Miracle-dz/UniFAR-FTUs huggingface dataset:
Integration experiences of student and qualified nurses with disabilities who graduated from selected KwaZulu-Natal nursing education institutions: An exploratory case study

Background Despite the introduction of the Disability Policy Guidelines in South Africa (SA), student nurses who have disabilities (SNWDs) are still habitually and effectively excluded from nurse training programmes, and hence from the nursing profession. Yet SNWD may be able to offer a unique perspective. Objectives To explore and describe the integration experiences of both student and qualified nurses with disabilities who graduated from selected KwaZulu-Natal nursing education institutions (NEIs). Method A concurrent mixed-method design based on multiple embedded case studies served as the primary data collection instrument in this paper. The researcher initially conducted a survey of all the private NEIs to determine which had experienced training SNWDs; 3 cases and 10 embedded cases were selected, using non-probability purposive sampling. Individual interviews were conducted with students and qualified nurses with who have a disability (n = 10) who had graduated from NEIs. Results The findings of the study indicated that, largely, private NEIs are paving the way for integrating SNWDs; however, there are still some gaps in meeting the needs of these students. Despite strong legislative policies, an inclusive and enabling teaching and learning environment for SNWDs in nurse training remains largely absent. Conclusion The study recommends that NEIs develop policy guidelines for integrating SNWDs in nursing education programmes promoting an inclusive nursing education for SNWDs. The introduction of a disability liaison to assist SNWDs by liaising between key stakeholders and, perhaps, addressing many of the challenges that SNWDs experience in the clinical facilities where nursing personnel are unaware of their disability.
Health-related quality of life: Impact of surgery and treatment modality in breast cancer

Background: Breast cancer is the most common malignancy among women leading to serious sequelae on the health-related quality of life (HRQOL). Materials and Methods: This is a cross-sectional study. The Arabic version of EORTC QLQ-C30 (version 3) and EORTC QLQ-BR23 questionnaire was administered to a random sample of 172 Egyptian women with breast cancer. One hundred and nineteen patients had modified radical mastectomy (MRM) and 53 had breast conservative surgery (BCS). Results: The mean age was 50.32 years (±standard deviation [SD] = 8.54) with a mean period of 4.75 years (±SD 3.33) from surgery. The global health was poor (28.38 ± 11.7, 95% confidence interval [95% CI]: 30.71). Among the functional scales of QLQ-C30, social functioning scored the highest (87.91 ± 17.92, 95% CI: 91.64) whereas emotional functioning scored the lowest (59.61 ± 24.96, 95% CI: 64.66). The most distressing symptom on the symptom scales of QLQ-C30 was financial impact followed by fatigue and pain (mean: 57.87, 39.43, and 36.44). Using the disease-specific tools, it was found that body image and sexual functioning scored the lowest (mean 74.51 ± 13.21 and 74.45 ± 14.89, 95% CI: 77.27 and 77.55), respectively. On the symptom scale, arm symptoms scored the highest with a mean of 32.35 ± 23.22 (95% CI: 37.19). MRM patients had more favorable global health status and body image among the functional scale (P = 0.011, 0.027) due to social and religious issues. The functional scale was better in BCS with significant role function (P = 0.004). In the symptom scale, fatigue, pain, systemic side effects, and arm symptoms were statistically significant better in the BCS (P = 0.004, 0.006, 0.002, and 0.003, respectively). Conclusion: Egyptian breast cancer survivors reported lower overall global QOL. HRQOL is better in BCS in spite of good global health and body image in MRM.
Endocrine complications of celiac disease: a case report and review of the literature

ABSTRACT Purpose: The purpose of this article is to review recent literature regarding endocrine disorders related to celiac disease (CD). Methods: We describe a case report and review existing literature on the endocrine manifestations of CD. Results: CD is an autoimmune disorder characterized by intestinal inflammation in response to gluten. CD can cause a wide range of extra-intestinal complications, including endocrine manifestations. Metabolic bone disease including osteoporosis and osteopenia, vitamin D deficiency, secondary hyperparathyroidism and less frequently osteomalacia can be seen. In CD, fracture risk is increased by 30–40%, while risk for hip fracture is approximately doubled. The risk for other endocrine disorders, particularly autoimmune endocrinopathies, is also increased in those with CD compared to the general population. Epidemiologic data indicate the risk for hypothyroidism is 3–4 times higher among those with CD, while risk of type 1 diabetes is greater than double. Risk for primary adrenal insufficiency is a striking 11-fold higher in those with versus without CD, though the absolute risk is low. Fertility is reduced in women with CD before diagnosis by 37% while male fertility in the absence of hypogonadism does not appear to be affected. Other endocrine conditions including hyperthyroidism, ovarian failure, androgen insensitivity, impaired growth and growth hormone deficiency and autoimmune polyendocrine syndromes have also been associated with CD. Conclusions: CD is associated with a wide range of endocrine manifestations.
Deep Recurrent Survival Analysis

Survival analysis is a hotspot in statistical research for modeling time-to-event information with data censorship handling, which has been widely used in many applications such as clinical research, information system and other fields with survivorship bias. Many works have been proposed for survival analysis ranging from traditional statistic methods to machine learning models. However, the existing methodologies either utilize counting-based statistics on the segmented data, or have a pre-assumption on the event probability distribution w.r. t. time. Moreover, few works consider sequential patterns within the feature space. In this paper, we propose a Deep Recurrent Survival Analysis model which combines deep learning for conditional probability prediction at finegrained level of the data, and survival analysis for tackling the censorship. By capturing the time dependency through modeling the conditional probability of the event for each sample, our method predicts the likelihood of the true event occurrence and estimates the survival rate over time, i.e., the probability of the non-occurrence of the event, for the censored data. Meanwhile, without assuming any specific form of the event probability distribution, our model shows great advantages over the previous works on fitting various sophisticated data distributions. In the experiments on the three realworld tasks from different fields, our model significantly outperforms the state-of-the-art solutions under various metrics.
Engagement and social interaction in dementia care settings. A call for occupational and social justice

As full citizens, people with dementia are entitled to engage in social and occupational activities in residential care settings. Limitation or deprivation of choice and experience of valued occupations has been described elsewhere as occupational injustice. This research frames the unmet needs of people with dementia for occupation and social interaction, as issues of human rights and citizenship. It identifies a gap in current measurement tools of engagement in residential settings and in response, presents the Assessment Tool for Occupational and Social Engagement (ATOSE) as an objective measure of engagement. It examines results from a study of five residential care settings in Ireland using the ATOSE which included 73 residents with dementia and/or enduring mental health diagnoses. Residents spent on average, 38% of their time engaged and 62% of their time not engaged while in their communal sitting rooms. The ATOSE observations supported the rights of residents as citizens to have low levels of engagement addressed. A critical gerontology lens is employed to discuss concepts of citizenship, occupational justice, and social justice in the context of this research project.
The association between anxiety, traumatic stress, and obsessive–compulsive disorders and chronic inflammation: A systematic review and meta‐analysis

Anxiety is characterized by prolonged preparation for real or perceived threat. This may manifest both as psychological and physiological activation, ultimately leading to greater risk for poor health. Chronic inflammation may play an integral role in this relationship, given the influential role that it has in chronic illness. The aim of this meta‐analysis is to examine levels of chronic inflammation, measured by inflammatory cytokines and C‐reactive protein, in people with anxiety disorders, PTSD (posttraumatic stress disorder), or obsessive–compulsive disorder compared to healthy controls. Several moderating variables, including specific diagnosis and depression comorbidity, were also assessed.
Inflammatory myopathies after allogeneic stem cell transplantation

Introduction,: Graft‐versus‐host disease (GVHD) is a recognized complication of allogeneic stem cell transplantation (allo‐SCT) and may affect muscle. We investigated the incidence and subtypes of inflammatory myopathy (IM) in South Australian recipients of allo‐SCT. Methods: Recipients of allo‐SCT from 2004 to 2014 at the Royal Adelaide Hospital were identified. Records were reviewed to identify patients with weakness, creatine kinase (CK) elevation, and muscle biopsy confirming IM. Results: Weakness was present in 32 of 224 patients who received allo‐SCT patients reviewed, and CK was raised in 7 of 20 patients with weakness. Six patients developed biopsy‐confirmed IM; 3 patients had chronic GVHD‐related myopathy, 2 had necrotizing myopathy, and 1 had dermatomyositis (DM) associated with anti–melanoma differentiation associated protein 5 (MDA5) antibodies. The incidence of IM was calculated to be 2 cases per thousand annually. Discussion: Among recipients of allo‐SCT, weakness is common, and the incidence of IM is increased. Histopathological diagnoses are varied, and we report findings of necrotizing myopathy and anti‐MDA5‐associated DM. Muscle Nerve 58:790–795, 2018
Nomogram Using Optical Coherence Tomography and Visual Field Parameters to Predict Brain Lesions in Patients with Bitemporal Hemianopia

ABSTRACT Purpose: This study aims to develop a nomogram to predict brain lesions in patients with complete or incomplete bitemporal hemianopia by combining results from optical coherence tomography (OCT) and visual field (VF) testing. Material and Methods: We reviewed the medical records of patients who underwent magnetic resonance imaging (MRI) to identify brain lesions due to bitemporal hemianopia between January 2010 and March 2017, retrospectively. The patients were divided into two groups based on MRI findings: brain-lesion (+) group that had brain lesions on MRI (n = 63), and brain-lesion (-) group without brain lesions on MRI (n = 16). We compared OCT and VF findings between the two groups to find factors that could predict a brain lesion. Multiple logistic regression analysis was performed to select prognostic factors, and we constructed a nomogram to predict brain lesions on MRI. Result: The VF mean deviation was lower (p = 0.011) and all sectors of peripapillary retinal nerve fiber layer thickness except the temporal region were thicker in the brain-lesion (+) group. However, there was no statistically significant difference in macular ganglion cell-inner plexiform layer between the two groups. The area under the receiver operating characteristic curve of the nomogram for predicting brain lesions on MRI was 0.916. Conclusion: We developed a nomogram using VF and OCT examinations as a novel and accurate screening method to predict brain lesions in patients with bitemporal hemianopia and aid ophthalmologists and other clinicians in deciding whether to further evaluate a patient by MRI.
Sodium and potassium conductances in principal neurons of the mouse piriform cortex: a quantitative description

The primary olfactory (or piriform) cortex is a promising model system for understanding how the cerebral cortex processes sensory information, although an investigation of the piriform cortex is hindered by a lack of detailed information about the intrinsic electrical properties of its component neurons. In the present study, we quantify the properties of voltage‐dependent sodium currents and voltage‐ and calcium‐dependent potassium currents in two important classes of excitatory neurons in the main input layer of the piriform cortex. We identify several classes of these currents and show that their properties are similar to those found in better‐studied cortical regions. Our detailed quantitative descriptions of these currents will be valuable to computational neuroscientists who aim to build models that explain how the piriform cortex encodes odours.
Evidence for Introgression Among Three Species of the Anastrepha fraterculus Group, a Radiating Species Complex of Fruit Flies

Introgression should no longer be considered as rare a phenomenon as once thought, since several studies have recently documented gene flow between closely related and radiating species. Here, we investigated evolutionary relationships among three closely related species of fruit flies of the Anastrepha fraterculus group (Anastrepha fraterculus, A. obliqua and A. sororcula). We sequenced a set of 20 genes and implemented a combined populational and phylogenetic inference with a model selection approach by an ABC framework in order to elucidate the demographic history of these species. The phylogenetic histories inferred from most genes showed a great deal of discordance and substantial shared polymorphic variation. The analysis of several population and speciation models reveal that this shared variation is better explained by introgression rather than convergence by parallel mutation or incomplete lineage sorting. Our results consistently showed these species evolving under an isolation with migration model experiencing a continuous and asymmetrical pattern of gene flow involving all species pairs, even though still showed a more closely related relationship between A. fraterculus and A. sororcula when compared with A. obliqua. This suggests that these species have been exchanging genes since they split from their common ancestor ∼2.6 MYA ago. We also found strong evidence for recent population expansion that appears to be consequence of anthropic activities affecting host crops of fruit flies. These findings point that the introgression here found may have been driven by genetic drift and not necessary by selection, which has implications for tracking and managing fruit flies.
Serum and Adipose Tissue mRNA Levels of ATF3 and FNDC5/Irisin in Colorectal Cancer Patients With or Without Obesity

Objectives: To explore the activating transcription factor 3 (ATF3) and fibronectin type III domain-containing protein 5 (FNDC5)/irisin protein levels in serum and mRNA levels in subcutaneous and visceral white adipose tissue (sWAT and vWAT) in normal-weight (NW) and overweight/obese (OW/OB) patients with colorectal cancer (CRC). Methods: 76 CRC patients and 40 healthy controls were recruited. Serum ATF3 and irisin levels were detected by using ELISA kits, and the mRNA expression levels in sWAT and vWAT were measured by performing RT-qPCR. Results: The serum ATF3 levels were greater by 37.2%, whereas the irisin levels were lower by 23.3% in NW+CRC patients compared with those in healthy controls. CRC was independently associated with both ATF3 and irisin levels. The probability of CRC greater by 22.3-fold in individuals with high ATF3 levels compared with those with low ATF3 levels, whereas the risk of CRC in subjects with high irisin levels was lower by 78.0% compared to the risk in those with low irisin levels after adjustment for age, gender, BMI, and other biochemical parameters. Serum ATF3 and irisin could differentiate CRC patients from controls with receiver operating characteristic (ROC) curve areas of 0.745 (95% CI, 0.655–0.823) and 0.656 (95% CI, 0.561–0.743), respectively. The combination of ATF3 and irisin exhibited improved diagnosis value accuracy with ROC curve areas of 0.796 (95% CI, 0.710–0.866) as well as 72.6% sensitivity and 80.0% specificity. Conclusion: Increased ATF3 and reduced irisin levels were observed in sera from CRC patients. Individuals with high ATF3 and low irisin levels were more likely to have CRC. ATF3 and irisin represent potential diagnostic biomarkers for CRC patients.
Effect of adipocyte-derived IGF-I on adipose tissue mass and glucose metabolism in the Berlin Fat Mouse

Abstract Besides liver, IGF-I is expressed in adipose tissue. However, the effects of this local IGF-I on adipose tissue and metabolism are unclear. We generated adipocyte-specific knock-out mice on the background of the Berlin Fat Mouse Inbred (BFMI) line to evaluate the contribution of adipocyte-IGF-I on glucose metabolism and adipose tissue development. BFMI mice are obese, non-diabetic with elevated plasma insulin and IGF-I concentration. The knock-out in adipocytes led to a total white adipose tissue expression of 50–60% due to unaltered Igf-1 expression in stromavascular cells. The lack of IGF-I from adipocytes did not alter plasma IGF-I concentration. BFMIChr3-Igf-I-KOQ-AT mice had reduced adipose tissue mass in most depots. During oral glucose tolerance tests, BFMIChr3-Igf-I-KOQ-AT mice showed an impaired glucose clearance (p = .03). Interestingly, insulin action was enhanced during insulin tolerance tests (p = .05). In conclusion, adipocyte-specific IGF-I ablation in obese BFMI mice results in reduced adipose tissue mass and thereby alters glucose metabolism.
Improving On-policy Learning with Statistical Reward Accumulation

Deep reinforcement learning has obtained significant breakthroughs in recent years. Most methods in deep-RL achieve good results via the maximization of the reward signal provided by the environment, typically in the form of discounted cumulative returns. Such reward signals represent the immediate feedback of a particular action performed by an agent. However, tasks with sparse reward signals are still challenging to on-policy methods. In this paper, we introduce an effective characterization of past reward statistics (which can be seen as long-term feedback signals) to supplement this immediate reward feedback. In particular, value functions are learned with multi-critics supervision, enabling complex value functions to be more easily approximated in on-policy learning, even when the reward signals are sparse. We also introduce a novel exploration mechanism called "hot-wiring" that can give a boost to seemingly trapped agents. We demonstrate the effectiveness of our advantage actor multi-critic (A2MC) method across the discrete domains in Atari games as well as continuous domains in the MuJoCo environments. A video demo is provided at https://youtu.be/zBmpf3Yz8tc.
Making the Most of Your Research Budget: Efficiency of a Three-Method Measurement Design With Planned Missing Data

Planned missing data (PMD) designs are an elegant way to incorporate expensive gold standard methods (e.g., biomarker) and cheaper but systematically biased methods (e.g., questionnaires) in research designs while ensuring high statistical power and low research costs. This article outlines a PMD design with one expensive gold standard and two cheap but biased methods (three-method measurement [3-MM] design). The cost effectiveness of different 3-MM-PMD designs is investigated and compared with the cost effectiveness of corresponding same-price two-method measurement designs using a simulation study. The results underline that PMD designs yield higher statistical power compared with complete data designs in a wide variety of conditions. Adding a second cheap method to the measurement model (i.e., using a 3-MM-PMD design) can increase the statistical power of the research design even further while keeping costs constant, when the additional measure is inexpensive, shares only small amounts of bias variance with the initial cheap measure, and when the gold standard measure is highly expensive compared with the cheap measures. Recommendations as well as a computer program for finding the optimal research design are provided.
Sparse Kernel PCA for Outlier Detection

In this paper, we propose a new method to perform Sparse Kernel Principal Component Analysis (SKPCA) and also mathematically analyze the validity of SKPCA. We formulate SKPCA as a constrained optimization problem with elastic net regularization in kernel feature space and solve it. We consider outlier detection (where KPCA is employed) as an application for SKPCA, using the RBF kernel. We test it on 5 real world datasets and show that by using just 4% (or even less) of the principal components (PCs), where each PC has on average less than 12% non-zero elements in the worst case among all 5 datasets, we are able to nearly match and in 3 datasets even outperform KPCA. We also compare the performance of our method with a recently proposed method for SKPCA and show that our method performs better in terms of both accuracy and sparsity. We also provide a novel probabilistic proof to justify the existence of sparse solutions for KPCA using the RBF kernel. To the best of our knowledge, this is the first attempt at theoretically analyzing the validity of SKPCA.
National Trends and Factors Associated With Inpatient Mortality in Adult Patients With Opioid Overdose

BACKGROUND: The prevalence of opioid misuse and opioid-related mortality has increased dramatically over the past decade. There is limited evidence on factors associated with mortality from opioid overdose in the inpatient setting. The primary objective was to report national trends in opioid overdose and mortality. The secondary objectives were to explore factors associated with inpatient mortality and report differences in prescription opioid overdose (POD) versus illicit opioid overdose (IOD) cohorts. METHODS: Using the 2010–2014 Nationwide Inpatient Sample, we performed a cross-sectional analysis and identified a weighted estimate of 570,987 adult patients with an International Classification of Disease, Ninth Revision, or External Cause of Injury code of POD or IOD. We performed multivariable logistic regression to identify predictors of inpatient mortality. The odds ratio (OR) and their associated 95% confidence interval (CI) are reported. RESULTS: Of the 570,987 patients with opioid overdose, 13.8% had an admissions diagnosis of IOD, and the remaining had POD. Among all opioid overdose admissions, the adjusted odds of IOD admissions increased by 31% per year (OR, 1.31; 95% CI, 1.29–1.31; P < .001); however, the adjusted odds POD admissions decreased by 24% per year (OR, 0.76; 95% CI, 0.75–0.77; P < .001). The mortality was 4.7% and 2.3% among IOD and POD admissions, respectively. The odds of inpatient mortality increased by 8% per year among IOD admissions (OR, 1.08; 95% CI, 1.02–1.14; P < .007). The odds of inpatient mortality increased by 6% per year among all POD admissions (OR, 1.06; 95% CI, 1.03–1.09; P < .001). Those with IOD compared to POD had higher odds of mortality (OR, 2.03; 95% CI, 1.79–2.29; P < .001). Patients with age ≥80 years of age and those with a diagnosis of a solid tumor malignancy had higher odds of mortality. Odds of inpatient mortality were decreased in African American versus Caucasian patients and in patients undergoing alcohol rehabilitation therapy. CONCLUSIONS: The increase in mortality provides a strong basis for further risk reduction strategies and intervention program implementation. Medical management of not only the opioid overdose but also the comorbidities calls for a multidisciplinary approach that involves policy makers and health care teams.