Urban Water Demand Prediction for a City that Suffers from Climate Change and Population Growth: Gauteng Province case study

The proper management of municipal water system is essential to sustain cities and support water security of societies. Urban water estimating has always been a challenging task for managers of water utilities and policymakers. This paper applies a novel methodology that includes data pre-processing and Artificial Neural Network (ANN) optimized with Backtracking Search Algorithm (BSA-ANN) to estimate monthly water demand in relation to previous water consumption. Historical data of monthly water consumption in the Gauteng Province, South Africa, for the period 2007–2016, were selected for the creation and evaluation of the methodology. Data pre-processing techniques played a crucial role in the enhancing of the quality of the data before creating the prediction model. The BSA-ANN model yielded the best result with a root mean square error and a coefficient of efficiency of 0.0099 mega liters and 0.979, respectively. Also, it proved more efficient and reliable than the Crow Search Algorithm (CSA-ANN), based on the scale of error. Overall, this paper presents a new application for the hybrid model BSA-ANN that can be successfully used to predict water demand with high accuracy, in a city that heavily suffers from the impact of climate change and population growth

A Novel Methodology for Prediction Urban Water Demand by Wavelet Denoising and Adaptive Neuro-Fuzzy Inference System Approach

Accurate and reliable urban water demand prediction is imperative for providing the basis to design, operate, and manage water system, especially under the scarcity of the natural water resources. A new methodology combining discrete wavelet transform (DWT) with an adaptive neuro-fuzzy inference system (ANFIS) is proposed to predict monthly urban water demand based on several intervals of historical water consumption. This ANFIS model is evaluated against a hybrid crow search algorithm and artificial neural network (CSA-ANN), since these methods have been successfully used recently to tackle a range of engineering optimization problems. The study outcomes reveal that 1) data preprocessing is essential for denoising raw time series and choosing the model inputs to render the highest model performance; 2) both methodologies, ANFIS and CSA-ANN, are statistically equivalent and capable of accurately predicting monthly urban water demand with high accuracy based on several statistical metric measures such as coefficient of efficiency (0.974, 0.971, respectively). This study could help policymakers to manage extensions of urban water system in response to the increasing demand with low risk related to a decision

Dynamics of FitzHugh-Nagumo excitable systems with delayed coupling

Small lattices of $N$ nearest neighbor coupled excitable FitzHugh-Nagumo systems, with time-delayed coupling are studied, and compared with systems of FitzHugh-Nagumo oscillators with the same delayed coupling. Bifurcations of equilibria in N=2 case are studied analytically, and it is then numerically confirmed that the same bifurcations are relevant for the dynamics in the case $N>2$. Bifurcations found include inverse and direct Hopf and fold limit cycle bifurcations. Typical dynamics for different small time-lags and coupling intensities could be excitable with a single globally stable equilibrium, asymptotic oscillatory with symmetric limit cycle, bi-stable with stable equilibrium and a symmetric limit cycle, and again coherent oscillatory but non-symmetric and phase-shifted. For an intermediate range of time-lags inverse sub-critical Hopf and fold limit cycle bifurcations lead to the phenomenon of oscillator death. The phenomenon does not occur in the case of FitzHugh-Nagumo oscillators with the same type of coupling.Comment: accepted by Phys.Rev.

Macrocyclic colibactin induces DNA double-strand breaks via copper-mediated oxidative cleavage.

Colibactin is an assumed human gut bacterial genotoxin, whose biosynthesis is linked to the clb genomic island that has a widespread distribution in pathogenic and commensal human enterobacteria. Colibactin-producing gut microbes promote colon tumour formation and enhance the progression of colorectal cancer via cellular senescence and death induced by DNA double-strand breaks (DSBs); however, the chemical basis that contributes to the pathogenesis at the molecular level has not been fully characterized. Here, we report the discovery of colibactin-645, a macrocyclic colibactin metabolite that recapitulates the previously assumed genotoxicity and cytotoxicity. Colibactin-645 shows strong DNA DSB activity in vitro and in human cell cultures via a unique copper-mediated oxidative mechanism. We also delineate a complete biosynthetic model for colibactin-645, which highlights a unique fate of the aminomalonate-building monomer in forming the C-terminal 5-hydroxy-4-oxazolecarboxylic acid moiety through the activities of both the polyketide synthase ClbO and the amidase ClbL. This work thus provides a molecular basis for colibactin's DNA DSB activity and facilitates further mechanistic study of colibactin-related colorectal cancer incidence and prevention

Pathogenic Bacillus anthracis in the progressive gene losses and gains in adaptive evolution

Background: Sequence mutations represent a driving force of adaptive evolution in bacterial pathogens. It is especially evident in reductive genome evolution where bacteria underwent lifestyles shifting from a free-living to a strictly intracellular or host-depending life. It resulted in loss of function mutations and/or the acquisition of virulence gene clusters. Bacillus anthracis shares a common soil bacterial ancestor with its closely related bacillus species but is the only obligate, causative agent of inhalation anthrax within the genus Bacillus. The anthrax-causing Bacillus anthracis experienced the similar lifestyle changes. We thus hypothesized that the bacterial pathogen would follow a compatible evolution path. Results: In this study, a cluster-based evolution scheme was devised to analyze genes that are gained by or lost from B. anthracis. The study detected gene losses/gains at two separate evolutionary stages. The stage I is when B. anthracis and its sister species within the Bacillus cereus group diverged from other species in genus Bacillus. The stage II is when B. anthracis differentiated from its two closest relatives: B. cereus and B. thuringiensis. Many genes gained at these stages are homologues of known pathogenic factors such those for internalin, B. anthracis-specific toxins and large groups of surface proteins and lipoproteins. Conclusion: The analysis presented here allowed us to portray a progressive evolutionary process during the lifestyle shift of B. anthracis, thus providing new insights into how B. anthracis had evolved and bore a promise of finding drug and vaccine targets for this strategically important pathogen

The pregnane X receptor drives sexually dimorphic hepatic changes in lipid and xenobiotic metabolism in response to gut microbiota in mice.

The gut microbiota-intestine-liver relationship is emerging as an important factor in multiple hepatic pathologies, but the hepatic sensors and effectors of microbial signals are not well defined. By comparing publicly available liver transcriptomics data from conventional vs. germ-free mice, we identified pregnane X receptor (PXR, NR1I2) transcriptional activity as strongly affected by the absence of gut microbes. Microbiota depletion using antibiotics in Pxr <sup>+/+</sup> vs Pxr <sup>-/-</sup> C57BL/6J littermate mice followed by hepatic transcriptomics revealed that most microbiota-sensitive genes were PXR-dependent in the liver in males, but not in females. Pathway enrichment analysis suggested that microbiota-PXR interaction controlled fatty acid and xenobiotic metabolism. We confirmed that antibiotic treatment reduced liver triglyceride content and hampered xenobiotic metabolism in the liver from Pxr <sup>+/+</sup> but not Pxr <sup>-/-</sup> male mice. These findings identify PXR as a hepatic effector of microbiota-derived signals that regulate the host's sexually dimorphic lipid and xenobiotic metabolisms in the liver. Thus, our results reveal a potential new mechanism for unexpected drug-drug or food-drug interactions. Video abstract

A Novel Semi-Supervised Methodology for Extracting Tumor Type-Specific MRS Sources in Human Brain Data

BackgroundThe clinical investigation of human brain tumors often starts with a non-invasive imaging study, providing information about the tumor extent and location, but little insight into the biochemistry of the analyzed tissue. Magnetic Resonance Spectroscopy can complement imaging by supplying a metabolic fingerprint of the tissue. This study analyzes single-voxel magnetic resonance spectra, which represent signal information in the frequency domain. Given that a single voxel may contain a heterogeneous mix of tissues, signal source identification is a relevant challenge for the problem of tumor type classification from the spectroscopic signal.Methodology/Principal FindingsNon-negative matrix factorization techniques have recently shown their potential for the identification of meaningful sources from brain tissue spectroscopy data. In this study, we use a convex variant of these methods that is capable of handling negatively-valued data and generating sources that can be interpreted as tumor class prototypes. A novel approach to convex non-negative matrix factorization is proposed, in which prior knowledge about class information is utilized in model optimization. Class-specific information is integrated into this semi-supervised process by setting the metric of a latent variable space where the matrix factorization is carried out. The reported experimental study comprises 196 cases from different tumor types drawn from two international, multi-center databases. The results indicate that the proposed approach outperforms a purely unsupervised process by achieving near perfect correlation of the extracted sources with the mean spectra of the tumor types. It also improves tissue type classification.Conclusions/SignificanceWe show that source extraction by unsupervised matrix factorization benefits from the integration of the available class information, so operating in a semi-supervised learning manner, for discriminative source identification and brain tumor labeling from single-voxel spectroscopy data. We are confident that the proposed methodology has wider applicability for biomedical signal processing

Multiproject–multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy

Contains fulltext : 75361.pdf (publisher's version ) (Open Access)14 p

Final results from the PERUSE study of first-line pertuzumab plus trastuzumab plus a taxane for HER2-positive locally recurrent or metastatic breast cancer, with a multivariable approach to guide prognostication

Background: The phase III CLinical Evaluation Of Pertuzumab And TRAstuzumab (CLEOPATRA) trial established the combination of pertuzumab, trastuzumab and docetaxel as standard first-line therapy for human epidermal growth factor receptor 2 (HER2)-positive locally recurrent/metastatic breast cancer (LR/mBC). The multicentre single-arm PERtUzumab global SafEty (PERUSE) study assessed the safety and efficacy of pertuzumab and trastuzumab combined with investigator-selected taxane in this setting. Patients and methods: Eligible patients with inoperable HER2-positive LR/mBC and no prior systemic therapy for LR/mBC (except endocrine therapy) received docetaxel, paclitaxel or nab-paclitaxel with trastuzumab and pertuzumab until disease progression or unacceptable toxicity. The primary endpoint was safety. Secondary endpoints included progression-free survival (PFS) and overall survival (OS). Prespecified subgroup analyses included subgroups according to taxane, hormone receptor (HR) status and prior trastuzumab. Exploratory univariable analyses identified potential prognostic factors; those that remained significant in multivariable analysis were used to analyse PFS and OS in subgroups with all, some or none of these factors. Results: Of 1436 treated patients, 588 (41%) initially received paclitaxel and 918 (64%) had HR-positive disease. The most common grade 653 adverse events were neutropenia (10%, mainly with docetaxel) and diarrhoea (8%). At the final analysis (median follow-up: 5.7 years), median PFS was 20.7 [95% confidence interval (CI) 18.9-23.1] months overall and was similar irrespective of HR status or taxane. Median OS was 65.3 (95% CI 60.9-70.9) months overall. OS was similar regardless of taxane backbone but was more favourable in patients with HR-positive than HR-negative LR/mBC. In exploratory analyses, trastuzumab-pretreated patients with visceral disease had the shortest median PFS (13.1 months) and OS (46.3 months). Conclusions: Mature results from PERUSE show a safety and efficacy profile consistent with results from CLEOPATRA and median OS exceeding 5 years. Results suggest that paclitaxel is a valid alternative to docetaxel as backbone chemotherapy. Exploratory analyses suggest risk factors that could guide future trial design