Electronic depth profiles with atomic layer resolution from resonant soft x-ray reflectivity

The analysis of x-ray reflectivity data from artificial heterostructures usually relies on the homogeneity of optical properties of the constituent materials. However, when the x-ray energy is tuned to an absorption edge, this homogeneity no longer exists. Within the same material, spatial regions containing elements at resonance will have optical properties very different from regions without resonating sites. In this situation, models assuming homogeneous optical properties throughout the material can fail to describe the reflectivity adequately. As we show here, resonant soft x-ray reflectivity is sensitive to these variations, even though the wavelength is typically large as compared to the atomic distances over which the optical properties vary. We have therefore developed a scheme for analyzing resonant soft x-ray reflectivity data, which takes the atomic structure of a material into account by "slicing" it into atomic planes with characteristic optical properties. Using LaSrMnO4 as an example, we discuss both the theoretical and experimental implications of this approach. Our analysis not only allows to determine important structural information such as interface terminations and stacking of atomic layers, but also enables to extract depth-resolved spectroscopic information with atomic resolution, thus enhancing the capability of the technique to study emergent phenomena at surfaces and interfaces.Comment: Completely overhauled with respect to the previous version due to peer revie

Risk assessment of drug management process in women surgery department of qaem educational hospital (QEH) using HFMEA method (2013)

Evaluation and improvement of drug management process are essential for patient safety. The present study was performed whit the aim of assessing risk of drug management process in Women Surgery Department of QEH using HFMEA method in 2013. A mixed method was used to analyze failure modes and their effects with HFMEA. To classify failure modes; nursing errors in clinical management model, for classifying factors affecting error; approved model by the UK National Health System, and for determining solutions for improvement; Theory of Inventive Problem Solving, were used. 48 failure modes were identified for 14 sub-process of five steps drug management process. The frequency of failure modes were as follow:35.3 in supplying step, 20.75 in prescription step, 10.4 in preparing step, 22.9 in distribution step and 10.35 in follow up and monitoring step. Seventeen failure modes (35.14) were considered as non-acceptable risk (hazard score� 8) and were transferred to decision tree. Among 51 Influencing factors, the most common reasons for error were related to environmental factors (21.5), and the less common reasons for error were related to patient factors (4.3). HFMEA is a useful tool to evaluating, prioritization and analyzing failure modes in drug management process. Revision drug management process based focus-PDCA, assessing adverse drug reactions (ADR), USE patient identification bracelet, holding periodical pharmaceutical conferences to improve personnel knowledge, patient contribution in drug therapy; are performance solutions which were placed in work order. © 2015 by School of Pharmac

Nasopharyngeal carcinoma protein interaction mapping analysis via proteomic approaches

Nasopharyngeal carcinoma (NPC), although not very common in many parts of the world, is a major concern in some countries, including Iran. Molecular studies are very helpful to provide essential information regarding underlying carcinogenetic mechanisms. Here, considering NPC proteomic approaches, established biomarkers were designated for protein-protein interaction network construction and analysis with corresponding plug-ins. A network of reported protein markers was constructed and topological and biological process features were investigated. Centrality analysis showed that JUN, CALM1, HSB1, and SOD1 are more important than other differentially expressed proteins in an interacting pattern. What is more, by extending the network, Tp53, PRDM10, AKT1, ALB, HSP90AA1, and EGFR achieved the highest values for NPC network strength. It can be concluded that these proteins as well as their contributing processes, particularly in a second network, may be important for NPC onset and development. Targeting these candidate proteins may allow novel treatment approaches following appropriate validation. © Asian Pacific Journal of Cancer Prevention, 2017

Nasopharyngeal carcinoma protein interaction mapping analysis via proteomic approaches

Nasopharyngeal carcinoma (NPC), although not very common in many parts of the world, is a major concern in some countries, including Iran. Molecular studies are very helpful to provide essential information regarding underlying carcinogenetic mechanisms. Here, considering NPC proteomic approaches, established biomarkers were designated for protein-protein interaction network construction and analysis with corresponding plug-ins. A network of reported protein markers was constructed and topological and biological process features were investigated. Centrality analysis showed that JUN, CALM1, HSB1, and SOD1 are more important than other differentially expressed proteins in an interacting pattern. What is more, by extending the network, Tp53, PRDM10, AKT1, ALB, HSP90AA1, and EGFR achieved the highest values for NPC network strength. It can be concluded that these proteins as well as their contributing processes, particularly in a second network, may be important for NPC onset and development. Targeting these candidate proteins may allow novel treatment approaches following appropriate validation. © Asian Pacific Journal of Cancer Prevention, 2017

Interpretation of tongue squamous cell carcinoma via protein-protein interaction network construction and analysis

Background: Tongue squamous cell carcinoma is one of the prominent cancers in the oral cavity. Molecular investigations based on interaction analysis can be promising towards providing a better resolution of malignant neoplasms. Here, the protein-protein interaction network of tongue cancer is studied. Methods: The protein-protein interaction network was constructed by the application of Cytoscape 3.5.1 and the related algorithms. Centrality analysis via the degree, betweenness, and closeness centralities was conducted. Results: The result indicated that there are seven chief proteins in the network foundation. Moreover, enrichment evaluation suggested two associated biological processes including Response to UV-A, Response to interlukin-7, cellular response to alcohol, and catenin import into nucleus process using CluePedia. Conclusions: It can be concluded that the identified central panel proteins and their related biological processes can shed light on the neoplasm mechanisms and are worth pursuing for clinical approaches. © 2018, Cancer Research Center (CRC), Shahid Beheshti University of Medical Sciences

Interpretation of tongue squamous cell carcinoma via protein-protein interaction network construction and analysis

Background: Tongue squamous cell carcinoma is one of the prominent cancers in the oral cavity. Molecular investigations based on interaction analysis can be promising towards providing a better resolution of malignant neoplasms. Here, the protein-protein interaction network of tongue cancer is studied. Methods: The protein-protein interaction network was constructed by the application of Cytoscape 3.5.1 and the related algorithms. Centrality analysis via the degree, betweenness, and closeness centralities was conducted. Results: The result indicated that there are seven chief proteins in the network foundation. Moreover, enrichment evaluation suggested two associated biological processes including Response to UV-A, Response to interlukin-7, cellular response to alcohol, and catenin import into nucleus process using CluePedia. Conclusions: It can be concluded that the identified central panel proteins and their related biological processes can shed light on the neoplasm mechanisms and are worth pursuing for clinical approaches. © 2018, Cancer Research Center (CRC), Shahid Beheshti University of Medical Sciences

The transcriptional response to oxidative stress is part of, but not sufficient for, insulin resistance in adipocytes.

Insulin resistance is a major risk factor for metabolic diseases such as Type 2 diabetes. Although the underlying mechanisms of insulin resistance remain elusive, oxidative stress is a unifying driver by which numerous extrinsic signals and cellular stresses trigger insulin resistance. Consequently, we sought to understand the cellular response to oxidative stress and its role in insulin resistance. Using cultured 3T3-L1 adipocytes, we established a model of physiologically-derived oxidative stress by inhibiting the cycling of glutathione and thioredoxin, which induced insulin resistance as measured by impaired insulin-stimulated 2-deoxyglucose uptake. Using time-resolved transcriptomics, we found > 2000 genes differentially-expressed over 24 hours, with specific metabolic and signalling pathways enriched at different times. We explored this coordination using a knowledge-based hierarchical-clustering approach to generate a temporal transcriptional cascade and identify key transcription factors responding to oxidative stress. This response shared many similarities with changes observed in distinct insulin resistance models. However, an anti-oxidant reversed insulin resistance phenotypically but not transcriptionally, implying that the transcriptional response to oxidative stress is insufficient for insulin resistance. This suggests that the primary site by which oxidative stress impairs insulin action occurs post-transcriptionally, warranting a multi-level 'trans-omic' approach when studying time-resolved responses to cellular perturbations

Factors affecting the technical efficiency of rural primary health care centers in Hamadan, Iran: data envelopment analysis and Tobit regression

Background: Studying and monitoring the efficiency of primary health care centers has a special place in the health system. Although studies have been conducted in the field of efficiency in Iran, few have focused on rural primary health care centers. In addition, previous studies have not used the child mortality rate and Behvarzes as input and output. Objective: The present study was conducted aimed to estimate the technical efficiency of rural primary health care centers and determinant factors in Hamadan using data envelopment analysis and Tobit regression. Methods: This is a Longitudinal study of rural primary health care centers in Hamadan province (2002�2016). Data Envelopment Analysis was employed to estimate technical efficiency of sampled health facilities while Panel Tobit Analysis was applied to predict factors associated with efficiency levels. The outputs were child mortality rate under 1 year of age and child mortality rate 1 year to 5 years of age. The input was Behvarzes (rural health workers). Results: The results of efficiency analysis showed that the average efficiency scores of the centers had a fluctuating trend during the period of the study, but the average performance scores generally decreased in 2016, as compared with 2002. The highest and lowest average performance scores were observed in 2003 (0.78) and 2013 (0.56), respectively. Number of physicians and rural primary healthcare centers per population had a positive statistically significant and the number of midwives and the total fertility per population had a negative statistically significant effect on efficiency. Conclusions: The findings suggest some level of wastage of health resources in primary health centers. Findings indicate a level of waste of health resources in primary health centers. Behvarz functions in providing primary care services can be considered in the reallocation and optimal use of available resources at the level of rural health centers. © 2020, The Author(s)

Coronavirus, its neurologic manifestations, and complications

Context: We are going to face an epidemic of severe acute respiratory syndrome coronavirus (SARS-CoV-2) virus in our country. The main manifestation of this viral infection is respiratory and cardiovascular; however, up-to-date knowledge of its probable neurologic complications is highly needed. Evidence Acquisition: To provide up-to-date information on neurologic manifestation on coronaviruses, we concisely reviewed the neurologic manifestations and their complications. Using the keywords, coronavirus, corona, human coronaviruses (HCoVs), SARS, Middle East respiratory syndrome-related (MERS), coronavirus disease 2019 (COVID-19), manifestations, complications, and neurologic, all the relevant articles were retrieved from PubMed, reviewed, and critically analyzed. Results: Although the main clinical manifestation of human coronaviruses is respiratory involvement and the main cause of death is acute respiratory failure, extra respiratory manifestations such as neurologic findings have been reported. Fortunately, the neurologic manifestations in COVID-19 have not been reported yet. Conclusions: We need well-designed studies to monitor neurologic manifestations of COVID-19 in adults and children. © 2020, Author(s)

Anti-cancer potential of synergistic phytochemical combinations is influenced by the genetic profile of prostate cancer cell lines

Introduction: Despite strong epidemiological evidence that dietary factors modulate cancer risk, cancer control through dietary intervention has been a largely intractable goal for over sixty years. The effect of tumour genotype on synergy is largely unexplored. Methods: The effect of seven dietary phytochemicals, quercetin (0–100 μM), curcumin (0–80 μM), genistein, indole-3-carbinol (I3C), equol, resveratrol and epigallocatechin gallate (EGCG) (each 0–200 μM), alone and in all paired combinations om cell viability of the androgen-responsive, pTEN-null (LNCaP), androgen-independent, pTEN-null (PC-3) or androgen-independent, pTEN-positive (DU145) prostate cancer (PCa) cell lines was determined using a high throughput alamarBlue® assay. Synergy, additivity and antagonism were modelled using Bliss additivism and highest single agent equations. Patterns of maximum synergy were identified by polygonogram analysis. Network pharmacology approaches were used to identify interactions with known PCa protein targets. Results: Synergy was observed with all combinations. In LNCaP and PC-3 cells, I3C mediated maximum synergy with five phytochemicals, while genistein was maximally synergistic with EGCG. In contrast, DU145 cells showed resveratrol-mediated maximum synergy with equol, EGCG and genistein, with I3C mediating maximum synergy with only quercetin and curcumin. Knockdown of pTEN expression in DU145 cells abrogated the synergistic effect of resveratrol without affecting the synergy profile of I3C and quercetin. Discussion: Our study identifies patterns of synergy that are dependent on tumour cell genotype and are independent of androgen signaling but are dependent on pTEN. Despite evident cell-type specificity in both maximally-synergistic combinations and the pathways that phytochemicals modulate, these combinations interact with similar prostate cancer protein targets. Here, we identify an approach that, when coupled with advanced data analysis methods, may suggest optimal dietary phytochemical combinations for individual consumption based on tumour molecular profile