ADOPTION BEHAVIOUR OF BRINJAL GROWERS TOWARDS INTEGRATED PEST MANAGEMENT PRACTICES IN EAST GODAVARI DISTRICT OF ANDHRA PRADESH

The present study was conducted in Korukonda and Ramchandrapuram   division having prominent area under brinjal in East Godavari district by selecting 4 villages  from each  mandal  for study. Total 72 brinjal growers were selected. The study revealed  that personal and socio economic characteristics of the respondents education, , land holding , extension  participation , area under brinjal , extension contact and mass media exposure  were positively and significantly correlated with their level of adoption of IPM  practices.  The variable age, family type, annual income and occupation had negative and significant correlation with the adoption level. Availability of biopesticides, pheromone traps and light traps at reasonable price and at local places were the important suggestions made by brinjal growers. The other suggestions were insect organization of demonstration campaign for proper guidance on IPM practices and for identifying insect pest from state department of agriculture and state agricultural universities. View Article DOI: 10.47856/ijaast.2021.v08i10.00

Analyzation of Multistoried Building Strengthening in Seismic Region within fills and Using Etabs

Current building codes for seismic design and evaluation in Europe and American component execution based criteria that involve the estimation of inelastic reaction of the building because of seismic. These seismic requests can be precisely decide by utilizing strategies for nonlinear time history analysis. Streamlined strategies in view of nonlinear static analysis, known as sucker analysis technique and straight element analysis, known as time history analysis strategy, have been produced by a few controls to fulfill the execution based criteria for seismic design and evaluation of buildings. This proposal manages multistory buildings with open (soft story) ground floor are inalienably defenseless against crumple because of seismic burdens, their developments is still boundless in create countries. Social and utilitarian need to give auto parking spot at ground level far exceeds the notice against such buildings from designing group. In this review, 3D expository model of multistory building have been producing for multistoried building model and breaking down utilizing auxiliary analysis instrument 'ETABS'. The investigative model of building incorporates immeasurably vital segments that impact the mass, quality, solidness of the structure. Numerical outcomes for the accompanying seismic requests considering the inelastic conduct of the building, malleability coefficients of structures

Assessing the ownership, usage and knowledge of Insecticide Treated Nets (ITNS) in malaria prevention in the Hohoe Municipality, Ghana

Introduction: Malaria remains one of the top five killer diseases in sub-Saharan Africa (SSA) and its burden is skewed towards pregnant women and children under five. Insecticide Treated Bed-Net (ITN) usage is considered one of the most cost-effective, preventive interventions against malaria. This study sought to assess ownership, usage, effectiveness, knowledge, access and availability of ITNs among mothers with children under five in the Hohoe municipality.Methods: in August 2010 a cross-sectional survey was carried out in 30  communities, selected using the WHO 30 cluster sampling technique. In the  selected communities, mothers/caregivers with children under five years were selected using the snowball method. Data were collected through questionnaires and direct observation of ITN. Descriptive statistics was used to analyse the datacollected. Results: A total of 450 mothers/caregivers were interviewed and their mean age was 30 ± 7 years. ITN ownership was 81.3%, and usage was 66.4%. The majority (97.8%) of the mothers/caregivers said ITNs were effective for malaria prevention. Awareness about ITNs was high (98.7%) and the majority (52.9%) had heard about ITNs from Reproductive and Child Health (RCH) Clinic and antenatal care ANC clinic (33.6%). Over 60% of the ITNs were acquired through free distribution at RCH clinics, clinic and home distribution during mass immunization sessions. The majority of the mothers/caregivers (78.6%) knew the signs and symptoms of malaria, what causes malaria (82.2%) and who is most at risk (90%).Conclusion: Behaviour change communication strategies on ITN use may need to be further targeted to ensure full use of available ITNs

DEVELOPMENTAND EVALUATION OF IN SITU GELS OF MOXIFLOXACIN FOR THE TREATMENT OF PERIODONTITIS

Gel dosage forms are successfully used as drug delivery systems to control drug release and protect the medicaments from a hostile environment. The main objective of the present investigation is to formulate and evaluate in situ gels of moxifloxacin for the treatment of periodontitis using gellan gum and sodium alginate based on the concept of ion activated systems. The system utilizes polymers that exhibit sol-to-gel phase transition due to change in specific physico-chemical parameters. Sol-to-gel transformation occurred in the presence of monovalent /divalent cations. It was found that increase in the concentration of calcium ions produced stronger gels. Formulations were evaluated for gelling capacity, drug content, clarity, viscosity, gel strength, spread ability, microbiological studies and in vitro release. The results shown by the above characterization studies were found to be satisfactory. Experimental part showed that viscosity of sols and gel strength was increased with increase in the concentration of polymers and the sustained release of drug was observed. The formulations were therapeutically efficacious, sterile and provided sustained release of the drug over a period of time. These results demonstrated that the developed system is an alternative to conventional drug delivery systems, provides patient compliance and economical

Determining the control networks regulating stem cell lineages in colonic crypts

The question of stem cell control is at the center of our understanding of tissue functioning, both in healthy and cancerous conditions. It is well accepted that cellular fate decisions (such as divisions, differentiation, apoptosis) are orchestrated by a network of regulatory signals emitted by different cell populations in the lineage and the surrounding tissue. The exact regulatory network that governs stem cell lineages in a given tissue is usually unknown. Here we propose an algorithm to identify a set of candidate control networks that are compatible with (a) measured means and variances of cell populations in different compartments, (b) qualitative information on cell population dynamics, such as the existence of local controls and oscillatory reaction of the system to population size perturbations, and (c) statistics of correlations between cell numbers in different compartments. Using the example of human colon crypts, where lineages are comprised of stem cells, transit amplifying cells, and differentiated cells, we start with a theoretically known set of 32 smallest control networks compatible with tissue stability. Utilizing near-equilibrium stochastic calculus of stem cells developed earlier, we apply a series of tests, where we compare the networks' expected behavior with the observations. This allows us to exclude most of the networks, until only three, very similar, candidate networks remain, which are most compatible with the measurements. This work demonstrates how theoretical analysis of control networks combined with only static biological data can shed light onto the inner workings of stem cell lineages, in the absence of direct experimental assessment of regulatory signaling mechanisms. The resulting candidate networks are dominated by negative control loops and possess the following properties: (1) stem cell division decisions are negatively controlled by the stem cell population, (2) stem cell differentiation decisions are negatively controlled by the transit amplifying cell population

Cell Lineages and Growth Control by Feedback

The molecular mechanisms that regulate tissue growth are diverse, but the objectives of growth control are generic in many tissues: to reach and stably maintain an appropriate size, to regenerate rapidly following injury, to possess appropriate proportions of different cell types, and to form specific tissue structures during development. It is known that feedback mechanisms play a role in growth control, and that cells the give rise to a tissue are organized into lineages—successive stages in which cells at each stage have the option either to self-renew or differentiate to the next stage. Negative feedback on progenitor cell self-renewal has been previously shown to confer “perfect adaptation” for steady-state size control (maintenance of an exact tissue size independent of numbers of starting cells, rates of cell division, or rates of cell death), stability, and a low steady-state load of progenitor cells (Lander, Gokoffski et al. 2009). Negative feedback is also useful for fast regeneration, and it will be shown that negative feedback can be used to approximate a bang-bang controller and therefore be used to build a tissue in the shortest time possible. This control strategy, however, suffers from inherent performance tradeoffs. Namely, rapid regeneration and robustness to parameters/initial conditions tend to be competing objectives, and certain perturbations can result in undesirable oscillations. Stem cells in lineages, such as in the olfactory epithelium (OE), are also known to undergo branching decisions (i.e. to be bipotent) (Gokoffski, Wu et al. 2011) and to receive feedback that promotes self-renewal divisions, such as by FGFs (DeHamer, Guevara et al. 1994). This study seeks to understand the role of the latter phenomenon, which amounts to a type of positive feedback. We find that mixing negative and positive feedback on progenitor self-renewal enables two distinct types of stable growth: either high or low, which we refer to as bi-modality. A critical feedback ratio sets the threshold between the two states, and spatial simulations reveal that this threshold can be used by tissues to self-organize into distinct shapes. A transient, local exogenous positive signal can boost progenitor self-renewal within a discrete zone of planar tissue, which induces bud formation and self-sustaining growth. Furthermore, these zones can self-organize in ways that control tissue shape with spatial precision – i.e. a bud elongates and maintains a constant width as growth self-sustains at its tip, neighboring elongating branches maintain even spacing, and branch numbers change according to changes in the feedback ratio. Disturbances to growth factors that regulate progenitor self-renewal have been previously shown to have morphological consequences during early branching of the olfactory epithelium (OE) (Kawauchi, Kim et al. 2009). Finally, results will be presented from counting progenitor cells in BrdU/EdU pulse-chase/fix experiments in the embryonic OE to measure regional differences in progenitor self-renewal. Preliminary data reveals high progenitor self-renewal in regions undergoing branching morphogenesis, while low self-renewal maintains cell populations in equilibrium at the anterior end of the OE

Genes and factors responsible for Pseudomonas aeruginosa resistance ability

Antibiotic resistance has become a growing medical problem in the past years due to the resistance shown by numerous microorganisms that are potential disease-causing agents. This developed resistance makes it hard to treat and prevent infections. It is vital to understand the genetic mechanisms behind resistance to address this problem. Pseudomonas aeruginosa is a motile, non-fermenting, Gram-negative bacterium. It is an opportunistic pathogen implicated in respiratory and urinary tract infections, particularly in immunocompromised patients. It is a multi-drug resistant pathogen that can quickly acquire new resistance traits. This study aims to identify genes and factors responsible for antibiotic resistance in P. aeruginosa. A previously generated insertion sequencing (INSeq) dataset consisting of 50 samples from a high-throughput transposon mutant screen was analyzed using the in-house developed CAFE (Coefficient-based Analysis of Fitness by read Enrichment) protocol. The INSeq dataset consisted of previously prepared samples of five biological replicates from P. aeruginosa overnight cultures that were grown under exposure to sublethal levels of the antibiotics tetracycline and ciprofloxacin, as well as control samples without antibiotic exposure. Both the planktonic and biofilm phases were sampled from each treatment. Following the CAFE analysis, a network analysis using two different networks, KEGG (Kyoto encyclopedia of genes and genomes) and GSMM (Genome-scale metabolic model), was performed. KEGG is a pathway-based network and GSMM is based on genes connected by sharing metabolites. In these two networks, the genes with significantly positive fitness coefficients were identified, and their connected genes were extracted. A subset of these genes was tested in an antibiotic exposure assay to verify their involvement in antibiotic resistance. A priority gene list containing 67 genes of planktonic and biofilm phases in ciprofloxacin and tetracycline were identified using the CAFE protocol where network analysis on these genes by KEGG and GSMM resulted in twelve resistance candidate genes, and 117 metabolically connected genes with similar response patterns were investigated by network analysis. Out of these genes, seven candidate and eleven metabolically connected deletion mutants were verified in the antibiotic exposure essay comparing single mutants to the wild type (MPAO1). The experimental work resulted in confirmation of the resistance function for six candidate and ten connected genes. The twelve resistance gene candidates and their metabolically connected genes were also statistically analyzed by Pearson’s correlation test to check if they function as a single gene or together as a pathway that can help in producing future antibiotic targets. In conclusion, the findings suggest that out of a total of 18 genes (both candidate and connected), 16 genes are involved in ciprofloxacin resistance. Furthermore, out of twelve resistance gene candidates, nine showed a pathway effect, while three had a gene-specific effect. The study highlights that P. aeruginosa carries multiple resistance mechanisms, many of which have not been previously linked to antibiotic resistance. The pathways identified in this work could be potential drug targets for future antibiotics treatment

Genes and factors responsible for Pseudomonas aeruginosa resistance ability

Antibiotic resistance has become a growing medical problem in the past years due to the resistance shown by numerous microorganisms that are potential disease-causing agents. This developed resistance makes it hard to treat and prevent infections. It is vital to understand the genetic mechanisms behind resistance to address this problem. Pseudomonas aeruginosa is a motile, non-fermenting, Gram-negative bacterium. It is an opportunistic pathogen implicated in respiratory and urinary tract infections, particularly in immunocompromised patients. It is a multi-drug resistant pathogen that can quickly acquire new resistance traits. This study aims to identify genes and factors responsible for antibiotic resistance in P. aeruginosa. A previously generated insertion sequencing (INSeq) dataset consisting of 50 samples from a high-throughput transposon mutant screen was analyzed using the in-house developed CAFE (Coefficient-based Analysis of Fitness by read Enrichment) protocol. The INSeq dataset consisted of previously prepared samples of five biological replicates from P. aeruginosa overnight cultures that were grown under exposure to sublethal levels of the antibiotics tetracycline and ciprofloxacin, as well as control samples without antibiotic exposure. Both the planktonic and biofilm phases were sampled from each treatment. Following the CAFE analysis, a network analysis using two different networks, KEGG (Kyoto encyclopedia of genes and genomes) and GSMM (Genome-scale metabolic model), was performed. KEGG is a pathway-based network and GSMM is based on genes connected by sharing metabolites. In these two networks, the genes with significantly positive fitness coefficients were identified, and their connected genes were extracted. A subset of these genes was tested in an antibiotic exposure assay to verify their involvement in antibiotic resistance. A priority gene list containing 67 genes of planktonic and biofilm phases in ciprofloxacin and tetracycline were identified using the CAFE protocol where network analysis on these genes by KEGG and GSMM resulted in twelve resistance candidate genes, and 117 metabolically connected genes with similar response patterns were investigated by network analysis. Out of these genes, seven candidate and eleven metabolically connected deletion mutants were verified in the antibiotic exposure essay comparing single mutants to the wild type (MPAO1). The experimental work resulted in confirmation of the resistance function for six candidate and ten connected genes. The twelve resistance gene candidates and their metabolically connected genes were also statistically analyzed by Pearson’s correlation test to check if they function as a single gene or together as a pathway that can help in producing future antibiotic targets. In conclusion, the findings suggest that out of a total of 18 genes (both candidate and connected), 16 genes are involved in ciprofloxacin resistance. Furthermore, out of twelve resistance gene candidates, nine showed a pathway effect, while three had a gene-specific effect. The study highlights that P. aeruginosa carries multiple resistance mechanisms, many of which have not been previously linked to antibiotic resistance. The pathways identified in this work could be potential drug targets for future antibiotics treatment

Application of System Dynamic Modelling for Evaluation of Carbon Mitigation Strategies in Cement Industries: A Comparative Overview of the Current State of the Art

Cement is the key ingredient in concrete, which is the most consumed resource on the planet after water. As an energy-intensive industry, cement production is one of the largest sources of greenhouse emissions in the world today. The demand for cement is synonymous with the growth in infrastructure demand and per-capita gross domestic product in the world, calling the need for mitigation measures within the industry in order to contribute to the global climate change efforts. System dynamics (SD) is a simulation approach that is used for studying the nonlinear behaviours in complex systems over time, often used in industrial domains for emission forecasts as well as policy experimentation. With the adoption rates of mitigation strategies in the cement industry being inadequate, there is a need for improvisation in policymaking through better decision-support tools. In this paper, a comparative overview of the studies that specifically utilise the SD approach for evaluation of carbon mitigation strategies in the cement industry is presented on the basis of their scope, model description, scenarios tested, and featured mitigation methods. Additionally, the potential for improvements in future studies is discussed