Selenium biochemistry and its role for human health

Despite its very low level in humans, selenium plays an important and unique role among the (semi)metal trace essential elements because it is the only one for which incorporation into proteins is genetically encoded, as the constitutive part of the 21st amino acid, selenocysteine. Twenty-five selenoproteins have been identified so far in the human proteome. The biological functions of some of them are still unknown, whereas for others there is evidence for a role in antioxidant defence, redox state regulation and a wide variety of specific metabolic pathways. In relation to these functions, the selenoproteins emerged in recent years as possible biomarkers of several diseases such as diabetes and several forms of cancer. Comprehension of the selenium biochemical pathways under normal physiological conditions is therefore an important requisite to elucidate its preventing/therapeutic effect for human diseases. This review summarizes the most recent findings on the biochemistry of active selenium species in humans, and addresses the latest evidence on the link between selenium intake, selenoproteins functionality and beneficial health effects. Primary emphasis is given to the interpretation of biochemical mechanisms rather than epidemiological/observational data. In this context, the review includes the following sections: (1) brief introduction; (2) general nutritional aspects of selenium; (3) global view of selenium metabolic routes; (4) detailed characterization of all human selenoproteins; (5) detailed discussion of the relation between selenoproteins and a variety of human diseases

Postoperative Chemoradiotherapy versus Radiotherapy Alone in Major Salivary Gland Cancers: A Stratified Study Based on the External Validation of the Distant Metastasis Risk Score Model

Background: The role of additional chemoradiotherapy (CRT) for distant metastasis (DM) on the resected malignancy of the major salivary gland (SGM) remained unknown. We conducted this study to externally validate a recently reported DM risk score model and compare the survival outcome between adjuvant CRT and RT alone. Materials: We retrospectively reviewed the patients with SGM following postoperative radiotherapy (PORT). The cumulative incidence of DM was assessed using a competing risk method. Multivariate analysis was performed with Cox proportional-hazards regression to identify significant predictors for DM. Patients were classified as high- and low-risk subgroups with the cutoff value of the DM risk score model. The inverse probability of treatment weighting (IPTW) was conducted to minimize the bias of the groups. Results: A total of 586 eligible patients were analyzed and 67 cases underwent adjuvant CRT. The 5-year incidence of DM was 19.5% (95% CI 16.0–23.0%). The model reasonably discriminated the DM risk between the high- and low-risk subgroup in our cohort, and the c-index was 0.75. No survival benefit was observed for the CRT group compared with RT alone in the entire cohort after IPTW (p = 0.095). After subgroup analysis, increased mortality was identified with the administration of CRT in the low-risk subset (p = 0.002) while no significant difference in OS was illustrated in the high-risk subgroup (p = 0.98). Conclusions: This external validation provides further exploration of the DM risk score model in major SGM. Our results demonstrated no support for the utility of additional chemotherapy to PORT in the major SGM, especially in the low-risk subgroup of patients with DM

Quantitative Metastatic Lymph Node Regions on Magnetic Resonance Imaging Are Superior to AJCC N Classification for the Prognosis of Nasopharyngeal Carcinoma

Purpose. Quantitative lymph node burden has been demonstrated to be a critical prognosticator in various malignancies, yet it was seldom explored in nasopharyngeal carcinoma (NPC). This study aimed to investigate the impact of the number of metastatic lymph node regions (LRN) on prognosis of NPC and to establish a new N classification system based on LRN. Methods and Materials. The magnetic resonance images (MRI) of 354 nondisseminated NPC patients before radical treatment were retrospectively evaluated. The regions with positive lymph nodes (LNs) were quantified according to 2013 updated guidelines for neck node levels. Prognostic value of LRN on distant metastasis-free survival (DMFS) was analyzed using multivariable Cox model after adjusting for other nodal characteristics and therapeutic factors. Results. LRN strongly correlated with the size, laterality, level, extracapsular extension (ECE), and necrosis of LNs. Risk of distant metastasis significantly escalated with increased LRN (P6cm (HR 4.11; 95% CI 2.23-7.56; P<0.001) were identified as independent predictors of DMFS. Laterality and level showed no prognostic significance when accounting for LRN. A novel N classification scheme was derived by recursive partitioning analysis based on LRN and MLD. Compared with the 7th and 8th edition of American Joint Committee on Cancer (AJCC) systems, the new stratification exhibited better accuracy in predicting survivals. Conclusions. LRN is a promising quantitative predictor of survival in NPC, eclipsing other classic LN characteristics in prognostic value. The simplified N classification scheme with LRN and MLD is predictive and practical, thus warranting further validation in future

Development and validation of a model for temporal lobe necrosis for nasopharyngeal carcinoma patients with intensity modulated radiation therapy

Abstract Purpose To develop and validate a quantitative complication model of temporal lobe necrosis (TLN). To analyze the effect of clinical and dosimetric factors on TLN. Patients and methods In this study the prediction model was developed in a training cohort that consisted of 256 nasopharyngeal carcinoma (NPC) patients from January 2009 to December 2009. Dosimetric and clinical factors were extracted for model building. Dosimetric factors including the maximum dose, minimum dose, mean dose, dose covering specific volume and dose of percentage volume. Clinical factors include age, gender, T/N-stage, overall stage, diabetes and hypertension. LASSO (least absolute shrinkage and selection operator) regression model was used for feature selection, and prediction model building. A testing cohort containing 493 consecutive patients from January 2010 to December 2010 was used for model validation. The performance of the prediction model was assessed with respect to its calibration, discrimination. Results The prediction model, which consisted of two dosimetric features (D0.5cc and D10), is significantly associated with LN status (P < .001 for both training and testing cohorts). None of clinical factors show direct prediction value. The model shows good discrimination, with a C-index of 0.685 (95% CI: 0.6048–0.765) on testing set, and a consistent trend in calibration on testing set. Conclusion This study presents a prediction model can be conveniently used to facilitate the individualized prediction of TLN in patients with NPC. Clinical factors have no direct impact on TLN

Advanced Process Simulation of Low Pressure Die Cast A356 Aluminum Automotive Wheels—Part II Modeling Methodology and Validation

This manuscript presents an advanced modeling methodology developed to accurately simulate the temperature field evolution in the die and wheel in an industrial low-pressure die casting (LPDC) machine employed in the production of A356 automotive wheels. The model was developed in the commercial casting simulation platform ProCAST for a production die operating under production conditions. Key elements in the development of the model included the definition of the resistance to heat transfer across the die/casting interfaces and die/water-cooling channel interfaces. To examine the robustness of the modeling methodology, the model was applied to simulate production and non-production process conditions for a die cooled by a combination of water and air-cooling (Die-A), and to a second die for a different wheel geometry (Die-B) utilizing only water cooling for production conditions. In each case, the model predictions with respect to in-die and in-wheel temperature evolution were compared to industrially derived thermocouple (TC) data, and were found to be in good agreement. Once tuned to the process conditions for Die-A operating under production conditions, no further tuning of the die/casting interface resistance was applied. Additionally, the model results, in terms of the prediction of pockets of solid encapsulated liquid, were used to compare to x-ray images of wheels. This comparison indicated that the model was able to predict clusters of porosity associated with encapsulated liquid with an equivalent radius of ~27 mm.Applied Science, Faculty ofNon UBCMaterials Engineering, Department ofReviewedResearcherFacult

Advanced Process Simulation of Low Pressure Die Cast A356 Aluminum Automotive Wheels—Part I, Process Characterization

In this work, a plant trial was conducted on an industrial low pressure die casting (LPDC) manufacturing process for the production of aluminum alloy wheels. Various types of data have been acquired, including extensive measurements of temperature at different locations (die, wheel and cooling channels), pressure in cooling channels and size/location of shrinkage porosity in the produced wheels. Moreover, two process conditions were tested in the trial—one was the standard production process condition and the other was designed to generate shrinkage porosity in wheels by altering the die temperature. The large amount of quantitative data acquired in this study helped us to understand the key transport phenomena occurring in the process, which include: (1) a thorough picture of the evolution in temperature at a large number of discrete locations in the die and the casting; (2) the dynamic and complicated heat transfer in the cooling channels both water-on and water-off stages, associated with boiling water heat transfer. This paper (Part I) presents the results and findings obtained from the process characterization. The follow-on paper (Part II) will introduce the developed modeling methodology based on the data produced from this work.Applied Science, Faculty ofNon UBCMaterials Engineering, Department ofReviewedFacult

Cloning and expression analysis of <i>BmYki</i> gene in silkworm, <i>Bombyx mori</i>

<div><p>The transcriptional coactivator Yorkie(Yki), is a critical downstream effector of the Hippo(Hpo) signaling pathway that controls organ size through the regulation of cell proliferation and apoptosis. During the past ten years the biological function of Yki has been studied extensively in <i>Drosophila</i> and a few other insects, however, little is known about it in the silkworm, <i>Bombyx mori</i>, a major research model of lepidopteran insect. Here, we describe the isolation, characterization and expression of the <i>B</i>. <i>mori</i> Yki ortholog, BmYki. The coding sequence of the <i>BmYki</i> was 1314 bp in length, encoding a protein of 437 amino acids containing two conserved WW domains. <i>BmYki</i> transcripts were ubiquitous but not abundant in all detected tissues and developmental stages. Comparatively, it was expressed at pretty high level in silk glands and at the stage of fifth-instar day-3 larvae. Overexpression of <i>BmYki</i> in cultured <i>B</i>. <i>mori</i> embryonic cells significantly promoted transcription of genes associated with cell proliferation and apoptosis, indicating that <i>BmYki</i> functions in the regulation of organ growth-related biological processes. Interestingly, transcription of silk protein-coding genes and transcription factors regulating the synthesis of silk proteins was downregulated remarkably, suggesting that <i>BmYki</i> was involved in the regulation of silk protein synthesis. This study provides new insights into the role of <i>BmYki</i> in Hpo pathway regulation in silkworm.</p></div

Expression profiles of <i>BmYki</i> in <i>B</i>. <i>mori</i>.

<p>(A)mRNA levels of <i>BmYki</i> in different tissues of <i>Dazao</i> strain. HD(head); EP(epidermis); FB (fat body); TR (trachea); HA(hemocyte); MG(midgut); MT(malpighian tubule); TE(testis); OV(ovary); ASG(anterior silk gland); MSG(middle silk gland); PSG(posterior silk gland); SG (total silk gland). (B)mRNA levels of <i>BmYki</i> at different developmental stages of <i>Dazao</i> strain. 1L-1, 2L-1, 3L-1, and 4L-1(day-1 of the first, second, third, and fourth larval instar); 5L-1, 5L-3, 5L-5, and 5L-7(day-1, 3, 5, and 7 of the fifth instar), P-1(day-1 of the pupal stage), MM-1 and FM-1(day-1 of the male and female moth). Relative mRNA levels of <i>BmYki</i> against <i>sw22934</i> are shown. Error bars represent mean ±SD of three samples.</p

Localization of BmYki-EGFP fusion proteins in BmN cells.

<p>The coding sequence of the BmYki with the stop codon deleted was fused to EGFP and transiently transfected into the BmN cells. Subcelluar localization of the expressed BmYki-EGFP fusion proteins was observed by fluorescence microscopy.</p