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The temporal dynamics in biological systems displays a wide range of behaviors, from periodic oscillations, as in rhythms, bursts, long-range (fractal) correlations, chaotic dynamics up to brown and white noise. Herein, ...

People learn from experience, but with considerable individual differences in the degree and type of behavioral adjustments resulting from a given experience. Error driven learning rules provide an elegant framework for ...

Background The long-term biological effects of low-level exposure to artificial sweeteners remain debated. We integrated computational toxicology and Mendelian randomization (MR) to explore potential biological responses...

Abstract A Schiff base ligand L 1 was synthesized via the condensation reaction between from 2-hydroxy-1-naphthaldehyde and 4-methoxyaniline. This Schiff base was employed for the preparation of metal complexes of type [...

Abstract Quantum-mechanical simulations provide the most fundamental description of matter, yet their computational cost commonly limits applications to systems containing at most thousands of atoms. Here, we present an ...

Background Cognitive–behavioural theories of panic disorder posit that panic attacks arise from a positive feedback loop between arousal-related bodily sensations and perceived threat. In a recently developed computati...

Sepsis remains one of the most complex and lethal syndromes in pediatric critical care, driven by dysregulated and heterogeneous host responses to infection. Despite decades of biomarker research, few biomarkers have bee...

Abstract Background N6-methyladenosine ( $$m^{6}A$$ ) plays a crucial role in enriching RNA functional and genetic information. While deep learning has advanced $$m^{6}A$$ site identification, current state-of-the-art me...

The menstrual cycle affects many aspects of female physiology, from the immune system to behavioral and emotional regulation. It is unclear however if these physiological changes are reflected in everyday, naturalistic l...

Abstract The Error Diffusion Learning Algorithm (EDLA) is a learning scheme that performs synaptically local weight updates driven by a single, globally defined error signal. Although originally proposed as an alternativ...

Abstract Advances in artificial intelligence (AI) and multi-omics integration are reshaping precision oncology by enabling deeper mechanistic understanding, improved characterization of tumor heterogeneity, and the accel...

Abstract Echo State Networks are recurrent neural networks that leverage a random reservoir’s dynamics, training only a simple readout layer. This approach is computationally efficient but limits network performance. B...

Abstract Background and purpose Claudin-5 plays a crucial role in maintaining blood-brain barrier (BBB) integrity through endothelial tight junction formation. Alternative splicing of claudin-5 within the microvascular e...

Computer-aided drug discovery and design involve the use of information technologies to identify and develop, on a rational ground, chemical compounds that align a set of desired physicochemical and biological properties...

Abstract Background Reliable identification of protein‑protein interactions (PPIs) is crucial for deciphering cellular functional networks. Current research models still face limitations in aligning heterogeneous featu...

Abstract Background Super-enhancers are critical cis-regulatory elements that play a central role in modulating gene expression and driving cellular identity. Their dysregulation is closely associated with the developmen...

IntroductionTiller production is a critical determinant of turfgrass canopy density and plant performance, yet manual tiller counting is too labor-intensive for large breeding programs.MethodsTo address this limitation, ...

IntroductionLiver diseases continue to impose a major global health burden, and therapeutic progress is constrained by the limited availability of validated small-molecule modulators. TEAD4, a central Hippo-YAP effector,...

Although vaccination remains one of the most impactful interventions in contemporary public health, with consistent and widely documented reductions in morbidity and mortality, the traditional empirical development of va...

Abstract Corollary discharge denotes internal signals about the expected sensory consequences of one’s own actions, leading to reduced sensory responses to self-generated stimulation. To investigate the underlying neur...

A common feature in biological neuromuscular systems is the redundancy in joint actuation. Understanding how these redundancies are resolved in typical joint movements has been a long-standing problem in biomechanics, ne...

Introduction Sarcoidosis is a heterogeneous granulomatous disease with highly variable clinical trajectories, yet no validated biomarkers exist to distinguish progressive sarcoidosis (P-sarcoidosis) from non-progressive ...

Next generation risk assessment (NGRA) demands a fundamental transformation in how toxicological test methods are validated. Traditional validation approaches, designed for animal tests and mainly for simple in vitro met...

Introduction. Metaheuristic algorithms are effective for solving complex power system optimization problems characterized by nonlinearity, multimodality, and high dimensionality. Nature-inspired strategies based on adapt...