Articles

A Gamma Ionization Chamber was developed for the purpose of high gamma radiation detection during accident conditions in a Light Water reactor. The pre-eminence of the detector is that it was designed and developed to monitor gamma exposure rates in the wide range of 100 mR/hr to 107 R/hr. The detector has an overall diameter of 90 mm with a length of 400 mm. The response of the detector is accurate and the sensitivity is within ± 6% over gamma energies ranging from 660 KeV to 1.25 MeV. The detector operates with a DC voltage of 500V. The V0.9 voltage is about 250V for 107 R/hr. The estimated operation life of the detector is about 20 years. 

The purpose of this work is to implement methods and develop tools for nonlinear dynamic identification of the Oculomotor System (OMS) “input-output” in the form of Multidimensional Transient Functions (MTF) based on eye tracking data and their use in an information system for diagnosing the psychophysiological state of a person. The object of the study is the process of diagnosing the psychophysiological state of an individual based on innovative eye-tracking technology. The subject of the research is computational algorithms and software for determining diagnostic features based on identification data of compulsory medical insurance in the form of MTF, constructing a Bayesian classifier using machine learning in the established space of the most informative features. A methodology has been developed and implemented for the experimental study of human compulsory mental health using innovative eye-tracking technology to record compulsory mental health responses to test visual stimuli. The obtained empirical data from input-output studies are used for the identification of OMS based on Volterra polynomials. Experimental studies of compulsory medical insurance of respondents were carried out before and after the working day. Based on the data obtained using the Tobii Pro TX300 eye tracker, the transient functions of the first, second, and third orders of the OMS were determined. Variability of second and third order transient functions was revealed for different psychophysiological states of the respondent (normal or fatigue). Thus, it seems appropriate to use MTF in diagnostic studies in the fields of neuroscience and psychology. Information technology for diagnosing human psychophysiological conditions has been further developed through the use of compulsory health insurance information models based on Volterra polynomials as a source of primary data. This allows for an increase in the accuracy of OMS modeling and, consequently, enhances the reliability of diagnosis within the framework of the proposed heuristic features. A set of heuristic features is proposed, which are determined using integral and differential transformations of the MTF OMS. The information content of individual features and all possible combinations of them in pairs was studied using the Probability of Correct Recognition (PCR) indicator. Two-dimensional feature spaces with the maximum PCR value (0.938) were identified during the diagnosis of a person’s psychophysiological state.

Tuva has been a cattle-breeding region since ancient times, extremely continental climate of this region is little suitable for agriculture. However, the steppes of intermountain depressions in Tuva were heavily plowed by the early 1980s. In the 1990s most of the arable lands were abandoned; the process of restoration (demutation) of natural vegetation on fallow lands began. By now, 30 years later, the old fallows are expected to achieve the stage of the secondary steppe.The purpose of this work is to estimate the differences between virgin steppes and corresponding secondary steppes in Tuva. Tussock, hummock, and desert virgin steppes have been compared with corresponding to three types of 30-year-old fallow communities. For this study, 330 geobotanical releves have been used. The criteria for comparison have been chosen as follows: the similarity of species composition, the spectrum of dominant species, species richness, grass cover, and grass height. The statistical validity of their differences has been verified. According to these criteria, virgin steppes and their 30-year-old fallow derivatives are shown to differ significantly.

Diffuse pediatric-type high-grade glioma H3-wildtype and IDH-wildtype (pHGG H3/IDH WT) is a heterogeneous entity that is currently defined by a combination of highly malignant morphology, glial or primitive neuroectodermal differentiation, and a number of molecular features. Depending on the DNA methylation profile in pHGG H3/IDH WT, three molecular subgroups are distinguished, one of which (pHGG MYCN) is characterized by amplification of the indicated gene. We report a unique case of pHGG H3/IDH WT in a 19-year-old girl with a deletion of the MYCN gene and constitutional mismatch repair deficiency syndrome.

Background: CPTs are rare intraventricular papillary neoplasms derived from the choroid plexus epithelium. Anti-collagenase and extracellular matrix which have not been expressed in brain tumors. Objective: The purpose of this study was to investigate the expression levels of collagen type VI, anti-collagenase, laminin, MM9, claudins 1 and 5, N and E cadherins, and collagen VII, tejido, and collagen degradation enzyme complexes in choroid plexus tumors.Materials and methods: We studied the expression of adhesion molecules, extracellular matrix, and anticollagenase with an immunohistochemistry approach and electron microscopy analysis in 42 choroid plexus tumors. Results: 28(67%) were choroid plexus papillomas, 8 (19%) were atypical choroid plexus papillomas and 6 (14%) were choroid plexus carcinomas. The Ki67-li and MVD increased from CPC to ACPP, being the highest in malignant tumors as well as a strong immunoexpression of anti-collagenase and were inverse correlation with claudin 5, E, and N cadherin and collagen IV immunoexpressions which added further significant information to the prognosis and varied according to the histologic classification. By ultrastructure, the loss of basal membrane and cilia, disorganization, and proliferation of ECM were observed in CPC. Cerebral homeostasis largely results from the ability of both the Blood–Brain Barrier (BBB) at the brain microvascular endothelium and the Blood–Cerebrospinal Fluid Barrier (BCSFB) at the epithelium of the Choroid Plexuses (CPs), to control the composition of the CSF and cerebral extracellular fluid. Under expression of the tight junction proteins occludin, claudin-1 and claudin-5 are key molecular abnormalities responsible for the increased permeability of tumor endothelial tight junctions. Conclusion: The loss of basement membrane and ECM overexpression could be considered as a poor prognosis predictor in CPT. Anti-collagenase and MMP9 overexpression could be related to basal membrane and BBB plasticity in CPTs.

Background: Clinical practice guidelines recommend monitoring the depth of anesthesia during endoscopic examination of the gastrointestinal tract using sedation scales, despite their subjective nature, while the use of the bispectral index, an objective measure, during sedation, remains controversial. The main objective of this study was to assess the ability of bispectral index monitoring to characterize the depth of anesthesia during endoscopy.Methods: We conducted a cross-sectional study to assess the performance of the bispectral index using data from a multicentre clinical trial with 180 patients undergoing scheduled colonoscopies. Sedation was monitored using the bispectral index and Ramsay Sedation Scale. Data on sedation were recorded at five-time points (t1 to t5) during the colonoscopy.Results: Bispectral values were significantly associated with Ramsay scores (rho, -0.73; p < 0.0001). In regression analysis, each unit increase in bispectral value was associated with a reduction in the risk of a high Ramsay score (> 3) at all points (OR 0.922; 95% CI: 0.865–0.979; p < 0.0001 at t1). Receiver operating characteristic curve analysis found areas under the curve of 0.8272 for a bispectral index cut-off for deep sedation of 69.76 (sensitivity, 95.35%; negative predictive value, 97.53%) when reaching the colic flexure (t2) and 0.8399 for a cut-off of 69.29 (sensitivity, 96.15%; negative predictive value, 98.81%) at the end of the colonoscopy (t5).Conclusion: Bispectral index monitoring enables objective real-time reliable assessment of sedation. It enables easy continuous monitoring with a very good performance for detecting deep sedation and correlates with a clinical scale routinely used in endoscopic procedures.

Yemen with its diverse climatic regions represents a rich resource for bioactive compounds obtained from microorganisms. This study was designed to screen fungal isolates obtained from the Microbiology branch, Biological Sciences Department, Faculty of Science, Sana’a University for their ability to produce L-asparaginase enzyme. In preliminary screening for L-asparaginase, among 77 fungal isolates about 29 fungal isolates representing 37.66% were high producers of L-asparaginase. These fungal isolates belonged to the genera Aspergillus, Eupenicillium, Fusarium, Penicillium, and Stachyobotrys. These 29 fungal isolates were screened for their ability to produce L-asparaginase using the agar well diffusion method. 12 fungal isolates out of 29 showed the ability to produce extracellular L-asparaginase. These isolates belonged to 8 species which were: A. sulphurs, A. ustus, F. sacchari, P. chrysogenum, P. citrinum, P. corylophilum, P. melinii, and P. subturcoseum. Only 5 isolates were obtained for the determination of enzymatic activity, among them P. chrysogenum showed the highest activity (279.8696U ml-1) followed by A. ustus (170.9435U ml-1). This finding is the first report on the L-asparaginase production from filamentous fungi in Yemen.

Background: Patients undergoing percutaneous coronary intervention are at risk of different complications such as periprocedural bleeding and acute hemoglobin reduction that can lead to myocardial injury. Blood loss through the catheter during the procedure and through puncture site haematoma causes periprocedural acute haemoglobin drop.Objectives: To find out the association between acute haemoglobin reduction and myocardial injury after PCI in patients with unstable angina. Methods: This prospective observational study was conducted at the National Institute of Cardiovascular Diseases (NICVD) for one year of time. A total of 130 patients were enrolled based on inclusion and exclusion criteria during the study period. Haemoglobin and troponin-I were measured before and after PCI within 24 to 48 hours of the procedure. On the basis of post-procedural acute haemoglobin level, the study population was categorized into two groups: Group I patients with normal haemoglobin levels and Group II patients with significant acute haemoglobin reduction (≥ 1 gm/dl). Results: A total of 24 patients developed a periprocedural myocardial injury, among them 17 (70.8%) were in the reduced haemoglobin group and 7 (29.2%) in the normal haemoglobin group. Elevation of troponin I after PCI was higher in group II than in group I patients with a statistically significant difference. Multivariate logistic regression analysis showed that haemoglobin reduction was an independent predictor of PMI (OR 1.94; 95% CI, 1.241-8.684; p = 0.01). Conclusion: Periprocedural haemoglobin reduction in patients with unstable angina was associated with myocardial injury after percutaneous coronary intervention (PCI).

The article gives a general classification of non-invariant points in phase equilibrium diagrams of all possible types. The complete topological isomorphism of the diagrams of fusibility, solubility, and liquid-vapor equilibria in various sets of variables is demonstrated. The stability of mono-variant equilibria near the non-variant points is investigated. Recurrent formulas for calculating the number of topological elements of phase diagrams are given. A previously undescribed type of non-invariant points and phase processes in the solubility diagrams is described and characterized. The last ones have no topological analogs in other types of diagrams. Thus, we have carried out, as far as is available to the authors, a complete classification of invariant points and invariant processes in phase equilibrium diagrams of an arbitrary type and with an arbitrary number of components.

Background and aim: Congestive heart failure is a prevalent and serious condition that poses significant challenges in the emergency department setting. Prompt and accurate management of congestive heart failure patients is crucial for improving outcomes and optimizing resource utilization. This study aims to address these challenges by developing a machine learning algorithm and comparing it to a traditional logistic regression model that can assist in the triage, resource allocation, and long-term prognostication of congestive heart failure patients.Methods: In this investigation, we used the MIMIC-III database, a publicly accessible resource containing patient data from ICU settings. Traditional logistic regression, along with the robust XGBoost and random forest algorithms, was harnessed to construct predictive models. These models were built using a range of pretreatment clinical variables. To pinpoint the most pertinent features, we carried out a univariate analysis. Ensuring robust performance and broad applicability, we adopted a nested cross-validation approach. This method enhances the precision and validation of our models by implementing multiple cross-validation iterations.Results: The performance of machine learning algorithms was assessed using the area under the receiver operating characteristic curve (AUC). Notably, the random forest algorithm, despite having lower performance among the machine learning models still demonstrated significantly higher AUC than traditional logistic regression. The AUC for the XGBoost was 0.99, random forest 0.98, while traditional logistic regression was 0.57. The most important pretreatment variables associated with congestive heart failure include total bilirubin, creatine kinase, international normalized ratio (INR), sodium, age, creatinine, potassium, gender, alkaline phosphatase, and platelets.Conclusion: Machine learning techniques utilizing multiple pretreatment clinical variables outperform traditional logistic regression in aiding the triage, resource allocation, and long-term prognostication of congestive heart failure patients in the intensive care unit setting using MIMIC III data.