Embedding-based search in JetBrains IDEs

Most modern Integrated Development Environments (IDEs) and code editors have a feature to search across available functionality and items in an open project. In JetBrains IDEs, this feature is called Search Everywhere: it allows users to search for files, actions, classes, symbols, settings, and anything from VCS history from a single entry point. However, it works with the candidates obtained by algorithms that don't account for semantics, e.g., synonyms, complex word permutations, part of the speech modifications, and typos. In this work, we describe the machine learning approach we implemented to improve the discoverability of search items. We also share the obstacles encountered during this process and how we overcame them

Verification of NADH content measurements by portable optical diagnostic system in living brain tissue

The overall aim of this study was verification of the possibility to register the change of NADH fluorescence in live tissue by a portable diagnostical laser system with fibre optical probe output and excitation by compact semiconductor UV light source. The measurements were conducted in fresh brain tissue slices of Wistar rat pups. The fluorescence measurements were conducted simultaneously at intervals of 5 s by the microscopic system with excitation at 360 nm and registering of the emitted fluorescence light at 455 nm and by the tested diagnostical system equipped with the fibre optical probe with excitation at 365 nm and registration of the fluorescence spectrum by the inbuilt spectroscopic subsystem. To modulate the mitochondrial function in the living cells, in the chamber sequentially were added 1 μM FCCP and 1 mM NaCN. The comparisons between the curves registered by the methods allowed us to find well agreement between the microscopic measurements and measurements by the fibre optical probe. The obtained results prove that the tested diagnostic system is capable of sensing the changes in brain metabolic activity associated with the NADH content alterations within the physiological range

Nrf2 regulates glucose uptake and metabolism in neurons and astrocytes

The transcription factor Nrf2 and its repressor Keap1 mediate cell stress adaptation by inducing expression of genes regulating cellular detoxification, antioxidant defence and energy metabolism. Energy production and antioxidant defence employ NADH and NADPH respectively as essential metabolic cofactors; both are generated in distinct pathways of glucose metabolism, and both pathways are enhanced by Nrf2 activation. Here, we examined the role of Nrf2 on glucose distribution and the interrelation between NADH production in energy metabolism and NADPH homeostasis using glio-neuronal cultures isolated from wild-type, Nrf2-knockout and Keap1-knockdown mice. Employing advanced microscopy imaging of single live cells, including multiphoton fluorescence lifetime imaging microscopy (FLIM) to discriminate between NADH and NADPH, we found that Nrf2 activation increases glucose uptake into neurons and astrocytes. Glucose consumption is prioritized in brain cells for mitochondrial NADH and energy production, with a smaller contribution to NADPH synthesis in the pentose phosphate pathway for redox reactions. As Nrf2 is suppressed during neuronal development, this strategy leaves neurons reliant on astrocytic Nrf2 to maintain redox balance and energy homeostasis

α-synuclein oligomers interact with ATP synthase and open the permeability transition pore in Parkinson's disease.

Protein aggregation causes α-synuclein to switch from its physiological role to a pathological toxic gain of function. Under physiological conditions, monomeric α-synuclein improves ATP synthase efficiency. Here, we report that aggregation of monomers generates beta sheet-rich oligomers that localise to the mitochondria in close proximity to several mitochondrial proteins including ATP synthase. Oligomeric α-synuclein impairs complex I-dependent respiration. Oligomers induce selective oxidation of the ATP synthase beta subunit and mitochondrial lipid peroxidation. These oxidation events increase the probability of permeability transition pore (PTP) opening, triggering mitochondrial swelling, and ultimately cell death. Notably, inhibition of oligomer-induced oxidation prevents the pathological induction of PTP. Inducible pluripotent stem cells (iPSC)-derived neurons bearing SNCA triplication, generate α-synuclein aggregates that interact with the ATP synthase and induce PTP opening, leading to neuronal death. This study shows how the transition of α-synuclein from its monomeric to oligomeric structure alters its functional consequences in Parkinson's disease

Alpha synuclein aggregation drives ferroptosis: an interplay of iron, calcium and lipid peroxidation.

Protein aggregation and abnormal lipid homeostasis are both implicated in neurodegeneration through unknown mechanisms. Here we demonstrate that aggregate-membrane interaction is critical to induce a form of cell death called ferroptosis. Importantly, the aggregate-membrane interaction that drives ferroptosis depends both on the conformational structure of the aggregate, as well as the oxidation state of the lipid membrane. We generated human stem cell-derived models of synucleinopathy, characterized by the intracellular formation of α-synuclein aggregates that bind to membranes. In human iPSC-derived neurons with SNCA triplication, physiological concentrations of glutamate and dopamine induce abnormal calcium signaling owing to the incorporation of excess α-synuclein oligomers into membranes, leading to altered membrane conductance and abnormal calcium influx. α-synuclein oligomers further induce lipid peroxidation. Targeted inhibition of lipid peroxidation prevents the aggregate-membrane interaction, abolishes aberrant calcium fluxes, and restores physiological calcium signaling. Inhibition of lipid peroxidation, and reduction of iron-dependent accumulation of free radicals, further prevents oligomer-induced toxicity in human neurons. In summary, we report that peroxidation of polyunsaturated fatty acids underlies the incorporation of β-sheet-rich aggregates into the membranes, and that additionally induces neuronal death. This suggests a role for ferroptosis in Parkinson's disease, and highlights a new mechanism by which lipid peroxidation causes cell death

Inorganic Polyphosphate Modulates TRPM8 Channels

Polyphosphate (polyP) is an inorganic polymer built of tens to hundreds of phosphates, linked by high-energy phosphoanhydride bonds. PolyP forms complexes and modulates activities of many proteins including ion channels. Here we investigated the role of polyP in the function of the transient receptor potential melastatin 8 (TRPM8) channel. Using whole-cell patch-clamp and fluorescent calcium measurements we demonstrate that enzymatic breakdown of polyP by exopolyphosphatase (scPPX1) inhibits channel activity in human embryonic kidney and F-11 neuronal cells expressing TRPM8. We demonstrate that the TRPM8 channel protein is associated with polyP. Furthermore, addition of scPPX1 altered the voltage-dependence and blocked the activity of the purified TRPM8 channels reconstituted into planar lipid bilayers, where the activity of the channel was initiated by cold and menthol in the presence of phosphatidylinositol 4,5-biphosphate (PtdIns(4,5)P2). The biochemical analysis of the TRPM8 protein also uncovered the presence of poly-(R)-3-hydroxybutyrate (PHB), which is frequently associated with polyP. We conclude that the TRPM8 protein forms a stable complex with polyP and its presence is essential for normal channel activity

On Sea Ice Measurement by a C-Band Scatterometer at VV Polarization: Methodology Optimization Based on Computer Simulations

We consider sea ice and water microwave backscatter features at the C-band with vertical transmit and receive polarization and present a method for sea ice/water discrimination using a multiple fixed fan-beam satellite scatterometer. The method is based on the criterion of the minimum statistical distance of measured backscatter values to the sea ice and water (CMOD7) geophysical model functions. Implementation of the method is considered both for a typical three fan-beam geometry as well as for a potential five fan-beam geometry of a satellite scatterometer. By using computer simulations, we show explicitly that the number of looks at the same cell from different azimuthal directions needs to be increased to provide better (unambiguous) retrieval of the wind vector and sea ice/water discrimination. The algorithms for sea ice/water discrimination are described, and the results obtained are also discussed along with recommendations for the number of different azimuthal looks (beams) at the same cell from the point of view of sea ice/water discrimination as well as unambiguous wind direction retrieval during the satellite’s single pass

Pharmacological protection of the detoxification activity of animals’ liver with the help of phospholipid and polysaccharide nature substances complex

Currently, among chemical pollutants a significant danger to the health of animals and humans represent oxygen-containing nitrogen compounds nitrates and nitrites, which are widely used as mineral fertilizers. The article presents data on the study of chronic nitrate intoxication, reproduced in laboratory animals and its pharmacological correction with a complex of substances of phospholipid and polysaccharide nature. The introduction of sodium nitrate to non-linear rats for 30 days at a dose of 3.8 mg per animal leads to the development of intoxication in rats with dominant signs of liver damage. On this background, the use of the complex of beet fiber and rapeseed lecithin leads to a weakening of nitrate toxicosis, which is demonstrated by an increase in rats’ body weight, weakening of the clinical manifestations of intoxication, a decrease in cytolytic syndrome, intrahepatic cholestasis and impaired protein synthesis function of liver

A Data Normalization Technique for Detecting Cyber Attacks on UAVs

The data analysis subsystem of an Unmanned Aerial Vehicle (UAV) includes two main modules: a data acquisition module for data processing and a normalization module. One of the main features of an adaptive UAV protection system is the analysis of its cyber-physical parameters. An attack on a general-purpose computer system mainly affects the integrity, confidentiality and availability of important information. By contrast, an attack on a Cyber-Physical System (CPS), such as a UAV, affects the functionality of the system and may disrupt its operation, ultimately preventing it from fulfilling its tasks correctly. Cyber-physical parameters are the internal parameters of a system node, including the states of its computing resources, data storage, actuators and sensor system. Here, we develop a data normalization technique that additionally allows us to identify the signs of a cyber-attack. In addition, we define sets of parameters that can highlight an attack and define a new database format to support intrusion detection for UAVs. To achieve these goals, we performed an experimental study of the impact of attacks on UAV parameters and developed a software module for collecting data from UAVs, as well as a technique for normalizing and presenting data for detecting attacks on UAVs. Data analysis and the evaluation of the quality of a parameter (whether the parameter changes normally, or abrupt anomalous changes are observed) are facilitated by converting different types of data to the same format. The resulting formalized CPS model allows us to identify the nature of an attack and its potential impact on UAV subsystems. In the future, such a model could be the basis of a CPS digital twin in terms of security. The presented normalization technique supports processing raw data, as well as classifying data sets for their use in machine learning (ML) analyses in the future. The data normalization technique can also help to immediately determine the presence and signs of an attack, which allows classifying raw data automatically by dividing it into different categories. Such a technique could form the basis of an intrusion detection system for CPSs. Thus, the obtained results can be used to classify attacks, including attack detection systems based on machine learning methods, and the data normalization technique can be used as an independent method for detecting attacks