NOS1AP Gene Variants and Their Role in Metabolic Syndrome: A Study of Patients with Schizophrenia.

Metabolic syndrome (MetS) is common among schizophrenia patients, and one of MetS's causes may be an imbalance in nitric oxide regulation. In this study, we examined associations of three polymorphic variants of the nitric oxide synthase 1 adapter protein (NOS1AP) gene with MetS in schizophrenia. NOS1AP regulates neuronal nitric oxide synthase, which controls intracellular calcium levels and may influence insulin secretion. The aim of the investigation was to study polymorphic variants of the NOS1AP gene as possible markers of MetS in patients with schizophrenia. A total of 489 Caucasian patients with schizophrenia (ICD-10) from Siberia (Russia) were included in the study, and 131 (26.8%) patients had MetS (IDF classification, 2007). The participants were genotyped for three single-nucleotide polymorphisms in NOS1AP (rs12143842, rs10494366, and rs12029454). Logistic regression was used for association analysis. Single-nucleotide polymorphisms, sex, and age served as covariates; the dependent variable was the coded parameter of the presence/absence of MetS. Polymorphisms rs12143842 and rs10494366 showed a stable association even after Bonferroni's correction for multiple comparisons (p = 0.005 and 0.002, respectively), indicating a statistically significant contribution of these polymorphic variants to the pathogenesis of MetS. Our results suggest that in patients with schizophrenia, NOS1AP may be involved in MetS pathophysiology.

Highly Effective Non-Noble MnO2 Catalysts for 5-Hydroxymethylfurfural Oxidation to 2,5-Furandicarboxylic Acid.

Noble metal-free catalyst or catalytic oxidation of 5-hydroxymethylfurfural into 2,5-furandicarboxylic acid are proposed in this study as a proposal to solve one of the great disadvantages of this reaction of using preferably noble metal-based catalysts. The catalytic activity of six MnO2 crystal structures is studied as alternative. The obtained results showed a strong connection between catalytic activity the type of MnO2 structure organization and redox behavior. Among all tested catalysts, ϵ-MnO2 showed the best performance with an excellent yield of 74 % of 2,5-furandicarboxylic acid at full -hydroxymethylfurfural conversion.

Complete genome sequence of Chlamydia psittaci АМК-16, isolated from a small ruminant in the Middle Volga Region, Russia.

We report the complete genome sequence of the Chlamydia psittaci АМК-16, recovered from the aborted caprine fetus during a case of chlamydia infection. This 1,152,497-bp genome with 7,552-bp cryptic plasmid provides novel insights into the genetic diversity of chlamydia agent strains particularly those causing the infection in small ruminants.

Untargeted Plasma Metabolomic Profiling in Patients with Depressive Disorders: A Preliminary Study.

Depressive disorder is a multifactorial disease that is based on dysfunctions in mental and biological processes. The search for biomarkers can improve its diagnosis, personalize therapy, and lead to a deep understanding of the biochemical processes underlying depression. The purpose of this work was a metabolomic analysis of blood serum to classify patients with depressive disorders and healthy individuals using Compound Discoverer software. Using high-resolution mass spectrometry, blood plasma samples from 60 people were analyzed, of which 30 were included in a comparison group (healthy donors), and 30 were patients with a depressive episode (F32.11) and recurrent depressive disorder (F33.11). Differences between patient and control groups were identified using the built-in utilities in Compound Discoverer software. Compounds were identified by their accurate mass and fragment patterns using the mzCloud database and tentatively identified by their exact mass using the ChemSpider search engine and the KEGG, ChEBI, FDA UNII-NLM, Human Metabolome and LipidMAPS databases. We identified 18 metabolites that could divide patients with depressive disorders from healthy donors. Of these, only two compounds were tentatively identified using the mzCloud database (betaine and piperine) based on their fragmentation spectra. For three compounds ((4S,5S,8S,10R)-4,5,8-trihydroxy-10-methyl-3,4,5,8,9,10-hexahydro-2H-oxecin-2-one, (2E,4E)-N-(2-hydroxy-2-methylpropyl)-2,4-tetradecadienamide and 17α-methyl-androstan-3-hydroxyimine-17ß-ol), matches were found in the mzCloud database but with low score, which could not serve as reliable evidence of their structure. Another 13 compounds were identified by their exact mass in the ChemSpider database, 9 (g-butyrobetaine, 6-diazonio-5-oxo-L-norleucine, 11-aminoundecanoic acid, methyl N-acetyl-2-diazonionorleucinate, glycyl-glycyl-argininal, dilaurylmethylamine, 12-ketodeoxycholic acid, dicetylamine, 1-linoleoyl-2-hydroxy-sn-glycero-3-PC) had only molecular formulas proposed, and 4 were unidentified. Thus, the use of Compound Discoverer software alone was not sufficient to identify all revealed metabolites. Nevertheless, the combination of the found metabolites made it possible to divide patients with depressive disorders from healthy donors.

A Water-Stable Boronate Ester Cage.

The reversible condensation of catechols and boronic acids to boronate esters is a paradigm reaction in dynamic covalent chemistry. However, facile backward hydrolysis is detrimental for stability and has so far prevented applications for boronate-based materials. Here, we introduce cubic boronate ester cages 6 derived from hexahydroxy tribenzotriquinacenes and phenylene diboronic acids with ortho-t-butyl substituents. Due to steric shielding, dynamic exchange at the Lewis acidic boron sites is feasible only under acid or base catalysis but fully prevented at neutral conditions. For the first time, boronate ester cages 6 tolerate substantial amounts of water or alcohols both in solution and solid state. The unprecedented applicability of these materials under ambient and aqueous conditions is showcased by efficient encapsulation and on-demand release of ß-carotene dyes and heterogeneous water oxidation catalysis after the encapsulation of ruthenium catalysts.

Fermentation of micro- and macroalgae as a way to produce value-added products.

Fermentation of both microalgae and macroalgae is one of the most efficient methods of obtaining valuable value-added products due to the minimal environmental pollution and the availability of economic benefits, as algae do not require arable land and drift algae and algal bloom biomass are considered waste and must be recycled and their fermentation waste utilized. The compounds found in algae can be effectively used in the fuel, food, cosmetic, and pharmaceutical industries, depending on the type of fermentation used. Products such as methane and hydrogen can be produced by anaerobic digestion and dark fermentation of algae, and lactic acid and its polymers can be produced by lactic acid fermentation of algae. Article aims to provide an overview of the different types potential of micro- and macroalgae fermentation, the advantages and disadvantages of each type considered, and the economic feasibility of algal fermentation for the production of various value-added products.

Size Determination of Organic Cages by Diffusion NMR Spectroscopy.

Reliable structure elucidation of covalent organic cage compounds remains challenging as routine analysis might leave ambiguities. Diffusion-ordered NMR spectroscopy (DOSY) allows insight into the molecular size and mass of the species present in solution, but a systematic evaluation of the diffusion behavior for cage assemblies is rarely considered. Here we report the synthesis of four series of covalent organic cages based on tribenzotriquinacenes and diboronic acids with varying geometry and exohedral substituents. We provide a guideline for the consistent measurement of diffusion coefficients from 1 H-DOSY NMR spectroscopy, which was utilized to study the diffusion behavior for the whole set of cages and selected examples from the literature. For structurally similar cages, a linear correlation between the solvodynamic volume and the molecular mass allows precise size determination. For more complex systems, multiple parameters, such as window size or rigid exohedral functionalization. further modulate cage diffusion in solution.

Artificial Intelligence Methods for the Construction and Management of Buildings.

Artificial intelligence covers a variety of methods and disciplines including vision, perception, speech and dialogue, decision making and planning, problem solving, robotics and other applications in which self-learning is possible. The aim of this work was to study the possibilities of using AI algorithms at various stages of construction to ensure the safety of the process. The objects of this research were scientific publications about the use of artificial intelligence in construction and ways to optimize this process. To search for information, Scopus and Web of Science databases were used for the period from the early 1990s (the appearance of the first publication on the topic) until the end of 2022. Generalization was the main method. It has been established that artificial intelligence is a set of technologies and methods used to complement traditional human qualities, such as intelligence as well as analytical and other abilities. The use of 3D modeling for the design of buildings, machine learning for the conceptualization of design in 3D, computer vision, planning for the effective use of construction equipment, artificial intelligence and artificial superintelligence have been studied. It is proven that automatic programming for natural language processing, knowledge-based systems, robots, building maintenance, adaptive strategies, adaptive programming, genetic algorithms and the use of unmanned aircraft systems allow an evaluation of the use of artificial intelligence in construction. The prospects of using AI in construction are shown.

Study of the polysaccharide production by the microalgae C-1509 Nannochloris sp. Naumann.

Biologically active compounds, including polysaccharides isolated from microalgae, have various properties. Although Nannochloropsis spp. have the potential to produce secondary metabolites important for biotechnology, only a small part of the research on these microalgae has focused on their ability to produce polysaccharide fractions. This study aims to evaluate the physicochemical growth factors of Nannochloropsis spp. microalgae, which ensure the maximum accumulation of polysaccharides, as well as to optimize the parameters of polysaccharide extraction. The optimal nutrient medium composition was selected to maximize biomass and polysaccharide accumulation. The significance of selecting the extraction module and extraction temperature regime, as well as the cultivation conditions (temperature and active acidity value) is emphasized. Important chemical components of polysaccharides responsible for their biological activity were identified.

Investigation of Inter- and Intra-Day Variability of Tear Fluid Regarding Flow Rate, Protein Concentration as well as Protein Composition.

Purpose: The purpose of this study was to present the determination of inter- and intra-day variations in tear flow rate, and tear fluid protein concentration, as well as protein composition regarding their impact for future biomarker studies. Methods: Tear fluid was collected noninvasively from 18 healthy subjects by performing Schirmer tests at 4 different time points repetitive in a period of 2 days. The tear flow rate on the Schirmer test strips was measured. Proteins were extracted from strips and quantified using amino acid analysis. Protein composition was analyzed by the strips data-independent (DIA) based mass spectrometry. To exclude any impairments to health, volunteers underwent a detailed neurological as well as an ophthalmological examination. Results: Whether tear fluid was collected from oculus sinister or oculus dexter did not affect the tear flow rate (P ≈ 0.63) or protein concentration (P ≈ 0.97) of individual subjects. Moreover, protein concentration was independent from the tear volume, so that a change in volume may only influence the total protein amount. When the examination days were compared, investigation of tear flow rate (P ≈ 0.001) and protein concentration (P ≈ 0.0003) indicated significant differences. Further, mass spectrometric analysis of tear fluid revealed 11 differentially regulated proteins when comparing both examination days. Conclusions: Our findings provide evidence of inter-day variation in tear flow rate, tear proteome concentration, and composition in healthy subjects, suggesting that inter-day variation needs to be taken into consideration in biomarker research of tear fluid. Identified proteins were assigned to functions in the immune response, oxidative and reducing processes, as well as mannose metabolism.

Differential Expression of Proteins Associated with Bipolar Disorder as Identified Using the PeptideShaker Software.

The prevalence of bipolar disorder (BD) in modern society is growing rapidly, but due to the lack of paraclinical criteria, its differential diagnosis with other mental disorders is somewhat challenging. In this regard, the relevance of proteomic studies is increasing due to the development of methods for processing large data arrays; this contributes to the discovery of protein patterns of pathological processes and the creation of new methods of diagnosis and treatment. It seems promising to search for proteins involved in the pathogenesis of BD in an easily accessible material-blood serum. Sera from BD patients and healthy individuals were purified via affinity chromatography to isolate 14 major proteins and separated using 1D SDS-PAGE. After trypsinolysis, the proteins in the samples were identified via HPLC/mass spectrometry. Mass spectrometric data were processed using the OMSSA and X!Tandem search algorithms using the UniProtKB database, and the results were analyzed using PeptideShaker. Differences in proteomes were assessed via an unlabeled NSAF-based analysis using a two-tailed Bonferroni-adjusted t-test. When comparing the blood serum proteomes of BD patients and healthy individuals, 10 proteins showed significant differences in NSAF values. Of these, four proteins were predominantly present in BD patients with the maximum NSAF value: 14-3-3 protein zeta/delta; ectonucleoside triphosphate diphosphohydrolase 7; transforming growth factor-beta-induced protein ig-h3; and B-cell CLL/lymphoma 9 protein. Further exploration of the role of these proteins in BD is warranted; conducting such studies will help develop new paraclinical criteria and discover new targets for BD drug therapy.

Canagliflozin, an Inhibitor of the Na+-Coupled D-Glucose Cotransporter, SGLT2, Inhibits Astrocyte Swelling and Brain Swelling in Cerebral Ischemia.

Brain swelling is a major cause of death and disability in ischemic stroke. Drugs of the gliflozin class, which target the Na+-coupled D-glucose cotransporter, SGLT2, are approved for type 2 diabetes mellitus (T2DM) and may be beneficial in other conditions, but data in cerebral ischemia are limited. We studied murine models of cerebral ischemia with middle cerebral artery occlusion/reperfusion (MCAo/R). Slc5a2/SGLT2 mRNA and protein were upregulated de novo in astrocytes. Live cell imaging of brain slices from mice following MCAo/R showed that astrocytes responded to modest increases in D-glucose by increasing intracellular Na+ and cell volume (cytotoxic edema), both of which were inhibited by the SGLT2 inhibitor, canagliflozin. The effect of canagliflozin was studied in three mouse models of stroke: non-diabetic and T2DM mice with a moderate ischemic insult (MCAo/R, 1/24 h) and non-diabetic mice with a severe ischemic insult (MCAo/R, 2/24 h). Canagliflozin reduced infarct volumes in models with moderate but not severe ischemic insults. However, canagliflozin significantly reduced hemispheric swelling and improved neurological function in all models tested. The ability of canagliflozin to reduce brain swelling regardless of an effect on infarct size has important translational implications, especially in large ischemic strokes.

Serum Levels of S100B Protein and Myelin Basic Protein as a Potential Biomarkers of Recurrent Depressive Disorders.

Nowadays, nervous tissue damage proteins in serum are considered promising drug targets and biomarkers of Mood Disorders. In a cross-sectional naturalistic study, the S100B, MBP and GFAP levels in the blood serum were compared between two diagnostic groups (patients with Depressive Episode (DE, n = 28) and patients with Recurrent Depressive Disorder (RDD, n = 21)), and healthy controls (n = 25). The diagnostic value of serum markers was assessed by ROC analysis. In the DE group, we did not find changed levels of S100B, MBP and GFAP compared with controls. In the RDD group, we found decreased S100B level (p = 0.011) and increased MBP level (p = 0.015) in comparison to those in healthy controls. Provided ROC analysis indicates that MBP contributes to the development of a DE (AUC = 0.676; 95%Cl 0.525-0.826; p = 0.028), and S100B and MBP have a significant effect on the development of RDD (AUC = 0.732; 95%Cl 0.560-0.903; p = 0.013 and AUC = 0.712; 95%Cl 0.557-0.867; p = 0.015, correspondingly). The study of serum markers of nervous tissue damage in patients with a current DE indicates signs of disintegration of structural and functional relationships, dysfunction of gliotransmission, and impaired secretion of neurospecific proteins. Modified functions of astrocytes and oligodendrocytes are implicated in the pathophysiology of RDD.

Study of the Effect of Baicalin from Scutellaria baicalensis on the Gastrointestinal Tract Normoflora and Helicobacter pylori.

The antimicrobial properties of baicalin against H. pylori and several probiotic cultures were evaluated. Baicalin was isolated from a dry plant extract obtained by extraction with water at 70 °C. For isolation, extraction was carried out with n-butanol and purification on a chromatographic column. The antimicrobial potential was assessed by evaluating changes in the optical density of the bacterial suspension during cultivation; additionally, the disk diffusion method was used. During the study, the baicalin concentrations (0.25, 0.5, and 1 mg/mL) and the pH of the medium in the range of 1.5-8.0 were tested. The test objects were: suspensions of H. pylori, Lactobacillus casei, L. brevis, Bifidobacterium longum, and B. teenis. It was found that the greater the concentration of the substance in the solution, the greater the delay in the growth of the strain zone. Thus, the highest antimicrobial activity against H. pylori was observed at pH 1.5-2.0 and a baicalin concentration of 1.00 mg/mL. In relation to probiotic strains, a stimulating effect of baicalin (1.00 mg/mL) on the growth of L. casei biomass at pH 1.5-2.0 was observed. The results open up the prospects for the use of baicalin and probiotics for the treatment of diseases caused by H. pylori.

Building Predictive Models for Schizophrenia Diagnosis with Peripheral Inflammatory Biomarkers.

Machine learning and artificial intelligence technologies are known to be a convenient tool for analyzing multi-domain data in precision psychiatry. In the case of schizophrenia, the most commonly used data sources for such purposes are neuroimaging, voice and language patterns, and mobile phone data. Data on peripheral markers can also be useful for building predictive models. Here, we have developed five predictive models for the binary classification of schizophrenia patients and healthy individuals. Data on serum concentrations of cytokines, chemokines, growth factors, and age were among 38 parameters used to build these models. The sample consisted of 217 schizophrenia patients and 90 healthy individuals. The models architecture was involved logistic regression, deep neural networks, decision trees, support vector machine, and k-nearest neighbors algorithms. It was shown that the algorithm based on a deep neural network (consisting of five layers) showed a slightly higher sensitivity (0.87 ± 0.04) and specificity (0.52 ± 0.06) than other algorithms. Combining all variables into a single classifier showed a cumulative effect that exceeded the effectiveness of individual variables, indicating the need to use multiple biomarkers to diagnose schizophrenia. Thus, the data obtained showed the promise of using data on peripheral biomarkers and machine learning methods for diagnosing schizophrenia.

Association of Single Nucleotide Polymorphisms of Cytokine Genes with Depression, Schizophrenia and Bipolar Disorder.

Immune gene variants are known to be associated with the risk of psychiatric disorders, their clinical manifestations, and their response to therapy. This narrative review summarizes the current literature over the past decade on the association of polymorphic variants of cytokine genes with risk, severity, and response to treatment for severe mental disorders such as bipolar disorder, depression, and schizophrenia. A search of literature in databases was carried out using keywords related to depressive disorder, bipolar disorder, schizophrenia, inflammation, and cytokines. Gene lists were extracted from publications to identify common genes and pathways for these mental disorders. Associations between polymorphic variants of the IL1B, IL6, and TNFA genes were the most replicated and relevant in depression. Polymorphic variants of the IL1B, IL6, IL6R, IL10, IL17A, and TNFA genes have been associated with schizophrenia. Bipolar disorder has mainly been associated with polymorphic variants of the IL1B gene. Interestingly, the IL6R gene polymorphism (rs2228145) was associated with all three diseases. Some cytokine genes have also been associated with clinical presentation and response to pharmacotherapy. There is also evidence that some specific polymorphic variants may affect the expression of cytokine genes. Thus, the data from this review indicate a link between neuroinflammation and severe mental disorders.

Mitigation of galvanized steel biocorrosion by Pseudomonas aeruginosa biofilm using a biocide enhanced by trehalase.

Pseudomonas aeruginosa is a facultative bacterium that is pathogenic. It is ubiquitous in the environment including air handling systems. It causes microbiologically influenced corrosion (MIC) aerobically and anaerobically. In this work, P. aeruginosa was grown as a nitrate reducing bacterium (NRB) in Luria-Bertani medium with KNO3 at 37 °C. Trehalase, an enzyme which plays a crucial role in biofilm formation was found to enhance the treatment of P. aeruginosa biofilm and its MIC against galvanized steel by tetrakis-hydroxymethyl phosphonium sulfate (THPS) green biocide. After a 7-d incubation, 30 ppm (w/w) trehalase reduced sessile cell count by 0.8-log, and it also reduced galvanized steel weight loss by 14%, compared to 2.3-log and 39%, respectively for the 30 ppm THPS treatment. The combination of 30 ppm THPS + 30 ppm trehalase reduced sessile cell count further by 0.1-log and weight loss by 13% compared to using THPS alone. Electrochemical corrosion measurements supported weight loss results. The injection of 20 ppm riboflavin into a 3-d P. aeruginosa broth failed to accelerate the corrosion rate, suggesting that nitrate reducing P. aeruginosa MIC of galvanized steel did not belong to extracellular electron transfer-MIC, because Zn was hydrolyzed after the microbe damaged the passive film.

Cation flux through SUR1-TRPM4 and NCX1 in astrocyte endfeet induces water influx through AQP4 and brain swelling after ischemic stroke.

Brain swelling causes morbidity and mortality in various brain injuries and diseases but lacks effective treatments. Brain swelling is linked to the influx of water into perivascular astrocytes through channels called aquaporins. Water accumulation in astrocytes increases their volume, which contributes to brain swelling. Using a mouse model of severe ischemic stroke, we identified a potentially targetable mechanism that promoted the cell surface localization of aquaporin 4 (AQP4) in perivascular astrocytic endfeet, which completely ensheathe the brain's capillaries. Cerebral ischemia increased the abundance of the heteromeric cation channel SUR1-TRPM4 and of the Na+/Ca2+ exchanger NCX1 in the endfeet of perivascular astrocytes. The influx of Na+ through SUR1-TRPM4 induced Ca2+ transport into cells through NCX1 operating in reverse mode, thus raising the intra-endfoot concentration of Ca2+. This increase in Ca2+ stimulated calmodulin-dependent translocation of AQP4 to the plasma membrane and water influx, which led to cellular edema and brain swelling. Pharmacological inhibition or astrocyte-specific deletion of SUR1-TRPM4 or NCX1 reduced brain swelling and improved neurological function in mice to a similar extent as an AQP4 inhibitor and was independent of infarct size. Thus, channels in astrocyte endfeet could be targeted to reduce postischemic brain swelling in stroke patients.

The Influence of Antipsychotic Treatment on the Activity of Abzymes Targeting Myelin and Levels of Inflammation Markers in Patients with Schizophrenia.

Catalytic antibodies, or abzymes, are capable of not only binding but also hydrolyzing various proteins. Previously, an increase in the level of myelin basic protein (MBP)-hydrolyzing activity of antibodies was shown in patients with a number of neurological and mental disorders, including schizophrenia. Furthermore, antipsychotic therapy is known to induce a change in cytokine levels in patients with schizophrenia, which affects regulation of the immune response and inflammatory status. This study investigated the influence of typical and atypical antipsychotics on catalytic antibody activity and the 10 major pro- and anti-inflammatory serum cytokine levels. The study included 40 patients with schizophrenia: 15 treated with first-generation antipsychotics and 25 treated with atypical antipsychotics for 6 weeks. It was found that treatment with atypical antipsychotics changed the levels of some pro-inflammatory cytokines. Antipsychotic therapy also caused a significant decrease in MBP-hydrolyzing activity in patients with schizophrenia (p = 0.0002), and associations of catalytic activity with interleukins were observed.

Association of Peripheral Inflammatory Biomarkers and Growth Factors Levels with Sex, Therapy and Other Clinical Factors in Schizophrenia and Patient Stratification Based on These Data.

Multiple lines of evidence are known to confirm the pro-inflammatory state of some patients with schizophrenia and the involvement of inflammatory mechanisms in the pathogenesis of psychosis. The concentration of peripheral biomarkers is associated with the severity of inflammation and can be used for patient stratification. Here, we analyzed changes in serum concentrations of cytokines (IL-1ß, IL-2, IL-4, IL-6, IL-10, IL-21, APRIL, BAFF, PBEF/Visfatin, IFN-α, and TNF-α) and growth/neurotrophic factors (GM-CSF, NRG1-ß1, NGF-ß, and GDNF) in patients with schizophrenia in an exacerbation phase. IL-1ß, IL-2, IL-4, IL-6, BAFF, IFN-α, GM-CSF, NRG1-ß1, and GDNF increased but TNF-α and NGF-ß decreased in schizophrenia compared to healthy individuals. Subgroup analysis revealed the effect of sex, prevalent symptoms, and type of antipsychotic therapy on biomarker levels. Females, patients with predominantly negative symptoms, and those taking atypical antipsychotics had a more pro-inflammatory phenotype. Using cluster analysis, we classified participants into "high" and "low inflammation" subgroups. However, no differences were found in the clinical data of patients in these subgroups. Nevertheless, more patients (17% to 25.5%) than healthy donors (8.6% to 14.3%) had evidence of a pro-inflammatory condition depending on the clustering approach used. Such patients may benefit from personalized anti-inflammatory therapy.