Raman-based machine-learning platform reveals unique metabolic differences between IDHmut and IDHwt glioma.

Background: Formalin-fixed, paraffin-embedded (FFPE) tissue slides are routinely used in cancer diagnosis, clinical decision-making, and stored in biobanks, but their utilization in Raman spectroscopy-based studies has been limited due to the background coming from embedding media.

Methods: Spontaneous Raman spectroscopy was used for molecular fingerprinting of FFPE tissue from 46 patient samples with known methylation subtypes. Spectra were used to construct tumor/non-tumor, IDH1WT/IDH1mut, and methylation-subtype classifiers.

Southern Carpathian ultramafic grasslands within the central-southeast European context: syntaxonomic classification and overall eco-coenotic patterns.

Background: Previous investigations carried out in ultramafic habitats emphasized the greater importance of site conditions over soil toxic metal content for vegetation composition. Very little is known about the floristic structure of the Southern Carpathian ultramafic grasslands and there is no information on the local environmental drivers of their composition and coenotic features. Here, we aim to fill these knowledge gaps by referring to similar phytocoenoses described in the Balkan Peninsula and central Europe.

Network controllability solutions for computational drug repurposing using genetic algorithms.

Control theory has seen recently impactful applications in network science, especially in connections with applications in network medicine. A key topic of research is that of finding minimal external interventions that offer control over the dynamics of a given network, a problem known as network controllability. We propose in this article a new solution for this problem based on genetic algorithms.

Scalable reaction network modeling with automatic validation of consistency in Event-B.

Constructing a large biological model is a difficult, error-prone process. Small errors in writing a part of the model cascade to the system level and their sources are difficult to trace back. In this paper we extend a recent approach based on Event-B, a state-based formal method with refinement as its central ingredient, allowing us to validate for model consistency step-by-step in an automated way.

Addressing the Selectivity of Enzyme Biosensors: Solutions and Perspectives.

Enzymatic biosensors enjoy commercial success and are the subject of continued research efforts to widen their range of practical application. For these biosensors to reach their full potential, their selectivity challenges need to be addressed by comprehensive, solid approaches. This review discusses the status of enzymatic biosensors in achieving accurate and selective measurements via direct biocatalytic and inhibition-based detection, with a focus on electrochemical enzyme biosensors.

Reaction Systems and Synchronous Digital Circuits.

A reaction system is a modeling framework for investigating the functioning of the living cell, focused on capturing cause-effect relationships in biochemical environments. Biochemical processes in this framework are seen to interact with each other by producing the ingredients enabling and/or inhibiting other reactions. They can also be influenced by the environment seen as a systematic driver of the processes through the ingredients brought into the cellular environment.

Refinement-based modeling of the ErbB signaling pathway.

The construction of large scale biological models is a laborious task, which is often addressed by adopting iterative routines for model augmentation, adding certain details to an initial high level abstraction of the biological phenomenon of interest. Refitting a model at every step of its development is time consuming and computationally intensive. The concept of model refinement brings about an effective alternative by providing adequate parameter values that ensure the preservation of its quantitative fit at every refinement step.

Versatile SPR aptasensor for detection of lysozyme dimer in oligomeric and aggregated mixtures.

A Surface Plasmon Resonance (SPR) sensor for the quantitation of lysozyme dimer in monomer-dimer mixtures, reaching a detection limit of 1.4nM dimer, has been developed. The sensor is based on an aptamer which, although developed for the monomeric form, binds also the dimeric form but with a strikingly different kinetics.