Landscape Fragmentation as a Risk Factor for Buruli Ulcer Disease in Ghana

Land cover and its change have been linked to Buruli ulcer (BU), a rapidly emerging tropical disease. However, it is unknown whether landscape structure affects the disease prevalence. To examine the association between landscape pattern and BU presence, we obtained land cover information for 20 villages in southwestern Ghana from high resolution satellite images, and analyzed the landscape pattern surrounding each village. Eight landscape metrics indicated that landscape patterns between BU case and reference villages were different (P < 0.05) at the broad spatial extent examined (4 km). The logistic regression models showed that landscape fragmentation and diversity indices were positively associated with BU presence in a village. Specifically, for each increase in patch density and edge density by 100 units, the likelihood of BU presence in a village increased 2.51 (95% confidence interval [CI] = 1.36–4.61) and 4.18 (95% CI = 1.63–10.76) times, respectively. The results suggest that increased landscape fragmentation may pose a risk to the emergence of BU

Diarrheal Diseases in Rural Bangladesh: Spatial-Temporal Patterns, Risk Factors and Pathogen Detection

Diarrheal diseases are still a leading cause of child mortality in less developed countries. In the past three decades, in an effort to reduce the transmission of diarrheal diseases, millions of tubewells have been installed as a way to provide safe drinking water in Bangladesh. However, this effort may have been counterproductive since widespread arsenic contamination has been found in groundwater. Thus, there is a reason to rethink the use of tubewells and to assess risk factors related to diarrheal disease in Bangladesh. This study primarily focused on 142 villages of Matlab, a rural area in Bangladesh, using datasets collected through a local health surveillance system to explore the spatiotemporal patterns of diarrheal disease and its relevant risk factors. First, a geographic information system (GIS) and spatial statistics were used to illustrate the occurrence and spatial-temporal clusters of diarrhea (including community childhood diarrhea data and hospital data on diarrhea caused by rotavirus and Shigella). Second, the study determined the relationship between diarrheal disease among children under five and identified several important risk factors, such as tubewell access, depth and arsenic levels. Additionally, simple and rapid concentration methods were developed and evaluated to detect adenovirus, a common etiologic pathogen of diarrhea in water. The study attempted to answer the following questions: What are the trends and spatial patterns of diarrheal diseases? Are tubewells protective against diarrheal diseases? Does arsenic mitigation by well switching raise the risk of diarrheal disease among children? The results obtained from this study provide some useful information to help policy-makers implement relevant scientific measures for diarrhea reduction and arsenic mitigation. The concentration methods developed in this study are applicable to monitor pathogens in water in Bangladesh and worldwide

Urbanisation and health in China.

China has seen the largest human migration in history, and the country's rapid urbanisation has important consequences for public health. A provincial analysis of its urbanisation trends shows shifting and accelerating rural-to-urban migration across the country and accompanying rapid increases in city size and population. The growing disease burden in urban areas attributable to nutrition and lifestyle choices is a major public health challenge, as are troubling disparities in health-care access, vaccination coverage, and accidents and injuries in China's rural-to-urban migrant population. Urban environmental quality, including air and water pollution, contributes to disease both in urban and in rural areas, and traffic-related accidents pose a major public health threat as the country becomes increasingly motorised. To address the health challenges and maximise the benefits that accompany this rapid urbanisation, innovative health policies focused on the needs of migrants and research that could close knowledge gaps on urban population exposures are needed

Tandem mass spectrometric analysis of protein and peptide adducts of lipid peroxidation-derived aldehydes

The adduction of proteins and other biomolecules by electrophilic lipid peroxidation products such as 4-hydroxy-2-nonenal (HNE), 4-oxo-2-nonenal (ONE), malondialdehyde (MDA) or acrolein (ACR) is thought to be an initiating and/or propagating factor in the pathophysiology of several diseases such as atherosclerosis, diabetes, Alzheimer's, Parkinson's and other age-related disorders. The identification of protein sites modified by oxylipids is of key relevance for advancing our understanding how oxidative damage affects structure and function of proteins. Here, the use of MALDI tandem mass spectrometry with high energy collision-induced dissociation (CID) on a TOF/TOF instrument for sequencing oxylipid-peptide conjugates was systematically studied. Three synthesized model peptides containing one nucleophilic residue (i.e. Cys, His or Lys) were reacted with MDA, HNE, ONE and ACR. MALDI-MS analysis and MS/MS analysis were performed to confirm the adduct type and the modification sites. Michael adducts and Schiff bases were the predominant products under pH 7.4 within 2 hours. All MS/MS spectra of Michael adducts show the neutral loss of the oxylipid moiety ions. MS/MS spectra of Cys-containing peptide oxylipid conjugates exhibit additional characteristic neutral loss of HS-oxylipid moiety ions. MS/MS spectra of His-containing peptide oxylipid conjugates show characteristic oxylipid-containing His immonium ions. Spectra of Lys-containing peptide oxylipid conjugates (Schiff base) also show oxylipid-containing Lys immonium ions. However, there is no neutral loss of the oxylipid moiety ion for these Schiff bases. Determining the extent or relative amounts of the oxidative damage in cells could provide valuable insights into the molecular mechanisms of the diseases caused by oxidative stress. Relative quantitation of oxylipid-modified proteins in biological samples is a challenging problem because of the complexity and extreme dynamic range that characterize these samples. In this study, the reagents, N'-aminooxymethylcarbonylhydrazino-D-biotin (ARP) and iodoacetyl-PEO2- biotin (IPB), were used to enrich acrolein-modified Cys-containing peptides and the corresponding unmodified ones from subsarcolemmal mitochondria (SSM). The ratios between them were determined by nanoLC-SRM analysis. Model Cys-containing peptides labeled with ARP-acrolein and IPB were employed to demonstrate this method. Seven acrolein-modifed Cys-containing peptides from five mitochondrial proteins were quantified. The ratios for those seven peptides from the CCl₄-treated rats are higher than the control ones indicating that the ratios of acrolein-modified peptides to unmodified ones are potential markers of oxidative stress in vivo. Age-dependent changes of protein carbonyls were investigated in subsarcolemmal mitochondria by using LC-SRM analysis of distinct ACR-modified Cys-containing peptides. Immunochemical analysis using an anti-ACR monoclonal antibody supported an increase of proteins modified by acrolein with age. However, total protein carbonyls measurement using ARP in Western blot analysis did not conform to this change suggesting that age-related changes in protein carbonyls are complex and would benefit from more specific measurement protocols

(E)-N′-[4-(Dimethyl­amino)­benzyl­idene]-4-methyl­benzohydrazide methanol monosolvate

In the title compound, C17H19N3O·CH3OH, the hydrazone mol­ecule exists in a trans geometry with respect to the methyl­idene unit and the dihedral angle between the two substituted benzene rings is 42.6 (2)°. In the crystal, the components are linked through N—H⋯O and O—H⋯O hydrogen bonds, forming [100] chains of alternating hydrazone and methanol mol­ecules

MOEA/D with Adaptive Weight Adjustment

Recently, MOEA/D (multi-objective evolutionary algorithm based on decomposition) has achieved great success in the field of evolutionary multi-objective optimization and has attracted a lot of attention. It decomposes a multi-objective optimization problem (MOP) into a set of scalar subproblems using uniformly distributed aggregation weight vectors and provides an excellent general algorithmic framework of evolutionary multi-objective optimization. Generally, the uniformity of weight vectors in MOEA/D can ensure the diversity of the Pareto optimal solutions, however, it cannot work as well when the target MOP has a complex Pareto front (PF; i.e., discontinuous PF or PF with sharp peak or low tail). To remedy this, we propose an improved MOEA/D with adaptive weight vector adjustment (MOEA/D-AWA). According to the analysis of the geometric relationship between the weight vectors and the optimal solutions under the Chebyshev decomposition scheme, a new weight vector initialization method and an adaptive weight vector adjustment strategy are introduced in MOEA/D-AWA. The weights are adjusted periodically so that the weights of subproblems can be redistributed adaptively to obtain better uniformity of solutions. Meanwhile, computing efforts devoted to subproblems with duplicate optimal solution can be saved. Moreover, an external elite population is introduced to help adding new subproblems into real sparse regions rather than pseudo sparse regions of the complex PF, that is, discontinuous regions of the PF. MOEA/D-AWA has been compared with four state of the art MOEAs, namely the original MOEA/D, Adaptive-MOEA/D, [Formula: see text]-MOEA/D, and NSGA-II on 10 widely used test problems, two newly constructed complex problems, and two many-objective problems. Experimental results indicate that MOEA/D-AWA outperforms the benchmark algorithms in terms of the IGD metric, particularly when the PF of the MOP is complex.</jats:p

Adaptive Robust Actuator Fault Accommodation for a Class of Uncertain Nonlinear Systems with Unknown Control Gains

An adaptive robust fault tolerant control approach is proposed for a class of uncertain nonlinear systems with unknown signs of high-frequency gain and unmeasured states. In the recursive design, neural networks are employed to approximate the unknown nonlinear functions, K-filters are designed to estimate the unmeasured states, and a dynamical signal and Nussbaum gain functions are introduced to handle the unknown sign of the virtual control direction. By incorporating the switching function σ algorithm, the adaptive backstepping scheme developed in this paper does not require the real value of the actuator failure. It is mathematically proved that the proposed adaptive robust fault tolerant control approach can guarantee that all the signals of the closed-loop system are bounded, and the output converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by the simulation examples