bluuebunny/crossref_metadata_2025_split huggingface dataset:
Allosteric Residue Dynamics in Insulin: Temperature Induces Shift from Dihexamer to Hexamer Collective Motion
Authors: Ayan Esra , Kepceoglu Abdullah 
Published: January 2025

AbstractStructures using X-ray diffraction data collected to 2.3 Å, 2.85 Å, and 2.88 Å resolutions have been determined for the long-acting dihexamer insulin at three different temperatures ranging from 100°K to 300°K. It is determined that the unit-cell value of insulin crystal at 100°K temperature has changed at 200°K temperature. This change might be due primarily to subtle repacking of the molecule and loss of noncovalent interactions of myristic acid that binds two hexamers, exhibiting the largest movements. Computational analyses show that allosteric residues and fatty-acid binding residue of insulin hexamers display reduced overall collectivity and inter-residue coupling, likely arising from crystal mosaicity increase and structural fluctuations through elevated thermal motion. This breakpoint has been observed at a characteristic temperature of 200°K, perhaps emphasizing underlying alterations in the dynamic structure of the fatty acid-solvent interface in dimer of hexamer. Combined with computational analysis, findings reveal key insights into thermal stability mechanisms crucial for developing thermostable insulin formulations in industrial applications.TeaserTemperature-driven shifts in insulin’s structure reveal dynamic changes crucial for enhancing thermal stability in drug formulations.
DeepPROTECTNeo: A Deep learning-based Personalized and RV-guided Optimization tool for TCR Epitope interaction using Context-aware Transformers
Authors: Das Debraj , Bhaduri Soumyadeep , Pramanick Avik , Mitra Pralay 
Published: January 2025

AbstractThe development of personalized cancer vaccines relies heavily on accurately identifying neoepitopes capable of eliciting strong immune responses. Traditional methods primarily focus on predicting interactions between major histocompatibility complex (MHC) molecules and peptides, often neglecting the crucial step of T-cell receptor (TCR) binding in the context of anchor motif and hydrophobicity, which are critical variables in the elicitation of robust tumor-specific responses. T cells perpetually monitor lymphoid and peripheral organs for antigens, such as peptides or lipids, that are presented by peptide-MHC (pMHC) molecules in other cells. This oversight limits the efficacy of these vaccines in triggering a robust adaptive immune response. We introduce a stand-alone web-server DeepPROTECTNeo (https://cosmos.iitkgp.ac.in/DeepPROTECTNeo/) that processes Whole Exome Sequencing (WES) or Whole Genome Sequencing (WGS) data and mitigate the process of extracting patient-specific neoantigen candidate leveraging genomic and variational TCR information directly, a pivotal component in the development of adaptive immunity and personalized cancer vaccines. Along with traditional MHC binding and B-cell receptor (BCR) recognition, we introduce a context-aware transformer block leveraging cross-attention mechanisms to enhance the analysis of TCR-epitope interactions, thereby advancing neoepitope discovery with unparalleled precision and facilitating reverse vaccinology (RV)-guided multi-epitope vaccine design. With extensive hyperparameter tuning, our model shows exceptional generalizability in predicting TCR-peptide binding on independent test data with AUC 0.7234 and AUPRC 0.7659, substantially outperforming state-of-the-art methods. Furthermore, our pipeline successfully identified 372 neoepitopes out of 532 unique neoepitopes presented in the TESLA benchmark dataset, with 24 true neoantigens, demonstrating its high efficacy and precision in neoepitope discovery.HighlightsDeepPROTECTNeo is an all-in-one platform for neo-epitope identification from raw sequencing readsIncorporate a novel transformer-based architecture for peptide-TCR binding affinity prediction and outperforming current methodsAccepts flexible input formats from users to provide comprehensive analysis and has a separate module for predicting peptide-TCR bindingSuccessfully identified 24 true neoepitopes among 37 reported in TESLA using only SNVs, indels
BICD2 is a centriolar protein that controls mother-daughter centriole engagement and the licensing of duplication
Authors: Montes-Ruiz Lídia , Gallisà-Suñé Núria , Regué Laura , Fernández-de-Larrea Lorena , Roig Joan 
Published: January 2025

AbstractCentrosomes and the centrioles at their core have key cellular roles that require their duplication exactly once during each cell cycle. Abnormal centriole numbers can contribute to the onset of different pathologies and thus different mechanisms have evolved to tightly control centriole duplication. Importantly, centriole pairs are barred from duplicating until they go through a not completely understood process of licensing that includes the physical separation of older (mother) and younger (daughter) centrioles. Here we report that the dynein adaptor BICD2 is a centriolar protein with a previously unknown dynein-independent role controlling mother-daughter centriole engagement. We show that a pool of BICD2 resides at the centrosome, surrounding mother centrioles close to the daughter centriole. Removal of BICD2 results in premature centriole disengagement in G2 and early M and in centriole amplification in both non-transformed and transformed cells. We characterize the molecular determinants of BICD2 centriolar localization and suggest that this localization, and thus the role of BICD2 at the centriole, is controlled by phosphorylation. Our findings reveal a novel function of BICD2, independent of its ability to interact with dynein, which is crucial for the regulation of centriole licensing and the centrosome duplication cycle.
Studies of all-transretinoic acid transport in myopigenesis
Authors: Chatterjee Saptarshi , Roy Ankana , Yu Jianshi , Read A. Thomas , Bentley-Ford Melissa R , Pardue Machelle T. , Kane Maureen A. , Finn M. G. , Ethier C. Ross 
Published: January 2025

AbstractPurposeMyopia incidence is increasing globally. All-transretinoic acid (atRA) is important in myopigenic retinoscleral signaling, motivating research on its ocular transport. However, atRA’s weak autofluorescence limits its direct visualization in tissues. Further, atRA is hydrophobic and must bind to protein carriers for transport. We assessed a fluorescent analog of atRA (LightOxTM14, CAS:198696-03-6, referred as ‘floRA’), as an experimentally accessible atRA surrogate by: (i) evaluating its binding to carrier proteins and (ii) visualizing its distribution in ocular tissues.MethodsBindingWe assessed atRA-carrier protein binding using fluorescence quenching assays with bovine serum albumin (BSA), high density lipoprotein (HDL), apolipoprotein A-I (Apo A-I) and retinol binding protein 4 (RBP4).Direct visualizationWild-type C57BL/6J mice were euthanized, eyes enucleated, and wedges containing sclera and choroid incubated for specific durations in 50 μM floRA+BSA. The wedge centers were cryo-sectioned and counterstained for nuclei. Fluorescent micrographs were acquired and analyzed using ImageJ.ResultsAssociation constants (Ka) for atRA and floRA binding to carrier proteins were similar and ranged from 2-13 × 105M-1, indicating non-specific binding. floRA could be visualized in sclera and choroid, yet showed significant spatial heterogeneity (enhanced fluorescence often colocalizing with nuclei).ConclusionsfloRA is a reasonable surrogate for atRA binding to BSA, HDL, Apo A-I and RBP4. Considering these proteins’ relative serum and extravascular abundances, and their similar binding affinity to atRA, we predict that serum albumin is an important atRA carrier. Use of floRA in whole tissue tracer studies shows promise but requires further refinement.
Impact of bystander intervention on clinical outcome in out-of-hospital cardiac arrest. A study of 8,253 Polish cases from the European Registry of Cardiac Arrest (2014-2022)
Authors: Żądło Anna , Wilczek Dawid , Cebula Grzegorz , Orzechowska Daria , Tokarek Tomasz 
Published: January 2025

AbstractBackgroundOut-of-Hospital Cardiac Arrest (OCHA) remains a significant challenge for healthcare systems, with actions by witnesses playing a critical role. This study examines Polish data from the European Registry of Cardiac Arrest (EuReCa), identifying progress in updated paramedic protocols and public availability of automated external defibrillators (AED) while noting issues such as delays in emergency call localization, lack of synchronization in defibrillator maps, inadequate reporting, and absence of information on long-term neurological outcomes.AimsThe aim of this study was to assess the role of bystanders and dispatchers in the chain of survival for OHCA.MethodsA retrospective analysis was conducted on 8,253 patients included in the EuReCa between 2014 and 2022. Data were collected from emergency medical team reports, and survival outcomes at 30 days were obtained from the national death registry.ResultsFull cardiopulmonary resuscitation (CPR) performed by witnesses, including both chest compressions and rescue breaths, combined with the use of AED, significantly increased the likelihood of return of spontaneous circulation (ROSC) compared to chest compressions alone or no intervention. Dispatcher-guided resuscitation increased ROSC from 22.1% to 30.6% (p=0.01), though the increase in 30-day survival from 42.8% to 48.2% was not statistically significant (p=0.27). CPR by witnesses increased the number of patients transported to hospital with ROSC(74.0% vs. 26.0%; p=0.01).ConclusionsBystanders and dispatchers are pivotal in the chain of survival. Improving the quality of reporting on actions taken by witnesses, including dispatcher-assisted resuscitation and the use of automated defibrillators, is critical for identifying effective strategies and allocating resources to improve survival and outcomes for cardiac arrest outside hospitals in Poland.
NfκBin: A Machine Learning based Method for Screening Nf-κB Inhibitors
Authors: Jain Shipra , Tomer Ritu , Patiyal Sumeet , Raghava Gajendra P. S. 
Published: January 2025

AbstractNuclear Factor kappa B (NF-κB) is a transcription factor whose upregulation is associated in chronic inflammatory diseases, including rheumatoid arthritis, inflammatory bowel disease, and asthma. In order to develop therapeutic strategies targeting NF-κB-related diseases, we developed a computational approach to predict drugs capable of inhibiting NF-κB signaling pathways. In this study, we utilized a dataset comprising 1,149 inhibitors and 1,332 non-inhibitors retrieved from PubChem. Chemical descriptors were computed using the PaDEL software, and relevant features were selected using advanced feature selection techniques. Initially, machine learning models were constructed using 2D descriptors, 3D descriptors, and molecular fingerprints, achieving maximum AUC values of 0.66, 0.56, and 0.66, respectively. To improve feature selection, we applied univariate analysis and SVC-L1 regularization to identify features that can effectively differentiate inhibitors from non-inhibitors. Using these selected features, we developed machine learning models, our support vector classifier achieved an AUC of 0.75 on the validation dataset. All models were trained using five-fold cross-validation and rigorously evaluated on an independent validation dataset, which was not used during training or hyperparameter optimization. Finally, our best-performing model was employed to screen FDA-approved drugs for potential NF-κB inhibitors. Notably, most of the predicted inhibitors corresponded to drugs previously identified as inhibitors in experimental studies, underscoring the model’s predictive reliability. Our best- performing models have been integrated into a standalone software and web server, NfκBin, to enable the scientific community to perform high-throughput screening of Nf-κB inhibitors from chemical libraries. (https://webs.iiitd.edu.in/raghava/nfkbin/).Highlights1)Inhibitors of Nf-κB can be used to manage disease like rheumatoid arthritis, asthma.2)A novel tool NfκBin developed for screening Nf-κB inhibitors from chemical library.3)Cutting-edge feature selection techniques used to identify the most relevant chemical descriptors.4)Models were developed and validated on a robust dataset of inhibitors and non-inhibitors.5)Integrated best-performing models into the NfκBin software and web server.
Discovery of Expression-Governing Residues in Proteins
Authors: Jiang Fan , Li Mingchen , Wu Banghao , Zhang Liang , Zhong Bozitao , Yu Yuanxi , Hong Liang 
Published: January 2025

AbstractUnderstanding how amino acids influence protein expression is crucial for advancements in biotechnology and synthetic biology. In this study, we introduce Venus-TIGER, a deep learning model designed to accurately identify amino acids critical for expression. By constructing a two-dimensional matrix that links model representations to experimental fitness, Venus-TIGER achieves improved predictive accuracy and enhanced extrapolation capability. We validated our approach on both public deep mutational scanning datasets and low-throughput experimental datasets, demonstrating notable performance compared to traditional methods. Venus-TIGER exhibits robust trans-ferability in zero-shot predicting scenarios and enhanced predictive performance in few-shot learning, even with limited experimental data. This capability is particularly valuable for protein design aimed at enhancing expression, where generating large datasets can be costly and time-consuming. Additionally, we conducted a statistical analysis to identify expression-associated features, such as sequence and structural preferences, distinguishing between those linked to high and low expression. Our investigation also revealed a correlation among stability, activity and expression, providing insight into their interconnected roles and underlying mechanisms.
Improving MALDI Mass Spectrometry Imaging Performance: Low-Temperature Thermal Evaporation for Controlled Matrix Deposition and Improved Image Quality
Authors: Mahamdi Toufik , Serna Cristina Gomez , Giné Roger , Rofes Jordi , Mohammed Shad Arif , Ràfols Pere , Correig Xavier , García-Altares María , Hopf Carsten , Iakab Stefania-Alexandra , Yanes Oscar 
Published: January 2025

AbstractThe deposition of matrix compounds significantly influences the effectiveness of matrix-assisted laser desorption/ionization (MALDI) Mass Spectrometry Imaging (MSI) experiments, impacting sensitivity, spatial resolution, and reproducibility. Dry deposition methods offer advantages by producing homogeneous matrix layers and minimizing analyte delocalization without the use of solvents. However, refining these techniques to precisely control matrix thickness, minimize heating temperatures, and ensure high-purity matrix layers is crucial for optimizing MALDI-MSI performance. Here, we present a novel approach utilizing low-temperature thermal evaporation (LTE) for organic matrix deposition under reduced vacuum pressure. Our method allows for reproducible control of matrix layer thickness, as demonstrated by linear calibration for two organic matrices, 2,5-dihydroxybenzoic acid (DHB), and 1,5-Diaminonaphthalene (DAN). The environmental scanning electron microscopy images reveal a uniform distribution of small-sized matrix crystals, consistently on the submicrometer scale, across tissue slides following LTE deposition. Remarkably, LTE serves as an additional purification step for organic matrices, producing very pure layers irrespective of initial matrix purity. Furthermore, stability assessment of MALDI-MSI data from mouse brain sections coated with LTE-deposited DHB or DAN matrix indicates minimal impact on ionization efficiency, signal intensity, and image quality even after storage at - 80°C for two weeks, underscoring the robustness of LTE-deposited matrices for MSI applications. Comparative analysis with the spray-coating method highlights several advantages of LTE deposition, including enhanced ionization, reduced analyte diffusion, and improved MSI image quality.
An algorithm for the transformation of the Petri net models of biological signaling networks into influence graphs
Authors: Gamache-Poirier Simon , Souvane Alexia , Leclerc William , Villeneuve Catherine , Hardy Simon V. 
Published: January 2025

AbstractA common depiction for biological signaling networks is the influence graph in which the activation and inhibition effects between molecular species are shown with vertices and arcs connecting them. Another formalism for reaction-based models is the Petri nets which has a graphical representation and a mathematical notation that enables structural analysis and quantitative simulation. In this paper, we present an algorithm based on Petri nets topological features for the transformation of the computational model of a biological signaling network into an annotated influence graph. We also show the transformation of the Petri nets model of the beta-adrenergic receptor activating the PKA-MAPK signaling network into its representation as an influence graph.
Chemokine induces phase transition from non-directional to directional migration during angiogenesis
Authors: Gui Ning , Sako Keisuke , Fukumoto Moe , Mochizuki Naoki , Nakajima Hiroyuki 
Published: January 2025

AbstractDuring angiogenesis, sprouting endothelial cells (ECs) migrate and eventually connect to target vessels to form new vessel branches. However, it remains unclear how these sprouting vessels migrate toward the target vessels in three-dimensional space. We performedin vivoimaging of the cerebral capillary network formation in zebrafish to investigate how sprouting tip cells migrate toward their targets. Of note, we found that tip cells reach the target vessels through two phases: a non-directional phase and a directional phase. In the non-directional phase, sprouting tip cells dynamically extend and retract their protrusions at the leading front and have less directionality in their movement. In contrast, once tip cells enter the directional phase, they migrate directly toward the anastomotic targets. Chemokine receptor Cxcr4a and its ligand Cxcl12b are important for the phase transition to the directional phase. Incxcr4amutants, sprouting tip cells lose their directionality and tend to connect to nearby sprouting ECs, resulting in altered capillary network patterning. Furthermore, in wild-type (WT) larvae, local Ca2+oscillations were detected in protrusions of tip cells, specifically in the non-directional phase, but almost disappeared in the directional phase as a result of the Cxcr4-dependent phase transition. Thus, this study provides evidence of a chemokine-induced phase transition in migrating tip cells, which is important for proper vascular network formation in the zebrafish brain.
The Inflation Reduction Act’s Impact upon Early-stage Venture Capital Investments
Authors: Schulthess Duane G. , O’Loughlin Gwen , Askeland Madeline , Gassull Daniel , Bowen Harry P. 
Published: January 2025

AbstractBackgroundThe Congressional Budget Office has stated there is no evidence of a systematic decrease in the percentage of venture capital flowing to pharmaceutical companies since IRA’s passage. This was echoed in Prof. Rita Conti’s September 17, 2024, Senate Finance Committee testimony.MethodsTo test the IRA’s impacts on early-stage investments targeting therapeutics for the Medicare-aged population, a longitudinal dataset of commercially sponsored clinical trials by companies with a market valuation < $2 billion was obtained from the BioMedTracker database from January 1, 2018, to May 6, 2024. These trials were filtered to match early-stage investments to lead assets undergoing clinical development.ResultsFrom 161 lead assets with 897 investments, we find the aggregated total into large molecules in 2024 was 10 times larger than that for small molecules, which underwent a 70% decline after passage of the IRA. Individual investments made into small molecules decline by minus one-half as exposure to the Medicare-aged population increases after the passage of the IRA (p < 0.0018). Testing large molecule investments by their exposure to Medicare post IRA’s passage is statistically inconclusive.Research ConclusionsThis study presents evidence of a decline in the development of new therapies targeting the Medicare-aged population since the passage of the IRA. If these impacts were due to the economic downturn post-pandemic, we would observe statistically similar results in both large and small molecules. However, the results by molecule type diverge. Investors perceive large molecules to be of a lower investment risk relative to small molecules after IRA’s passage.
Clinical Development and Performance of the First To Know Syphilis Self-Test for Over-the-Counter Usage: a De Novo Rapid Test for Treponemal Antibody
Authors: Clark Kevin , Rabine Sharon , Qian Jianghong , Biddison Diane , Spradlin Sydney , Thompson Vicki , Shi Qinwei , Xu Jing , Pillai Raji , Zhang Lu , Brown Alicia , Nibauer Lisa , Joyee Antony George , Berry Jody D. 
Published: January 2025

ABSTRACTThe resurgence of syphilis in the USA and globally has hastened the need for widely available syphilis testing. Early detection of syphilis is crucial for avoiding serious clinical complications and preventing spread of infection. Self-tests enhance access to testing and promote timely treatment for positive cases. Herein we describe the performance of First to Know Syphilis Test (FTK), the first over the counter (OTC) treponemal test. A prospective multi-site clinical study with 1270 subjects was conducted, where subjects self-collected fingerstick capillary blood and self-tested without assistance. FTK test results were compared with a composite reference standard to evaluate diagnostic performance. The FTK test exhibited an overall sensitivity of 93.4% (95% CI, 87.0% to 96.8%) and specificity of 99.5% (95% CI, 98.9% - 99.8%) and accuracy of 99%. The overall agreement was 98.9%, with Cohens Kappa (ⱪ) value 0.93 (95% CI, 0.90 to 0.97) showing excellent agreement between the reference standard and FTK results. In addition, the test was validated in a panel of 125 clinically staged syphilis patient samples and the results showed 100% agreement in detecting anti-treponemal antibodies in all the samples. These data show excellent performance of the FTK Test demonstrating its utility in the screening and diagnosis of syphilis. The availability of this OTC test and its excellent performance at low prevalence, will have a profound impact on syphilis detection and prevention strategies and could reduce co morbidities such as HIV and other STI transmission.