Dean\u27s perceptions of leadership strategies used to manage a multicultural faculty environment in Saudi Arabia

Majority of nursing faculty in Saudi Arabia are expatriates. Because leading an academic multicultural environment in Saudi Arabia has not been examined, five interviews were conducted via Skype with Saudi deans of Schools of Nursing to explore how they lead their multicultural environments and improve school performance

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

Bio-nanotechnology application in wastewater treatment

The nanoparticles have received high interest in the field of medicine and water purification, however, the nanomaterials produced by chemical and physical methods are considered hazardous, expensive, and leave behind harmful substances to the environment. This chapter aimed to focus on green-synthesized nanoparticles and their medical applications. Moreover, the chapter highlighted the applicability of the metallic nanoparticles (MNPs) in the inactivation of microbial cells due to their high surface and small particle size. Modifying nanomaterials produced by green-methods is safe, inexpensive, and easy. Therefore, the control and modification of nanoparticles and their properties were also discussed

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors

BACKGROUND AND PURPOSE: Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features. MATERIALS AND METHODS: This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data. RESULTS: ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix. CONCLUSIONS: Support vector machine–based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology

Kafka at the West Bank checkpoint: de-normalizing the Palestinian encounter before the law

The checkpoint has emerged as a quintessential trope within the contemporary Palestinian imagination, to such an extent that “checkpoint narratives” have arguably come to assume a dangerously “normalized” status as everyday, even iconic features of Palestinian existence. Turning to the films Route 181 by Michel Khleifi and Eyal Sivan, and like twenty impossibles by Annemarie Jacir, this article explores how alternative representations (and theorizations) of checkpoint encounter might serve to “de-normalize” the checkpoint in a way that invites us to interrogate the very nature of the checkpoint apparatus in itself, including the nature of the “law” that it represents. Mobilizing the critical paradigms of the “state of exception” and “homo sacer” drawn from the theoretical work of Giorgio Agamben and the literary work of Franz Kafka, the article argues that apprehension of the enduring oddity and abnormality of the checkpoint serves as a vital mode of critical resistance to the policies of “spatio-cide”, “securitization” and colonialism exercised at the hands of the State of Israel through the checkpoint mechanism

Dual acting therapeutic proteins for intraocular use

Antibody-based medicines that target vascular endothelial growth factor (VEGF) are administered by intravitreal injection to treat chronic neovascular retinal diseases. Much ongoing effort is focused on enhancing therapeutic outcome of these medicines. One strategy is the use of dual acting drugs (e.g. bispecific antibodies) to simultaneously bind to more than one intraocular biological target. A dual acting molecule targeting components within the vitreal cavity could also potentially extend vitreous residence time. In this review, the applications of bispecific antibodies within the eye are described with consideration to potential targets, applications and suitable bispecific formats

Aberrant expression of cyclin A in head and neck cancer

Cyclin A expression was studied in a series of 65 squamous cell carcinomas of the head and neck (HNSCC) and compared with known markers of proliferation, iododeoxyuridine (IdUrd) and Ki-67, to assess whether aberrant expression was prevalent. Patients had previously been administered IdUrd to study cell kinetics in relation to outcome of radiotherapy. The data showed that all three parameters were highly correlated although the absolute values were different. The median labelling indices (LI) for IdUrd, cyclin A and Ki-67 were 10.7, 17.1 and 30.8% respectively, reflecting the known pattern of differential cell cycle expression. However, there were a significant number of cases in which an unexpected relationship between cyclin A and either IdUrd or Ki-67 was present. Some of these were attributable to overexpression but others indicated underexpression. Although the greater variability and range of cyclin A expression, coupled with its more closely associated role in cell cycle regulation, might suggest that it may be a more informative marker for cell proliferation than Ki-67, the aberrant expression seen in over one third of cases would indicate that caution should be exercised in interpreting cyclin A as a surrogate marker of proliferation in HNSCC. © 2000 Cancer Research Campaig

Cytokine storm of a different flavor: the different cytokine signature of SARS-CoV2 the cause of COVID-19 from the original SARS outbreak.

We present a case series of three patients with COVID-19 who had a cytokine panel which revealed elevation of interleukin-6 (IL-6), but normal levels of interleukin-10 (IL-10), interferon-gamma (INF-γ) and interleukin-8 (IL-8) in contrast to the cytokine signature described in Severe Acute Respiratory Syndrome (SARS) and Middle Eastern Respiratory Syndrome (MERS). We also documented evidence of a compromised T-cell IFN-gamma response in two of these patients