bluuebunny/crossref_metadata_2025_split huggingface dataset:
Monitoring the Risk of Type-2 Circulating Vaccine-Derived Poliovirus Emergence during Roll-Out of Type-2 Novel Oral Polio Vaccine
Authors: Peak Corey M. , Lyons Hil , Voorman Arend , Gray Elizabeth J , Cooper Laura V , Blake Isobel M , Hawes Kaija , Bandyopadhyay Ananda S 
Published: October 2024

AbstractBackground/ObjectivesAlthough wild poliovirus type 2 has been eradicated, prolonged transmission of the live-attenuated virus contained in the type-2 oral polio vaccine (OPV2) in under-immunized populations has led to emergence of circulating vaccine derived poliovirus type-2 (cVDPV2). The novel OPV2 (nOPV2) was designed to be more genetically stable and reduce the chance of cVDPV2 emergence while retaining comparable immunogenicity to the Sabin monovalent OPV2 (mOPV2). This study aims to estimate the relative reduction in the emergence risk due to use of nOPV2 instead of mOPV2.MethodsData on OPV2 vaccination campaigns from May 2016 to 1 August 2024 were analyzed to estimate type-2 OPV-induced immunity in children under 5 years of age. Poliovirus surveillance data were used to estimate seeding date and classify cVDPV2 emergences as Sabin- or novel-derived. The expected number of emergences if mOPV2 was used instead of nOPV2 was estimated accounting for the timing and volume of nOPV2 doses, the known emergence risk factors for emergence from mOPV2, and censoring due to the incomplete observation period for more recent nOPV2 doses.ResultsAs of 1 August 2024, over 98% of the approximately 1.19 billion nOPV2 doses administered globally were in Africa. We estimate approximately 76 (95% confidence interval 69-85) index isolates of cVDPV2 emergences would be expected to be detected by 1 August 2024 if mOPV2 had been used instead of nOPV2 in Africa. The 18 observed nOPV2-derived emergences represent a 76% (74%-79%) lower risk of emergence by nOPV2 than mOPV2 in Africa. The crude global analysis produced similar results. Key limitations include the incomplete understanding of the drivers of heterogeneity in emergence risk across geographies and variance in the per-dose risk of emergence may be incompletely captured using known risk factors.ConclusionsThese results are consistent with the accumulating clinical and field evidence showing enhanced genetic stability of nOPV2 relative to mOPV2, and this approach has been implemented in near-real time to contextualize new findings during roll-out of this new vaccine. While nOPV2 has resulted in new emergences of cVDPV2, the number of cVDPV2 emergences is estimated to be approximately four-fold lower than if mOPV2 had been used instead.
DEEP LEARNING BASED DETECTION OF URETHRAL STRICTURE: SEGMENTATION & CLASSIFICATION
Authors: Gurung Nikhil , Udaya Kumar L , Chandrasekar S N , Muthukumar V Sai , Gera Darshan , Sharma Raghunatha , Shekar P Ashwin 
Published: October 2024

AbstractPurposeThe retrograde urethrogram (RUG) has been a key diagnostic tool for over a century, remaining essential despite the availability of other imaging techniques for screening, diagnosis and follow up of Urethral strictures. However, interpretation of RUG images has to be done manually and needs experience on the part of the treating urologist, which calls for a common understanding of RUGs and presents a chance to improve stricture management in a practical way. Artificial intelligence (AI) algorithms present a novel way to prevent human discrepancy while concomitantly improving the accuracy of stricture identification and classification.MethodsDatasetWe have used a balanced dataset which includes RUGs of 168 strictured cases and 178 non-strictured(healthy) cases.Task#1The primary requirement is to identify the Urethral region in any clinically obtained RUGs and detect the presence of stricture in it. We successfully deployed a Segmentation and Classification model to categorize the whole dataset as strictured or non-strictured RUGs.Task#2On obtaining superior accuracy, we effectively went on to identify the type of stricture based on their location, which is of clinical importance.ResultsWith the above-mentioned available RUG dataset from 346 cases, we could train our Deep learning model and achieve a significant accuracy of 91.53% in detection and categorizing the type of stricture. At the end, a 10-fold cross-validation yielded an accuracy of about 86.66%.ConclusionOur attempts have successfully validated that using Deep learning (DL) tools, one could readily (i) Detect the presence of stricture in a given RUG and (ii) ultimately locate and classify these strictures effectively. Thus, these Deep learning tools could be of great clinical assistance for Urinary stricture related disease management.
Alternatives to photorespiration: A systems-level analysis reveals mechanisms of enhanced plant productivity
Authors: Smith Edward N. , van Aalst Marvin , Weber Andreas P.M. , Ebenhöh Oliver , Heinemann Matthias 
Published: October 2024

Photorespiration causes a significant decrease in crop yield due to mitochondrial decarboxylation. Alternative pathways (APs) have been designed to relocate the decarboxylating step or even fix additional carbon. To improve the success of transferring those engineered APs from model species to crops we must understand how they will interact with metabolism and how the plant physiology affects their performance. Here we used multiple mathematical modelling techniques to analyse and compare existing AP designs. We show that carbon-fixing APs are the most promising candidates to replace native photorespiration in major crop species. Our results demonstrate the different metabolic routes that APs employ to increase yield and which plant physiology can profit most from them. We anticipate our results to guide the design of new APs and to help improve existing ones.Codehttps://gitlab.com/gain4crops/2024-paper
Stimulus-dependent delay of perceptual filling-in by microsaccades
Authors: Levinson Max , Pack Christopher C. , Baillet Sylvain 
Published: October 2024

AbstractPerception is a function of both stimulus features and active sensory sampling. The illusion ofperceptual filling-in occurs when eye gaze is kept still: visual boundary perception may fail, causing adjacent visual features to remarkably merge into one uniform visual surface. Microsaccades–small, involuntary eye movements during gaze fixation–counteract perceptual filling-in, but the mechanisms underlying this process are not well understood. We investigated whether microsaccade efficacy for preventing filling-in depends on two boundary properties, color contrast and retinal eccentricity (distance from gaze center). Twenty-one human participants (male and female) fixated on a point until they experienced filling-in between two isoluminant colored surfaces. We found that increased color contrast independently extends the duration before filling-in but does not alter the impact of individual microsaccades. Conversely, lower eccentricity delayed filling-in only by increasing microsaccade efficacy. We propose that microsaccades facilitate stable boundary perception via a transient retinal motion signal that scales with eccentricity but is invariant to boundary contrast. These results shed light on how incessant eye movements integrate with ongoing stimulus processing to stabilize perceptual detail, with implications for visual rehabilitation and the optimization of visual presentations in virtual and augmented reality environments.Significance StatementTo perceive, sense organs actively sample the environment—for example, by touching, sniffing, or moving the eyes. Visual sampling persists even when gaze is fixed on a single point: involuntary microsaccades continuously move the eye in small jumps. We investigated a previously documented observation that microsaccades prevent illusory fading of perceived visual boundaries during fixation. We discovered that despite being connected, microsaccades and fading are sensitive to different stimulus features. Boundaries separating surfaces with more distinct colors inherently took longer to fade. Boundaries closer to the center of vision also took longer to fade, but only because microsaccades were more effective. These findings reveal new insight into how pervasive sensory sampling delivers a stable and detailed perceptual experience.
Pharmacoproteomic profiling identifies secreted markers for aberrant drug action
Authors: Knecht Sascha , Kalxdorf Mathias , Korbeń Johanna , Mathieson Toby , Sevin Daniel C. , Kuster Bernhard , Kasprowicz Richard , Sakatis Melanie Z. , Eberl H. Christian , Bantscheff Marcus 
Published: October 2024

AbstractAdverse drug reactions (ADRs) contribute significantly to late-stage attrition in drug discovery due to their unpredictability and enigmatic underlying mechanisms. Here we applied mass spectrometry-based proteomics to assess the effects of 46 approved or retracted drugs with various levels of concerns for drug-induced liver injury and annotated for mitochondrial mechanisms, along with 8 tool compounds, on the secretome of a hepatocyte liver model. We observed distinct clusters of non-canonical secretion, and intracellular thermal proteome profiling linked dysregulated mechanisms to extracellular markers. Functional follow-up confirmed lysosomal alterations by cationic-amphiphilic drugs, connected damage of the respiratory chain to Rab7-dependent secretion of mitochondrial proteins, and linked drug-induced endoplasmic reticulum stress to reduced basal secretion. Perturbation of sphingolipid biosynthesis pathways specifically induced secretion of the cargo sorting protein SDF4 whilst suppressing secretion of its cargo proteins. Thermal stability changes of clusters of membrane proteins in distinct subcellular compartments suggest local accumulation as important driver for unexpected drug effects through direct and indirect interactions.
Artificial light at night enhances the defensive behavior in aquatic shredders under predation risk
Authors: Rufaida Zahira , Czarnecka Magdalena 
Published: October 2024

AbstractCaddisfly larvae (Trichoptera) are mostly nocturnal aquatic invertebrates that contribute to the decomposition of coarse organic matter, such as plant litter in streams. Artificial light at night (ALAN) can interfere with their behavior, particularly in the presence of predation threat. We investigated the effects of various types of ALAN onLepidostoma hirtum, a common caddisfly species in running waters. We tested its behavior (activity and tendency to shelter) in darkness, as well as under white warm LED light and HPS (sodium lamp) light (2 lux), with and without the presence of predation cues (crushed conspecifics). We found that in darkness caddisflies did not change their behavior in the presence of predation threat. When exposed to ALAN only, caddisflies decreased their activity compared to dark nights, regardless of the type of light. The presence of both predation threat and ALAN enhanced a defensive behavior in caddisflies, especially under LED light. They not only reduced their activity, but also spent more time in shelter, compared to other treatments. This study highlights that impact of ALAN on the behavior of nocturnal aquatic invertebrates may vary depending on the spectral composition of light and may be intensified in the presence of predation threat.
PRMT5-mediated histone methylation regulates alternative splicing via MECP2-PTBP1 to promote EMT in breast cancer hypoxia
Authors: Mutnuru Srinivas Abhishek , Yadav Pooja , Kakani Parik , Dhamdhere Shruti Ganesh , Kumari Poorva , Agarwal Shruti , Samaiya Atul , Shukla Sanjeev 
Published: October 2024

AbstractTumor hypoxia induced alterations in the epigenetic landscape and alternative splicing influence cellular adaptations. PRMT5 is a type II protein arginine methyltransferase that regulates several tumorigenic events in many cancer types. However, the regulation of PRMT5 and its direct implication on aberrant alternative splicing under hypoxia remains unexplored. In this study, we observed hypoxia induced upregulation of PRMT5 via the CCCTC binding factor, CTCF. Further, PRMT5-mediated symmetric arginine dimethylation H4R3me2s and H3R8me2s directly regulated the alternative splicing of Transcription Factor 3 (TCF3). Under hypoxia, PRMT5-mediated histone dimethylation at the intronic conserved region (ICR) present betweenTCF3exon 18a and exon 18b recruits DNA methyltransferase 3A (DNMT3A), resulting in DNA methylation. DNA methylation at theTCF3-ICR is recognized and bound by Methyl CpG binding protein (MECP2) resulting in RNA-Pol II pausing, promoting the recruitment of the negative splicing factor PTBP1 to the splicing locus ofTCF3mRNA. PTBP1 promotes the exclusion of exon 18a which results in the production of the pro-invasive TCF3-18B (E47) isoform which promotes EMT and invasion of breast cancer cells under hypoxia. Collectively, our results indicate PRMT5-mediated symmetric arginine dimethylation of histones regulates alternative splicing ofTCF3gene thereby enhancing EMT and invasion in breast cancer hypoxia.
A thermodynamic bottleneck in the TCA cycle contributes to acetate overflow inStaphylococcus aureus
Authors: Shahreen Nabia , Ahn Jongsam , Alsiyabi Adil , Chowdhury Niaz Bahar , Shinde Dhananjay , Chaudhari Sujata S , Bayles Kenneth W , Thomas Vinai C , Saha Rajib 
Published: October 2024

AbstractDuring aerobic growth,S. aureusrelies on acetate overflow metabolism, a process where glucose is incompletely oxidized to acetate, for its bioenergetic needs. Acetate is not immediately captured as a carbon source and is excreted as waste by cells. The underlying factors governing acetate overflow inS. aureushave not been identified. Here, we show that acetate overflow is favored due to a thermodynamic bottleneck in the TCA cycle, specifically involving the oxidation of succinate to fumarate by succinate dehydrogenase. This bottleneck reduces flux through the TCA cycle, making it more efficient forS. aureusto generate ATP via acetate overflow metabolism. Additionally, the protein allocation cost of maintaining ATP flux through the restricted TCA cycle is greater than that of acetate overflow metabolism. Finally, we show that the TCA cycle bottleneck providesS. aureusthe flexibility to redirect carbon towards maintaining redox balance through lactate overflow when oxygen becomes limiting, albeit at the expense of ATP production through acetate overflow. Overall, our findings suggest that overflow metabolism offersS. aureusdistinct bioenergetic advantages over a thermodynamically constrained TCA cycle, potentially supporting its commensal-pathogen lifestyle.
Unraveling the developmental heterogeneity within the human retina to reconstruct the continuity of retinal ganglion cell maturation and stage-specific intrinsic and extrinsic factors
Authors: Kriukov Emil , Soucy Jonathan R. , Labrecque Everett , Baranov Petr 
Published: October 2024

AbstractTissue development is a complex spatiotemporal process with multiple interdependent components. Anatomical, histological, sequencing, and evolutional strategies can be used to profile and explain tissue development from different perspectives. The introduction of scRNAseq methods and the computational tools allows to deconvolute developmental heterogeneity and draw a decomposed uniform map. In this manuscript, we decomposed the development of a human retina with a focus on the retinal ganglion cells (RGC). To increase the temporal resolution of retinal cell classes maturation state we assumed the working hypothesis that that maturation of retinal ganglion cells is a continuous, non-discrete process. We have assembled the scRNAseq atlas of human fetal retina from fetal week 8 to week 27 and applied the computational methods to unravel maturation heterogeneity into a uniform maturation track. We align RGC transcriptomes in pseudotime to map RGC developmental fate trajectories against the broader timeline of retinal development. Through this analysis, we identified the continuous maturation track of RGC and described the cell-intrinsic (DEGs, maturation gene profiles, regulons, transcriptional motifs) and -extrinsic profiles (neurotrophic receptors across maturation, cell-cell interactions) of different RGC maturation states. We described the genes involved in the retina and RGC maturation, including de novo RGC maturation drivers. We demonstrate the application of the human fetal retina atlas as a reference tool, allowing automated annotation and universal embedding of scRNAseq data. Altogether, our findings deepen the current knowledge of the retina and RGC maturation by bringing in the maturation dimension for the cell class vs. state analysis. We show how the pseudotime application contributes to developmental-oriented analyses, allowing to order the cells by their maturation state. This approach not only improves the downstream computational analysis but also provides a true maturation track transcriptomics profile.
Detection of mesial temporal lobe epilepsy with OP-MEG
Authors: Mellor Stephanie , O’Neill George C. , Bush Daniel , Ramaswamy Arjun , Doig David , Tierney Tim M. , Spedden Meaghan E. , Walker Matthew C. , Barnes Gareth R. , Vivekananda Umesh 
Published: October 2024

AbstractBackground and ObjectivesMagnetoencephalography (MEG) using optically pumped magnetometers (OP-MEG) is a relatively novel neuroimaging modality that holds great clinical promise for presurgical planning in epilepsy. However, there is limited data demonstrating that interictal discharges from deep neural sources can be visually identified and localised using OP-MEG. In this study, we sought to demonstrate the potential of OP-MEG for recording interictal epileptiform activity from patients with mesial temporal lobe epilepsy, the most common focal epilepsy, with a diverse range of aetiologies.MethodsWe recorded whole-head OP-MEG for a minimum of 30 minutes from 8 patients with temporal lobe epilepsies. Patients were seated with their head unconstrained. For comparison, we collected information from previous clinical assessment, including findings from MRI and EEG telemetry.ResultsWe observed interictal epileptiform activity in 4 of the patients, in 3 of which the localisation of the activity was concordant with previous clinical MRI and EEG. In 2 of those patients, we also observed ictal events. Of those 2 patients, one had a clear abnormality in MRI, with which the localisation of this ictal activity was concordant. The other patient’s MRI was negative, but the ictal localisation is consistent with the seizure semiology.DiscussionWe demonstrate that interictal and ictal epileptiform activity from mesial temporal lobe epilepsies can be observed with OP-MEG and localised to the region of the anatomical lesion, identified in MRI. This affirms the utility of OP-MEG for epilepsy surgery planning.
Integrating Functional Protein Drug Target Data into a Precision Oncology Molecular Tumor Board
Authors: Hunt Allison L. , Randall Jamie , Mansukhani Mahesh M. , Nyberg Kara , Nutcharoen Aratara , Davis Justin , Corgiat Brian , Mueller Claudius , Melvin Savannah , Sharma Meenakshi , Johnston Laura , Swain Whitney , Abulez Tamara , Bateman Nicholas W. , Maxwell G. Larry , Deeken John , Benyounes Amin , Petricoin Emanuel F. , Cannon Timothy L. , Conrads Thomas P. 
Published: October 2024

AbstractCollaborative review of molecular profiling data by multidisciplinary molecular tumor boards (MTB) is increasingly important for improving patient management and outcomes, though currently relies nearly exclusively on nucleic acid next-generation sequencing (NGS) and limited panels of immunohistochemistry-based protein abundance data. We examined the feasibility of incorporating real-time laser microdissection (LMD) enrichment of tumor epithelium and commercial CLIA-based reverse phase protein array (RPPA) protein drug target expression/activation profiling into our cancer center’s MTB to complement standard clinical NGS-based profiling. The LMD-RPPA workflow was performed within a therapeutically permissive timeframe with a median dwell time of nine days, during which specimens were processed outside of standard clinical workflows. The RPPA-generated data supported additional and/or alternative therapeutic considerations for 54% of profiled patients following review by the MTB. These findings suggest that integrating proteomic/phosphoproteomic and NGS-based genomic data creates opportunities to further personalize clinical decision-making for precision oncology.
Validation of Machine-Learning Angiography-Derived Physiological Pattern of Coronary Artery Disease
Authors: Zhu Yueyun , Fezzi Simone , Bargary Norma , Ding Daixin , Scarsini Roberto , Lunardi Mattia , Mammone Concetta , Wagener Max , Mcinerney Angela , Toth Gabor , Pesarini Gabriele , Connolly David , Ribichini Flavio , Tu Shengxian , Wijns William , Simpkin Andrew J 
Published: October 2024

ABSTRACTBackgroundThe classification of physiological patterns of coronary artery disease (CAD) is crucial for clinical decision-making, significantly affecting the planning and success of percutaneous coronary interventions (PCI).ObjectivesThis study aimed to develop a novel index to reliably interpret and classify physiological CAD patterns based on virtual pullbacks from single-view Murray’s law-based quantitative flow ratio (μFR) analysis.MethodsThe pullback pressure gradient index (PPGi) was used to classify CAD patterns, with a cut-off value of PPGi=0.78 distinguishing focal from diffuse and non-focal disease. A machine learning method using penalized logistic regression models was proposed to assess CAD patterns. Scores derived from multivariate functional principal component analysis (MFPCA) of μFR and quantitative coronary analysis improved model performance. Expert panel interpretations served as the reference.ResultsA total of 179 vessels (134 patients) underwent classification. The PPGi cut-off of 0.78 achieved 70% accuracy (95% CI: 0.70 to 0.71) for focal vs. diffuse and 77% accuracy (95% CI: 0.76 to 0.77) for focal vs. non-focal classification. The penalized logistic regression model, including PPGi as a feature, provided superior accuracy: 95% (95% CI: 0.94 to 0.95) for focal vs. diffuse and 84% (95% CI: 0.83 to 0.84) for focal vs. non-focal classification. Positive predictive value (PPV) and negative predictive value (NPV) were 95% and 92% (focal vs. diffuse) and 84% each (focal vs. non-focal). Overall, the penalized logistic regression model successfully identified more focal lesions and ensured fewer diffuse or non-focal lesions were misclassified.ConclusionsThe machine learning method with penalized logistic regression outperformed the PPGi cut-off values, providing robust and generalizable classification across different study populations.