Health-seeking behaviour and its determinants of health of Under-5 Children living in urban slums of Chennai, India 2018.

Background: Appropriate health-seeking behaviour could help in reducing child mortality and morbidity. Information on social factors of mortality and health-seeking behaviours of caregivers of under-5 children from slums of Indian cities is minimal in literature. Objectives: We estimated the prevalence of health-seeking behaviour for morbidity ofunder-5 children and its determinants in urban slums in Chennai city, India. Methods: A cross-sectional study was conducted using a mixed-method design among primary caregivers of under-5 children living in Chennai slums, India. Two-stage cluster sampling was adopted to select 40 slums. A total of 233 primary caregivers were interviewed. Nine focus group discussions and 18 in-depth interviews were conducted among the primary caregivers. Prevalence of inappropriate health-seeking behaviour was estimated, and determinants were identified by multivariate binary logistic regression analysis. Thematic analysis was done on qualitative data. Results: We interviewed 233 primary caregivers. The weighted prevalence of inappropriate health-seeking behaviour for under-five children in urban slums of Chennai was 53.9% (95% CI: 46.9 - 60.8). Primary caregivers educated above secondary school were more likely (AOR of 2.3, 95% CI: 1.3-4.1) to follow inappropriate health-seeking behaviour compared to those educated below. Similarly, caregivers who were unaware of young child feeding practices (AOR of 3.6, 95% CI: 1.9-6.5) and early care-seeking and health practices (AOR of 2.5, 95% CI: 1.3-4.9) were more likely to engage in inappropriate health-seeking behaviour compared to those who were aware and we found that illness symptoms influenced health-seeking behaviour and that early disease detection might prevent severe illness. Conclusion: Health-seeking behaviour was found to be suboptimal among under-5 children in Chennai's urban slums. We suggest policymakers improve interventions on early care-seeking of common childhood illnesses in the urban health programme.

Impact of COVID-19 lockdown on the particulate matter over Perungudi, Chennai, India.

The nationwide lockdown of Phase-1 in India was started from March 25 to April 14, 2020 and Phase-2 from April 15 to May 3, 2020 with severe restrictions on public activities in India. Utilizing the particulate matter PM10 and PM2.5 data recorded during this adverse time, the present study is undertaken to assess the impact of phase 1 and 2 lockdown on the air quality of Perungudi, Chennai, India. The data obtained from the Tamil Nadu Pollution Control Board was assessed for lockdown phase. We compared particulate matter data for the unlock phase with a coinciding period in March 2020 to determine the changes in pollutant concentrations during the lockdown period of April 2020. The descriptive analysis of PM continuous data was performed to determine the mean, standard deviation, variance, skew and kurtosis to identify the nature of data. Correlogram analysis gives the information that the data under study has non-stationary behaviour and not random. Along with this linear regression analysis were performed to determine the relationship and trend for the data. The results revealed decreasing trend in the concentrations (PM10, PM2.5).

Modification of sesame (Sesamum indicum L.) for Triacylglycerol accumulation in plant biomass for biofuel applications.

Sesame is considered as the queen of oil seeds owing to its high oil content of about 56-62% and good quality oil. Sesame oil alone or in combination with other vegetable oils can yield good quality biodiesel. Sesame biodiesel blends up to 20% yields fuel efficiency and power output on par with mineral diesel but superior in environmental performance. Though biodiesel from edible oil is highly criticized, the demand for renewable energy compels the development of high-performance sesame plants. Triacylglycerol synthesis in flowering plants follows an acyl CoA-dependent and independent manner. This study envisages transgenic approaches to enhance oil production in sesame biomass. The genes of choice for oil enhancement includes DGAT1, PDAT1, FAD3 and cytochrome b5F. Diacylglycerol acyltransferase (DGAT) and phospholipid diacylglycerol acyltransferases (PDAT) are key enzymes in TAG synthesis. Fatty acid desaturases (FAD) has the ability to enhance specific fatty acids, whereas cytochrome b5 genes augment the process by donating electrons. A combination of the above categories of genes which performed well in terms of oil content in the yeast expression system from our earlier studies is used in Agrobacterium-mediated sesame transformation experiments to evaluate the biodiesel potential of transgenic sesame plants. The transgenic construct with PDAT1 and FAD3 combination yielded a 10% increase in TAG content. The possibility of transgenic sesame as a biodiesel plant is discussed.

Secondary Observer System for Detection of Microaneurysms in Fundus Images Using Texture Descriptors.

The increase of diabetic retinopathy patients and diabetic mellitus worldwide yields lot of challenges to ophthalmologists in the screening of diabetic retinopathy. Different signs of diabetic retinopathy were identified in retinal images taken through fundus photography. Among these stages, the early stage of diabetic retinopathy termed as microaneurysms plays a vital role in diabetic retinopathy patients. To assist the ophthalmologists, and to avoid vision loss among diabetic retinopathy patients, a computer-aided diagnosis is essential that can be used as a second opinion while screening diabetic retinopathy. On this vision, a new methodology is proposed to detect the microaneurysms and non-microaneurysms through the stages of image pre-processing, candidate extraction, feature extraction, and classification. The feature extractor, generalized rotational invariant local binary pattern, contributes in extracting the texture-based features of microaneurysms. As a result, our proposed system achieved a free-response receiver operating characteristic score of 0.421 with Retinopathy Online Challenge database.

A genome-scale metabolic network of the aroma bacterium Leuconostoc mesenteroides subsp. cremoris.

Leuconostoc mesenteroides subsp. cremoris is an obligate heterolactic fermentative lactic acid bacterium that is mostly used in industrial dairy fermentations. The phosphoketolase pathway (PKP) is a unique feature of the obligate heterolactic fermentation, which leads to the production of lactate, ethanol, and/or acetate, and the final product profile of PKP highly depends on the energetics and redox state of the organism. Another characteristic of the L. mesenteroides subsp. cremoris is the production of aroma compounds in dairy fermentation, such as in cheese production, through the utilization of citrate. Considering its importance in dairy fermentation, a detailed metabolic characterization of the organism is necessary for its more efficient use in the industry. To this aim, a genome-scale metabolic model of dairy-origin L. mesenteroides subsp. cremoris ATCC 19254 (iLM.c559) was reconstructed to explain the energetics and redox state mechanisms of the organism in full detail. The model includes 559 genes governing 1088 reactions between 1129 metabolites, and the reactions cover citrate utilization and citrate-related flavor metabolism. The model was validated by simulating co-metabolism of glucose and citrate and comparing the in silico results to our experimental results. Model simulations further showed that, in co-metabolism of citrate and glucose, no flavor compounds were produced when citrate could stimulate the formation of biomass. Significant amounts of flavor metabolites (e.g., diacetyl and acetoin) were only produced when citrate could not enhance growth, which suggests that flavor formation only occurs under carbon and ATP excess. The effects of aerobic conditions and different carbon sources on product profiles and growth were also investigated using the reconstructed model. The analyses provided further insights for the growth stimulation and flavor formation mechanisms of the organism.

Unveiling novel 2-cyclopropyl-3-ethynyl-4-(4-fluorophenyl)quinolines as GPCR ligands via PI3-kinase/PAR-1 antagonism and platelet aggregation valuations; development of a new class of anticancer drugs with thrombolytic effects.

In the present study, novel 2-cyclopropyl-3-ethynyl-4-(4-fluorophenyl) quinolines (4a-l) were recognized and evaluated as G-Protein Coupled Receptor (GPCR) ligands through molecular evaluations. Thrombin mediates adhesion of mast cell, a type of cell abundantly found in connective tissue and releasing histamine and other substances during inflammatory and allergic reactions, through phosphoinositol 3-kinase pathway. With this background, as preliminary, 4a-l are resolute to be potential leads, designated from their effective phosphoinositol 3-kinase (PI3-Kinase) inhibition potentials, best-docked scores, comparative ligand efficiency, and significant structural attributes evaluated by ab initio simulations. Since thrombin is one of the main reason for various cancer invasion in association with PI3Kinase, a thrombolytic potential of the compounds also analyzed. The experimental in vitro studies confirmed the significant enhancement as PI3Kinase inhibitors and appreciable enhancement in MTT assay of breast and skin cancer cell lines. Significantly, acetophenone substituent in the quinoline scaffold could be coherent to note the significant binding affinity to all the evaluated drug targets.

Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach.

Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes.

Bioprospecting of gum kondagogu (Cochlospermum gossypium) for bioremediation of uranium (VI) from aqueous solution and synthetic nuclear power reactor effluents.

An ecofriendly green chemistry method using a natural biopolymer, Gum Kondagogu (GK) for the removal of U (VI) from aqueous, simulated nuclear effluents was studied. The adsorption characteristic of GK towards U (VI) from aqueous solution was studied at varied pH, contact time, adsorbent dose, initial U (VI) concentration and temperature using UV-Visible spectroscopy and ICP-MS. Maximum adsorption was seen at pH 4, 0.1% GK with 60 min contact time at room temperature. The GK- U (VI) composite was characterized by FT-IR, zeta potential, TEM and SEM-EDAX. The Langmuir isotherm was found to be 487 mg of U (VI) g(-1) of GK. The adsorption capacity and (%) of U (VI) was found to be 490 ± 5.4 mg g(-1) and 98.5%. Moreover adsorption of U (VI) by GK was not influenced by other cations present in the simulated effluents. The adsorbed U (VI) was efficiently stripped from composite using 1 M HCl.

Efficient Scheduling of Scientific Workflows with Energy Reduction Using Novel Discrete Particle Swarm Optimization and Dynamic Voltage Scaling for Computational Grids.

One of the most significant and the topmost parameters in the real world computing environment is energy. Minimizing energy imposes benefits like reduction in power consumption, decrease in cooling rates of the computing processors, provision of a green environment, and so forth. In fact, computation time and energy are directly proportional to each other and the minimization of computation time may yield a cost effective energy consumption. Proficient scheduling of Bag-of-Tasks in the grid environment ravages in minimum computation time. In this paper, a novel discrete particle swarm optimization (DPSO) algorithm based on the particle's best position (pbDPSO) and global best position (gbDPSO) is adopted to find the global optimal solution for higher dimensions. This novel DPSO yields better schedule with minimum computation time compared to Earliest Deadline First (EDF) and First Come First Serve (FCFS) algorithms which comparably reduces energy. Other scheduling parameters, such as job completion ratio and lateness, are also calculated and compared with EDF and FCFS. An energy improvement of up to 28% was obtained when Makespan Conservative Energy Reduction (MCER) and Dynamic Voltage Scaling (DVS) were used in the proposed DPSO algorithm.

Evaluation of antimicrobial efficacy of Triphala (an Indian Ayurvedic herbal formulation) and 0.2% chlorhexidine against Streptococcus mutans biofilm formed on tooth substrate: an in vitro study.

BACKGROUND: Streptococcus mutans is one of the most important cariogenic species of the human oral microbial flora. Biofilm style of microbial growth thought to resist the actions of antimicrobials. AIM: The purpose of this study was to evaluate the antimicrobial efficacy of Triphala, and 0.2% chlorhexidine against S. mutans biofilm formed on tooth substrate. SETTINGS AND DESIGN: Randomized control trial. METHODS: Extracted human mandibular premolars sectioned below the cemento-enamel junction were placed in the tissue culture wells exposing the crown surface to S. mutans to form a biofilm. At the end of 3 rd and 7 th day, all groups were treated for 10 min with the test solutions and control and were analyzed qualitatively and quantitatively. STATISTICAL ANALYSIS USED: One-way ANOVA. RESULTS: Qualitative assay with 3 days biofilm showed complete inhibition of bacterial growth with Triphala, but 0.2% chlorhexidine and saline showed the presence of bacterial growth. In quantitative analysis, 0.2% chlorhexidine and Saline treated tooth samples have shown 1052 Χ 10(4) ± 15.1 Χ 10(4) CFU/ml, 141.3 Χ 10(9) ± 2.1Χ10(9) CFU/ml, respectively. Qualitative assay with 7 days biofilm on crown portion showed dense growth when treated with 0.2% chlorhexidine and saline, whereas Triphala has shown minimal growth. In Quantitative analysis, Triphala showed statistically significant result when compared with 0.2% chlorhexidine and saline. CONCLUSION: Triphala showed statistically significant antibacterial activity against S. mutans biofilm formed on tooth substrate. The incorporation of Triphala in mouth rinse could prove to be effective in reducing S. mutans count in the oral cavity.

Computer-aided detection of breast cancer on mammograms: a swarm intelligence optimized wavelet neural network approach.

Breast cancer is the second leading cause of cancer death in women. Accurate early detection can effectively reduce the mortality rate caused by breast cancer. Masses and microcalcification clusters are an important early signs of breast cancer. However, it is often difficult to distinguish abnormalities from normal breast tissues because of their subtle appearance and ambiguous margins. Computer aided diagnosis (CAD) helps the radiologist in detecting the abnormalities in an efficient way. This paper investigates a new classification approach for detection of breast abnormalities in digital mammograms using Particle Swarm Optimized Wavelet Neural Network (PSOWNN). The proposed abnormality detection algorithm is based on extracting Laws Texture Energy Measures from the mammograms and classifying the suspicious regions by applying a pattern classifier. The method is applied to real clinical database of 216 mammograms collected from mammogram screening centers. The detection performance of the CAD system is analyzed using Receiver Operating Characteristic (ROC) curve. This curve indicates the trade-offs between sensitivity and specificity that is available from a diagnostic system, and thus describes the inherent discrimination capacity of the proposed system. The result shows that the area under the ROC curve of the proposed algorithm is 0.96853 with a sensitivity 94.167% of and specificity of 92.105%.

Mating compatibility and competitiveness of transgenic and wild type Aedes aegypti (L.) under contained semi-field conditions.

We conducted the world's first experiments under semi-field conditions (ACL-2 field house) to assess the mating competitiveness of genetically sterile RIDL male mosquitoes (513A strain). The field house is a state-of-the-art, fully-contained trial facility, simulating the living space for a household of 2-4 people in Peninsular Malaysia. Ten genetically sterile RIDL male A. aegypti mosquitoes competed with ten wild type males inside this field house to mate with ten wild type females. Hatched larvae from mated females were screened under a fluorescent microscope for genetic markers to determine if they were fathered by RIDL male or wild type male, and all results were cross-checked by PCR. Two such experiments were conducted, each repeated sufficient number of times. All strains were on a Malaysian lab strain background for the first experiment, while the RIDL males alone were on a recently-colonised Mexican strain background for the second experiment. A total of 52 % of the matings were with RIDL males in the first experiment, while 45 % of the matings were with RIDL (Mexican) males in the second experiment. Statistically, this is not significantly different from 50 % of the matings expected to take place with RIDL males if the latter were as competitive as that of the wild type males. This shows that A. aegypti RIDL-513A has excellent mating competitiveness under semi-field conditions, verifying earlier trends obtained in small lab cages. We also observed high mating compatibility between recently-colonised Mexican RIDL males and lab-reared Malaysian wild type females.

Ang II induce kidney damage by recruiting inflammatory cells and up regulates PPAR gamma and Renin 1 gene: effect of ß carotene on chronic renal damage.

Antioxidants are widely used for prevention of diseases associated with oxidative stress and ischemic disorder. We investigated the hypothesis of antioxidants (α-tocopherol and ß-carotene) can suppress the renal disorder in apo E-/-mice. Renal damage induced by chronic infusion of Angiotensin II (Ang II) into 4 month old male apo E-/-mice. After that the mice were treated with diet enriched α tocopherol and ß carotene (800 mg/kg) for 150 days. Ang II treated kidney showed polycystic appearance with accumulation of clear fluid and constriction of renal artery and renal vein was noticed. Vacuolar/cystic degeneration as well as inflammatory reactions was noticed in the tubules/glomerulus of Ang II treated mice. ß carotene treated mice showed enormous numbers of regenerated tubules in the kidney and over expression of ICAM proteins in the regenerated tubules. CD 45.2, MAC 3 proteins were over expressed in the inflammatory cells infiltrated into the tubular region of Ang II treated kidney. Gene expression studies revealed up regulation of Renin 1 (Ren 1) and PPARγ genes in the kidney of Ang II treated animals, but the ß carotene treatment controlled the expression of these genes in the regenerated kidneys. ß carotene may have protective effective on chronic renal disorder. It may repress the inflammatory genes (Ren 1, PPARγ) to achieve the protective effect on Ang II induced renal damage.

A swarm optimized neural network system for classification of microcalcification in mammograms.

Early detection of microcalcification clusters in breast tissue will significantly increase the survival rate of the patients. Radiologists use mammography for breast cancer diagnosis at early stage. It is a very challenging and difficult task for radiologists to correctly classify the abnormal regions in the breast tissue, because mammograms are noisy images. To improve the accuracy rate of detection of breast cancer, a novel intelligent computer aided classifier is used, which detects the presence of microcalcification clusters. In this paper, an innovative approach for detection of microcalcification in digital mammograms using Swarm Optimization Neural Network (SONN) is used. Prior to classification Laws texture features are extracted from the image to capture descriptive texture information. These features are used to extract texture energy measures from the Region of Interest (ROI) containing microcalcification (MC). A feedforward neural network is used for detection of abnormal regions in breast tissue is optimally designed using Particle Swarm Optimization algorithm. The proposed intelligent classifier is evaluated based on the MIAS database where 51 malignant, 63 benign and 208 normal images are utilized. The approach has also been tested on 216 real time clinical images having abnormalities which showed that the results are statistically significant. With the proposed methodology, the area under the ROC curve (A ( z )) reached 0.9761 for MIAS database and 0.9138 for real clinical images. The classification results prove that the proposed swarm optimally tuned neural network highly contribute to computer-aided diagnosis of breast cancer.

In vitro anti-biofilm and anti-bacterial activity of Junceella juncea for its biomedical application.

OBJECTIVE: To investigate the anti-biofilm and anti-bacterial activity of Junceella juncea (J. juncea) against biofilm forming pathogenic strains. METHODS: Gorgonians were extracted with methanol and analysed with fourier transform infrared spectroscopy. Biofilm forming pathogens were identified by Congo red agar supplemented with sucrose. A quantitative spectrophotometric method was used to monitor in vitro biofilm reduction by microtitre plate assay. Anti-bacterial activity of methanolic gorgonian extract (MGE) was carried out by disc diffusion method followed by calculating the percentage of increase with crude methanol (CM). RESULTS: The presence of active functional group was exemplified by FT-IR spectroscopy. Dry, black, crystalline colonies confirm the production of extracellular polymeric substances responsible for biofilm formation in Congo red agar. MGE exhibited potential anti-biofilm activity against all tested bacterial strains. The anti-bacterial activity of methanolic extract was comparably higher in Salmonella typhii followed by Escherichia coli, Vibrio cholerae and Shigella flexneri. The overall percentage of increase was higher by 50.2% to CM. CONCLUSIONS: To conclude, anti-biofilm and anti-bacterial efficacy of J. juncea is impressive over biofilm producing pathogens and are good source for novel anti-bacterial compounds.

An improved decision support system for detection of lesions in mammograms using Differential Evolution Optimized Wavelet Neural Network.

In this paper, a computerized scheme for automatic detection of cancerous lesion in mammograms is examined. Breast lesions in mammograms are an area with an abnormality or alteration in the breast tissues. Diagnosis of these lesions at the early stage is a very difficult task as the cancerous lesions are embedded in normal breast tissue structures. This paper proposes a supervised machine learning algorithm - Differential Evolution Optimized Wavelet Neural Network (DEOWNN) for detection of tumor masses in mammograms. Differential Evolution (DE) is a population based optimization algorithm based on the principle of natural evolution, which optimizes real parameters and real valued functions. By utilizing the DE algorithm, the parameters of the Wavelet Neural Network (WNN) are optimized. To increase the detection accuracy a feature extraction methodology is used to extract the texture features of the abnormal breast tissues and normal breast tissues prior to classification. Then DEOWNN classifier is applied at the end to determine whether the given input data is normal or abnormal. The performance of the computerized decision support system is evaluated using a mini database from Mammographic Image Analysis Society (MIAS). The detection performance is evaluated using Receiver Operating Characteristic (ROC) curves. The result shows that the proposed algorithm has a sensitivity of 96.9% and specificity of 92.9%.

Insecticide susceptibility and resistance development in malathion selected Aedes albopictus (Skuse).

Aedes albopictus was bioassayed to determine resistance development to malathion (OP). Two methods were applied, including WHO larval bioassay to determine the susceptibility to lethal concentration (LC), and adult bioassay to determine lethal time (LT). Larvae from colonies that had undergone selection pressure with malathion to yield 50% mortality were further subjected to selection for subsequent 10 generations. Selection of Ae. albopictus with malathion could relatively induce a consistent resistance ratio of 1.0 throughout 10 generations. It was noted that Ae. albopictus larvae showed less susceptibility to malathion compared to adults. The susceptibility test of adult mosquitoes to diagnostic dosage of 5.0% malathion-impregnated paper showed a variety of susceptibility to malathion when compared to the susceptible strain. Bioassay results indicated that the LT50 values of malathion-selected Ae. albopictus ranged between 11.5 - 58.8 minutes for ten consecutive generations. Biochemical enzyme studies indicated that there was a significant difference (p < 0.05) in esterase level in malathion-selected mosquitoes compared to non-selected control. Electrophoretic patterns of non-specific esterases at different life stages in malathion-selected Ae. albopictus suggested that non-specific esterases do not play a role in resistance of malathion-selected Ae. albopictus.

Susceptibility status of transgenic Aedes aegypti (L.) against insecticides

Two strains of Aedes aegypti, a RIDL® strain (MyRIDL513A) and a laboratory strain (MyWT), were used in the insecticide-susceptibility study. Two-to-five-day-old female mosquitoes from both strains were tested for their susceptibility against seven insecticides from the class of organophosphate, carbamate, pyrethroids and organochlorine. The adult bioassay was performed according to WHO standard procedures. The 50% lethal time (LT50) value was determined for each strain against the seven insecticides. Both the MyRIDL513A and MyWT strains were resistant to DDT, exhibiting mortality of 48% and 33% respectively, but were susceptible to malathion (5%), permethrin (0.75%), cyfluthrin (0.15%) and lambdacyhalothrin (0.05%). This study shows there is no evidence of altered susceptibility to insecticides in the RIDL strain compared to a WT strain of Ae. aegypti.

No evidence for successful interspecific cross-mating of transgenic Aedes aegypti (L.) and wild type Aedes albopictus Skuse.

The natural and artificial mating of laboratory bred Aedes albopictus and transgenic Aedes aegypti RIDL-513A-Malaysian strain was conducted. The experiment consisted of crossmating of homologous Ae. aegypti RIDL female symbol X Ae. aegypti RIDL male symbol and reciprocal Ae. aegypti RIDL female symbol X Ae. albopictus WT male symbol. The other set comprised homologous Ae. albopictus WT female symbol X Ae. albopictus WT male symbol and reciprocal Ae. albopictus WT female symbol X Ae. aegypti RIDL male symbol. This study demonstrated that reproductive barriers exist between these two species. Cross insemination occurred between A. albopictus male and Ae. aegypti female and their reciprocals. There was 26.67% and 33.33% insemination rate in Ae. aegypti RIDL female cross-mating with A. albopictus WT male and Ae. albopictus female cross-mating with Ae. aegypti RIDL male, respectively. There was 0% hatchability in both directions of the reciprocals. There was also no embryonation of these eggs which were bleached. Although none of the female Ae. albopictus WT was inseminated in the cross-mating with Ae. albopictus WT female symbol X Ae. aegypti RIDL male symbol, a total of 573 eggs were obtained. The homologous mating was very productive resulting in both high insemination rate and hatchability rates. Generally there was a significantly higher insemination rate with artificial mating insemination of homologous than with artificial mating of reciprocal crosses. Interspecific mating between Ae. aegypti RIDL and Ae. albopictus wild type was not productive and no hybrid was obtained, indicating absence of horizontal transfer of introduced RIDL gene in Ae. aegypti to Ae. albopictus.

No evidence for successful interspecific cross-mating of transgenic Aedes aegypti (L.) and wild type Aedes albopictus Skuse

The natural and artificial mating of laboratory bred Aedes albopictus and transgenic Aedes aegypti RIDL-513A-Malaysian strain was conducted. The experiment consisted of crossmating of homologous Ae. aegypti RIDL female symbol X Ae. aegypti RIDL male symbol and reciprocal Ae. aegypti RIDL female symbol X Ae. albopictus WT male symbol. The other set comprised homologous Ae. albopictus WT female symbol X Ae. albopictus WT male symbol and reciprocal Ae. albopictus WT female symbol X Ae. aegypti RIDL male symbol. This study demonstrated that reproductive barriers exist between these two species. Cross insemination occurred between A. albopictus male and Ae. aegypti female and their reciprocals. There was 26.67% and 33.33% insemination rate in Ae. aegypti RIDL female cross-mating with A. albopictus WT male and Ae. albopictus female cross-mating with Ae. aegypti RIDL male, respectively. There was 0% hatchability in both directions of the reciprocals. There was also no embryonation of these eggs which were bleached. Although none of the female Ae. albopictus WT was inseminated in the cross-mating with Ae. albopictus WT female symbol X Ae. aegypti RIDL male symbol, a total of 573 eggs were obtained. The homologous mating was very productive resulting in both high insemination rate and hatchability rates. Generally there was a significantly higher insemination rate with artificial mating insemination of homologous than with artificial mating of reciprocal crosses. Interspecific mating between Ae. aegypti RIDL and Ae. albopictus wild type was not productive and no hybrid was obtained, indicating absence of horizontal transfer of introduced RIDL gene in Ae. aegypti to Ae. albopictus.