METHOD: The model was formulated by integrating the Caputo fractional derivative with the previous cancer treatment model. Thereafter, the linear-quadratic with the repopulation model was coupled into the model to account for the cells' population decay due to radiation. The treatment process was then simulated with numerical variables, numerical parameters, and radiation parameters. The numerical parameters which included the proliferation coefficients of the cells, competition coefficients of the cells, and the perturbation constant of the normal cells were obtained from previous literature. The radiation and numerical parameters were obtained from reported clinical data of six patients treated with radiotherapy. The patients had tumor volumes of 24.1cm3, 17.4cm3, 28.4cm3, 18.8cm3, 30.6cm3, and 12.6cm3 with fractionated doses of 2 Gy for the first two patients and 1.8 Gy for the other four. The initial tumor volumes were used to obtain initial populations of cells after which the treatment process was simulated in MATLAB. Subsequently, a global sensitivity analysis was done to corroborate the model with clinical data. Finally, 96 radiation protocols were simulated by using the biologically effective dose formula. These protocols were used to obtain a regression equation connecting the value of the Caputo fractional derivative with the fractionated dose.
RESULTS: The final tumor volumes, from the results of the simulations, were 3.58cm3, 8.61cm3, 5.68cm3, 4.36cm3, 5.75cm3, and 6.12cm3, while those of the normal cells were 23.87cm3, 17.29cm3, 28.17cm3, 18.68cm3, 30.33cm3, and 12.55cm3. The sensitivity analysis showed that the most sensitive model factors were the value of the Caputo fractional derivative and the proliferation coefficient of the cancer cells. Lastly, the obtained regression equation accounted for 99.14% of the prediction.
CONCLUSION: The model can simulate a cancer treatment process and predict the results of other radiation protocols.
METHODS: An initial bibliometric analysis shows that the reviewed papers focused on Electromyogram(EMG), Electroencephalogram(EEG), Electrocardiogram(ECG), and Electrooculogram(EOG). These four categories were used to structure the subsequent content review.
RESULTS: During the content review, we understood that deep learning performs better for big and varied datasets than classic analysis and machine classification methods. Deep learning algorithms try to develop the model by using all the available input.
CONCLUSIONS: This review paper depicts the application of various deep learning algorithms used till recently, but in future it will be used for more healthcare areas to improve the quality of diagnosis.
METHODS: Data for this study, consisting of 2202 older adults aged 60 years and above, were taken from a population-based survey entitled "Identifying Psychosocial and Identifying Economic Risk Factor of Cognitive Impairment among Elderly. Data analysis was conducted using the IBM SPSS Version 23.0.
RESULTS: The mean of MMSE was found to be 22.67 (SD = 4.93). The overall prevalence of selfreported diabetes was found to be 23.6% (CI95%: 21.8% - 25.4%). The result of independent t-test showed diabetic subjects had a higher mean score of MMSE (M = 23.05, SD =4 .55) than their counterparts without diabetes (M = 22.55, SD = 5.04) (t = -2.13 plinear regression analysis showed that diabetes was not significantly associated with cognitive function, after controlling the possible confounding factors.
CONCLUSIONS: The findings from the current study revealed that diabetes is not associated with cognitive decline. This study supports the findings that long-term treatment of diabetes may reduce the risk of cognitive decline. This finding may provide new opportunities for the prevention and management of cognitive decline.
OBJECTIVES: The current study investigated the gene expression profile of hepatocellular carcinoma, HepG2, cells after treatment with Limonene.
METHODS: The concentration that killed 50% of HepG2 cells was used to elucidate the genetic mechanisms of limonene anticancer activity. The apoptotic induction was detected by flow cytometry and confocal fluorescence microscope. Two of the pro-apoptotic events, caspase-3 activation and phosphatidylserine translocation were manifested by confocal fluorescence microscopy. Highthroughput real-time PCR was used to profile 1023 cancer-related genes in 16 different gene families related to the cancer development.
RESULTS: In comparison to untreated cells, limonene increased the percentage of apoptotic cells up to 89.61%, by flow cytometry, and 48.2% by fluorescence microscopy. There was a significant limonene- driven differential gene expression of HepG2 cells in 15 different gene families. Limonene was shown to significantly (>2log) up-regulate and down-regulate 14 and 59 genes, respectively. The affected gene families, from the most to the least affected, were apoptosis induction, signal transduction, cancer genes augmentation, alteration in kinases expression, inflammation, DNA damage repair, and cell cycle proteins.
CONCLUSION: The current study reveals that limonene could be a promising, cheap, and effective anticancer compound. The broad spectrum of limonene anticancer activity is interesting for anticancer drug development. Further research is needed to confirm the current findings and to examine the anticancer potential of limonene along with underlying mechanisms on different cell lines.
METHOD: A multicenter cross-sectional observational study was conducted in 388 diabetes patients attending daily diabetes clinics and teaching hospitals in Pakistan's twin city between August 2019 and February 2020. The chi-square test and linear regression were used to detect RLS-related factors in type 2 diabetes mellitus.
RESULTS: The prevalence of RLS found was; 3.1% patients with diabetes were suffering from very severe RLS, 23.5% from severe RLS, 34% from moderate RLS, 21.1% from mild RLS and 18.3% from non-RLS. Gender, age, education, blood glucose fasting (BSF), blood glucose random (BSR) and HBA1c were found to be significant predictors of RLS in patients with diabetes.
CONCLUSION: Policy makers can develop local interventions to curb the growing RLS prevalence by keeping in control the risk factors of RLS in people living with type 2 diabetes.
Methods: People diagnosed with type 2 diabetes (n=218) were selected from three health care centers, located in different cities of Pakistan. Disease knowledge and self-care practices were assessed by Urdu versions of Diabetes Knowledge Questionnaire (DKQ) and Diabetes Self-Management Questionnaire (DSMQ), using a cross-sectional design. Chi-square and correlation analysis were applied to explore the relationship of disease knowledge with glycemic control and self-care practices. Linear regression was used to explore the predictors for disease knowledge.
Results: Majority of the sample was >45-60 years old (48.8%), suffering from type 2 diabetes mellitus for <5 years (49.5%) and had poor glycemic control (HbA1C≥7%; n=181 participants). Disease knowledge was significantly associated (p<0.05) with patient's gender, level of education, family history of diabetes, nature of euglycemic therapy, and glycemic control. Correlation matrix showed strongly inverse correlations of DKQ with glycated hemoglobin levels (r=-0.62; p<0.001) and strongly positive with DSMQ sum scale (r=0.63; p<0.001). PWD having university-level education (β=0.22; 95% Confidence Interval (CI) 0.189, 0.872; p<0.01), doing job (β=0.22; 95% CI 0.009, 0.908]; p=0.046), and use of oral hypoglycemic agents in combination with insulin (β=-0.16; 95% CI [-1.224, -0.071]; p=0.028) were the significant predictors for disease knowledge.
Conclusion: Disease knowledge significantly correlated with glycated hemoglobin levels and self-care activities of PWD. These findings will help in designing patient-tailored diabetes educational interventions for yielding a higher probability of achieving target glycemic control.
DESIGN: Forty-four full-term healthy neonates (17 males and 27 females) participated in a longitudinal study. The neonates were assessed at 1-month intervals from 0 to 6 months of age using high-frequency tympanometry, acoustic stapedial reflex, distortion product otoacoustic emissions, and pressurized WBA. The values of WBA at tympanometric peak pressure (TPP) and 0 daPa across the frequencies from 0.25 to 8 kHz were analyzed as a function of age.
RESULTS: A linear mixed model analysis, applied to the data, revealed significantly different WBA patterns among the age groups. In general, WBA measured at TPP and 0 daPa decreased at low frequencies (<0.4 kHz) and increased at high frequencies (2 to 5and 8 kHz) with age. Specifically, WBA measured at TPP and 0 daPa in 3- to 6-month-olds was significantly different from that of 0- to 2-month-olds at low (0.25 to 0.31 kHz) and high (2 to 5 and 8 kHz) frequencies. However, there were no significant differences between WBA measured at TPP and 0 daPa for infants from 3 to 6 months of age.
CONCLUSIONS: The present study provided clear evidence of maturation of the outer and middle ear system in healthy infants from birth to 6 months. Therefore, age-specific normative data of pressurized WBA are warranted.
Objectives: This study aimed to determine post-treatment oral cancer patients' concerns and its relationship with patients' clinical characteristics, health-related quality of life (HRQoL), psychological distress and patient satisfaction with the follow-up consultation.
Methods: A total of 85 oral cancer patients were recruited from a three-armed pragmatic RCT study on the patient concerns inventory for head and neck cancer (PCI-H&N), which was conducted at six hospital-based oral maxillofacial specialist clinics throughout Malaysia. Malaysians aged 18 years and above and on follow-ups from 1 month to 5 years or more were eligible. Patients completed the PCI-H&N, functional assessment of cancer therapy -H&N v4.0 and Distress Thermometer at pre-consultation and satisfaction questionnaire at post-consultation. The data were analysed descriptively; multiple linear regression and multivariate logistic regression analyses were used to determine possible predictors of patients' HRQoL and psychological distress.
Results: 'Recurrence or fear of cancer coming back' (31.8%) was most frequently selected. 43.5% of patients selected ≥4 concerns. A significantly high number of concerns were associated with patients of '1-month to 1-year post-treatment' (n = 84%; p = 0.001). A significant association existed between 'time after treatment completed' and patients' concerns of 'chewing/eating', 'mouth opening', 'swelling', 'weight', 'ability to perform', 'cancer treatment' and 'supplement/diet-related'. 'Chewing/eating' was predicted for low HRQoL (p < 0.0001) followed by 'appearance' and 'ability to perform recreation activities' (personal functions domain). Patients with high psychological distress levels were 14 times more likely to select 'ability to perform recreation activities' and seven times more likely to select 'feeling depressed'. No significant association was identified between patients' concerns and patients' satisfaction with the consultation.
Conclusion: Routine follow-up consultations should incorporate the PCI-H&N prompt list to enhance patient-centred care approach as the type and number of patients' concerns are shown to reflect their HRQoL and psychological distress.TRIAL REGISTRATION: NMRR-18-3624-45010 (IIR).
METHODS: Diabetes data were derived from the Malaysian National Health and Morbidity Surveys conducted in 2006, 2011 and 2015. The air pollution data (NOx, NO2, SO2, O3 and PM10) were obtained from the Department of Environment Malaysia. Using multiple logistic and linear regression models, the association between long-term exposure to these pollutants and prevalence of diabetes among Malaysian adults was evaluated.
RESULTS: The PM10 concentration decreased from 2006 to 2014, followed by an increase in 2015. Levels of NOx decreased while O3 increased annually. The air pollutant levels based on individual modelled air pollution exposure as measured by the nearest monitoring station were higher than the annual averages of the five pollutants present in the ambient air. The prevalence of overall diabetes increased from 11.4% in 2006 to 21.2% in 2015. The prevalence of known diabetes, underdiagnosed diabetes, overweight and obesity also increased over these years. There were significant positive effect estimates of known diabetes at 1.125 (95% CI, 1.042, 1.213) for PM10, 1.553 (95% CI, 1.328, 1.816) for O3, 1.271 (95% CI, 1.088, 1.486) for SO2, 1.124 (95% CI, 1.048, 1.207) for NO2, and 1.087 (95% CI, 1.024, 1.153) for NOx for NHMS 2006. The adjusted annual average levels of PM10 [1.187 (95% CI, 1.088, 1.294)], O3 [1.701 (95% CI, 1.387, 2.086)], NO2 [1.120 (95% CI, 1.026, 1.222)] and NOx [1.110 (95% CI, 1.028, 1.199)] increased significantly from NHMS 2006 to NHMS 2011 for overall diabetes. This was followed by a significant decreasing trend from NHMS 2011 to 2015 [0.911 for NO2, and 0.910 for NOx].
CONCLUSION: The findings of this study suggest that long-term exposure to O3 is an important associated factor of underdiagnosed DM risk in Malaysia. PM10, NO2 and NOx may have mixed effect estimates towards the risk of DM, and their roles should be further investigated with other interaction models. Policy and intervention measures should be taken to reduce air pollution in Malaysia.