Temporal dynamics of affective scene processing in the healthy adult human brain.

Understanding how the brain distinguishes emotional from neutral scenes is crucial for advancing brain-computer interfaces, enabling real-time emotion detection for faster, more effective responses, and improving treatments for emotional disorders like depression and anxiety. However, inconsistent research findings have arisen from differences in study settings, such as variations in the time windows, brain regions, and emotion categories examined across studies. This review sought to compile the existing literature on the timing at which the adult brain differentiates basic affective from neutral scenes in less than one second, as previous studies have consistently shown that the brain can begin recognizing emotions within just a few milliseconds.

From text to insight: large language models for chemical data extraction.

The vast majority of chemical knowledge exists in unstructured natural language, yet structured data is crucial for innovative and systematic materials design. Traditionally, the field has relied on manual curation and partial automation for data extraction for specific use cases. The advent of large language models (LLMs) represents a significant shift, potentially enabling non-experts to extract structured, actionable data from unstructured text efficiently.

Automated sample annotation for diabetes mellitus in healthcare integrated biobanking.

Healthcare integrated biobanking describes the annotation and collection of residual samples from hospitalized patients for research purposes. The central idea of the current work is to establish an automated workflow for sample annotation, selection and storage for diabetes mellitus. This is challenging due to incomplete data at the time of sample selection.

Meditation dosage predicts self- and teacher-perceived responsiveness to an 18-month randomised controlled trial.

Understanding the factors that predict why some individuals perceive to respond more to meditation training than others could impact the development, efficacy, adherence levels, and implementation of meditation-based interventions. We investigated individual-level variables associated with self- and teacher-perceived responsiveness to longer-term meditation training. This study presents a secondary analysis of the Age-Well trial (NCT02977819, 30/11/2016) and includes 90 healthy older adults (65-84 years) that were randomised to an 18-month meditation training or a non-native language (English) training.

Effects of physical therapy modalities for motor function, functional recovery, and post-stroke complications in patients with severe stroke: a systematic review update.

Background: Physical therapy interventions play a crucial role in the daily care of patients recovering from severe stroke. However, the efficacy of these interventions and associated modalities, including duration, intensity, and frequency, have not been fully elucidated. In 2020, a systematic review reported the beneficial effects of physical therapy for patients with severe stroke but did not assess therapeutic modalities.

Quality Assessment of YouTube Videos on Complementary and Alternative Medicine (CAM) for Cancer Using a Newly Developed Tool.

Background: The global burden of cancer continues to rise and complementary and alternative medicine (CAM) is attracting a lot of interest. However, quality of online information on CAM, particularly on platforms like YouTube, remains questionable. This study aimed to create a comprehensive assessment tool to assess the quality of CAM-related YouTube videos, crucial for informed decision-making in oncology.

Complex Words as Shortest Paths in the Network of Lexical Knowledge.

Lexical models diverge on the question of how to represent complex words. Under the morpheme-based approach, each morpheme is treated as a separate unit, while under the word-based approach, morphological structure is derived from complex words. In this paper, we propose a new computational model of morphology that is based on graph theory and is intended to elaborate the word-based network approach.

Spatial communication systems and action.

Spatial cognition is fundamental to our species. One might therefore expect that spatial communication systems would have evolved to make common distinctions. However, many have argued that spatial communication systems exhibit considerable cross-linguistic diversity, challenging the view that space structures language.

Democratising artificial intelligence in healthcare: community-driven approaches for ethical solutions.

The rapid advancement and widespread adoption of artificial intelligence (AI) has ushered in a new era of possibilities in healthcare, ranging from clinical task automation to disease detection. AI algorithms have the potential to analyse medical data, enhance diagnostic accuracy, personalise treatment plans and predict patient outcomes among other possibilities. With a surge in AI's popularity, its developments are outpacing policy and regulatory frameworks, leading to concerns about ethical considerations and collaborative development.

A global database of soil seed bank richness, density, and abundance.

A soil seed bank is the collective name for viable seeds that are stored naturally in the soil. At the species or population level, the ability to form a seed bank represents a strategy for (re)colonization following a disturbance or other change in the local environmental conditions. At the community level, seed banks are thought to buffer local diversity during periods of environmental change and are often studied in relation to the potential for passive habitat restoration.

A longitudinal study on the relation between parenting and Toddler's disruptive behavior: what is the role of Toddler's negative emotionality and physiological stress reactivity?

Harsh and unsupportive parenting is a risk factor for the development of disruptive behavior in children. However, little is known about how children's temperament and stress reactivity influence this relation. In a three-wave longitudinal study, we examined whether the associations between parenting practices (supportive parenting, positive discipline, and harsh discipline) and child disruptive behavior were mediated by child temperament (negative emotionality) and stress reactivity (heart rate reactivity).

Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data.

Feature-based molecular networking (FBMN) is a popular analysis approach for liquid chromatography-tandem mass spectrometry-based non-targeted metabolomics data. While processing liquid chromatography-tandem mass spectrometry data through FBMN is fairly streamlined, downstream data handling and statistical interrogation are often a key bottleneck. Especially users new to statistical analysis struggle to effectively handle and analyze complex data matrices.

Non-verbal effecting - animal research sheds light on human emotion communication.

Cracking the non-verbal "code" of human emotions has been a chief interest of generations of scientists. Yet, despite much effort, a dictionary that clearly maps non-verbal behaviours onto meaning remains elusive. We suggest this is due to an over-reliance on language-related concepts and an under-appreciation of the evolutionary context in which a given non-verbal behaviour emerged.

Unsupervised Learning of Eye State Prototypes for Semantically Rich Blinking Detection.

Blinking contributes to the health and protection of the eye and also holds potential in the context of muscle or nerve disorder diagnosis. Traditional methods of classifying eye blinking as open or closed are insufficient, as they do not capture medical-relevant aspects like closure speed, duration, or percentage. The issue could be solved by reliably detecting blinking intervals in high-temporal recordings.

Large-scale analysis of structural brain asymmetries during neurodevelopment: Associations with age and sex in 4265 children and adolescents.

Only a small number of studies have assessed structural differences between the two hemispheres during childhood and adolescence. However, the existing findings lack consistency or are restricted to a particular brain region, a specific brain feature, or a relatively narrow age range. Here, we investigated associations between brain asymmetry and age as well as sex in one of the largest pediatric samples to date (n = 4265), aged 1-18 years, scanned at 69 sites participating in the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium.

A practice-based approach to teaching antimicrobial therapy using artificial intelligence and gamified learning.

Objectives: Scalable teaching through apps and artificial intelligence (AI) is of rising interest in academic practice. We focused on how medical students could benefit from this trend in learning antibiotic stewardship (ABS). Our study evaluated the impact of gamified learning on factual knowledge and uncertainty in antibiotic prescription.

Overcoming the Tropical Andes publication divide: Insights from local researchers on challenges and solutions.

The Tropical Andes, one of the world's most biodiverse regions, is vital for ecological research and conservation. However, while researchers in Bolivia, Ecuador, and Peru contribute significantly to scientific knowledge, their publication rates in academic journals have historically lagged behind neighboring nations. A multifaceted strategy was employed to understand and address the publication divide in the Tropical Andes region.

Effects of testosterone on speech production and perception: Linking hormone levels in males to vocal cues and female voice attractiveness ratings.

This study sets out to investigate the potential effect of males' testosterone level on speech production and speech perception. Regarding speech production, we investigate intra- and inter-individual variation in mean fundamental frequency (f) and formant frequencies and highlight the potential interacting effect of another hormone, i.e.