A contemporary review on drought modeling using machine learning approaches

Drought is the least understood natural disaster due to the complex relationship of multiple contributory factors. Its beginning and end are hard to gauge, and they can last for months or even for years. India has faced many droughts in the last few decades. Predicting future droughts is vital for framing drought management plans to sustain natural resources. The data-driven modelling for forecasting the metrological time series prediction is becoming more powerful and flexible with computational intelligence techniques. Machine learning (ML) techniques have demonstrated success in the drought prediction process and are becoming popular to predict the weather, especially the minimum temperature using backpropagation algorithms. The favourite ML techniques for weather forecasting include singular vector machines (SVM), support vector regression, random forest, decision tree, logistic regression, Naive Bayes, linear regression, gradient boosting tree, k-nearest neighbours (KNN), the adaptive neuro-fuzzy inference system, the feed-forward neural networks, Markovian chain, Bayesian network, hidden Markov models, and autoregressive moving averages, evolutionary algorithms, deep learning and many more. This paper presents a recent review of the literature using ML in drought prediction, the drought indices, dataset, and performance metrics

Prisoner's Dilemma in Cancer Metabolism

As tumors outgrow their blood supply and become oxygen deprived, they switch to less energetically efficient but oxygen-independent anaerobic glucose metabolism. However, cancer cells maintain glycolytic phenotype even in the areas of ample oxygen supply (Warburg effect). It has been hypothesized that the competitive advantage that glycolytic cells get over aerobic cells is achieved through secretion of lactic acid, which is a by-product of glycolysis. It creates acidic microenvironment around the tumor that can be toxic to normal somatic cells. This interaction can be seen as a prisoner's dilemma: from the point of view of metabolic payoffs, it is better for cells to cooperate and become better competitors but neither cell has an incentive to unilaterally change its metabolic strategy. In this paper a novel mathematical technique, which allows reducing an otherwise infinitely dimensional system to low dimensionality, is used to demonstrate that changing the environment can take the cells out of this equilibrium and that it is cooperation that can in fact lead to the cell population committing evolutionary suicide

Migraine with aura is not linked to the FHM gene CACNA1A or the chromosomal region, 19p13.

Two microsatellite markers, tightly linked to CACNA1A, were genotyped in migraine with aura (MA) families to determine if this gene, which underlies the 19p13 linked forms of familial hemiplegic migraine, is also linked to MA. Two-point parametric lod and nonparametric linkage scores did not support linkage. Transmission disequilibrium testing provided no evidence for linkage of MA to CACNA1A. In a large dataset of 64 Canadian MA families, the authors did not find evidence to support an MA susceptibility gene in the region of 19p13

p53-Based strategy to reduce hematological toxicity of chemotherapy: A proof of principle study

p53 activation is a primary mechanism underlying pathological responses to DNA damaging agents such as chemotherapy and radiotherapy. Our recent animal studies showed that low dose arsenic (LDA)-induced transient p53 inhibition selectively protected normal tissues from chemotherapy-induced toxicity. Study objectives were to: 1) define the lowest safe dose of arsenic trioxide that transiently blocks p53 activation in patients and 2) assess the potential of LDA to decrease hematological toxicity from chemotherapy. Patients scheduled to receive minimum 4 cycles of myelosuppressive chemotherapy were eligible. For objective 1, dose escalation of LDA started at 0.005 mg/kg/day for 3 days. This dose satisfied objective 1 and was administered before chemotherapy cycles 2, 4, and 6 for objective 2. p53 level in peripheral lymphocytes was measured on day 1 of each cycle by ELISA assay. Chemotherapy cycles 1, 3, and 5 served as the baseline for the subsequent cycles of 2, 4, and 6 respectively. If p53 level for the subsequent cycle was lower (or higher) than the baseline cycle, p53 was defined as "suppressed" (or "activated") for the pair of cycles. Repeated measures linear models of CBC in terms of day, cycle, p53 activity and interaction terms were used. Twenty-six patients treated with 3 week cycle regimens form the base of analyses. The mean white blood cell, hemoglobin and absolute neutrophil counts were significantly higher in the "suppressed" relative to the "activated" group. These data support the proof of principle that suppression of p53 could lead to protection of bone marrow in patients receiving chemotherapy.This trial is registered in ClinicalTrials.gov. Identifier: NCT01428128

p53-Based strategy to reduce hematological toxicity of chemotherapy: A proof of principle study

p53 activation is a primary mechanism underlying pathological responses to DNA damaging agents such as chemotherapy and radiotherapy. Our recent animal studies showed that low dose arsenic (LDA)-induced transient p53 inhibition selectively protected normal tissues from chemotherapy-induced toxicity. Study objectives were to: 1) define the lowest safe dose of arsenic trioxide that transiently blocks p53 activation in patients and 2) assess the potential of LDA to decrease hematological toxicity from chemotherapy. Patients scheduled to receive minimum 4 cycles of myelosuppressive chemotherapy were eligible. For objective 1, dose escalation of LDA started at 0.005 mg/kg/day for 3 days. This dose satisfied objective 1 and was administered before chemotherapy cycles 2, 4, and 6 for objective 2. p53 level in peripheral lymphocytes was measured on day 1 of each cycle by ELISA assay. Chemotherapy cycles 1, 3, and 5 served as the baseline for the subsequent cycles of 2, 4, and 6 respectively. If p53 level for the subsequent cycle was lower (or higher) than the baseline cycle, p53 was defined as "suppressed" (or "activated") for the pair of cycles. Repeated measures linear models of CBC in terms of day, cycle, p53 activity and interaction terms were used. Twenty-six patients treated with 3 week cycle regimens form the base of analyses. The mean white blood cell, hemoglobin and absolute neutrophil counts were significantly higher in the "suppressed" relative to the "activated" group. These data support the proof of principle that suppression of p53 could lead to protection of bone marrow in patients receiving chemotherapy.This trial is registered in ClinicalTrials.gov. Identifier: NCT01428128