Human HPSE2 gene transfer ameliorates bladder pathophysiology in a mutant mouse model of urofacial syndrome.

Rare early-onset lower urinary tract disorders include defects of functional maturation of the bladder. Current treatments do not target the primary pathobiology of these diseases. Some have a monogenic basis, such as urofacial, or Ochoa, syndrome (UFS). Here, the bladder does not empty fully because of incomplete relaxation of its outflow tract, and subsequent urosepsis can cause kidney failure. UFS is associated with biallelic variants of HPSE2, encoding heparanase-2. This protein is detected in pelvic ganglia, autonomic relay stations that innervate the bladder and control voiding. Bladder outflow tracts of Hpse2 mutant mice display impaired neurogenic relaxation. We hypothesized that HPSE2 gene transfer soon after birth would ameliorate this defect and explored an adeno-associated viral (AAV) vector-based approach. AAV9/HPSE2, carrying human HPSE2 driven by CAG, was administered intravenously into neonatal mice. In the third postnatal week, transgene transduction and expression were sought, and ex vivo myography was undertaken to measure bladder function. In mice administered AAV9/HPSE2, the viral genome was detected in pelvic ganglia. Human HPSE2 was expressed and heparanase-2 became detectable in pelvic ganglia of treated mutant mice. On autopsy, wild-type mice had empty bladders, whereas bladders were uniformly distended in mutant mice, a defect ameliorated by AAV9/HPSE2 treatment. Therapeutically, AAV9/HPSE2 significantly ameliorated impaired neurogenic relaxation of Hpse2 mutant bladder outflow tracts. Impaired neurogenic contractility of mutant detrusor smooth muscle was also significantly improved. These results constitute first steps towards curing UFS, a clinically devastating genetic disease featuring a bladder autonomic neuropathy.

Development of microsatellite markers for the soft tick Ornithodoros phacochoerus.

BACKGROUND: Soft ticks of the genus Ornithodoros are responsible for the maintenance and transmission of the African swine fever (ASF) virus in the sylvatic and domestic viral cycles in Southern Africa. They are also the main vectors of the Borrelia species causing relapsing fevers. Currently, no genetic markers are available for Afrotropical Ornithodoros ticks. As ASF spreads globally, such markers are needed to assess the role of ticks in the emergence of new outbreaks. The aim of this study is to design microsatellite markers that could be used for ticks of the Ornithodoros moubata complex, particularly Ornithodoros phacochoerus, to assess population structure and tick movements in ASF endemic areas. METHODS: A total of 151 markers were designed using the O. moubata and O. porcinus genomes after elimination of repeated sequences in the genomes. All designed markers were tested on O. phacochoerus and O. porcinus DNA to select the best markers. RESULTS: A total of 24 microsatellite markers were genotyped on two populations of O. phacochoerus and on individuals from four other Ornithodoros species. Nineteen markers were selected to be as robust as possible for population genetic studies on O. phacochoerus. CONCLUSIONS: The microsatellite markers developed here represent the first genetic tool to study nidicolous populations of O. phacochoerus.

Effectiveness of Vaccination Against Tick-Borne Encephalitis in the Czech Republic, 2018-2022.

Background: Tick-borne encephalitis (TBE) is caused by the tick-borne encephalitis virus (TBEV). TBEV infection can cause symptoms of central nervous system (CNS) inflammation and result in severe consequences including death. TBE is an increasing health threat in the Czech Republic and elsewhere in Europe. In 2020, 23% of 3734 TBE cases reported to the European Centre for Disease Prevention and Control were from the Czech Republic. TBE vaccination is universally recommended in the Czech Republic, but a full analysis of TBE vaccine effectiveness (VE) in the Czech Republic has not been published. Methods: TBE is a notifiable disease in the Czech Republic with mandatory reporting of cases (i.e., laboratory-confirmed TBEV infected patient with symptoms of CNS inflammation) and vaccination history to public health authorities. TBE VE was estimated using the screening method utilizing public health surveillance data from 2018 to 2022 and online household surveys of the general population on TBE vaccine uptake conducted in 2019-2022. Results: In 2018-2022, 3648 TBE cases were reported in the Czech Republic; 98.1% (3105/3166) of TBE cases with known vaccination history were unvaccinated. Among 42,671 persons surveyed from the general population who had known TBE vaccination history, 66.5% were unvaccinated. VE against TBE was 97.6% (95% confidence interval 95.7-98.7). When stratified by age group, VE was 97.1% (88.4-99.3) in 1-15 years of age, 97.9% (95.3-99.0) in 16-59 years of age, and 96.9% (90.5-99.0) in ≥60 years of age. TBE vaccination averted an estimated 1020 TBE cases in the Czech Republic from 2018 to 2022. Conclusions: This first published study with a full analysis of TBE VE in the Czech Republic showed that vaccination was highly effective for the prevention of TBE including in children, an age group with increasing TBE disease burden. Vaccination averted hundreds of TBE cases and hospitalizations despite the relatively low compliance with TBE vaccine recommendations. To prevent additional TBE cases in the Czech Republic, enhanced efforts to increase TBE vaccine uptake are needed.

Design and validation of a GMP stem cell manufacturing protocol for MPSII hematopoietic stem cell gene therapy.

Hematopoietic stem cell gene therapy (HSCGT) is a promising therapeutic strategy for the treatment of neurodegenerative, metabolic disorders. The approach involves the ex vivo introduction of a missing gene into patients' own stem cells via lentiviral-mediated transduction (TD). Once transplanted back into a fully conditioned patient, these genetically modified HSCs can repopulate the blood system and produce the functional protein, previously absent or non-functional in the patient, which can then cross-correct other affected cells in somatic organs and the central nervous system. We previously developed an HSCGT approach for the treatment of Mucopolysaccharidosis type II (MPSII) (Hunter syndrome), a debilitating pediatric lysosomal disorder caused by mutations in the iduronate-2-sulphatase (IDS) gene, leading to the accumulation of heparan and dermatan sulfate, which causes severe neurodegeneration, skeletal abnormalities, and cardiorespiratory disease. In HSCGT proof-of-concept studies using lentiviral IDS fused to a brain-targeting peptide ApoEII (IDS.ApoEII), we were able to normalize brain pathology and behavior of MPSII mice. Here we present an optimized and validated good manufacturing practice hematopoietic stem cell TD protocol for MPSII in preparation for first-in-man studies. Inclusion of TEs LentiBOOST and protamine sulfate significantly improved TD efficiency by at least 3-fold without causing adverse toxicity, thereby reducing vector quantity required.

An encoding framework for binarized images using hyperdimensional computing.

Introduction: Hyperdimensional Computing (HDC) is a brain-inspired and lightweight machine learning method. It has received significant attention in the literature as a candidate to be applied in the wearable Internet of Things, near-sensor artificial intelligence applications, and on-device processing. HDC is computationally less complex than traditional deep learning algorithms and typically achieves moderate to good classification performance. A key aspect that determines the performance of HDC is encoding the input data to the hyperdimensional (HD) space. Methods: This article proposes a novel lightweight approach relying only on native HD arithmetic vector operations to encode binarized images that preserves the similarity of patterns at nearby locations by using point of interest selection and local linear mapping. Results: The method reaches an accuracy of 97.92% on the test set for the MNIST data set and 84.62% for the Fashion-MNIST data set. Discussion: These results outperform other studies using native HDC with different encoding approaches and are on par with more complex hybrid HDC models and lightweight binarized neural networks. The proposed encoding approach also demonstrates higher robustness to noise and blur compared to the baseline encoding.

Vector-borne diseases imported to Poland between 2021 and 2023.

Introduction: The aim of the study was to monitor the occurrence of selected vector-borne diseases in anaemic dogs arriving in or returning to Poland from areas endemic for these diseases. Material and Methods: The study involved 497 dogs, of which 184 came to Poland from Ukraine with their owners fleeing the war. Other animals returned to the country from holidays spent in Croatia (n = 96), Turkey (n = 79), Italy (n = 48), Bulgaria (n = 42), Albania (n = 36) and Romania (n = 12). Molecular biology methods were used for detection of pathogens transmitted by the vectors. Results: Molecular tests revealed the presence of vector-borne pathogens in 79 dogs. The most commonly diagnosed infection was caused by Babesia canis (27 dogs), followed by infections with Anaplasma phagocytophilum (in 20 dogs), Mycoplasma haemocanis (15 dogs), Bartonella henselae (7 dogs), Ehrlichia canis (4 dogs), Hepatozoon canis (3 dogs), Babesia gibsoni (2 dogs) and Leishmania infantum (1 dog). Most of the sick dogs (n = 39) came from Ukraine. In dogs spending holidays with their owners outside Poland, vector-borne diseases were most often detected after their return from Turkey (n = 16), and next in descending order from Croatia (n = 7), Italy (n = 6), Albania (n = 4), Bulgaria (n = 4) and Romania (n = 3). Conclusion: The wider migration crisis and increasingly frequent trips of owners with their dogs to areas of endemic infectious and parasitic diseases observed in recent years are the main risk factors for the occurrence of these diseases in Poland. Therefore, constant monitoring of vector-borne diseases, especially in dogs returning from holidays and arriving in Poland from abroad, seems to be crucial for their early detection and introduction of appropriate therapy.

Is Culex modestus a New Usutu virus vector?

Usutu virus is an emerging pathogen transmitted by mosquitoes. Culex modestus mosquitoes are widespread in Europe, but their role in disease transmission is poorly understood. Recent data from a single infectious mosquito suggested that Culex modestus could be an unrecognized vector for Usutu virus. In this study, our aim was to corroborate this finding using a larger sample size. We collected immature Culex modestus from a reedbed pond in Flemish Brabant, Belgium, and reared them in the laboratory until the third generation. Adult females were then experimentally infected with Usutu virus in a blood meal and incubated at 25 °C for 14 days. The presence of Usutu virus in the saliva, head and body of each female was determined by plaque assay and quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR). The transmission efficiency was 54% (n = 15/28), confirming that Belgian Culex modestus can experimentally transmit Usutu virus.

Slow recovery rates and spatial aggregation of Triatoma infestans populations in an area with high pyrethroid resistance in the Argentine Chaco.

BACKGROUND: The emergence of pyrethroid resistance has threatened the elimination of Triatoma infestans from the Gran Chaco ecoregion. We investigated the status and spatial distribution of house infestation with T. infestans and its main determinants in Castelli, a municipality of the Argentine Chaco with record levels of triatomine pyrethroid resistance, persistent infestation over 2005-2014, and limited or no control actions over 2015-2020. METHODS: We conducted a 2-year longitudinal survey to assess triatomine infestation by timed manual searches in a well-defined rural section of Castelli including 14 villages and 234 inhabited houses in 2018 (baseline) and 2020, collected housing and sociodemographic data by on-site inspection and a tailored questionnaire, and synthetized these data into three indices generated by multiple correspondence analysis. RESULTS: The overall prevalence of house infestation in 2018 (33.8%) and 2020 (31.6%) virtually matched the historical estimates for the period 2005-2014 (33.7%) under recurrent pyrethroid sprays. While mean peridomestic infestation remained the same (26.4-26.7%) between 2018 and 2020, domestic infestation slightly decreased from 12.2 to 8.3%. Key triatomine habitats were storerooms, domiciles, kitchens, and structures occupied by chickens. Local spatial analysis showed significant aggregation of infestation and bug abundance in five villages, four of which had very high pyrethroid resistance approximately over 2010-2013, suggesting persistent infestations over space-time. House bug abundance within the hotspots consistently exceeded the estimates recorded in other villages. Multiple regression analysis revealed that the presence and relative abundance of T. infestans in domiciles were strongly and negatively associated with indices for household preventive practices (pesticide use) and housing quality. Questionnaire-derived information showed extensive use of pyrethroids associated with livestock raising and concomitant spillover treatment of dogs and (peri) domestic premises. CONCLUSIONS: Triatoma infestans populations in an area with high pyrethroid resistance showed slow recovery and propagation rates despite limited or marginal control actions over a 5-year period. Consistent with these patterns, independent experiments confirmed the lower fitness of pyrethroid-resistant triatomines in Castelli compared with susceptible conspecifics. Targeting hotspots and pyrethroid-resistant foci with appropriate house modification measures and judicious application of alternative insecticides with adequate toxicity profiles are needed to suppress resistant triatomine populations and prevent their eventual regional spread.

Identifying responders to vagus nerve stimulation based on microstructural features of thalamocortical tracts in drug-resistant epilepsy.

The mechanisms of action of Vagus Nerve Stimulation (VNS) and the biological prerequisites to respond to the treatment are currently under investigation. It is hypothesized that thalamocortical tracts play a central role in the antiseizure effects of VNS by disrupting the genesis of pathological activity in the brain. This pilot study explored whether in vivo microstructural features of thalamocortical tracts may differentiate Drug-Resistant Epilepsy (DRE) patients responding and not responding to VNS treatment. Eighteen patients with DRE (37.11 â€‹± â€‹10.13 years, 10 females), including 11 responders or partial responders and 7 non-responders to VNS, were recruited for this high-gradient multi-shell diffusion Magnetic Resonance Imaging (MRI) study. Using Diffusion Tensor Imaging (DTI) and multi-compartment models - Neurite Orientation Dispersion and Density Imaging (NODDI) and Microstructure Fingerprinting (MF), we extracted microstructural features in 12 subsegments of thalamocortical tracts. These characteristics were compared between responders/partial responders and non-responders. Subsequently, a Support Vector Machine (SVM) classifier was built, incorporating microstructural features and 12 clinical covariates (including age, sex, duration of VNS therapy, number of antiseizure medications, benzodiazepine intake, epilepsy duration, epilepsy onset age, epilepsy type - focal or generalized, presence of an epileptic syndrome - no syndrome or Lennox-Gastaut syndrome, etiology of epilepsy - structural, genetic, viral, or unknown, history of brain surgery, and presence of a brain lesion detected on structural MRI images). Multiple diffusion metrics consistently demonstrated significantly higher white matter fiber integrity in patients with a better response to VNS (pFDR < 0.05) in different subsegments of thalamocortical tracts. The SVM model achieved a classification accuracy of 94.12%. The inclusion of clinical covariates did not improve the classification performance. The results suggest that the structural integrity of thalamocortical tracts may be linked to therapeutic effectiveness of VNS. This study reveals the great potential of diffusion MRI in improving our understanding of the biological factors associated with the response to VNS therapy.

Temporal trend and driving effect of demographic transitions on embedded carbon emissions of Chinese households.

A population is regarded as the main non-economic driver of carbon emissions, causing the climatic crisis, especially in China experiencing a dramatic demographic transition. In contrast to aging, low fertility, the most remarkable feature of the Chinese population transition, has always been ignored when evaluating carbon emissions, due to the lack of long-run data. To narrow this gap, an integrated framework combining the continuous input-output tables from 1997 to 2018 with the Mann-Kendall test and vector auto-regression was presented to clarify the fluctuating trend of household embedded carbon emissions and the driving pattern of low fertility, aging, and urbanization. Our main findings showed that changes in household embedded carbon emissions have increased sharply in the last two decades. The growth of Chinese household embedded carbon emissions began to accelerate in 2001, which lagged 1 year behind the demographic indicators. Low fertility has a positive impact on households' embedded carbon emissions. More importantly, the impact of low fertility is more significant and far-reaching than that of aging. These suggest that aggressive policies for stimulating fertility and low-carbon lifestyles should be considered by policy makers.

Potential climate change effects on the distribution of urban and sylvatic dengue and yellow fever vectors.

Climate change may increase the risk of dengue and yellow fever transmission by urban and sylvatic mosquito vectors. Previous research primarily focused on Aedes aegypti and Aedes albopictus. However, dengue and yellow fever have a complex transmission cycle involving sylvatic vectors. Our aim was to analyze how the distribution of areas favorable to both urban and sylvatic vectors could be modified as a consequence of climate change. We projected, to future scenarios, baseline distribution models already published for these vectors based on the favorability function, and mapped the areas where mosquitoes' favorability could increase, decrease or remain stable in the near (2041-2060) and distant (2061-2080) future. Favorable areas for the presence of dengue and yellow fever vectors show little differences in the future compared to the baseline models, with changes being perceptible only at regional scales. The model projections predict dengue vectors expanding in West and Central Africa and in South-East Asia, reaching Borneo. Yellow fever vectors could spread in West and Central Africa and in the Amazon. In some locations of Europe, the models suggest a reestablishment of Ae. aegypti, while Ae. albopictus will continue to find new favorable areas. The results underline the need to focus more on vectors Ae. vittatus, Ae. luteocephalus and Ae. africanus in West and Central sub-Saharan Africa, especially Cameroon, Central Africa Republic, and northern Democratic Republic of Congo; and underscore the importance of enhancing entomological monitoring in areas where populations of often overlooked vectors may thrive as a result of climate changes.

Seasonal Variability and Stochastic Branching Process in Malaria Outbreak Probability.

BACKGROUND: Malaria is the world's most fatal and challenging parasitic disease, caused by the Plasmodium parasite, which is transmitted to humans by the bites of infected female mosquitoes. Bangladesh is the most vulnerable region to spread malaria because of its geographic position. In this paper, we have considered the dynamics of vector-host models and observed the stochastic behavior. This study elaborates on the seasonal variability and calculates the probability of disease outbreaks. METHODS: We present a model for malaria disease transmission and develop its corresponding continuous-time Markov chain (CTMC) representation. The proposed vector-host models illustrate the malaria transmission model along with sensitivity analysis. The deterministic model with CTMC curves is depicted to show the randomness in real scenarios. Sequentially, we expand these studies to a time-varying stochastic vector-host model that incorporates seasonal variability. Phase plane analysis is conducted to explore the characteristics of the disease, examine interactions among various compartments, and evaluate the impact of key parameters. The branching process approximation is developed for the corresponding vector-host model to calculate the probability outbreak. Numerous numerical results are accomplished to observe the analytical investigation. RESULTS: Seasonality and contact patterns affect the dynamics of disease outbreaks. The numerical illustration provides that the probability of a disease outbreak depends on the infected host or vector. Additionally, periodic transmission rates have a great influence on the probability outbreak. The basic reproduction number (R0) is derived, which is the main justification for studying the dynamical behavior of epidemic models. CONCLUSIONS: Seasonal variability significantly impacts malaria transmission, and the probability of disease outbreaks is influenced by time and the initial number of infected individuals. Moreover, the branching process approximation is applicable when the population size is large enough and the basic reproduction number is less than 1. In the future, such analysis can help decision-makers understand the impact of various parameters and their stochastic behavior in the vector-host model to prevent such types of disease outbreaks.

Forecasting deep learning-based risk assessment of vector-borne diseases using hybrid methodology.

BACKGROUND: Dengue fever is rapidly becoming Malaysia's most pressing health concern, as the reported cases have nearly doubled over the past decade. Without efficacious antiviral medications, vector control remains the primary strategy for battling dengue, while the recently introduced tetravalent immunization is being evaluated. The most significant and dangerous risk increasing recently is vector-borne illnesses. These illnesses induce significant human sickness and are transmitted by blood-feeding arthropods such as fleas, parasites, and mosquitos. A thorough grasp of various factors is necessary to improve prediction accuracy and typically generate inaccurate and unstable predictions, as well as machine learning (ML) models, weather-driven mechanisms, and numerical time series. OBJECTIVE: In this research, we propose a novel method for forecasting vector-borne disease risk using Radial Basis Function Networks (RBFNs) and the Darts Game Optimizer (DGO) algorithm. METHODS: The proposed approach entails training the RBFNs with historical disease data and enhancing their parameters with the DGO algorithm. To prepare the RBFNs, we used a massive dataset of vector-borne disease incidences, climate variables, and geographical data. The DGO algorithm proficiently searches the RBFN parameter space, fine-tuning the model's architecture to increase forecast accuracy. RESULTS: RBFN-DGO provides a potential method for predicting vector-borne disease risk. This study advances predictive demonstrating in public health by shedding light on effectively controlling vector-borne diseases to protect human populations. We conducted extensive testing to evaluate the performance of the proposed method to standard optimization methods and alternative forecasting methods. CONCLUSION: According to the findings, the RBFN-DGO model beats others in terms of accuracy and robustness in predicting the likelihood of vector-borne illness occurrences.

Using continuous relative phase and modified vector coding analyses to quantify spinal coordination and coordinative variability for healthy and chronic low back pain patients: An exploratory comparative analysis.

Differences in coordination and coordinative variability are common in people with low back pain. While differences may relate to the different analyses used to quantify these metrics, the preferred approach remains unclear. We aimed to compare coordination and coordinative variability, in people with and without low back pain performing a lifting/lowering task, using continuous relative phase and vector coding procedures, and to identify which technique better detects group differences. Upper lumbar (T12-L3), lower lumbar (L3-S1), and hip angular kinematics were measured using electromagnetic motion capture during 10 crate lifting/lowering repetitions from adults with (n = 47) and without (n = 17) low back pain. Coordination and coordinative variability for the Hip-Lower Lumbar and Lower Lumbar-Upper Lumbar joint pairs were quantified using mean absolute relative phase and deviation phase (continuous relative phase), and coupling angle and coupling angle variability (vector coding), respectively. T-tests examined group differences in coordination and variability. Cohen's d bootstrapping analyses identified the more sensitive technique for detecting group differences. Less in-phase and more variable behavior was observed in the low back pain group, mostly independent of joint pair and analytical technique (P < 0.05, Cohen's d range = 0.61 to 1.33). Qualitatively, the low back group limited motion at the lower lumbar spine during lifting/lowering. Continuous relative phase was more sensitive in detecting group differences in coordinative variability, while vector coding was more sensitive towards differences in coordination. These procedures convey distinct information and have their respective merits. Researchers should consider the choice of analytical techniques based on their study objectives.

Machine learning models and performance dependency on 2D chemical descriptor space for retention time prediction of pharmaceuticals.

The predictive modeling of liquid chromatography methods can be an invaluable asset, potentially saving countless hours of labor while also reducing solvent consumption and waste. Tasks such as physicochemical screening and preliminary method screening systems where large amounts of chromatography data are collected from fast and routine operations are particularly well suited for both leveraging large datasets and benefiting from predictive models. Therefore, the generation of predictive models for retention time is an active area of development. However, for these predictive models to gain acceptance, researchers first must have confidence in model performance and the computational cost of building them should be minimal. In this study, a simple and cost-effective workflow for the development of machine learning models to predict retention time using only Molecular Operating Environment 2D descriptors as input for support vector regression is developed. Furthermore, we investigated the relative performance of models based on molecular descriptor space by utilizing uniform manifold approximation and projection and clustering with Gaussian mixture models to identify chemically distinct clusters. Results outlined herein demonstrate that local models trained on clusters in chemical space perform equivalently when compared to models trained on all data. Through 10-fold cross-validation on a comprehensive set containing 67,950 of our company's proprietary analytes, these models achieved coefficients of determination of 0.84 and 3 % error in terms of retention time. This promising statistical significance is found to translate from cross-validation to prospective prediction on an external test set of pharmaceutically relevant analytes. The observed equivalency of global and local modeling of large datasets is retained with METLIN's SMRT dataset, thereby confirming the wider applicability of the developed machine learning workflows for global models.

Leveraging VQ-VAE tokenization for autoregressive modeling of medical time series.

In this work, we present CodeAR, a medical time series generative model for electronic health record (EHR) synthesis. CodeAR employs autoregressive modeling on discrete tokens obtained using a vector quantized-variational autoencoder (VQ-VAE), which addresses key challenges of accurate distribution modeling and patient privacy preservation in the medical domain. The proposed model is trained with next-token prediction instead of a regression problem for more accurate distribution modeling, where the autoregressive property of CodeAR is useful to capture the inherent causality in time series data. In addition, the compressive property of the VQ-VAE prevents CodeAR from memorizing the original training data, which ensures patient privacy. Experimental results demonstrate that CodeAR outperforms the baseline autoregressive-based and GAN-based models in terms of maximum mean discrepancy (MMD) and Train on Synthetic, Test on Real tests. Our results highlight the effectiveness of autoregressive modeling on discrete tokens, the utility of CodeAR in causal modeling, and its robustness against data memorization.

Viral-vectored boosting of OmcB or CPAF-specific T cell responses fail to enhance protection from Chlamydia muridarum in infection immune mice and elicits a non-protective CD8-dominant response in naïve mice.

A vaccine is needed to combat the Chlamydia epidemic. Replication-deficient viral vectors are safe and induce antigen-specific T cell memory. We tested the ability of intramuscular immunization with modified vaccinia virus Ankara (MVA) or Chimpanzee Adenovirus (ChAd) expressing chlamydial outer membrane protein, OmcB, or the secreted protein, CPAF, to enhance T cell immunity and protection in mice previously infected with plasmid-deficient Chlamydia muridarum CM972, and to elicit protection in naïve mice. MVA.OmcB or MVA.CPAF increased antigen-specific T cells in CM972-immune mice ∼150 and 50-fold respectively but failed to improve bacterial clearance. ChAd.OmcB/MVA.OmcB prime-boost immunization of naïve mice elicited a CD8-dominant T cell response that failed to protect. ChAd.CPAF/ChAd.CPAF prime-boost also induced a CD8-dominant response with a marginal reduction in burden. Challenge of ChAd.CPAF-immunized mice genetically deficient in CD4 or CD8 T cells showed that protection was entirely CD4-dependent. CD4-deficient mice had prolonged infection, while CD8-deficient mice had higher frequencies of CPAF-specific CD4 T cells, earlier clearance, and reduced burden compared to wild-type controls. These data reinforce the essential nature of the CD4 T cell response in protection from chlamydial genital infection in mice and the need for vaccine platforms that drive CD4-dominant responses.

Contextual factors related to vector-control interventions for malaria: a scoping review and evidence and gap map protocol.

Objective: This scoping review will identify existing literature regarding contextual factors relevant to vector-control interventions to prevent malaria. We will use the findings of the scoping review to produce an interactive evidence and gap map. The map will assist in the priority setting, development, and conduct of targeted systematic reviews. These systematic reviews seek to assist the Vector Control and Insecticide Resistance Unit of the World Health Organization's Global Malaria Programme by informing recommendation development by their Guidelines Development Group. Introduction: Malaria contributes substantially to the global burden of disease, with an estimated 247 million cases and 619,000 deaths in 2021. Vector-control is key in reducing malaria transmission. Vector-control interventions directly target the mosquito, reducing the potential for parasite infections. These interventions commonly include insecticides used in indoor residual spraying or insecticide-treated nets and larval source management. Several new vector-control interventions are under evaluation to complement these. In addition to estimating the effects of interventions on health outcomes, it is critical to understand how populations at risk of malaria consider them in terms of their feasibility, acceptability, and values. Inclusion Criteria: Eligible studies will have assessed the contextual factors of feasibility or acceptability of the interventions of interest, or the valuation of the outcomes of interests. These assessments will be from the perspective of people who receive (residents) or deliver (workers or technicians) the vector-control intervention for the purpose of preventing malaria. Methods: We will conduct this scoping review in accordance with the JBI methodology for scoping reviews and report in line with the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews (PRISMA-ScR). We will construct the evidence and gap map following guidance from the Campbell Collaboration.

Reciprocal interactions between neuropeptide F and RYamide regulate host attraction in the mosquito Aedes aegypti.

Female mosquitoes produce eggs in gonadotrophic cycles that are divided between a previtellogenic and vitellogenic phase. Previtellogenic females consume water and sugar sources like nectar while also being attracted to hosts for blood feeding. Consumption of a blood meal activates the vitellogenic phase, which produces mature eggs and suppresses host attraction. In this study, we tested the hypothesis that neuropeptide Y-like hormones differentially modulate host attraction behavior in the mosquito Aedes aegypti. A series of experiments collectively indicated that enteroendocrine cells (EECs) in the posterior midgut produce and release neuropeptide F (NPF) into the hemolymph during the previtellogenic phase which stimulates attraction to humans and biting behavior. Consumption of a blood meal, which primarily consists of protein by dry weight, down-regulated NPF in EECs until mature eggs developed, which was associated with a decline in hemolymph titer. NPF depletion depended on protein digestion but was not associated with EEC loss. Other experiments showed that neurons in the terminal ganglion extend axons to the posterior midgut and produce RYamide, which showed evidence of increased secretion into circulation after a blood meal. Injection of RYamide-1 and -2 into previtellogenic females suppressed host attraction, while coinjection of RYamides with or without short NPF-2 also inhibited the host attraction activity of NPF. Overall, our results identify NPF and RYamide as gut-associated hormones in A. aegypti that link host attraction behavior to shifts in diet during sequential gonadotrophic cycles.

TOPO Cloning for Efficient Plasmid Construction.

This chapter outlines the use of TOPO cloning for streamlined generation of a recombinant plasmid containing your gene of interest for use in the Bac-to-Bac™ Baculovirus Expression System.