Embedding-based pair generation for contrastive representation learning in audio-visual surveillance data.

Smart cities deploy various sensors such as microphones and RGB cameras to collect data to improve the safety and comfort of the citizens. As data annotation is expensive, self-supervised methods such as contrastive learning are used to learn audio-visual representations for downstream tasks. Focusing on surveillance data, we investigate two common limitations of audio-visual contrastive learning: false negatives and the minimal sufficient information bottleneck.

CytoNorm 2.0: A flexible normalization framework for cytometry data without requiring dedicated controls.

Cytometry is a single cell, high-dimensional, high-throughput technique that is being applied across a range of disciplines. However, many elements alongside the data acquisition process might give rise to technical variation in the dataset, called batch effects. CytoNorm is a normalization algorithm for batch effect removal in cytometry data that was originally published in 2020 and has been applied on a variety of datasets since then.

Aortic valve repair in adults: long-term clinical outcomes and echocardiographic evolution in different valve repair techniques.

Objective: Aortic valve repair/sparing have been established as effective treatments for aortic regurgitation and/or aortic aneurysms. However, concerns remain regarding long-term durability, reproducibility, and patient selection. This study aims to asses long-term clinical and echocardiographic outcomes, with a focus on aortic regurgitation grade and left ventricular ejection fraction evolution, in adults undergoing these procedures.

Multiple Sclerosis Nursing to Improve Care and Education (MSNICE): an observational study.

Objective: To explore differences in patient reported outcomes, health care resources and expenditures in persons with multiple sclerosis (pwMS) with or without access to an MS-nurse.

Methodology: An observational, multicenter and cross-sectional study was conducted. Seven centers with, and twelve centers without an MS-nurse participated.

The multi-omics signatures of telomere length in childhood.

Background: Telomere length is an important indicator of biological age and a complex multi-factor trait. To date, the telomere interactome for comprehending the high-dimensional biological aspects linked to telomere regulation during childhood remains unexplored. Here we describe the multi-omics signatures associated with childhood telomere length.

Developing a clinical prediction model to modify empirical antibiotics for non-typhoidal Salmonella bloodstream infection in children under-five in the Democratic Republic of Congo.

Background: Non-typhoidal Salmonella (NTS) frequently cause bloodstream infection in children under-five in sub-Saharan Africa, particularly in malaria-endemic areas. Due to increasing drug resistance, NTS are often not covered by standard-of-care empirical antibiotics for severe febrile illness. We developed a clinical prediction model to orient the choice of empirical antibiotics (standard-of-care versus alternative antibiotics) for children admitted to hospital in settings with high proportions of drug-resistant NTS.

The biodiversity of ice-free Antarctica database.

Antarctica is one of Earth's most untouched, inhospitable, and poorly known regions. Although knowledge of its biodiversity has increased over recent decades, a diverse, wide-ranging, and spatially explicit compilation of the biodiversity that inhabits Antarctica's permanently ice-free areas is unavailable. This absence hinders both Antarctic biodiversity research and the integration of Antarctica in global biodiversity-related studies.

Oocyte/zygote/embryo maturation arrest: a clinical study expanding the phenotype of NOBOX variants.

Purpose: Primary ovarian insufficiency (POI) is an important cause of female infertility, stemming from follicle dysfunction or premature oocyte depletion. Pathogenic variants in genes such as NOBOX, GDF9, BMP15, and FSHR have been linked to POI. NOBOX, a transcription factor expressed in oocytes and granulosa cells, plays a pivotal role in folliculogenesis.

An Exploration of the Interplay Between Caffeine and Antidepressants Through the Lens of Pharmacokinetics and Pharmacodynamics.

Caffeine consumption is regarded as a widespread phenomenon, and its usage has continued to increase. In addition, the growing usage of antidepressants worldwide and increase in mental health disorders were shown in recent statistical analyses conducted by the World Health Organisation. The coadministration of caffeine and antidepressants remains a concern due to potential interactions that can alter a patient's response to therapy.

Rome Foundation Working Team Report on overlap in disorders of gut-brain interaction.

In patients with disorders of gut-brain interaction (DGBI), overlapping non-gastrointestinal conditions such as fibromyalgia, headaches, gynaecological and urological conditions, sleep disturbances and fatigue are common, as is overlap among DGBI in different regions of the gastrointestinal tract. These overlaps strongly influence patient management and outcome. Shared pathophysiology could explain this scenario, but details are not fully understood.

RNA-sequencing unveils FLT4 splice site variants in variable congenital heart disease.

The etiology of congenital heart disease (CHD) is complex, comprising both genetic and environmental factors. Despite documented familial occurrences, the genetic etiology remains largely elusive. Trio exome sequencing identified a heterozygous FLT4 splice site variant in two families with respectively tetralogy of Fallot (TOF), and variable CHD comprising both the TOF spectrum and aortic coarctation.

Machine learning meta-analysis identifies individual characteristics moderating cognitive intervention efficacy for anxiety and depression symptoms.

Cognitive training is a promising intervention for psychological distress; however, its effectiveness has yielded inconsistent outcomes across studies. This research is a pre-registered individual-level meta-analysis to identify factors contributing to cognitive training efficacy for anxiety and depression symptoms. Machine learning methods, alongside traditional statistical approaches, were employed to analyze 22 datasets with 1544 participants who underwent working memory training, attention bias modification, interpretation bias modification, or inhibitory control training.

NIRS-BIDS: Brain Imaging Data Structure Extended to Near-Infrared Spectroscopy.

Functional near-infrared spectroscopy (fNIRS) is an increasingly popular neuroimaging technique that measures cortical hemodynamic activity in a non-invasive and portable fashion. Although the fNIRS community has been successful in disseminating open-source processing tools and a standard file format (SNIRF), reproducible research and sharing of fNIRS data amongst researchers has been hindered by a lack of standards and clarity over how study data should be organized and stored. This problem is not new in neuroimaging, and it became evident years ago with the proliferation of publicly available neuroimaging datasets.

Helioseismic inference of the solar radiative opacity.

The Sun is the most studied of all stars, and thus constitutes a benchmark for stellar models. However, our vision of the Sun is still incomplete, as illustrated by the current debate on its chemical composition. The problem reaches far beyond chemical abundances and is intimately linked to microscopic and macroscopic physical ingredients of solar models such as radiative opacity, for which experimental results have been recently measured that still await theoretical explanations.

Genetic coupling of enhancer activity and connectivity in gene expression control.

Gene enhancers often form long-range contacts with promoters, but it remains unclear if the activity of enhancers and their chromosomal contacts are mediated by the same DNA sequences and recruited factors. Here, we study the effects of expression quantitative trait loci (eQTLs) on enhancer activity and promoter contacts in primary monocytes isolated from 34 male individuals. Using eQTL-Capture Hi-C and a Bayesian approach considering both intra- and inter-individual variation, we initially detect 19 eQTLs associated with enhancer-eGene promoter contacts, most of which also associate with enhancer accessibility and activity.

Lateral pterygoid muscle enthesis reconstruction in alloplastic total temporomandibular joint replacement: An animal experiment with histological verification.

In current alloplastic total temporomandibular joint replacements (TMJRs) typically the lateral pterygoid muscle (LPM) insertion is sacrificed, affecting joint function. This study assesses a novel additively manufactured TMJR (CADskills BV, Gent, Belgium) designed to enable LPM reinsertion through a scaffold feature on the implant. Thirteen TMJRs were implanted in Swifter crossbreed sheep, with follow-up CT scans after 288 days to evaluate LPM reintegration.

Bullous pyoderma gangrenosum revealing acute myeloid leukaemia.

We describe a man in his 60s presenting poor scar development following surgical treatment for popliteal aneurysm. The clinical features in a postoperative context and the poor clinical response to intravenous broad-spectrum antibiotics were highly suggestive of bullous pyoderma gangrenosum. Histology, with dense inflammatory infiltrate of neutrophils, subsequently confirmed the diagnosis and the response to systemic corticosteroids was rapid and complete.

How to: share and reuse data - challenges and solutions from PrIMAVeRa project.

Background: Data sharing accelerates scientific progress and improves evidence quality. Even though journals and funding institutions require investigators to share data, only a small part of studies made their data publicly available upon publication. The procedures necessary to share retrospective data for re-use in secondary data analysis projects can be cumbersome.

Combination of clinical frailty score and myostatin concentrations as mortality predictor in hemodialysis patients.

Background And Aims: Frailty is common among hemodialysis (HD) patients. Its assessment is usually based on clinical criteria. In the present work, we evaluated the interest of combining clinical frailty score and biomarkers to predict mortality of chronic HD patients.

Molecular miscibility of ASD blend components: an evaluation of (the added value of) solid state NMR spectroscopy and relaxometry.

In order to evaluate the stability of an amorphous solid dispersion (ASD) it is crucial to be able to accurately determine whether the ASD components are homogeneously mixed or not. Several solid-state analysis techniques are at the disposal of the formulation scientist, such as for example modulated differential scanning calorimetry (mDSC) and solid-state nuclear magnetic resonance spectroscopy (ssNMR). ssNMR is a robust, versatile, and accurate analysis technique with a large number of application possibilities.

Optimizing thermal and thermal-alkaline pretreatments for polylactic acid biodegradation by Amycolatopsis orientalis and Amycolatopsis thailandensis.

Environmental pollution from packaging, has led to a need for sustainable alternatives. This study investigates the biodegradation of polylactic acid (PLA) by Amycolatopsis orientalis and Amycolatopsis thailandensis after thermal and thermal-alkaline pretreatments. The biodegradation was assessed based on weight loss, CO evolution, carbon balance analysis and scanning electron microscopy (SEM).

Environmental impact of peat alternatives in growing media for European mushroom production.

Button mushrooms are an important protein source with a production of >48 million metric tonnes in 2021. Several life cycle assessments (LCAs) have been employed in assessing mushroom cultivation. This paper assessed potential impacts of relevant alternatives (sphagnum moss, grass fibres, spent casing and bark) to peat as casing materials for mushroom production across Europe by using LCA using a cradle to farm gate approach.

Guidelines International Network: Principles for Use of Artificial Intelligence in the Health Guideline Enterprise.

Description: Artificial intelligence (AI) has been defined by the High-Level Expert Group on AI of the European Commission as "systems that display intelligent behaviour by analysing their environment and taking actions-with some degree of autonomy-to achieve specific goals." Artificial intelligence has the potential to support guideline planning, development and adaptation, reporting, implementation, impact evaluation, certification, and appraisal of recommendations, which we will refer to as "guideline enterprise." Considering this potential, as well as the lack of guidance for the use of AI in guidelines, the Guidelines International Network (GIN) proposes a set of principles for the development and use of AI tools or processes to support the health guideline enterprise.