Morphology of Intestinal Goblet Cells of The Dromedary (Camelus dromedarius)

Morphology of the goblet cells in the intestine of the dromedary (Camelus dromedarius ) was carried out by light and electron microscopes. Histologically, the goblet cells appeared as globular or ovoidshaped with basally located flat nuclei. They were dispersed among the columnar cells lining the epithelia of the villi and crypts of Lieberkuhn, and they increased greatly in number towards the rectum. Goblet cells showed positive reaction to (PAS) stain. Ultrastructurally, the scanning electron microscopy showed villi with rough surface which displayed goblet cells and microvilli in the small intestine. In the large intestine, the surface of the mucosal fold was characteristically covered by goblet cells and epithelial cells. The ultrastructure of the goblet cells showed the cell membrane lacked microvilli and the cytoplasm contained numerous large spherical granules of mucin, rough endoplasmic reticulum and mitochondria. The nucleus containing eccentric nucleolus, chromatin and heterochromatin materials.Key words: dromedary, goblet cells, intestine, morpholog

Early Mechanical Alterations in Phospholamban Mutation Carriers: Identifying Subclinical Disease Before Onset of Symptoms

OBJECTIVES: This study aimed to explore echocardiographic characteristics of phospholamban (PLN) p.Arg14del mutation carriers to investigate whether structural and/or functional abnormalities could be identified before onset of symptoms. BACKGROUND: Carriers of the genetic PLN p.Arg14del mutation may develop arrhythmogenic and/or dilated cardiomyopathy. Overt disease is preceded by a pre-symptomatic phase of variable length in which disease expression seems to be absent. METHODS: PLN p.Arg14del mutation carriers with an available echocardiogram were included. Mutation carriers were classified as pre-symptomatic if they had no history of ventricular arrhythmias (VAs), a premature ventricular complex count of <500/24 h, and a left ventricular (LV) ejection fraction of ≥45%. In addition, we included 70 control subjects with similar age and sex distribution as the pre-symptomatic mutation carriers. Comprehensive echocardiographic analysis (including deformation imaging) was performed. RESULTS: The final study population consisted of 281 PLN p.Arg14del mutation carriers, 139 of whom were classified as pre-symptomatic. In comparison to control subjects, pre-symptomatic mutation carriers had lower global longitudinal strain and higher LV mechanical dispersion (both p < 0.001). In addition, post-systolic shortening (PSS) in the LV apex was observed in 43 pre-symptomatic mutation carriers (31%) and in none of the control subjects. During a median follow-up of 3.2 years (interquartile range: 2.1 to 5.6 years) in 104 pre-symptomatic mutation carriers, nonsustained VA occurred in 13 (13%). Presence of apical PSS was the strongest echocardiographic predictor of VA (multivariable hazards ratio: 5.11; 95% confidence interval [CI]: 1.37 to 19.08; p = 0.015), which resulted in a negative predictive value of 96% (95% CI: 89% to 98%) and a positive predictive value of 29% (95% CI: 21% to 40%). CONCLUSIONS: Global and regional LV mechanical alterations in PLN p.Arg14del mutation carriers precede arrhythmic symptoms and overt structural disease. Pre-symptomatic mutation carriers with normal deformation patterns in the apex are at low risk of developing VA within 3 years, whereas mutation carriers with apical PSS appear to be at higher risk

Prediction of ventricular arrhythmia in phospholamban p.Arg14del mutation carriers–reaching the frontiers of individual risk prediction

Aims: This study aims to improve risk stratification for primary prevention implantable cardioverter defibrillator (ICD) implantation by developing a new mutation-specific prediction model for malignant ventricular arrhythmia (VA) in phospholamban (PLN) p.Arg14del mutation carriers. The proposed model is compared to an existing PLN risk model. / Methods and results: Data were collected from PLN p.Arg14del mutation carriers with no history of malignant VA at baseline, identified between 2009 and 2020. Malignant VA was defined as sustained VA, appropriate ICD intervention, or (aborted) sudden cardiac death. A prediction model was developed using Cox regression. The study cohort consisted of 679 PLN p.Arg14del mutation carriers, with a minority of index patients (17%) and male sex (43%), and a median age of 42 years [interquartile range (IQR) 27-55]. During a median follow-up of 4.3 years (IQR 1.7-7.4), 72 (10.6%) carriers experienced malignant VA. Significant predictors were left ventricular ejection fraction, premature ventricular contraction count/24 h, amount of negative T waves, and presence of low-voltage electrocardiogram. The multivariable model had an excellent discriminative ability {C-statistic 0.83 [95% confidence interval (CI) 0.78-0.88]}. Applying the existing PLN risk model to the complete cohort yielded a C-statistic of 0.68 (95% CI 0.61-0.75). / Conclusion: This new mutation-specific prediction model for individual VA risk in PLN p.Arg14del mutation carriers is superior to the existing PLN risk model, suggesting that risk prediction using mutation-specific phenotypic features can improve accuracy compared to a more generic approach

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children &lt;18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p&lt;0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p&lt;0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p&lt;0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer

A clinical prediction model for hospitalized COPD exacerbations based on &ldquo;treatable traits&rdquo;

Anthony CA Yii,1 CH Loh,1 PY Tiew,2,3 Huiying Xu,4 Aza AM Taha,1 Jansen Koh,1 Jessica Tan,5 Therese S Lapperre,6,7 Antonio Anzueto,8 Augustine KH Tee1 1Department of Respiratory and Critical Care Medicine, Changi General Hospital, Singapore; 2Department of Respiratory and Critical Care Medicine, Singapore General Hospital, Singapore; 3Translational Respiratory Research Laboratory, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; 4Department of Respiratory and Critical Care Medicine, Tan Tock Seng Hospital, Singapore; 5Department of General Medicine, Sengkang General Hospital, Singapore; 6Department of Respiratory Medicine, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark; 7Duke-National University of Singapore Medical School, Singapore; 8Division of Pulmonary Diseases and Critical Care Medicine, Department of Medicine, UT Health Science Center, San Antonio, TX, USA Background: Assessing risk of future exacerbations is an important component in COPD management. History of exacerbation is a strong and independent predictor of future exacerbations, and the criterion of &ge;2 nonhospitalized or &ge;1 hospitalized exacerbation is often used to identify high-risk patients in whom therapy should be intensified. However, other factors or &ldquo;treatable traits&rdquo; also contribute to risk of exacerbation.Objective: The objective of the study was to develop and externally validate a novel clinical prediction model for risk of hospitalized COPD exacerbations based on both exacerbation history and treatable traits.Patients and methods: A total of 237 patients from the COPD Registry of Changi General Hospital, Singapore, aged 75&plusmn;9 years and with mean post-bronchodilator FEV1 60%&plusmn;20% predicted, formed the derivation cohort. Hospitalized exacerbation rate was modeled using zero-inflated negative binomial regression. Calibration was assessed by graphically comparing the agreement between predicted and observed annual hospitalized exacerbation rates. Predictive (discriminative) accuracy of the model for identifying high-risk patients (defined as experiencing &ge;1 hospitalized exacerbations) was assessed with area under the curve (AUC) and receiver operating characteristics analyses, and compared to other existing risk indices. We externally validated the prediction model using a multicenter dataset comprising 419 COPD patients.Results: The final model included hospitalized exacerbation rate in the previous year, history of acute invasive/noninvasive ventilation, coronary artery disease, bronchiectasis, and sputum nontuberculous mycobacteria isolation. There was excellent agreement between predicted and observed annual hospitalized exacerbation rates. AUC was 0.789 indicating good discriminative accuracy, and was significantly higher than the AUC of the Global Initiative for Chronic Obstructive Lung Disease (GOLD) risk assessment criterion (history of &ge;1 hospitalized exacerbation in the previous year) and the age, dyspnea, and obstruction index. When applied to the independent multicenter validation cohort, the model was well-calibrated and discrimination was good.Conclusion: We have derived and externally validated a novel risk prediction model for COPD hospitalizations which outperforms several other risk indices. Our model incorporates several treatable traits which can be targeted for intervention to reduce risk of future hospitalized exacerbations. Keywords: exacerbations, clinical prediction model, risk assessment &nbsp