Block cipher based Public Key Encryption viaIndistinguishability Obfuscation

The article is devoted to generation techniques of thenew public key crypto-systems, which are based on applicationof indistinguishability obfuscation methods to selected privatekey crypto-systems. The techniques are applied to symmetrickey crypto-system and the target system is asymmetric one.As an input for our approach an implementation of symmetricblock cipher with a given private-key is considered. Differentobfuscation methods are subjected to processing. The targetsystem would be treated as a public-key for newly createdpublic crypto-system. The approach seems to be interestingfrom theoretical point of view. Moreover, it can be useful forinformation protection in a cloud-computing model

Confidential greedy graph algorithm

Confidential algorithm for the approximate graph vertex covering problem is presented in this article. It can preserve privacy of data at every stage of the computation, which is very important in context of cloud computing. Security of~our solution is based on fully homomorphic encryption scheme. The time complexity and the security aspects of considered algorithm are described

Peripheral Markers of Depression

Major Depressive Disorder (MDD) is a leading cause of disability worldwide, creating a high medical and socioeconomic burden. There is a growing interest in the biological underpinnings of depression, which are reflected by altered levels of biological markers. Among others, enhanced inflammation has been reported in MDD, as reflected by increased concentrations of inflammatory markers—C-reactive protein, interleukin-6, tumor necrosis factor-α and soluble interleukin-2 receptor. Oxidative and nitrosative stress also plays a role in the pathophysiology of MDD. Notably, increased levels of lipid peroxidation markers are characteristic of MDD. Dysregulation of the stress axis, along with increased cortisol levels, have also been reported in MDD. Alterations in growth factors, with a significant decrease in brain-derived neurotrophic factor and an increase in fibroblast growth factor-2 and insulin-like growth factor-1 concentrations have also been found in MDD. Finally, kynurenine metabolites, increased glutamate and decreased total cholesterol also hold promise as reliable biomarkers for MDD. Research in the field of MDD biomarkers is hindered by insufficient understanding of MDD etiopathogenesis, substantial heterogeneity of the disorder, common co-morbidities and low specificity of biomarkers. The construction of biomarker panels and their evaluation with use of new technologies may have the potential to overcome the above mentioned obstacles

Urine 3-Nitrotyrosine and Serum HDL as Potential Biomarkers of Depression

Depression (MDD) is a leading psychiatric entity worldwide, with a high impact on individual life and public health. In recent years, efforts have been made to elucidate its biological underpinnings. MDD biomarker research provides promise for a better understanding of the biochemical processes involved in its pathogenesis. Oxidative and nitrosative stress (O&NS) and lipid disturbances are reported as major factors favoring the occurrence of depression. A total of 29 patients with MDD and 30 healthy volunteers were examined using the Hamilton Depression Scale (HAM-D), the Hamilton Anxiety Scale (HAM-A), and the Beck Depression Inventory (BDI). Blood and urine were collected to search for potential MDD biomarkers. O&NS parameters and β-amyloid were assessed in the urine, while cholesterol fractions were assessed in the blood. The group of depressed patients was characterized by higher concentrations of urine superoxide dismutase (SOD), 3-nitrotyrosine (3-NT), catalase (CAT), reduced glutathione (GSH), tryptophan (TRY), and serum triglycerides (TGA), along with lower levels of serum high-density lipoprotein (HDL). Elevated urine 3-NT and decreased serum HDL, considered together, were found to have the greatest potential as markers of depression. The study supports the importance of oxidative stress and cholesterol disturbances in MDD. Further research is required to assess their clinical usefulness as markers

The Effect of Antidepressant Treatment on Neurocognitive Functions, Redox and Inflammatory Parameters in the Context of COVID-19

Inflammation is an important component of the etiopathology of depression that uses oxidative and nitrosative stress (O&NS) and elevated inflammatory markers. SARS-CoV-2 infection is also associated with abnormal inflammatory processes, which may impair effective treatment of depression in COVID-19 survivors. In the presented study, thirty-three hospitalized patients with major depressive disorder (MDD) were started on antidepressant treatment, and twenty-one were re-evaluated after 4–6 weeks. The control group consisted of thirty healthy volunteers. All participants underwent neuropsychiatric evaluation, biochemical blood and urine analyses. The results of the research demonstrated positive correlations of the Hamilton Depression Rating Scale (HAM-D) scores with serum catalase (CAT) and urinary S-Nitrosothiols levels, and the Beck Depression Inventory (BDI) scores with serum reduced glutathione (GSH) and superoxide dismutase (SOD) levels. Depressed patients with a history of COVID-19 prior to the treatment had higher urinary nitric oxide (NO) levels and lower serum glutathione peroxidase (GPx) levels. In the control group, COVID-19 survivors had higher levels of urinary N-formylkynurenine (NFK). Our results suggest that the antidepressant treatment has a modulating effect on O&NS, reduces depressive symptoms and improves cognitive functions The present study does not indicate that clinical response to antidepressant treatment is associated with COVID-19 history and baseline SARS-CoV-2 antibody levels. Nevertheless, further research in this area is needed to systematize antidepressant treatment in COVID-19 survivors

Salivary Carbohydrate-Deficient Transferrin in Alcohol- and Nicotine-Dependent Males

Serum carbohydrate-deficient transferrin (CDT), an 80 kDa glycoprotein, is one of the most commonly employed biomarkers to detect alcohol dependence. Some salivary glycoproteins such as α-amylase, clusterin, haptoglobin, light/heavy-chain immunoglobulin, and transferrin, which alter glycosylation in alcohol-dependent persons, have been suggested to be potential alcohol markers. However, their identification is based on indirect analysis of lectin glycosidic bonds and molecular weight. We investigated the CDT content in the saliva of alcohol- and nicotine-dependent men. The CDT concentration (ng/mL, ng/mg protein) was determined by an Enzyme-Linked Immunosorbent Assay (ELISA) commercial kit in 55 men: 20 healthy social drinkers (C), 10 chronic cigarette smokers (S), 10 alcohol-dependent non-smokers (A), and 15 alcohol-dependent smokers (AS). Surprisingly, there were no differences in the concentrations of CDT between the studied groups. Salivary pH was the lowest in the AS and the highest in the A group. Therefore, salivary CDT cannot be used as an alcohol dependence marker as measured by ELISA. We suggest that direct identification of glycoproteins is necessary to search for potential salivary alcohol biomarkers. Molecules smaller than 40 kDa, which easily translocate from blood to the saliva, might be preferred as salivary alcohol markers