Developing GIS-based water poverty and rainwater harvesting suitability maps for domestic use in the Dead Sea region (West Bank, Palestine)

In the arid region of the Dead Sea, water shortage and the inability to satisfy the increasing domestic water demand threatens sustainable development. In such situations, domestic rainwater harvesting is considered an efficient way to combat water poverty. This paper aims to develop domestic water poverty (DWP) and domestic rainwater harvesting suitability (DRWHS) maps for the West Bank, Palestine. The analytical hierarchy process (AHP) and the GIS-based weighted overlay summation process (WOSP) were utilized in the development of these maps. Results of the DWP map indicate that 57&thinsp;% of the West Bank is under high to very high poverty of domestic water. The DRWHS map shows that 60&thinsp;% of the West Bank is highly suitable for domestic rainwater harvesting. Spatial intersection (combined mapping) between DWP and DRWHS maps indicates that around 31&thinsp;% of the total West Bank areas could be classified as high potential locations (hotspot areas) for adopting rainwater harvesting techniques for domestic purposes. The developed maps are valuable to the stakeholders to better identify the best areas of rainwater harvesting in the West Bank.</p

The Unconserved Groucho Central Region Is Essential for Viability and Modulates Target Gene Specificity

Groucho (Gro) is a Drosophila corepressor required by numerous DNA-binding repressors, many of which are distributed in gradients and provide positional information during development. Gro contains well-conserved domains at its N- and C-termini, and a poorly conserved central region that includes the GP, CcN, and SP domains. All lethal point mutations in gro map to the conserved regions, leading to speculation that the unconserved central domains are dispensable. However, our sequence analysis suggests that the central domains are disordered leading us to suspect that the lack of lethal mutations in this region reflects a lack of order rather than an absence of essential functions. In support of this conclusion, genomic rescue experiments with Gro deletion variants demonstrate that the GP and CcN domains are required for viability. Misexpression assays using these same deletion variants show that the SP domain prevents unrestrained and promiscuous repression by Gro, while the GP and CcN domains are indispensable for repression. Deletion of the GP domain leads to loss of nuclear import, while deletion of the CcN domain leads to complete loss of repression. Changes in Gro activity levels reset the threshold concentrations at which graded repressors silence target gene expression. We conclude that co-regulators such as Gro are not simply permissive components of the repression machinery, but cooperate with graded DNA-binding factors in setting borders of gene expression. We suspect that disorder in the Gro central domains may provide the flexibility that allows this region to mediate multiple interactions required for repression

Optimal Structural Inference of Signaling Pathways from Unordered and Overlapping Gene Sets

Motivation: A plethora of bioinformatics analysis has led to the discovery of numerous gene sets, which can be interpreted as discrete measurements emitted from latent signaling pathways. Their potential to infer signaling pathway structures, however, has not been sufficiently exploited. Existing methods accommodating discrete data do not explicitly consider signal cascading mechanisms that characterize a signaling pathway. Novel computational methods are thus needed to fully utilize gene sets and broaden the scope from focusing only on pairwise interactions to the more general cascading events in the inference of signaling pathway structures. Results: We propose a gene set based simulated annealing (SA) algorithm for the reconstruction of signaling pathway structures. A signaling pathway structure is a directed graph containing up to a few hundred nodes and many overlapping signal cascades, where each cascade represents a chain of molecular interactions from the cell surface to the nucleus. Gene sets in our context refer to discrete sets of genes participating in signal cascades, the basic building blocks of a signaling pathway, with no prior information about gene orderings in the cascades. From a compendium of gene sets related to a pathway, SA aims to search for signal cascades that characterize the optimal signaling pathway structure. In the search process, the extent of overlap among signal cascades is used to measure the optimality of a structure. Throughout, we treat gene sets as random samples from a first-order Markov chain model. We evaluated the performance of SA in three case studies. In the first study conducted on 83 KEGG pathways, SA demonstrated a significantly better performance than Bayesian network methods. Since both SA and Bayesian network methods accommodate discrete data, use a \u27search and score\u27 network learning strategy and output a directed network, they can be compared in terms of performance and computational time. In the second study, we compared SA and Bayesian network methods using four benchmark datasets from DREAM. In our final study, we showcased two context-specific signaling pathways activated in breast cancer

Early Changes in Cortical Emotion Processing Circuits after Mild Traumatic Brain Injury from Motor Vehicle Collision

Mild traumatic brain injury (mTBI) patients frequently experience emotion dysregulation symptoms, including post-traumatic stress. Although mTBI likely affects cortical activation and structure, resulting in cognitive symptoms after mTBI, early effects of mTBI on cortical emotion processing circuits have rarely been examined. To assess early mTBI effects on cortical functional and structural components of emotion processing, we assessed cortical activation to fearful faces within the first 2 weeks after motor vehicle collision (MVC) in survivors who did and did not experience mTBI. We also examined the thicknesses of cortical regions with altered activation. MVC survivors with mTBI (n = 21) had significantly less activation in left superior parietal gyrus (SPG) (−5.9, −81.8, 33.8; p = 10(−3.623)), left medial orbitofrontal gyrus (mOFG) (−4.7, 36.1, −19.3; p = 10(−3.231)), and left and right lateral orbitofrontal gyri (lOFG) (left: −16.0, 41.4, −16.6; p = 10(−2.573); right: 18.7, 22.7, −17.7; p = 10(−2.764)) than MVC survivors without mTBI (n = 23). SPG activation in mTBI survivors within 2 weeks after MVC was negatively correlated with subsequent post-traumatic stress symptom severity at 3 months (r = −0.68, p = 0.03). Finally, the SPG region was thinner in the mTBI survivors than in the non-mTBI survivors (F = 11.07, p = 0.002). These results suggest that early differences in activation and structure in cortical emotion processing circuits in trauma survivors who sustain mTBI may contribute to the development of emotion-related symptoms