bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interictal intracranial EEG asymmetry lateralizes temporal lobe epilepsy
Authors: Conrad Erin C. , Lucas Alfredo , Ojemann William K.S. , Aguila Carlos A. , Mojena Marissa , LaRocque Joshua J. , Pattnaik Akash R. , Gallagher Ryan , Greenblatt Adam , Tranquille Ashley , Parashos Alexandra , Gleichgerrcht Ezequiel , Bonilha Leonardo , Litt Brian , Sinha Saurabh , Ungar Lyle , Davis Kathryn A. 
Published: December 2023

ABSTRACTPatients with drug-resistant temporal lobe epilepsy often undergo intracranial EEG recording to capture multiple seizures in order to lateralize the seizure onset zone. This process is associated with morbidity and often ends in postoperative seizure recurrence. Abundant interictal (between-seizure) data is captured during this process, but these data currently play a small role in surgical planning. Our objective was to predict the laterality of the seizure onset zone using interictal (between-seizure) intracranial EEG data in patients with temporal lobe epilepsy. We performed a retrospective cohort study (single-center study for model development; two-center study for model validation). We studied patients with temporal lobe epilepsy undergoing intracranial EEG at the University of Pennsylvania (internal cohort) and the Medical University of South Carolina (external cohort) between 2015 and 2022. We developed a logistic regression model to predict seizure onset zone laterality using interictal EEG. We compared the concordance between the model-predicted seizure onset zone laterality and the side of surgery between patients with good and poor surgical outcomes. 47 patients (30 women; ages 20-69; 20 left-sided, 10 right-sided, and 17 bilateral seizure onsets) were analyzed for model development and internal validation. 19 patients (10 women; ages 23-73; 5 left-sided, 10 right-sided, 4 bilateral) were analyzed for external validation. The internal cohort cross-validated area under the curve for a model trained using spike rates was 0.83 for a model predicting left-sided seizure onset and 0.68 for a model predicting right-sided seizure onset. Balanced accuracies in the external cohort were 79.3% and 78.9% for the left- and right-sided predictions, respectively. The predicted concordance between the laterality of the seizure onset zone and the side of surgery was higher in patients with good surgical outcome. In conclusion, interictal EEG signatures are distinct across seizure onset zone lateralities. Left-sided seizure onsets are easier to distinguish than right-sided onsets. A model trained on spike rates accurately identifies patients with left-sided seizure onset zones and predicts surgical outcome.
Machine learning models for blood pressure phenotypes combining multiple polygenic risk scores
Authors: Hrytsenko Yana , Shea Benjamin , Elgart Michael , Kurniansyah Nuzulul , Lyons Genevieve , Morrison Alanna C. , Carson April P. , Haring Bernhard , Mitchel Braxton D. , Psaty Bruce M. , Jaeger Byron C. , Gu C Charles , Kooperberg Charles , Levy Daniel , Lloyd-Jones Donald , Choi Eunhee , Brody Jennifer A , Smith Jennifer A , Rotter Jerome I. , Moll Matthew , Fornage Myriam , Simon Noah , Castaldi Peter , Casanova Ramon , Chung Ren-Hua , Kaplan Robert , Loos Ruth J.F. , Kardia Sharon L. R. , Rich Stephen S. , Redline Susan , Kelly Tanika , O’Connor Timothy , Zhao Wei , Kim Wonji , Guo Xiuqing , Chen Yii Der Ida ,   the Trans-Omics in Precision Medicine Consortium, Sofer Tamar 
Published: December 2023

AbstractWe construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model’s performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1% to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8% to 5.1% (SBP) and 4.7% to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs.
County-level Socio-Environmental Factors and Obesity Prevalence in the United States
Authors: Salerno Pedro R.V.O. , Qian Alice , Dong Weichuan , Deo Salil , Nasir Khurram , Rajagopalan Sanjay , Al-Kindi Sadeer 
Published: December 2023

AbstractAimsThere are substantial geographical variations in obesity prevalence. Sociodemographic and environmental determinants of health (SEDH), understood as upstream determinants of obesogenic behaviors, may be contributing to this disparity. Thus, we investigated high-risk SEDH potentially associated with adult obesity in American counties using machine learning (ML) techniques.Materials and methodsWe performed a cross-sectional analysis of county-level adult obesity prevalence (≥30 kg/m2) in the U.S. using data from the Diabetes Surveillance System 2017. We harvested 49 county-level SEDH factors that were used by a Classification and Regression Trees (CART) model to identify county-level clusters. CART was validated using a “hold-out” set of counties and variable importance was evaluated using Random Forest.ResultsOverall, we analyzed 2,752 counties in the U.S identifying a national median obesity prevalence of 34.1% (IQR, 30.2, 37.7). CART identified 11 clusters with a 60.8% relative increase in prevalence across the spectrum. Additionally, 7 key SEDH variables were identified by CART to guide the categorization of clusters, includingPhysically Inactive(%),Diabetes, Severe Housing Problems(%),Food Insecurity(%),Uninsured(%),Population over 65 years(%), andNon-Hispanic Black(%).ConclusionThere is significant county-level geographical variation in obesity prevalence in the United States which can in part be explained by complex SEDH factors. The use of ML techniques to analyze these factors can provide valuable insights into the importance of these upstream determinants of obesity and, therefore, aid in the development of geo-specific strategic interventions and optimize resource allocation to help battle the obesity pandemic.Article HighlightsWhy did we undertake this study?To improve the understanding of the association between complex sociodemographic and environmental determinants of health (SEDH) and obesity prevalence in the U.S.What is the specific question(s) we wanted to answer?What are the SEDH associated with obesity prevalence?What did we find?Seven key SEDH variables were identified by CART to guide the categorization of clusters, includingPhysically Inactive(%),Diabetes, Severe Housing Problems(%),Food Insecurity(%),Uninsured(%),Population over 65 years(%), andNon-Hispanic Black(%).What are the implications of our findings?Our study shows the importance of SEDH for the regional variation of obesity prevalence and aids in the development of geo-specific strategies to reduce disparities.
Genetic analysis of cognitive preservation in the midwestern Amish reveals a novel locus on chromosome 2
Authors: Main Leighanne R , Song Yeunjoo E , Lynn Audrey , Laux Renee A , Miskimen Kristy L , Osterman Michael D , Cuccaro Michael L , Ogrocki Paula K , Lerner Alan J , Vance Jeffery M , Fuzzell M Denise , Fuzzell Sarada L , Hochstetler Sherri D , Dorfsman Daniel A , Caywood Laura J , Prough Michael B , Adams Larry D , Clouse Jason E , Herington Sharlene D , Scott William K , Pericak-Vance Margaret A , Haines Jonathan L 
Published: December 2023

ABSTRACTINTRODUCTIONAlzheimer disease (AD) remains a debilitating condition with limited treatments and additional therapeutic targets needed. Identifying AD protective genetic loci may identify new targets and accelerate identification of therapeutic treatments. We examined a founder population to identify loci associated with cognitive preservation into advanced age.METHODSGenome-wide association and linkage analyses were performed on 946 examined and sampled Amish individuals, aged 76-95, who were either cognitively unimpaired (CU) or impaired (CI).RESULTS12 SNPs demonstrated suggestive association (P≤5x10-4) with cognitive preservation. Genetic linkage analyses identified >100 significant (LOD≥3.3) SNPs, some which overlapped with the association results. Only one locus on chromosome 2 retained significance across multiple analyses.DISCUSSIONA novel significant result for cognitive preservation on chromosome 2 includes the genesLRRTM4andCTNNA2. Additionally, the lead SNP, rs1402906, impacts the POU3F2 transcription factor binding affinity, which regulatesLRRTM4andCTNNA2.
Characterisation of tomato (Solanum lycopersiconMill.) genotypes for morphological and disease resistance traits through cluster analysis
Authors: Tejaswini Uppuluri , Parashivamurthy  , Siddaraju R. , Vishwanath K. , Ramanappa T. M. , Srinivasappa K. N. , Nagaraju N. 
Published: December 2023

AbstractThe characterisation of germplasm is very important for the seed material (breeding) and development of improved varieties. The seed material is collected from the M/s. Noble Seeds Pvt. Ltd., Yelhanka few of them are resistant to ToLCV, where Ty gene background is inserted, five genotypes are non-resistant to ToLCV and one check ArkaVikas (susceptible to ToLCV) conducted the research at Kestur Village Doddballapura duringKharif, 2021 andKharif, 2022. The genotypes were morphologically characterised according to DUS guidelines(PPV&FRA). The 20 qualitative and 22 quantitative traits were characterised, out of which 25 traits were observed with variations. Multivariate cluster analysis were assessed for which two clusters (A and B) were formed and for each two, two more sub-clusters (C and D) were observed. The 66.67 % of 30 genotypes (20) are clustered under the Cluster E (15 genotypes), 5 genotypes are considered under the Cluster C, 3 genotypes under the Cluster D and only 2 genotypes are classified under F cluster. The distance in terms of variations is high between the NBLTM-22 and NBLTM-11. And nearing the distance closer and less variations are observed. By this we can say that minimum the distance between the clusters maximum of similarity between the genotypes for the traits.
De novo genome assembly of four Andean potato weevil species (Premnotrypes, Rhigopsidius), the primary agricultural pest of the potato in South America
Authors: Jorgensen Kelsey C. , Garcia Obed A. , Alcázar Jesús , Walden Kimberly K.O. , Bigham Abigail W. , Morón Norma Mujica , Cobián Clorinda Vergara , Lesnik Julie J. , Fan Chuanzhu 
Published: December 2023

AbstractThe Andean potato weevil complex are the most widespread and serious insect pests to potato crops in the Andes. More broadly, genomic assemblies of insect pests are currently lacking in agricultural research, especially those from the order Coleoptera. These genome data are essential for identifying potential underlying mechanisms important to biological control strategies and food security in the highlands. Here, we present thede novogenome assemblies for four species of the Andean potato weevil complex:Premnotrypes vorax, P. suturicallus,P. latithorax, andRhigopsidius piercei. Genome assemblies exceeded the average size of those from the order Coleoptera and were highly repetitive: forP. vorax(1.33 Gb, 71.51% repetitive),P. latithorax(623 Mb, 59.03% repetitive),P. suturicallus(1.23 Gb, 70.19% repetitive), andR. piercei(1.55 Gb, 71.91% repetitive). We examined genomic regions related to metabolic potato plant detoxification and insecticide resistance using the available Colorado potato beetle (Leptinotarsa decemlineata) genome annotations as a guide. Our analysis of these weevil genomes identified chemosensory receptors and odorant binding proteins that could be related to detecting their hosts, the potato plant (Solanum tuberosum), as well as many genomic regions involved in subverting pesticide resistance. We have generated the first whole-genome assemblies of the Andean potato weevil complex that will be foundational for future agricultural pest management and entomological research in South America.Author SummaryWithin the South American Andean mountains the Andean potato weevil insects are the most widespread and serious pests to potatoes, destroying around 89% of potato harvests a year when insecticides are not used. Here, we collected and performed whole-genome sequencing for the first time for four Andean potato weevil species:Premnotrypes vorax, P. suturicallus,P. latithorax, andRhigopsidius piercei. After analysis of these genome assemblies, we found that they were large and highly repetitive compared to other published beetle genome data in the order Coleoptera. After further examination of these genome assemblies, we found regions related to metabolic potato plant detoxification, insecticide resistance, and chemosensory and odorant binding protein receptors that could be related to detecting potato plants. These genomic identifications provide novel molecular insight into regions associated with insecticide resistance, metabolic abilities, and environmental receptors, and can serve as a future valuable resource in classifying phylogenetic relationships as well as identifying regions of interest for improved pest management for potato farmers.
Inactivation of the Niemann Pick C1 cholesterol transporter 1 (NPC1) restricts SARS-CoV-2 infection
Authors: La Rosa Piergiorgio , Tiberi Jessica , Palermo Enrico , Tiano Sofia , Cortese Mirko , Hiscott John , Fiorenza Maria Teresa 
Published: December 2023

AbstractThe Niemann Pick C1 (NPC1) protein is an intracellular cholesterol transporter located in the late endosome/lysosome (LE/Ly) and is involved in cholesterol mobilization. Loss-of-function mutations of theNPC1gene lead to accumulation of cholesterol and sphingolipids in LE/Ly, resulting in severe fatal NPC1 disease. Cellular alterations associated with NPC1 inactivation affect both the integrity of lipid rafts and the endocytic pathway. Because the angiotensin-converting enzyme 2 (ACE2) and type 2 serine transmembrane protease (TMPRSS2) of the SARS-CoV-2 Spike (S) protein also localize to lipid rafts, we sought to investigate the hypothesis that NPC1 inactivation would generate an intrinsically unfavorable barrier to SARS-CoV-2 entry. In this study, we demonstrate that NPC1 pharmacological inactivation or CRISP/R-Cas mediated ablation of NPC1 dramatically reduced SARS-CoV-2 infectivity. More specifically, our findings demonstrate that pharmacological inactivation of NPC1 results in massive accumulation of ACE2 in the autophagosomal/lysosomal compartment. A >40-fold decrease in virus titer indicates that this effectively prevents VSV-Spike-GFP infection by impeding virus binding and entry. A similarly marked decrease in viral infectivity is observed in cells that had NPC1 expression genetically abrogated. These observations were further confirmed in ade novoSARS-CoV-2 infection paradigm, where cells were infected with the naturally pathogenic SARS-CoV-2. Overall, this work offers strong evidence that NPC1 function is essential for successful SARS-CoV-2 infection, thus implicating NPC1 as a potential therapeutic target in COVID-19 management.SignificanceA significant convergence exists between the cellular alterations associated with NPC1 inactivation and the mechanistic processes of SARS-CoV-2 infectivity. These alterations affect the integrity of lipid-enriched plasma membrane microdomains and the endocytic pathway. Furthermore, the cholesterol-regulated ACE2 receptor protein that facilitates SARS-Cov-2 viral binding and entry is targeted to the autophagolysosomal compartment upon NPC1 inactivation, thus hindering virus-host cell interaction. To our knowledge, this study provides the first evidence that NPC1 function represents a crucial factor for SARS-CoV-2 infection and suggests therapeutic opportunities.
Combining muscle-computer interface guided training with bihemispheric tDCS improves upper limb function in chronic stroke patients
Authors: Zhang Xue , Meesen Raf , Swinnen Stephan P. , Feys Hilde , Woolley Daniel G. , Cheng Hsiao-Ju , Wenderoth Nicole 
Published: December 2023

ABSTRACTTranscranial direct current stimulation (tDCS) may facilitate neuroplasticity but with a limited effect when administered while stroke patients are at rest. Muscle-computer interface (MCI) training is a promising approach for training stroke patients even if they cannot produce overt movements. However, using tDCS to enhance MCI training has not been investigated. We combined bihemispheric tDCS with MCI training of the paretic wrist and examined the effectiveness of this intervention in chronic stroke patients. A crossover, double-blind, randomized trial was conducted. Twenty-six chronic stroke patients performed MCI wrist training for three consecutive days at home while receiving either real tDCS or sham tDCS in counterbalanced order and separated by at least 8 months. The primary outcome measure was the Fugl-Meyer Assessment Upper Extremity Scale (FMA-UE) which was measured one week before training, on the first training day, on the last training day, and one week after training. There was no significant difference in the baseline FMA-UE score between groups nor between intervention periods. Patients improved 3.850 ± 0.582 points in FMA-UE score when receiving real tDCS, and 0.963 ± 0.725 points when receiving sham tDCS (p=0.003). Additionally, patients also showed continuous improvement of their motor control of the MCI tasks over the training days. Our study showed that the training paradigm could lead to functional improvement in chronic stroke patients. We argue that an appropriate MCI training in combination with bihemispheric tDCS could be a useful adjuvant for neurorehabilitation in stroke patients.NEW & NOTEWORTHYBihemispheric tDCS combined with a novel MCI training for motor control of wrist extensor can improve both proximal and distal arm function in chronic stroke patients. The training regimen can be personalized with adjustments made daily to accommodate the functional change throughout the intervention. This demonstrates that bihemispheric tDCS with MCI training could complement conventional post-stroke neurorehabilitation.
Combined multiplex panel test results are a poor estimate of disease prevalence without adjustment for test error
Authors: Challen Robert , Chatzilena Anastasia , Qian George , Oben Glenda , Kwiatkowska Rachel , Hyams Catherine , Finn Adam , Tsaneva-Atanasova Krasimira , Danon Leon 
Published: December 2023

AbstractMultiplex panel tests identify many individual pathogens at once, using a set of component tests. In some panels the number of components can be large. If the panel is detecting causative pathogens for a single syndrome or disease then we might estimate the burden of that disease by combining the results of the panel, for example determining the prevalence of pneumococcal pneumonia as caused by many individual pneumococcal serotypes. When we are dealing with multiplex test panels with many components, test error in the individual components of a panel, even when present at very low levels, can cause significant overall error. Uncertainty in the sensitivity and specificity of the individual tests, and statistical fluctuations in the numbers of false positives and false negatives, will cause large uncertainty in the combined estimates of disease prevalence. In many cases this can be a source of significant bias. In this paper we develop a mathematical framework to characterise this issue, present novel statistical methods that adjust for this bias and quantify uncertainty, and use simulation to test these methods. As multiplex testing becomes more commonly used for screening in routine clinical practice, accumulation of test error due to the combination of large numbers of test results needs to be identified and corrected for.Author summaryDuring analysis of pneumococcal incidence data obtained from serotype specific multiplex urine antigen testing, we identified that despite excellent test sensitivity and specificity, the small error rate in each individual serotype test has the potential to compound and cause large uncertainty in the resulting estimates of pneumococcal prevalence, obtained by combining individual results. This limits the accuracy of estimates of the burden of disease caused by vaccine preventable pneumococcal serotypes, and in certain situations can produce marked bias.
Small peptide fingerprint (peptidomics) of Amyotrophic Lateral Sclerosis in CSF
Authors: Lumi Rea , Petri Susanne , Siwy Justyna , Latosinska Agnieszka , Raad Julia , Zürbig Petra , Skripuletz Thomas , Mischak Harald , Beige Joachim 
Published: December 2023

AbstractBackgroundAmyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by abnormal protein aggregates in motor neurons. Present and earlier proteomic studies to characterize peptides in cerebrospinal fluid (CSF) associated with motoneuron pathology did not target the low molecular weight proteins and peptides. We generated the hypothesis that specific changes in CSF peptides or low molecular weight proteins are significantly changed in ALS, and that these changes may support deciphering molecular pathophysiology and even guide approaches towards therapeutic interventions.MethodsCerebrospinal fluid (CSF) from 50 ALS patients and 50 non-ALS controls was collected, centrifuged immediately after collection, aliquoted into polypropylene test tubes, frozen within 30–40 min after the puncture and stored at −80°C until use. Peptides were sequenced using capillary electrophoresis or liquid chromatography / mass spectrometry (CE-MS/MS or LC-MS/MS) analyses.FindingsIn cerebrospinal CSF from 50 patients and 50 non-ALS controls 33 peptides were found, of which 14 could be sequenced using a non-lytic single pot proteomic detection method, CE/MS. ALS deregulated peptides vs. controls included Integral membrane protein 2B, Neurosecretory protein VGF, Osteopontin, Neuroendocrine protein 7B2 (Secretogranin-V), EGF-containing fibulin-like extracellular matrix protein 1, Xylosyltransferase 1 XT-1, Chromogranin-A, Superoxide dismutase SOD-1, Secretogranin-1 (Chromogranin B), NR2F2 Nuclear Receptor Subfamily 2 Group F Member 2 and Collagen alpha-1(VII) chain.InterpretationMost striking deregulations in CSF from ALS patients were found in VGF, Osteopontin, SOD-1 and EFEMP1 peptides. No associations of disease severity, duration and region of onset with sequenced peptides were found.Declarations of InterestS. Petri received honoraria as speaker/consultant from Biogen GmbH, Roche, Novartis, Teva, Cytokinetics Inc., Desitin, Italfarmaco, Ferrer, Amylyx, and Zambon; and grants from DGM e.V, Federal Ministry of Education and Research, German Israeli Foundation for Scientific Research and Development, EU Joint Program for Neurodegenerative Disease Research. J. Beige received funding from GSK and German Federal Ministries of Research and Health.FundingThere was no funding to the presented investigationEthical ApprovalThis study was approved by the ethics committee of Hannover Medical School. Written informed consent was obtained from all participants in accordance with the Declaration of Helsinki. Key words: ALS, CSF, proteomics, biomarker, peptidomics, peptide deregulation