bluuebunny/crossref_metadata_2025_split huggingface dataset:
Presymptomatic amyotrophic lateral sclerosis: from characterization to prevention
Authors: Benatar Michael , Turner Martin R. , Wuu Joanne 
Published: June 2023

Purpose of review
Significant progress in characterizing presymptomatic amyotrophic lateral sclerosis (ALS) is ushering in an era of potential disease prevention. Although these advances have largely been based on cohorts of deep-phenotyped mutation carriers at an elevated risk for ALS, there are increasing opportunities to apply principles and insights gleaned, to the broader population at risk for ALS [and frontotemporal dementia (FTD)].

Recent findings
The discovery that blood neurofilament light chain (NfL) level increases presymptomatically and may serve as a susceptibility biomarker, predicting timing of phenoconversion in some mutation carriers, has empowered the first-ever prevention trial in SOD1-ALS. Moreover, there is emerging evidence that presymptomatic disease is not uniformly clinically silent, with mild motor impairment (MMI), mild cognitive impairment (MCI), and/or mild behavioral impairment (MBI) representing a prodromal stage of disease. Structural and functional brain abnormalities, as well as systemic markers of metabolic dysfunction, have emerged as potentially even earlier markers of presymptomatic disease. Ongoing longitudinal studies will determine the extent to which these reflect an endophenotype of genetic risk.

Summary
The discovery of presymptomatic biomarkers and the delineation of prodromal states is yielding unprecedented opportunities for earlier diagnosis, treatment, and perhaps even prevention of genetic and apparently sporadic forms of disease.
Late-onset hereditary ataxias with dementia
Authors: Linares Anthony J. , Fogel Brent L. 
Published: June 2023

Purpose of review
Late-onset genetic cerebellar ataxias are clinically heterogenous with variable phenotypes. Several of these conditions are commonly associated with dementia. Recognition of the relationship between ataxia and dementia can guide clinical genetic evaluation.

Recent findings
Spinocerebellar ataxias often present with variable phenotypes that may include dementia. Genomic studies have begun to identify links between incomplete penetrance and such variable phenotypes in certain hereditary ataxias. Recent studies evaluating the interaction of TBP repeat expansions and STUB1 sequence variants provide a framework to understand how genetic interactions influence disease penetrance and dementia risk in spinocerebellar ataxia types 17 and 48. Further advances in next generation sequencing methods will continue to improve diagnosis and create new insights into the expressivity of existing disorders.

Summary
The late-onset hereditary ataxias are a clinically heterogenous group of disorders with complex presentations that can include cognitive impairment and/or dementia. Genetic evaluation of late-onset ataxia patients with dementia follows a systemic testing approach that often utilizes repeat expansion testing followed by next-generation sequencing. Advances in bioinformatics and genomics is improving both diagnostic evaluation and establishing a basis for phenotypic variability. Whole genome sequencing will likely replace exome sequencing as a more comprehensive means of routine testing.
Nerve ultrasound for the diagnosis and follow-up of peripheral neuropathies
Authors: Pitarokoili Kalliopi , Gold Ralf , Fisse Anna Lena 
Published: June 2023

Purpose of review
The purpose if this review is to provide an overview of the available data on the use of nerve ultrasound for the diagnosis and follow-up of peripheral neuropathies.

Recent findings
During the last decade, nerve ultrasound has been established as a complementary tool for the evaluation of morphological changes mostly for immune-mediated polyneuropathies. Through the development of ultrasound protocols for evaluation of disease-specific sites, nerve ultrasound has proven to be a practical, widely available, reproducible diagnostic tool with no relevant contraindications.

Summary
Cross-sectional area, echogenicity, morphology of the individual nerve fascicles, thickness of the epineurium, vascularization and mobility of the nerve are the main parameters evaluated with nerve ultrasound in polyneuropathies. Patients with typical chronic inflammatory demyelinating polyneuropathy show multifocal nerve enlargements easily visible on the upper extremities and the brachial plexus, whereas its variants show focal nerve enlargements. On the other hand, axonal neuropathies including diabetic neuropathy present with isolated nerve enlargement mostly in compression sites.
High blood viscosity in acute ischemic stroke
Authors: Kang Jihoon , Oh Ju Seok , Kim Beom Joon , Kim Jun Yup , Kim Do Yeon , Yun So-Yeon , Han Moon-Ku , Bae Hee-Joon , Park Inwon , Lee Jae Hyuk , Jo You Hwan , Ahn Kyung Hyun 
Published: June 2023

AbstractBackground:Changes in blood viscosity can influence the shear stress level at the vessel wall. However, there is limited evidence to date regarding the role of high blood viscosity in acute thrombogenic events. We aimed to investigate the effect of blood viscosity on stroke occurrence and the clinical utility of blood viscosity measurements obtained immediately upon hospital arrival.Methods:Patients with suspected stroke visiting the hospital within 24 h of the last known well time were enrolled. Point-of-care testing was used to obtain blood viscosity measurements before intravenous fluid infusion. Blood viscosity was measured as the reactive torque generated at three different oscillatory frequencies (1, 5, and 10Hz). Blood viscosity results were compared among patients with stroke mimics, ischemic stroke, and hemorrhagic stroke.Results:Among 112 enrolled patients, blood viscosity measurements were accomplished within 2.4 ± 1.3 min of vessel puncture. At an oscillatory frequency of 10Hz, blood viscosity differed significantly between the ischemic stroke (24.2 ± 4.9cP) and stroke mimic groups (17.8 ± 6.5cP, P < 0.001). This finding was consistent at different oscillatory frequencies (134.2 ± 46.3 vs. 102.4 ± 47.2 at 1Hzand 39.2 ± 11.5 vs. 30.4 ± 12.4 at 5Hz, Ps < 0.001), suggesting a relationship between decreases in viscosity and shear rate. Among patients with ischemic, blood viscosity values were lower (16.4 ± 3.3) in those who had received intravenous fluid before blood sampling than in those who had not. The area under the receiver operating curve for differentiating cases of stroke from stroke mimic was 0.79 (95% confidence interval, 0.69 – 0.88).Conclusion:Patients with ischemic stroke exhibit increases in whole blood viscosity when admitted within 24 h of last known well time, suggesting that blood viscosity measurements can aid in differentiating ischemic stroke from other diseases.
Radial and Axial Fractional Shortening for Rapid Estimation of Left Ventricular Ejection Fraction: A Computational Analysis
Authors: Rifkin Robert D. , Rich Michael W. 
Published: June 2023

ABSTRACTBACKGROUND AND PURPOSESimpson Rule based planimetry remains the gold standard for left ventricular (LV) ejection fraction (EF) but due to sub-optimal endocardial delineation, planimetry is not feasible in many cases. The purpose of this study was to derive and to analytically evaluate the theoretical accuracy of several simple novel formulas for estimating EF in ventricles with uniform wall motion using only the radial diameter and axial length LV fractional shortening (FDand FLrespectively), which are less subject to image quality limitations than planimetry.METHODSA truncated ellipsoidal model of the LV at end-diastole and end-systole was assumed leading to a novel compact formula for directly calculating an exact EF that is identical to the Simpson Rule EF when the ventricle has ellipsoidal end-diastolic (ED) and end-systolic (ES) shapes.Three linear formulas were then developed to directly calculate an approximation to the exact EF without intermediate calculation of volumes. To avoid population selection bias in this initial investigation the linear coefficients were determined by an analytic graphical optimization procedure that minimized the EF errors compared to the exact EF over the full range of exact EFs from 0 to 80% (FDand FLin percent).RESULTSIn single factor linear approximations #1 and #2, the EF difference from the exact EF was dependent on the ratio FL/ FD, which is normally between 40 and 50%. Subject to the assumption of ellipsoidal LV shape at ED and ES, for ratios of FL/ FDbetween 20% and 80%, and over EFs ranging from 0 to 55%, the calculated differences from the exact EF were less than 6 EF points. At extremes of the ratio, less than 20% or over 80%, or for EFs over 55%, the difference could reach or exceed 10 points. Formula #2 produced slightly smaller differences than formula #1. Formula #3 reduced the difference error substantially to less than 4 EF percentage points regardless of the FL/ FDratio except at EFs over 75%.CONCLUSIONSIn uniformly contracting ventricles, simple linear formulas could provide rapid estimation of EF and may be helpful when image quality degrades planimetric EF accuracy, as well as in point-of-care echocardiography where planimetry is not feasible. Validation of these formulas through empirical testing is warranted.
PA-FGRS is a novel estimator of pedigree-based genetic liability that complements genotype-based inferences into the genetic architecture of major depressive disorder
Authors: Krebs Morten Dybdahl , Hellberg Kajsa-Lotta Georgii , Lundberg Mischa , Appadurai Vivek , Ohlsson Henrik , Pedersen Emil , Steinbach Jette , Matthews Jamie , LaBianca Sonja , Calle Xabier , Meijsen Joeri J. ,   iPSYCH Study Consortium, Ingason Andrés , Buil Alfonso , Vilhjálmsson Bjarni J. , Flint Jonathan , Bacanu Silviu-Alin , Cai Na , Dahl Andy , Zaitlen Noah , Werge Thomas , Kendler Kenneth S. , Schork Andrew J. 
Published: June 2023

AbstractLarge biobank samples provide an opportunity to integrate broad phenotyping, familial records, and molecular genetics data to study complex traits and diseases. We introduce Pearson-Aitken Family Genetic Risk Scores (PA-FGRS), a new method for estimating disease liability from patterns of diagnoses in extended, age-censored genealogical records. We then apply the method to study a paradigmatic complex disorder, Major Depressive Disorder (MDD), using the iPSYCH2015 case-cohort study of 30,949 MDD cases, 39,655 random population controls, and more than 2 million relatives. We show that combining PA-FGRS liabilities estimated from family records with molecular genotypes of probands improves the three lines of inquiry. Incorporating PA-FGRS liabilities improves classification of MDD over and above polygenic scores, identifies robust genetic contributions to clinical heterogeneity in MDD associated with comorbidity, recurrence, and severity, and can improve the power of genome-wide association studies (GWAS). Our method is flexible and easy to use and our study approaches are generalizable to other data sets and other complex traits and diseases.
Increased circulating fibronectin, depletion of natural IgM and heightened EBV, HSV-1 reactivation in ME/CFS and long COVID
Authors: Liu Zheng , Hollmann Claudia , Kalanidhi Sharada , Grothey Arnhild , Keating Sam , Mena-Palomo Irene , Lamer Stephanie , Schlosser Andreas , Kaiping Agnes , Scheller Carsten , Sotzny Franzeska , Horn Anna , Nürnberger Carolin , Cejka Vladimir , Afshar Boshra , Bahmer Thomas , Schreiber Stefan , Vehreschild Jörg Janne , Miljukov Olga , Schäfer Christian , Kretzler Luzie , Keil Thomas , Reese Jens-Peter , Eichner Felizitas A , Schmidbauer Lena , Heuschmann Peter U , Störk Stefan , Morbach Caroline , Riemekasten Gabriela , Beyersdorf Niklas , Scheibenbogen Carmen , Naviaux Robert K , Williams Marshall , Ariza Maria E , Prusty Bhupesh K 
Published: June 2023

SummaryMyalgic Encephalomyelitis/ Chronic Fatigue syndrome (ME/CFS) is a complex, debilitating, long-term illness without a diagnostic biomarker. ME/CFS patients share overlapping symptoms with long COVID patients, an observation which has strengthened the infectious origin hypothesis of ME/CFS. However, the exact sequence of events leading to disease development is largely unknown for both clinical conditions. Here we show antibody response to herpesvirus dUTPases, particularly to that of Epstein-Barr virus (EBV) and HSV-1, increased circulating fibronectin (FN1) levels in serum and depletion of natural IgM against fibronectin ((n)IgM-FN1) are common factors for both severe ME/CFS and long COVID. We provide evidence for herpesvirus dUTPases-mediated alterations in host cell cytoskeleton, mitochondrial dysfunction and OXPHOS. Our data show altered active immune complexes, immunoglobulin-mediated mitochondrial fragmentation as well as adaptive IgM production in ME/CFS patients. Our findings provide mechanistic insight into both ME/CFS and long COVID development. Finding of increased circulating FN1 and depletion of (n)IgM-FN1 as a biomarker for the severity of both ME/CFS and long COVID has an immediate implication in diagnostics and development of treatment modalities.
Natural language processing and expert follow-up establishes tachycardia association withCDKL5deficiency disorder
Authors: Ivaniuk Alina , Boßelmann Christian M , Zhang Xiaoming , St John Mark , Taylor Sara C , Krishnaswamy Gokul , Milinovich Alex , Aziz Peter F , Pestana-Knight Elia , Lal Dennis 
Published: June 2023

AbstractPurposeCDKL5 deficiency disorder (CDD) is a developmental and epileptic encephalopathy with multisystemic comorbidities. Cardiovascular involvement in CDD was shown in animal models but is yet poorly described in CDD cohorts.MethodsWe identified 38 individuals with genetically confirmed CDD through the Cleveland Clinic CDD specialty clinic and matched 190 individuals with non-genetic epilepsy to them as a comparison group. Natural language processing was applied to yield Human Phenotype Ontology (HPO) terms from medical records. We conducted HPO association testing and manual chart review to explore cardiovascular comorbidities associated with CDD.ResultsWe extracted 243,541 HPO terms from 30,512 medical encounters. Phenome-wide analysis confirmed well-established CDD phenotypes and identified association of tachycardia with CDD (OR 4.2, 95%CI 1.75-9.93, padj<0.001). We found a 99.6-fold enrichment of supraventricular tachycardia (SVT) in CDD encounter notes (padj< 0.001), which led to identification of two cases of fetal/neonatal onset SVT previously undescribed in CDD. Tachycardia in CDD individuals was associated with the presence of other autonomic symptoms (OR 5.63, 95%CI 1.08-40.3, p=0.038).ConclusionsCDD is associated with tachycardia, potentially including early-onset supraventricular tachycardia. Alongside prospective validation studies, semiautomated genotype-phenotype analysis with matched controls is a scalable, rapid, and efficient approach for validating known and identifying novel phenotype associations.
A Supervised Machine Learning Model to Predict Therapy Response and Mortality at 90 days After Acute Myeloid Leukemia Diagnosis
Authors: Delgado Sanchis Juan A. , Pons-Suñer Pedro , Alvarez Noemi , Sargas Claudia , Dorado Sara , Gil Ortí Jose Vicente , Signol François , Llop Marta , Arnal Laura , Llobet Rafael , Perez-Cortes Juan-Carlos , Ayala Rosa , Barragán Eva 
Published: June 2023

AbstractBackground and ObjectiveThe main objective in this paper is to validate a machine-learning model trained to predict the 90-day risk of complications for patients with Acute Myeloid Leukemia using variables available at diagnosis. This is a first fundamental step towards the development of a tool that could help physicians in their therapeutic decisions.Methods266 patients and 36 variables form the training dataset collected by Hospital 12 de Octubre (Madrid, Spain). The external test cohort provided by Instituto de Investigación Sanitaria La Fe (Valencia, Spain) contains 162 observations. An XGBoost model was trained with one dataset and validated with the other. Additionally, the features were ranked by permutation importance and compared with the ELN 2022 risk classification by genetics at initial diagnosis.ResultsThe model was evaluated with the training cohort using leave-one-out cross-validation, reaching a ROC-AUC of 0.85. By setting the functioning point that maximises Youden’s index, 3 out of 4 patients with complications and 84 out of 100 in remission are correctly classified. The model was validated with external data collected in a different hospital, achieving 0.7 ROC-AUC. At the best functioning point, almost 6 out of 10 patients with complications and 8 out of 10 patients in remission are correctly classified. Ranking the variables by descending importance, the top four are, in order: age, white-blood-cells count, Gender, and TP53. The list exhibits good coherence with the ELN 2022 risk classification.ConclusionsThe model achieves performances that suggest it could be used as a therapeutical decision support tool. Important variables are coherent with ELN 2022 risk classification. Further work is needed to understand the reasons for the drop in test performance. The 90-day model should be supplemented by others that predict the risk of complications at six months or one year.
Six novel nsSNPs affectRUNX1gene may leading to Acute Myeloid Leukemia (AML) using Bioinformatics approach
Authors: Omer Dalia , Ameer Tebyan , Alsheikh Tarig , NjmEldin Ahmed , Abdalmonem Zeinab , Suliman Hadil , Agbash Abubaker , Hamad Howaida , Alshareif Baha Aldeen , Hassan Mohammed A. 
Published: June 2023

ABSTRACTBackgroundRUNX1is one of the most frequently mutated genes in human AMLs, most ofRUNX1mutations in acute myeloid leukemia (AML) are missense or deletion-truncation and behave as loss-of-function mutations. The molecular consequences of cancer associated mutations in Acute myeloid leukemia (AML) linked factors are not very well understood. Here, we recognize possible pathogenic SNPs in theRUNX1gene as Functional differences caused by SNPs might have harmful effects on protein structure and function using various computational tools.MethodologyData gained from NCBI database and various tools used to study nsSNPs which they are: SIFT, Polyphen-2, Provean, SNAP2, I-Mutant, Project Hope, Raptor X, PolymiRTS and Gene MANIA.ResultOur study reveals six novel SNPs observed to be the most damaging SNPs that affect structure and function ofRUNX1gene using various bioinformatics tools.ConclusionThis study revealed 7 damaging SNPs, 6 novel nsSNP out of them in theRUNX1gene that leads to AML, by using different bioinformatics tools. Also, 23 functional classes were predicted in 8 SNPs in the 3’UTR, among them, 6 alleles disrupted a conserved miRNA site and 16 derived alleles created a new site of miRNA. This might result in the de regulation of the gene function. Hopefully, these results will help in genetic studying and diagnosis of AML improvement.
Optimizing Proteomics Data Differential Expression Analysis via High-Performing Rules and Ensemble Inference
Authors: Peng Hui , Wang He , Kong Weijia , Li Jinyan , Goh Wilson Wen Bin 
Published: June 2023

AbstractIn the process of identifying phenotype-specific or differentially expressed proteins from proteomic data, a standard workflow consists of five key steps: raw data quantification, expression matrix construction, matrix normalization, missing data imputation, and differential expression analysis. However, due to the availability of multiple options at each step, selecting ad hoc combinations of options can result in suboptimal analysis. To address this, we conducted an extensive study involving 10,808 experiments to compare the performance of exhaustive option combinations for each step across 12 gold standard spike-in datasets and three quantification platforms: FragPipe, MaxQuant, and DIA-NN. By employing frequent pattern mining techniques on the data from these experiments, we discovered high-performing rules for selecting optimal workflows. These rules included avoiding normalization, utilizing MinProb for missing value imputation, and employing limma for differential expression analysis. We found that workflow performances were predictable and could be accurately categorized using average F1 scores and Matthew’s correlation coefficients, both exceeding 0.79 in 10-fold cross-validations. Furthermore, by integrating the top-ranked workflows through ensemble inference, we not only improved the accuracy of differential expression analysis (e.g., achieving a 1-5% gain under five performance metrics for FragPipe), but also enhanced the workflow’s ability to aggregate proteomic information across various levels, including peptide and protein level intensities and spectral counts, providing a comprehensive perspective on the data. Overall, our study highlights the importance of selecting optimal workflow combinations and demonstrates the benefits of ensemble inference in improving both the accuracy and comprehensiveness of proteomic data analysis.
A method for deep and quantitative protein profiling of urine sediment, soluble and exosome fractions for biomarker research
Authors: Pichler Peter , Kurnikowski Amelie , Matzinger Manuel , Mechtler Karl 
Published: June 2023

AbstractUrine collection is painless and offers the potential for kidney liquid-biopsy(1), which appears particularly appealing with regard to the diagnosis of kidney disease (2) and patient follow-up after renal transplantation (3). From a nephrological point of view, urinary sediment and the soluble and exosome fractions of urine constitute different biological entities. We here describe a method that allows deep profiling of the protein content of the above-mentioned three fractions of urine by quantitative data-independent label-free proteomics. The method was evaluated using 19 urine samples from the Nephrology outpatient clinic at Vienna General Hospital, comprising a diverse set of chronic kidney disease (CKD) as well as patients after kidney transplantation (NTX). Peptide separation was accomplished through 60 min active gradients. A timsTOF Pro2 mass spectrometer was operated in DIA mode. The total analysis time per urine sample (three fractions) was around four hours. We demonstrate adequate technical and experimental reproducibility. Our data suggest that the protein information content of these three fractions is diverse, strengthening the importance of separate analysis. The depth of our quantitative proteomics approach permitted a detection of proteins characteristic for different parts of the nephron, such as Podocin, CD2-AP and Podocalyxin (Podocytes), SLC22A8 and SLC22A13 (proximal tubule) and Aquaporin-2 (collecting duct), suggesting that our method is sensitive enough to detect and quantify biologically relevant proteins that might serve as potential biomarkers. To the best of our knowledge, the ability to quantify up to 4000 protein groups per urine sample and more than 6000 protein groups in total makes our strategy the deepest proteome profiling study of urine to date. In conclusion, we established a method with promising figures of merit that we consider broadly applicable and useful for future clinical biomarker research studies in urine.