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The sterile insect technique (SIT) is an environmentally safe and proven technology to suppress wild populations. To further advance its utility, a novel CRISPR-based technology termed precision guided SIT (pgSIT) is described. PgSIT mechanistically relies on a dominant genetic technology that enables simultaneous sexing and sterilization, facilitating the release of eggs into the environment ensuring only sterile adult males emerge. Importantly, for field applications, the release of eggs will eliminate burdens of manually sexing and sterilizing males, thereby reducing overall effort and increasing scalability. Here, to demonstrate efficacy, we systematically engineer multiple pgSIT systems in Drosophila which consistently give rise to 100% sterile males. Importantly, we demonstrate that pgSIT-generated sterile males are fit and competitive. Using mathematical models, we predict pgSIT will induce substantially greater population suppression than can be achieved by currently-available self-limiting suppression technologies. Taken together, pgSIT offers to potentially transform our ability to control insect agricultural pests and disease vectors. Sterile Insect Technique (SIT) is used to suppress wild populations. Here the authors integrate CRISPR-based technology and SIT to develop a precision guided SIT (pgSIT), and demonstrate its proof-of-principle by generating 100% sterile males.

As Africa-wide malaria prevalence declines, an understanding of human movement patterns is essential to inform how best to target interventions. We fitted movement models to trip data from surveys conducted at 3–5 sites throughout each of Mali, Burkina Faso, Zambia and Tanzania. Two models were compared in terms of their ability to predict the observed movement patterns – a gravity model, in which movement rates between pairs of locations increase with population size and decrease with distance, and a radiation model, in which travelers are cumulatively “absorbed” as they move outwards from their origin of travel. The gravity model provided a better fit to the data overall and for travel to large populations, while the radiation model provided a better fit for nearby populations. One strength of the data set was that trips could be categorized according to traveler group – namely, women traveling with children in all survey countries and youth workers in Mali. For gravity models fitted to data specific to these groups, youth workers were found to have a higher travel frequency to large population centers, and women traveling with children a lower frequency. These models may help predict the spatial transmission of malaria parasites and inform strategies to control their spread.

About one third of non-IPF ILD patients progresses over time. Serum KL-6, a lung epithelial mucin type 1, is an established marker to assess disease severity in ILD but its ability to predict progression needs to be further explored. To investigate whether serum KL-6 is of additional value to stratify the patients for the risk of developing clinical or functional progression at one year. ILD patients from 6 European centers were retrospectively enrolled. Disease progression was defined as relative decline ⩾10% in FVC or ⩾15% in DLco from baseline. Serum KL-6 was measured using a full-automated chemiluminescent immunoassay (Fujirebio). Comparative logistic regression was used to identify predictors of progression at one year. 303 patients were included. 37% developed progression after one year from KL-6 measurement. A stepwise selection was used to identify and include five predictors of progression in a risk score: age, gender, BMI, FVC, and KL-6. The final model was superior to KL-6 alone to predict progression at one year, with 55% sensitivity, 73% specificity and 67% accuracy at a cut-off of 5. Patients were stratified in low and high risk of progression at one year based on the cut-off of 5, with a similar accuracy for IIP 0.687 and CTD-ILD 0.720 but not for HP. Serum KL-6 levels, included in a risk score with other clinical and functional variables, may help to better stratify patients for the risk of disease progression at one year, compared to any individual predictor.

The high impact of air quality on environmental and human health justifies the increasing research activity regarding its measurement, modelling, forecasting and anomaly detection. Raw data offered by sensors usually makes the mentioned time series disciplines difficult. This is why the application of techniques to improve time series processing is a challenge. In this work, Singular Spectral Analysis (SSA) is applied to air quality analysis from real recorded data as part of the Help Responder research project. Authors evaluate the benefits of working with SSA processed data instead of raw data for modelling and estimation of the resulting time series. However, what is more relevant is the proposal to detect indoor air quality anomalies based on the analysis of the time derivative SSA signal when the time derivative of the noisy original data is useless. A dual methodology, evaluating level and dynamics of the SSA signal variation, contributes to identifying risk situations derived from air quality degradation.

The Ross-Macdonald model has exerted enormous influence over the study of malaria transmission dynamics and control, but it lacked features to describe parasite dispersal, travel, and other important aspects of heterogeneous transmission. Here, we present a patch-based differential equation modeling framework that extends the Ross-Macdonald model with sufficient skill and complexity to support planning, monitoring and evaluation for Plasmodium falciparum malaria control. We designed a generic interface for building structured, spatial models of malaria transmission based on a new algorithm for mosquito blood feeding. We developed new algorithms to simulate adult mosquito demography, dispersal, and egg laying in response to resource availability. The core dynamical components describing mosquito ecology and malaria transmission were decomposed, redesigned and reassembled into a modular framework. Structural elements in the framework—human population strata, patches, and aquatic habitats—interact through a flexible design that facilitates construction of ensembles of models with scalable complexity to support robust analytics for malaria policy and adaptive malaria control. We propose updated definitions for the human biting rate and entomological inoculation rates. We present new formulas to describe parasite dispersal and spatial dynamics under steady state conditions, including the human biting rates, parasite dispersal, the “vectorial capacity matrix,” a human transmitting capacity distribution matrix, and threshold conditions. An R package that implements the framework, solves the differential equations, and computes spatial metrics for models developed in this framework has been developed. Development of the model and metrics have focused on malaria, but since the framework is modular, the same ideas and software can be applied to other mosquito-borne pathogen systems.

The key issues in any fire emergency are recognising fire hotspots, locating the emergency intervention team (EI), following the evolution of the fire, and selecting the evacuation path. This leads to the study and development of HelpResponder, a solution capable of detecting the focus of interest in hostile spaces derived from fire due to high temperatures without visibility. A study is conducted to determine which model best predicts measured CO 2 levels. The variables used are temperature, humidity, and air quality, obtained from sensors installed in a fire tower. The statistical methods applied, namely ARIMAX, KNN, SVM, and TBATS, allow the adjustment and modelling of the variables. Explanatory variables with temporal structure are incorporated into SVM, a new improvement proposal. Moreover, combining different models showed the best efficiency in forecasting. In fact, another contribution of our work lies in offering a small-scale prediction system that is specifically designed to save batteries. The system has been tested and validated in a hostile environment (building), simulating real emergency situations. The system has been tested and validated in several hostile environments, simulating real emergency situations. It can help firefighters respond faster in an emergency. This reduces the risks associated with the lack of information and improves the time for tactical operations, which could save lives.

Schistosomiasis is a major public health concern, with 200 million people infected worldwide. In Brazil, this disease has been reported in 19 states, and its prevalence in the city of Barra Mansa in Rio de Janeiro State is 1 %. The parasitological diagnostic methods currently available in these areas lack sensitivity; however, enzyme-linked immunosorbent assays (ELISAs) have been employed successfully for the diagnosis of schistosomiasis by using antibodies against antigens of Schistosoma mansoni adult worms and eggs, and for the detection of circulating antigens. The objective of this study was to determine systematically the prevalence of S. mansoni infection in the peripheral areas of Barra Mansa. A cross-sectional study was conducted from April to December 2011 by using probabilistic sampling that collected 610 fecal samples and 612 serum samples. ELISA-IgG with total extracts and ELISA-IgM with trichloroacetic acid-soluble fractions were employed to detect antibodies against S. mansoni and were compared with the Kato–Katz and Hoffman parasitological techniques. Among the individuals studied, anti- S. mansoni antibodies were detected in 11.16 % ( n  = 71) by ELISA-IgG and in 20.75 % ( n  = 132) by ELISA-IgM, while the parasitological techniques showed 0.82 % ( n  = 5) positivity. The agreement between the two ELISA tests was 85.38 % ( n  = 543), and 8.65 % ( n  = 55) of the serum samples showed positive results in both tests. The higher positivity of the ELISA-IgM test corroborates the results of previous reports and indicates that the test may be a useful tool in epidemiological studies, particularly in areas of low endemicity for S. mansoni .

An imbalance in the redox state, increased levels of lipid precursors and overactivation of de novo lipogenesis determine the development of fibrosis during nonalcoholic steatohepatitis (NASH). We evaluated the modulation of NADPH-producing enzymes associated with the antifibrotic, antioxidant and antilipemic effects of nicotinamide (NAM) in a model of NASH induced by excess fructose consumption. Male rats were provided drinking water containing 40% fructose for 16 weeks. During the last 12 weeks of fructose administration, water containing NAM was provided to some of the rats for 5 h/day. The biochemical profiles and the ghrelin, leptin, lipoperoxidation and TNF-α levels in serum and the glucose-6-phosphate dehydrogenase (G6PD), malic enzyme (ME) and NADP + -dependent isocitric dehydrogenase (IDP) levels, the reduced/oxidized glutathione (GSH/GSSG) and reduced/oxidized nicotinamide adenine dinucleotide (phosphate) (NAD(P)H/NAD(P) + ) ratios, and the levels of various lipogenic and fibrotic markers in the liver were evaluated. The results showed that hepatic fibrosis induced by fructose consumption was associated with weight gain, hunger-satiety system dysregulation, hyperinsulinemia, dyslipidemia, lipoperoxidation and inflammation. Moreover, increased levels of hepatic G6PD and ME activity and expression, the NAD(P)H/NAD(P) + ratios, and GSSG concentration and increased expression of lipogenic and fibrotic markers were detected, and these alterations were attenuated by NAM administration. Specifically, NAM diminished the activity and expression of G6PD and ME, and this effect was associated with a decrease in the NADPH/NADP + ratios, increased GSH levels and decreased lipoperoxidation and inflammation, ameliorating fibrosis and NASH development. NAM reduces liver steatosis and fibrosis by regulating redox homeostasis through a G6PD- and ME-dependent mechanism.

In this work, we overview time-reversal nuclear magnetic resonance (NMR) experiments in many-spin systems evolving under the dipolar Hamiltonian. The Loschmidt echo (LE) in NMR is the signal of excitations which, after evolving with a forward Hamiltonian, is recovered by means of a backward evolution. The presence of non-diagonal terms in the non-equilibrium density matrix of the many-body state is directly monitored experimentally by encoding the multiple quantum coherences. This enables a spin counting procedure, giving information on the spreading of an excitation through the Hilbert space and the formation of clusters of correlated spins. Two samples representing different spin systems with coupled networks were used in the experiments. Protons in polycrystalline ferrocene correspond to an 'infinite' network. By contrast, the liquid crystal N-(4-methoxybenzylidene)-4-butylaniline in the nematic mesophase represents a finite proton system with a hierarchical set of couplings. A close connection was established between the LE decay and the spin counting measurements, confirming the hypothesis that the complexity of the system is driven by the coherent dynamics.