RESULTS: Our models learned several syntactic, lexical, and n-gram linguistic biomarkers to distinguish the probable AD group from the healthy group. In contrast to the healthy group, we found that the probable AD patients had significantly less usage of syntactic components and significantly higher usage of lexical components in their language. Also, we observed a significant difference in the use of n-grams as the healthy group were able to identify and make sense of more objects in their n-grams than the probable AD group. As such, our best diagnostic model significantly distinguished the probable AD group from the healthy elderly group with a better Area Under the Receiving Operating Characteristics Curve (AUC) using the Support Vector Machines (SVM).
CONCLUSIONS: Experimental and statistical evaluations suggest that using ML algorithms for learning linguistic biomarkers from the verbal utterances of elderly individuals could help the clinical diagnosis of probable AD. We emphasise that the best ML model for predicting the disease group combines significant syntactic, lexical and top n-gram features. However, there is a need to train the diagnostic models on larger datasets, which could lead to a better AUC and clinical diagnosis of probable AD.
METHODS: Ten subjects (n = 10) who had upper and lower fixed appliances (MBT, 3 M Unitek, 0.022″ × 0.028″) were recruited for this study. Human gingival crevicular fluid (GCF) was obtained using periopaper strips at pre-treatment (T0), 1 month (T1), 3 months (T3), and 6 months (T6) of orthodontic treatment. Periapical radiographs of the upper permanent central incisors were taken at T0 and T6 to measure the amount of root resorption. Identification of changes in PA was performed using liquid chromatography-tandem mass spectrometry. Student's t-test was then performed to determine the significance of the differences in protein abundance before and after orthodontic treatment.
RESULTS: Our findings showed that all ten subjects had mild root resorption, with an average resorption length of 0.56 ± 0.30 mm. A total of 186 proteins were found to be commonly present at T0, T1, T3, and T6. There were significant changes in the abundance of 16 proteins (student's t-test, p ≤ 0.05). The increased PA of S100A9, immunoglobulin J chain, heat shock protein 1A, immunoglobulin heavy variable 4-34 and vitronectin at T1 suggested a response to stress that involved inflammation during the early phase of orthodontic treatment. On the other hand, the increased PA of thymidine phosphorylase at T3 suggested growth promotion and, angiogenic and chemotactic activities.
CONCLUSIONS: The identified proteins can be potential early markers for root resorption based on the increase in their respective PA and predicted roles during the early phase of orthodontic treatment. Non-invasive detection of root resorption using protein markers as early as possible is extremely important as it can aid orthodontists in successful orthodontic treatment.
Methods: The Iraqi Anti-Diabetic Medication Adherence Scale (IADMAS) consists of eight items. The face and content validity of the IADMAS were established via an expert panel. For convergent validity, the IADMAS was compared with the Medication Adherence Questionnaire (MAQ). For concurrent validity, the IADMAS was compared with glycosylated hemoglobin. A total of 84 patients with types 2 diabetes were recruited from a diabetes center in Baghdad, Iraq. Test-retest reliability was measured by readministering the IADMAS to the same patients 4 weeks later.
Results: Only 80 patients completed the study (response rate: 95%). Reliability analysis of the IADMAS showed a Cronbach's alpha value of 0.712, whereas that of the MAQ was 0.649. All items in the IADMAS showed no significant difference in the test-retest analysis, indicating that the IADMAS has stable reliability. There was no difference in the psychometric properties of the IADMAS and the MAQ. The sensitivity and specificity of the IADMAS were higher than that of the MAQ (100% vs 87.5% and 33.9% vs 29.7%, respectively).
Conclusion: The IADMAS developed in this study is a reliable and valid instrument for assessing antidiabetic medication adherence among Iraqi patients.
METHODS: Primary cultures of young, pre-senescent, and senescent fibroblast cells were incubated with γ-tocotrienol for 24 h. The expression levels of ELN, COL1A1, MMP1, CCND1, RB1, and IL6 genes were determined using the quantitative real-time polymerase chain reaction. Cell cycle profiles were determined using a FACSCalibur Flow Cytometer.
RESULTS: The cell cycle was arrested in the G(0)/G(1) phase, and the percentage of cells in S phase decreased with senescence. CCND1, RB1, MMP1, and IL6 were upregulated in senescent fibroblasts. A similar upregulation was not observed in young cells. Incubation with γ-tocotrienol decreased CCND1 and RB1 expression in senescent fibroblasts, decreased cell populations in the G(0)/G(1) phase and increased cell populations in the G(2)/M phase. γ-Tocotrienol treatment also upregulated ELN and COL1A1 and downregulated MMP1 and IL6 expression in young and senescent fibroblasts.
CONCLUSION: γ-Tocotrienol prevented cellular aging in human diploid fibroblasts, which was indicated by the modulation of the cell cycle profile and senescence-associated gene expression.