bluuebunny/crossref_metadata_2025_split huggingface dataset:
Usefulness of Interposition Arteriovenous Bundle Grafts in Free Flap Surgery
Authors: Kim Jisu , Lee Kyeong-Tae 
Published: June 2022

Background
The paucity of reliable recipient vessels adjacent to defects poses a great challenge in free flap reconstruction. Although the use of interposition vein grafts to cover the vascular gap is common, its potential association with higher risks of flap compromise is often reported. Interposition arteriovenous bundle grafts have been introduced as an alternative. This study aimed to evaluate the outcomes of free tissue transfer using interposition arteriovenous bundle grafts and to conduct a systematic review of studies that reported the use of the technique.

Methods
Patients who underwent free tissue transfer using the interposition arteriovenous bundle graft technique were assessed for flap perfusion-related complications. A systematic review of literature was performed using pooled analysis to calculate the rate of perfusion-related complications.

Results
Overall, 14 cases of free flap reconstruction used the interposition arteriovenous bundle graft technique to cover vascular gaps in diverse regions. The most common donor vessel of this graft was the descending branch of the lateral circumflex femoral vessels (mean length, 6.9 cm). All flaps survived except for 1 case of partial flap loss, showing a flap compromise rate of 7.1%. A systematic review identified 13 studies that represented 78 cases using this technique. In the pooled analysis, including the current series, the overall flap survival rate was 95.7%, reporting 4 of 92 cases of flap compromise.

Conclusions
The interposition arteriovenous bundle graft technique may help overcome the challenges of pedicle shortage or lack of adjacent recipient vessels in free flap reconstruction.
Synchronous Telemedicine Model in Urogynecology: Are Patients Willing to Continue Telemedicine in the Post–COVID-19 Pandemic Era?
Authors: Kim Youngwu , Ortega Marcus V. , Acker Rachael , Valentine Kathrene D. , Ayati Elnaz , Von Bargen Emily 
Published: June 2022

Importance
Following the recent expansion of telemedicine during the COVID-19 pandemic, this remote model of care in female pelvic medicine and reconstructive surgery will likely remain and continue to evolve.

Objective
This study was conducted to assess patients’ perceptions of and willingness to participate in a synchronous telemedicine visit beyond the COVID-19 pandemic for women with pelvic floor disorders.

Study Design
We conducted a cross-sectional study of women who completed a synchronous telemedicine visit from March 16 through May 22, 2020, at a urogynecology practice in an academic medical center. An electronic survey was distributed to women after all telemedicine visits. Demographic data, visit type, and survey responses were analyzed.

Results
Two hundred two women received the survey, and 135 women completed it (response rate of 66.8%). The mean age of the respondents was 62.9 ± 16.4 years, and the 3 most common visit diagnoses were overactive bladder (43.7%), stress urinary incontinence (22.2%), and pelvic organ prolapse (21.4%). Most survey participants (88.9%) found that the quality of their telemedicine visits was better than expected, and 89.6% reported that they would like to continue telemedicine care. Our survey showed that 19.4% of women reported difficulty with technology.

Conclusions
We found that most women presenting for synchronous telemedicine urogynecology care had a positive visit experience and would continue to use telemedicine for their care. Further developmental work needs to be done on improving the ease of technology as well as availability of telemedicine in the care of women affected by pelvic floor disorders.
Pharmacological determination of the fractional block of Nav channels required to impair neuronal excitability and ex vivo seizures
Authors: Thouta Samrat , Waldbrook Matthew G. , Lin Sophia , Mahadevan Arjun , Mezeyova Jannette , Soriano Maegan , Goodchild Samuel J. , Parrish R. Ryley 
Published: June 2022

AbstractVoltage-gated sodium channels (Nav) are essential for the initiation and propagation of action potentials in neurons. Of the different channel subtypes, Nav1.1, Nav1.2 and Nav1.6 are prominently expressed in the adult central nervous system (CNS). All three of these sodium channel subtypes are sensitive to block by the neurotoxin tetrodotoxin (TTX), with TTX being almost equipotent on all three subtypes. In the present study we have used TTX to determine the fractional block of Nav channels required to impair action potential firing in pyramidal neurons and reduce network seizure-like activity.Using automated patch-clamp electrophysiology, we first determined the IC50s of TTX on mouse Nav1.1, Nav1.2 and Nav1.6 channels expressed in HEK cells, demonstrating this to be consistent with previously published data on human Nav channels. We then compared this data to the potency of block of Nav current measured in pyramidal neurons from neocortical brain slices. Interestingly, we found that it requires nearly 10-fold greater concentration of TTX over the IC50 to induce significant block of action potentials using a current-step protocol. In contrast, concentrations near the IC50 resulted in a significant reduction in AP firing and increase in rheobase using a ramp protocol. Surprisingly, a 20% reduction in action potential generation observed with 3 nM TTX resulted in significant block of seizure-like activity in the 0 Mg2+ model of epilepsy. Additionally, we found that approximately 50% block in pyramidal cell intrinsic excitability is sufficient to completely block all seizure-like events. These data serve as a critical starting point in understanding how fractional block of Nav channels affect intrinsic neuronal excitability and seizure-like activity. It further suggests that seizures can be controlled without significantly compromising intrinsic neuronal activity and determines the required fold over IC50 for novel and clinically relevant Nav channel blockers to produce efficacy and limit side effects.
Virtual Liver Needle Biopsy from Reconstructed Three-Dimensional Histopathological Images: Quantification of Sampling Error
Authors: Li Qiang , Wang Fusheng , Chen Yaobing , Chen Hao , Wu Shengdi , Farris Alton B. , Jiang Yi , Kong Jun 
Published: June 2022

AbstractIntroductionPrevalently considered as the “gold-standard” for diagnosis of hepatic fibrosis and cirrhosis, the clinical liver needle biopsy is known to be subject to inadequate sampling and a high mis-sampling rate. However, quantifying such sampling bias has been difficult as generating a large number of needle biopsies from the same living patient is practically infeasible. We construct a three-dimension (3D) virtual liver tissue volume by spatially registered high resolution Whole Slide Images (WSIs) of serial liver tissue sections with a novel dynamic registration method. We further develop a Virtual Needle Biopsy Sampling (VNBS) method that mimics the needle biopsy sampling process. We apply the VNBS method to the reconstructed digital liver volume at different tissue locations and angles. Additionally, we quantify Collagen Proportionate Area (CPA) in all resulting virtual needle biopsies in 2D and 3D.ResultsThe staging score of the center 2D longitudinal image plane from each 3D biopsy is used as the biopsy staging score, and the highest staging score of all sampled needle biopsies is the diagnostic staging score. The Mean Absolute Difference (MAD) in reference to the Scheuer and Ishak diagnostic staging scores are 0.22 and 1.00, respectively. The absolute Scheuer staging score difference in 22.22% of sampled biopsies is 1. By the Ishak staging method, 55.56% and 22.22% of sampled biopsies present score difference 1 and 2, respectively. There are 4 (Scheuer) and 6 (Ishak) out of 18 3D virtual needle biopsies with intra-needle variations. Additionally, we find a positive correlation between CPA and fibrosis stages by Scheuer but not Ishak method. Overall, CPA measures suffer large intra- and inter-needle variations.ConclusionsThe developed virtual liver needle biopsy sampling pipeline provides a computational avenue for investigating needle biopsy sampling bias with 3D virtual tissue volumes. This method can be applied to other tissue-based disease diagnoses where the needle biopsy sampling bias substantially affects the diagnostic results.
Metagenomics of Parkinson’s disease implicates the gut microbiome in multiple disease mechanisms
Authors: Wallen Zachary D , Demirkan Ayse , Twa Guy , Cohen Gwendolyn , Dean Marissa N , Standaert David G , Sampson Timothy , Payami Haydeh 
Published: June 2022

AbstractParkinson’s disease (PD) may start in the gut and spread to the brain. To investigate the role of gut microbiome, we enrolled 490 PD and 234 control individuals, conducted deep shotgun sequencing of fecal DNA, followed by metagenome-wide association studies requiring significance by two methods (ANCOM-BC and MaAsLin2) to declare disease association. Thirty-percent of species and pathways tested had altered abundances in PD, depicting a widespread dysbiosis. Network analysis showed PD-associated species form polymicrobial clusters that grow or shrink together, and some compete. Metagenomic profile of PD indicates a disease permissive microbiome, evidenced by overabundance of pathogens and immunogenic components, dysregulated neuroactive signaling, preponderance of molecules that induce alpha-synuclein pathology, and over-production of toxicants; with the reduction in anti-inflammatory and neuroprotective factors limiting the capacity to recover. These data provide a broad foundation with a wealth of concrete testable hypotheses to discern the role of the gut microbiome in PD.
Human iPSC-CMs and in-silico technologies define mechanisms and accelerate targeted pharmacogenetics in hypertrophic cardiomyopathy
Authors: Margara Francesca , Psaras Yiangos , Wang Zhinuo Jenny , Schmid Manuel , Doste Ruben , Garfinkel Amanda , Repetti Giuliana G. , Seidman Jonathan , Seidman Christine , Rodriguez Blanca , Toepfer Christopher N. , Bueno-Orovio Alfonso 
Published: June 2022

AbstractCardiomyopathies have unresolved genotype-phenotype relationships and lack disease-specific treatments. Here we identify genotype-specific pathomechanisms and therapeutic targets combining experimental hiPSC-CM modelling and human-based cardiac electromechanical in-silico modelling and simulation bridging from specific mutations to clinical biomarkers. We select hypertrophic cardiomyopathy as a challenge for this approach and study genetic variations that mutate proteins of the thick (MYH7R403Q/+) and thin filaments (TNNT2R92Q/+,TNNI3R21C/+) of the cardiac sarcomere. We show that destabilisation of myosin super relaxation drives disease inMYH7R403Q/+with secondary effects on thin filament activation, which are corrected by Mavacamten. Thin filament variantsTNNT2R92Q/+andTNNI3R21C/+share calcium regulation-related pathomechanisms, for which Mavacamten provides incomplete salvage. We define the ideal characteristics of a novel thin filament-targeting compound and show its efficacy in-silico. We demonstrate that hybrid human-based hiPSC-CM and in-silico studies accelerate pathomechanism discovery and classification testing, improving clinical interpretation of genetic variants, and directing rational therapeutic targeting and design.
An Internal Model of Sensorimotor Context in Freely Swimming Electric Fish
Authors: Wallach Avner , Sawtell Nathaniel B. 
Published: June 2022

AbstractNervous systems are hypothesized to learn and store internal models that predict the sensory consequences of motor actions. However, little is known about the neural mechanisms for generating accurate predictions under real-world conditions in which the sensory consequences of action depend on environmental context. Using novel methods for underwater neural recording in freely swimming electric fish, we demonstrate that complex movement-related input to the active electrosensory system is effectively cancelled, despite being highly-dependent on the nearby environment. Computational modeling and closed-loop electrophysiological experiments indicate that the cerebellum-like circuitry of the electrosensory lobe generates context-specific predictions of self-generated input by combining motor signals with electrosensory feedback. These results provide mechanistic insight into sophisticated internal models supporting natural behavior in freely moving animals.One-Sentence SummaryUnderwater recordings in electric fish reveal neural mechanisms for predicting the sensory consequences of behavior under natural conditions in freely moving animals.
Whole-brain dynamical modeling for classification of Parkinson’s disease
Authors: Jung Kyesam , Florin Esther , Patil Kaustubh R. , Caspers Julian , Rubbert Christian , Eickhoff Simon B. , Popovych Oleksandr V. 
Published: June 2022

AbstractSimulated whole-brain connectomes demonstrate an enhanced inter-individual variability depending on data processing and modeling approach. By considering the human brain connectome as an individualized attribute, we investigate how empirical and simulated whole-brain connectome-derived features can be utilized to classify patients with Parkinson’s disease against healthy controls in light of varying data processing and model validation. To this end, we applied simulated blood oxygenation level-dependent signals derived by a whole-brain dynamical model simulating electrical signals of neuronal populations to reveal differences between patients and controls. In addition to the widely used model validation via fitting the dynamical model to empirical neuroimaging data, we invented a model validation against behavioral data, such as subject classes, which we refer to as behavioral model fitting and show that it can be beneficial for Parkinsonian patient classification. Furthermore, the results of machine-learning reported in this study also demonstrated that performance of the patient classification can be improved when the empirical data are complemented by the simulation results. We also showed that temporal filtering of blood oxygenation level-dependent signals influences the prediction results, where the filtering in the low-frequency band is advisable for Parkinsonian patient classification. In addition, composing the feature space of empirical and simulated data from multiple brain parcellation schemes provided complementary features that improve prediction performance. Based on our findings, we suggest including the simulation results with empirical data is effective for inter-individual research and its clinical application.
Enhancing associative learning in rats with a computationally designed training protocol
Authors: Zhang Xu O. , Zhang Yili , Cho Claire E. , Engelke Douglas S. , Smolen Paul , Byrne John H , Do-Monte Fabricio H. 
Published: June 2022

AbstractBackgroundLearning requires the activation of protein kinases with distinct temporal dynamics. InAplysia,nonassociative learning can be enhanced by a computationally designed learning protocol with intertrial intervals (ITIs) that maximize the interaction between fast-activated protein kinase A (PKA) and slow-activated extracellular signal-regulated kinase (ERK). Whether a similar strategy can enhance associative learning in mammals is unknown.MethodsWe simulated 1,000 training protocols with varying ITIs to predict an optimal protocol based on empirical data for PKA and ERK dynamics in rat hippocampus. Adult male rats received the optimal protocol or control protocols in auditory fear conditioning and fear extinction experiments. Immunohistochemistry was performed to evaluate phosphorylated cAMP responsive element binding (pCREB) protein levels in brain regions implicated in fear acquisition.ResultsRats exposed to the optimal conditioning protocol with irregular ITIs exhibited impaired extinction memory acquisition within the session using a standard footshock intensity, and stronger fear memory retrieval and spontaneous recovery with a weaker footshock intensity, compared to rats that received massed or spaced conditioning protocols with fixed ITIs. Rats exposed to the optimal extinction protocol displayed improved extinction of contextual fear memory and reduced spontaneous recovery compared to rats that received standard extinction protocols. Moreover, the optimal conditioning protocol increased pCREB levels in the dentate gyrus (DG) of the dorsal hippocampus, suggesting enhanced induction of long-term potentiation.ConclusionThese findings demonstrate that a computational model-driven behavioral intervention can enhance associative learning in mammals, and may provide insight into strategies to improve cognition in humans.
An integrative web-based software tool for multi-dimensional pathology whole-slide image analytics
Authors: Shen Alice , Wang Fusheng , Paul Saptarshi , Bhuvanapalli Divya , Alayof Jacob , Farris Alton B. , Teodoro George , Brat Daniel J. , Kong Jun 
Published: June 2022

AbstractIn the era of precision medicine, human tumor atlas oriented studies have been significantly facilitated by high-resolution, multi-modal tissue based microscopic pathology image analytics. To better support such tissue-based investigations, we develop Digital Pathology Laboratory (DPLab), a publicly available web-based platform, to assist biomedical research groups, non-technical end users, and clinicians for pathology Whole-Slide Image (WSI) visualization, annotation, analysis, and sharing via web browsers. A major advance of this work is the easy-to-follow methods to reconstruct three-dimension (3D) tissue image volumes by registering two-dimension (2D) whole-slide pathology images of serial tissue sections stained by hematoxylin and eosin (H&E), and immunohistochemistry (IHC). The integration of these serial slides stained by different methods provides cellular phenotype and pathophysiologic states in the context of a 3D tissue micro-environment. DPLab is hosted on a publicly accessible server and connected to a backend computational cluster for intensive image analysis computations, with results visualized, downloaded, and shared via a web interface. Equipped with an analysis toolbox of numerous image processing algorithms, DPLab supports continued integration of community-contributed algorithms and presents an effective solution to improve the accessibility and dissemination of image analysis algorithms by research communities. It represents the first step in making next generation tissue investigation tools widely available to the research community, enabling and facilitating discovery of clinically relevant disease mechanisms in a digital 3D tissue space.
Characterization of TGFβ-induced tendon-like structure in scaffold-free three-dimensional tendon cell culture
Authors: Koo Bon-hyeock , Lee Yeon-Ju , Park Na Rae , Heo Su-Jin , Hudson David M. , Fernandes Aysel A. , Friday Chet S. , Hast Michael W. , Corr David T. , Keene Douglas R. , Tufa Sara F. , Dyment Nathaniel A. , Joeng Kyu Sang 
Published: June 2022

AbstractTendons transmit mechanical forces between muscle and bone. Their biomechanical function requires high tensile strength provided by highly organized collagen fibers. Tenocytes mainly drive tendon growth via extracellular matrix (ECM) production and organization. The biological mechanisms regulating tenocyte differentiation and morphological maturation have not been well-established, partly due to the lack of reliablein vitrosystems that produce highly aligned collagenous tissues. In this study, we developed a scaffold-free, three-dimensional (3D) tendon culture system using mouse tendon cells and a differentially adherent growth channel. TGFβ treatment promoted tendon-like structure in the peripheral layer of the constructs with decreased cell density, decreased cell proliferation, increased thickness, and more elongated cells within highly aligned extracellular matrix. The constructs were used to understand the function of TGFβ signaling in tenogenic differentiation, collagen fibrillogenesis, and biomechanical properties. This scaffold-free 3D constructs system can serve as a reliablein vitrosystem to study underlying biological mechanisms that regulate cellular and matrix maturation in tendon development and growth.
omicsGAT: Graph Attention Network for Cancer Subtype Analyses
Authors: Baul Sudipto , Ahmed Khandakar Tanvir , Filipek Joseph , Zhang Wei 
Published: June 2022

MotivationThe use of high-throughput omics technologies is becoming increasingly popular in all facets of biomedical science. The mRNA sequencing (RNA-seq) method reports quantitative measures of more than tens of thousands of biological features. It provides a more comprehensive molecular perspective of studied cancer mechanisms compared to traditional approaches. Graph-based learning models have been proposed to learn important hidden representations from gene expression data and network structure to improve cancer outcome prediction, patient stratification, and cell clustering. However, these graph-based methods cannot rank the importance of the different neighbors for a particular sample in the downstream cancer subtype analyses. In this study, we introduce omicsGAT, a graph attention network (GAT) model to integrate graph-based learning with an attention mechanism for RNA-seq data analysis. The multi-head attention mechanism in omicsGAT can more effectively secure information of a particular sample by assigning different attention coefficients to its neighbors.ResultsComprehensive experiments on The Cancer Genome Atlas (TCGA) breast cancer and bladder cancer bulk RNA-seq data, and primary diffuse gliomas single-cell RNA-seq data validate that (1) the proposed model can effectively integrate neighborhood information of a sample and learn an embedding vector to improve disease phenotype prediction, cancer patient stratification, and cell clustering of the sample. (2) The attention matrix generated from the multi-head attention coefficients provides more useful information compared to the sample correlation-based adjacency matrix. From the results, we can conclude that some neighbors play a more important role than others in cancer subtype analyses of a particular sample based on the attention coefficient.Availability and implementationSource code is available at: https://github.com/CompbioLabUCF/omicsGATSupplementary informationSupplementary data are available at BioRxiv online.