This study showed moderate associations between depression and poor treatment adherence. Targeting behaviour and social environments, however, may ultimately provide more cost-effective health gains than targeting depressive symptoms.

BackgroundMany popular dengue forecasting techniques have been used by several researchers to extrapolate dengue incidence rates, including the K-H model, support vector machines (SVM), and artificial neural networks (ANN). The time series analysis methodology, particularly ARIMA and SARIMA, has been increasingly applied to the field of epidemiological research for dengue fever, dengue hemorrhagic fever, and other infectious diseases. The main drawback of these methods is that they do not consider other variables that are associated with the dependent variable. Additionally, new factors correlated to the disease are needed to enhance the prediction accuracy of the model when it is applied to areas of similar climates, where weather factors such as temperature, total rainfall, and humidity are not substantially different. Such drawbacks may consequently lower the predictive power for the outbreak.ResultsThe predictive power of the forecasting model-assessed by Akaike’s information criterion (AIC), Bayesian information criterion (BIC), and the mean absolute percentage error (MAPE)-is improved by including the new parameters for dengue outbreak prediction. This study’s selected model outperforms all three other competing models with the lowest AIC, the lowest BIC, and a small MAPE value. The exclusive use of climate factors from similar locations decreases a model’s prediction power. The multivariate Poisson regression, however, effectively forecasts even when climate variables are slightly different. Female mosquitoes and seasons were strongly correlated with dengue cases. Therefore, the dengue incidence trends provided by this model will assist the optimization of dengue prevention.ConclusionsThe present work demonstrates the important roles of female mosquito infection rates from the previous season and climate factors (represented as seasons) in dengue outbreaks. Incorporating these two factors in the model significantly improves the predictive power of dengue hemorrhagic fever forecasting models, as confirmed by AIC, BIC, and MAPE.

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About a half of patients receiving warfarin therapy was prescribed concomitant drug(s) that has a high potential of interactions with warfarin. These patients should be closely monitored and counselled to watch for signs and symptoms of bleeding and thrombosis to avoid adverse events associated with drug interactions.

Several tropical flowers have distinctive fragrances which are very appealing to use in perfumery, cosmetics and spa. However, to obtain a 'natural fragrance' from the flower is a challenge as the scent could change during the extraction process. The aim of the study is to find the suitable procedure for extraction of volatile oils from some Thai fragrant flowers. Three different methods: hydrodistillation, solvent extraction and enfleurage methods have been applied for the extraction of volatile oil from Jasminum sambac L. Aiton; Oleaceae (jasmine). The quantities and quality of jasmine volatile oils obtained from the different tested methods were compared. The solvent extraction method using 95% ethanol provided the greatest level of oil yield. However, sensory evaluation using preference test showed that the scents of the volatile oils from solvent extraction using diethyl ether and from enfleurage method were the closest to the fresh flowers compared with the volatile oils obtained from other methods. Their chemical constituents were analysed using gas chromatography coupled with mass spectrometer. Both volatile oils were then evaluated using a triangle discrimination test. From the triangle test, we found that 14 panellists from the total of 36 could not distinguish between the scents of jasmine oil from enfleurage and fresh jasmine flowers whereas only one panellist could not distinguish between the scent of jasmine oil from the solvent extraction and fresh jasmine flowers. These results suggest that the scent of the volatile oil obtained from the enfleurage method was the closest to fresh flowers compared with that obtained from other methods. This method was then successfully applied for extraction of volatile oils from three other Thai fragrant flowers, Michelia alba DC.; Magnoliaceae, Millingtonia hortensis L.; Bignoniaceae and Hedychium coronarium J. Konig; Zingiberaceae.

Cellulite remains an obstinate clinical and cosmetic problem. In this study, we adapted the Thai traditional noninvasive treatment formulated with 5 additional herbals to improve blood flow, edema, and lipolysis, thereby augmenting cellulite treatment. This was a double-blind, randomized placebo-controlled paired trial. Twenty-one women (20-55 years) having cellulite (grade ≥2) were treated with steamed placebo or herbal compresses randomly assigned to one or other thigh twice weekly for 8 weeks with 2 weeks washout. Cellulite reduction was assessed from standardized photographs by 3 blinded evaluators at baseline and every 2 weeks; also assessed were thigh circumferences and cutaneous skin-fold thicknesses, trial diaries, and participant feedback. After 8 weeks, herbal compress treatment reduced Nürnberger-Müller cellulite scores from 12.6 ± 2.0 to 9.9 ± 2.4 compared with 12.5 ± 2.1 to 12.1 ± 2.0 (means ± SEM) for contralateral placebo-treated thighs (P < .0001; effect size [ES] = 1.16, confidence interval [CI] = 0.48-1.83). Thigh circumferences diminished by 2.2 ± 0.9 cm (herbal) and 1.4 ± 0.7 cm (placebo) (ES = 0.96, CI = 0.30-1.61) and correspondingly skin-folds by 5.6 ± 2.2 and 2.4 ± 1.3 mm (ES = 1.72, CI = 0.99-2.45). No adverse actions were reported, and there were no dropouts, no missing data, and 100% adherence. Herbal compresses were efficacious against cellulite and thigh sizes. The herbal formula might be adapted to other delivery options, and rationally added herbals may increase effectiveness of traditional therapies and more sustainable actions.

The tympanic thermometer designed for use in humans can be used in adult squirrel monkeys as an alternative to rectal thermometry for assessing core body temperature.

Thailand is one of the countries where foot and mouth disease outbreaks have resulted in considerable economic losses. Forecasting is an important warning technique that can allow authorities to establish an FMD surveillance and control program. This study aimed to model and forecast the monthly number of FMD outbreak episodes (n-FMD episodes) in Thailand using the time-series methods, including seasonal autoregressive integrated moving average (SARIMA), error trend seasonality (ETS), neural network autoregression (NNAR), and Trigonometric Exponential smoothing state–space model with Box–Cox transformation, ARMA errors, Trend and Seasonal components (TBATS), and hybrid methods. These methods were applied to monthly n-FMD episodes (n = 1209) from January 2010 to December 2020. Results showed that the n-FMD episodes had a stable trend from 2010 to 2020, but they appeared to increase from 2014 to 2020. The outbreak episodes followed a seasonal pattern, with a predominant peak occurring from September to November annually. The single-technique methods yielded the best-fitting time-series models, including SARIMA(1,0,1)(0,1,1)12, NNAR(3,1,2)12,ETS(A,N,A), and TBATS(1,{0,0},0.8,{<12,5>}. Moreover, SARIMA-NNAR and NNAR-TBATS were the hybrid models that performed the best on the validation datasets. The models that incorporate seasonality and a non-linear trend performed better than others. The forecasts highlighted the rising trend of n-FMD episodes in Thailand, which shares borders with several FMD endemic countries in which cross-border trading of cattle is found common. Thus, control strategies and effective measures to prevent FMD outbreaks should be strengthened not only in Thailand but also in neighboring countries.