bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Machine Learning Approach to Predict Cellular Mechanical Stresses in Response to Chemical Perturbation
Authors: SubramanianBalachandar V.A. , Islam Md. Mydul , Steward R. L. 
Published: February 2023

AbstractMechanical stresses generated at the cell-cell level and cell-substrate level have been suggested to be important in a host of physiological and pathological processes. However, the influence various chemical compounds have on the mechanical stresses mentioned above is poorly understood, hindering the discovery of novel therapeutics and representing a barrier in the field. To overcome this barrier, we implemented two machine learning (ML) Models: Stepwise Linear Regression (SLR) and Quadratic Support Vector Machine (QSVM) to predict the dose-dependent response of tractions and intercellular stresses to chemical perturbation. We used traction and intercellular stress experimental data gathered from 0.2 μg/mL and 2 μg/mL drug concentrations along with cell morphological properties to train our model. To demonstrate the predictive capability of our ML model we predicted tractions and intercellular stresses in response to 0 μg/ml & 1 μg/ml drug concentrations. Results revealed the QSVM model to best predict intercellular stresses, while SLR best predicted tractions.Author SummaryThe ML framework we present here can be used to predict the mechanical response of any anchorage-dependent cell type to any chemical perturbation. The proposed ML can directly predict the intercellular stresses or tractions as a function of drug dosage and/or monolayer/cell coverage area which could potentially reduce the experimental time on studying the mechanics of cells to external chemicals or mechanical constraints. We believe our findings could be helpful in accelerating drug discovery and increase our understanding in the role of cellular stresses during disease progression.
A maize lipid droplet-associated protein is modulated by a virus to promote viral multiplication and infection
Authors: Wang Siyuan , Li Siqi , Wang Xinyu , Sun Xi , Xue Mingshuo , Di Dianping , Zhang Aihong , Zhang Yongjiang , Xia Yiji , Zhou Tao , Fan Zaifeng 
Published: February 2023

AbstractPathogen infection induces massive reprogramming of host primary metabolism. Lipid and fatty acid metabolism is generally disrupted by pathogens and co-opted for their proliferation. Lipid droplets (LDs) that play important roles in regulating cellular lipid metabolism are utilized by a variety of pathogens in mammalian cells. However, the function of LDs during pathogenic infection in plants remains unknown. We show here that infection by rice black streaked dwarf virus (RBSDV) affects the lipid metabolism of maize, which causes elevated accumulation of C18 polyunsaturated fatty acids (PUFAs) leading to viral proliferation and symptom development. Overexpression of one of the two novel LD-associated proteins (LDAPs) of maize (ZmLDAP1 and ZmLDAP2) induces LD clustering. The core capsid protein P8 of RBSDV interacts with ZmLDAP2 and prevents its degradation through the ubiquitin-proteasome system mediated by a UBX domain-containing protein, PUX10. In addition, silencing of theZmLDAP2down-regulates expression of fatty acid desaturase genes in maize, leading to a decrease in C18 PUFAs levels and suppression of RBSDV accumulation. Our findings reveal that the plant virus recruits LDAP to regulate cellular fatty acid metabolism to promote viral multiplication and infection. These results expand the knowledge of the LD functions and viral infection mechanism in plants.One Sentence SummaryRice black streaked dwarf virus recruits a lipid droplet-associated protein to regulate cellular fatty acid metabolism for promoting viral multiplication and infection.
Mental health outcomes of encephalitis: an international web-based study
Authors: Abdat Yasmin , Butler Matt , Zandi Michael , Michael Benedict D , Coutinho Ester , Nicholson Timothy R , Easton Ava , Pollak Thomas A 
Published: February 2023

AbstractEncephalitis is associated with psychiatric symptoms in the acute and post-acute stages, and many survivors experience long-term sequelae. Despite this, the breadth and severity of mental health symptoms in survivors of encephalitis has not been systematically reported. We recruited adults who had been diagnosed with encephalitis of any aetiology to complete a web-based questionnaire assessing a wide range of mental health symptoms and disorders. In total, 445 respondents from 31 countries (55.1% UK, 23.1% USA, 2.2% low-and middle-income countries) completed the survey, with a median seven years since encephalitis diagnosis; 84.7% were diagnosed by a neurologist or infectious diseases doctor. Infectious encephalitis constituted 65.4% of cases, autoimmune 29.7%. Mean age was 50.1 years (SD 15.6); 65.8% were female. The most common self-reported psychiatric symptoms were anxiety (75.2%), sleep problems (64.4%), mood problems (62.2%), unexpected crying (35.2%), and aggression (29.9%). Rates of self-reported psychiatric diagnoses following encephalitis were high: anxiety (44.0%), depression (38.6%), panic disorder (15.7%), and post-traumatic stress disorder (PTSD, 21.3%); these rates were broadly consistent with the results of a validated self-report measure, the Psychiatric Diagnostic Screening Questionnaire (PDSQ). Severe mental illnesses such as psychosis (3.3%) and bipolar affective disorder (3.1%) were also reported. Many respondents also felt they had symptoms of disorders including anxiety (37.5%), depression (28.1%), PTSD (26.8%), or panic disorder (20.9%) which had not been diagnosed by a professional. Overall, rates of major self-reported psychiatric diagnoses and symptoms did not significantly differ between autoimmune and infectious encephalitis. In total, 37.5% of respondents had thought about suicide, and 4.4% had attempted suicide since their encephalitis diagnosis. Over half (53.5%) reported that they either had no, or substandard, access to appropriate care for their mental health. High rates of sensory hypersensitivities (>75%) suggest a previously unreported association between encephalitis and this distressing symptom cluster. This large international survey indicates that psychiatric symptoms following encephalitis are common, and that mental healthcare provision to this population may be inadequate, highlighting a need for increased provision of proactive psychiatric care for these patients.
Prediction of Preeclampsia from Clinical and Genetic Risk Factors in Early and Late Pregnancy Using Machine Learning and Polygenic Risk Scores
Authors: Kovacheva Vesela P , Eberhard Braden W , Cohen Raphael Y , Maher Matthew , Saxena Richa , Gray Kathryn J 
Published: February 2023

ABSTRACTBackgroundPreeclampsia, a pregnancy-specific condition associated with new-onset hypertension after 20 weeks gestation, is a leading cause of maternal and neonatal morbidity and mortality. Predictive tools to understand which individuals are most at risk are needed.MethodsWe identified a cohort of N=1,125 pregnant individuals who delivered between 05/2015-05/2022 at Mass General Brigham hospitals with available electronic health record (EHR) data and linked genetic data. Using clinical EHR data and systolic blood pressure polygenic risk scores (SBP PRS) derived from a large genome-wide association study, we developed machine learning (xgboost) and linear regression models to predict preeclampsia risk.ResultsPregnant individuals with an SBP PRS in the top quartile had higher blood pressures throughout pregnancy compared to patients within the lowest quartile SBP PRS. In the first trimester, the most predictive model was xgboost, with an area under the curve (AUC) of 0.73. Adding the SBP PRS to the models improved the performance only of the linear regression model from AUC 0.70 to 0.71; the predictive power of other models remained unchanged. In late pregnancy, with data obtained up to the delivery admission, the best performing model was xgboost using clinical variables, which achieved an AUC of 0.91.ConclusionsIntegrating clinical and genetic factors into predictive models can inform personalized preeclampsia risk and achieve higher predictive power than the current practice. In the future, personalized tools can be implemented in clinical practice to identify high-risk patients for preventative therapies and timely intervention to improve adverse maternal and neonatal outcomes.
Increased Spatiotemporal Variability after Stroke is not Just the Outcome of Walking Velocity
Authors: Koren Yogev , Barzel Oren , Shmuelof Lior , Handelzalts Shirley 
Published: February 2023

AbstractBackgroundIncreased spatiotemporal gait variability is considered a clinical biomarker of ageing and pathology, and a predictor of future falls. Nevertheless, it is unclear whether the increased spatiotemporal variability observed in persons with stroke (PwS) is directly related to the pathology or simply reflects their choice of walking velocity.Research questionDoes increased spatiotemporal gait variability directly relate to motor coordination deficits after stroke?MethodsForty PwS and 20 healthy adults participated in this cross-sectional study. Participants performed the lower-extremity motor coordination test (LEMOCOT) on an electronic mat equipped with force sensors. Then, participants walked for 120 s over a computerized treadmill at their comfortable walking velocity. For the LEMOCOT we used the traditional score of in-target touch count and computed the absolute and variable error around the targets. For gait variability, we extracted the standard deviation of step time, step length, step velocity, and step width. Using a data-based approach, we generated a model of the relationship between velocity and variability and tested the correlations of the velocity-controlled values with the outcome measures from the LEMOCOT.ResultsPwS demonstrated increased variability in step time, step length, and step velocity, as well as decreased variability in step width, in comparison to healthy adults, even after controlling for walking velocity. After controlling for walking velocity, we observed that for PwS the LEMOCOT score correlated with the variance in step time, and the variable error in the LEMOCOT correlated with the variance in step length, in step width, and in step velocity. No significant correlation with any of the velocity-controlled step parameters was found for the absolute error in the LEMOCOT.SignificanceDecreased performance in the LEMOCOT was associated with increased spatiotemporal variability in PwS, regardless of their walking velocity. Our results demonstrate the connection between lower-extremity coordination impairments and deficits in gait function.
Anticipating and assessing adverse and other unintended consequences of public health interventions: the (CONSEQUENT) framework
Authors: Stratil Jan M , Biallas Renke L , Movsisyan Ani , Oliver Kathryn , Rehfuess Eva A 
Published: February 2023

1AbstractDespite the best intentions public health interventions (PHIs) can have adverse and other unintended consequences (AUCs). AUCs are rarely systematically examined when developing, evaluating or implementing PHIs. We used a structured, multi-pronged and evidence-based approach to develop a framework to support researchers and decision-makers in conceptualising and categorising AUCs of PHIs.We employed the ‘best-fit’ framework synthesis approach. We designed the a-priori framework using elements of the WHO-INTEGRATE framework and the Behaviour Change Wheel. Next, we conducted a qualitative systematic review of theoretical and conceptual publications on the AUCs of PHIs in the databases Medline and Embase as well as through grey literature searches. Based on these findings, we iteratively revised and advanced the a-priori framework based on thematic analysis of the identified research. To validate and further refine the framework, we coded four systematic reviews on AUCs of distinct PHIs against it.The CONSEQUENT framework includes two components: the first focuses on AUCs and serves to categorise them; the second component highlights the mechanisms through which AUCs may arise. The first component comprises eight domains of consequences – health, health system, human and fundamental rights, acceptability and adherence, equality and equity, social and institutional, economic and resource, and ecological.The CONSEQUENT framework is intended to facilitate conceptualisation and categorising of AUCs of PHIs during their development, evaluation and implementation to support evidence-informed decision-making.
Trends in cross-border and illicit tobacco purchases and associations with motivation to stop smoking and quit attempts: a representative survey of smokers in England, 2019-2022
Authors: Jackson Sarah E. , Cox Sharon , Brown Jamie 
Published: February 2023

AbstractObjectivesThe last five years have seen substantial changes in England’s social and economic landscape as a result of Brexit, the Covid-19 pandemic, and cost-of-living crisis. We aimed to examine changes in cross-border and illicit tobacco purchasing, and associations with quitting activity, over this period.DesignNationally-representative monthly cross-sectional survey.SettingEngland, 2019-2022.Participants11,232 adult (≥18y) past-year smokers.Main outcome measuresWe estimated time trends in the proportion of smokers reporting purchasing tobacco from (i) cross-border and (ii) illicit sources in the past 6 months, and examined associations with motivation to stop smoking (among current smokers) and past-year quit attempts (among past-year smokers).ResultsBetween February 2019 and October 2022, there was a non-linear increase in the proportion of smokers reporting purchasing cross-border tobacco (from 5.2% to 16.1%; PR=3.10, 95%CI=2.03-4.73) but no overall change in the proportion reporting purchasing illicit tobacco (from 9.2% to 8.5%; PR=0.92, 95%CI=0.70-1.21). Both cross-border (ORadj=0.65, 95%CI=0.56-0.77) and illicit (ORadj=0.74, 95%CI=0.63-0.86) tobacco purchasing were associated with lower odds of reporting a recent quit attempt. Smokers who purchased cross-border tobacco also reported lower motivation to stop smoking (ORadj=0.84, 95%CI=0.75-0.95).ConclusionsDespite a fall in cross-border tobacco purchasing during the first year of the Covid-19 pandemic, the proportion of smokers in England reporting purchasing cross-border tobacco is now three times higher than it was at the start of 2019. The proportion reporting purchasing illicit tobacco has not changed substantially. Tackling the increasing use of cheap tobacco in England may be an important target for motivating quit attempts.What this paper addsWhat is already known on this topicTobacco tax avoidance and evasion strategies, such as buying tobacco cheaply from cross-border or illicit sources, undermine the effectiveness of tax policy.What this study addsSince February 2019, the proportion of smokers in England reporting purchasing cross-border tobacco has tripled, while the proportion reporting purchasing illicit tobacco remains similar. Smokers who use cheap tobacco are less likely to try to quit.How this study might affect research, practice or policyPolicy measures that reduce smokers’ access to these cheaper sources of tobacco could help to increase the rate of quit attempts among smokers and accelerate progress toward the government’s smokefree 2030 target.
Effect of Total Sphingomyelin Synthase Activity on Low Density Lipoprotein Catabolism in Mice
Authors: Li Zhiqiang , He Mulin , Chen Guangzhi , Worgall Tilla S. , Jiang Xian-Cheng 
Published: February 2023

AbstractBackgroundSphingomyelin (SM) and cholesterol are two key lipid partners on cell membranes and on lipoproteins. Many studies have indicated the influence of cholesterol on SM metabolism. This study examined the influence of SM biosynthesis on cholesterol metabolism.MethodsInducible globalSms1KO/globalSms2KO mice were prepared to evaluate the effect of whole-body SM biosynthesis deficiency on lipoprotein metabolism. Tissue cholesterol, SM, ceramide, and glucosylceramide levels were measured. TG production rate and LDL catabolism were measured. Lipid rafts were isolated and LDL receptor mass and function were evaluated. Also, the effects of exogenous sphingolipids on hepatocytes were investigated.ResultsWe found that total SMS depletion significantly reduced plasma SM levels. Also, the total deficiency significantly induced plasma cholesterol, apoB, and apoE levels. Importantly, total SMS deficiency, but not SMS2 deficiency, dramatically decreased LDL receptors in the liver and attenuated LDL uptake through the receptor. Further, we found that total SMS deficiency greatly reduced LDL receptors in the lipid rafts which contained significantly lower SM and significantly higher glucosylceramide as well as cholesterol. Furthermore, we treated primary hepatocytes and Huh7 cells (a human hepatoma cell line) with SM, ceramide, or glucosylceramide, and we found that only SM could up-regulate LDL receptor levels in a dose-dependent fashion.ConclusionsWhole-body SM biosynthesis plays an important role in LDL-cholesterol catabolism. The total SMS deficiency, but not SMS2 deficiency, reduces LDL uptake and causes LDL-cholesterol accumulation in the circulation. Given the fact that serum SM level is a risk factor for cardiovascular diseases, inhibiting SMS2 but not SMS1 should be the desirable approach.Graphic Abstract
Prior vaccination enhances immune responses during SARS-CoV-2 breakthrough infection with early activation of memory T cells followed by production of potent neutralizing antibodies
Authors: Painter Mark M. , Johnston Timothy S. , Lundgreen Kendall A. , Santos Jefferson J.S. , Qin Juliana S. , Goel Rishi R. , Apostolidis Sokratis A. , Mathew Divij , Fulmer Bria , Williams Justine C. , McKeague Michelle L. , Pattekar Ajinkya , Goode Ahmad , Nasta Sean , Baxter Amy E. , Giles Josephine R. , Skelly Ashwin N. , Felley Laura E. , McLaughlin Maura , Weaver Joellen ,   Penn Medicine BioBank, Kuthuru Oliva , Dougherty Jeanette , Adamski Sharon , Long Sherea , Kee Macy , Clendenin Cynthia , da Silva Antunes Ricardo , Grifoni Alba , Weiskopf Daniela , Sette Alessandro , Huang Alexander C. , Rader Daniel J. , Hensley Scott E. , Bates Paul , Greenplate Allison R. , Wherry E. John 
Published: February 2023

AbstractSARS-CoV-2 infection of vaccinated individuals is increasingly common but rarely results in severe disease, likely due to the enhanced potency and accelerated kinetics of memory immune responses. However, there have been few opportunities to rigorously study early recall responses during human viral infection. To better understand human immune memory and identify potential mediators of lasting vaccine efficacy, we used high-dimensional flow cytometry and SARS-CoV-2 antigen probes to examine immune responses in longitudinal samples from vaccinated individuals infected during the Omicron wave. These studies revealed heightened Spike-specific responses during infection of vaccinated compared to unvaccinated individuals. Spike-specific CD4 T cells and plasmablasts expanded and CD8 T cells were robustly activated during the first week. In contrast, memory B cell activation, neutralizing antibody production, and primary responses to non-Spike antigens occurred during the second week. Collectively, these data demonstrate the functionality of vaccine-primed immune memory and highlight memory T cells as rapid responders during SARS-CoV-2 infection.
Automatic Whole Body FDG PET/CT Lesion Segmentation using Residual UNet and Adaptive Ensemble
Authors: Murugesan Gowtham Krishnan , McCrumb Diana , Brunner Eric , Kumar Jithendra , Soni Rahul , Grigorash Vasily , Chang Anthony , VanOss Jeff , Moore Stephen 
Published: February 2023

AbstractMultimodal Positron Emission Tomography/Computed Tomography (PET/CT) plays a key role in the diagnosis, staging, restaging, treatment response assessment, and radiotherapy planning of malignant tumors. The complementary nature of high-resolution anatomic CT and high sensitivity/specificity molecular PET imaging provides accurate assessment of disease status [14] In oncology, 18-fluorodeoxyglucose (FDG) PET/CT is the most widely used method to identify and analyze metabolically active tumors. In particular, FDG uptake allows for more accurate detection of both nodal and distant forms of metastatic disease. Accurate quantification and staging of tumors is the most important prognostic factor for predicting the survival of patients and for designing personalized patient management plans. [8,3] Analyzing PET/CT quantitatively by experienced medical imaging experts/radiologists is timeconsuming and error-prone. Automated quantitative analysis by deep learning algorithms to segment tumor lesions will enable accurate feature extraction, tumor staging, radiotherapy planning, and treatment response assessment. The AutoPET Challenge 2022 provided an opensource platform to develop and benchmark deep learning models for automated PET lesion segmentation by providing large open-source wholebody FDG-PET/CT data. Using the multimodal PET/CT data from 900 subjects with 1014 studies provided by the AutoPET MICCAI 2022 Challenge, we applied fivefold cross-validation on residual UNETs to automatically segment lesions. We then utilized the output from adaptive ensemble highly contributive models as the final segmentation. Our method achieved a 10th ranking with a dice score of 0.5541 in the heldout test dataset (N=150 studies).
Intraoral thermal processing in the gustatory cortex of awake mice
Authors: Bouaichi Cecilia G. , Odegaard Katherine E. , Neese Camden , Vincis Roberto 
Published: February 2023

AbstractOral temperature is a sensory cue relevant to food preference and nutrition. To understand how orally-sourced thermal inputs are represented in the gustatory cortex (GC) we recorded neural responses from the GC of male and female mice presented with deionized water at different innocuous temperatures (14 °C, 25 °C, 36 °C) and taste stimuli (room temperature). Our results demonstrate that GC neurons encode orally-sourced thermal information in the absence of classical taste qualities at the single neuron and population levels, as confirmed through additional experiments comparing GC neuron responses to water and artificial saliva. Analysis of thermal-evoked responses showed broadly tuned neurons that responded to temperature in a mostly monotonic manner. Spatial location may play a minor role regarding thermosensory activity; aside from the most ventral GC, neurons reliably responded to and encoded thermal information across the dorso-ventral and antero-postero cortical axes. Additional analysis revealed that more than half of GC neurons that encoded chemosensory taste stimuli also accurately discriminated thermal information, providing additional evidence of the GC’s involvement in processing thermosensory information important for ingestive behaviors. In terms of convergence, we found that GC neurons encoding information about both taste and temperature were broadly tuned and carried more information than taste-selective only neurons; both groups encoded similar information about the palatability of stimuli. Altogether, our data reveal new details of the cortical code for the mammalian intraoral thermosensory system in behaving mice and pave the way for future investigations on GC functions and operational principles with respect to thermogustation.