Authors: Delgado Thomas , Emerson Jacen , Hong Matthew , Keillor Jeffrey W. , Johnson Gail VW 
Published: April 2024

AbstractAstrocytes play critical roles in supporting structural and metabolic homeostasis in the central nervous system (CNS). CNS injury leads to the development of a range of reactive phenotypes in astrocytes whose molecular determinants are poorly understood. Finding ways to modulate astrocytic injury responses and leverage a pro-recovery phenotype holds promise in treating CNS injury. Recently, it has been demonstrated that ablation of astrocytic transglutaminase 2 (TG2) modulates the phenotype of reactive astrocytes in a way that improves neuronal injury outcomes bothin vitroandin vivo. In anin vivomouse model, pharmacological inhibition of TG2 with the irreversible inhibitor VA4 phenocopies the neurosupportive effects of TG2 deletion in astrocytes. In this study, we provide insights into the mechanisms by which TG2 deletion or inhibition result in a more neurosupportive astrocytic phenotype. Using a neuron-astrocyte co-culture model, we show that VA4 treatment improves the ability of astrocytes to support neurite outgrowth on an injury-relevant matrix. To better understand how pharmacologically altering TG2 affects its ability to regulate reactive astrocyte phenotypes, we assessed how VA4 inhibition impacts TG2’s interaction with Zbtb7a, a transcription factor we have previously identified as a functionally relevant TG2 nuclear interactor. The results of these studies demonstrate that VA4 significantly decreases the interaction of TG2 and Zbtb7a. TG2’s interactions with Zbtb7a, as well as a wide range of other transcription factors and chromatin regulatory proteins, suggest that TG2 may act as an epigenetic regulator to modulate gene expression. To begin to understand if TG2-mediated epigenetic modification may impact astrocytic phenotypes in our models, we interrogated the effect of TG2 deletion and VA4 treatment on histone acetylation and found significantly greater acetylation in both experimental groups. Consistent with these findings, previous RNA-sequencing and our present proteomic analysis also supported a predominant transcriptionally suppressive role of TG2 in astrocytes. Our proteomic data additionally unveiled pronounced changes in lipid and antioxidant metabolism in astrocytes with TG2 deletion or inhibition, which likely contribute to the enhanced neurosupportive function of these astrocytes.
Endothelial and neuronal engagement by AAV-BR1 alleviates neurological symptoms and cholesterol deposition in a mouse model of Niemann-Pick type C2
Authors: Rasmussen Charlotte Laurfelt Munch , Heegaard Christian Würtz , Thomsen Maj Schneider , Hede Eva , Laczek Bartosz , Körbelin Jakob , Thomsen Louiza Bohn , Schwaninger Markus , Moos Torben , Burkhart Annette 
Published: April 2024

AbstractBackgroundPatients with the genetic disorder Niemann-Pick type C2 disease (NP-C2) suffer from lysosomal accumulation of cholesterol causing both systemic and severe neurological symptoms. In a murine NP-C2 model, otherwise successful intravenous Niemann-Pick C2 protein (NPC2) replacement therapy fails to alleviate progressive neurodegeneration as infused NPC2 is unable to cross the blood-brain barrier (BBB). Genetic modification of brain endothelial cells (BECs) is thought to enable secretion of recombinant proteins thereby overcoming the restrictions of the BBB. We hypothesized that BBB-directed gene therapy using the AAV-BR1-NPC2 vector would transduce both BECs and neurons in a mouse model of NP-C2 (Npc2-/-).MethodsSix weeks oldNpc2-/- mice were intravenously injected with the AAV-BR1-NPC2 vector. Post-mortem analyses included gene expression analyses, determination of NPC2 transduction in the CNS, and co-detection of cholesterol with NPC2 in neurons.ResultsThe vector exerted tropism for BECs and neurons resulting in a widespread NPC2 distribution in the brain with a concomitant reduction of cholesterol in adjacent neurons, presumably not transduced by the vector.ConclusionThe data suggests cross-correcting gene therapy to the brain via delivery of NPC2 from BECs and neurons.
The disappointment centre of the brain gets exciting: A systematic review of habenula dysfunction in depression
Authors: Cameron Sarah , Weston-Green Katrina , Newell Kelly A 
Published: April 2024

AbstractBackgroundThe habenula is an epithalamic brain structure that acts as a neuroanatomical hub connecting the limbic forebrain to the major monoamine centres. Abnormal habenula activity is increasingly implicated in depression, with a surge in publications on this topic in the last 5 years. Direct stimulation of the habenula is sufficient to induce a depressive phenotype in rodents, suggesting a causative role in depression. However, the molecular basis of habenula dysfunction in depression remains elusive and it is unclear how the preclinical advancements translate to the clinical field.MethodsA systematic literature search was conducted following the PRISMA guidelines. The two search terms depress* and habenula* were applied across the databases Scopus, Web of Science and PubMed. Studies eligible for inclusion must have examined changes in the habenula in clinical cases of depression or preclinical models of depression.ResultsPreclinical studies (n=57) measured markers of habenula activity (n=16) and neuronal firing (n=21), largely implicating habenula hyperactivity in depression. Neurotransmission was briefly explored (n=13), suggesting imbalances within excitatory and inhibitory habenula signalling. Additional preclinical studies reported neuroconnectivity (n=1), inflammatory (n=2), genomic (n=2) and circadian rhythm (n=2) abnormalities. Seven preclinical studies (12.2%) included both males and females. From these, 5 studies (71%) reported a significant difference between the sexes in at least one habenula measure taken. Clinical studies (n=18) reported abnormalities in habenula connectivity (n=11), volume (n=5) and molecular markers (n=2). Clinical studies generally included male and female subjects (n=15), however, few of these studies examined sex as a biological variable (n=5)ConclusionsBoth preclinical and clinical evidence suggest the habenula is disrupted in depression. However, there are opportunities for sex-specific analyses across both areas. Preclinical evidence consistently suggests habenula hyperactivity as a primary driver for the development of depressive symptoms. Clinical studies support gross habenula abnormalities such as altered activation, connectivity, and volume, with emerging evidence of blood brain barrier dysfunction, however, progress is limited by a lack of detailed molecular analyses.
Short report: A judgment bias task reveals stress produces a negative affective state in cuttlefish
Authors: Giancola-Detmering Sarah E. , Crook Robyn J. 
Published: April 2024

AbstractJudgment Bias Tasks (JBT) are used to assess emotional state and welfare of animals in zoos, farms, and laboratories, based on a subject’s interpretation of an ambiguous or intermediate cue. Animals in positive affective states are more likely to interpret the ambiguous cue positively, reflecting optimistic bias and animals with negative affect are more likely to interpret ambiguous cues pessimistically. Here, we developed a JBT assay for the stumpy-spined cuttlefish,Sepia bandensis, to determine whether cuttlefish exhibit negative affective states resulting from chronic and acute stress. Cuttlefish learned to associate food with a visual cue. Positive and neutral cues were presented twice daily until animals oriented to the positive cue and searched for food. After training, one treatment group was exposed to combined chronic and acute stress produced by 5 days of impoverished housing and once-daily simulated net capture. Our control group received no stress experience. In test trials performed after the stress experience, stressed animals had higher latencies to approach ambiguous cues, spent significantly less time in rooms with ambiguous cues once they entered, and were less likely to enter first into the ambiguous cue-paired room compared with controls. These behaviors suggest that stress induces pessimistic judgment bias in cuttlefish, the first indication of this capacity in cephalopods.
Protein Translation Dysregulation and Immune Cell Evasion Define Metastatic Clones in HPV-related Cancer of the Oropharynx
Authors: Chin Venessa T , Muskovic Walter , McCloy Rachael A , Neavin Drew R , Alquicira-Hernandez Jose , Arora Himanshi , Senabouth Anne , Keith Patricia , Spenceley Ellie , Murphy Angela , Kaczorowski Dominik , Floros Peter , Earls Peter , Leavers Brett , Crawford Julia , Gallagher Richard , Powell Joseph E. 
Published: April 2024

SummaryHead and neck cancers, representing the seventh most common malignancy globally, have seen a shift in causative factors from traditional smoking and alcohol use to human papillomavirus (HPV) infection, now accounting for up to 80% of oropharyngeal cancers. We identify the cellular and clonal mechanisms underlying immune avoidance and metastasis by analysing single-cell and spatial genomic data from primary and metastatic cancers. We first map the clonal evolution of malignant cells based on the accumulation of mutations. We identify metastasising clones based on mutational similarity scores between cells in the primary and lymph node metastasis. Genomic analysis of metastasising and non-metastasising clones identified virally mediated protein translation relief (P=4.24x10-24) pathway underlying metastatic expansion. We show that in metastatic clones, this process is driven through upregulation of transition-initiating factors,EIF4E(P=1.5x10-13) andEIFG1(P<2.22x10-16), and suppression of regulatory kinasesEIF4EBP1(P=2.1x10),EIF2AK2(P<2.22x10-16), andEIF2S1(P<2.22x10-16). We subsequently identify that metastatic clones have a corresponding downregulation of theJAK/STATpathway and immunoproteasome genesPSMB8(P<2.22x10-16) andPSMB9(P<2.22x10-16), suggesting these clones escape immune surveillance through decreasedINFinflammatory response and antigen presentation. We validate these results using spatial RNA-seq data, where metastatic cancer clones show decreased cell-to-cell interactions with CD4 T-effector memory cells (CD4TEM) (P=0.0077), CD8 T-exhausted cells (CD8Ex) (P=0.0191), and innate lymphoid cells (ILC) (P=0.04). Finally, we demonstrate that the upregulation of cap-independent translational drives cell proliferation in metastatic clones through the expression of translation initiation factors (EIF4G1: P<2.22x10-16). Our results provide evidence of the mechanisms by which virally induced cancer clones lead to advanced disease and poor prognosis in patients.
Augmenting mortality prediction with medication data and machine learning models
Authors: Murray Brian , Zhang Tianyi , Most Amoreena , Chen Xianyan , Smith Susan E. , Devlin John W. , Murphy David J. , Sikora Andrea , Kamaleswaran Rishikesan 
Published: April 2024

AbstractBackgroundIn critically ill patients, complex relationships exist among patient disease factors, medication management, and mortality. Considering the potential for nonlinear relationships and the high dimensionality of medication data, machine learning and advanced regression methods may offer advantages over traditional regression techniques. The purpose of this study was to evaluate the role of different modeling approaches incorporating medication data for mortality prediction.MethodsThis was a single-center, observational cohort study of critically ill adults. A random sample of 991 adults admitted ≥ 24 hours to the intensive care unit (ICU) from 10/2015 to 10/2020 were included. Models to predict hospital mortality at discharge were created. Models were externally validated against a temporally separate dataset of 4,878 patients. Potential mortality predictor variables (n=27, together with 14 indicators for missingness) were collected at baseline (age, sex, service, diagnosis) and 24 hours (illness severity, supportive care use, fluid balance, laboratory values, MRC-ICU score, and vasopressor use) and included in all models. The optimal traditional (equipped with linear predictors) logistic regression model and optimal advanced (equipped with nature splines, smoothing splines, and local linearity) logistic regression models were created using stepwise selection by Bayesian information criterion (BIC). Supervised, classification-based ML models [e.g., Random Forest, Support Vector Machine (SVM), and XGBoost] were developed. Area under the receiver operating characteristic (AUROC), positive predictive value (PPV), and negative predictive value (NPV) were compared among different mortality prediction models.ResultsA model including MRC-ICU in addition to SOFA and APACHE II demonstrated an AUROC of 0.83 for hospital mortality prediction, compared to AUROCs of 0.72 and 0.81 for APACHE II and SOFA alone. Machine learning models based on Random Forest, SVM, and XGBoost demonstrated AUROCs of 0.83, 0.85, and 0.82, respectively. Accuracy of traditional regression models was similar to that of machine learning models. MRC-ICU demonstrated a moderate level of feature importance in both XGBoost and Random Forest. Across all ten models, performance was lower on the validation set.ConclusionsWhile medication data were not included as a significant predictor in regression models, addition of MRC-ICU to severity of illness scores (APACHE II and SOFA) improved AUROC for mortality prediction. Machine learning methods did not improve model performance relative to traditional regression methods.
Crisis Readiness and Innovation for Burnout Prevention Among Community Health Workers
Authors: Raghavan Ramya 
Published: April 2024

AbstractThe performance of community health workers is an important factor in the success of health systems in underserved, vulnerable populations. Community health workers (CHWs) face work-related burnout. This study used a survey instrument to identify facilitators and barriers to a health crisis or pandemic preparedness. Causes of burnout and factors of crisis readiness were examined, including CHWs’ health status, readiness to use technology, and organisational culture. Findings suggest that more technology training and organisational support are needed to develop a resilient healthcare system. Increased workloads and demanding work schedules contribute to burnout, highlighting the need for support resources to promote the physical and mental health of CHWs. The study also collected data on CHWs’ perspectives on organisational commitment and individual innovation behaviours. The sample population is motivated to try new ideas and work methods to meet dynamic challenges and work expectations. Despite systemic shortcomings, more than 50% of them can envision a career with their community health organisation. Therefore, collaborative efforts are needed to create a work environment that promotes the physical well-being and professional development of CHWs. It is of practical importance for managers to value fostering innovation and organisational commitment in their healthcare workforce. In addition, our study is relevant to policymakers at local and central levels to plan national programmes for crisis preparedness and building a healthy nation.
Genomic and phenotypic correlates of mosaic loss of chromosome Y in blood
Authors: Jakubek Yasminka A. , Ma Xiaolong , Stilp Adrienne M. , Yu Fulong , Bacon Jason , Wong Justin W. , Aguet Francois , Ardlie Kristin , Arnett Donna , Barnes Kathleen , Bis Joshua C. , Blackwell Tom , Becker Lewis C. , Boerwinkle Eric , Bowler Russell P. , Budoff Matthew J. , Carson April P. , Chen Jiawen , Cho Michael H. , Coresh Josef , Cox Nancy , de Vries Paul S. , DeMeo Dawn L. , Fardo David W. , Fornage Myriam , Guo Xiuqing , Hall Michael E. , Heard-Costa Nancy , Hidalgo Bertha , Irvin Marguerite Ryan , Johnson Andrew D. , Kenny Eimear E. , Levy Dan , Li Yun , Lima Joao AC. , Liu Yongmei , Loos Ruth J.F. , Machiela Mitchell J. , Mathias Rasika A. , Mitchell Braxton D. , Murabito Joanne , Mychaleckyj Josyf C. , North Kari , Orchard Peter , Parker Stephen CJ. , Pershad Yash , Peyser Patricia A. , Pratte Katherine A. , Psaty Bruce M. , Raffield Laura M. , Redline Susan , Rich Stephen S. , Rotter Jerome I. , Shah Sanjiv J. , Smith Jennifer A. , Smith Aaron P. , Smith Albert , Taub Margaret , Tiwari Hemant K. , Tracy Russell , Tuftin Bjoernar , Bick Alexander G. , Sankaran Vijay G. , Reiner Alexander P. , Scheet Paul , Auer Paul L. 
Published: April 2024

AbstractMosaic loss of Y (mLOY) is the most common somatic chromosomal alteration detected in human blood. The presence of mLOY is associated with altered blood cell counts and increased risk of Alzheimer’s disease, solid tumors, and other age-related diseases. We sought to gain a better understanding of genetic drivers and associated phenotypes of mLOY through analyses of whole genome sequencing of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program. This approach enabled us to identify differences in mLOY frequencies across populations defined by genetic similarity, revealing a higher frequency of mLOY in the European American (EA) ancestry group compared to those of Hispanic American (HA), African American (AA), and East Asian (EAS) ancestry. Further, we identified two genes (CFHR1andLRP6) that harbor multiple rare, putatively deleterious variants associated with mLOY susceptibility, show that subsets of human hematopoietic stem cells are enriched for activity of mLOY susceptibility variants, and that certain alleles on chromosome Y are more likely to be lost than others.
Effects of parental autoimmune diseases on type 1 diabetes in offspring can be partially explained by HLA and non-HLA polymorphisms
Authors: Wang Feiyi , Liu Aoxing , Yang Zhiyu , Vartiainen Pekka , Jukarainen Sakari , Koskela Satu , Oram Richard A. , Allen Lowri , Ritari Jarmo , Partanen Jukka , FinnGen Markus Perola , Tuomi Tiinamaija , Ganna Andrea 
Published: April 2024

SUMMARYType 1 diabetes (T1D) and other autoimmune diseases (AIDs) often co-occur in families. Leveraging data from 58,284 family trios in Finnish nationwide registers (FinRegistry), we identified that, out of 50 parental AIDs examined, 15 were associated with an increased T1D risk in offspring. These identified epidemiological associations were further assessed in 470K genotyped Finns from FinnGen study through comprehensive genetic analyses, partitioned into HLA and non-HLA variations. Using FinnGen’s 12,563 trios, a within-family polygenic transmission analysis demonstrated that the aggregation of many parental AIDs with offspring T1D can be partially explained by HLA and non-HLA polymorphisms in a disease-dependent manner. We, therefore, proposed a parental polygenic score (PGS), incorporating both HLA and non-HLA polymorphisms, to characterize the cumulative risk pattern of T1D in offspring. This raises an intriguing possibility of using parental PGS, in conjunction with clinical diagnoses, to inform individuals about T1D risk in their offspring.