From land to water: "Sunken" T-maze for associated learning in cichlid fish.

The study introduced and evaluated learning paradigms for Maylandia callainos cichlids using a modified version of the rodent T-maze, filled with tank water (the "sunken" modification). Both male and female fish underwent training in two distinct conditioning paradigms. Firstly, simple operant conditioning involved placing a food reward in either the right or left compartment. Cichlids demonstrated the ability to purposefully find the bait within 6 days of training, with a persistent place preference lasting up to 6 days. Additionally, the learning dynamics varied with sex: female cichlids exhibited reduction in latency to visit the target compartment and consume the bait, along with a decrease in the number of errors 3 and 4 days earlier than males, respectively. Secondly, visually-cued operant conditioning was conducted, with a food reward exclusively placed in the yellow compartment, randomly positioned on the left or right side of the maze during each training session. Visual learning persisted for 10 days until reaction time improvement plateaued. Color preference disappeared after 4 consecutive check-ups, with no sex-related interference. For further validation of visually-cued operant conditioning paradigm, drugs MK-801 (dizocilpine) and caffeine, known to affect performance in learning tasks, were administered intraperitoneally. Chronic MK-801 (0.17 mg/kg) impaired maze learning, resulting in no color preference development. Conversely, caffeine administration enhanced test performance, increasing precision in fish. This developed paradigm offers a viable approach for studying learning and memory and presents an effective alternative to rodent-based drug screening tools, exhibiting good face and predictive validity.

Mitochondrial Disorders in Alzheimer's Disease.

Alzheimer's disease is the most common age-related neurodegenerative disease. Understanding of its etiology and pathogenesis is constantly expanding. Thus, the increasing attention of researchers is directed to the study of the role of mitochondrial disorders. In addition, in recent years, the concept of Alzheimer's disease as a stress-induced disease has begun to form more and more actively. The stress-induced damage to the neuronal system can trigger a vicious circle of pathological processes, among which mitochondrial dysfunctions have a significant place, since mitochondria represent a substantial component in the anti-stress activity of the cell. The study of mitochondrial disorders in Alzheimer's disease is relevant for at least two reasons: first, as important pathogenetic component in this disease; second, due to vital role of mitochondria in formation of the body resistance to various conditions, including stressful ones, throughout the life. This literature review analyzes the results of a number of recent studies assessing potential significance of the mitochondrial disorders in Alzheimer's disease. The probable mechanisms of mitochondrial disorders associated with the development of this disease are considered: bioenergetic dysfunctions, changes in mitochondrial DNA (including assessment of the significance of its haplogroup features), disorders in the dynamics of these organelles, oxidative damage to calcium channels, damage to MAM complexes (membranes associated with mitochondria; mitochondria-associated membranes), disruptions of the mitochondrial quality control system, mitochondrial permeability, etc. The issues of the "primary" or "secondary" mitochondrial damage in Alzheimer's disease are discussed. Potentials for the development of new methods for diagnosis and therapy of mitochondrial disorders in Alzheimer's disease are considered.

Annotation of tandem mass spectrometry data using stochastic neural networks in shotgun proteomics.

MOTIVATION: The discrimination ability of score functions to separate correct from incorrect peptide-spectrum-matches in database-searching-based spectrum identification is hindered by many superfluous peaks belonging to unexpected fragmentation ions or by the lacking peaks of anticipated fragmentation ions. RESULTS: Here, we present a new method, called BoltzMatch, to learn score functions using a particular stochastic neural networks, called restricted Boltzmann machines, in order to enhance their discrimination ability. BoltzMatch learns chemically explainable patterns among peak pairs in the spectrum data, and it can augment peaks depending on their semantic context or even reconstruct lacking peaks of expected ions during its internal scoring mechanism. As a result, BoltzMatch achieved 50% and 33% more annotations on high- and low-resolution MS2 data than XCorr at a 0.1% false discovery rate in our benchmark; conversely, XCorr yielded the same number of spectrum annotations as BoltzMatch, albeit with 4-6 times more errors. In addition, BoltzMatch alone does yield 14% more annotations than Prosit (which runs with Percolator), and BoltzMatch with Percolator yields 32% more annotations than Prosit at 0.1% FDR level in our benchmark. AVAILABILITY AND IMPLEMENTATION: BoltzMatch is freely available at: https://github.com/kfattila/BoltzMatch. CONTACT: akerteszfarkas@hse.ru. SUPPORTING INFORMATION: Supplementary data are available at Bioinformatics online.

Bias in False Discovery Rate Estimation in Mass-Spectrometry-Based Peptide Identification.

Accurate target-decoy-based false discovery rate (FDR) control of peptide identification from tandem mass-spectrometry data relies on an important but often neglected assumption that incorrect spectrum annotations are equally likely to receive either target or decoy peptides. Here we argue that this assumption is often violated in practice, even by popular methods. Preference can be given to target peptides by biased scoring functions, which result in liberal FDR estimations, or to decoy peptides by correlated spectra, which result in conservative estimations.