Search

Zeolites with different structures (P1, sodalite, and X) were synthesized from coal fly ash by applying ultrasonically assisted hydrothermal and fusion–hydrothermal synthesis. Bimetallic catalysts, containing 5 wt.% Ni and 2.5 wt.% Cu, supported on the zeolites, were prepared by a post-synthesis incipient wetness impregnation method. The catalysts were characterized by X-ray powder diffraction (XRPD), N2 physisorption, transmission electron microscopy (TEM), Mössbauer and X-ray photoelectron spectroscopies (XPS), and H2–temperature-programmed reduction (H2-TPR) analyses. The XRPD results showed that crystalline Cu0 and NixCuy intermetallic nanoparticles were formed in the reduced catalysts. The presence of the intermetallic phase affected the reducibility of the nickel by shifting it to a lower temperature, as confirmed by the H2-TPR curves. Based on the Mössbauer spectroscopic results, it was established that the iron contamination of the coal fly ash zeolites (CFAZs) was distributed in ionic positions of the zeolite lattice and as a finely dispersed iron oxide phase on the external surface of the supports. The formation of the NiFe alloy, not detectable by XRPD, was also evidenced on the impregnated samples. The catalysts were studied in the upgrading of levulinic acid (LA), derived from lignocellulosic biomass, to γ-valerolactone (GVL), in a batch reactor under 30 bar H2 pressure at 150 and 200 °C, applying water as a solvent. The NiCu/SOD and NiCu/X catalysts showed total LA conversion and a high GVL yield (>75%) at a reaction temperature of 200 °C. It was found that the textural parameters of the catalysts have less influence on the catalytic activity, but rather the stable dispersion of metals during the reaction. The characterization of the spent catalyst found the rearrangement of the support structure. The high LA conversion and GVL yield can be attributed to the weak acidic character of the support and the moderate hydrogenation activity of the Ni-Cu sites with high dispersion.

Objectives: SARS-CoV-2 caused the COVID-19 pandemic, which overwhelmed global healthcare systems. Over 776 million COVID-19 cases and more than 7 million deaths were reported by WHO in September 2024. COVID-19 vaccination is crucial for preventing infection and controlling the pandemic. Here, we describe the design and development of a next-generation multi-epitope vaccine for SARS-CoV-2, consisting of T cell epitopes. Methods: Immunoinformatic methods were used to derive models for the selection of MHC binders specific for the mouse strain used in this study among a set of human SARS-CoV-2 T cell epitopes identified in convalescent patients with COVID-19. The immunogenicity of the vaccine prototype was tested on humanized-ACE2 transgenic B6.Cg-Tg(K18-ACE2)2Prlmn/J mice by in vitro, in vivo, and ex vivo immunoassays. Results: Eleven binders (two from the Envelope (E) protein; two from the Membrane (M) protein; three from the Spike (S) protein; and four from the Nucleocapsid (N) protein) were synthesized and included in a multi-epitope vaccine prototype. The animals were immunized with a mix of predicted MHC-I, MHC-II, or MHC-I/MHC-II peptide epitopes in Complete Freund’s Adjuvant, and boosted with peptides in Incomplete Freund’s Adjuvant. Immunization with SARS-CoV-2 epitopes remodeled the lymphocyte profile. A weak humoral response and the significant production of IL-4 and IFN-γ from T cells were found after the vaccination of the animals. Conclusions: The multi-epitope vaccine prototype presented in this study demonstrates immunogenicity in mice and shows potential for human vaccine construction.

The drop-shipping method is an innovative alternative to the traditional supply chain, rooted in the principles of e-commerce. Drop-shipping has gained increasing popularity over the years. The main objective of this research is to identify the key factors and conditions for its implementation as part of the traditional supply chain. An empirical study was conducted among Bulgarian Small and Medium-sized Enterprises (SMEs) from various industries using survey and interview methods to gather the necessary data. Descriptive analysis was employed to examine the characteristics and distribution of the studied variables. Furthermore, regression analysis was conducted to explore the influence of various factors on delivery times and the average number of annual sales. Additionally, a correlation analysis was performed to examine the relationships between suppliers, delivery times, and levels of customer satisfaction when implementing the drop-shipping method. A variation analysis was also carried out to delve into the connections and changes between the two categories of factors – supplier-related and customer-related. The data from this study can serve as guidelines for implementing new innovative delivery methods within SMEs, aiming to provide the necessary factors and conditions for their successful operation.

Peanut allergy, a prevalent and potentially severe condition affecting millions worldwide, has been linked to specific human leukocyte antigens (HLAs), suggesting increased susceptibility. Employing an immunoinformatic strategy, we developed a “logo model” based on amino acid frequencies in the peptide binding core and used it to predict peptides originating from 28 known peanut allergens binding to HLA-DRB1*03:01, one of the susceptibility alleles. These peptides hold promise for immunotherapy in HLA-DRB1*03:01 carriers, offering reduced allergenicity compared to whole proteins. By targeting essential epitopes, immunotherapy can modulate immune responses with minimal risk of severe reactions. This precise approach could induce immune tolerance with fewer adverse effects, presenting a safer and more effective treatment for peanut allergy and other allergic conditions.

Error in Figure [...]

The identification and characterization of immunogenic tumor antigens are essential for cancer vaccine development. In light of the impracticality of isolating and evaluating each putative antigen individually, in silico prediction algorithms, particularly those utilizing machine learning (ML) approaches, play a pivotal role. These algorithms significantly reduce the experimental workload necessary for discovering vaccine candidates. In this study, we employed six supervised ML methods on a dataset comprising 212 experimentally validated human tumor peptide antigens and an equal number of non-antigenic human peptides to develop models for immunogenicity prediction. These methods encompassed k-nearest neighbor (kNN), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost). The models underwent validation through internal cross-validation within 10 groups from the training set and were further assessed using an external test set. Remarkably, the kNN model demonstrated superior performance, recognizing 90% of the known immunogens in the test set. The RF model excelled in the identification of non-immunogens, accurately classifying 93% of them in the test set. The three top-performing ML models according to multiple evaluation metrics (SVM, RF, and XGBoost) are to be subsequently integrated into the new version of the VaxiJen server, facilitating tumor antigen prediction through a majority voting mechanism.

Epidermoid and dermoid cysts are slow-developing formations of ectodermal origin and their most common location is underneath the skin. Epidermoid cysts of the jaw bones are extremely rare, with only several cases documented in the dental literature. Their most common intraoral location is the floor of the oral cavity, the tongue, lips, palate and cheeks. They are slow-growing painless formations, usually discovered incidentally when imaging scans, as well as histopathological examinations, are performed. A patient sought assistance from us, presenting with painful swelling in the right side of the mandible, without added infection. The radiograph and the CBCT scans revealed a lesion in the region of tooth #48, extending halfway into the mandibular ramus, which was surgically removed under general anesthesia. The surgical technique was cystectomy- complete removal of the cyst with the fibrous capsule. The mucosa above the bone defect is then tightly sealed. The histopathology report described an epidermal cyst. It follows that this type of lesions, though extremely uncommon in the jaw bones, must be considered in the differential diagnosis with odontogenic cysts like follicular odontogeneic cyst and odontogeneic keratocyst.

Blockchain technology is recognised as a digital tool that contributes to increasing the competitiveness of a business organisation, and it is most often applied in the financial sector and supply chains. The technology is widely used in developed countries, but it is also gradually entering developing economies. Attention to technology is provoked under the influence of factors determining innovation development and penetration into the entrepreneurial ecosystem. Some of them are psychological, the others are economical, but in general, they influence the management decision-making to use the technology in the enterprises. The primary purpose of the research is to reveal and group the factors provoking the implementation of blockchain technology in Bulgarian companies. In order to collect the necessary data, an empirical study of the Bulgarian entrepreneurial ecosystem was conducted using a survey method. A factor analysis of the two groups of reasons motivating and limiting the application of blockchain technology was performed with a view to uncovering the hidden factors influencing its implementation in organisations. A regression analysis was then performed to answer the question of which factors most affect the interest in implementing BCT in the business organisation to increase their competitiveness in the supply chain. The research data can be used as a working framework for implementing decentralised software applications in companies that are not informed about the pros and cons of blockchain technology but are looking for a position in the global digitised world.

Peptide–protein interactions form a cornerstone in molecular biology, governing cellular signaling, structure, and enzymatic activities in living organisms. Improving computational models and experimental techniques to describe and predict these interactions remains an ongoing area of research. Here, we present a computational method for peptide–protein interactions’ description and prediction based on leveraged amino acid frequencies within specific binding cores. Utilizing normalized frequencies, we construct quantitative matrices (QMs), termed ‘logo models’ derived from sequence logos. The method was developed to predict peptide binding to HLA-DQ2.5 and HLA-DQ8.1 proteins associated with susceptibility to celiac disease. The models were validated by more than 17,000 peptides demonstrating their efficacy in discriminating between binding and non-binding peptides. The logo method could be applied to diverse peptide–protein interactions, offering a versatile tool for predictive analysis in molecular binding studies.

Monometallic (Ni, Co, Cu) and bimetallic (Ni-Co, Ni-Cu) 10–20 wt.% metal containing catalysts supported on fly ash zeolite were prepared by post-synthesis impregnation method. The catalysts were characterized by X-ray powder diffraction, N2 physisorption, XPS and H2-TPR methods. Finely dispersed metal oxides and mixed oxides were detected after the decomposition of the impregnating salt on the relevant zeolite support. Via reduction intermetallic, NiCo and NiCu phases were identified in the bimetallic catalysts. The catalysts were studied in hydrodeoxygenation of lignocellulosic biomass-derived levulinic acid to γ-valerolactone (GVL) in a batch system by water as a solvent. Bimetallic, 10 wt.% Ni, and 10 wt.% Cu or Co containing fly ash zeolite catalysts showed higher catalytic activity than monometallic ones. Their selectivity to GVL reached 70–85% at about 100% conversion. The hydrogenation activity of catalysts was found to be stronger compared to their hydration ability; therefore, the reaction proceeds through formation of 4-hydroxy pentanoic acid as the only intermediate compound.

Human leukocyte antigens (HLAs) are pivotal in antigen processing, presenting to CD4+ T cells, and are linked to autoimmune disease susceptibility. In celiac disease, HLA-DQ2.5 and HLA-DQ8.1 bind gluten peptides on APCs, some recognized by CD4+ T cells, prompting inflammation and tissue damage. While extensively studied experimentally, these alleles lack comprehensive in silico analysis. To explore peptide–HLA preferences, we used molecular docking on peptide libraries, deriving quantitative matrices (QMs) for evaluating amino acids at nine-residue peptide binding cores. Our findings tie specific residue preferences to peptide backbone conformations. Validating QMs on known binders and non-binders showed strong predictive power (89–94% accuracy). These QMs excel in screening protein libraries, even whole proteomes, notably reducing time and costs for celiac disease risk assessment in novel proteins. This computational approach aligns with European Food Safety Authority guidance, promising efficient screening for potential celiac disease triggers.

Синдромът на Dyke-Davidoff-Masson представлява съчетание на мозъчна хемиатрофия с контралатерален двигателен дефицит, лицева асиметрия и епилептични пристъпи. Образната диагностика е ключова за диагностицирането му, като освен хемисферната хипоплазия, находките включват дилатация ex vacuo на латералния вентрикул, ипсилатерална хиперпневматизация на околоносните синуси и хипертрофия на черепните кости. По-голямата част от съвременните случаи са описани в детската възраст при пациенти с обсъждана диагноза детска церебрална парализа, а описания в литературата при възрастни се срещат рядко. В настоящата статия е представен клиничен случай, демонстри ращ синдрома при жена на 59 години с ДЦП, епилепсия и умствена изостаналост с начало в детска възраст, както и с типична находка от проведената компютърна томография на главен мозък. Синдромът би трябвало да се обсъжда при пациенти, които имат типичната клинична картина, макар и в зряла възраст, като се търси потвърждение чрез провеждане на компютърна или магнитно-резонансна томография на главен мозък.

Неврологичните заболявания, изявени с епилептични и когнитивни нарушения, изискват изключване на структурни мозъчни промени. Сред тях са случаите на компенсирана хидроцефалия с повишено ликворно налягане, при които минимални отключващи фактори могат да доведат до декомпенсация. Променената динамика на цереброспиналния ликвор е условие за по-голяма уязвимост на мозъка от свързани с възрастта промени, с по-бърз когнитивен регрес. В литературата се обсъжда несъответствието между степента на структурните промени и клиничните прояви. В настоящата работа е представен клиничен случай на пациент, хоспитализиран по повод получен по време на сън двустранен тонично-клоничен пристъп, след който бил сънлив и объркан за няколко часа. При компютърна томография на главен мозък е установена хронична високостепенна хидроцефалия с обструкция на акведукта. Пациентът е насочен за оперативно лечение. Клиничният случай демонстрира епилептичен пристъп като повод за образна диагностика при високостепенна хидроцефалия. Представеното несъответствие между промените в мозъчните структури и цялостно съхраненото когнитивно състояние се разглежда като пример за компенсаторните възможности на мозъка и значението на невропластичността.

By assessing basic agro-technical factors, optimal decisions can be made for good agricultural practice on soils with heavy soil texture, such as the Haplic Vertisols. The aim of the study is to identify the changes in the physical and agrochemical status of Haplic Vertisols that occur under the influence of applied agro-technical measures. For the achievement of the purpose in the period 2016 -2019, field experiments, based on the block method in the Sofia Region on a Haplic Vertisols were carried out. The study found out that soil moisture was a major limiting factor for crop development. The soil moisture content is influenced by the type of soil tillage, although the density of the weeds is also less affected by the parameter. The bulk density of the Haplic Vertisols is inversely correlated with the soil moisture content. In the case of deep loosening of maize, its values are reduced compared to those with plowing. Lower values were found for the parameter after plowing as a pre-sowing treatment for wheat, compared to the variants with disking. The applied fertilization mainly affects the content of nitrate and ammonium nitrogen, the phosphorus forms remain with low values, it is clearly necessary to raise the norm and with a methodical approach it is necessary to achieve a sustainable level of absorbed phosphates. The content of the absorbed potassium is still satisfactory, and based on the data from the analysis, its reduction and export with the produced products are smaller.

Injurious pecking (IP) represents a serious concern for the welfare of laying hens (Gallus gallus domesticus). The risk of IP among hens with intact beaks in cage-free housing prompts a need for solutions based on an understanding of underlying mechanisms. In this review, we explore how behavioural programming via prenatal and early postnatal environmental conditions could influence the development of IP in laying hens. The possible roles of early life adversity and mismatch between early life programming and subsequent environmental conditions are considered. We review the role of maternal stress, egg conditions, incubation settings (temperature, light, sound, odour) and chick brooding conditions on behavioural programming that could be linked to IP. Brain and behavioural development can be programmed by prenatal and postnatal environmental conditions, which if suboptimal could lead to a tendency to develop IP later in life, as we illustrate with a Jenga tower that could fall over if not built solidly. If so, steps taken to optimise the environmental conditions of previous generations and incubation conditions, reduce stress around hatching, and guide the early learning of chicks will aid in prevention of IP in commercial laying hen flocks.

Acetylcholinesterase (AChE) is one of the classical targets in the treatment of Alzheimer’s disease (AD). Inhibition of AChE slows down the hydrolysis of acetycholine and increases choline levels, improving the cognitive function. The achieved success of plant-based natural drugs acting as AChE inhibitors, such as galantamine (GAL) from Galanthus genus and huperzine A from Huperzia serrate (approved drug in China), in the treatment of AD, and the fact that natural compounds (NCs) are considered as safer and less toxic compared to synthetic drugs, led us to screen the available NCs (almost 150,000) in the ZINC12 database for AChE inhibitory activity. The compounds were screened virtually by molecular docking, filtered for suitable ADME properties, and 32 ligands from 23 structural groups were selected. The stability of the complexes was estimated via 1 μs molecular dynamics simulation. Ten compounds formed stable complexes with the enzyme and had a vendor and a reasonable price per mg. They were tested for AChE inhibitory and antioxidant activity. Five compounds showed weak AChE inhibition and three of them exhibited high antioxidant activity.

Sickness can change our mood for the worse, leaving us sad, lethargic, grumpy and less socially inclined. This mood change is part of a set of behavioral symptoms called sickness behavior and has features in common with core symptoms of depression. Therefore, the physiological changes induced by immune activation, for example following infection, are in the spotlight for explaining mechanisms behind mental health challenges such as depression. While humans may take a day off and isolate themselves until they feel better, farm animals housed in groups have only limited possibilities for social withdrawal. We suggest that immune activation could be a major factor influencing social interactions in pigs, with outbreaks of damaging behavior such as tail biting as a possible result. The hypothesis presented here is that the effects of several known risk factors for tail biting are mediated by pro-inflammatory cytokines, proteins produced by the immune system, and their effect on neurotransmitter systems. We describe the background for and implications of this hypothesis.

Chronic neurotoxicity of lead is a major problem in all countries around the world. Long-term exposure to lead in the environment has recently become of interest as a possible risk factor for cognitive impairment in workers exposed to lead. The consequences for the brain after cessation of the exposure are also subject to research. The aims of our study were: to investigate and analyze cognitive impairment in workers in professional contact with lead. For the purpose of the study, a total of 72 workers in chronic professional contact with lead aerosols were examined. The investigated men (n = 72) were aged 39.4 ± 10.4 (19 - 58) years with an average duration of service of 13.0 ± 8.7 (1 - 33) years and mean lead concentration in blood of 43.4 ± 9.0 μg / dl. The screening set included a subjective cognitive impairment survey, a depression scale, a set of cognitive tests (MMSE, IST, DRT, CDT), and a scale for activities of daily living (4-IADL Score). With the increase of lead levels in the blood, a statistically reliable trend is observed for decrease of MMSE, IST and CDT scores. Eleven of the screened individuals (15.28%) achieved a score of

The inhibition of the enzyme acetylcholinesterase (AChE) increases the levels of the neurotransmitter acetylcholine and symptomatically improves the affected cognitive function. In the present study, we searched for novel AChE inhibitors by docking-based virtual screening of the standard lead-like set of ZINC database containing more than 6 million small molecules using GOLD software. The top 10 best-scored hits were tested in vitro for AChE affinity, neurotoxicity, GIT and BBB permeability. The main pharmacokinetic parameters like volume of distribution, free fraction in plasma, total clearance, and half-life were predicted by previously derived models. Nine of the compounds bind to the enzyme with affinities from 0.517 to 0.735 µM, eight of them are non-toxic. All hits permeate GIT and BBB and bind extensively to plasma proteins. Most of them are low-clearance compounds. In total, seven of the 10 hits are promising for further lead optimisation. These are structures with ZINC IDs: 00220177, 44455618, 66142300, 71804814, 72065926, 96007907, and 97159977.

Oleraceins are a class of indoline amide glycosides found in Portulaca oleracea L. (Portulacaceae), or purslane. These compounds are characterized by 5,6-dihydroxyindoline-2-carboxylic acid N-acylated with cinnamic acid derivatives, and many are glucosylated. Herein, hydromethanolic extracts of the aerial parts of purslane were subjected to UHPLC-Orbitrap-MS analysis, in negative ionization mode. Diagnostic ion filtering (DIF), followed by diagnostic difference filtering (DDF), were utilized to automatically filter out MS data and select plausible oleracein structures. After an in-depth MS2 analysis, a total of 51 oleracein compounds were tentatively identified. Of them, 26 had structures, matching one of the already known oleracein, and the other 25 were new, undescribed in the literature compounds, belonging to the oleracein class. Moreover, based on selected diagnostic fragment ions, clustering algorithms and visualizations were utilized. As we demonstrate, clustering methods provide valuable insights into the mass fragmentation elucidation of natural compounds in complex mixtures.

Introduction: Multiple sclerosis (MS) is a progressive demyelinating and degenerative neurological disease. The degree of disability increases along with pathological damage, especially in cases with comorbidity. Methodology: The objective of this study was to analyze the influence of MS alone and with comorbidity on some neuropsychological patterns. Individual quality of life of 80 MS patients at a mean age of 49 years, 56 females and 24 males, was examined by means of Multiple Sclerosis Quality of Life-54 Questionnaire (MSQOL-54) in 2002-2015. Forty patients presented with MS alone and 40 with MS and comorbidity. The frequency of troubles of mental concentration/thinking, fixation of attention, and memory as well as of difficulty at work and other activities were examined. Results: Statistically significant differences were observed between patients with MS alone and those with MS and comorbidity concerning troubles of mental concentration/thinking (t=4.822; p

Amyotrophic lateral sclerosis (ALS) is a severe and fatal neurodegenerative disorder affecting both the upper and lower motor neurons. We present the clinical cases of four patients with ALS and vibration syndrome. All patients had over 20 years of exposure to general and local vibrations and common subjective complaints: pain, paresthesia, twitching and weakness of limb muscles. Evidence of ALS syndrome was demonstrated by the abnormal neurological examination (pseudobulbar syndrome and pyramidal signs) as well as by neurophysiological studies (peripheral motor neuron degeneration). We discuss the possible relationship between the exposure to general and local vibrations and the ALS syndrome in our patients, and the role of vibrations as a possible risk factor for the disease. Occupational contact with chemicals and pesticides is also discussed as a risk factor.

Due to its high catalytic activity and readily available supply, ribonuclease A (RNase A) has become a pivotal enzyme in the history of protein science. Moreover, this great interest has carried over to computational chemistry and molecular dynamics, where RNase A has become a model system for various types of studies, all the while being an important drug design target in its own right. Here, we present a detailed molecular dynamics study of RNase-ligand binding involving 22 compounds, spanning nearly five orders of magnitude in affinity, and totaling 8.8 μs of sampling with the standard Amber parameters and an additional 8.8 μs of sampling with a modified potential. We show that short-lived, solvent-mediated bridging interactions are crucial to RNase-ligand binding. We characterize the behavior of bridging solvent molecules, uncovering a power-law dependence between the lifetime of a solvent bridge and the probability of its occurrence. We also demonstrate that from an energetic perspective, bridging solvent in RNase A-ligand binding behaves like part of the enzyme, rather than the ligands. Moreover, we describe an automated pipeline for the detection and processing of bridging interactions, and offer an independent assessment of the performance of the state-of-the-art fixed-charge force fields. Thus, our work has broad implications for drug design and computational chemistry in general.

Features of intensive farming can seriously threaten pig homeostasis, well-being and productivity. Disease tolerance of an organism is the adaptive ability in preserving homeostasis and at the same time limiting the detrimental impact that infection can inflict on its health and performance without affecting pathogen burden per se. While disease resistance (DRs) can be assessed measuring appropriately the pathogen burden within the host, the tolerance cannot be quantified easily. Indeed, it requires the assessment of the changes in performance as well as the changes in pathogen burden. In this paper, special attention is given to criteria required to standardize methodologies for assessing disease tolerance (DT) in respect of infectious diseases in pigs. The concept is applied to different areas of expertise and specific examples are given. The basic physiological mechanisms of DT are reviewed. Disease tolerance pathways, genetics of the tolerance-related traits, stress and disease tolerance, and role of metabolic stress in DT are described. In addition, methodologies based on monitoring of growth and reproductive performance, welfare, emotional affective states, sickness behavior for assessment of disease tolerance, and methodologies based on the relationship between environmental challenges and disease tolerance are considered. Automated Precision Livestock Farming technologies available for monitoring performance, health and welfare-related measures in pig farms, and their limitations regarding DT in pigs are also presented. Since defining standardized methodologies for assessing DT is a serious challenge for biologists, animal scientists and veterinarians, this work should contribute to improvement of health, welfare and production in pigs.

The polyphenols curcumin (CU) and ferulic acid (FA) are able to inhibit the aggregation of amyloid-β (Aβ) peptide with different strengths. CU is a strong inhibitor while FA is a weaker one. In the present study, we examine the effects of CU and FA on the folding process of an Aβ monomer by 1 µs molecular dynamics (MD) simulations. We found that both inhibitors increase the helical propensity and decrease the non-helical propensity of Aβ peptide. They prevent the formation of a dense bulk core and shorten the average lifetime of intramolecular hydrogen bonds in Aβ. CU makes more and longer-lived hydrogen bonds, hydrophobic, π–π, and cation–π interactions with Aβ peptide than FA does, which is in a good agreement with the observed stronger inhibitory activity of CU on Aβ aggregation.

The assessment of immunogenicity of biopharmaceuticals is a crucial step in the process of their development. Immunogenicity is related to the activation of adaptive immunity. The complexity of the immune system manifests through numerous different mechanisms, which allows the use of different approaches for predicting the immunogenicity of biopharmaceuticals. The direct experimental approaches are sometimes expensive and time consuming, or their results need to be confirmed. In this case, computational methods for immunogenicity prediction appear as an appropriate complement in the process of drug design. In this review, we analyze the use of various In silico methods and approaches for immunogenicity prediction of biomolecules: sequence alignment algorithms, predicting subcellular localization, searching for major histocompatibility complex (MHC) binding motifs, predicting T and B cell epitopes based on machine learning algorithms, molecular docking, and molecular dynamics simulations. Computational tools for antigenicity and allergenicity prediction also are considered.

The main food-origin antigens that the infant’s body is in contact with are cow’s milk proteins (CMP). Still, CMP are one of the main sources of beneficial biologically active peptides that play a role in treatment of non-communicable diseases. Safe methods to quickly predict the sensitizing potential of food proteins among their range of health-promoting properties are essential. The aim of study was to adapt an integrated approach combining several in silico (IS) studies and in vitro (IV) assays to screen the multifunctionality of CMP-derived peptides. Major histocompatability complex type II MHC II-binders, interleukin-4 and -10 inducers, interferon γ -inducers and immunobioactivity tools were used to predict the peptide-power of inducing allergies or tolerance. A comparison of the peptide profiless revealed the presence of one identical and one overlapping sequence in IS and IV hydrolysate. By IS analysis, four of 24 peptides were found to have high affinity and stimulate IL-4 expression, and by IV, one of seven peptides had this potential (Bos d9 peptide DIPNPIGSENSEK (195–208)). Three IV peptides may induce IL-10 expression. The IV/IS assessment seems promising agents for peptides’ potential determination dedicated only to preliminary screening of peptides. The IV verification is still crucial in further steps of studies.

Background: The continuous progress of information technology has made possible the creation of tools for post processing of magnetic resonance and other imaging modalities, including software programmes aimed at volumetric studies of the brain. They have the potential to enrich visual data with precise numeric values but have to be used with caution because of their possible susceptibility to errors if scans with specific pathology are fed in. Objective: The purpose of the present study is to assess whether filling white matter lesions on magnetic resonance scans of multiple sclerosis patients would influence volumetric values. Methods: MS lesions were filled on T1 3D images of 49 patients by the lesion-filling algorithm of FSL, using previously created lesion masks. Volumes of brain grey and white matter, peripheral grey matter and ventricle CSF were calculated using SIENAX for the filled and non-filled series, which were then compared. Results: There were statistically significant differences for white matter volume before and after lesion filling (p

Background: The lack of a total numeric score of the CERAD neuropsychological battery may to some extent limit the possibilities for presenting the cognitive status and the degree of dementia. The objective of the present study is to apply the CERAD battery in a Bulgarian population of demented and control subjects, to compute the total score for each participant, and to compare the performance of the two groups. Methods: a total of 164 subjects, 134 patients with dementia and 30 controls were assessed using the Bulgarian version of the CERAD battery. The total score was calculated according to the method described by Chandler et al. Mean values were compared using independent samples t-test. ROC curves were built, and the area under the curve was calculated. Results: The total score for the whole sample has a mean value of 63.45±20.56. After correction for age and education x=79.51±20.24. The total score is significantly lower in the demented subjects compared to the control group, for both raw and corrected score. The area under the ROC curve shows values of 0.988 and 0.986 before and after correction, respectively. Conclusion: The statistically significant difference between the results of demented and control subjects, with and without correction for age and education, support the good applicability and high informative value of the instrument. The results of ROC analysis demonstrate the high value of the battery for diagnosing dementia.

Background: Seeking and receiving psychological help after a stressful life event is associated with certain prejudice attitudes, especially present in minority ethnic groups. Case description: This case report describes the specific reactions and psychopathological dynamics of a female patient, the age of 43, who survived the terrible accident on December the 10th 2016, in Hitrino village. Discussion: Due to stigmatising beliefs, patient reluctantly had only a few meeting with a clinical psychologist, refused proper psychiatric treatment, and developed an acute stress reaction in the first few days after the accident, followed by post-traumatic stress disorder the next few weeks, as described chronologically in the ICD-10. Conclusion: Stigmatising beliefs are further amplified by ethnic minorities’ prejudice of seeking mental health and having a mental illness, which affects professionals’ ability to provide comprehensive medical care.

Background: Autism is a mental developmental disorder, manifested in the early childhood. Attention deficit hyperactivity disorder is another psychiatric condition of the neurodevelopmental type. Both disorders affect information processing in the nervous system, altering the mechanisms which control how neurons and their synapses are connected and organized. Purpose: To examine if quantitative EEG assessment is sensitive and simple enough to differentiate autism from attention deficit hyperactivity disorder and neurologically typical children. Material and methods: Quantitative EEG is a type of electrophysiological assessment that uses computerized mathematical analysis to convert the raw waveform data into different frequency ranges. Each frequency range is averaged across a sample of data and quantified into mean amplitude (voltage in microvolts mV). We performed quantitative EEG analysis and compared 4 cohorts of children (aged from 3 to 7 years): with autism (high [n=27] and low [n=52] functioning), with attention deficit hyperactivity disorder [n=34], and with typical behavior [n75]. Results: Our preliminary results show that there are significant qEEG differences between the groups of patients and the control cohort. The changes affect the potential levels of delta-, theta-, alpha-, and beta- frequency spectrums. Conclusion: The present study shows some significant quantitative EEG findings in autistic patients. This is a step forward in our efforts, aimed at defining specific neurophysiologic changes, in order to develop and refine strategies for early diagnosis of autism spectrum disorders, differentiation from other development conditions in childhood, detection of specific biomarkers and early initiation of treatment.

The identification of protective immunogens is the most important and vigorous initial step in the long-lasting and expensive process of vaccine design and development. Machine learning (ML) methods are very effective in data mining and in the analysis of big data such as microbial proteomes. They are able to significantly reduce the experimental work for discovering novel vaccine candidates. Here, we applied six supervised ML methods (partial least squares-based discriminant analysis, k nearest neighbor (kNN), random forest (RF), support vector machine (SVM), random subspace method (RSM), and extreme gradient boosting) on a set of 317 known bacterial immunogens and 317 bacterial non-immunogens and derived models for immunogenicity prediction. The models were validated by internal cross-validation in 10 groups from the training set and by the external test set. All of them showed good predictive ability, but the xgboost model displays the most prominent ability to identify immunogens by recognizing 84% of the known immunogens in the test set. The combined RSM-kNN model was the best in the recognition of non-immunogens, identifying 92% of them in the test set. The three best performing ML models (xgboost, RSM-kNN, and RF) were implemented in the new version of the server VaxiJen, and the prediction of bacterial immunogens is now based on majority voting.

The amyloid plaques are a key hallmark of neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease. Amyloidogenesis is a complex long-lasting multiphase process starting with the formation of nuclei of amyloid peptides: a process assigned as a primary nucleation. Curcumin (CU) is a well-known inhibitor of the aggregation of amyloid-beta (Aβ) peptides. Even more, CU is able to disintegrate preformed Aβ firbils and amyloid plaques. Here, we simulate by molecular dynamics the primary nucleation process of 12 Aβ peptides and investigate the effects of CU on the process. We found that CU molecules intercalate among the Aβ chains and bind tightly to them by hydrogen bonds, hydrophobic, π–π, and cation–π interactions. In the presence of CU, the Aβ peptides form a primary nucleus of a bigger size. The peptide chains in the nucleus become less flexible and more disordered, and the number of non-native contacts and hydrogen bonds between them decreases. For comparison, the effects of the weaker Aβ inhibitor ferulic acid (FA) on the primary nucleation are also examined. Our study is in good agreement with the observation that taken regularly, CU is able to prevent or at least delay the onset of neurodegenerative disorders.

Background: Demyelination and neurodegeneration are hallmarks of multiple sclerosis (MS). Axonal damage is considered to be the leading factor for persisting disability in the course of the disease. In different studies, expanded disability status scale (EDSS) scores have been found to correlate with brain atrophy, lesion load, or both. Objective: To assess the possible correlations between EDSS scores and volumes of brain, grey and white matter, and subcortical structures in patients with relapsing-remitting multiple sclerosis. Subjects and Methods: 46 patients with RRMS were included in the study. Total brain volume, grey and white matter volumes were calculated using SIENAX, and subcortical structure volumes were obtained using FIRST, parts of FSL. EDSS was scored by a qualified rater. Statistical analysis was performed. Results: Moderate negative correlation of EDSS was demonstrated with total brain volume, grey and white matter volume, volumes of left and right pallidum, putamen, caudate nucleus, n. accumbens (p

Background: Syphilis is not only a disease of historical importance. It has been recognized that nowadays, in the era of AIDS, it still remains a serious challenge. For the last two decades there has been a resumption of neurosyphilis cases. This has revived the interest in the diagnostic and therapeutic challenges that the disease presents to clinical practice and to healthcare systems. Material/Methods: We present the overall picture of newly registered cases of syphilis in Varna municipality between 2009 and 2013, and report a case of neurosyphilis diagnosed at the first clinic of neurological diseases of St. Marina University Hospital during this period. Results: For the 5-year period, newly registered cases of syphilis in Varna have shown a tendency towards a decrease. Patients were typically in the early stages of the disease, primary and secondary. Late manifestations dropped from 29 in 2009 to 0 in 2010, but increased again to 15 in 2013. Only 1 case of neurosyphilis was registered during the 5-year period, in 2013. Conclusions: Neurological syndromes observed in cases of late neurosyphilis, presenting in different clinical forms, require a broad spectrum of differential diagnoses. Attention in everyday clinical practice should be focused on these cases which, though rare, are of high medical and social importance. Clinical cases of late neurosyphilis are often atypical and the early consideration of serologic tests or even biopsy may be of critical importance.

Primary adenoid cystic carcinoma (PACC) of the skin is a rare tumor with fewer than 70 cases studied in detail in the English literature. This type of tumor shows a prolonged course and a growth pattern usually manifested by multiple local recurrences and has a low potential for distant metastases. The most important modality for primary treatment is surgical resection followed by radiotherapy. We report a woman aged 43 years at the time of diagnosis, who presented with a slow-growing nodule in the right axilla without lymph node enlargement. A wide local excision was performed, and the histology revealed an adenoid cystic carcinoma. During the next 24 years, another four local recurrences were excised (the last one in 2015) and confirmed histologically to be adenoid cystic carcinoma. The patient was given 44 Gy of radiotherapy after the second surgery in 1996. PACC of the skin is a rare tumor with insufficient data concerning the efficacy of the surgical technique and chemotherapy and radiotherapy treatment, even more so in the case of multiple recurrences. After the last recurrence, the patient was offered an active follow-up based on the long tumor-free intervals in the past and because the site of the primary tumor allowed further surgical excisions in future recurrences.

OBJECTIVE:To test the validity of diffusion tensor imaging (DTI) measures of tissue injury by examining such measures in a white matter structure with well-defined function, the medial longitudinal fasciculus (MLF). Injury to the MLF underlies internuclear ophthalmoparesis (INO). METHODS:40 MS patients with chronic INO and 15 healthy controls were examined under an IRB-approved protocol. Tissue integrity of the MLF was characterized by DTI parameters: longitudinal diffusivity (LD), transverse diffusivity (TD), mean diffusivity (MD) and fractional anisotropy (FA). Severity of INO was quantified by infrared oculography to measure versional disconjugacy index (VDI). RESULTS:LD was significantly lower in patients than in controls in the medulla-pons region of the MLF (p < 0.03). FA was also lower in patients in the same region (p < 0.0004). LD of the medulla-pons region correlated with VDI (R = -0.28, p < 0.05) as did FA in the midbrain section (R = 0.31, p < 0.02). CONCLUSIONS:This study demonstrates that DTI measures of brain tissue injury can detect injury to a functionally relevant white matter pathway, and that such measures correlate with clinically accepted evaluation indices for INO. The results validate DTI as a useful imaging measure of tissue integrity.