Longitudinal survey of insecticide resistance in a village of central region of Burkina Faso reveals co-occurrence of 1014F, 1014S and 402L mutations in Anopheles coluzzii and Anopheles arabiensis.

BACKGROUND: Pyrethroid resistance is one of the major threats for effectiveness of insecticide-treated bed nets (ITNs) in malaria vector control. Genotyping of mutations in the voltage gated sodium channel (VGSC) gene is widely used to easily assess the evolution and spread of pyrethroid target-site resistance among malaria vectors. L1014F and L1014S substitutions are the most common and best characterized VGSC mutations in major African malaria vector species of the Anopheles gambiae complex. Recently, an additional substitution involved in pyrethroid resistance, i.e. V402L, has been detected in Anopheles coluzzii from West Africa lacking any other resistance alleles at locus 1014. The evolution of target-site resistance mutations L1014F/S and V402L was monitored in An. coluzzii and Anopheles arabiensis specimens from a Burkina Faso village over a 10-year range after the massive ITN scale-up started in 2010. METHODS: Anopheles coluzzii (N = 300) and An. arabiensis (N = 362) specimens collected both indoors and outdoors by different methods (pyrethrum spray catch, sticky resting box and human landing collections) in 2011, 2015 and 2020 at Goden village were genotyped by TaqMan assays and sequencing for the three target site resistance mutations; allele frequencies were statistically investigated over the years. RESULTS: A divergent trend in resistant allele frequencies was observed in the two species: 1014F decreased in An. coluzzii (from 0.76 to 0.52) but increased in An. arabiensis (from 0.18 to 0.70); 1014S occurred only in An. arabiensis and slightly decreased over time (from 0.33 to 0.23); 402L increased in An. coluzzii (from 0.15 to 0.48) and was found for the first time in one An. arabiensis specimen. In 2020 the co-occurrence of different resistance alleles reached 43% in An. coluzzii (alleles 410L and 1014F) and 32% in An. arabiensis (alleles 1014F and 1014S). CONCLUSIONS: Overall, an increasing level of target-site resistance was observed among the populations with only 1% of the two malaria vector species being wild type at both loci, 1014 and 402, in 2020. This, together with the co-occurrence of different mutations in the same specimens, calls for future investigations on the possible synergism between resistance alleles and their phenotype to implement local tailored intervention strategies.

Specific spectral sub-images for machine learning evaluation of optical differences between carbon ion and X ray radiation effects.

Advances in radiotherapy, particularly the exploration of alternative radiation types such as carbon ions have updated our understanding of its effects and applicability on chondrosarcoma cells. Here we compare the optical effects produced by carbon ions (CI) and X-rays (XR) radiations on chondrosarcoma cells nuclei and set an automated method for evaluating the radiation-induced alterations without the need of chemical marking. Hyperspectral images (HSI) of SW1353 chondrosarcoma line carry detectable optical changes of the cells irradiated either with CI or XR compared to non-irradiated ones (REF). The differences between the spectral profiles of CI, XR and REF nuclei classes led to partitioning the HSIs into spectral sub-images. The changes are detected by support vector machine (SVM) classifiers whose performances are evaluated by the most used point metrics: sensitivity (SEN), accuracy (ACC), and precision (PREC), applied on spatial feature values. Specific interaction mechanisms by radiation type reveal distinct subintervals where HSIs changes are more prominent, and the classifiers perform at best. For CI the best classifiers are obtained for sub-images in the interval (424-436 nm), while for XR the best classifiers are obtained for sub-images in the interval (436-445 nm). The classifiers work better with texture features than roughness features in both cases. The classifier with the best SEN point metric in the testing phase is the most suitable to measure the irradiation efficiency irrespective of the radiation type. The altered nuclei are easier to discriminate when irradiated with CI than with XR. The study proves that SVM with optical data offers a rapid, automated, and label-free method for evaluating radiation-induced alterations in chondrosarcoma nuclei, thereby enabling effective analysis of extensive data.

Structural parameters are superior to eigenvector centrality in detecting progressive supranuclear palsy with machine learning & multimodal MRI.

Progressive supranuclear palsy (PSP) is an atypical Parkinsonian syndrome characterized initially by falls and eye movement impairment. This multimodal imaging study aimed at eliciting structural and functional disease-specific brain alterations. T1-weighted and resting-state functional MRI were applied in multi-centric cohorts of PSP and matched healthy controls. Midbrain, cerebellum, and cerebellar peduncles showed severely low gray/white matter volume, whereas thinner cortical gray matter was observed in cingulate cortex, medial and temporal gyri, and insula. Eigenvector centrality analyses revealed regionally specific alterations. Multivariate pattern recognition classified patients correctly based on gray and white matter segmentations with up to 98 % accuracy. Highest accuracies were obtained when restricting feature selection to the midbrain. Eigenvector centrality indices yielded an accuracy around 70 % in this comparison; however, this result did not reach significance. In sum, the study reveals multimodal, widespread brain changes in addition to the well-known midbrain atrophy in PSP. Alterations in brain structure seem to be superior to eigenvector centrality parameters, in particular for prediction with machine learning approaches.

Evaluation of a rapid multi-attribute combinatorial high-throughput UV-Vis/DLS/SLS analytical platform for rAAV quantification and characterization.

Recombinant adeno-associated virus (rAAV)-based gene therapies are expanding in their application. Despite progress in manufacturing, current analytical methods for product quantification and characterization remain largely unchanged. Although critical for product and process development, in-process testing, and batch release, current analytical methods are labor-intensive, costly, and hampered by extended turnaround times and low throughput. The field requires more efficient, cost-effective analytical techniques capable of handling large sample quantities to accelerate product and process development. Here, we evaluated Stunner from Unchained Labs for quantifying and characterizing rAAVs and compared it with established analytical methods. Stunner is a combinatorial analytic technology platform that interpolates ultraviolet-visible (UV-Vis) absorption with static and dynamic light scattering (SLS/DLS) analysis to determine capsid and genomic titer, empty and full capsid ratio, and assess vector size and polydispersity. The platform offers empirical measurements with minimal sample requirements. Upon testing hundreds of rAAV vectors, comprising various serotypes and transgenes, the data show a strong correlation with established analytical methods and exhibit high reproducibility and repeatability. Some analyses can be applied to in-process samples from different purification stages and processes, fulfilling the demand for rapid, high-throughput analysis during development. In sum, the pipeline presented streamlines small- and large-batch analytics.

Unpacking WHO and CDC Bottle Bioassay Methods: A Comprehensive Literature Review and Protocol Analysis Revealing Key Outcome Predictors.

Background: Resistance monitoring is a key element in controlling vector-borne diseases. The World Health Organization (WHO) and Centres for Disease Control and Prevention (CDC) have each developed bottle bioassay methods for determining insecticide susceptibility in mosquito vectors which are used globally. Methods: This study aimed to identify variations in bottle bioassay methodologies and assess the potential impact on the data that is generated. Our approach involved a systematic examination of existing literature and protocols from WHO and CDC, with a focus on the specifics of reported methodologies, variation between versions, and reported outcomes. Building on this, we experimentally evaluated the impact of several variables on bioassay results. Results: Our literature review exposed a significant inconsistency in the how bioassay methods are reported, hindering reliable interpretation of data and the ability to compare results between studies. The experimental research provided further insight by specifically identifying two key factors that influence the outcomes of bioassays: mosquito dry weight and relative humidity (RH). This finding not only advances our comprehension of these assays but also underscores the importance of establishing precisely defined methodologies for resistance monitoring. The study also demonstrates the importance of controlling bioassay variables, noting the significant influence of wing length, as an indicator of mosquito size, on mortality rates in standardized bioassays. Conclusions: Generating data with improved protocol consistency and precision will not only deepen our understanding of resistance patterns but also better inform vector control measures. We call for continued research and collaboration to refine and build consensus on bioassay techniques, to help bolster the global effort against vector-borne diseases like malaria.

Multiview learning with twin parametric margin SVM.

Multiview learning (MVL) seeks to leverage the benefits of diverse perspectives to complement each other, effectively extracting and utilizing the latent information within the dataset. Several twin support vector machine-based MVL (MvTSVM) models have been introduced and demonstrated outstanding performance in various learning tasks. However, MvTSVM-based models face significant challenges in the form of computational complexity due to four matrix inversions, the need to reformulate optimization problems in order to employ kernel-generated surfaces for handling non-linear cases, and the constraint of uniform noise assumption in the training data. Particularly in cases where the data possesses a heteroscedastic error structure, these challenges become even more pronounced. In view of the aforementioned challenges, we propose multiview twin parametric margin support vector machine (MvTPMSVM). MvTPMSVM constructs parametric margin hyperplanes corresponding to both classes, aiming to regulate and manage the impact of the heteroscedastic noise structure existing within the data. The proposed MvTPMSVM model avoids the explicit computation of matrix inversions in the dual formulation, leading to enhanced computational efficiency. We perform an extensive assessment of the MvTPMSVM model using benchmark datasets such as UCI, KEEL, synthetic, and Animals with Attributes (AwA). Our experimental results, coupled with rigorous statistical analyses, confirm the superior generalization capabilities of the proposed MvTPMSVM model compared to the baseline models. The source code of the proposed MvTPMSVM model is available at https://github.com/mtanveer1/MvTPMSVM.

Uridine diphosphate (UDP)-glycosyltransferases (UGTs) are associated with insecticide resistance in the major malaria vectors Anopheles gambiae s.l. and Anopheles funestus.

Malaria remains one of the highest causes of morbidity and mortality, with 249 million cases and over 608,000 deaths in 2022. Insecticides, which target the Anopheles mosquito vector, are the primary method to control malaria. The widespread nature of resistance to the most important insecticide class, the pyrethroids, threatens the control of this disease. To reverse the stall in malaria control there is urgent need for new vector control tools, which necessitates understanding the molecular basis of pyrethroid resistance. In this study we utilised multi-omics data to identify uridine-diphosphate (UDP)-glycosyltransferases (UGTs) potentially involved in resistance across multiple Anopheles species. Phylogenetic analysis identifies sequence similarities between Anopheline UGTs and those involved in agricultural pesticide resistance to pyrethroids, pyrroles and spinosyns. Expression of five UGTs was characterised in An. gambiae and An. coluzzii to determine constitutive over-expression, induction, and tissue specificity. Furthermore, a UGT inhibitor, sulfinpyrazone, restored susceptibility to pyrethroids and DDT in An. gambiae, An. coluzzii, An. arabiensis and An. funestus, the major African malaria vectors. Taken together, this study provides clear association of UGTs with pyrethroid resistance as well as highlighting the potential use of sulfinpyrazone as a novel synergist for vector control.

Machine learning prediction and explanatory models of serious infections in patients with rheumatoid arthritis treated with tofacitinib.

BACKGROUND: Patients with rheumatoid arthritis (RA) have an increased risk of developing serious infections (SIs) vs. individuals without RA; efforts to predict SIs in this patient group are ongoing. We assessed the ability of different machine learning modeling approaches to predict SIs using baseline data from the tofacitinib RA clinical trials program. METHODS: This analysis included data from 19 clinical trials (phase 2, n = 10; phase 3, n = 6; phase 3b/4, n = 3). Patients with RA receiving tofacitinib 5 or 10 mg twice daily (BID) were included in the analysis; patients receiving tofacitinib 11 mg once daily were considered as tofacitinib 5 mg BID. All available patient-level baseline variables were extracted. Statistical and machine learning methods (logistic regression, support vector machines with linear kernel, random forest, extreme gradient boosting trees, and boosted trees) were implemented to assess the association of baseline variables with SI (logistic regression only), and to predict SI using selected baseline variables using 5-fold cross-validation. Missing values were handled individually per prediction model. RESULTS: A total of 8404 patients with RA treated with tofacitinib were eligible for inclusion (15,310 patient-years of total follow-up) of which 473 patients reported SIs. Amongst other baseline factors, age, previous infection, and corticosteroid use were significantly associated with SI. When applying prediction modeling for SI across data from all studies, the area under the receiver operating characteristic (AUROC) curve ranged from 0.656 to 0.739. AUROC values ranged from 0.599 to 0.730 in data from phase 3 and 3b/4 studies, and from 0.563 to 0.643 in data from ORAL Surveillance only. CONCLUSIONS: Baseline factors associated with SIs in the tofacitinib RA clinical trial program were similar to established SI risk factors associated with advanced treatments for RA. Furthermore, while model performance in predicting SI was similar to other published models, this did not meet the threshold for accurate prediction (AUROC > 0.85). Thus, predicting the occurrence of SIs at baseline remains challenging and may be complicated by the changing disease course of RA over time. Inclusion of other patient-associated and healthcare delivery-related factors and harmonization of the duration of studies included in the models may be required to improve prediction. TRIAL REGISTRATION: ClinicalTrials.gov: NCT00147498; NCT00413660; NCT00550446; NCT00603512; NCT00687193; NCT01164579; NCT00976599; NCT01059864; NCT01359150; NCT02147587; NCT00960440; NCT00847613; NCT00814307; NCT00856544; NCT00853385; NCT01039688; NCT02187055; NCT02831855; NCT02092467.

The Combined Delivery of the Vegf, Ang, and Gdnf Genes Stimulates Angiogenesis and Improves Post-Ischemic Innervation and Regeneration in Skeletal Muscle.

In this study, the effects of different combinations of the genes Vegf, Ang, and Gdnf injected both using direct virus-mediated injection (adenovirus, Ad5) and umbilical cord blood mononuclear cells (UCBCs) on the processes of stimulation of post-ischemic innervation, angiogenesis, and regeneration in skeletal muscle were investigated in a rat hindlimb chronic ischemia model. It was shown that more pronounced stimulation of angiogenesis and restoration of post-ischemic innervation were achieved both in the early (28 days post-ischemia, dpi) and late (42 dpi) terms of the experiment in the calf muscle when UCBCs delivered the combination of Ad5-Vegf and Ad5-Ang compared to the direct injection of the same vector combination into the area of ischemia. At the same time, the inclusion of Ad5-Gdnf in the combination of Ad5-Vegf and Ad5-Ang directly injected or administered by UCBCs provided a significant increase in the number of centronuclear muscle fibers, indicating stimulation of post-ischemic reparative myogenesis. This study allowed us to determine the most effective gene combinations for angiogenesis and neurogenesis, which, in the future, may serve as the basis for the development of gene and gene cell products for the treatment of chronic lower limb ischemia.

Monitoring Mosquito Abundance: Comparing an Optical Sensor with a Trapping Method.

Optical sensors have shown significant promise in offering additional data to track insect populations. This article presents a comparative study between abundance measurements obtained from a novel near-infrared optical sensor and physical traps. The optical instrument, named an Entomological Bistatic Optical Sensor System, or eBoss, is a non-destructive sensor operating in the near-infrared spectral range and designed to continuously monitor the population of flying insects. The research compares the mosquito aerial density (#/m3) obtained through the eBoss with trap counts from eight physical traps during an eight-month field study. The eBoss recorded over 302,000 insect sightings and assessed the aerial density of all airborne insects as well as male and female mosquitoes specifically with a resolution of one minute. This capability allows for monitoring population trends throughout the season as well as daily activity peaks. The results affirmed the correlation between the two methods. While optical instruments do not match traps in terms of taxonomic accuracy, the eBoss offered greater temporal resolution (one minute versus roughly three days) and statistical significance owing to its much larger sample size. These outcomes further indicate that entomological optical sensors can provide valuable complementary data to more common methods to monitor flying insect populations, such as mosquitoes or pollinators.

Aedes (Ochlerotatus) scapularis, Aedes japonicus japonicus, and Aedes (Fredwardsius) vittatus (Diptera: Culicidae): Three Neglected Mosquitoes with Potential Global Health Risks.

More than 3550 species of mosquitoes are known worldwide, and only a fraction is involved in the transmission of arboviruses. Mosquitoes in sylvatic and semi-sylvatic habitats may rapidly adapt to urban parks and metropolitan environments, increasing human contact. Many of these mosquitoes have been found naturally infected with arboviruses from the Alphaviridae, Flaviviridae, and Bunyaviridae families, with many being the cause of medically important diseases. However, there is a gap in knowledge about the vector status of newly invasive species and their potential threat to human and domestic animal populations. Due to their rapid distribution, adaptation to urban environments, and anthropophilic habits, some neglected mosquito species may deserve more attention regarding their role as secondary vectors. Taking these factors into account, we focus here on Aedes (Ochlerotatus) scapularis (Rondani), Aedes japonicus japonicus (Theobald), and Aedes (Fredwardsius) vittatus (Bigot) as species that have the potential to become important disease vectors. We further discuss the importance of these neglected mosquitoes and how factors such as urbanization, climate change, and globalization profoundly alter the dynamics of disease transmission and may increase the participation of neglected species in propagating diseases.

Optimized Crop Disease Identification in Bangladesh: A Deep Learning and SVM Hybrid Model for Rice, Potato, and Corn.

Agriculture plays a vital role in Bangladesh's economy. It is essential to ensure the proper growth and health of crops for the development of the agricultural sector. In the context of Bangladesh, crop diseases pose a significant threat to agricultural output and, consequently, food security. This necessitates the timely and precise identification of such diseases to ensure the sustainability of food production. This study focuses on building a hybrid deep learning model for the identification of three specific diseases affecting three major crops: late blight in potatoes, brown spot in rice, and common rust in corn. The proposed model leverages EfficientNetB0's feature extraction capabilities, known for achieving rapid high learning rates, coupled with the classification proficiency of SVMs, a well-established machine learning algorithm. This unified approach streamlines data processing and feature extraction, potentially improving model generalizability across diverse crops and diseases. It also aims to address the challenges of computational efficiency and accuracy that are often encountered in precision agriculture applications. The proposed hybrid model achieved 97.29% accuracy. A comparative analysis with other models, CNN, VGG16, ResNet50, Xception, Mobilenet V2, Autoencoders, Inception v3, and EfficientNetB0 each achieving an accuracy of 86.57%, 83.29%, 68.79%, 94.07%, 90.71%, 87.90%, 94.14%, and 96.14% respectively, demonstrated the superior performance of our proposed model.

The Impact of COVID-19 Vaccination Side-Effects on Work Attendance among Saudi Healthcare Workers.

OBJECTIVE: This cross-sectional-survey-based study aimed to investigate the severity of side-effects from Coronavirus disease (COVID-19) mRNA (Pfizer, Moderna), viral vector DNA (Oxford-AstraZeneca, J&J/Janssen), inactivated virus (Sinopharm, Sinovac), and other vaccines among healthcare workers (HCWs) in Saudi Arabia, focusing on their impact on work attendance. METHODS: A total of 894 HCWs residing in Saudi Arabia participated in this study from March 2023 to May 2023. Participants completed an online questionnaire assessing demographic information, vaccination status, comorbidities, vaccine side-effects, and missed work information after vaccination. Descriptive statistics and chi-square tests were used for data analysis. RESULTS: The majority of participants were female (83.7%) and aged 25-34 years (42.8%). Most participants were predominantly vaccinated with mRNA vaccines. Common side-effects included pain at the injection site, fatigue, fever, and chills. However, no significant association was found between vaccine type, side-effects, and work absenteeism. While demographic factors such as age and healthcare profession did not influence work absenteeism, variations were observed among different racial groups. CONCLUSION: COVID-19 vaccination among HCWs in Saudi Arabia is associated with common side-effects, but their impact on work attendance is not significant. Understanding these implications can inform strategies to support the healthcare workforce and mitigate the impact on patient care and staffing during the ongoing COVID-19 pandemic.

Repurposing Insecticides for Mosquito Control: Evaluating Spiromesifen, a Lipid Synthesis Inhibitor against Aedes aegypti (L.).

The growing resistance of Aedes aegypti (L.) to conventional insecticides presents a major challenge in arbovirus control, necessitating the exploration of alternative insecticidal chemistries. Spiromesifen, derived from spirocyclic tetronic acids, is widely used against agricultural pests and is crucial in resistance management due to its unique lipid synthesis inhibition. This study evaluates the insecticidal activity of spiromesifen against temephos-resistant Ae. aegypti populations, focusing on larval body weight, volume, biochemical composition, and adult female reproductive potential. Spiromesifen demonstrated effective larvicidal activity, significantly reducing adult emergence. Resistance to spiromesifen was not observed, with resistance ratios (RR50, RR90) ranging from 0.36- to 3.31-fold. Larvae exposed to LC50 showed significant reductions in body weight and volume, and reduced carbohydrate, lipid, and protein contents. Enhanced catalase activity and malondialdehyde levels indicated increased oxidative stress and lipid peroxidation, highlighting its effects on lipid metabolism. Spiromesifen also exhibited sterilizing effects, significantly reducing fecundity and fertility in adult females, thereby impacting Ae. aegypti reproductive capacity. These findings highlight the potential of spiromesifen as a component of integrated vector management strategies, especially in regions with prevalent insecticide resistance in Ae. aegypti, serving as an effective larvicide and impacting adult reproductive outcomes.

Powassan Virus Encephalitis after Tick Bite, Manitoba, Canada.

A case of Powassan encephalitis occurred in Manitoba, Canada, after the bite of a black-legged tick. Awareness of this emerging tickborne illness is needed because the number of vector tick species is growing. No specific treatment options exist, and cases with illness and death are high. Prevention is crucial.

A self-complementary AAV proviral plasmid that reduces cross-packaging and ITR promoter activity in AAV vector preparations.

Adeno-associated viral vectors (AAVs) are a leading delivery system for gene therapy in animal models and humans. With several Food and Drug Administration-approved AAV gene therapies on the market, issues related to vector manufacturing have become increasingly important. In this study, we focused on potentially toxic DNA contaminants that can arise from AAV proviral plasmids, the raw materials required for manufacturing recombinant AAV in eukaryotic cells. Typical AAV proviral plasmids are circular DNAs containing a therapeutic gene cassette flanked by natural AAV inverted terminal repeat (ITR) sequences, and a plasmid backbone carrying prokaryotic sequences required for plasmid replication and selection in bacteria. While the majority of AAV particles package the intended therapeutic payload, some capsids instead package the bacterial sequences located on the proviral plasmid backbone. Since ITR sequences also have promoter activity, potentially toxic bacterial open reading frames can be produced in vivo, thereby representing a safety risk. In this study, we describe a new AAV proviral plasmid for vector manufacturing that (1) significantly decreases cross-packaged bacterial sequences, (2) increases correctly packaged AAV payloads, and (3) blunts ITR-driven transcription of cross-packaged material to avoid expressing potentially toxic bacterial sequences. This system may help improve the safety of AAV vector products.

Viral escape mutations do not account for non-protection from SIVmac239 challenge in RhCMV/SIV vaccinated rhesus macaques.

Simian immunodeficiency virus (SIV) vaccines based upon 68-1 Rhesus Cytomegalovirus (RhCMV) vectors show remarkable protection against pathogenic SIVmac239 challenge. Across multiple independent rhesus macaque (RM) challenge studies, nearly 60% of vaccinated RM show early, complete arrest of SIVmac239 replication after effective challenge, whereas the remainder show progressive infection similar to controls. Here, we performed viral sequencing to determine whether the failure to control viral replication in non-protected RMs is associated with the acquisition of viral escape mutations. While low level viral mutations accumulated in all animals by 28 days-post-challenge, which is after the establishment of viral control in protected animals, the dominant circulating virus in virtually all unprotected RMs was nearly identical to the challenge stock, and there was no difference in mutation patterns between this cohort and unvaccinated controls. These data definitively demonstrate that viral mutation does not explain lack of viral control in RMs not protected by RhCMV/SIV vaccination. We further demonstrate that during chronic infection RhCMV/SIV vaccinated RMs do not acquire escape mutation in epitopes targeted by RhCMV/SIV, but instead display mutation in canonical MHC-Ia epitopes similar to unvaccinated RMs. This suggests that after the initial failure of viral control, unconventional T cell responses induced by 68-1 RhCMV/SIV vaccination do not exert strong selective pressure on systemically replicating SIV.

In silico studies of benzothiazole derivatives as potential inhibitors of Anopheles funestus and Anopheles gambiae trehalase.

Introduction: In malaria management, insecticides play a crucial role in targeting disease vectors. Benzothiazole derivatives have also been reported to possess insecticidal properties, among several other properties they exhibit. The female Anopheles mosquito is responsible for transmitting the malaria parasite when infected. Anopheles gambiae (Ag) and Anopheles funestus (Af) are two of the most notable Anopheles species known to spread malaria in Nigeria. Trehalase is an enzyme that breaks down trehalose. Recent research has proposed it as a viable target for inhibition since it aids in flight and stress adaptation. Methods: This study aimed to investigate benzothiazole derivatives as potential inhibitors of trehalase of Anopheles funestus (AfTre) and Anopheles gambiae (AgTre) using toxicity profiling, molecular docking, and dynamic simulation for future insecticidal intervention. A total of 4,214 benzothiazole-based compounds were obtained from the PubChem database and subjected to screening against the 3D modelled structure of AfTre and AgTre. Compounds with some toxicity levels were optimised, and the obtained lead compounds were further investigated through molecular docking studies. Furthermore, the best hit was subjected to parameters such as RMSD, RMSF, SASA, Rg, and hydrogen bond to confirm its stability when in a complex with AfTre, and these parameters were compared to that of validamycin A (control ligand). Results and discussion: The post-screening analysis showed binding affinities of -8.7 and -8.2 kcal/mol (compound 1), -8.2 and -7.4 kcal/mol (compound 2), compared to -6.3 and -5.1 kcal/mol (Validamycin A, a known inhibitor) against AfTre and AgTre, respectively. The molecular dynamics simulation showed that compound 1 (the best hit) had good stability when in complex with AfTre. These findings suggest that these best hits can serve as potential inhibitors for the development of novel insecticides in the control of malaria vectors.

Commercial Enzyme-Linked Immunosorbent Assay Kit Is Useful for Detection of Recombinant and Secretory Nonstructural-1 Protein Antigen of Dengue Virus.

Background: Dengue is a mosquito-borne tropical disease, caused by the Dengue virus (DENV). It has become a severe problem and is a rising threat to public health. In this study, we have evaluated commercial Merilisa i Dengue NS1 Antigen kit (Meril LifeSciences India Pvt. Ltd.) to detect recombinant dengue virus 2 NS1 antigen (rDNS1Ag) and secreted forms of NS1 antigen (sDNS1Ag). Methods: To determine the detection limit of the kit, 100 nanogram (ng) to 0.001 ng rDNS1Ag was tested. The sensitivity and specificity of the kit was determined using recombinant NS1 antigens of all serotypes of DENV and other flaviviruses. For testing sDNS1Ag, the culture supernatant of the Vero cell lines infected with DENV-2 was tested. Further, a spiking experiment was carried out to check the sensitivity of the kit to detect rDNS1Ag in the pools of Aedes aegypti mosquitoes. Results: It was observed that the kit can detect the rDNS1Ag at 1 ng concentration. The kit was sensitive to detect NS1 antigen of DENV-1, DENV-2 and DENV-3 serotypes and specific for detection of only DNS1Ag as it did not cross-react with NS1 antigen of flaviviruses. The kit was sensitive to detect rDNS1Ag in the mosquito pools as well. In addition, the kit was able to detect the sDNS1Ag in Vero cell culture supernatant. Conclusions: Overall, we observed that the Merilisa i Dengue NS1 Ag kit is sensitive and specific for the detection of DNS1Ag both in recombinant and secretory forms.

Quantifying Dendritic Arbors In Vitro and In Vivo in Rodent Models.

Dendritic arborization is a critical determinant of neuronal connectivity. The structure of a neuron's dendritic arbor determines the number of synaptic inputs a neuron can receive and how it processes synaptic input from other neurons. Here, we describe methods for visualizing and quantifying the dendritic arbor in primary cell cultures and in the intact rodent brain. These techniques can be used to answer significant scientific questions, such as the effects of disease processes, drugs, growth factors, and diverse environmental stressors on dendritogenesis in both in vitro and in vivo rodent models.