Students' perception of e-learning during the Covid-19 pandemic: a survey study of Iranian nutrition science students

BACKGROUND

COVID-19 pandemic caused university closures, which created learning challenges for students worldwide. Switching to online educational systems had significant impact on students' performances. The current study aims to investigate the perception of university students from the Nutrition Science department regarding e-learning in Iran.

METHODS

The design of the study is cross-sectional. Data were collected through online surveys from Iranian students from the Nutrition Sciences Department. Stratified random sampling was used to randomly select 955 participants. A self-administered validated questionnaire was used for data collection. Descriptive statistics, Analysis of Variance (ANOVA) and Chi-Square tests were used for analysis of the data.

RESULTS

Results revealed that 67.2% of students didn't have any former experience of e-learning. About 38.3% had moderate levels of Information Technology (IT) skills. Our results revealed that based on students' responses, being able to stay at home was one of the most common benefits of e-learning (39.1%). However, the most common challenge that students faced was related to technical problems (39.6%). When compared to e-learning, most students preferred face-to face type of learning. Students believed that this method no only increased their knowledge but also their skills and social competence as compared to e-learning. Only 28% of students rated e-learning as enjoyable. Furthermore, acceptance of online based education was statistically associated with students' degree level.

CONCLUSION

In conclusion, students reported both advantages and disadvantages of e-learning but still reported that face-to-face learning is considered the most effective form of learning.

Applying an interpretive machine learning algorithm to predict in-hospital mortality in elderly asian patients with acute coronary syndrome (ACS)

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Mosti TED1 grant

Background

No study has used interpretative Machine Learning (ML) algorithms to predict in-hospital mortality for the Asian elderly (65+). TIMI predicts mortality for STEMI and NSTEMI using two different scores. It was based on the Western cohort with limited Asian data.

Purpose

Develop a single mortality risk scoring system for STEMI and NSTEMI patients and use interpretative ML to identify and analyse risk factors in elderly Asian patients with ACS.

Methods

The National Cardiovascular Disease Database registry identified 4305 elderly. 70% of the data was used to develop algorithms and 30% for validation. Fifty-four parameters were considered, including demographics, cardiovascular risk, medications, and clinical variables. A sequential backward elimination (SBE) algorithm was used to identify variables associated to elderly mortality. XGBoost classification algorithm and SHapley Additive exPlanation (SHAP) were used to understand mortality impact. The SHAP value of each variable represents its impact on model output (mortality). The main performance metric was area under the curve (AUC). The model was validated using a validation dataset and compared to STEMI and NSTEMI for TIMI.

Results

XGBoost's validation dataset performance using the top 12 predictors from SBE for; STEMI (AUC = 0.822, 95% CI: 0.775-0.868, Accuracy: 0.875, Sensitivity: 0.164, Specificity: 0.966) and NSTEMI (AUC = 0.853, 95% CI: 0.802-0.904, Accuracy: 0.950, Sensitivity: 0.154, Specificity: 0.997). XGBoost's validation dataset performance using the eight emergency predictors selected from the top twelve predictors for; STEMI (AUC = 0.813, 95% CI: 0.766-0.861, Accuracy: 0.868, Sensitivity: 0.194, Specificity 0.954) and NSTEMI (AUC = 0.867, 95% CI: 0.812-0.921, Accuracy: 0.941, Sensitivity: 0.333, Specificity: 0.978). Both models outperformed TIMI score (STEMI AUC = 0.702, NSTEMI AUC = 0.524). The predictors were chosen and ranked in ascending order using the SHAP values (Figure 1). On the y-axis, the variable names are displayed in ascending order of importance and the colour represents the feature's value, ranging from low to high, allowing comprehension of the distribution of SHAP values for each feature. The x-axis displays the SHAP values. Eight out of the twelve predictors were identified to be emergency variables and was ranked according to SHAP values (Figure 2). When compared to TIMI, cardiac catheterization, percutaneous coronary intervention, and pharmacotherapy drugs are chosen as predictors that improve mortality prediction in STEMI and NSTEMI elderly patients. High killip class and age are linked to a poorer ACS patient survival rate, but cardiac catheterization and use of pharmacotherapy drugs improve patient mortality.

Conclusions

A single algorithm can better classify elderly ASIAN patients with ACS than TIMI, which requires two scores. The use of interpretative algorithms aids in the understanding of ACS elderly hospital mortality factors.

Clinical and Molecular Epidemiological Study on Herpesviruses Infection among Equid Populations in Upper Egypt

The present study was carried out to record the clinical signs of equine herpesviruses (EHVs) infection and to detect the prevalence of EHVs infection among working equids in different provinces of Egypt. A total number of 115 working equids (92 horses and 23 donkeys) were clinically examined and sampled from November 2018 till November 2019 for this study. Two samples were collected from each animal (nasal swab and blood sample) and were subjected to multiplex-PCR to detect the prevalence of different EHVs infection among equids. In the current study, the overall prevalence of EHVs infection among equid populations in Egypt was 80% by using multiplex-PCR. Moreover, the most prevalent equine herpesvirus (EHV) among equids in Upper Egypt was EHV-2 (61.74%), followed by EHV-5 (43.48%), EHV-1 (20%), and EHV-4 (13.04%). The recorded clinical signs of the examined equids harbored EHVs (PCR-positive) can be summarized as follow: a higher percentage was detected among equids with a history of acute onset (59.78%), pyrexia (57.61%), and/or systemic illness (45.65%) with or without respiratory signs (56.52%) and ocular signs (35.87%). Furthermore, 4.35% and 1.09% of EHV-1 PCR-positive equids displayed neurological signs and abortion, respectively.  

30 days mortality prediction and risk factor analysis of Asian patients with ACS using interpretable machine learning algorithm

Background

Thrombolysis in Myocardial Infarction (TIMI) is used to predict the mortality rate in patients with acute coronary syndrome (ACS). TIMI was developed with limited data on the Asian cohort and was based on the Western cohort. STEMI and NSTEMI have separate TIMI scores. There has been limited research on Asian ACS patients using interpretable machine learning (ML) algorithms.

Purpose

To construct a single 30-day mortality risk scoring system, as well as identify and analyse risk factors in ASIAN patients with ACS, that is applicable to both STEMI and NSTEMI patients, using an interpretable ML algorithm.

Methods

The National Cardiovascular Disease Database registry data of 9054 patients was used. 70% of the data was used for algorithm development, with the remaining 30% used for validation Fifty-four parameters were considered, demographics, cardiovascular risk, medications, and clinical variables. To provide better guidance and advice for clinical judgement, the gradient boosting algorithm (XGBoost) for classification analysis and SHapley Additive exPlanation (SHAP) value analysis graphs were used. Each indicator's SHAP value indicates the impact on model output (mortality) and was calculated using the XGBoost model. The performance evaluation metric was the area under the curve (AUC). The model was validated with a validation dataset and compared to the conventional score TIMI for STEMI and NSTEMI.

Results

The performance on validation dataset of the XGBoost algorithm using the top ten predictors from SHAP for; STEMI (AUC = 0.8534, 95% CI: 0.8226–0.8842, Accuracy: 0.8053, Sensitivity: 0.73125, Specificity: 0.81355) and NSTEMI (AUC = 0.8145, 95% CI: 0.77–0.8589, Accuracy: 0.7972, Sensitivity: 0.64356, Specificity: 0.81232) outperformed TIMI score (STEMI AUC = 0.785, NSTEMI AUC = 0.543). Killip class, age, heart rate, fasting blood glucose, ACEI, creatine kinase, systolic blood pressure, HDLC, cardiac catheterization, and oralhypogly are the top ten predictors chosen by the SHAP feature selection in ascending order. Cardiac catheterization and pharmacotherapy drugs as selected predictors improve mortality prediction in STEMI and NSTEMI patients compared to TIMI. The variable names are displayed on the y-axis in ascending order of importance. The average SHAP value is shown next to them. The SHAP value is shown on the x-axis. The colour represents the value of the feature, ranging from small to large, allowing comprehension of the distribution of the SHAP values for each feature (Figure 1). We can see that having a high killip class and being older are linked to a lower survival rate in ACS patients. Cardiac catheterization procedures, as well as the use of ACEI and OHA, both improve patient mortality (Figure 2).

Conclusions

A single algorithm would classify ACS patients better than TIMI, which requires two distinct scores. In order to better predict 30-day mortality in an ASIAN population, interpretable ML can be used.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Technology Development Fund 1

Association of vitamin D deficiency with COVID-19 severity and mortality in Iranian people: a prospective observational study

Background

As the coronavirus disease 2019 (COVID-19) pandemic continues to escalate, it is important to identify the prognostic factors related to increased mortality and disease severity. To assess the possible associations of vitamin D level with disease severity and survival, we studied 248 hospitalized COVID-19 patients in a single center in a prospective observational study from October 2020 to May 2021 in Tehran, Iran.

Methods

Patients who had a record of their 25-hydroxyvitamin D level measured in the previous year before testing positive with COVID-19 were included. Serum 25-hydroxyvitamin D level was measured upon admission in COVID-19 patients. The associations between clinical outcomes of patients and 25-hydroxyvitamin D level were assessed by adjusting for potential confounders and estimating a multivariate logistic regression model.

Results

The median (interquartile range) age of patients was 60 years (44–74 years), and 53% were male. The median serum 25-hydroxyvitamin D level prior to admission decreased with increasing COVID-19 severity (P=0.009). Similar findings were obtained when comparing median serum 25-hydroxyvitamin D on admission between moderate and severe patients (P=0.014). A univariate logistic regression model showed that vitamin D deficiency prior to COVID-19 was associated with a significant increase in the odds of mortality (odds ratio, 2.01; P=0.041). The multivariate Cox model showed that vitamin D deficiency on admission was associated with a significant increase in risk for mortality (hazard ratio, 2.35; P=0.019).

Conclusions:

Based on our results, it is likely that deficient vitamin D status is associated with increased mortality in COVID-19 patients. Thus, evaluating vitamin D level in COVID-19 patients is warranted.

Machine learning to predict in-hospital mortality risk among heterogenous STEMI patients with diabetes

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): TECHNOLOGY DEVELOPMENT FUND 1

Background

Diabetes has become a major public health concern in Asia. In Malaysia, the prevalence of diabetes has escalated in adults above the age of 18, affecting 3.9  million individuals. Patients with diabetes and coronary heart disease have worse outcomes, compared with patients without diabetes who have coronary heart disease. Conventional Risk scores such as TIMI and GRACE were derived from a Western Caucasian cohort with limited data from  Asian countries, despite Asia hosting 60% of the world’s population.

Purpose

It is important to recognize the significant features associated with in-hospital mortality risk that is population-specific in Asian diabetes patients with STEMI to achieve a reliable and effective clinical diagnosis and improved outcome. Electronic health records contain large amounts of information on patients’ medical history and are becoming invaluable research tools that could be applied to cardiovascular disease risk prediction through machine learning (ML) algorithms. With the current success of ML  over conventional methods in STEMI mortality prediction, we aim to develop ML algorithms for in-hospital risk mortality in Asian patients diagnosed with DM that can be adopted for clinical predictions

Methods

We used registry data from the Malaysian National Cardiovascular Disease Database of 5783 patients diagnosed with DM from 2006 to 2016. Fifty parameters including demographics, cardiovascular risk, medications and clinical variables were considered. Four machine learning (ML) algorithms were constructed using a 70% registry dataset; Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Booster (XGB) and Logistic Regression (LR). Feature selections were done based on ML algorithms feature importance combined with Sequential Backward Selection (SBS). The area under the curve (AUC)  was used as the performance evaluation metric. All algorithms were validated using a 30 % validation dataset and compared to the conventional TIMI risk score for STEMI.

Results

The best model SVM (AUC = 0.90) outperformed other ML algorithms (Figure 1) and TIMI risk score (AUC = 0.83). The best SVM model consists of 11 predictors which are Killip class, fasting blood glucose, age, systolic blood pressure, heart rate, ACE inhibitor, beta-blocker, total cholesterol, diastolic blood pressure, lower density lipoprotein, and diuretic (Figure 2). Common predictors of SVM and TIMI risk score are Killip class, age, systolic blood pressure, and heart rate. We have shown that the population-specific data mining approach for the prediction of diabetes patients’ mortality post-STEMI outperformed conventional TIMI risk score.

Conclusion

In the Asian multiethnic population, combination of ML approaches with features selection demonstrated promising outcomes in patients with DM that may be used for better patient prognostic than the conventional method. Abstract Figure 1: ML Best Model Performance  Abstract Figure 2: Selected Predictors for ML

Dietary Total Antioxidant Capacity and Risk of Polycystic Ovary Syndrome: A Case-Control Study

Among multiple factors that affect the etiology of polycystic ovary syndrome (PCOS), diet has<br />an important contribution. Chronic oxidative stress has also been implicated in the development of PCOS. The<br />present study is an attempt to evaluate dietary total antioxidant capacity (TAC) and its relationship with odds of<br />PCOS in Iran.<br />Materials and Methods: The study was carried out as a case-control study in hospital outpatient clinics, Tehran,<br />Iran. Totally, 310 female participants with a history of PCOS and 602 age-matched controls took part in this<br />study between June 2015 and December 2018. A reproducible and valid 168-item semi-quantitative food frequency<br />inventory was utilized to determine the entire antioxidants of the usual diet in order to calculate dietary<br />TAC. The relationship of dietary TAC with odds of PCOS were assessed adjusting for potential confounders<br />through an estimation of two multivariable conditional regression models. The first tertile was presented as a<br />reference category.<br />Results: In a fully adjusted model, the highest tertile of dietary TAC was associated with a reduced odds of<br />PCOS [odds ratio (OR): 0.81, 95% confidence interval (95% CI): 0.59, 0.96, P for trend: 0.038). In addition, PCOS odds decreased in the highest tertile of α-tocopherol intake (OR: 0.73, 95% CI: 0.56, 0.88, P for trend:<br />0.023). The adjusted ORs in the highest tertile of vitamin C, β-carotene and magnesium were 0.79 (95% CI: 0.83-0.97), 0.81 (95% CI: 0.67-0.98) and 0.91 (95% CI: 0.55-0.9 8) respectively, with a significant trend.<br />Conclusion: Our results provide evidence that there was a relationship between high TAC diets and lower odds of<br />PCOS.

ACS mortality prediction in Asian in-hospital patients with deep learning using machine learning feature selection

Background

Thrombolysis in Myocardial infarction (TIMI) is used in predicting the mortality rate of the acute coronary syndrome (ACS) patients. TIMI was developed based on the Western cohort with limited data on the Asian cohort. There are separate TIMI scores for STEMI and NSTEMI. Deep learning (DL) and machine learning (ML) algorithms such as support vector machine (SVM) in population-specific dataset resulted in a higher area under the curve (AUC) to TIMI. The limitation of DL is selected features by the algorithm is unknown compared to ML algorithms.

Purpose

To construct a single in-hospital mortality risk scoring system that combines SVM feature importance and the DL algorithm in ASIAN patients with ACS that is applicable for both STEMI and NSTEMI patients. To investigate DL performance constructed using predictors selected from SVM feature extraction and DL using complete features and compare with TIMI risk score for STEMI and NSTEMI patients.

Methods

We constructed four algorithms: i) DL and SVM algorithm with feature selected from SVM variable importance, ii) DL and SVM algorithm without feature selection. SVM feature importance with the backward elimination method is used to select and rank important variables. We used registry data from the National Cardiovascular Disease Database of 13190 patient's data. Fifty-four parameters including demographics, cardiovascular risk, medications and clinical variables were considered. AUC was used as the performance evaluation metric. All algorithms were validated using validation dataset and compared to the conventional TIMI for STEMI and NSTEMI.

Results

Validation results in Figure 1 are by STEMI and NTEMI patients. Both DL algorithms outperformed ML and TIMI score on validation data. Similar performance is observed for DL and SVM algorithms using all predictors (54 predictors) with DL and SVM algorithm using selected predictors (14 predictors). Predictors selected by the SVM feature selection are: age, heart rate, Killip class, fasting blood glucose, ST-elevation, CABG, cardiac catheterization, angina episode, HDLC, LDC, other lipid-lowering agents, statin, anti-arrhythmic agent, oralhypogly. CABG and pharmacotherapy drugs as selected predictors improve mortality prediction compared to TIMI score. In DL, 25.87% of STEMI patients and 19.71% of NSTEMI patients are estimated as high risk (risk probabilities of &gt;50%). TIMI underestimated the risk of mortality of high-risk patients (≥5 risk scores) with 13.08% from STEMI patients and 4.65% from NSTEMI patients (Figure 2).

Conclusions

In the ASIAN multi-ethnicity population, patients with ACS can be better classified using one single algorithm compared to the conventional method like TIMI which requires two different scores. Combining ML feature selection with DL allows the identification of distinct factors related to in-hospital mortality of ACS patients in a unique ASIAN population for better mortality prediction.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Technology Development Fund 1 Figure 1. Performance resultsFigure 2. Analysis on the validation set

Investigating performance of deep learning and machine learning risk stratification of Asian in-hospital patients after ST-elevation myocardial infarction

Background

Machine learning (ML) algorithm support vector machine (SVM) performed better than Thrombolysis in Myocardial Infarction (TIMI) score for ASIAN STEMI patients. However, Deep Learning (DL) effectiveness in the multiethnic ASIAN population has yet to be determined. DL has automatic learning of the feature from a given dataset without the need to conduct feature selection. However, the selected features by the algorithm is black box. Identifying features associated with mortality is essential to recognize characteristics of patients with high risk for better patient management.

Purpose

To develop a DL algorithm for in-hospital mortality in multiethnic STEMI patients using predictors identified from the SVM algorithm. To investigate DL performance constructed using predictors from SVM feature extraction and expert-recommended predictors.

Methods

We constructed four algorithms; a) DL and SVM algorithms with predictors identified from the SVM variable importance b) DL and SVM using predictors based on expert recommendation. We used registry data from the National Cardiovascular Disease Database of 11397 patient's. Fifty parameters including demographics, cardiovascular risk, medications and clinical variables were considered. The Area under the curve (AUC) is the performance evaluation metric. Algorithms were validated against the TIMI and tested using the same validation data. SVM variable importance with backward elimination was used to select and rank important variables.

Results

DL algorithms outperform SVM and TIMI on the validation dataset; i) DL with SVM selected predictors (15 predictors, AUC = 0.97), ii) DL with expert-recommended predictors (16 predictors, AUC = 0.96), iii) SVM with selected predictors (15 predictors, AUC = 0.92), iv) SVM with expert-recommended predictors (AUC = 0.89) and TIMI (AUC = 0.82). Common predictors across SVM feature selection, expert-recommendation and TIMI are: age, heart rate, Killip class, fasting blood glucose, systolic blood pressure, comorbid diseases and ST-elevation. SVM feature selection also identified diuretics, PCI and pharmacotherapy drugs as predictors that improve mortality prediction in STEMI patients. Our findings suggest that the TIMI score underestimates patients risk of mortality. DL algorithm using selected predictors classified 35% of nonsurvival patients as high risk (risk probabilities &gt;50%) compared to only 12.7% nonsurvival patients by TIMI (score &gt;5) (Figure below).

Conclusions

In the ASIAN population, patients with STEMI can be better classified using the DL algorithm compared to the ML and TIMI score. Combining ML feature selection with DL allows the identification of distinct factors in a unique ASIAN population for better mortality prediction than relying solely on an expert recommendation as it is a very subjective approach. Continuous validation on population-specific algorithms using DL and ML is needed before implementing in a real clinical setting.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Technology Development Fund 1 TIMI performance on validation setDL performance on validation set

Associations between systemic inflammation and intestinal permeability with Onodera's prognostic nutritional index in critically ill patients

Background

Malnutrition is a serious condition in critically ill patients. The aim of this study is to evaluate the relationships between the Onodera’s prognostic nutritional index (OPNI) and intestinal permeability and between OPNI and systemic inflammation in critically ill patients.

Methods

This was a cross-sectional study conducted in the general intensive care unit (ICU) of a university-affiliated hospital. A total of 162 patients admitted between May 2018 and December 2019, was included in the study. The OPNI was calculated at admission and categorized as ≤40 or >40. We assessed plasma endotoxin and zonulin concentrations as markers of intestinal permeability as well as serum interleukin-6 (IL-6) and high-sensitivity C-reactive protein (hs-CRP) as markers of systemic inflammation upon admission under stringent conditions. The relationships between these markers and OPNI were assessed after adjusting for potential confounders through estimation of a binary logistic regression model.

Results

Median (interquartile range) hs-CRP, IL-6 zonulin, and endotoxin were significantly greater in the low OPNI subgroup than in the high OPNI subgroup (all P<0.05). Multivariate analyses showed significant association between serum IL-6 (odds ratio [OR], 0.88; 95% confidence interval [CI], 0.64–0.96), serum hs-CRP (OR, 0.77; 95% CI, 0.53–0.92), plasma endotoxin (OR, 0.81; 95% CI, 0.72–0.93), and plasma zonulin (OR, 0.83; 95% CI, 0.75–0.98) levels with OPNI in the overall population.

Conclusions

Our results provide evidence that higher plasma endotoxin, zonulin, IL-6, and hs-CRP levels are associated with progressively lower OPNI in mixed ICU populations, particularly in surgical ICU patients.

The association between fertility diet score and polycystic ovary syndrome: A Case-Control study

We performed this case-control study with 303 polycystic ovarian syndrome (PCOS) patients and 588 age-matched controls to evaluate the relation between fertility diet score and odds of PCOS. In a fully adjusted model, the top tertile of fertility diet score compared to the bottom was associated with 22% [95%CI 0.71-0.93] lower odds of PCOS (P trend = 0.012). Ratio of monounsaturated to trans fat and vegetable protein was associated with a lower odd of PCOS. Animal protein intake and glycemic load were associated with a higher odd of PCOS. Based on our results, increasing the quality of the diet according to fertility diet score can reduce the odds of PCOS.

Risk stratification of Asian patients after ST-elevation myocardial infarction using machine learning methods

Background

Risk stratification in ST-elevation myocardial infarction (STEMI) that is population-specific is essential. Conventional risk stratification methods such Thrombolysis in Myocardial Infarction (TIMI) score is used to evaluate the risk associated with the acute coronary syndrome (ACS) which are derived from Western Caucasian cohort with a limited participant from the Asian region. In Malaysia, multi-ethnic developing country, patients presenting with STEMI are younger, have a much higher prevalence of diabetes, hypertension and renal failure, and present later to medical care than their western counterparts.

Purpose

We aim to investigate the predictors, predict mortality and develop a risk stratification tool for short and long term mortality in multi-ethnic STEMI patients using machine learning (ML) method.

Methods

We created three separate mortality prediction models using support vector machine (SVM) to identify predictors and predict mortality for in-hospital, 30-days and 1-year for STEMI patients. We used registry data from the National Cardiovascular Disease Database of 6299 patient's data for in-hospital, 3130 for 30-days and 2939 for 1-year for ML model development. Fifty parameters including demographics, cardiovascular risk, medications and clinical variables were utilised for training the models. The Area under the curve (AUC) was used as the primary performance evaluation metric. All models were validated against conventional method TIMI and tested using testing data. SVM variable importance method were used to select and rank important variables. We converted the final algorithm into an online tool with a database for continuous algorithm validation. We implemented the online calculator in selected hospitals for further testing using prospective patients data.

Results

The calculator is available at http://myheartstemi.uitm.edu.my. The calculator outperforms TIMI on testing data for in-hospital (15 predictors) (AUC=0.88 vs 0.81), 30 days (12 predictors) (AUC=0.90 vs 0.80) and 1-year (13 predictors) (AUC=0.84 vs 0.76). Common predictors for in-hospital, 30 days and 1-year mortality model identified in this study are; age, heart rate, Killip class, fasting blood glucose and diuretics. Invasive and less invasive treatments such as PCI pharmacotherapy drugs are also selected as important variables that improve mortality prediction. Our results also suggest that TIMI score underestimates patients risk of mortality. 90% of non-survival patients are classified as high risk (&gt;30%) by the calculator compared 10–30% non-survival patients by TIMI.

Conclusions

In the multi-ethnicity population, patients with STEMI are better classified using ML method compared to the TIMI score. ML allows identification of distinct factors in unique ASIAN population for better mortality prediction. Availability of population-specific calculator and continuous testing and validation allows better risk stratification.

Machine learning and TIMI performance

Funding Acknowledgement

Type of funding source: Public Institution(s). Main funding source(s): University of Malaya Grant

Trial of ready-to-use supplemental food and corn-soy blend in pregnant Malawian women with moderate malnutrition: a randomized controlled clinical trial

Background

Malnutrition during pregnancy in sub-Saharan Africa is associated with poor birth outcomes.

Objective

This study compared maternal and offspring anthropometry for moderately malnourished pregnant women receiving ready-to-use supplemental food (RUSF), a fortified corn-soy blend (CSB+) with a daily multiple micronutrient antenatal supplement [United Nations International Multiple Micronutrient Preparation (UNIMMAP)], or standard of care comprising CSB+ and iron and folic acid (IFA).

Design

A single-blind randomized controlled clinical trial was conducted in southern Malawi among 1828 pregnant women with moderate malnutrition, defined as a midupper arm circumference (MUAC) ≥20.6 and ≤23.0 cm. Women received 1 of 3 dietary treatment regimens that provided ∼900 kcal/d and 33-36 g protein/d. Maternal and infant anthropometry were followed until the child was 3 mo old.

Results

Newborns had a mean length-for-age z score of -1.3 ± 1.2 and 22% were stunted at birth. Mothers receiving RUSF had the highest weight gain during supplementation (3.4 ± 2.6, 3.0 ± 2.2, and 3.2 ± 2.4 kg for the RUSF, CSB+ with UNIMMAP, and CSB+ with IFA groups, respectively; P = 0.03). Newborn birth weights and lengths were similar across intervention groups, but the incidence of newborns with a birth weight <2.4 kg (weight-for-age z score <-2) was higher in the CSB+ with UNIMMAP group than the other groups (17%, 18%, and 24% for the CSB+ with IFA, RUSF, and CSB+ with UNIMMAP groups, respectively; P = 0.02). At birth, HIV-exposed newborns had a similar length and weight as newborns without HIV exposure, but their head circumference was smaller (34.0 ± 1.5 and 34.3 ± 1.6 cm, respectively; P = 0.02). At 3 mo of age, HIV-exposed infants had smaller weights, lengths, and head and arm circumferences than infants without HIV exposure.

Conclusions

RUSF improved maternal weight gain compared with CSB+ with UNIMMAP. The large amount of food given and the modest effect on linear growth in newborns suggests that stunting in utero is unlikely to be reduced by supplemental food alone. This trial was registered at clinicaltrials.gov as NCT02120599.

Comparative study of resin sealant and resin modified glass ionomer as pit and fissure sealant

<p>The purpose of the present study was to compare the marginal integrity of resin modified glass ionomer cement with that of resin sealant, <em>in vitro</em>. Forty artificial pit and fissure cavities were prepared in occlusal surface of extracted premolar teeth by using ¼ round carbide bur. Cavities were condensed with artificial organic debris followed by cleaning with prophylaxis pumice brush and paste and then separated into two treatment groups. In Group A, 15 fissure cavities were sealed by resin sealant and in Group B, 15 fissure cavities were sealed by resin modified glass ionomer sealant. These specimens were subjected to thermo-cycling followed by dye penetration test. The remaining 5 cavities from each group were analyzed for debris score by the SEM. The results of the microleakage test showed that the efficacy of preventing microleakage of samples sealed by resin modified glass ionomer sealant was higher than the samples sealed by resin sealant. However, no significant differences were found. It can be concluded that use of resin modified glass ionomer sealant is a good alternative for sealing pits and fissures.</p>

[Ten Cases of Cryptotia Corrected using Ono's Technique]

Cryptotia is a very rare condition of ear deformity found in Europe which is more common in Asian populations. The upper ear portion is hidden and fixed in a pocket of skin of the mastoid. Conservatively, this deformity can be treated by molding of the posterior sulcus starting early after birth. Various surgical procedures are described in the literature. We successfully operated on a total of 10 ears of 9 patients with the technique described by Ichiro Ono in 1995. Here, a triangular flap is raised above the ear to reconstruct the posterior sulcus together with a rhomboid-shaped flap in the anterior part of the ear in order to elongate the helix. Among all patients, regular contours and a stable and successful outcome was observed.

Advanced wear of an Oxinium™ femoral head implant following polyethylene liner dislocation

Oxinium™ (Smith & Nephew, Memphis, TN, US) has been used in hip arthroplasty since 2003. The surface coating is hard and provides low wear rates but if this surface coating is damaged, the soft metal core is at risk of accelerated wear. Previous reports have described accelerated wear following intra and postoperative hip dislocation. We report a case of advanced wear of an in situ Oxinium™ femoral head implant following a cracked acetabular liner. The liner had disengaged from the titanium shell, allowing the Oxinium™ head to articulate directly with the shell. The disengaged liner led to dislocation of the Oxinium™ head, with associated pronounced wear of the head and the acetabular cup. The patient had a successful revision procedure. We advise close follow-up of patients with Oxinium™ implants, especially if associated with dislocation and closed reduction.

Advanced wear of an Oxinium™ femoral head implant following polyethylene liner dislocation

Oxinium™ (Smith & Nephew, Memphis, TN, US) has been used in hip arthroplasty since 2003. The surface coating is hard and provides low wear rates but if this surface coating is damaged, the soft metal core is at risk of accelerated wear. Previous reports have described accelerated wear following intra and postoperative hip dislocation. We report a case of advanced wear of an in situ Oxinium™ femoral head implant following a cracked acetabular liner. The liner had disengaged from the titanium shell, allowing the Oxinium™ head to articulate directly with the shell. The disengaged liner led to dislocation of the Oxinium™ head, with associated pronounced wear of the head and the acetabular cup. The patient had a successful revision procedure. We advise close follow-up of patients with Oxinium™ implants, especially if associated with dislocation and closed reduction.

Decision making for knee replacement: variation in treatment choice for late stage medial compartment osteoarthritis

BACKGROUND

Patients with medial unicompartmental osteoarthritic disease of the knee requiring arthroplasty can be treated with either Total or Unicompartmental Knee Replacement (TKR or UKR). Currently, the decision to choose one operation over another is not well defined and may depend on the profile of the surgeon consulted. We tested the hypothesis that different surgeons will select different treatment for identical patients requiring knee replacement.

METHOD

Four different surgeons, representing four different levels of expertise, made a forced choice decision of whether they would perform TKR or UKR based on radiographs alone and subsequent additional clinical information including gender and age, in 140 patients. Individual surgeon repeatability was tested by repeat assessment 3 months later.

RESULTS

The knee surgeon from the UKR design centre would have performed a UKR in up to 88% of the patients. The remaining surgeons would have performed UKR in 29-48% of patients; a variation in decision making of up to 59%. Additional clinical information had little effect on decision making with surgeons maintaining their radiographic based choice in 80 to 87% of cases. The repeatability study showed high within surgeon consistency for treatment choice.

CONCLUSION

Surgeons, given identical information, do not concur on treatment for patients with the same pathology. The decision making process appears heavily influenced by radiographic findings but individual surgeons are consistent with their own treatment choice. The study shows that consensus treatment for medial osteoarthritis of the knee remains in question.

The sensitivity, specificity and predictive values of raised plasma metal ion levels in the diagnosis of adverse reaction to metal debris in symptomatic patients with a metal-on-metal arthroplasty of the hip

Plasma levels of cobalt and chromium ions and Metal Artefact Reduction Sequence (MARS)-MRI scans were performed on patients with 209 consecutive, unilateral, symptomatic metal-on-metal (MoM) hip arthroplasties. There was wide variation in plasma cobalt and chromium levels, and MARS-MRI scans were positive for adverse reaction to metal debris (ARMD) in 84 hips (40%). There was a significant difference in the median plasma cobalt and chromium levels between those with positive and negative MARS-MRI scans (p < 0.001). Compared with MARS-MRI as the potential reference standard for the diagnosis of ARMD, the sensitivity of metal ion analysis for cobalt or chromium with a cut-off of > 7 µg/l was 57%. The specificity was 65%, positive predictive value was 52% and the negative predictive value was 69% in symptomatic patients. A lowered threshold of > 3.5 µg/l for cobalt and chromium ion levels improved the sensitivity and negative predictive value to 86% and 74% but at the expense of specificity (27%) and positive predictive value (44%).

Metal ion analysis is not recommended as a sole indirect screening test in the surveillance of symptomatic patients with a MoM arthroplasty. The investigating clinicians should have a low threshold for obtaining cross-sectional imaging in these patients, even in the presence of low plasma metal ion levels.

Abstract IA24: Drugging the undruggable: Small-molecule inhibition of Ras oncoprotein

Ras is a nucleotide-dependent switch that converts from an inactive GDP-bound state to an active GTP-bound state when activated by guanine nucleotide exchange factors, such as SOS. Active RasGTP then binds to and activates downstream signaling effectors. Ras is the most frequently mutated oncogene and hyperactive mutant Ras constitutively signals to effectors to promote cell survival, proliferation and metastasis. Thus, Ras oncoprotein has been considered by the cancer community to be one of the most important oncology drug targets. Despite the enormous interest and extensive exploratory efforts in industry and academia, small molecules that bind to Ras in a well-defined manner and exert inhibitory effects have not been uncovered to date. We report here the identification and characterization of small-molecule inhibitors of the Ras oncoprotein.

To explore a new means of directly targeting Ras, we used a fragment-based lead discovery approach via an NMR-based screen. Hits from the fragment screen were characterized for their interactions with Ras by NMR and X-ray crystallography and for their effects on Ras activation and signaling in reconstituted biochemical assays in vitro and in cellular assays in vivo. From the fragment-based screen, we identified a group of small molecules that each bind to a common site adjacent to the switch I/II regions in the Ras protein. X-ray crystallography studies of three compound-Ras complexes indicate that the binding site can be expanded upon ligand binding. Nucleotide exchange factors, notably SOS, are required to convert inactive RasGDP to active RasGTP. We determined that the compound-binding site is located at the interface of Ras and SOS. A subset of our Ras-binding molecules indeed inhibited SOS-mediated nucleotide exchange. Further mechanistic studies revealed that through steric hindrance the compounds block the formation of the Ras-SOS complex, a key intermediate of the exchange reaction. At the cellular level, our compounds inhibit the formation of active RasGTP and prevent Ras signaling to downstream effectors. To define the potential clinic utility of these compounds, we performed biological characterization of Ras-driven tumors and identified a subset of Ras mutant tumors that depend on nucleotide exchange factors for the activation of Ras, suggesting a specific profile for the use of exchange inhibitors.

We conclude that the compounds act as competitive inhibitors of nucleotide exchange to prevent the activation of Ras. The discovery of a binding pocket on Ras with functional significance represents a breakthrough finding that will offer a new direction for therapeutic intervention of Ras. Our findings provide new opportunities to target the “undruggable” Ras oncoprotein.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the Second AACR International Conference on Frontiers in Basic Cancer Research; 2011 Sep 14-18; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2011;71(18 Suppl):Abstract nr IA24.

Computer assisted orthopaedic surgical system for insertion of distal locking screws in intra-medullary nails: a valid and reliable navigation system

The insertion of distal locking screws is a difficult task in intra-medullary (IM) nailing operations of long bones and contributes a significant proportion to the overall operating time. The current technique to insert these screws uses numerous fluoroscopic images and depends on the skills and expertise of the surgeon. The Computer Assisted Orthopaedic Surgical System (CAOSS) was developed to assist orthopaedic surgeons in these operations. The laboratory based test results for insertion of distal locking screws in IM nailing procedures are presented and discussed in terms of accuracy and as part of the validation process to introduce new CAOS procedures into clinical use. This study shows that CAOSS in IM nailing is robust and reliable. Positional accuracy was shown to be within 0.3 mm and angular accuracy within 0.2 degrees with femoral IM nail. CAOSS was also shown to be very reliable and accurate at different angles of distal screws in fluoroscopic image space.

Emergency repair of groin herniae: outcome and implications for elective surgery waiting times

Patients with groin herniae do not always seek medical advice and, when listed for surgery, often wait many months for elective repair. We audited our emergency admissions for complicated groin herniae to establish whether a change in policy for elective surgery could lower their incidence. We performed a retrospective review of all admissions for complicated groin herniae from 1 January 2000 to 31 December 2001. Besides outcome, we recorded patients' awareness of their diagnosis before admission and whether they had been listed for elective surgery. We identified 19 patients (16 men and three women) with an inguinal and 19 (four men and 15 women) with a femoral hernia. Sixteen (42%) knew of their hernia before admission (11 inguinal and five femoral), but only three had been awaiting surgical repair for 1, 7 and 26 weeks, respectively. The median (interquartile range) age was 70 (54-84) years in inguinal and 79 (64-88) years in femoral herniae. Surgery was performed in all but an 84-year-old man who died pre-operatively. Two patients with inguinal and 11 with femoral herniae required a laparotomy (p = 0.006). Bowel resection was necessary in one patient with an inguinal and 12 with femoral herniae (p = 0.001). Complications occurred in 12 cases (31%). Four patients, all with femoral herniae, died post-operatively, for an overall mortality of 13% (5/38). Morbidity and mortality for complicated groin hernia, particularly femoral, remain high. As most patients were elderly and unaware of their diagnosis, reducing waiting times for elective repair is unlikely to influence the incidence of complicated herniae.

IkappaBbeta, but not IkappaBalpha, functions as a classical cytoplasmic inhibitor of NF-kappaB dimers by masking both NF-kappaB nuclear localization sequences in resting cells

NF-kappaB dimers, inhibitor IkappaB proteins, and NF-kappaB.IkappaB complexes exhibit distinct patterns in partitioning between nuclear and cytoplasmic cellular compartments. IkappaB-dependent modulation of NF-kappaB subcellular localization represents one of the more poorly understood processes in the NF-kappaB signaling pathway. In this study, we have combined in vitro biochemical and cell-based methods to elucidate differences in NF-kappaB regulation exhibited by the inhibitors IkappaBbeta and IkappaBalpha. We show that although both IkappaBalpha and IkappaBbeta bind to NF-kappaB with similar global architecture and stability, significant differences exist that contribute to their unique functional roles. IkappaBbeta derives its high affinity toward NF-kappaB dimers by binding to both NF-kappaB subunit nuclear localization signals. In contrast, IkappaBalpha contacts only one NF-kappaB NLS and employs its carboxyl-terminal proline, glutamic acid, serine, and threonine-rich region for high affinity NF-kappaB binding. We show that the presence of one free NLS in the NF-kappaB.IkappaBalpha complex renders it a dynamic nucleocytoplasmic complex, whereas NF-kappaB.IkappaBbeta complexes are localized to the cytoplasm of resting cells.

Varying treatments of Class II malocclusions: two case reports

Two female patients, JH aged 13 years 5 months and CN, aged 13 years 10 months, presented at the Sydney University Orthodontic Clinic, Australia. Patient JH complained that her lower teeth were "too far back behind her top teeth". She was treated using the Speed Appliance. Patient CN complained that her teeth were "crooked". The main point of interest of her case is the mechanics used following the extraction of her four first molar teeth. Both patients were keen to improve their appearance.

[Predictive factors of normal coronary angiography]

The aim of this study is to compare two groups of patients Group A consisted of 120 patients (70 men and 50 women) hospitalised for anginal symptoms, with either clinical or electrical positive exercise test and/or ischemic events on a 24 H electrocardiography and having angiographically normal coronaries Group B consisted of 120 patients (102 men and 18 women) hospitalised for an acute coronary syndrome with pathological coronaries. The analysis of the 2 groups showed that in the group A the average age was lesser (56 years vs 60 years), women's percentage was higher (41% vs 15%) and cardiovascular risk factors were less frequent. Data from non invasive tests was significantly different in the 2 groups: the exercise test showed both clinical and electrical ischemic events in 35% of the patients in group A versus 75% in group B (p < 0.01) and the 24 h electocardiography showed ST depression in 9% of patients in group A versus 25% in group B (p < 0.01%). The coronary angiography is an invasive and an expensive procedure. The results of our study allow us to modulate its indications, especially in young women patients, with few or no cardivascular risk factors and with only electrical positive exercise test.

[Dumesnil's method: is it viable?]

BACKGROUND

Left ventricular (LV) ejection fraction (EF) is an indicator of left ventricular systolic function and is a potent predictor of cardiovascular mortality. LVEF is assessed by a variety of methods, however echocardiography is the most used in clinical practice. Simpson biplane multiple disc method (BMDM) is recommended by the American Society of Echocardiography; Dumesnil's method based on doppler echocardiography seems to be simpler and theoritically less influenced by distortion of LV geometry.

OBJECTIVE AND METHODS

To assess the accuracy and reproducibility of Dumesnil's method a group of 100 patients proposed for coronarography with left ventricular angiography, prospectively underwent LVEF measurements by both BMDM and Dumesnil's method.

RESULTS

Compared with LV angiography, the correlation coefficient for the Dumesnil's method was r = 0.85 and it was r = 0.9 for BMDM. Correlation in patients with LV regional asynergy were respectively r = 0.69 and r = 0.85. Intraobserver and interobserver variabilities were less then 7% for both echocardiographic methods.

CONCLUSION

Although Dumesnil's method is less accurate than BMDM, it is simpler, more rapid with a satisfactory reliability and reproducibility.

Physical properties of root cementum: Part I. A new method for 3-dimensional evaluation

Cementum is a nonuniform connective tissue that covers the roots of human teeth. Investigation of the physical properties of cementum may help in understanding or evaluating any possible connection to root resorption. A variety of engineering tests are available to investigate these properties. However, the thickness of the cementum layer varies, and this limits the applicability of these techniques in determining the physical properties of cementum. Hardness testing with Knoop and Vickers indentations overcame some of these limitations, but they prohibited the retrieval and retesting of the sample and therefore the testing was restricted to one area or section of the tooth. Another limiting factor with the existing techniques was the risk of artifacts related to the embedding material such as acrylic. A new method to investigate the physical properties of human premolar cementum was developed to obtain a 3-dimensional map of these properties with the Ultra Micro Indentation System (UMIS-2000; Commonwealth Scientific and Industrial Research Organization, Campbell, Australia). UMIS-2000 is a nano-indentation instrument for investigation of the properties of the near-surface region of materials. Premolars were harvested from orthodontic patients requiring extractions and then mounted on a newly designed surveyor that allowed sample retrieval and 3-dimensional rotation. This novel method enabled the quantitative testing of root surface cementum, on all 4 root surfaces, extending from the apex to the cementoenamel junction at 60 different sites.

Preparation and crystallization of dynamic NF-kappa B.Ikappa B complexes

The formation of single, well-diffracting crystals is a requirement for any molecular structure determination by x-ray crystallography. Crystallization of biological macromolecules can represent a significant obstacle when the subject exhibits internal flexibility or indiscriminate self-association. In such cases, the removal of inherently flexible regions and the addition of stabilizing ligands can improve the probability of crystal formation and ordered growth. We have applied these principles in order to form crystals of the Rel homology region of transcription factor NF-kappaB in complex with its inhibitors IkappaBalpha and IkappaBbeta. None of these molecules crystallizes in the absence of a binding partner. Recombinant overexpression of truncated IkappaBalpha required selection of the correct start site. NF-kappaB.IkappaBalpha complex crystals formed under relatively stringent conditions. NF-kappaB. IkappaBbeta complex crystals were formed by analogy to NF-kappaB. IkappaBalpha, although some modifications in purification and complex formation were necessary due to differences between the inhibitors.

Mechanism of kappa B DNA binding by Rel/NF-kappa B dimers

The DNA binding of three different NF-kappaB dimers, the p50 and p65 homodimers and the p50/p65 heterodimer, has been examined using a combination of gel mobility shift and fluorescence anisotropy assays. The NF-kappaB p50/p65 heterodimer is shown here to bind the kappaB DNA target site of the immunoglobulin kappa enhancer (Ig-kappaB) with an affinity of approximately 10 nm. The p50 and p65 homodimers bind to the same site with roughly 5- and 15-fold lower affinity, respectively. The nature of the binding isotherms indicates a cooperative mode of binding for all three dimers to the DNA targets. We have further characterized the role of pH, salt, and temperature on the formation of the p50/p65 heterodimer-Ig-kappaB complex. The heterodimer binds to the Ig-kappaB DNA target in a pH-dependent manner, with the highest affinity between pH 7.0 and 7.5. A strong salt-dependent interaction between Ig-kappaB and the p50/p65 heterodimer is observed, with optimum binding occurring at monovalent salt concentrations below 75 mm, with binding becoming virtually nonspecific at a salt concentration of 200 mm. Binding of the heterodimer to DNA was unchanged across a temperature range between 4 degrees C and 42 degrees C. The sensitivity to ionic environment and insensitivity to temperature indicate that NF-kappaB p50/p65 heterodimers form complexes with specific DNA in an entropically driven manner.