Dynamic electrocardiogram changes are a novel risk marker for sudden cardiac death.

BACKGROUND AND AIMS: Electrocardiogram (ECG) abnormalities have been evaluated as static risk markers for sudden cardiac death (SCD), but the potential importance of dynamic ECG remodelling has not been investigated. In this study, the nature and prevalence of dynamic ECG remodelling were studied among individuals who eventually suffered SCD. METHODS: The study population was drawn from two prospective community-based SCD studies in Oregon (2002, discovery cohort) and California, USA (2015, validation cohort). For this present sub-study, 231 discovery cases (2015-17) and 203 validation cases (2015-21) with ≥2 archived pre-SCD ECGs were ascertained and were matched to 234 discovery and 203 validation controls based on age, sex, and duration between the ECGs. Dynamic ECG remodelling was measured as progression of a previously validated cumulative six-variable ECG electrical risk score. RESULTS: Oregon SCD cases displayed greater electrical risk score increase over time vs. controls [+1.06 (95% confidence interval +0.89 to +1.24) vs. -0.05 (-0.21 to +0.11); P < .001]. These findings were successfully replicated in California [+0.87 (+0.7 to +1.04) vs. -0.11 (-0.27 to 0.05); P < .001]. In multivariable models, abnormal dynamic ECG remodelling improved SCD prediction over baseline ECG, demographics, and clinical SCD risk factors in both Oregon [area under the receiver operating characteristic curve 0.770 (95% confidence interval 0.727-0.812) increased to area under the receiver operating characteristic curve 0.869 (95% confidence interval 0.837-0.902)] and California cohorts. CONCLUSIONS: Dynamic ECG remodelling improved SCD risk prediction beyond clinical factors combined with the static ECG, with successful validation in a geographically distinct population. These findings introduce a novel concept of SCD dynamic risk and warrant further detailed investigation.

Social Phenotyping for Cardiovascular Risk Stratification in Electronic Health Registries.

PURPOSE OF REVIEW: Evaluation of social influences on cardiovascular care requires a comprehensive analysis encompassing economic, societal, and environmental factors. The increased utilization of electronic health registries provides a foundation for social phenotyping, yet standardization in methodology remains lacking. This review aimed to elucidate the primary approaches to social phenotyping for cardiovascular risk stratification through electronic health registries. RECENT FINDINGS: Social phenotyping in the context of cardiovascular risk stratification within electronic health registries can be separated into four principal approaches: place-based metrics, questionnaires, ICD Z-coding, and natural language processing. These methodologies vary in their complexity, advantages and limitations, and intended outcomes. Place-based metrics often rely on geospatial data to infer socioeconomic influences, while questionnaires may directly gather individual-level behavioral and social factors. Z-coding, a relatively new approach, can capture data directly related to social determinant of health domains in the clinical context. Natural language processing has been increasingly utilized to extract social influences from unstructured clinical narratives-offering nuanced insights for risk prediction models. Each method plays an important role in our understanding and approach to using social determinants data for improving population cardiovascular health. These four principal approaches to social phenotyping contribute to a more structured approach to social determinant of health research via electronic health registries, with a focus on cardiovascular risk stratification. Social phenotyping related research should prioritize refining predictive models for cardiovascular diseases and advancing health equity by integrating applied implementation science into public health strategies.

United States-Mexico Border Disparities in Alcoholic Liver Disease Mortality: A Cross-Sectional Analysis 1999-2020.

BACKGROUND: US-Mexico (US-MX) border regions are impacted by socioeconomic disadvantages. Alcohol use disorder remains widely prevalent in US-MX border regions, which may increase the risk of alcoholic liver disease (ALD). GOALS: We aimed to characterize ALD mortality trends in border regions compared to non-border regions from 1999 to 2020 in the United States (US). METHODS: We performed a cross-sectional analysis using the CDC repository. We queried death certificates to find ALD-related deaths from 1999 to 2020, which included demographic information such as gender, race/ethnicity, and area of residence. We estimated age-adjusted mortality rates (AAMR) per 100,000 population and compared the AAMRs across border and non-border regions. We also explored yearly mortality shifts using log-linear regression models and calculated the average annual percentage change (AAPC) using the Monte Carlo permutation test. RESULTS: In all, 11,779 ALD-related deaths were identified in border regions (AAMR 7.29) compared with 361,523 in non-border regions (AAMR 5.03). Border male (AAMR 11.21) and female (AAMR 3.77) populations were higher compared with non-border male (AAMR 7.42) and female (2.85) populations, respectively. Border non-Hispanic populations (AAMR 7.53) had higher mortality compared with non-border non-Hispanic populations (4.79), while both populations experienced increasing mortality shifts (AAPC +1.7, P<0.001 and +3.1, P<0.001, respectively). Border metropolitan (AAMR 7.35) and non-metropolitan (AAMR 6.76) regions had higher mortality rates compared with non-border metropolitan (AAMR 4.96) and non-metropolitan (AAMR 5.44) regions. CONCLUSIONS: Mortality related to ALD was higher in border regions compared with non-border regions. Border regions face significant health disparities when comparing ALD-related mortality.

Efficacy and safety of fenofibrate in combination with phototherapy for the treatment of neonatal hyperbilirubinemia: a systematic review and meta-analyses.

Phototherapy is the standard treatment for neonatal jaundice. We aimed to review the efficacy and safety of fenofibrate as an adjunct therapy. Twelve databases were searched and a systematic review and meta-analysis were conducted. Mean change (MC), mean difference (MD), and risk ratios (RR) with a 95% confidence interval (CI) were calculated using a random effects model. The GRADE approach was used to evaluate the evidence's certainty. Nine randomized trials were included. The MC of total serum bilirubin (mg/dL) was significant at 12, 24, 36, 48, and 72 h with respective MC (95% CI) values of -0.46 (-0.61, -0.310), -1.10 (-1.68, -0.52), -2.06 (-2.20, -1.91), -2.15 (-2.74, -1.56), and -1.13 (-1.71, -0.55). The FEN + PT group had a shorter duration of phototherapy (MD: -14.36 h; 95% CI: -23.67, -5.06) and a shorter hospital stay (MD: -1.40 days; 95% CI: -2.14, -0.66). There was no significant difference in the risk of complications (RR: 0.89; 95% CI: 0.54, 1.46) or the need for exchange transfusion (RR: 0.58; 95% CI: 0.12, 2.81). The certainty of the evidence was very low for all outcomes. In conclusion, fenofibrate might be a safe adjunct to neonatal phototherapy. Larger randomized controlled trials are needed for the confirmation of these results.

Three neo-Clerodane Diterpenoids from Tinospora cordifolia Stems and Their Arginase Inhibitory Activities.

Three neo-clerodane diterpenoids, including two new tinocordifoliols A (1) and B (2) and one known tinopanoid R (3), were isolated from the ethyl acetate-soluble fraction of the 70% ethanol extract of Tinospora cordifolia stems. The structures were elucidated by various spectroscopic methods, including one dimensional (1D) and 2D-NMR, high resolution-electrospray ionization (HR-ESI)-MS, and electronic circular dichroism (ECD) data. The T. cordifolia extract and all isolated compounds 1-3 possessed arginase I inhibitory activities. Among them, 3 exhibited moderate competitive inhibition of human arginase I (IC50 = 61.9 µM). Furthermore, docking studies revealed that the presence of a ß-substituted furan in 3 may play a key role in the arginase I inhibitory activities.

Rural-urban stroke mortality gaps in the United States.

INTRODUCTION: Disparities in stroke outcomes, influenced by the use of systemic thrombolysis, endovascular therapies, and rehabilitation services, have been identified. Our study assesses these disparities in mortality after stroke between rural and urban areas across the United States (US). METHODS: We analyzed the CDC data on deaths attributed to cerebrovascular disease from 1999 to 2020. Data was categorized into rural and urban regions for comparative purposes. Age-adjusted mortality rates (AAMR) were computed using the direct method, allowing us to examine the ratios of rural to urban deaths for the cumulative population and among demographic subpopulations. Linear regression models were used to assess temporal changes in mortality ratios over the study period, yielding beta-coefficients (ß). RESULTS: There was a total of 628,309 stroke deaths in rural regions and 2,556,293 stroke deaths within urban regions. There were 1.13 rural deaths for each one urban death per 100,000 population in 1999 and 1.07 in 2020 (ß = -0.001, ptrend = 0.41). The rural-urban mortality ratio in Hispanic populations decreased from 1.32 rural deaths for each urban death per 100,000 population in 1999 to 0.85 in 2020 (ß = -0.011, ptrend < 0.001). For non-Hispanic populations, mortality remained stagnant with 1.12 rural deaths for each urban death per 100,000 population in 1999 and 1.07 in 2020 (ß = -0.001, ptrend = 0.543). Regionally, the Southern US exhibited the highest disparity with a urban-rural mortality ratio of 1.19, followed by the Northeast (1.13), Midwest (1.04), and West (1.01). CONCLUSIONS: Our findings depict marked disparities in stroke mortality between rural and urban regions, emphasizing the importance of targeted interventions to mitigate stroke-related disparities.

3D-ordered porous CdS/AgI/ZnO nanostructures for high-performance photoelectrochemical water splitting.

3D-ordered porous CdS/AgI/ZnO nanostructures were designed to perform as high-performance photoelectrodes for photoelectrochemical (PEC) water-splitting applications. They rely on the advantages of an extremely large active surface area, high absorption capacity in the visible-light region, fast carrier separation and transportation caused by the intrinsic ladder-like band arrangement. These nanostructures were fabricated by employing a three-stage experiment in a sequence of hard mold-assisted electrochemical deposition, wet chemical method and deposition-precipitation. First, 3D-ordered ZnO nanostructures were electrochemically deposited using a polystyrene film as the sacrificed template. AgI nanoparticles were then decorated on the interfacial ZnO nanostructures by deposition-precipitation. Finally, these binary AgI/ZnO nanoporous networks were thoroughly wet-chemically coated with a CdS film to form a so-called 'ternary interfacial CdS/AgI/ZnO nanostructures'. The PEC water-splitting properties of the fabricated 3D nanostructures were systematically studied and compared. As a result, the highest efficiency of the fabricated 3D-ordered porous CdS/AgI/ZnO measured under the irradiation of solar simulation is about 5.2%, which is relatively 1.5, 3.5 and 11.3 times greater than that of the corresponding CdS/ZnO (3,4%), AgI/ZnO (1.5%) and pristine porous ZnO (0.46%) photoelectrodes, respectively. The significant improvement in the PEC activity is attributed to the enhanced charge separation and transport of ternary photoelectrodes caused by an unconventional ladder-like band arrangement formed between interfacial CdS-AgI-ZnO. Our study provides a promising strategy for developing such ternary photoelectrode generation that possesses higher stability and efficiency towards water-splitting processes.

Assessment of Mobilization Potential of Per- and Polyfluoroalkyl Substances for Soil Remediation.

This study investigated the mobilization of a wide range of per- and polyfluoroalkyl substances (PFASs) present in aqueous film-forming foams (AFFFs) in water-saturated soils through one-dimensional (1-D) column experiments with a view to assessing the feasibility of their remediation by soil desorption and washing. Results indicated that sorption/desorption of most of the shorter-carbon-chain PFASs (C ≤ 6) in soil reached greater than 99% rapidly─after approximately two pore volumes (PVs) and were well predicted by an equilibrium transport model, indicating that they will be readily removed by soil washing technologies. In contrast, the equilibrium model failed to predict the mobilization of longer-chain PFASs (C ≥ 7), indicating the presence of nonequilibrium sorption/desorption (confirmed by a flow interruption experiment). The actual time taken to attain 99% sorption/desorption was up to 5 times longer than predicted by the equilibrium model (e.g., ∼62 PVs versus ∼12 PVs predicted for perfluorooctane sulfonate (PFOS) in loamy sand). The increasing contribution of hydrophobic interactions over the electrostatic interactions is suggested as the main driving factor of the nonequilibrium processes. The inverse linear relationship (R2 = 0.6, p < 0.0001) between the nonequilibrium mass transfer rate coefficient and the Freundlich sorption coefficient could potentially be a useful means for preliminary evaluation of potential nonequilibrium sorption/desorption of PFASs in soils.

Flavonoids from Woodfordia fruticosa as potential SmltD inhibitors in the alternative biosynthetic pathway of peptidoglycan.

SmltD is an ATP-dependent ligase that catalyzes the condensation of UDP-MurNAc-l-Ala and l-Glu to form UDP-MurNAc-l-Ala-l-Glu, in the newly discovered peptidoglycan biosynthesis pathway of a Gram-negative multiple-drug-resistant pathogen, Stenotrophomonas maltophilia. Phytochemical investigation of the 70% ethanol extract from Woodfordia fruticosa flowers collected in Myanmar led to the identification of anti-SmltD active flavonoids, kaempferol 3-O-(6''-galloyl)-ß-d-glucopyranoside (1), astragalin (2), and juglalin (3). Among them, 1 showed the most potent SmltD inhibitory activity. An enzyme steady-state kinetic study revealed that 1 exerted competitive inhibition with respect to ATP. The results of this study provided an attractive foundation for the further development of novel inhibitors of SmltD.

Low-operating temperature and remarkably responsive methanol sensors using Pt-decorated hierarchical ZnO structure.

Highly responsive methanol sensors working at low temperatures are developed using hierarchical ZnO nanorods decorated by Pt nanoparticles. The sensing materials are fabricated following a 3-step process: electrospinning of ZnO nanofibers, hydrothermal growth of hierarchical ZnO nanorods on the nanofibers and UV-assisted deposition of Pt nanoparticles. The morphology, structure and properties of the materials are examined by field-effect scanning electron microscopy, transmission electron microscope, x-ray diffraction, x-ray photoelectron spectroscopy, UV-Vis absorption spectroscopy, and electrical measurements. The methanol sensing performance is investigated at different working temperatures in the range of 110 °C-260 °C. It is observed that the surface modification of the ZnO hierarchical nanorods by Pt nanoparticles results in a remarkable enhancement of the sensing response toward methanol, which can reach approximately 19 500 times higher than that of the unmodified ZnO nanorods-based sensor. In addition, this modification enables lower working temperatures with an optimum range of 140 °C-200 °C. Based on the achieved results, a methanol sensing mechanism of the Pt/ZnO structure is proposed.

A New Monoterpene from the Rhizomes of Alpinia galanga and Its Anti-Vpr Activity.

A new menthane-type monoterpene, alpigalanol (1), together with four known terpenes (2-5) were isolated from the ethyl acetate soluble fraction of the 70 % ethanol extract of the Alpinia galanga rhizomes. The structure of 1 was determined by spectroscopic analyses, including 1D- and 2D-NMR. The extract of the A. galanga rhizomes and all isolated compounds (1-5) possessed Vpr inhibitory activities against the TREx-HeLa-Vpr cells at a concentration of 1.25 µM without showing any cytotoxicity.

A new hybrid equilibrium optimized SysFor based geospatial data mining for tropical storm-induced flash flood susceptible mapping.

Flash flood is one of the most dangerous hydrologic and natural phenomena and is considered as the top ranking of such events among various natural disasters due to their fast onset characteristics and the proportion of individual fatalities. Mapping the probability of flash flood events remains challenges because of its complexity and rapid onset of precipitation. Thus, this study aims to propose a state-of-the-art data mining approach based on a hybrid equilibrium optimized SysFor, namely, the HE-SysFor model, for spatial prediction of flash floods. A tropical storm region located in the Northwest areas of Vietnam is selected as a case study. For this purpose, 1866 flash-flooded locations and ten indicators were used. The results show that the proposed HE-SysFor model yielded the highest predictive performance (total accuracy = 93.8%, Kappa index = 0.875, F1-score = 0.939, and AUC = 0.975) and produced the better performance than those of the C4.5 decision tree (C4.5), the radial basis function-based support vector machine (SVM-RBF), the logistic regression (LReg), and deep learning neural network (DeepLNN) models in both the training and the testing phases. Among the ten indicators, elevation, slope, and land cover are the most important. It is concluded that the proposed model provides an alternative tool and may help for effectively monitoring flash floods in tropical areas and robust policies for decision making in mitigating the flash flood impacts.

Antimelanogenic Activity of Ocotillol-Type Saponins from Panax vietnamensis.

The ocotillol (OCT)-type saponins have been known as a tetracyclic triterpenoid, possessing five- or six-membered epoxy ring in the side chain. Interestingly, this type saponin was mostly found in Panax vietnamensis Ha et Grushv., Araliaceae (VG), hence making VG unique from the other Panax spp. Five OCT-type saponins, majonoside R2, vina-ginsenoside R2, majonoside R1, pseudoginsenoside RT4, vina-ginsenoside R11, together with three protopanaxadiol (PPD)-type saponins and four protopanaxatriol (PPT)-type saponins from VG were evaluated for their antimelanogenic activity. All of isolates were found to be active. More importantly, the five OCT-type saponins inhibited melanin production in B16-F10 mouse melanoma cells, without showing any cytotoxicity. Besides ginsenoside Rd and ginsenoside Rg3 in PPD and notoginsenoside R1 in PPT-type saponins, majonoside R2 was the most potent melanogenesis inhibitory activity in OCT-type saponins. In this article, we highlighted antimelanogenic activity of OCT-type saponins and potential structure-activity relationship (SAR) of ginsenosides. Our results suggested that OCT-type saponins could be used as a depigmentation agent.

Bentonite-supported nano zero-valent iron composite as a green catalyst for bisphenol A degradation: Preparation, performance, and mechanism of action.

Bisphenol A (BPA) is a toxic environmental pollutant commonly found in wastewater. Using non-toxic materials and eco-friendly technology to remove this pollutant from wastewater presents multiple advantages. Treatment of wastewater with clay minerals has received growing interest because of the environment friendliness of these materials. Bentonite is a 2:1 layered phyllosilicate clay mineral that can support nano-metal catalysts. It can prevent the agglomeration of nano-metal catalysts and improve their activity. In this article, a green catalytic nano zero-valent iron/bentonite composite material (NZVI@bentonite) was synthesized via liquid-phase reduction. The average size of NZVI was approximately 40-50 nm. Good dispersion and low aggregation were observed when NZVI was loaded on the surface or embedded into the nanosheets of bentonite. Degradation of BPA, a harmful contaminant widely found in wastewater at relatively high levels, by NZVI@bentonite was then investigated and compared with that by pristine NZVI through batch Fenton-like reaction experiments. Compared with pristine NZVI and bentonite alone, the NZVI@bentonite showed a higher BPA degradation ratio and offered highly effective BPA degradation up to 450 mg/g in wastewater under optimum operating conditions. Adsorption coupled with the Fenton-like reaction was responsible for BPA degradation by NZVI@bentonite. This work extends the application of NZVI@bentonite as an effective green catalyst for BPA degradation in aqueous environments.

Do Intracerebral Cytokine Responses Explain the Harmful Effects of Dexamethasone in Human Immunodeficiency Virus-associated Cryptococcal Meningitis?

BACKGROUND: The CryptoDex trial showed that dexamethasone caused poorer clinical outcomes and slowed fungal clearance in human immunodeficiency virus-associated cryptococcal meningitis. We analyzed cerebrospinal fluid (CSF) cytokine concentrations from participants over the first week of treatment to investigate mechanisms of harm and test 2 hypotheses: (1) dexamethasone reduced proinflammatory cytokine concentrations, leading to poorer outcomes and (2) leukotriene A4 hydrolase (LTA4H) genotype influenced the clinical impact of dexamethasone, as observed in tuberculous meningitis. METHODS: We included participants from Vietnam, Thailand, and Uganda. Using the Luminex system, we measured CSF concentrations of the following: interferon γ, tumor necrosis factor (TNF) α, granulocyte-macrophage colony-stimulating factor, monocyte chemoattractant 1, macrophage inflammatory protein 1α, and interleukin 6, 12p70, 8, 4, 10, and 17. We determined the LTA4H genotype based on the promoter region single-nucleotide polymorphism rs17525495. We assessed the impact of dexamethasone on cytokine concentration dynamics and the association between cytokine concentration dynamics and fungal clearance with mixed effect models. We measured the influence of LTA4H genotype on outcomes with Cox regression models. RESULTS: Dexamethasone increased the rate TNF-α concentration's decline in (-0.13 log2pg/mL/d (95% confidence interval, -.22 to -.06 log2pg/mL/d; P = .03), which was associated with slower fungal clearance (correlation, -0.62; 95% confidence interval, -.83 to -.26). LTA4H genotype had no statistically significant impact on outcome or response to dexamethasone therapy. Better clinical outcomes were associated with higher baseline concentrations of interferon γ. CONCLUSIONS: Dexamethasone may slow fungal clearance and worsen outcomes by increasing TNF-α concentration's rate of decline.

Spatial pattern analysis and prediction of forest fire using new machine learning approach of Multivariate Adaptive Regression Splines and Differential Flower Pollination optimization: A case study at Lao Cai province (Viet Nam).

Understanding spatial patterns of forest fire is of key important for fire danger management and ecological implication. This aim of this study was to propose a new machine learning methodology for analyzing and predicting spatial patterns of forest fire danger with a case study of tropical forest fire at Lao Cai province (Vietnam). For this purpose, a Geographical Information System (GIS) database for the study area was established, including ten influencing factors (slope, aspect, elevation, land use, distance to road, normalized difference vegetation index, rainfall, temperature, wind speed, and humidity) and 257 fire locations. The relevance level of these factors with the forest fire was analyzed and assessed using the Mutual Information algorithm. Then, a new hybrid artificial intelligence model named as MARS-DFP, which was Multivariate Adaptive Regression Splines (MARS) optimized by Differential Flower Pollination (DFP), was proposed and used construct forest fire model for generating spatial patterns of forest fire. MARS is employed to build the forest fire model for generalizing a classification boundary that distinguishes fire and non-fire areas, whereas DFP, a metaheuristic approach, was utilized to optimize the model. Finally, global prediction performance of the model was assessed using Area Under the curve (AUC), Classification Accuracy Rate (CAR), Wilcoxon signed-rank test, and various statistical indices. The result demonstrated that the predictive performance of the MARS-DFP model was high (AUC = 0.91 and CAR = 86.57%) and better to those of other benchmark methods, Backpropagation Artificial Neural Network, Adaptive neuro fuzzy inference system, Radial Basis Function Neural Network. This fact confirms that the newly constructed MARS-DFP model is a promising alternative for spatial prediction of forest fire susceptibility.

Removal and monitoring acetaminophen-contaminated hospital wastewater by vertical flow constructed wetland and peroxidase enzymes.

Hospital wastewater contains acetaminophen (ACT) and nutrient, which need adequate removal and monitoring to prevent impact to environment and community. This study developed a pilot scale vertical flow constructed wetland (CW) to (1) remove high-dose ACT and pollutants in hospital wastewater and (2) identify the correlation of peroxidase enzyme extruded by Scirpus validus and pollutants removal efficiency. By that correlation, a low-cost method to monitor pollutants removal was drawn. Plants, such as Scirpus validus, generated peroxidase enzymes to alleviate pollutants' stress. Results showed that the CW removed 3.5 to 6 logs of initial concentration 10 mg ACT/L to a recommended level for drinking water. The CW eliminated COD, TKN and TP efficiently, meeting the wastewater discharged standards of Thailand and Vietnam. By various multivariable regression models, concentrations of ACT in CW effluent and enzymes in S. validus exhibited a significant correlation (p < 0.01, R2 = 68.3%). These findings suggested that (i) vertical flow CW could remove high-dose ACT and nutrient and (ii) peroxidase enzymes generated in S. validus, such as soluble and covalent ones, could track ACT removal efficiency. This would help to reduce facilities and analytical cost of micro-pollutants.

Establishment of a Wolbachia Superinfection in Aedes aegypti Mosquitoes as a Potential Approach for Future Resistance Management.

Wolbachia pipientis is an endosymbiotic bacterium estimated to chronically infect between 40-75% of all arthropod species. Aedes aegypti, the principle mosquito vector of dengue virus (DENV), is not a natural host of Wolbachia. The transinfection of Wolbachia strains such as wAlbB, wMel and wMelPop-CLA into Ae. aegypti has been shown to significantly reduce the vector competence of this mosquito for a range of human pathogens in the laboratory. This has led to wMel-transinfected Ae. aegypti currently being released in five countries to evaluate its effectiveness to control dengue disease in human populations. Here we describe the generation of a superinfected Ae. aegypti mosquito line simultaneously infected with two avirulent Wolbachia strains, wMel and wAlbB. The line carries a high overall Wolbachia density and tissue localisation of the individual strains is very similar to each respective single infected parental line. The superinfected line induces unidirectional cytoplasmic incompatibility (CI) when crossed to each single infected parental line, suggesting that the superinfection would have the capacity to replace either of the single constituent infections already present in a mosquito population. No significant differences in fitness parameters were observed between the superinfected line and the parental lines under the experimental conditions tested. Finally, the superinfected line blocks DENV replication more efficiently than the single wMel strain when challenged with blood meals from viremic dengue patients. These results suggest that the deployment of superinfections could be used to replace single infections and may represent an effective strategy to help manage potential resistance by DENV to field deployments of single infected strains.

A Novel Hybrid Swarm Optimized Multilayer Neural Network for Spatial Prediction of Flash Floods in Tropical Areas Using Sentinel-1 SAR Imagery and Geospatial Data.

Flash floods are widely recognized as one of the most devastating natural hazards in the world, therefore prediction of flash flood-prone areas is crucial for public safety and emergency management. This research proposes a new methodology for spatial prediction of flash floods based on Sentinel-1 SAR imagery and a new hybrid machine learning technique. The SAR imagery is used to detect flash flood inundation areas, whereas the new machine learning technique, which is a hybrid of the firefly algorithm (FA), Levenberg⁻Marquardt (LM) backpropagation, and an artificial neural network (named as FA-LM-ANN), was used to construct the prediction model. The Bac Ha Bao Yen (BHBY) area in the northwestern region of Vietnam was used as a case study. Accordingly, a Geographical Information System (GIS) database was constructed using 12 input variables (elevation, slope, aspect, curvature, topographic wetness index, stream power index, toposhade, stream density, rainfall, normalized difference vegetation index, soil type, and lithology) and subsequently the output of flood inundation areas was mapped. Using the database and FA-LM-ANN, the flash flood model was trained and verified. The model performance was validated via various performance metrics including the classification accuracy rate, the area under the curve, precision, and recall. Then, the flash flood model that produced the highest performance was compared with benchmarks, indicating that the combination of FA and LM backpropagation is proven to be very effective and the proposed FA-LM-ANN is a new and useful tool for predicting flash flood susceptibility.