Deep learning models for forecasting dengue fever based on climate data in Vietnam.

BACKGROUND: Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to climate change in Vietnam. OBJECTIVE: This study aimed to develop an accurate DF prediction model in Vietnam using a wide range of meteorological factors as inputs to inform public health responses for outbreak prevention in the context of future climate change. METHODS: Convolutional neural network (CNN), Transformer, long short-term memory (LSTM), and attention-enhanced LSTM (LSTM-ATT) models were compared with traditional machine learning models on weather-based DF forecasting. Models were developed using lagged DF incidence and meteorological variables (measures of temperature, humidity, rainfall, evaporation, and sunshine hours) as inputs for 20 provinces throughout Vietnam. Data from 1997-2013 were used to train models, which were then evaluated using data from 2014-2016 by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). RESULTS AND DISCUSSION: LSTM-ATT displayed the highest performance, scoring average places of 1.60 for RMSE-based ranking and 1.95 for MAE-based ranking. Notably, it was able to forecast DF incidence better than LSTM in 13 or 14 out of 20 provinces for MAE or RMSE, respectively. Moreover, LSTM-ATT was able to accurately predict DF incidence and outbreak months up to 3 months ahead, though performance dropped slightly compared to short-term forecasts. To the best of our knowledge, this is the first time deep learning methods have been employed for the prediction of both long- and short-term DF incidence and outbreaks in Vietnam using unique, rich meteorological features. CONCLUSION: This study demonstrates the usefulness of deep learning models for meteorological factor-based DF forecasting. LSTM-ATT should be further explored for mitigation strategies against DF and other climate-sensitive diseases in the coming years.

Can short-term fasting protect against doxorubicin-induced cardiotoxicity?

Doxorubicin (Dox) is one of the most effective chemotherapeutic agents used in the treatment of several types of cancer. However the use is limited by cardiotoxicity. Despite extensive investigation into the mechanisms of toxicity and preventative strategies, Dox-induced cardiotoxicity still remains a major cause of morbidity and mortality in cancer survivors. Thus, continued research into preventative strategies is vital. Short-term fasting has proven to be cardioprotective against a variety of insults. Despite the potential, only a few studies have been conducted investigating its ability to prevent Dox-induced cardiotoxicity. However, all show proof-of-principle that short-term fasting is cardioprotective against Dox. Fasting affects a plethora of cellular processes making it difficult to discern the mechanism(s) translating fasting to cardioprotection, but may involve suppression of insulin and insulin-like growth factor-1 signaling with stimulated autophagy. It is likely that additional mechanisms also contribute. Importantly, the literature suggests that fasting may enhance the antitumor activity of Dox. Thus, fasting is a regimen that warrants further investigation as a potential strategy to prevent Dox-induced cardiotoxicity. Future research should aim to determine the optimal regimen of fasting, confirmation that this regimen does not interfere with the antitumor properties of Dox, as well as the underlying mechanisms exerting the cardioprotective effects.

Doxorubicin alters the mitochondrial dynamics machinery and mitophagy in the liver of treated animals.

Doxorubicin (Dox) is an effective chemotherapeutic agent, but known to cause cardiac and hepatic toxicity. Mechanisms of toxicity have not been clearly identified, but shown to involve oxidative stress and mitochondrial dysfunction. However, antioxidant supplementation has only shown modest protection from Dox-induced toxicity in clinical trials. Therefore, further research is required to discern alternative mechanisms that may also play an important role in Dox-induced toxicity. Thus, we aimed to investigate the role of mitochondrial fusion and fission in Dox-induced hepatic toxicity, which has not yet been investigated. Six-week-old male F344 rats were injected IP with 20 mg/kg of Dox or saline. Once administered, both groups of animals were fasted with no food or water until sacrifice 24 h later. Dox decreased content of primary regulators of mitochondrial fusion (OPA1, MFN1, and MFN2) with no effect on regulators of fission (DRP1 and FIS1), thus shifting the balance favoring mitochondrial fission. Moreover, it was determined that mitochondrial fission was likely not coupled to cell proliferation or cytochrome c release leading to the activation of mitochondrial-mediated apoptotic signaling. Rather, mitochondrial fission may be coupled to mitophagy and may be an adaptive response to protect against Dox-induced hepatic toxicity. This is the first study to report the role of altered mitochondrial dynamics and mitophagy machinery in Dox-induced hepatic injury.