bluuebunny/crossref_metadata_2025 huggingface dataset:
New developments in diagnostics and treatment of adult-onset focal dystonia
Authors: Centen Liesanne M. , van Egmond Martje E. , Tijssen Marina A.J.
Published: June 2023

Purpose of review

The aim of this review is to showcase the recent developments in the field of diagnosis and treatment of adult-onset focal dystonia.

Recent findings

Accurate phenotyping of focal dystonia is essential in the process of finding an underlying cause, including acquired, genetic, and idiopathic causes. Motor symptoms as well as the associated nonmotor symptoms and their detrimental impact on quality of life have received increased interest over the last years. The diagnostic process is complicated by the steadily increasing numbers of newly discovered genes associated with dystonia. Recent efforts have been aimed at further developing recommendations and algorithms to aid in diagnosis and in navigating the use of diagnostic tools. In terms of treatment, research on DBS is advancing towards a better understanding of the most effective stimulation locations within the globus pallidus. Moreover, with the introduction of the LFP-recording devices, the search continues for an accurate electrophysiological biomarker for dystonia.

Accurate phenotyping and (sub)classification of patients with dystonia is important for improving diagnosis, subsequent treatment effect and population-based study outcomes in research. Medical practitioners should be attentive to the presence of nonmotor symptoms in dystonia.
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.

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.

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.

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.
PHOTONAI-Graph - A Python Toolbox for Graph Machine Learning
Authors: Ernsting Jan , Holstein Vincent , Winter Nils R. , Sarink Kelvin , Leenings Ramona , Gruber Marius , Repple Jonathan , Risse Benjamin , Dannlowski Udo , Hahn Tim
Published: June 2023

Graph data is an omnipresent way to represent information in machine learning. Especially, in neuroscience research, data from Diffusion-Tensor Imaging (DTI) and functional Magnetic Resonance Imaging (fMRI) is commonly represented as graphs. Exploiting the graph structure of these modalities using graph-specific machine learning applications is currently hampered by the lack of easy-to-use software. PHOTONAI Graph aims to close the gap between domain experts of machine learning, graph experts and neuroscientists. Leveraging the rapid machine learning model development features of the Python machine learning API PHOTONAI, PHOTONAI Graph enables the design, optimization, and evaluation of reliable graph machine learning models for practitioners. As such, it provides easy access to custom graph machine learning pipelines including, hyperparameter optimization and algorithm evaluation ensuring reproducibility and valid performance estimates. Integrating established algorithms such as graph neural networks, graph embeddings and graph kernels, it allows researchers without significant coding experience to build and optimize complex graph machine learning models within a few lines of code. We showcase the versatility of this toolbox by building pipelines for both resting–state fMRI and DTI data in the hope that it will increase the adoption of graph-specific machine learning algorithms in neuroscience research.
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

Background:

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

BACKGROUND AND PURPOSE

Simpson 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.

METHODS

A 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).

RESULTS

In 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%.

CONCLUSIONS

In 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

Large 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

Myalgic 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

Purpose

CDKL5 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.

Methods

We 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.

Results

We 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).

Conclusions

CDD 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

Background and Objective

The 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.

Methods

266 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.

Results

The 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.

Conclusions

The 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

Background

RUNX1is 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.

Methodology

Data 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.

Result

Our study reveals six novel SNPs observed to be the most damaging SNPs that affect structure and function ofRUNX1gene using various bioinformatics tools.

Conclusion

This 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

In 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

Urine 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.
Concatenated tandem constructs of BK channels reveal three distinct types of subunit stoichiometry in channel modulation by the auxiliary γ subunit and mutations in the channel pore region
Authors: Chen Guanxing , Li Qin , Yan Jiusheng
Published: June 2023

The large-conductance, Ca2+-activated K+(BK) channels consist of the Ca2+- and voltage-sensing and pore-forming α (BKα) subunits and regulatory auxiliary β or γ subunits. Concatenated tandem constructs have been proved to be necessary and powerful in understanding the subunit stoichiometry of K+channel gating and regulation by constraining the stoichiometry, organization, and mutation of individual subunits. However, because of its unique possession of an extra S0 transmembrane segment that puts the N- and C- termini on the opposite sides of the membrane, it is impossible to generate concatenated tandem subunit constructs of BK channels as those done with other K+channels. In order to investigate the molecular mechanisms of the atypical “all-or-none” modulatory function of the γ subunits and the subunit stoichiometry of BK channel gating, we have taken a novel strategy and generated functional concatenated tandem constructs containing 2 or 4 copies of the BKα subunits by splicing BKα into 2 protein constructs that can be co-expressed to form functional channels. We observed that the BK channels formed by concatenated tandem constructs are similar to intact channels in voltage and Ca2+gating properties. Interestingly, the BKγ1 subunit and mutations located at the S6 transmembrane segment and selectivity filter displayed 3 distinct types of subunit stoichiometry in BK channel modulation. By fusion of the BKγ1 subunit to the N-terminus of the concatenated tandem BKα constructs, we observed that a single molecule of BKγ1 subunit per tetrameric BKα channel is sufficient to fully modulate the channels. The Y294K, F303A, and L312A mutations at each BKα subunit has an incremental effect on BK channel gating. The V288A mutation at the selectivity filter produce an “all-or-none” effect but requires mutations at all 4 BKα subunits to have modulatory effect on channel gating, i.e., mutations at 1, 2, or 3 subunits have nearly no effect. Interestingly, the F307A mutation exhibited an atypical “all-or-none” modulatory function similar to that of the γ1 subunit. The diversity in subunit stoichiometry of BK channel modulation indicates distinct mechanisms in affecting BK channel gating. Overall, we have developed novel concatenated tandem constructs for BK channels and revealed three distinct types of subunit stoichiometry in BK channel modulation by the auxiliary γ subunit and mutations at the pore-lining S6 transmembrane segment and selectivity filter.
Trends in Complications among Patients undergoing Aortic Valve Replacement (AVR) in the United States
Authors: Harvey James E. , Kapadia Samir R. , Cohen David J. , Kalra Ankur , Irish William , Gunnarsson Candace , Ryan Michael , Chikermane Soumya , Thompson Christin , Puri Rishi
Published: June 2023

Background

The treatment of severe aortic stenosis has evolved considerably since the introduction of transcatheter aortic valve replacement (TAVR), yet trends in in-hospital complications for patients undergoing TAVR or surgical aortic valve replacement (SAVR) at a national level have yet to be evaluated.

Methods

We performed a retrospective cohort study using Medicare data to evaluate temporal trends in complications among beneficiaries aged ≥65 years treated with elective isolated transfemoral TAVR or SAVR between 2012 and 2019. The study endpoint was the occurrence of a major complication during the index AVR hospitalization, defined as a composite outcome. Multivariable logistic regression was used to assess odds of complications for TAVR and SAVR, individually over time, after adjusting for baseline characteristics. Another risk-adjusted model assessed the risk of complications for TAVR vs SAVR, over time.

Results

The cohort included 211,212 patients (mean age:78.6±7.3 years, female:45.0%). Complication rates following elective isolated AVR decreased from 49% in 2012 to 22% in 2019. These reductions were more pronounced for TAVR (41%->19%, delta=22%) than SAVR (51%->47%, delta=4%). After risk adjustment, the risk of any complication with TAVR was 47% (p<0.0001) lower compared to SAVR in 2012, and 78% (p<0.0001) lower in 2019. TAVR was independently associated with reduced odds of complications each year compared to 2012, with the magnitude of benefit increasing over time (2013 vs 2012: OR=0.89(0.81-0.97); 2019 vs 2012: OR=0.35(0.33-0.38)).

Conclusions

Between 2012-2019, the risk of complications after AVR among Medicare beneficiaries decreased significantly, with larger absolute and relative changes among patients treated with TAVR than SAVR.
All-optical mapping of cAMP transport reveals rules of sub-cellular localization
Authors: Xiang Katherine M. , Park Pojeong , Koren Shon A. , Hayward Rebecca Frank , Cohen Adam E.
Published: June 2023

Cyclic adenosine monophosphate (cAMP) is a second messenger that mediates diverse intracellular signals. Studies of cAMP transport in cells have produced wildly different results, from reports of nearly free diffusion to reports that cAMP remains localized in nanometer-scale domains. We developed an all-optical toolkit, termed cAMP-SITES, to locally perturb and map cAMP transport. In MDCK cells and in cultured neurons, cAMP had a diffusion coefficient of ∼120 µm2/s, similar to the diffusion coefficients of other small molecules in cytoplasm. In neuronal dendrites, a balance between diffusion and degradation led to cAMP domains with a length scale of ∼30 µm. Geometrical confinement by membranes led to subcellular variations in cAMP concentration, but we found no evidence of nanoscale domains or of distinct membrane-local and cytoplasmic pools. We introduce theoretical relations between cell geometry and small-molecule reaction-diffusion dynamics and transport to explain our observations.
A closer look at Type I left-handed β-helices provides a better understanding in their sequence-structure relationship: towards their rational design
Authors: Naudé Maxime , Faller Peter , Lebrun Vincent
Published: June 2023

Understanding the sequence-structure relationship in protein is of fundamental interest, but has practical applications such as the rational design of peptides and proteins. This relationship in the Type I left-handed β–helix containing proteins is updated and revisited in this study. Analysing the available structures in the Protein Data Base, we could describe further in details the structural features that are important for the stability of this fold, as well as its nucleation and termination. This study is meant to complete previous work, as it provides a separate analysis of the N-terminal and C-terminal rungs of the helix. Particular sequence motifs of these rungs are described along with the structural element they form.
Temporal spiking sequences in visual cortex carry unique information about natural movies
Authors: Sotomayor-Gómez Boris , Battaglia Francesco P. , Vinck Martin
Published: June 2023

Information in the nervous system is encoded by the spiking patterns of large populations of neurons. The analysis of such high-dimensional data is typically restricted to simple, arbitrarily defined features like spike rates, which discards information in the temporal structure of spike trains. Here, we use a recently developed method called SpikeShip based on optimal transport theory, which captures information from all of the relative spike-timing relations among neurons. We compared spike-rate and spike-timing codes in neural ensembles from six visual areas during natural video presentations. Temporal spiking sequences conveyed substantially more information about natural movies than population spike-rate vectors, especially for larger number of neurons. As previously, shown, population rate vectors exhibited substantial drift across repetitions and between blocks. Conversely, encoding through temporal sequences was stable over time, and did not show representational drift both within and between blocks. These findings reveal a purely spike-based neural code that is based on relative spike timing relations in neural ensembles alone.
Peripheral linker mediates ACP’s recognition of DH and stabilizes Mycobacterium tuberculosis FAS-I
Authors: Kumar Akhil , Sharma Manisha , Katkar Harshwardhan H.
Published: June 2023

1

Incomplete structural details of Mycobacterium tuberculosis (Mtb) fatty acid synthase-I (FAS-I) at near-atomic resolution have limited our understanding of the shuttling mechanism of its mobile acyl carrier protein (ACP). Here, we have performed atomistic molecular dynamics simulation of Mtb FAS- I with a homology-modelled structure of ACP stalled at dehydratase (DH), and identified key residues that mediate anchoring of the recognition helix of ACP near DH. The observed distance between catalytic residues of ACP and DH agrees with that reported for fungal FAS-I. Further, the conformation of the peripheral linker is found to be crucial in stabilizing ACP near DH. Correlated inter-domain motion is observed between DH, enoyl reductase (ER) and malonyl/palmitoyl transferase (MPT); consistent with prior experimental reports of fungal and Mtb FAS-I.
Physiological adaptation to high irradiance in duckweeds depends on light habitat niche and is ecotype and species-specific
Authors: Smith Kellie E. , Cowan Laura , Taylor Beth , McAusland Lorna , Heatley Matthew , Murchie Erik H.
Published: June 2023

Duckweeds are free-floating aquatic organisms with species ranging from 2 mm-10 mm, where each plant is a single leaflike structure. Recognized as an emerging food crop, their fast growth rates offer potential for cultivation in closed systemsHowever the majority of available duckweed clones lack information regarding habitat origin and physiology. We describe a novel UK collection derived from low light (dLL) or high light (dHL) habitats and profiled for growth, photosynthesis and photoprotection (Non Photochemical Quenching, NPQ) responses. Multiple ecotypes of threeLemnaspecies and one ecotype ofSpirodela polyrhiza, were grown under low light (LL:100 μmol m-2s-1) and high light (HL:350 μmol m-2s-1). We found species and ecotypic variation in photosynthesis acclimation. Duckweeds grown under HL exhibited lower growth rate, biomass, chlorophyll and quantum yield of photosynthesis. In HL-compared to LL, carotenoid de-epoxidation state and NPQ were higher whilst photosystem II efficiency (ϕPSII) and chla:b ratios were unchanged. Interestingly dLL plants showed relatively stronger acclimation to HL compared to dHL plants: These ecotypes achieved faster growth in HL: by area and colony gain, higher carotenoid levels and less degradation of chlorophyll. We conclude that adaptation to local habitat among ecotypes strongly affects performance under controlled conditions.
Non-image forming vision as measured through ipRGC-mediated pupil constriction is not modulated by covert visual attention
Authors: Vilotijević Ana , Mathôt Sebastiaan
Published: June 2023

In brightness the pupil constricts, while in darkness the pupil dilates; this is known as the pupillary light response (PLR). The PLR is driven by all photoreceptors: rods and cones, which contribute to image-forming vision, as well as intrinsically photosensitive retinal ganglion cells (ipRGCs), which contribute to non-image-forming vision. Rods and cones cause immediate pupil constriction upon light exposure, whereas ipRGCs cause sustained constriction for as long as light exposure continues. Recent studies have shown that the initial PLR is modulated by covert attention; however, it remains unclear whether the same holds for the sustained PLR. Here, we investigated the effect of covert attention on sustained, ipRGC-mediated pupil constriction. We leveraged the fact that ipRGCs are predominantly responsive to blue light, causing the most prominent sustained constriction in response to blue light. Replicating previous studies, we found that the pupil constricted more when either directly looking at, or covertly attending to, bright as compared to dim stimuli (with the same color). We also found that the pupil constricted more when directly looking at blue as compared to red stimuli (with the same luminosity); crucially, however, we didnotfind any difference in pupil size when covertly attending to blue as compared to red stimuli. This suggests that ipRGC-mediated pupil constriction, and possibly non-image-forming vision more generally, is not modulated by covert attention.

Significance statement

When we think of vision, we generally think of image-forming vision, that is, seeing things. However, vision can also be “non-image-forming”; for example, our day-night rhythm and pupil size are regulated by visual input, but not in a way that gives rise to conscious visual awareness. While visual attention shapes image-forming vision, its influence on non-image forming vision remains unclear. We investigated this by using ipRGCs,which contribute to non-image-forming vision and are responsive to blue light. Aside from replicating the effect of covert attention on image-forming vision, we showed that pupil constriction differed between directly looking at blue/ red stimuli, but not during covert attention to these stimuli. This suggests that non-image forming vision is not influenced by covert visual attention.
The Salivary Microbiome and Predicted Metabolite Production are Associated with Progression from Barrett’s Esophagus to Esophageal Adenocarcinoma
Authors: Solfisburg Quinn S , Baldini Federico , Baldwin-Hunter Brittany L , Lee Harry H , Park Heekuk , Freedberg Daniel E , Lightdale Charles J , Korem Tal , Abrams Julian A
Published: June 2023

Esophageal adenocarcinoma (EAC) is rising in incidence and associated with poor survival, and established risk factors do not explain this trend. Microbiome alterations have been associated with progression from the precursor Barrett’s esophagus (BE) to EAC, yet the oral microbiome, tightly linked to the esophageal microbiome and easier to sample, has not been extensively studied in this context. We aimed to assess the relationship between the salivary microbiome and neoplastic progression in BE to identify microbiome-related factors that may drive EAC development. We collected clinical data and oral health and hygiene history and characterized the salivary microbiome from 250 patients with and without BE, including 78 with advanced neoplasia (high grade dysplasia or early adenocarcinoma). We assessed differential relative abundance of taxa by 16S rRNA gene sequencing and associations between microbiome composition and clinical features and used microbiome metabolic modeling to predict metabolite production. We found significant shifts and increased dysbiosis associated with progression to advanced neoplasia, with these associations occurring independent of tooth loss, and the largest shifts were with the genusStreptococcus. Microbiome metabolic models predicted significant shifts in the metabolic capacities of the salivary microbiome in patients with advanced neoplasia, including increases in L- lactic acid and decreases in butyric acid and L-tryptophan production. Our results suggest both a mechanistic and predictive role for the oral microbiome in esophageal adenocarcinoma. Further work is warranted to identify the biological significance of these alterations, to validate metabolic shifts, and to determine whether they represent viable therapeutic targets for prevention of progression in BE.
Inadequate structural constraint on Fab approach rather than paratope elicitation limits HIV-1 MPER vaccine utility
Authors: Tan Kemin , Chen Junjian , Kaku Yu , Wang Yi , Donius Luke , Khan Rafiq Ahmad , Li Xiaolong , Richter Hannah , Seaman Michael S. , Walz Thomas , Hwang Wonmuk , Reinherz Ellis L. , Kim Mikyung
Published: June 2023

Broadly neutralizing antibodies (bnAbs) against HIV-1 target conserved epitopes, thereby inhibiting viral entry. Yet surprisingly, those recognizing linear epitopes in the HIV-1 gp41 membrane proximal external region (MPER) are elicited neither by peptide nor protein scaffold vaccines. Here, we observe that while Abs generated by MPER/liposome vaccines may exhibit human bnAb-like paratopes, B-cell programming without constraints imposed by the gp160 ectodomain selects Abs unable to access the MPER within its native “crawlspace”. During natural infection, the flexible hinge of IgG3 partially mitigates steric occlusion of less pliable IgG1 subclass Abs with identical MPER specificity, until affinity maturation refines entry mechanisms. The IgG3 subclass maintains B-cell competitiveness, exploiting bivalent ligation resulting from greater intramolecular Fab arm length, offsetting weak antibody affinity. These findings suggest future immunization strategies.
Truly tiny acoustic biomolecules for ultrasound imaging and therapy
Authors: Ling Bill , Gungoren Bilge , Yao Yuxing , Dutka Przemysław , Smith Cameron A. B. , Lee Justin , Swift Margaret B. , Shapiro Mikhail G.
Published: June 2023

Nanotechnology offers significant advantages for medical imaging and therapy, including enhanced contrast and precision targeting. However, integrating these benefits into ultrasonography has been challenging due to the size and stability constraints of conventional bubble-based agents. Here we describe bicones, truly tiny acoustic contrast agents based on gas vesicles, a unique class of air-filled protein nanostructures naturally produced in buoyant microbes. We show that these sub-80 nm particles can be effectively detected both in vitro and in vivo, infiltrate tumors via leaky vasculature, deliver potent mechanical effects through ultrasound-induced inertial cavitation, and are easily engineered for molecular targeting, prolonged circulation time, and payload conjugation.
Evolutionary potential of the monkeypox genome arising from interactions with human APOBEC3 enzymes
Authors: Delamonica Brenda , Davalos Liliana , Larijani Mani , Anthony Simon J , Liu Jia , MacCarthy Thomas
Published: June 2023

APOBEC3, an enzyme subfamily that plays a role in virus restriction by generating mutations at particular DNA motifs or mutational “hotspots,” can drive viral mutagenesis with host-specific preferential hotspot mutations contributing to pathogen variation. While previous analysis of viral genomes from the 2022 Mpox (formerly Monkeypox) disease outbreak has shown a high frequency of C>T mutations at TCmotifs, suggesting recent mutations are human APOBEC3-mediated, how emerging monkeypox virus (MPXV) strains will evolve as a consequence of APOBEC3-mediated mutations remains unknown. By measuring hotspot under-representation, depletion at synonymous sites, and a combination of the two, we analyzed APOBEC3-driven evolution in human poxvirus genomes, finding varying hotspot under-representation patterns. While the native poxvirus molluscum contagiosum exhibits a signature consistent with extensive coevolution with human APOBEC3, including depletion of TChotspots, variola virus shows an intermediate effect consistent with ongoing evolution at the time of eradication. MPXV, likely the result of recent zoonosis, showed many genes with more TChotspots than expected by chance (over-representation) and fewer GChotspots than expected (under-representation). These results suggest the MPXV genome: 1) may have evolved in a host with a particular APOBEC GChotspot preference, 2) has inverted terminal repeat (ITR) regions –which may be exposed to APOBEC3 for longer during viral replication– and longer genes likely to evolve faster, and therefore 3) has a heightened potential for future human APOBEC3-meditated evolution as the virus spreads in the human population. Our predictions of MPXV mutational potential can both help guide future vaccine development and identification of putative drug targets and add urgency to the task of containing human Mpox disease transmission and uncovering the ecology of the virus in its reservoir host.