Pre-Harvest Factors Optimization Using Genetic Algorithm for Lettuce

The agricultural sector is facing problems on crop development due to climate change and global warming. Crops such as rice, tomato, corn, lettuce, potato, wheat, soybeans and others are affected. Through analyzing the graphical representation of data, no optimum values are observed. In this study, the suitability of the genetic algorithm in finding the best condition for producing high quality lettuce crop was determined. The parameters that were optimized are the light intensity, temperature and CO2. These parameters were essential preharvest factors for lettuce. The system selected the 50 fittest individuals based on the fitness score and then proceeds to the recombination process. A mutation has been applied to test if the solution is the global one. When the iterations had reached the required number of generation, the system stopped and gave the best condition for lettuce. Critical design on GA was done and the best fitness plot was obtained. The GA results showed that the optimum conditions for a highquality lettuce crop needs a light intensity of 175.22296 μmol/m2/s, a temperature of 19.36228 ºC and a CO2 level of 803.01855 ppm

SMAC is expressed de novo in a subset of cervical cancer tumors

BACKGROUND: Smac/Diablo is a recently identified protein that is released from mitochondria after apoptotic stimuli. It binds IAPs, allowing caspase activation and cell death. In view of its activity it might participate in carcinogenesis. In the present study, we analyzed Smac expression in a panel of cervical cancer patients. METHODS: We performed semi quantitative RT-PCR on 41 cervical tumor and 6 normal tissue samples. The study included 8 stage I cases; 16 stage II; 17 stage III; and a control group of 6 samples of normal cervical squamous epithelial tissue. RESULTS: Smac mRNA expression was below the detection limit in the normal cervical tissue samples. In contrast, 13 (31.7%) of the 41 cervical cancer biopsies showed detectable levels of this transcript. The samples expressing Smac were distributed equally among the stages (5 in stage I, 4 in stage II and 4 in stage III) with similar expression levels. We found no correlation between the presence of Smac mRNA and histology, menopause, WHO stage or disease status. CONCLUSIONS: Smac is expressed de novo in a subset of cervical cancer patients, reflecting a possible heterogeneity in the pathways leading to cervical cancer. There was no correlation with any clinical variable

A surge in serum mucosal cytokines associated with seroconversion in children at risk for type 1 diabetes.

OnlinePublAims/Introduction: Autoantibodies to pancreatic islet antigens identify young children at high risk of type 1 diabetes. On a background of genetic susceptibility, islet autoimmunity is thought to be driven by environmental factors, of which enteric viruses are prime candidates. We sought evidence for enteric pathology in children genetically atrisk for type 1 diabetes followed from birth who had developed islet autoantibodies (“seroconverted”), by measuring mucosa-associated cytokines in their sera. Materials and Methods: Sera were collected 3 monthly from birth from children with a first-degree type 1 diabetes relative, in the Environmental Determinants of Islet Autoimmunity (ENDIA) study. Children who seroconverted were matched for sex, age, and sample availability with seronegative children. Luminex xMap technology was used to measure serum cytokines. Results: Of eight children who seroconverted, for whom serum samples were available at least 6 months before and after seroconversion, the serum concentrations of mucosaassociated cytokines IL-21, IL-22, IL-25, and IL-10, the Th17-related cytokines IL-17F and IL23, as well as IL-33, IFN-c, and IL-4, peaked from a low baseline in seven around the time of seroconversion and in one preceding seroconversion. These changes were not detected in eight sex- and age-matched seronegative controls, or in a separate cohort of 11 unmatched seronegative children. Conclusions: In a cohort of children at risk for type 1 diabetes followed from birth, a transient, systemic increase in mucosa-associated cytokines around the time of seroconversion lends support to the view that mucosal infection, e.g., by an enteric virus, may drive the development of islet autoimmunity.Leonard C Harrison, Esther Bandala-Sanchez, Helena Oakey, Peter G Colman, Kelly Watson, Ki Wook Kim, Roy Wu, Emma E Hamilton-Williams, Natalie L Stone, Aveni Haynes, Rebecca L Thomson, Peter J Vuillermin, Georgia Soldatos, William D Rawlinson, Kelly J McGorm, Grant Morahan, Simon C Barry, Richard O Sinnott, John M Wentworth, Jennifer J Couper, Megan AS Penno, on behalf of the ENDIA Study Grou

Regulation of the Actin Cytoskeleton by an Interaction of IQGAP Related Protein GAPA with Filamin and Cortexillin I

Filamin and Cortexillin are F-actin crosslinking proteins in Dictyostelium discoideum allowing actin filaments to form three-dimensional networks. GAPA, an IQGAP related protein, is required for cytokinesis and localizes to the cleavage furrow during cytokinesis. Here we describe a novel interaction with Filamin which is required for cytokinesis and regulation of the F-actin content. The interaction occurs through the actin binding domain of Filamin and the GRD domain of GAPA. A similar interaction takes place with Cortexillin I. We further report that Filamin associates with Rac1a implying that filamin might act as a scaffold for small GTPases. Filamin and activated Rac associate with GAPA to regulate actin remodelling. Overexpression of filamin and GAPA in the various strains suggests that GAPA regulates the actin cytoskeleton through interaction with Filamin and that it controls cytokinesis through association with Filamin and Cortexillin

Environmental determinants of islet autoimmunity (ENDIA): a pregnancy to early life cohort study in children at-risk of type 1 diabetes

Members of ENDIA Study Group: Peter Baghurst, Simon Barry, Jodie Dodd, Maria Makrides for the University of Adelaide.BACKGROUND The incidence of type 1 diabetes has increased worldwide, particularly in younger children and those with lower genetic susceptibility. These observations suggest factors in the modern environment promote pancreatic islet autoimmunity and destruction of insulin-producing beta cells. The Environmental Determinants of Islet Autoimmunity (ENDIA) Study is investigating candidate environmental exposures and gene-environment interactions that may contribute to the development of islet autoimmunity and type 1 diabetes. METHODS/DESIGN ENDIA is the only prospective pregnancy/birth cohort study in the Southern Hemisphere investigating the determinants of type 1 diabetes in at-risk children. The study will recruit 1,400 unborn infants or infants less than six months of age with a first-degree relative (i.e. mother, father or sibling) with type 1 diabetes, across five Australian states. Pregnant mothers/infants will be followed prospectively from early pregnancy through childhood to investigate relationships between genotype, the development of islet autoimmunity (and subsequently type 1 diabetes), and prenatal and postnatal environmental factors. ENDIA will evaluate the microbiome, nutrition, bodyweight/composition, metabolome-lipidome, insulin resistance, innate and adaptive immune function and viral infections. A systems biology approach will be used to integrate these data. Investigation will be by 3-monthly assessments of the mother during pregnancy, then 3-monthly assessments of the child until 24 months of age and 6-monthly thereafter. The primary outcome measure is persistent islet autoimmunity, defined as the presence of autoantibodies to one or more islet autoantigens on consecutive tests. DISCUSSION Defining gene-environment interactions that initiate and/or promote destruction of the insulin-producing beta cells in early life will inform approaches to primary prevention of type 1 diabetes. The strength of ENDIA is the prospective, comprehensive and frequent systems-wide profiling from early pregnancy through to early childhood, to capture dynamic environmental exposures that may shape the development of islet autoimmunity. TRIAL REGISTRATION Australia New Zealand Clinical Trials Registry ACTRN12613000794707.Megan AS Penno, Jennifer J Couper, Maria E Craig, Peter G Colman, William D Rawlinson, Andrew M Cotterill, Timothy W Jones, Leonard C Harrison and ENDIA Study Grou

Hybrid Genetic Programming and Multiverse-based Optimization of Pre-Harvest Growth Factors of Aquaponic Lettuce Based on Chlorophyll Concentration

Optimizing photosynthesis is vital in maintaining quality farm produce in the agricultural food production sector. The nonlinear behavior of the interaction of crop pre-harvest growth factors can promote or retard its growth. This study employed multigene symbolic regression genetic programming (MSRGP) in developing the chlorophyll-a fitness function allied with bioinspired algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), and multiverse optimization (MVO), in determining the ideal combination of carbon dioxide, light intensity, air temperature, and humidity that will induce photosynthesis based on aquaponic lettuce (Lactuca sativa var. Altima) leaf chlorophyll-a concentration. Light spectra were characterized through the floating leaf disk technique, which resulted in white spectra as the most photosynthetic conducive based on the light reaction and dark respiration. Leaf spectro-textural-morphological signatures were extracted for non-destructive MSRGP chlorophyll-a concentration measurement. Carbon dioxide and humidity have a strong positive impact on chlorophyll-a concentration. Photosynthesis is impeded by Vis/IR above 7.817. The hybrid MSRGP-MVO generated the ideal global solution of 880.744 ppm of CO2, 543.147 gmol m-2 s-1 of the visible white light spectrum, 22.238 °C air temperature, and 67.742% humidity which resulted in 651.144 mg g-1 of Chl-a, 0.934 leaf weight ratio, 0.066 roots to shoot ratio, 141 xylem vessels mm-2 127.389 stomata mm-2, and more prominent intracellular chloroplast concentration for the harvest stage lettuce. The established standard for fresh weight, chlorophylls a and b, and vitamin C concentrations are essential for developing an adaptive nutrient management system to maintain the expected growth signatures of lettuce at the end of the 6-week cultivation cycle. © 2021. All Rights Reserved.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Determination of aquaponic water macronutrient concentrations based on lactuca sativa leaf photosynthetic signatures using hybrid gravitational search and recurrent neural network

Crop quality depends dominantly on the nutrients present in its growth media. For precision farming, fertigation is a challenge, especially when dealing with economical and efficiency factors. In this study, the aquaponic pond water macronutrient prediction model (wNPK) was developed based on leaf photosynthetic signature predictors. Aquaphotomics was preliminarily used for correlating physical limnological properties with nitrate, phosphate, potassium concentrations, and the leaf signatures. Using a digital camera, 18 spectro-textural-morphological features were extracted. Neighborhood component analysis (NCA) and ReliefF algorithms selected the spectral components blue, a*, and red minus luma as the most significant as supported by principal component analysis, resulting in low computational cost. A Gravitational Search Algorithm (GSA) was employed to optimize the recurrent neural network (RNN) architecture resulting in higher sensitivity. The hybrid NCA-ReliefF-GSA-RNN (wNPK) predicted NPK with 93.61, 84.03, and 91.39 % accuracy, respectively, besting out other configured feature-based machine learning models. Using wNPK, it was confirmed that potassium helped in accelerating seed germination and nitrogen in promoting chlorophyll intensification, especially on the 6th week after sowing. Phosphate and potassium were the energy and health elements that were consumed in a larger amount at the end of the head development stage. wNPK rules out that macronutrient concentration have a direct resemblance to crop leaf signatures; thus, a leaf is a good indicator of the water quality. The results pointed out that the use of a single camera to measure both water macronutrient concentrations and crop signature at the same time is an innovative, efficient, and economical approach for precision farming.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Characterization and treatability of a contaminated soil from an oil exploration zone

A crude contaminated soil, arising from an oil production zone in Tabasco, Mexico was studied. A sample of about 40 kg was dried and screened through meshes 10-100. Total petroleum hydrocarbons and 6 metals (Cd, Cu, Cr, Ni, V and Zn) were determined to the different portions. For soil which passed mesh 10, six non-ionic, three anionic and one zwitterionic surfactant solutions (0.5%) were employed to wash the soil. Additional tests using surfactant salt mixtures and surfactants mixtures were carried out. Once the best soil washing conditions were identified, these experimental conditions were applied for washing the rest of the soil portions obtained (meshes 4, 6, 20, 40, 60, 80, 100). Total petroleum hydrocarbons values were in the range of 51,550 to 192,130 mg/kg. Cd was not found in any of the soils portions, and the rest of the metals were found at different concentrations, for every soil mesh. Treatability tests applied to the soils indicated that it is possible to get removals between 9.1 to 20.5%. For the case of a sodium dodecyl sulphate 1% solution, total petroleum hydrocarbons removal was as high as 35.4%. Combinations of sodium docecyl sulphate and salts, gave removal rates up to 49.5%. Total petroleum hydrocarbons concentrations for the whole soil were about 150,600 mg/kg. The higher the particle size, the lower the washing removal rate. The combined effect of particle size and total petroleum hydrocarbons concentration, determines the total petroleum hydrocarbons removal efficiencies. These facts are very important for designing an appropriate soil washing remediation process