bluuebunny/crossref_metadata_2025_split huggingface dataset:
Artificial neural network predicts sex differences of patients with advanced Parkinson’s disease under Levodopa-Carbidopa Intestinal gel
Authors: Bougea Anastasia , Derikvand Tajedin , Efthymiopoulou Efthymia , Angelopoulou Efthalia 
Published: June 2023

AbstractObjectiveAlthough Levodopa-carbidopa intestinal gel (LCIG) treatment has shown to be efficacious in motor and some non-motor symptoms (NMS), not all the patients with advanced Parkinson’s disease (PD) are ideal candidates. To improve their selection analysis knowledge of prognostic factors is of great importance. We aimed to develop a novel machine learning model to predict the clinical outcomes of patients with advanced PD at 2 years under the LCIG therapy.MethodsThis was a longitudinal 24-month, observational study of 59 patients with advanced PD of a Greek multicenter registry under LCIG treatment from September 2019 to September 2021. Motor status was assessed with the Unified Parkinson’s Disease Rating Scale (UPDRS) part III (off) and IV. NMS were assessed by the NMS Questionnaire (NMSQ) and the Geriatric Depression Scale (GDS), the quality of life by PDQ-39 and severity by Hoehn &Yahr (HY). Multivariate linear regression, ARIMA, SARIMA, and Long Short-Term Memory-recurrent neural network (LSTM-RNN) models were used.ResultsDyskinesia duration and quality of life were significantly improved with LCIG (19% and 10% greater improvement for men than women, respectively). Multivariate linear regression models showed that UPDRS-III was decreased by 1.5 and 4.39 units per one unit of increase of the PDQ-39, UPDRS-IV indexes, respectively. Among all the time series models, the LSTM-RNN model predicts these clinical characteristics with highest accuracy (mean square error =0.0069)ConclusionsΤhe LSTM-RNN model predicts with highest accuracy sex dependent clinical outcomes of patients with advanced PD after two years of LCIG therapy.
Identification of commensal gut microbiota signatures as predictors of clinical severity and disease progression in multiple sclerosis
Authors: Montgomery Theresa L , Wang Qin , Mirza Ali , Dwyer Deanna , Wu Qi , Dowling Catherine A , Martens Jacob WS , Yang Jennifer , Krementsov Dimitry N , Mao-Draayer Yang 
Published: June 2023

ABSTRACTBackgroundMultiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system and a leading cause of neurological disability in young adults. Clinical presentation and disease course are highly heterogeneous. Typically, disease progression occurs over time and is characterized by the gradual accumulation of disability. The risk of developing MS is driven by complex interactions between genetic and environmental factors, including the gut microbiome. How the commensal gut microbiota impacts disease severity and progression over time remains unknown.MethodsIn a longitudinal study, disability status and associated clinical features in 60 MS patients were tracked over 4.2 ± 0.97 years, and the baseline fecal gut microbiome was characterized via 16S amplicon sequencing. Progressor status, defined as patients with an increase in Expanded Disability Status Scale (EDSS), were correlated with features of the gut microbiome to determine candidate microbiota associated with risk of MS disease progression.ResultsWe found no overt differences in microbial community diversity and overall structure between MS patients exhibiting disease progression and non-progressors. However, a total of 45 bacterial species were associated with worsening disease, including a marked depletion inAkkermansia,Lachnospiraceae,andOscillospiraceae, with an expansion ofAlloprevotella,Prevotella-9, andRhodospirillales. Analysis of the metabolic potential of the inferred metagenome from taxa associated with progression revealed a significant enrichment in oxidative stress-inducing aerobic respiration at the expense of microbial vitamin K2production (linked toAkkermansia), and a depletion in SCFA metabolism (linked toLachnospiraceaeandOscillospiraceae). Further, statistical modeling demonstrated that microbiota composition and clinical features were sufficient to robustly predict disease progression. Additionally, we found that constipation, a frequent gastrointestinal comorbidity among MS patients, exhibited a divergent microbial signature compared with progressor status.ConclusionsThese results demonstrate the utility of the gut microbiome for predicting disease progression in MS. Further, analysis of the inferred metagenome revealed that oxidative stress, vitamin K2and SCFAs are associated with progression.Abstract Figure
pfb_fhir: A utility to extract clinical data systems into a portable format
Authors: Walsh Brian , Lee Jordan A. , Ellrott Kyle 
Published: June 2023

AbstractBackgroundFast Healthcare Interoperability Resources (FHIR) is a server specification and data model that allows for EHR systems to represent clinical metadata using a consistent API. There is a critical mass of EHR and clinical trial data stored in FHIR based systems. Research analysts can take advantage of existing FHIR tooling for de-identification, pseudonymization, and anonymization. More recently the BiodataCatalyst consortium has proposed the Portable Format for Bioinformatics (PFB) which is a carrier format for describing raw data and the data model in which it is structured, based on an efficient binary format (AVRO). PFB allows an entire cohort of metadata to be loaded into a research data system. Here, we describe an open source utility that will scan FHIR based systems and create PFB based archives.Resultspfb_fhir scans data from FHIR based clinical data systems and converts the data into a self contained PFB file. This utility identifies types, customizations (extensions), and element connections. It then converts all of these components into a graph model compatible for storage in the PFB specification. The structure of the original FHIR system is faithfully reproduced using the PFB schema description system. All records from the system are downloaded, converted and stored as vertices in a graph described by the PFB file. This system has been tested against a number of different FHIR installations, including ones hosted by dbGAP, The Kids First Data Resource and AnVIL.Conclusionspfb_fhir helps to unlock the potential of EHR and clinical trial data. pfb_fhir allows researchers to easily scan and store FHIR resources and create self contained PFB archives, called FHIR in PFB. These archive files can easily be moved to new data systems, allowing the clinical data to be connected to more complex genomic analysis and data science platforms. The FHIR in PFB archives generated by pfb_fhir have been loaded into data platforms including the Broad’s Terra system, Gen3 based data system, custom graph query engines and Jupyter notebooks. This flexibility will enable genomics investigators to do more integrated genotype to phenotype association analysis using whichever tools suit their line of research.
Impact of Hypertension on Left Heart Remodelling: Echocardiography and Computed Tomography Study
Authors: Lange Aleksandra , Palka Viktoria , Bian Chris , Huntress Harry , Morgan Jill , Allwood Sean , Swann Rohan , Palka Przemysław 
Published: June 2023

ABSTRACTBackgroundEarly recognition of left atrial (LA) and left ventricular (LV) remodelling may improve prognosis of patients with hypertension.MethodsLeft heart coupling indices were studied to investigate the adaptive effect of hypertension on cardiac remodelling. The ratio of LV to LA volumes was measured at selected phases of a cardiac cycle using computed tomography (CT) coronary angiography and transthoracic echocardiogram (TTE). A group of 180 patients was divided into Group 1 (no hypertension) and Group 2 (hypertension). Volume ratios were measured in diastasis by both CT and TTE: LVdiasand LAdias. Using TTE, volumes were measured at end-diastole (LVEDand LAmin)), and end-systole (LVESand LAmax). LA function and LV/LA ratios were analysed at: LVED/LAmax, LVdias/LAdias, LVED/LAmin, LVES/LAmin.ResultsThere were no differences between the age groups, LVED, and LV mass index. Compared to Group 1, Group 2 had bigger mean LV wall thickness (0.90±0.16 cmvs0.83±0.14 cm; p=0.006), increased relative wall thickness ratio (0.39±0.09vs0.35±0.008, p=0.004), and more frequent concentric LV remodelling (31vs12, p=0.020). LA volumes were bigger in Group 2 for LAmax, LAdias, and LAmin. All LV/LA volume ratios were lower in Group 2 compared to Group 1 (LVED/LAmax1.55±0.56vs1.79±0.69, p=0.010; LVED/LAmin3.56±2.00vs4.59±2.56, p=0.003; LVES/LAmin1.36±0.77, p=0.005, LVdias/LAdias(TTE) 1.75±0.61vs2.24±1.24, p<0.001, LVdias/LAdias(CT) 1.49±0.23vs1.69±0.41, p<0.001). LA reservoir function and conduit function indexed by E/e’ ratio was lower in Group 2. Combined TTE parameters of relative wall thickness >40, LVdias/LAdias≤1.81, and indexed by E/e’ LA reservoir function ≤0.068 had the highest discriminate power to differential patients from Group 1 and Group 2 (area under the curve 0.737).ConclusionsIn hypertension, prior to the development of LV hypertrophy, adaptive remodelling is based on reduced LV/LA volume ratio, reduced indexed reservoir LA function, and increased relative LV wall thickness.
Combination of NY-ESO-1-TCR-T-cells coengineered to secrete SiRPα decoys with anti-tumor antibodies to augment macrophage phagocytosis
Authors: Stefanidis Evangelos , Semilietof Aikaterini , Pujol Julien , Seijo Bili , Scholten Kirsten , Zoete Vincent , Michielin Olivier , Sandaltzopoulos Raphael , Coukos George , Irving Melita 
Published: June 2023

ABSTRACTThe adoptive transfer of T cell receptor (TCR)-engineered T cells (ACT) targeting the HLA-A2 restricted cancer-testis epitope NY-ESO-1157-165(A2/NY) has yielded favorable clinical responses against a variety of cancers. Two promising approaches to improve ACT efficacy are TCR affinity-optimization and combinatorial treatment strategies to reprogram the tumor microenvironment (TME). By computational design, we previously developed a panel of affinity-enhanced A2/NY-TCRs. Here, we have demonstrated improved tumor control and engraftment by T cells gene-modified to express one such TCR comprising a single amino acid replacement in CDR3β (A97L). To harness macrophages in the TME, we coengineered TCR-T cells to constitutively or inducibly secrete a high-affinity signal regulatory protein alpha (SiRPα) decoy (CV1) to block the CD47 ‘don’t eat me’ signal. We demonstrated better control of tumor outgrowth by CV1-Fc coengineered TCR-T cells but in subcutaneous xenograft tumor models we observed depletion of both CV1-Fc and CV1 coengineered T cells. Importantly, CV1 coengineered T cells were not depleted by human macrophages in vitro. Moreover, Avelumab and Cetuximab enhanced macrophage-mediated phagocytosis in vitro in the presence of CV1, and augmented tumor control upon ACT. Taken together, our study indicates important clinical promise for harnessing macrophages by combining CV1 coengineered TCR-T cells with tumor-targeting monoclonal antibodies.
Clustering the Planet: An Exascale Approach to Determining Global Climatype Zones
Authors: Streich Jared , Furches Anna , Kainer David , Garcia Benjamin J. , Jones Piet , Romero Jonathon , Garvin Michael R. , Climer Sharlee , Thornton Peter E. , Joubert Wayne , Jacobson Daniel 
Published: June 2023

AbstractWe present an exascale approach for producing global scale, high resolution, longitudinally based geoclimate classifications. Using a GPU implementation of the DUO Similarity Metric on the Summit supercomputer, we calculated the pairwise environmental similarity of 156,384,190 vectors of 414,640 encoded elements derived from 71 environmental variables over a 50-year time span at 1km2resolution. GPU matrix-matrix (GEMM) kernels were optimized for the GPU architecture and their outputs were managed through aggressive concurrent MPI rank CPU communication, calculations, and transfers. Using vector transformation and highly optimized operations of generalized distributed dense linear algebra, calculation of all-vector-pairs similarity resulted in 5.07 × 1021element comparisons and reached a peak performance of 2.31 exaflops. We demonstrated this method using existing and synthesized climate layers to show how geography can be parsed using high-performance computing. Geoclimate zones are important tools for understanding how environmental variables impact natural systems, particularly for agriculture and conservation with relevance to climate change. Historically, classification systems have been low resolution, based on limited variables, or subjective. To identify climate classes, we clustered DUO outputs at varying stringency, producing 69, 133, 340, and 717 global geoclimate zones. Our approach produced global scale, high resolution, longitudinally informed climate classifications that can be used in precision agriculture, cultivar breeding efforts, and conservation programs.
Shifts in diversification influence rates of song evolution in honeyeaters
Authors: Hay Eleanor M. , Chown Steven L. , McGee Matthew D. 
Published: June 2023

ABSTRACTBirdsongs are acoustic signals that can play a role in sexual selection. Despite the established role of birdsong in selection and reproductive isolation at microevolutionary scales, the macroevolutionary relationships between song evolution and clade diversification remain largely unexplored. We test the hypothesis that shifts in diversification influence rates of song evolution in honeyeaters, a diverse clade of songbirds restricted to Australasia. Using a song dataset for 163 honeyeater species, we identify lineage-specific shifts in diversification, and test the influence of these shifts on song evolution with state-dependent, relaxed, multivariate Brownian motion models. We also explore the underlying patterns of song evolution and phylogenetic signal of song. Shifts to lower rates of diversification are associated with lower rates of song evolution. This suggests the two factors are correlated, but is contrary to expectations that elevated rates of diversification will be associated with elevated rates of song evolution. We also found that song follows a punctuated mode of evolution, implying that birdsong has an important role in speciation events, although this signal likely erodes over time and is subject to phylogenetic constraints.
A human primary airway microphysiological system infected with SARS-CoV-2 distinguishes the treatment efficacy between nirmatrelvir and repurposed compounds fluvoxamine and amodiaquine
Authors: Quezada Landys Lopez , Medie Felix Mba , Gabriel Elizabeth P. , Luu Rebeccah J. , Rubio Logan D. , Mulhern Thomas J. , Borenstein Jeffrey T. , Fisher Christine R. , Gard Ashley L. 
Published: June 2023

AbstractThe COVID-19 pandemic necessitated a rapid mobilization of resources toward the development of safe and efficacious vaccines and therapeutics. Finding effective treatments to stem the wave of infected individuals needing hospitalization and reduce the risk of adverse events was paramount. For scientists and healthcare professionals addressing this challenge, the need to rapidly identify medical countermeasures became urgent, and many compounds in clinical use for other indications were repurposed for COVID-19 clinical trials after preliminary preclinical data demonstrated antiviral activity against SARS-CoV-2. Two repurposed compounds, fluvoxamine and amodiaquine, showed efficacy in reducing SARS-CoV-2 viral loads in preclinical experiments, but ultimately failed in clinical trials, highlighting the need for improved predictive preclinical tools that can be rapidly deployed for events such as pandemic emerging infectious diseases. The PREDICT96-ALI platform is a high-throughput, high-fidelity microphysiological system (MPS) that recapitulates primary human tracheobronchial tissue and supports highly robust and reproducible viral titers of SARS-CoV-2 variants Delta and Omicron. When amodiaquine and fluvoxamine were tested in PREDICT96-ALI, neither compound demonstrated an antiviral response, consistent with clinical outcomes and in contrast with prior reports assessing the efficacy of these compounds in other human cell-basedin vitroplatforms. These results highlight the unique prognostic capability of the PREDICT96-ALI proximal airway MPS to assess the potential antiviral response of lead compounds.
Effects of cannabis use on antidepressant treatment response to repetitive transcranial magnetic stimulation and ketamine
Authors: Shenasa Mohammad Ali , Afshar Houtan Totonchi , Miller Eric A. , Ellerman-Tayag Em , Mishra Jyoti , Ramanathan Dhakshin 
Published: June 2023

AbstractBackgroundThe antidepressant effects of ketamine and repetitive transcranial magnetic stimulation (rTMS) are hypothesized to rely on mechanisms of long-term-potentiation and synaptic plasticity. Cannabis, via activation of CB1 receptors has been shown to impair synaptic plasticity, suggesting that cannabis use might moderate the antidepressant effects of ketamine and/or rTMS.MethodsWe performed a retrospective chart review of 222 Veterans, including 58 females, treated for depression with either rTMS or ketamine/esketamine at the VA San Diego Medical Center (VASDMC). We estimated the effects of treatment using changes in the Patient-Health-Questionnaire 9 (PHQ-9) split by cannabis use. Cannabis use was determined using self-report for rTMS (102 total, 23 screening positive for cannabis use) or urinary drug screens for ketamine (120 total, 40 screening positive for cannabis use). Mixed-level repeated measures ANOVA was utilized to determine whether cannabis use affected PHQ-9 scores (group effect) or the change in PHQ-9 over time (group x time interaction).ResultsCannabis use did not affect overall symptom severity (group effect F (1, 100) = 0.58, p = 0.45) for rTMS, group effect (F (1, 118) = 0.58, p = 0.45) for ketamine, nor did it impact changes in symptoms for either treatment (group x time effect for ketamine: (F (7, 759) = 0.36, p = 0.93); group x time effect for rTMS (F (5, 412) = 0.4160, p = 0.83).ConclusionsCannabis use was unrelated to antidepressant treatment outcomes for either rTMS or ketamine, suggesting that cannabis use should not be a contraindication for these treatments.
Predicting up to 10 year breast cancer risk using longitudinal mammographic screening history
Authors: Wang Xin , Tan Tao , Gao Yuan , Su Ruisheng , Zhang Tianyu , Han Luyi , Teuwen Jonas , D’Angelo Anna , Drukker Caroline A. , Schmidt Marjanka K. , Beets-Tan Regina , Karssemeijer Nico , Mann Ritse 
Published: June 2023

AbstractRisk assessment of breast cancer (BC) seeks to enhance individualized screening and prevention strategies. BC risk informs healthy individuals of the short- and long-term likelihood of cancer development, also enabling detection of existing BC. Recent mammographic-based deep learning (DL) risk models outperform traditional risk factor-based models and achieve state-of-the-art (SOTA) at short-term risk prediction, but mainly use single-time exams, which seem to rely more on detecting existing lesions. We present a novel temporospatial and explainable deep learning risk model, the Multi-Time Point Breast Cancer Risk Model (MTP-BCR), which learns from longitudinal mammography data to identify subtle changes in breast tissue that may signal future malignancy. Utilizing a large in-house dataset of 171,168 screening mammograms from 42,792 consecutive exams involving 9,133 women, our model demonstrates a significant improvement in long-term (10-year) risk prediction with an area under the receiver operating characteristics (AUC) of 0.80, outperforming the traditional BCSC 10-year risk model and other SOTA methods at 5-year AUC in various screening cohorts. Furthermore, MTP-BCR provides unilateral breast-level predictions, achieving AUCs up to 0.81 and 0.77 for 5-year risk and 10-year risk assessments, respectively. The heatmaps derived from our model may help clinicians better understand the progression from normal tissue to cancerous growth, enhancing interpretability in breast cancer risk assessment.TeaserMTP-BCR model uses multi-time points mammograms and rich risk factors to predict 10-year breast cancer risk more accurately.
CHARR efficiently estimates contamination from DNA sequencing data
Authors: Lu Wenhan , Gauthier Laura D. , Poterba Timothy , Giacopuzzi Edoardo , Goodrich Julia K. , Stevens Christine R. , King Daniel , Daly Mark J. , Neale Benjamin M. , Karczewski Konrad J. 
Published: June 2023

AbstractDNA sample contamination is a major issue in clinical and research applications of whole genome and exome sequencing. Even modest levels of contamination can substantially affect the overall quality of variant calls and lead to widespread genotyping errors. Currently, popular tools for estimating the contamination level use short-read data (BAM/CRAM files), which are expensive to store and manipulate and often not retained or shared widely. We propose a new metric to estimate DNA sample contamination from variant-level whole genome and exome sequence data, CHARR, Contamination from Homozygous Alternate Reference Reads, which leverages the infiltration of reference reads within homozygous alternate variant calls. CHARR uses a small proportion of variant-level genotype information and thus can be computed from single-sample gVCFs or callsets in VCF or BCF formats, as well as efficiently stored variant calls in Hail VDS format. Our results demonstrate that CHARR accurately recapitulates results from existing tools with substantially reduced costs, improving the accuracy and efficiency of downstream analyses of ultra-large whole genome and exome sequencing datasets.
A member of a new dynamin superfamily modulates mitochondrial membrane branching inTrypanosoma brucei
Authors: Morel Chloé Alexandra , Asencio Corinne , Moreira David , Blancard Corinne , Salin Bénédicte , Gontier Etienne , Duvezin-Caubet Stéphane , Rojo Manuel , Bringaud Frédéric , Tetaud Emmanuel 
Published: June 2023

SUMMARYUnlike most other eukaryotes, where mitochondria continuously fuse and divide, the mitochondrion of trypanosome cells forms a single and continuously interconnected network that divides only during cytokinesis. However, the machinery governing mitochondrial remodeling and interconnection of trypanosome mitochondrion remain largely unknown. We functionally characterize a novel dynamin-superfamily protein (DSP) fromT. brucei(TbMfnL) which shares close similarity with a family of homologs present in various eukaryotic and prokaryotic phyla, but not in opisthokonts like mammals and budding yeast. The sequence and domain organization ofTbMfnL is distinct and it is phylogenetically very distant from the yeast and mammalian dynamin-related proteins involved in mitochondrial fusion/fission dynamincs, such as Opa1 and Mfn.TbMfnL localizes to the inner mitochondrial membrane facing the matrix, and upon overexpression, induces a strong increase in the interconnection and branching of mitochondrial filaments in a GTPase-dependent manner.TbMfnL is a component of a novel membrane remodeling machinery with an unprecedented matrix-side localization that is able to modulate the degree of intermitochondrial connections.