bluuebunny/crossref_metadata_2025_split huggingface dataset:
Consumption of processed meat and its interactions with alcohol drinking and polygentic risk scores on breast cancer risk: a cohort study in the UK biobank
Authors: Zhu Pingxiu , Zhang Yanyu , Zou Shuqing , Yu Xingxing , Song Mengjie , Lin Moufeng , Yang Haomin 
Published: August 2022

AbstractBackgroundProcessed meat and alcohol have been consistently associated with breast cancer risk, but evidence for their effects in women with different genetic susceptibility of breast cancer is scarce, and little is known about their interactions.MethodsWe analyzed data from 260,779 female participants in the UK Biobank. Multivariable adjusted Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for associations between processed meat and breast cancer risk. We further assessed its interaction with alcohol intake and polygenic risk score (PRS) for breast cancer.ResultsProcessed meat intake more than once a week was positively associated with risk of breast cancer, especially in women took alcohol ≥1/d (HR=1.50, 95% CI=1.17-1.93), and in women who usually took alcohol together with meals (HR=1.70, 95% CI=1.21-2.39, P for interaction=0.048). The association between processed meat and breast cancer did not differ by menopausal status. When further stratified by PRS, processed meat more than once a week intake was associated with risk of breast cancer (HR=1.17, 95% CI=1.02-1.35) in women with the highest quantile of PRS, and additive interaction was found between them.ConclusionsProcessed meat was associated with risk of breast cancer in women, and the effect was stronger in those who took alcohol together with the meal and with high PRS of breast cancer, suggesting the focus of future preventive measures on these women.FundingThis work was supported by the Natural Science Foundation of Fujian Province [grant no: 2021J01721], the Startup Fund for High-level Talents of Fujian Medical University [grant no: XRCZX2020007], Startup Fund for Scientific Research, Fujian Medical University [grant no: 2019QH1002] and Laboratory Construction Program of Fujian Medical University [grant no: 1100160208].
Automated severe aortic stenosis detection on single-view echocardiography: A multi-center deep learning study
Authors: Holste Gregory , Oikonomou Evangelos K. , Mortazavi Bobak J. , Coppi Andreas , Faridi Kamil F. , Miller Edward J. , Forrest John K. , McNamara Robert L. , Ohno-Machado Lucila , Yuan Neal , Gupta Aakriti , Ouyang David , Krumholz Harlan M. , Wang Zhangyang , Khera Rohan 
Published: August 2022

ABSTRACTBackground and AimsEarly diagnosis of aortic stenosis (AS) is critical to prevent morbidity and mortality but requires skilled examination with Doppler imaging. This study reports the development and validation of a novel deep learning model that relies on 2-dimensional parasternal long axis (PLAX) videos from transthoracic echocardiography (TTE) without Doppler imaging to identify severe AS, suitable for point-of-care ultrasonography.MethodsIn a training set of 5,257 studies (17,570 videos) from 2016-2020 (Yale-New Haven Hospital [YNHH], Connecticut), an ensemble of 3-dimensional convolutional neural networks was developed to detect severe AS, leveraging self-supervised contrastive pretraining for label-efficient model development. This deep learning model was validated in a temporally distinct set of 2,040 consecutive studies from 2021 from YNHH as well as two geographically distinct cohorts of 5,572 and 865 studies, from California and other hospitals in New England, respectively.ResultsThe deep learning model achieved an AUROC of 0.978 (95% CI: 0.966, 0.988) for detecting severe AS with 95.4% specificity and 90% sensitivity in the temporally distinct test set, maintaining its diagnostic performance in both geographically distinct cohorts (AUROC 0.972 [95% CI: 0.969, 0.975] in California and 0.915 [95% CI: 0.896, 0.933] in New England, respectively). The model was interpretable with saliency maps identifying the aortic valve as the predictive region. Among non-severe AS cases, predicted probabilities were associated with worse quantitative metrics of AS suggesting association with various stages of AS severity.ConclusionsThis study developed and externally validated an automated approach for severe AS detection using single-view 2D echocardiography, with implications for point-of-care screening.STRUCTURED GRAPHICAL ABSTRACTKey QuestionIs it feasible to automatically screen for the presence of severe aortic stenosis (AS) using single-view echocardiographic videos without the use of Doppler imaging?Key FindingUsing self-supervised pretraining and ensemble learning, we trained a deep learning model to detect severe AS using single-view echocardiography without Doppler imaging. The model maintained its high performance in multiple geographically and temporally distinct cohorts.Take-home MessageWe present an automated method to detect severe AS using single-view TTE videos, with implications for point-of-care ultrasound screening as part of routine clinic visits and in limited resource settings by individuals with minimal training.An automated deep learning approach for severe aortic stenosis detection from single-view echocardiography evaluated across geographically and temporally distinct cohorts.
On multistability and constitutive relations of motion of MDA-MB-231 cells on Fibronectin lanes
Authors: Amiri Behnam , Heyn Johannes C.J. , Schreiber Christoph , Rädler Joachim O. , Falcke Martin 
Published: August 2022

AbstractCell motility on flat substrates exhibits multistability between steady and oscillatory morphodynamics, spread and moving states, the biphasic adhesion-velocity relation, and the universal correlation between speed and persistence (UCSP) as simultaneously observed phenomena. Their universality and concurrency suggest a unifying mechanism to exist causing all of them. We search for that mechanism by investigating trajectories of MDA-MB-231 cells on Fibronectin lanes. We also find multistability caused by the clutch mechanism of retrograde flow. Control of the clutch parameters by integrin signalling causes the biphasic adhesion-velocity relation. Protrusion competition based on the clutch causes direction reversal events, the statistics of which explains the UCSP. We suggest that F-actin polymerisation, clutch mechanism of retrograde flow, protrusion competition via membrane tension and drag forces cause the multistability and dynamic cell states, state transition statistics causes the UCSP and the control of this dynamic system by integrin signalling entails the adhesion-velocity relation.
Automated assembly of molecular mechanisms at scale from text mining and curated databases
Authors: Bachman John A. , Gyori Benjamin M. , Sorger Peter K. 
Published: August 2022

ABSTRACTThe analysis of ‘omic data depends heavily on machine-readable information about protein interactions, modifications, and activities. Key resources include protein interaction networks, databases of post-translational modifications, and curated models of gene and protein function. Software systems that read primary literature can potentially extend and update such resources while reducing the burden on human curators, but machine-reading software systems have a high error rate. Here we describe an approach to precisely assemble molecular mechanisms at scale using natural language processing systems and the Integrated Network and Dynamical Reasoning Assembler (INDRA). INDRA identifies overlaps and redundancies in information extracted from published papers and pathway databases and uses probability models to reduce machine reading errors. INDRA enables the automated creation of high-quality, non-redundant corpora for use in data analysis and causal modeling. We demonstrate the use of INDRA in extending protein-protein interaction databases and explaining co-dependencies in the Cancer Dependency Map.
The Solvation of the E. coli CheY Phosphorylation Site Mapped by XFMS
Authors: Hamid Maham , Khalid Muhammad Farhan , Chaudhary Safee Ullah , Khan Shahid 
Published: August 2022

AbstractThe Escherichia coli CheY protein belongs to a large bacterial response regulator superfamily. X-ray hydroxy radical foot-printing with mass spectroscopy (XFMS) has shown that allosteric activation of CheY by its motor target triggers a concerted internalization of aromatic sidechains. We reanalyzed the XFMS data to compare polar versus non-polar CheY residue positions. The polar residues around and including the 57D phosphorylated site had an elevated hydroxy radical reactivity. Bioinformatic measures revealed that a water-mediated hydrogen bond network connected this ring of residues with the central 57D. These residues solvated 57D to energetically stabilize the apo-CheY fold. The abundance of these reactive residues was reduced upon activation. This result was supported by the bioinformatics and consistent with the previously reported activation-induced increase in core hydrophobicity. It further illustrated XFMS detection of structural waters. Direct contacts between the ring residues and the phosphorylation site would stabilize the aspartyl phosphate. In addition, we report that the ring residue, 18R, is a constant central node in the 57D solvation network and that 18R non-polar substitutions determine CheY diversity as assessed by its evolutionary trace in bacteria with well-studied chemotaxis. These results showcase the importance of structured water dynamics for phosphorylation-mediated signal transduction.
Immunopeptidomics reveals determinants of Mycobacterium tuberculosis antigen presentation on MHC class I
Authors: Leddy Owen , White Forest M. , Bryson Bryan D. 
Published: August 2022

AbstractCD8+ T cell recognition of Mycobacterium tuberculosis (Mtb)-specific peptides presented on major histocompatibility complex class I (MHC-I) contributes to immunity to tuberculosis (TB), but the principles that govern presentation of Mtb antigens on MHC-I are incompletely understood. In this study, mass spectrometry (MS) analysis of the MHC-I repertoire of Mtb-infected primary human macrophages reveals that substrates of Mtb’s type VII secretion systems (T7SS) are overrepresented among Mtb-derived peptides presented on MHC-I. Quantitative, targeted MS shows that ESX-1 activity contributes to presentation of Mtb antigens on MHC-I, consistent with a model in which Mtb T7SS substrates access a cytosolic antigen processing pathway via ESX-1-mediated phagosome permeabilization.Chemical inhibition of proteasome activity, lysosomal acidification, or cysteine cathepsin activity did not block presentation of Mtb antigens on MHC-I, suggesting involvement of other proteolytic pathways or redundancy among multiple pathways. Our study identifies Mtb antigens presented on MHC-I that could serve as targets for TB vaccines, and reveals an important role for T7SS activity in presentation of Mtb antigens on MHC-I.
BindingSiteAugmentedDTA: Enabling A Next-Generation Pipeline for Interpretable Prediction Models in Drug-Repurposing
Authors: Yousefi Niloofar , Yazdani-Jahromi Mehdi , Tayebi Aida , Kolanthai Elayaraja , Neal Craig J. , Banerjee Tanumoy , Gosai Agnivo , Balasubramanian Ganesh , Seal Sudipta , Garibay Ozlem Ozmen 
Published: August 2022

AbstractWhile research into Drug-Target Interaction (DTI) prediction is fairly mature, generalizability and interpretability are not always addressed in the existing works in this field. In this paper, we propose a deep learning-based framework, called BindingSite-AugmentedDTA, which improves Drug-Target Affinity (DTA) predictions by reducing the search space of potential binding sites of the protein, thus making the binding affinity prediction more efficient and accurate. Our BindingSite-AugmentedDTA is highly generalizable as it can be integrated with any DL-based regression model, while it significantly improves their prediction performance. Also, unlike many existing models, our model is highly interpretable due to its architecture and self-attention mechanism, which can provide a deeper understanding of its underlying prediction mechanism by mapping attention weights back to protein binding sites. The computational results confirm that our framework can enhance the prediction performance of seven state-of-the-art DTA prediction algorithms in terms of 4 widely used evaluation metrics, including Concordance Index (CI), Mean Squared Error (MSE), modified squared correlation coefficient , and the Area Under the Precision Curve (AUPC). We also contribute to the two most commonly used DTA benchmark datasets, namely Kiba and Davis, by including additional information on 3D structure of all proteins contained in these two datasets. We manually extracted this information from Protein Data Bank (PDB) files of proteins available at https://www.uniprot.org/. Furthermore, we experimentally validate the practical potential of our proposed framework through in-lab experiments. We measure the binding interaction between several drug candidate compounds for the inhibition of binding between (SARS-CoV-2 S-protein RBD) Spike and ACE-2 (host cell binding target) proteins. We then compare the computationally-predicted results against the ones experimentally-observed in the laboratory. The relatively high agreement between computationally-predicted and experimentally-observed binding interactions supports the potential of our framework as the next-generation pipeline for prediction models in drug repurposing.
Uracil-DNA glycosylase efficiency is modulated by substrate rigidity
Authors: Orndorff Paul B. , Poddar Souvik , Owens Aerial M. , Kumari Nikita , Ugaz Bryan T. , Amin Samrat , Van Horn Wade D. , van der Vaart Arjan , Levitus Marcia 
Published: August 2022

ABSTRACTUracil DNA-glycosylase (UNG) is a base excision repair enzyme that removes the highly mutagenic uracil lesion from DNA by a base flipping mechanism. UNG excision efficiency depends on DNA sequence, yet the underlying principles that dictate UNG substrate specificity have remained elusive. Here, we show that UNG efficiency is dictated by the intrinsic local deformability of the substrate sequence around the uracil. UNG specificity constants (kcat/KM) and DNA flexibilities were measured for an engineered set of DNA substrates containing AUT, TUA, AUA, and TUA motifs. Time-resolved fluorescence spectroscopy, NMR imino proton exchange measurements, and molecular dynamics simulations of the bare DNA indicated significant differences in substrate flexibilities. A strong correlation between UNG efficiency and substrate flexibility was observed, with higher kcat/KM values measured for more flexible strands. DNA bending and base flipping were observed in simulations, with more frequent uracil flipping observed for the more bendable sequences. Experiments show that bases immediately adjacent to the uracil are allosterically coupled and have the greatest impact on substrate flexibility and resultant UNG activity. The finding that substrate flexibility controls UNG efficiency has implications in diverse fields, including the genesis of mutation hotspots, molecular evolution, and understanding sequence preferences of emerging base editors.
Myo1f has an essential role in γδT intraepithelial lymphocyte adhesion and migration
Authors: Martínez-Vargas Irving Ulises , Sánchez-Bello Maria Elena , Miguel-Rodríguez Carlos Emilio , Hernández-Cázares Felipe , Santos-Argumedo Leopoldo , Talamás Rohana Patricia 
Published: August 2022

ABSTRACTγδT intraepithelial lymphocyte represents up to 60% of the small intestine intraepithelial compartment. They are highly migrating cells and constantly interact with the epithelial cell layer and lamina propria cells. This migratory phenotype is related to the homeostasis of the small intestine, the control of bacterial and parasitic infections, and the epithelial shedding induced by LPS. Here, we demonstrate that Myo1f participates in the adhesion and migration of intraepithelial lymphocytes. Using long-tailed class I myosins KO mice, we identified the requirement of Myo1f for their migration to the small intestine intraepithelial compartment. The absence of Myo1f affects intraepithelial lymphocytes’ homing due to reduced CCR9 and a4b7 expression.In vitro, we confirm that adhesion to integrin ligands and CCL25-dependent and independent migration of intraepithelial lymphocytes are Myo1f-dependent. Mechanistically, Myo1f deficiency prevents correct chemokine receptor and integrin polarization, leading to reduced tyrosine phosphorylation and having consequences in cell signaling. Overall, we demonstrate that Myo1f has an essential role in the adhesion and migration in γδT intraepithelial lymphocytes.SUMMARY STATEMENTThe adhesion and migration of γδT intraepithelial lymphocytes are regulated by the motor protein Myosin 1f through controlling the expression of integrins and the chemokine receptor CCR9.
Reconstituted branched actin networks sense and generate micron-scale membrane curvature
Authors: Baldauf Lucia , Frey Felix , Perez Marcos Arribas , Idema Timon , Koenderink Gijsje H. 
Published: August 2022

ABSTRACTThe actin cortex is a complex cytoskeletal machinery which drives and responds to changes in cell shape. It must generate or adapt to plasma membrane curvature to facilitate diverse functions such as cell division, migration and phagocytosis. Due to the complex molecular makeup of the actin cortex, it remains unclear whether actin networks are inherently able to sense and generate membrane curvature, or whether they rely on their diverse binding partners to accomplish this. Here, we show that curvature sensing and generation is an inherent capability of branched actin networks nucleated by Arp2/3 and VCA. We develop a robust method to encapsulate actin inside giant unilamellar vesicles (GUVs) and assemble an actin cortex at the inner surface of the GUV membrane. We show that actin forms a uniform and thin cortical layer when present at high concentration and distinct patches that generate negative membrane curvature at low concentration. Serendipitously, we find that the GUV production method also produces dumbbell-shaped GUVs, which we explain using mathematical modelling in terms of membrane hemifusion of nested GUVs. We find that dendritic actin networks preferentially assemble at the neck of the dumbbells, which possess a micron-range convex curvature that matches the curvature generated by actin patches in spherical GUVs. Minimal dendritic actin networks can thus both generate and sense membrane curvatures, which may help mammalian cells to robustly recruit actin to curved membranes in order to facilitate diverse cellular functions such as cytokinesis and migration.SIGNIFICANCEAnimal cells move, deform and divide using their actin cortex, a thin layer of filamentous proteins that supports the plasma membrane. For these actions, actin must often assemble at curved sections of the membrane, which is widely believed to require the action of dedicated actin- or membrane-bending proteins. Here, we use a bottom-up reconstitution approach to ask whether actin networks are intrinsically able to generate and sense membrane curvature. We show that membrane-nucleated actin cortices can indeed preferentially self-assemble at concave membranes generated by hemifusion of lipid vesicles. This raises intriguing questions about how such curvature recognition works, and whether cells exploit this intrinsic capability of branched actin networks to concentrate actin in specific cortical regions.
Developing a firewater deluge monitoring and forecasting system based on GA-ARMA model
Authors: Xu Feixiang , Qu Ruoyuan , Zhou Chen 
Published: August 2022

Purpose
The firewater deluge system (FDS) can provide water automatically through a deluge valve when a fire breaks out. However, there are many fire hazards caused by the abnormal operating state of the FDS. To monitor and predict the working state of the FDS, this paper aims to propose a firewater deluge monitoring and forecasting system using the Internet of Things (IoT) technology.

Design/methodology/approach
The firewater deluge monitoring and forecasting system consists of three layers: the sensing layer, network layer and application layer. The firewater pressure obtained by the monitoring nodes was transmitted to the local gateway and then to the remote monitoring center. In the application layer, an autoregressive moving average (ARMA) model was put forward to forecast the firewater pressure. Furthermore, a genetic algorithm (GA) was proposed to perfect the order determination method of the ARMA model. Finally, a Web application was developed to display the real time and predicted working status of the FDS.

Findings
The predicted results show that the ARMA model improved by the GA (GA-ARMA) is significantly better than traditional ARMA models in terms of mean relative error, mean absolute error and mean square error. Moreover, the proposed system is demonstrated to be effective, and an early warning can be alerted to remind users of repairing abnormal FDS equipment ahead of fire dangers.

Originality/value
The proposed system cannot only be applied to the FDS of all buildings to avoid fire hazards by monitoring and predicting the working state of the FDS, but can also be widely used in other fields, such as environmental monitoring, intelligent logistics and intelligent transportation.
Attending live music events with a visual impairment: experiences, accessibility and recommendations for the future
Authors: Castle Claire Louise , Burland Karen , Greasley Alinka 
Published: August 2022

PurposeThe current article focuses on the experiences of live music event attendees with visual impairment (VI). It outlines the factors which impact on the accessibility of events and considers how accessibility might be improved for these individuals.Design/methodology/approachThe article reports on findings from a mixed-methods project utilising a structured interview study (N = 20) and an online survey (N = 94). Interview data were analysed using Interpretative Phenomenological Analysis, providing in-depth insight into participants’ experiences before and during events. Quantitative survey data were analysed descriptively and statistically, and Thematic Analysis of open-ended responses was carried out.FindingsAttendance at live events varied amongst participants, and so too did the factors impacting on their attendance. Challenges were identified in relation to several key areas: accessing information and tickets, experiences with staff, navigation and orientation, and the use and availability of disabled facilities and specialist services.Originality/valueThis article is the first to offer in-depth exploration of music event accessibility for individuals with VI. It builds on existing research which has considered the experiences of deaf and disabled attendees but has not yet offered adequate representation of individuals with VI. The article offers practical recommendations for venues and organisers seeking to ensure accessible events for all and contributes to the wider discourse surrounding inclusivity at music, arts and cultural events.