A systematic review of the applications of Expert Systems (ES) and machine learning (ML) in clinical urology.

BackgroundTesting a hypothesis for 'factors-outcome effect' is a common quest, but standard statistical regression analysis tools are rendered ineffective by data contaminated with too many noisy variables. Expert Systems (ES) can provide an alternative methodology in analysing data to identify variables with the highest correlation to the outcome. By applying their effective machine learning (ML) abilities, significant research time and costs can be saved. The study aims to systematically review the applications of ES in urological research and their methodological models for effective multi-variate analysis. Their domains, development and validity will be identified.MethodsThe PRISMA methodology was applied to formulate an effective method for data gathering and analysis. This study search included seven most relevant information sources: WEB OF SCIENCE, EMBASE, BIOSIS CITATION INDEX, SCOPUS, PUBMED, Google Scholar and MEDLINE. Eligible articles were included if they applied one of the known ML models for a clear urological research question involving multivariate analysis. Only articles with pertinent research methods in ES models were included. The analysed data included the system model, applications, input/output variables, target user, validation, and outcomes. Both ML models and the variable analysis were comparatively reported for each system.ResultsThe search identified n = 1087 articles from all databases and n = 712 were eligible for examination against inclusion criteria. A total of 168 systems were finally included and systematically analysed demonstrating a recent increase in uptake of ES in academic urology in particular artificial neural networks with 31 systems. Most of the systems were applied in urological oncology (prostate cancer = 15, bladder cancer = 13) where diagnostic, prognostic and survival predictor markers were investigated. Due to the heterogeneity of models and their statistical tests, a meta-analysis was not feasible.ConclusionES utility offers an effective ML potential and their applications in research have demonstrated a valid model for multi-variate analysis. The complexity of their development can challenge their uptake in urological clinics whilst the limitation of the statistical tools in this domain has created a gap for further research studies. Integration of computer scientists in academic units has promoted the use of ES in clinical urological research

“I think that’s what he’s doing”: effects of intentional reasoning on second language (L2) speech performance

This study advances our understanding of the effects of task design on task complexity and second language (L2) performance. The research reported here focused on examining the impact of degree of intentional reasoning, operationalised at two levels of task content and task instructions, on language performance and perceptions of task difficulty. Using a mixed-methods approach, the study drew on quantitative and qualitative data collected from 20 Jordanian L2 learners performing video-based oral narratives and completing retrospective questionnaires. The results suggest that intentional reasoning has a noticeable effect in generating more syntactically complex and accurate language, and also influences perceptions of task difficulty. However, a higher intentional reasoning demand is associated with less lexical diversity and inconsistent patterns of fluency. An important finding of the study is that the link between the cognitive demands and the language used to convey intentional reasoning should be carefully considered when selecting analytic measures of complexity and accuracy

Biological Activity of Quinazolinones

The chemical structure of quinazolinones includes benzene ring fused with 2-pyrimidinone (1), 4-pyrimidinone (2) or 2,4-pyrimidinedione (3) ring, and are named as quinazolin-2(1H)-one, quinazolin-4(3H)-one or quinazolin-2,4(1H, 3H)-one, respectively. The chemical structure of quinazolinones constitutes a crucial scaffold of natural and synthetic compounds with various therapeutic and biological activities. Quinazolinones are first synthesized by Stefan Niementowski (1866–1925) and named after Niementowski quinazolinone synthesis. Quinazolinones have strongly attracted the interest of medicinal chemist as they constitute a large class of compounds that exhibited broad spectrum of biological activities including antimicrobial, antimalarial, anticonvulsant, anticancer, antileishmanial, anti-inflammatory, etc. This chapter provides a brief overview on the recent advances on chemical and pharmacological aspects of quinazolinone derivatives published in the last decade

In silico studies on novel inhibitors of MERS-CoV: Structure-based pharmacophore modeling, database screening and molecular docking

Purpose: To search for novel scaffolds as potential inhibitors of 3CLpro protease enzyme and as antiviral drugs.Methods: NCI database was screened using structure-based  pharmacophore modeling, database screening and molecular docking. Also, Lipininski’s rule of 5 was applied in order to test the druglikenessof the retrieved compound. Pharmacophore modelling and subsequent post-docking analyses were used for comparison of the binding mode of the retrieved hits with that of the x-ray inhibitor, R30, against MERS-CoV 3CLpro enzyme.Results: Five compounds were identified as potential agents for the  treatment of corona virus, MERSCoV, which showed similar binding to MERS-CoV 3CLpro like that of the x-ray inhibitor, R30. As protease enzyme plays an indispensable role during virus life cycle, CoV 3CLpro has been reported as a highly validated drug target and it is considered viable for the design of broad spectrum inhibitors. The selected five hit compounds bind to MERS-CoV 3CLpro in a manner similar to that of the x-ray inhibitor, R30, and showed pharmacophore-fit and docking score values higher than those of R30, MERS-CoV 3CLpro-inhibitor.Conclusion: The retrieved five hits are proposed as new scaffolds for further evaluation and optimization of their activity against MERS-CoV.Keywords: MERS-CoV pharmacophore, Molecular docking, Protease enzyme, X-ray inhibito

Pharmacophore Elucidation and Molecular Docking Studies on 5-Phenyl-1-(3-pyridyl)-1H-1,2,4-triazole-3-carboxylic Acid Derivatives as COX-2 Inhibitors

A set of 5-phenyl-1-(3-pyridyl)-1H-1,2,4-triazole-3-carboxylic acid derivatives (16–32) showing anti-inflammatory activity was analyzed using a three-dimensional qualitative structure-selectivity relationship (3D QSSR) method. The CatalystHipHop approach was used to generate a pharmacophore model for cyclooxygenase-2 (COX-2) inhibitors based on a training set of 15 active inhibitors (1–15). The degree of fitting of the test set compounds (16–32) to the generated hypothetical model revealed a qualitative measure of the more or less selective COX-2 inhibition of these compounds. The results indicate that most derivatives (16, 18, 20–25, and 30–32) are able to effectively satisfy the proposed pharmacophore geometry using energy accessible conformers (Econf < 20 kcal/mol). In addition, the triazole derivatives (16–32) were docked into COX-1 and COX-2 X-ray structures, using the program GOLD. Based on the docking results it is suggested that several of these novel triazole derivatives are active COX inhibitors with a significant preference for COX-2. In principle, this work presents an interesting, comprehensive approach to theoretically predict the mode of action of compounds that showed anti-inflammatory activity in an in vivo model

Coverage degree in mobile nodes wireless sensor network

Coverage degree and mobility have acquired a lot of attention lately in Wireless Sensor Network (WSN). This paper shows that nodes mobility can enhance coverage degree for WSN. Analytical model is introduced to describe the coverage degree in mobile nodes wireless sensor network. MATLAB was used to build the simulator. The analytical work is validated by simulated results. Both of analytical model and simulation showing that the coverage degree has been enhanced in Mobile Nodes Wireless Sensor Network (MNWSN) as compared to static network

A Systematic Review: The Prenatal and Postnatal Events Associated with Infant Mortality Rate (IMR)

Infant mortality rate (IMR) is an indication of overall population health, maternal and child health, accessibility and quality of primary health care, and the availability of community resources. The current IMR in the United States is high despite advances made in the medical field. The purpose of our systematic review is to describe and critically appraise research about prenatal events, postnatal events, and increased infant mortality rate and to give nursing practice recommendations to help decrease the rate. We used CINAHL, Medline and PubMed to find 20 research articles. Overall, the research stated that going to prenatal visits had a direct correlation to the outcomes of the infant after delivery, the importance of patient teaching after delivery is imperative to help prevent infant deaths through sudden infant death syndrome (SIDS), and that smoking before, during, or after pregnancy puts both the mother and infant at risk for a multitude of complications including ones that lead to infant death. Limitations across studies included small sample sizes, self-reported data, small population sizes, and government statistics being used to determine causation of death in infants

Accomplishes Foreign Direct Investment Affect Private Investment In Arab Nations In The Period Between (2000 – 2021)?

The article desires to examine the impact of FDI on PI with a sampling of 10 selected Arab countries from 2000- 2021. For further analysis, the study used OLS. Test method with fixed and random effects model, and after making Haussmanns test and accepting the Alternative Hypothesis (H1), the study used the fixed effects model. The results confirm the presence of crowding in reality, which indicates that FDI encourages PI in only one model. Aside from this, the delayed PI has a positive and essential impact on herself in the coming period reflecting stagnation in the direction of PI in the beneficiary nations. In the complete panel sample, thither is a significant negative effect between inflation and PI, there are some macro elements that as per capita GDP, electro, domestic credit, and labor force, which were positive and not statistically significant, while trade openness was negative and not statistically significant

Molecular scaffold and biological activities of anti- Alzheimer agents

Alzheimer’s disease (AD) is an age-associated and neurodegenerative illness which results in progressive dementia and severe cognitive malfunctions. The pathogenesis of AD is affected by some factors such as accumulation of β-amyloid, aggregation of tau protein, cholinergic insufficiency, neuroinflammation, oxidative stress and apoptosis. Factors such as gene mutation, as well as environmental, psychical and other co-existing diseases influence the pathogenesis of AD to varying extents. While there are no available drugs for arresting AD-associated neurodegeneration, the characteristics that result from AD treatment are considered as indexes of symptomatic cure. Several medications with varied scaffolds have been used for the treatment of many cognitive syndromes, including AD. These medications act as anti-inflammatory and antioxidant agents, and as inhibitors of cholinesterase and β-secretase. Moreover, these drugs suppress the accumulation of β-amyloid and its fibril. This review is an update and compilation of various scaffolds of anti-AD medications used to ameliorate the deleterious effects of the disease, based on their pharmacologic characteristics