Automatic Detection of Diseased Tomato Plants Using Thermal and Stereo Visible Light Images

Accurate and timely detection of plant diseases can help mitigate the worldwide losses experienced by the horticulture and agriculture industries each year. Thermal imaging provides a fast and non-destructive way of scanning plants for diseased regions and has been used by various researchers to study the effect of disease on the thermal profile of a plant. However, thermal image of a plant affected by disease has been known to be affected by environmental conditions which include leaf angles and depth of the canopy areas accessible to the thermal imaging camera. In this paper, we combine thermal and visible light image data with depth information and develop a machine learning system to remotely detect plants infected with the tomato powdery mildew fungus Oidium neolycopersici. We extract a novel feature set from the image data using local and global statistics and show that by combining these with the depth information, we can considerably improve the accuracy of detection of the diseased plants. In addition, we show that our novel feature set is capable of identifying plants which were not originally inoculated with the fungus at the start of the experiment but which subsequently developed disease through natural transmission.     

Cadmium and lead interactive effects on oxidative stress and antioxidative responses in rice seedlings

Interactive effects of two heavy metal pollutants Cd and Pb in the growth medium were examined on their uptake, production of reactive oxygen species (ROS), induction of oxidative stress and antioxidative defence responses in Indica rice (Oryza sativa L.) seedlings. When rice seedlings in sand culture were exposed to 150 μM Cd (NO₃)₂ or 600 μM Pb (CH₃COO)₂ individually or in combination for 8–16 days, a significant reduction in root/shoot length, fresh weight, relative water content, photosynthetic pigments and increased production of ROS (O₂˙^? and H₂O₂) was observed. Both Cd and Pb were readily taken up by rice roots and localisation of absorbed metals was greater in roots than in shoots. When present together in the growth medium, uptake of both the metals Cd and Pb declined by 25–40 %. Scanning electron microscope (SEM) imaging of leaf stomata revealed that Pb caused more distortion in the shape of guard cells than Cd. Dithizone staining of roots showed localisation of absorbed Cd on root hairs and epidermal cells. Both Cd and Pb caused increased lipid peroxidation, protein carbonylation, decline in protein thiol and increase in non-protein thiol. The level of reduced forms of non-enzymic antioxidants glutathione (GSH) and ascorbate (AsA) and their redox ratios (GSH/AsA) declined, whereas the activities of antioxidative enzymes superoxide dismutase (SOD) and guaiacol peroxidase (GPX) increased in metal treated seedlings compared to controls. In-gel activity staining also revealed increased intensities of SOD and GPX isoforms with metal treatments. Catalase (CAT) activity increased during early days (8 days) of metal exposure and declined by 16 days. Results suggest that oxidative stress is an important component in expression of Cd and Pb toxicities in rice, though uptake of both metals gets reduced considerably when present together in the medium.     

Manganese-induced oxidative stress,ultrastructural changes,and proteomics studies in rice plants

Protoplasma - Manganese (Mn) is an essential element for plant growth but it becomes phytotoxic at higher concentrations. The effect of Mn-excess in hydroponics medium was examined on growth,...     

<Emphasis Type="Italic">Terminalia arjuna</Emphasis> bark extract alleviates nickel toxicity by suppressing its uptake and modulating antioxidative defence in rice seedlings

Terminalia arjuna (Ta) bark contains various natural antioxidants and has been used to protect animal cells against oxidative stress. In the present study, we have examined alleviating effects of Ta bark aqueous extract against Ni toxicity in rice (Oryza sativa L.). When rice seedlings were raised for 8 days in hydroponics in Yoshida nutrient medium containing 200 μM NiSO₄, a decline in height, reduced biomass, increased Ni uptake, loss of root plasma membrane integrity, increase in the level of O₂˙^?, H₂O₂ and ˙OH, increased lipid peroxidation, decline in photosynthetic pigments, increase in the level of antioxidative enzymes superoxide dismutase, catalase and glutathione peroxidase and alterations in their isoenzyme profile patterns were observed. Transmission electron microscopy (TEM) showed damage to chloroplasts marked by disorganised enlarged starch granules and disrupted thylakoids under Ni toxicity. Exogenously adding Ta bark extract (3.2 mg ml^?1) to the growth medium considerably alleviated Ni toxicity in the seedlings by reducing Ni uptake, suppressing generation of reactive oxygen species, reducing lipid peroxidation, restoring level of photosynthesis pigments and ultrastructure of chloroplasts, and restoring levels of antioxidative enzymes. Results suggest that Ta bark extract considerably alleviates Ni toxicity in rice seedlings by preventing Ni uptake and reducing oxidative stress in the seedlings.     

Quantification of cell infection caused by Listeria monocytogenes invasion

Listeria monocytogenes causes a life-threatening food-borne disease known as Listeriosis. Elderly, immunocompromised, and pregnant women are primarily the victims of this facultative intracellular Gram-positive pathogen. Since the bacteria survive intracellularly within the human host cells they are protected against the immune system and poorly accessed by many antibiotics. In order to screen pharmaceutical substances for their ability to interfere with the infection, persistence and release of L. monocytogenes a high content assay is required. We established a high content screen (HCS) using the RAW 264.7 mouse macrophage cell line seeded into 96-well glass bottom microplates. Cells were infected with GFP-expressing L. monocytogenes and stained thereafter with Hoechst 33342. Automated image acquisition was carried out by the Scan^R screening station. We have developed an algorithm that automatically grades cells in microscopy images of fluorescent-tagged Listeria for the severity of infection. The grading accuracy of this newly developed algorithm is 97.1% as compared to a 74.3% grading accuracy we obtained using the commercial Olympus Scan^R software.     

Functional Connectivity Alterations in Epilepsy from Resting-State Functional MRI

The study of functional brain connectivity alterations induced by neurological disorders and their analysis from resting state functional Magnetic Resonance Imaging (rfMRI) is generally considered to be a challenging task. The main challenge lies in determining and interpreting the large-scale connectivity of brain regions when studying neurological disorders such as epilepsy. We tackle this challenging task by studying the cortical region connectivity using a novel approach for clustering the rfMRI time series signals and by identifying discriminant functional connections using a novel difference statistic measure. The proposed approach is then used in conjunction with the difference statistic to conduct automatic classification experiments for epileptic and healthy subjects using the rfMRI data. Our results show that the proposed difference statistic measure has the potential to extract promising discriminant neuroimaging markers. The extracted neuroimaging markers yield 93.08% classification accuracy on unseen data as compared to 80.20% accuracy on the same dataset by a recent state-of-the-art algorithm. The results demonstrate that for epilepsy the proposed approach confirms known functional connectivity alterations between cortical regions, reveals some new connectivity alterations, suggests potential neuroimaging markers, and predicts epilepsy with high accuracy from rfMRI scans.     

Bayesian Hierarchical Clustering for Studying Cancer Gene Expression Data with Unknown Statistics

Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper, we present an extension of the BHC algorithm. Our Gaussian BHC (GBHC) algorithm represents data as a mixture of Gaussian distributions. It uses normal-gamma distribution as a conjugate prior on the mean and precision of each of the Gaussian components. We tested GBHC over 11 cancer and 3 synthetic datasets. The results on cancer datasets show that in sample clustering, GBHC on average produces a clustering partition that is more concordant with the ground truth than those obtained from other commonly used algorithms. Furthermore, GBHC frequently infers the number of clusters that is often close to the ground truth. In gene clustering, GBHC also produces a clustering partition that is more biologically plausible than several other state-of-the-art methods. This suggests GBHC as an alternative tool for studying gene expression data.The implementation of GBHC is available at https://sites.google.com/site/gaussianbhc/     

RAMTaB: robust alignment of multi-tag bioimages

Background

In recent years, new microscopic imaging techniques have evolved to allow us to visualize several different proteins (or other biomolecules) in a visual field. Analysis of protein co-localization becomes viable because molecules can interact only when they are located close to each other. We present a novel approach to align images in a multi-tag fluorescence image stack. The proposed approach is applicable to multi-tag bioimaging systems which (a) acquire fluorescence images by sequential staining and (b) simultaneously capture a phase contrast image corresponding to each of the fluorescence images. To the best of our knowledge, there is no existing method in the literature, which addresses simultaneous registration of multi-tag bioimages and selection of the reference image in order to maximize the overall overlap between the images.

Methodology/Principal Findings

We employ a block-based method for registration, which yields a confidence measure to indicate the accuracy of our registration results. We derive a shift metric in order to select the Reference Image with Maximal Overlap (RIMO), in turn minimizing the total amount of non-overlapping signal for a given number of tags. Experimental results show that the Robust Alignment of Multi-Tag Bioimages (RAMTaB) framework is robust to variations in contrast and illumination, yields sub-pixel accuracy, and successfully selects the reference image resulting in maximum overlap. The registration results are also shown to significantly improve any follow-up protein co-localization studies.

Conclusions

For the discovery of protein complexes and of functional protein networks within a cell, alignment of the tag images in a multi-tag fluorescence image stack is a key pre-processing step. The proposed framework is shown to produce accurate alignment results on both real and synthetic data. Our future work will use the aligned multi-channel fluorescence image data for normal and diseased tissue specimens to analyze molecular co-expression patterns and functional protein networks.     

Spatiotemporal maps of CaMKII in dendritic spines

The calcium calmodulin dependent kinase (CaMKII) is important for long-term potentiation at dendritic spines. Photo-activatable GFP (PaGFP) - CaMKII fusions were used to map CaMKII movements between and within spines in dissociated hippocampal neurons. Photo-activated PaGFP (GFP*) generated in the shaft spread uniformly, but was retained for about 1?s in spines. The differential localization of GFP*-CaMKII isoforms was visualized with hundred nanometer precision frame to frame using de-noising algorithms. GFP*-CaMKIIα localized to the tips of mushroom spines. The spatiotemporal profiles of native and kinase defective GFP*-CaMKIIβ, differed markedly from GFP*-CaMKIIα and mutant GFP*-CaMKIIβ lacking the association domain. CaMKIIβ bound to cortical actin in the dendrite and the stable actin network in spine bodies. Glutamate produced a transiently localized GFP*-CaMKIIα fraction and a soluble GFP*-CaMKIIβ fraction in spine bodies. Single molecule simulations of the interplay between diffusion and biochemistry of GFP* species were guided by the spatiotemporal maps and set limits on binding parameters. They highlighted the role of spine morphology in modulating bound CaMKII lifetimes. The long residence times of GFP*-CaMKIIβ relative to GFP*-CaMKIIα followed as consequence of more binding sites on the actin cytoskeleton than the post-synaptic density. These factors combined to retain CaMKII for tens of seconds, sufficient to outlast the calcium transients triggered by glutamate, without invoking complex biochemistry.