A rare presentation of late right coronary artery spasm following aortic valve replacement

BACKGROUND: Coronary artery spasm (CAS) is defined as a reversible, sudden epicardial coronary artery stenosis that causes vessel occlusion or near occlusion. CASE REPORT: In this article, we present a clinical case of CAS in a 48-year-old woman undergoing elective aortic valve replacement surgery for aortic stenosis. On the 3rd post-operative day, the patient suffered from chest pain and dyspnea. Emergent coronary angiography demonstrated a significant spasm of the ostium portion of the right coronary artery. CONCLUSION: This case shows that delayed coronary spasm should be considered as a cause of hemodynamic instability after valvular surgery. © 2015, Isfahan University of Medical Sciences(IUMS). All rights reserved

Strong duality in conic linear programming: facial reduction and extended duals

The facial reduction algorithm of Borwein and Wolkowicz and the extended dual of Ramana provide a strong dual for the conic linear program $$(P) \sup {<c, x> | Ax \leq_K b}$$ in the absence of any constraint qualification. The facial reduction algorithm solves a sequence of auxiliary optimization problems to obtain such a dual. Ramana's dual is applicable when (P) is a semidefinite program (SDP) and is an explicit SDP itself. Ramana, Tuncel, and Wolkowicz showed that these approaches are closely related; in particular, they proved the correctness of Ramana's dual using certificates from a facial reduction algorithm. Here we give a clear and self-contained exposition of facial reduction, of extended duals, and generalize Ramana's dual: -- we state a simple facial reduction algorithm and prove its correctness; and -- building on this algorithm we construct a family of extended duals when $K$ is a {\em nice} cone. This class of cones includes the semidefinite cone and other important cones.Comment: A previous version of this paper appeared as "A simple derivation of a facial reduction algorithm and extended dual systems", technical report, Columbia University, 2000, available from http://www.unc.edu/~pataki/papers/fr.pdf Jonfest, a conference in honor of Jonathan Borwein's 60th birthday, 201

Parental wellbeing after diagnosing a child with biliary atresia:A prospective cohort study

PURPOSE: To determine anxiety, stress, and quality of life (QoL) in parents of children who are diagnosed with biliary atresia (BA). METHODS: Parents of BA patients (0-3 years) completed validated questionnaires at three time points: at first hospitalization (T0); 1-2 months post diagnosis (T1); and 2-3 years post diagnosis (T2). Results are presented in medians (min-max). RESULTS: We included 52 parents (age 31 [24-51 y], 31 females) of 30 BA patients. In fathers, neither anxiety nor stress levels significantly differed from reference values. Mothers reported significantly higher anxiety levels compared to reference values (T0: 48 vs 35, p = 0.001; T1: 43 vs 35, p = 0.03; T2: 37 vs 35, p = 0.04), which significantly decreased over time (-23% between T0 and T2: p = 0.04). Stress in mothers was significantly higher at T1 than at T2 (+35%, p = 0.02), but was not significantly different from reference values at each time point (T0: 17 vs 14, p = 0.07; T1: 18 vs 14, p = 0.09; T2: 13 vs 14, p = 0.52).The overall QoL in mothers and fathers was rather unaffected. CONCLUSIONS: Particularly mothers of infants diagnosed with BA report high anxiety levels up to three years after diagnosis. The overall QoL of parents is rather unaffected after diagnosing BA in their child. LEVEL OF EVIDENCE: Level 2

Long-Term Neurodevelopmental Outcomes in Children with Biliary Atresia

Objective: To assess long-term neurodevelopmental outcomes in school-aged children with biliary atresia. Study design: All Dutch children (6-12 years of age) diagnosed with biliary atresia were invited to participate in this study. We used validated neurodevelopmental tests to assess motor skills and cognition, and questionnaires to assess behavior. Scores were compared with the Dutch norm population, by means of 1-sample tests. Results are given as number and percentage or mean ± SD. Results: We included 46 children, with a median age of 11 years (range, 6-13 years); 36 children had undergone a liver transplantation (78%). Twelve children (26%) received special education (vs 2.4% in the norm population; P <.01). Motor outcomes were significantly affected compared with the norm population (P <.01), with 25% normal (vs 85%), 25% borderline (vs 10%), and 50% low scores (vs 5%). Total IQ was lower in patients with biliary atresia, compared with the norm population (91 ± 18 vs 100 ± 15; P <.01). There were no significant differences in test scores between children with native liver and after liver transplantation. Conclusions: School-aged children with biliary atresia show neurodevelopmental impairments compared with the norm population, especially in motor skills. Our data strongly warrant evaluation of neurodevelopmental intervention programs to assess whether long-term outcomes could be improved

Analyzing utilization of biomass in combined heat and power and combined cooling, heating, and power systems

Nowadays, ever-increasing energy demands and the depletion of fossil fuels require efficient and environmentally friendly technologies for energy generation. In this context, energy systems integration makes for a very strong proposition since it results in energy saving, fuel diversification, and the supply of cleaner energy. To this end, it is of the utmost importance to realize the current developments in this field and portray the state of the art of renewable generation in integrated energy systems. This review evaluates the utilization of bioenergy in cogeneration and trigeneration systems. The statistical reports of bioenergy and combined heat and power deployments in 28 countries of the European Union are discussed. Then, the most common research objectives of biomass-fueled combined heat and power systems are classified into three primary performance analyses, namely, energy and exergy analysis, thermo-economic optimization, and environment assessment. The influencing parameters of biomass utilization on each type of assessment are discussed, and the basic principles for carrying out such analyses in energy systems are explained. It is illustrated that the properties of feedstock, selection of appropriate conversion technology, associated costs with the biomass-to-bioenergy process, and sustainability of biomass are the primary influencing factors that could significantly affect the results of each assessment

Identification of disease-causing genes using microarray data mining and gene ontology

Background: One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small quantity of samples with respect to the number of genes. This problem reduces the classification accuracy of the methods, so gene selection is essential to improve the predictive accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVMRFE) has become one of the leading methods, but its performance can be reduced because of the small sample size, noisy data and the fact that the method does not remove redundant genes. Methods: We propose a novel framework for gene selection which uses the advantageous features of conventional methods and addresses their weaknesses. In fact, we have combined the Fisher method and SVMRFE to utilize the advantages of a filtering method as well as an embedded method. Furthermore, we have added a redundancy reduction stage to address the weakness of the Fisher method and SVMRFE. In addition to gene expression values, the proposed method uses Gene Ontology which is a reliable source of information on genes. The use of Gene Ontology can compensate, in part, for the limitations of microarrays, such as having a small number of samples and erroneous measurement results. Results: The proposed method has been applied to colon, Diffuse Large B-Cell Lymphoma (DLBCL) and prostate cancer datasets. The empirical results show that our method has improved classification performance in terms of accuracy, sensitivity and specificity. In addition, the study of the molecular function of selected genes strengthened the hypothesis that these genes are involved in the process of cancer growth. Conclusions: The proposed method addresses the weakness of conventional methods by adding a redundancy reduction stage and utilizing Gene Ontology information. It predicts marker genes for colon, DLBCL and prostate cancer with a high accuracy. The predictions made in this study can serve as a list of candidates for subsequent wet-lab verification and might help in the search for a cure for cancers

The outcome of olfactory impairment in patients with otherwise paucisymptomatic coronavirus disease 2019 during the pandemic

Objective This study aimed to measure the duration and recovery rate of olfactory loss in patients complaining of recent smell loss as their prominent symptom during the coronavirus disease 2019 outbreak. Method This was a prospective telephone follow-up observational study of 243 participants who completed an online survey that started on 12 March 2020. Results After a mean of 5.5 months from the loss of smell onset, 98.3 per cent of participants reported improvement with a 71.2 per cent complete recovery rate after a median of 21 days. The chance of complete recovery significantly decreased after 131 days from the onset of loss of smell (100 per cent sensitive and 97.7 per cent specific). Younger age and isolated smell loss were associated with a rapid recovery, whereas accompanying rhinological and gastrointestinal symptoms were associated with longer loss of smell duration. Conclusion Smell loss, occurring as a prominent symptom during the coronavirus disease 2019 pandemic, showed a favourable outcome. However, after 5.5 months from the onset, around 10 per cent of participants still complained of moderate or severe hyposmia. Copyright © The Author(s), 2021. Published by Cambridge University Press

Individualized prediction of three- and six-year outcomes of psychosis in a longitudinal multicenter study:a machine learning approach

Schizophrenia and related disorders have heterogeneous outcomes. Individualized prediction of long-term outcomes may be helpful in improving treatment decisions. Utilizing extensive baseline data of 523 patients with a psychotic disorder and variable illness duration, we predicted symptomatic and global outcomes at 3-year and 6-year follow-ups. We classified outcomes as (1) symptomatic: in remission or not in remission, and (2) global outcome, using the Global Assessment of Functioning (GAF) scale, divided into good (GAF &gt;= 65) and poor (GAF &lt; 65). Aiming for a robust and interpretable prediction model, we employed a linear support vector machine and recursive feature elimination within a nested cross-validation design to obtain a lean set of predictors. Generalization to out-of-study samples was estimated using leave-one-site-out cross-validation. Prediction accuracies were above chance and ranged from 62.2% to 64.7% (symptomatic outcome), and 63.5-67.6% (global outcome). Leave-one-site-out cross-validation demonstrated the robustness of our models, with a minor drop in predictive accuracies of 2.3% on average. Important predictors included GAF scores, psychotic symptoms, quality of life, antipsychotics use, psychosocial needs, and depressive symptoms. These robust, albeit modestly accurate, long-term prognostic predictions based on lean predictor sets indicate the potential of machine learning models complementing clinical judgment and decision-making. Future model development may benefit from studies scoping patient's and clinicians' needs in prognostication.</p

Breast cancer risk factors in Iran: A systematic review & Meta-analysis

Objectives: Breast cancer is known as one of the deadliest forms of cancer, and it is increasing globally. There are a variety of proven and controversial risk factors for this malignancy. Herein, we aimed to undertake a systematic review and meta-analysis focus on the epidemiology of breast cancer risk factors in Iran. Methods: We performed a systematic search via PubMed, Scopus, Web of Science, and Persian databases for identifying studies published on breast cancer risk factors up to March 2019. Meta-analyses were done for risk factors reported in more than one study. We calculated odds ratios (ORs) with corresponding 95 confidence intervals (CIs) using a fixed/random-effects models. Results: Thirty-nine studies entered into the meta-analysis. Pooling of ORs showed a significant harmful effect for risk factors including family history (OR: 1.80, 95CI 1.47-2.12), hormonal replacement therapy (HRT) (OR: 5.48, 95CI 0.84-1.74), passive smokers (OR: 1.68, 95CI 1.34-2.03), full-term pregnancy at age 30 (OR: 3.41, 95CI 1.19-5.63), abortion (OR: 1.84, 95CI 1.35-2.33), sweets consumption (OR: 1.71, 95CI 1.32-2.11) and genotype Arg/Arg (crude OR: 1.59, 95CI 1.07-2.10), whereas a significant protective effect for late menarche (OR: 0.58, 95CI 0.32-0.83), nulliparity (OR: 0.68, 95CI 0.39-0.96), 13-24 months of breastfeeding (OR: 0.68, 95CI 0.46-0.90), daily exercise (OR: 0.59, 95CI 0.44-0.73) and vegetable consumption (crude OR: 0.28, 95CI 0.10-0.46). Conclusions: This study suggests that factors such as family history, HRT, passive smokers, late full-term pregnancy, abortion, sweets consumption and genotype Arg/Arg might increase risk of breast cancer development, whereas late menarche, nulliparity, 13-24 months breastfeeding, daily exercise and vegetable consumption had an inverse association with breast cancer development. © 2020 Amir Shamshirian et al., published by De Gruyter