bluuebunny/crossref_metadata_2025_split huggingface dataset:
Discovery and Characterization of Brigimadlin, a Novel and Highly Potent MDM2–p53 Antagonist Suitable for Intermittent Dose Schedules
Authors: Gollner Andreas , Rudolph Dorothea , Weyer-Czernilofsky Ulrike , Baumgartinger Rosa , Jung Peter , Weinstabl Harald , Ramharter Jürgen , Grempler Rolf , Quant Jens , Rinnenthal Jörg , Pérez Pitarch Alejandro , Golubovic Bojana , Gerlach Daniel , Bader Gerd , Wetzel Kristiane , Otto Sebastian , Mandl Christian , Boehmelt Guido , McConnell Darryl B. , Kraut Norbert , Sini Patrizia 
Published: September 2024

Abstract
p53 is known as the guardian of the genome and is one of the most important tumor suppressors. It is inactivated in most tumors, either via tumor protein p53 (TP53) gene mutation or copy number amplification of key negative regulators, e.g., mouse double minute 2 (MDM2). Compounds that bind to the MDM2 protein and disrupt its interaction with p53 restore p53 tumor suppressor activity, thereby promoting cell cycle arrest and apoptosis. Previous clinical experience with MDM2–p53 protein–protein interaction antagonists (MDM2–p53 antagonists) has demonstrated that thrombocytopenia and neutropenia represent on-target dose-limiting toxicities that might restrict their therapeutic utility. Dosing less frequently, while maintaining efficacious exposure, represents an approach to mitigate toxicity and improve the therapeutic window of MDM2–p53 antagonists. However, to achieve this, a molecule possessing excellent potency and ideal pharmacokinetic properties is required. Here, we present the discovery and characterization of brigimadlin (BI 907828), a novel, investigational spiro-oxindole MDM2–p53 antagonist. Brigimadlin exhibited high bioavailability and exposure, as well as dose-linear pharmacokinetics in preclinical models. Brigimadlin treatment restored p53 activity and led to apoptosis induction in preclinical models of TP53 wild-type, MDM2-amplified cancer. Oral administration of brigimadlin in an intermittent dosing schedule induced potent tumor growth inhibition in several TP53 wild-type, MDM2-amplified xenograft models. Exploratory clinical pharmacokinetic studies (NCT03449381) showed high systemic exposure and a long plasma elimination half-life in patients with cancer who received oral brigimadlin. These findings support the continued clinical evaluation of brigimadlin in patients with MDM2-amplified cancers, such as dedifferentiated liposarcoma.
Stroke Prevention With Prophylactic Left Atrial Appendage Occlusion in Cardiac Surgery Patients Without Atrial Fibrillation: A Meta-Analysis of Randomized and Propensity-Score Studies
Authors: Baudo Massimo , Sicouri Serge , Yamashita Yoshiyuki , Senzai Mikiko , McCarthy Patrick M. , Gerdisch Marc W. , Whitlock Richard P. , Ramlawi Basel 
Published: September 2024

BACKGROUND:
The role of left atrial appendage occlusion (LAAO) in patients without previous atrial fibrillation (AF) is not established. This meta-analysis was conducted on patients with normal sinus rhythm who underwent cardiac surgery, with and without concomitant LAAO, to evaluate its effect on the incidence of cerebrovascular accidents (CVAs).

METHODS:
A systematic review was conducted from inception until December 2023 for randomized and propensity-score studies comparing CVA in patients without AF undergoing cardiac surgery with or without LAAO.

RESULTS:

Six studies met our inclusion criteria with a total of 4130 patients: 2146 in the LAAO group and 1984 in the no-LAAO group. The risk ratio of postoperative AF was 1.05 (95% CI, 0.86–1.28);
P
=0.628. The CVA rates at 5 years were 6.8±1.0% in the no-LAAO group and 4.3±0.8% in the LAAO group (log-rank
P
=0.021). The Cox regression analysis for CVA in patients undergoing LAAO reported a hazard ratio of 0.65 (95% CI, 0.45–0.94);
P
=0.022. Landmark analysis at 4 years highlighted a significant difference in overall survival between no-LAAO and LAAO groups, 86±12.2% versus 89.6±11.0%;
P
=0.041.

CONCLUSIONS:
In this meta-analysis of patients without previous AF undergoing cardiac surgery, LAAO was associated with a decreased risk of CVA, no difference in the incidence of postoperative atrial fibrillation, and a significant overall survival benefit at a 4-year landmark analysis. Although these findings support LAAO, the randomized LeAAPS trial (Left Atrial Appendage Exclusion for Prophylactic Stroke Reduction Trial), LAA-CLOSURE trial (A Randomized Prospective Multicenter Trial for Stroke Prevention by Prophylactic Surgical Closure of the Left Atrial Appendage in Patients Undergoing Bioprosthetic Aortic Valve Surgery), and LAACS-2 trial (Left Atrial Appendage Closure by Surgery-2) will help define the effectiveness of LAAO in patients undergoing cardiac surgery who have risk factors for AF and CVA.

REGISTRATION:

URL:
https://www.crd.york.ac.uk/prospero/
; Unique identifier: CRD42024496366.
Deep Learning‐Based Prediction of Final Infarct Core from CT Perfusion Data: A Comparison to the Clinical Standard
Authors: Werdiger Freda , Visser Milanka , Chen Chushuang , Lam Christina , Kolacz James , Parsons Mark W. , Lin Longting , Levi Christopher , Bivard Andrew ,   the INSPIRE (International Stroke Perfusion Imaging REgistry) Study Group
Published: September 2024

Background
In the management of acute ischemic stroke, computed tomography perfusion (CTP) is used to define the ischemic core and penumbra to estimate tissue fate after reperfusion therapy. The core/penumbra dichotomy uses single‐value thresholds, which potentially discards valuable data and oversimplifies the complexity of core and penumbral estimation. Advancing the dichotomous CTP output to a probability model has several advantages such as more sophisticated modeling of pathophysiology, supporting reader interpretation, and assessing a greater range of available data to estimate tissue fate.

Methods
In this retrospective study, we developed a CTP probability model to move away from single perfusion thresholds to estimate tissue fate. All patients from the International Stroke Perfusion Imaging Registry database had baseline CTP and were included in the current study if they had a large vessel occlusion that recanalized fully after thrombectomy and had follow‐up diffusion‐weighted imaging. Data were split into training, validation, and testing groups. Training and validation cohorts were used to develop a deep learning model in project MONAI (Medical Open Network for Artificial Intelligence) and performance metrics were derived from the testing set.

Results

In total, 243 patients were included in the study. The Attention U‐Net was the best performing deep learning model, producing the best prediction of follow‐up infarct core on the test set (n = 48): mean diverse counterfactual explanations score = 0.430±0.213, mean area under the curve = 0.765±0.095; better than the single‐value thresholding with a diverse counterfactual explanations scoreof 0.247±0.167 (paired
t
‐test,
P
<0.0001) and area under the curveof 0.604±0.074 (
P
<0.0001).

Conclusion
The deep learning probabilistic CTP model outperformed the current clinical standard, providing a more accurate core estimate than single‐threshold‐based measures.
BrainQCNet: A Deep Learning attention-based model for the automated detection of artifacts in brain structural MRI scans
Authors: Garcia Mélanie , Dosenbach Nico , Kelly Clare 
Published: September 2024

Abstract
Analyses of structural MRI (sMRI) data depend on robust upstream data quality control (QC). It is also crucial that researchers seek to retain maximal amounts of data to ensure reproducible, generalizable models and to avoid wasted effort, including that of participants. The time-consuming and difficult task of manual QC evaluation has prompted the development of tools for the automatic assessment of brain sMRI scans. Existing tools have proved particularly valuable in this age of Big Data; as datasets continue to grow, reducing execution time for QC evaluation will be of considerable benefit. The development of Deep Learning (DL) models for artifact detection in structural MRI scans offers a promising avenue toward fast, accurate QC evaluation. In this study, we trained an interpretable Deep Learning model, ProtoPNet, to classify minimally preprocessed 2D slices of scans that had been manually annotated with a refined quality assessment (ABIDE 1; n = 980 scans). To evaluate the best model, we applied it to 2141 ABCD T1-weighted MRI scans for which gold-standard manual QC annotations were available. We obtained excellent accuracy: 82.4% for good quality scans (Pass), 91.4% for medium to low quality scans (Fail). Further validation using 799 T1w MRI scans from ABIDE 2 and 750 T1w MRI scans from ADHD-200 confirmed the reliability of our model. Accuracy was comparable to or exceeded that of existing ML models, with fast processing and prediction time (1 minute per scan, GPU machine, CUDA-compatible). Our attention model also performs better than traditional DL (i.e., convolutional neural network models) in detecting poor quality scans. To facilitate faster and more accurate QC prediction for the neuroimaging community, we have shared the model that returned the most reliable global quality scores as a BIDS-app (https://github.com/garciaml/BrainQCNet).
A supervised data-driven spatial filter denoising method for speech artifacts in intracranial electrophysiological recordings
Authors: Peterson Victoria , Vissani Matteo , Luo Shiyu , Rabbani Qinwan , Crone Nathan E. , Bush Alan , Richardson R. Mark 
Published: September 2024

Abstract
Neurosurgical procedures that enable direct brain recordings in awake patients offer unique opportunities to explore the neurophysiology of human speech. The scarcity of these opportunities and the altruism of participating patients compel us to apply the highest rigor to signal analysis. Intracranial electroencephalography (iEEG) signals recorded during overt speech can contain a speech artifact that tracks the fundamental frequency (F0) of the participant’s voice, involving the same high-gamma frequencies that are modulated during speech production and perception. To address this artifact, we developed a spatial-filtering approach to identify and remove acoustic-induced contaminations of the recorded signal. We found that traditional reference schemes jeopardized signal quality, whereas our data-driven method denoised the recordings while preserving underlying neural activity.
Processus de focalisation multimodale lors des dîners familiaux français: une comparaison entre familles parlantes et familles signantes
Authors: Martel Karine , Dodane Christelle , Blondel Marion , Catteau Fanny , Bellifemine Corrado 
Published: September 2024

Abstract
Speech planning allows the speaker to highlight new information in order to draw the interlocutor’s attention. This focalization process has been described in spoken and sign languages, but rarely in a natural context such as family interaction. In this article, we study focalization at its prosodic level, by comparing the phenomena and parameters mobilized in the two types of language, within a privileged context, in order to observe focus marking during parent-children interaction: the family dinner. We make an inventory of prosodic focalization markers, mobilized in both languages and both modalities (spoken and gestural), from a sample of videorecorded meals in LSF and spoken French (ANR DinLang). We observe that prosodic features of focalization can be established in inter-modal terms and that focus is marked by the combination of various phenomena, which appear in contrast with the prosodic context. We give the example of a pattern that seems interesting to us to examine in the context of focalization, the one of scansion, and we emphasize the interest of considering sign languages and ‘spoken’ languages as embodied languages.
The Jive Verification System and Its Transformative Impact on Weather Forecasting Operations
Authors: Loveday Nicholas , Griffiths Deryn , Leeuwenburg Tennessee , Taggart Robert J. , Pagano Thomas C. , Cheng George , Plastow Kevin , Ebert Elizabeth E. , Templeton Cassandra , Carroll Maree , Khanarmuei Mohammadreza , Nagpal Isha 
Published: September 2024

Abstract
Forecast verification is critical for continuous improvement in meteorological organizations. The Jive verification system was originally developed to assess the accuracy of public weather forecasts issued by the Australian Bureau of Meteorology. It started as a research project in 2015 and gradually evolved to be a Bureau operational verification system in 2022. The system includes daily verification dashboards for forecasters to visualize recent forecast performance and “Evidence Targeted Automation” dashboards for exploring the performance of competing forecast systems. Additionally, Jive includes a Jupyter Notebook server with the Jive Python library, which supports research experiments, case studies, and the development of new verification metrics and tools. This paper describes the Jive verification system and how it helped bring verification to the forefront at the Bureau of Meteorology, leading to more accurate, streamlined forecasts. Jive has provided evidence to support forecast automation decisions and has helped to understand the evolving role of meteorologists in the forecast process. It has given operational meteorologists tools for evaluating forecast processes, including identifying when and how manual interventions lead to superior predictions. Work on Jive led to new verification science, including novel metrics that are decision-focused, including diagnostics for extreme conditions. Jive also provided the Bureau with an enterprise-wide data analysis environment and has prompted a clarification of forecast definitions. These collective impacts have resulted in more accurate forecasts, ultimately benefiting society and building trust with forecast users. These positive outcomes highlight the importance of meteorological organizations investing in verification science and technology.
Downscaling Vapor Pressure Deficit across Complex Forested Terrain
Authors: Burton Jamie E. , Pickering Bianca J. , Penman Trent D. , Cawson Jane G. 
Published: September 2024

Abstract
The forest microclimate shapes many aspects of forest functioning, including plant regeneration and wildfire occurrence. In complex landscapes with varying terrain, the forest microclimate varies at fine spatial scales (10–100 m2). However, accurately mapping this variation remains challenging. Vapor pressure deficit (VPD) is an important microclimatic variable for plant growth and fire activity, yet few studies have specifically focused on downscaling VPD. The aim of this study was to examine the drivers of in-forest VPD in temperate eucalypt forests and develop a model to predict in-forest VPD. We use microclimate data from 37 in-forest weather stations, installed across an aridity gradient in southeastern Australia. We used linear mixed models within an information theoretic approach to develop a predictive model for daily maximum in-forest VPD using open VPD and topographic variables. The highest-ranked model included fundamental topographic drivers of vegetation structure and microclimate in forested landscapes: aspect, elevation, and slope, in addition to open VPD. The model had high accuracy when tested against independent data. We used this model to map fine-scale (30 m2, daily) maximum in-forest VPD across a topographically complex case study landscape. Predicted in-forest VPD showed considerable spatial and temporal variations not captured by coarse-scale open VPD. This represents a significant advancement in our ability to model microclimatic conditions in temperate eucalypt forests and has the potential to advance our understanding of how ecosystem processes vary at fine spatial scales.
Assessment of mood after severe acquired brain injury: Interviews with UK clinical psychologists and medical professionals
Authors: Rose Alexandra E , Cullen Breda , Crawford Sarah , Evans Jonathan J 
Published: September 2024

Objective Mood assessment is challenging when people have cognitive and receptive communication impairments after severe brain injury. This study explored how UK-based medical and psychology professionals working with people with severe cognitive and communication impairments after brain injury assess mood in this population. Design Following their participation in an online survey, professionals were invited to participate in individual semi-structured interviews. Interviews were analysed using thematic analysis to label explicit data (semantic themes) and implicit data (latent themes). Participants Twenty-three clinical psychologists and nine medical professionals participated in online or in-person interviews. Results Both groups explicitly reported using a combination of collateral information, history, observations, and patient interviews when assessing mood in this population. Medical professionals did not routinely use standardised measures and clinical psychologists often adjusted them when they used them. The respondents discussed difficulties conceptualising depression after brain injury, the experience needed by the assessor, and the need for an individualised approach for this population. Clinical psychologists discussed the pressures of working in healthcare systems and medical professionals discussed how symptoms may influence prescription choices. Seven latent themes were labelled which highlighted additional challenges and complexities experienced by those assessing mood, beyond the actual assessment process itself. Conclusions No ‘gold standard’ approach to assessing mood in those with cognitive and communication difficulties after severe brain injury was identified. There was overlap in assessment approaches but no clear consensus. Interviewees felt that mood assessment must be approached differently in this population and that self-report measures are not useful.
Pulmonary Artery Endograft Implantation Using a Parallel Stent Grafting Technique to Enable the Treatment of a Bronchial Anastomosis Complication After Lung Transplantation
Authors: Schmid Bruno P. , Scordamaglio Paulo Rogério , Samano Marcos N. , Cunha Marcela Juliano S. , Valle Leonardo G. M. , Galastri Francisco L. , Nasser Felipe , Affonso Breno B. 
Published: September 2024

Background Bronchial stenosis associated with bronchial anastomosis dehiscence after lung transplantation is a catastrophic complication following lung transplantation with a paucity of therapeutic solutions. Purpose To describe an adaptation of the parallel stent grafting technique in the pulmonary arterial territory to treat this challenging situation. Research Design This is a case report of a 52-year-old patient who presented bronchus stenosis and bronchial anastomosis dehiscence after lung transplantion. Bronchial stenting and lung retransplantation were contraindicated. Therefore, an endovascular approach using pulmonary artery endograft placement to prevent bleeding during repeated right bronchial balloon dilation was propposed. The technique consists of the deployment of an aortic extender endoprosthesis in the right main pulmonary artery and a balloon expandable stent in the upper lobe pulmonary artery (using a parallel graft configuration) through the common femoral and right internal jugular veins, respectively. Intraoperative transesophageal echocardiogram and one-lung ventilatory ventilation are needed. Results The patient underwent a new bronchoscopy 16 days after the procedure, that showed epithelization at the previous eroded zone, enabling bronchocopic balloon dialtion to be safely performed. A post-operative contrast-enhanced CT scan revealed an adequate positioning of the stent grafts. Despite all eforts, the patient succumbed to ventilator associated pneumonia on postoperative day 108. Data Analysis The technique's advantages include its feasibility even in situations in which other techniques may be contraindicated and its potential use in emergencies. Its limitations include the need for experienced interventionists to perform it, and the potential risk of acute tricuspid regurgitation. Conclusion This study illustrates the early feasibility of the parallel stent grafting technique applied to the pulmonary artery territory. However, it's safety profile regarding infectious risk was not demontrated.
Remote postoperative management using Ecological Momentary Computerized Adaptive Testing (EMCAT): feasibility assessment survey
Authors: Bele Sumedh , Rodrigues Jeremy , Beard David , Harrison Conrad 
Published: September 2024

Our survey of 38 surgeons shows that Ecological Momentary Computerized Adaptive Testing (EMCAT), a platform to remotely collect patient-reported outcome measures (PROMs) is acceptable to surgeons, and 36 of 38 are willing to participate in future randomized control trials comparing EMCAT versus routine follow-up. Level of evidence: IV
Association Between SARS-CoV-2 Vaccination and Development of Antinuclear Antibodies Among Students
Authors: Laskowski Karol , Paszkiewicz Justyna , Plewik Dorota , Szepeluk Adam , Hozyasz Kamil K. 
Published: September 2024

Introduction: Antinuclear antibodies (ANA) are the hallmark of many connective tissue disorders (including lupus), which comprise roughly 5% to 10% of chronic debilitating diseases causing morbidity and mortality. In society, fear of these diseases increases illness-related uncertainty because the prognosis of progression is often difficult to determine and at least some symptoms fluctuate unpredictably. In the anti-vaccination movement, the question of the possible connection between vaccination and connective tissue disorders and other autoimmune diseases has grown to rank as an important argument for rejecting vaccination. In 2021, every fifth Polish first-degree nursing student decided to not be vaccinated against COVID-19. Objective: This study aimed to explore the prevalence of antinuclear antibodies in students vaccinated and unvaccinated against COVID-19. Participants and Methods: A single university cross-sectional study was performed in a small academic centre in Poland, where 210 students were recruited in 2022. All the participants were screened for SARS-CoV-2 IgG and antinuclear antibodies. Results: The mean age of the students who rejected vaccination was higher than that of those who were vaccinated. Among nursing students, 30.0% of vaccinated and 58.3% of unvaccinated individuals had COVID-19. The frequency of antinuclear antibodies was 3 times lower in vaccinated students than in unvaccinated students (2/159 vs 2/51; P > .05). Conclusion: The results of our study did not confirm the rationality of rejecting vaccinations against COVID-19 for fear of developing autoimmune diseases among healthy students.