Reliability of Visually Estimated Blood Loss with Hemoglobin Measurement: 200 Cases of Craniosynostosis Surgery

Background Bleeding is one of the most common complications of craniosynostosis surgery, which its appropriate management is associated with better post-operative outcomes. The aim of this retrospective study was to evaluate the visual estimated blood loss in intraoperative management of infants with craniosynostosis surgery. Materials and Methods This retrospective study was performed on 200 patients who underwent craniocinostosis surgery and hospitalized in intensive care unit (ICU) at Mofid Hospital, Tehran, Iran, from July 2015 to June 2017. Data collecting was done using a self-made checklist and from patients' medical record. Required data include age, gender, method of anesthesia, and arterial blood gas (ABG), hemoglobin (Hb), and platelet (Plt) changes during surgery, volume of administered blood and fluid were recorded and evaluated. Data analysis using SPSS software (version 22.0). Results Among the patients, 59% (n=118) were boys, the mean age of patients was 13.3 ± 13.52 months. Anesthesia technics were total intravenous anesthesia (TIVA) (15.5%, n= 31), and inhalation or mixed (84.5%, n=169). Patients received 992.02 ± 468 ml fluid and 205.86± 100 ml blood, before surgery.There was no significant difference between preoperative Hb and first Hb in pediatric intensive care unit (PICU) (p=0.12). However, preoperative and first Plt in PICU were different (p=0.000). Also, last Hb in ABG (10.5±1.90), and the first Hb in PICU showed no significant difference (r=0.088, p=0.219). Conclusion According the results, visual assessment and correction of blood loss with hemoglobin measurement and by experienced anesthesiologist was a reliable and safe method in patients with craniosynostosis surgery and feasible in every operating room

Prediction of Marital Commitment based on Personality Traits, Attachment Styles, and Religious Orientation in Married Students

For downloading the full-text of this article please click here.Background and Objective: The marital commitment of couples is constructive in stabilization of family unit and various factors can influence the level of marital commitment. The current study aimed at revealing some of these factors through predicting martial commitment based on personality characteristics, attachment styles, and religious orientation in married students.Method: The study is descriptive and correlational. The statistical population consisted of all married female students of Lorestan University in 2014/2015 academic year. Through applying Cochran's formula, 200 subjects were selected among them as the sample, using convenient sampling method. In order to gather data, Martial Commitment Inventory (DCI) by Adams Jones, Adult Attachment Scale (AAS) by Collins and Read, Personality Inventory (NEO), and Religious Orientation Scale (ROS) by Allport and Ross were used. The data were analyzed using correlation coefficient and Step by Step Regression Analysis. All ethical issues were observed in this study and the researchers declared no conflict of interests.Results: The findings indicated that personality characteristics (F=28.37), the attachment styles (F=24.44), and also religious orientation (F=18.65) significantly predicted the level of marital commitment at the significance levels of 0.001, 0.05, and 0.001 respectively. Out of these factors, attachment styles were a stronger predictor for marital commitment.Conclusion: The results illustrated that people’s personality characteristics, the attachment styles formed in the family environment, and also their religious orientation have a direct effect on the personal relationship and martial commitment in the adulthood. The findings can be used to propose some strategies to maintain and develop productive relationship among couples and offer better training to people on how they should try to know each other.For downloading the full-text of this article please click here.Please cite this article as: Sadeghi M, Ghaderijavid S,Shalani B. Prediction of Marital Commitment based on Personality Traits, Attachment Styles, and Religious Orientation in Married Students. J Res Relig Health. 2019; 5(3): 18- 31. doi:https://doi.org/10.22037/jrrh.v5i3.2020

Investigating the relationship of self-esteem and spirituality to homesickness among dormitory students of Razi University in Kermanshah

For downloading the full-text of this article please click here.Background and Objective: University is considered a positive opportunity for personal development; however, students often face challenges when they are at university. Homesickness is among the most frequently reported concerns of dormitory students. This study aimed to investigate the relationship of self-esteem and spirituality to homesickness among dormitory students of Razi University in Kermanshah, Iran in 1395.Method: The study is descriptive and correlational. All female and male students who were living in dormitories of Razi University in school year of 94-95 formed the statistical population. 322 of them were selected based on Morgan table, using multi-stage cluster sampling. Research instruments were self-concept questionnaire (1976), spirituality questionnaire by Corp and Downing (2009), and homesickness questionnaire by Archer (1998). The data were analyzed using descriptive statistics, correlation coefficient, and regression. In this study, all ethical issues were carefully observed and the authors declare no conflict of interest.Results: The results showed that there is a significant negative relationship between self-esteem and homesickness (p<.01); also spirituality and homesickness (p<.001). Data analysis also demonstrated that spirituality can predict the extent of homesickness among university students living in dormitories (p< .001).Conclusion: According to the findings of this research, spirituality and self-esteem can be perceived as complementary tools to reduce homesickness. It seems that when dealing with homesickness, these two variables should be taken into account.For downloading the full-text of this article please click here

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions