HYPERDONTIA IN CHILDREN AT THE PAEDIATRIC DENTAL CLINIC: HIPERDONSIA PADA PASIEN KLINIK GIGI ANAK

This was a retrospective study that looked at the prevalence, characteristics, gender predilection and common problems associated with supernumerary teeth found in children at the Paediatric Dental Clinic, National University of Malaysia (UKM). Four hundred ninety clinical records of children with relevant radiographs, mean age of 8 years (range 6-12 yearsold) were analyzed. The result showed that the prevalence of supernumerary teeth was found to be 3.1%. One hundred percent of the supernumerary teeth were found among patients of Mongoloid descendents (Malay and Chinese). Males were more frequently affected than females with a ratio of 4.1:1. Of the 22 supernumerary teeth found, 75.0% of the teeth were unerupted, 91.0% were located at the anterior maxillary region, 77.3% were conical in shape and 72.7% were of mesiodens type. Uneruption of permanent tooth and crowding were the common problems associated with the supernumerary teeth. All patients with supernumerary teeth were in the mixed dentition stage. In conclusion, majority of supernumerary teeth found were unerupted, located at the anterior maxillary region, mesiodens in conical shape and commonly seen in Mongoloid males

Doctor, how much weight will I lose? - a new individualized predictive model for weight loss

Bariatric surgery is an effective treatment for weight loss, but the patient’s ability to reach a sustained weight loss depends upon several technical and individual factors. Creating an easy model that adapts bariatric surgery’s weight loss goals for each patient is very important for pre-surgery and follow-up evaluations.info:eu-repo/semantics/publishedVersio

Frequency and predictors of the lupus low disease activity state in a multi-national and multi-ethnic cohort

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Student and tutor perceptions on attributes of effective problems in problem-based learning

This study aimed to identify the attributes that students and tutors associated with effective PBL problems, and assess the extent to which these attributes related to the actual effectiveness of problems. To this end, students and tutors in focus groups were asked to discuss about possible attributes of effective problems. The same participants were then asked to individually and independently judge eight sample problems they had worked with. Text analysis of the focus group discussion transcripts identified eleven problem attributes. Participants' judgments of the sample problems were then frequency-scored on the eleven problem attributes. Relating the participants' judgments with the entire student cohort's grades yielded high and significant correlations, suggesting that the eleven problem attributes reflect aspects of problem effectiveness

Oxaliplatin induces drug resistance more rapidly than cisplatin in H69 small cell lung cancer cells

Cisplatin produces good responses in solid tumours including small cell lung cancer (SCLC) but this is limited by the development of resistance. Oxaliplatin is reported to show activity against some cisplatin-resistant cancers but there is little known about oxaliplatin in SCLC and there are no reports of oxaliplatin resistant SCLC cell lines. Studies of drug resistance mainly focus on the cellular resistance mechanisms rather than how the cells develop resistance. This study examines the development of cisplatin and oxaliplatin resistance in H69 human SCLC cells in response to repeated treatment with clinically relevant doses of cisplatin or oxaliplatin for either 4 days or 2h. Treatments with 200ng/ml cisplatin or 400ng/ml oxaliplatin for 4 days produced sublines (H69CIS200 and H69OX400 respectively) that showed low level (approximately 2-fold) resistance after 8 treatments. Treatments with 1000ng/ml cisplatin or 2000ng/ml oxaliplatin for 2h also produced sublines, however these were not stably resistant suggesting shorter treatment pulses of drug may be more effective. Cells survived the first five treatments without any increase in resistance, by arresting their growth for a period and then regrowing. The period of growth arrest was reduced after the sixth treatment and the H69CIS200 and H69OX400 sublines showed a reduced growth arrest in response to cisplatin and oxaliplatin treatment suggesting that "regrowth resistance" initially protected against drug treatment and this was further upregulated and became part of the resistance phenotype of these sublines. Oxaliplatin dose escalation produced more surviving sublines than cisplatin dose escalation but neither set of sublines were associated with increased resistance as determined by 5-day cytotoxicity assays, also suggesting the involvement of regrowth resistance. The resistant sublines showed no change in platinum accumulation or glutathione levels even though the H69OX400 subline was more sensitive to buthionine sulfoximine treatment. The H69CIS200 cells were cross-resistant to oxaliplatin demonstrating that oxaliplatin does not have activity against low level cisplatin resistance. Relative to the H69 cells, the H69CIS200 and H69OX400 sublines were more sensitive to paclitaxel and taxotere suggests the taxanes may be useful in the treatment of platinum resistant SCLC. These novel cellular models of cisplatin and oxaliplatin resistant SCLC will be useful in developing strategies to treat platinum-resistant SCLC

Evaluation of the Genetic Association Between Adult Obesity and Neuropsychiatric Disease

Extreme obesity (EO, BMI>50) is frequently associated with neuropsychiatric disease (NPD). As both EO and NPD are heritable central nervous system disorders, we assessed the prevalence of protein truncating (PTV) and copy number variants (CNV) in genes/regions previously implicated in NPD, in adults with EO (n=149) referred for weight loss/bariatric surgery. We also assessed the prevalence of CNVs in patients referred to University College London Hospital (UCLH) with EO (n=218) and obesity (O, BMI 35-50, n=374) and a Swedish cohort of participants from the community with predominantly O (n=161). The prevalence of variants was compared to controls in ExAC/gnomAd database. In the discovery cohort (high NPD prevalence: 77%), the cumulative PTV/CNV allele frequency (AF) was 7.7 % vs 2.6% in controls (Odds Ratio (OR) 3.1, (95% CI 2-4.1, p<0.0001). In the UCLH EO cohort (intermediate NPD prevalence: 47%), CNV AF (1.8% vs 0.9% in controls, OR 1.95, 95% CI 0.96-3.93, p=0.06) was lower than the discovery cohort. CNV AF was not increased in the UCLH O cohort (0.8%). No CNVs were identified in the Swedish cohort with no NPD. These findings suggest PTV/CNVs, in genes/regions previously associated with NPD, may contribute to NPD in patients with EO

The relationships between problem characteristics, achievement-related behaviors, and academic achievement in problem-based learning

This study investigated the influence of five problem characteristics on students' achievement-related classroom behaviors and academic achievement. Data from 5,949 polytechnic students in PBL curricula across 170 courses were analyzed by means of path analysis. The five problem characteristics were: (1) problem clarity, (2) problem familiarity, (3) the extent to which the problem stimulated group discussion, (4) self-study, and (5) identification of learning goals. The results showed that problem clarity led to more group discussion, identification of learning goals, and self-study than problem familiarity. On the other hand, problem familiarity had a stronger and direct impact on academic achievement

Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinson’s Disease Affected by COVID‐19: A Narrative Review

Background and Motivation: Parkinson’s disease (PD) is one of the most serious, non-curable, and expensive to treat. Recently, machine learning (ML) has shown to be able to predict cardiovascular/stroke risk in PD patients. The presence of COVID‐19 causes the ML systems to be-come severely non‐linear and poses challenges in cardiovascular/stroke risk stratification. Further, due to comorbidity, sample size constraints, and poor scientific and clinical validation techniques, there have been no well‐explained ML paradigms. Deep neural networks are powerful learning machines that generalize non‐linear conditions. This study presents a novel investigation of deep learning (DL) solutions for CVD/stroke risk prediction in PD patients affected by the COVID‐19 framework. Method: The PRISMA search strategy was used for the selection of 292 studies closely associated with the effect of PD on CVD risk in the COVID‐19 framework. We study the hypothesis that PD in the presence of COVID‐19 can cause more harm to the heart and brain than in non‐ COVID‐19 conditions. COVID‐19 lung damage severity can be used as a covariate during DL training model designs. We, therefore, propose a DL model for the estimation of, (i) COVID‐19 lesions in computed tomography (CT) scans and (ii) combining the covariates of PD, COVID‐19 lesions, office and laboratory arterial atherosclerotic image‐based biomarkers, and medicine usage for the PD patients for the design of DL point‐based models for CVD/stroke risk stratification. Results: We validated the feasibility of CVD/stroke risk stratification in PD patients in the presence of a COVID‐ 19 environment and this was also verified. DL architectures like long short‐term memory (LSTM), and recurrent neural network (RNN) were studied for CVD/stroke risk stratification showing powerful designs. Lastly, we examined the artificial intelligence bias and provided recommendations for early detection of CVD/stroke in PD patients in the presence of COVID‐19. Conclusion: The DL is a very powerful tool for predicting CVD/stroke risk in PD patients affected by COVID‐19