Exploring Aluminum Tolerance Mechanisms in Plants with Reference to Rice and Arabidopsis: A Comprehensive Review of Genetic, Metabolic, and Physiological Adaptations in Acidic Soils.

Aluminum (Al) makes up a third of the Earth's crust and is a widespread toxic contaminant, particularly in acidic soils. It impacts crops at multiple levels, from cellular to whole plant systems. This review delves into Al's reactivity, including its cellular transport, involvement in oxidative redox reactions, and development of specific metabolites, as well as the influence of genes on the production of membrane channels and transporters, alongside its role in triggering senescence. It discusses the involvement of channel proteins in calcium influx, vacuolar proton pumping, the suppression of mitochondrial respiration, and the initiation of programmed cell death. At the cellular nucleus level, the effects of Al on gene regulation through alterations in nucleic acid modifications, such as methylation and histone acetylation, are examined. In addition, this review outlines the pathways of Al-induced metabolic disruption, specifically citric acid metabolism, the regulation of proton excretion, the induction of specific transcription factors, the modulation of Al-responsive proteins, changes in citrate and nucleotide glucose transporters, and overall metal detoxification pathways in tolerant genotypes. It also considers the expression of phenolic oxidases in response to oxidative stress, their regulatory feedback on mitochondrial cytochrome proteins, and their consequences on root development. Ultimately, this review focuses on the selective metabolic pathways that facilitate Al exclusion and tolerance, emphasizing compartmentalization, antioxidative defense mechanisms, and the control of programmed cell death to manage metal toxicity.

A Dual Cobalt-Photoredox Catalytic Approach for Asymmetric Dearomatization of Indoles with Aryl Amides via C-H Activation.

In this study, we unveil a novel method for the asymmetric dearomatization of indoles under cobalt/photoredox catalysis. By strategically activating C-H bonds of amides and subsequent migratory insertion of  p-bonds present in indole as reactive partner, we achieve syn-selective tetrahydro-5H-indolo[2,3-c]isoquinolin-5-one derivatives with excellent yields and enantiomeric excesses of up to >99%. The developed method operates without a metal oxidant, relying solely on oxygen as the oxidant and employing an organic dye as a photocatalyst under irradiation. Control experiments and stoichiometric studies elucidate the reversible nature of the enantiodetermining C-H activation step, albeit not being rate-determining. This study not only expands the horizon of cobalt-catalyzed asymmetric C-H bond functionalization, but also showcases the potential synergy between cobalt and photoredox catalysis in enabling asymmetric synthesis of complex molecules.

Modulation of secondary metabolism and redox regulation by exogenously applied glutathione improves the shelf life of Capsicum annuum L. fruit.

Role of redox homeostasis in fruit ripening of Capsicum annuum L. with oxidative metabolism was studied. The research aims the ability to reduce agents during postharvest storage on fruit for delayed ripening with the regulation of oxidative stress. Thus, we applied 10 mM reduced glutathione (GSH) to fruit as pretreatment followed by 1 mM hydrogen peroxide (H2O2) as ripening-inducing treatment and observed during 7 days of storage at 25 °C. A decrease in total soluble solid and firmness under H2O2, was increased while dehydration in tissue was decreased by GSH pretreatment. Glutathione regulated the turnover of organic acids to reducing sugars with higher activity of NADP malic enzyme that sustained the fruit coat photosynthesis through chlorophyll fluorescence, pigment composition, and photosystem II activity. Malondialdehyde accumulation was inversely correlated with GSH content and antioxidative enzyme activity that reduced loss of cell viability. Conclusively, regulation of oxidative stress with GSH may be effective in the extension of shelf life under postharvest storage.

Enantioselective C-H bond functionalization under Co(III)-catalysis.

While progress in enantioselective C-H functionalization has been accomplished by employing 4d and 5d transition metal-based catalysts, the rapid depletion of these metals in the earth's crust poses a serious threat to making these protocols sustainable. On the other hand, because of their unique reactivity, low toxicity, and high earth abundance, newer strategies utilizing affordable 3d transition metals have come to the forefront. Among the first-row transition metals, high-valent cobalt has recently attracted a lot of attention for catalytic C-H functionalization with mono and bidentate directing groups. This approach was extended for asymmetric catalysis due to a fairly thorough knowledge of its catalytic cycles. Four major themes have been investigated as a result of this insight: (1) rational design of a chiral Cp#Co(III)-catalyst, (2) chiral carboxylic acid with achiral Cp*Co(III)-catalysts using monodentate directing groups, (3) cobalt/salox-based systems, and (4) cobalt/chiral phosphoric acid-based hybrid systems with bidentate directing groups. Herein, we highlight the recent developments in high-valent cobalt-catalyzed enantioselective C-H functionalization up to October 2023, with the strong belief that the current state-of-the-art can attract considerable interest in the synthetic community, encouraging discoveries in the evolving landscape of asymmetric catalysis.

Reversal of Regioselectivity in Asymmetric C-H Bond Annulation with Bromoalkynes under Cobalt Catalysis.

Metal-catalyzed asymmetric C-H bond annulation strategy offers a versatile platform, allowing the construction of complex P-chiral molecules through atom- and step-economical fashion. However, regioselective insertion of π-coupling partner between M-C bond with high enantio-induction remain elusive. Using commercially available Co(II) salt and chiral-Salox ligands, we demonstrate an unusual protocol for the regio-reversal, enantioselective C-H bond annulation of phosphinamide with bromoalkyne through desymmetrization. The reaction proceeds through ligand-assisted enantiodetermining cyclocobaltation followed by regioselective insertion of bromoalkyne between Co-C, subsequent reductive elimination, and halogen exchange with carboxylate resulted in P-stereogenic compounds in excellent ee (up to >99 %). The isolation of cobaltacycle involved in the catalytic cycle and the outcome of control experiments provide support for a plausible mechanism.

Abscisic acid priming confers salt tolerance in maize seedlings by modulating osmotic adjustment, bond energies, ROS homeostasis, and organic acid metabolism.

This study aimed at investigating the influence of exogenous abscisic acid (ABA) on salt homeostasis under 100 mM NaCl stress in maize (Zea mays L. cv. Kaveri 50) through 3 and 5 days of exposure. The ratio of Na+ to K+, hydrogen peroxide (H2O2) and superoxide (O2•‒) accumulation, electrolyte leakage were the major determinants for salt sensitivity. Pretreatment with ABA [ABA (+)] had altered the salt sensitivity of plants maximally through 5 days of treatment. Plants controlled well for endogenous ABA level (92% increase) and bond energy minimization of cell wall residues to support salt tolerance proportionately to ABA (+). Salt stress was mitigated through maintenance of relative water content (RWC) (16%), glycine betaine (GB) (26%), proline (28%) and proline biosynthesis enzyme (ΔP5CS) (26%) under the application of ABA (+). Minimization of lipid peroxides (6% decrease), carbonyl content (9% decrease), acid, alkaline phosphatase activities were more tolerated under 100 mM salinity at 5 days duration. Malate metabolism for salt tolerance was dependent on the activity of the malic enzyme, malate dehydrogenase through transcript abundance in real-time manner as a function of ABA (+). Establishment of oxidative stress through days under salinity recorded by NADPH-oxidase activity (39% increase) following ROS generation as detected in tissue specific level. The ABA (+) significantly altered redox homeostasis through ratio of AsA to DHA (21% increase), GSH to GSSG (12% increase) by dehydroascorbate reductase and glutathione reductase respectively, and other enzymes like guaiacol peroxidase, catalase, glutathione reductase activities. The ABA in priming was substantially explained in stress metabolism as biomarker for salinity stress with reference to maize.

Regulation of NADP-Malic Enzyme Activity in Maize (Zea mays L.) under Salinity with Reference to Light and Darkness.

We revealed the functional characterization of C4-NADP-malic enzyme (NADP-ME), extracted and partially purified from maize (Zea mays L. cv. Kaveri 50). The leaf discs were previously activated under 1000-1200 µE m-2 s-1, incubated in bicarbonate (2.0 mM) solution, and subjected to salt stress (100 mM NaCl). Initially, salt stress was evident from the accumulations of proline, chlorophyll content, carbohydrate profile, and Hill activity influencing the C4 enzyme. Primarily, in illuminated tissues, the activity of the enzyme recorded a reduced trend through salinity irrespective of light and darkness compared to the control. On illumination, the kinetic parameters such as Vmax of the enzyme increased by 1.36-fold compared to in the dark under salinity whereas Km was decreased by 20% under the same condition. The extent of light induction was proportionate to limiting (0.01 mM) and saturated (4.0 mM) malate concentrations for enzyme activity. Moreover, the catalytic properties of the enzyme were also tested on concomitant responses to activator (citrate and succinate) and inhibitor (oxalate and pyruvate) residues. The sensitivity to light and dark effects was also tested for reducing agents such as dithiothreitol, suggesting the effect of the changes in redox on the regulatory properties of the enzyme. The ratio of enzyme activity under light and darkness in the presence or absence of a reducing agent was concomitantly increased with varying malate concentrations. At the molecular level, protein polymorphism of the enzyme represented minor variations in band intensities, however, not in numbers through salinity subjected to light and darkness. Therefore, salinity-induced changes in the decarboxylation reaction, evident by NADP-ME activity, may be based on the redox property of regulatory sites and sensitivity to light and darkness.

Room-temperature C-H bond alkynylation by merging cobalt and photocatalysts.

A new protocol is developed for the mono- and bis-ortho-C-H alkynylation of easily accessible benzamide derivatives using alkynyl bromides at room temperature by merging cobalt and photocatalysts. The diverse reactivity of various alkynyl bromides towards the C-H alkynylation and competing C-H/N-H bond annulation reactions has been demonstrated to give the corresponding products in good yields with excellent functional group tolerance.

Quantitative analysis of brain herniation from non-contrast CT images using deep learning.

BACKGROUND: Brain herniation is one of the fatal outcomes of increased intracranial pressure (ICP). It is caused due to the presence of hematoma or tumor mass in the brain. Ideal midline (iML) divides the healthy brain into two (right and left) nearly equal hemispheres. In the presence of hematoma, the midline tends to shift from its original position to the contralateral side of the mass and thus develops a deformed midline (dML). NEW METHOD: In this study, a convolutional neural network (CNN) was used to predict the deformed left and right hemispheres. The proposed algorithm was validated with non-contrast computed tomography (NCCT) of (n = 45) subjects with two types of brain hemorrhages - epidural hemorrhage (EDH): (n = 5) and intra-parenchymal hemorrhage (IPH): (n = 40)). RESULTS: The method demonstrated excellent potential in automatically predicting MLS with the average errors of 1.29 mm by location, 66.4 mm2 by 2D area, and 253.73 mm3 by 3D volume. Estimated MLS could be well correlated with other clinical markers including hematoma volume - R2 = 0.86 (EDH); 0.48 (IPH) and a Radiologist-defined severity score (RSS) - R2 = 0.62 (EDH); 0.57 (IPH). RSS was found to be even better correlated (R2 = 0.98 (EDH); 0.70 (IPH)), hence better predictable by a joint correlation between hematoma volume, midline pixel- or voxel-shift, and minimum distance of (ideal or deformed) midline from the hematoma (boundary or centroid). CONCLUSION: All these predictors were computed automatically, which highlighted the excellent clinical potential of the proposed automated method in midline shift (MLS) estimation and severity prediction in hematoma decision support systems.

Two-Stream Region Convolutional 3D Network for Temporal Activity Detection.

We address the problem of temporal activity detection in continuous, untrimmed video streams. This is a difficult task that requires extracting meaningful spatio-temporal features to capture activities, accurately localizing the start and end times of each activity. We introduce a new model, Region Convolutional 3D Network (R-C3D), which encodes the video streams using a three-dimensional fully convolutional network, then generates candidate temporal regions containing activities and finally classifies selected regions into specific activities. Computation is saved due to the sharing of convolutional features between the proposal and the classification pipelines. We further improve the detection performance by efficiently integrating an optical flow based motion stream with the original RGB stream. The two-stream network is jointly optimized by fusing the flow and RGB feature maps at different levels. Additionally, the training stage incorporates an online hard example mining strategy to address the extreme foreground-background imbalance typically observed in any detection pipeline. Instead of heuristically sampling the candidate segments for the final activity classification stage, we rank them according to their performance and only select the worst performers to update the model. This improves the model without heavy hyper-parameter tuning. Extensive experiments on three benchmark datasets are carried out to show superior performance over existing temporal activity detection methods. Our model achieves state-of-the-art results on the THUMOS'14 and Charades datasets. We further demonstrate that our model is a general temporal activity detection framework that does not rely on assumptions about particular dataset properties by evaluating our approach on the ActivityNet dataset.

Network Consistent Data Association.

Existing data association techniques mostly focus on matching pairs of data-point sets and then repeating this process along space-time to achieve long term correspondences. However, in many problems such as person re-identification, a set of data-points may be observed at multiple spatio-temporal locations and/or by multiple agents in a network and simply combining the local pairwise association results between sets of data-points often leads to inconsistencies over the global space-time horizons. In this paper, we propose a Novel Network Consistent Data Association (NCDA) framework formulated as an optimization problem that not only maintains consistency in association results across the network, but also improves the pairwise data association accuracies. The proposed NCDA can be solved as a binary integer program leading to a globally optimal solution and is capable of handling the challenging data-association scenario where the number of data-points varies across different sets of instances in the network. We also present an online implementation of NCDA method that can dynamically associate new observations to already observed data-points in an iterative fashion, while maintaining network consistency. We have tested both the batch and the online NCDA in two application areas-person re-identification and spatio-temporal cell tracking and observed consistent and highly accurate data association results in all the cases.

Re-Identification in the Function Space of Feature Warps.

Person re-identification in a non-overlapping multicamera scenario is an open challenge in computer vision because of the large changes in appearances caused by variations in viewing angle, lighting, background clutter, and occlusion over multiple cameras. As a result of these variations, features describing the same person get transformed between cameras. To model the transformation of features, the feature space is nonlinearly warped to get the "warp functions". The warp functions between two instances of the same target form the set of feasible warp functions while those between instances of different targets form the set of infeasible warp functions. In this work, we build upon the observation that feature transformations between cameras lie in a nonlinear function space of all possible feature transformations. The space consisting of all the feasible and infeasible warp functions is the warp function space (WFS). We propose to learn a discriminating surface separating these two sets of warp functions in the WFS and to re-identify persons by classifying a test warp function as feasible or infeasible. Towards this objective, a Random Forest (RF) classifier is employed which effectively chooses the warp function components according to their importance in separating the feasible and the infeasible warp functions in the WFS. Extensive experiments on five datasets are carried out to show the superior performance of the proposed approach over state-of-the-art person re-identification methods. We show that our approach outperforms all other methods when large illumination variations are considered. At the same time it has been shown that our method reaches the best average performance over multiple combinations of the datasets, thus, showing that our method is not designed only to address a specific challenge posed by a particular dataset.