SnCl2-catalyzed multicomponent coupling: synthesis of 1,3-oxazolidine derivatives using paraformaldehyde as a C1 feedstock.

SnCl2 catalyzed the three-component coupling of aniline, epoxide, and paraformaldehyde, resulting in the synthesis of 1,3-oxazolidine derivatives. The reaction is simple and does not require any additives, bases, or oxidants, and proceeds at moderate temperature with good functional group tolerance. The scope of the utilization of paraformaldehyde as the methylene source was further extended to the synthesis of benzothiazole and 4,4'-methylenebis(N,N-dimethylaniline) using the same catalyst. A catalytic pathway was proposed based on the control experiments.

Synergizing remote sensing and ecological indicators (RSEIs) for evaluating ecological environmental quality (EEQ) in Asansol Municipal Corporation: an integrated approach.

Human activities have dramatically affected global ecology over the past few decades. Geospatial technologies provide quick, efficient, and quantitative evaluation of spatiotemporal changes in eco-environmental quality (EEQ). This study focuses on a novel approach called remote sensing-based ecological indicators (RSEIs), which has used Landsat imagery data to assess environmental conditions and their changing trends. Four ecological indicators, mainly heatness, dryness, wetness, and greenness, have been used to assess the EEQ in Asansol Municipal Corporation Region (AMCR). Assembling all the indicators to generate RSEI, the principal component analysis (PCA) approach was applied. Our findings show that wetness and greenness favorably impact the province's EEQ, whereas dryness and heat create a negative impact. The RSEI assessment revealed that 24.53 to 28.83% of the area was poor and very poor, whereas the areas with very good decreased from 18.80 to 4.01% from 2001 to 2021 due to urban expansion and industrialization. The relative importance analysis indicates that greenness has a positive relation with RSEI, and dryness and heatness have a negative relation with RSEI. Finally, the receiving operating characteristic (ROC) was used for validation (AUC-0.885) of the RSEI. This study offers valuable insights for ecological management decision-making, guiding planners, and policymakers.

Application of extreme learning machine (ELM) forecasting model on CO2 emission dataset of a natural gas-fired power plant in Dhaka, Bangladesh.

Understanding and predicting CO2 emissions from individual power plants is crucial for developing effective mitigation strategies. This study analyzes and forecasts CO2 emissions from an engine-based natural gas-fired power plant in Dhaka Export Processing Zone (DEPZ), Bangladesh. This study also presents a rich dataset and ELM-based prediction model for a natural gas-fired plant in Bangladesh. Utilizing a rich dataset of Electricity generation and Gas Consumption, CO2 emissions in tons are estimated based on the measured energy use, and the ELM models were trained on CO2 emissions data from January 2015 to December 2022 and used to forecast CO2 emissions until December 2026. This study aims to improve the understanding and prediction of CO2 emissions from natural gas-fired power plants. While the specific operational strategy of the studied plant is not available, the provided data can serve as a valuable baseline or benchmark for comparison with similar facilities and the development of future research on optimizing operations and CO2 mitigation strategies. The Extreme Learning Machine (ELM) modeling method was employed due to its efficiency and accuracy in prediction. The ELM models achieved performance metrics Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Scaled Error (MASE), values respectively 3494.46 (<5000), 2013.42 (<2500), and 0.93 close to 1, which falls within the acceptable range. Although natural gas is a cleaner alternative, emission reduction remains essential. This data-driven approach using a Bangladeshi case study provides a replicable framework for optimizing plant operations and measuring and forecasting CO2 emissions from similar facilities, contributing to global climate change.

MYB4, a member of R2R3-subfamily of MYB transcription factor functions as a repressor of key genes involved in flavonoid biosynthesis and repair of UV-B induced DNA double strand breaks in Arabidopsis.

Plants accumulate flavonoids as part of UV-B acclimation, while a high level of UV-B irradiation induces DNA damage and leads to genome instability. Here, we show that MYB4, a member of the R2R3-subfamily of MYB transcription factor plays important role in regulating plant response to UV-B exposure through the direct repression of the key genes involved in flavonoids biosynthesis and repair of DNA double-strand breaks (DSBs). Our results demonstrate that MYB4 inhibits seed germination and seedling establishment in Arabidopsis following UV-B exposure. Phenotype analyses of atmyb4-1 single mutant line along with uvr8-6/atmyb4-1, cop1-6/atmyb4-1, and hy5-215/atmyb4-1 double mutants indicate that MYB4 functions downstream of UVR8 mediated signaling pathway and negatively affects UV-B acclimation and cotyledon expansion. Our results indicate that MYB4 acts as transcriptional repressor of two key flavonoid biosynthesis genes, including 4CL and FLS, via directly binding to their promoter, thus reducing flavonoid accumulation. On the other hand, AtMYB4 overexpression leads to higher accumulation level of DSBs along with repressed expression of several key DSB repair genes, including AtATM, AtKU70, AtLIG4, AtXRCC4, AtBRCA1, AtSOG1, AtRAD51, and AtRAD54, respectively. Our results further suggest that MYB4 protein represses the expression of two crucial DSB repair genes, AtKU70 and AtXRCC4 through direct binding with their promoters. Together, our results indicate that MYB4 functions as an important coordinator to regulate plant response to UV-B through transcriptional regulation of key genes involved in flavonoids biosynthesis and repair of UV-B induced DNA damage.

Empowering real-time flood impact assessment through the integration of machine learning and Google Earth Engine: a comprehensive approach.

Floods cause substantial losses to life and property, especially in flood-prone regions like northwestern Bangladesh. Timely and precise evaluation of flood impacts is critical for effective flood management and decision-making. This research demonstrates an integrated approach utilizing machine learning and Google Earth Engine to enable real-time flood assessment. Synthetic aperture radar (SAR) data from Sentinel-1 and the Google Earth Engine platform were employed to generate near real-time flood maps of the 2020 flood in Kurigram and Lalmonirhat. An automatic thresholding technique quantified flooded areas. For land use/land cover (LULC) analysis, Sentinel-2's high resolution and machine learning models like artificial neural networks (ANN), random forests (RF) and support vector machines (SVM) were leveraged. ANN delivered the best LULC mapping with 0.94 accuracy based on metrics like accuracy, kappa, mean F1 score, mean sensitivity, mean specificity, mean positive predictive value, mean negative value, mean precision, mean recall, mean detection rate and mean balanced accuracy. Results showed over 600,000 people exposed at peak inundation in July-about 17% of the population. The machine learning-enabled LULC maps reliably identified vulnerable areas to prioritize flood management. Over half of croplands flooded in July. This research demonstrates the potential of integrating SAR, machine learning and cloud computing to empower authorities through real-time monitoring and accurate LULC mapping essential for effective flood response. The proposed comprehensive methodology can assist stakeholders in developing data-driven flood management strategies to reduce impacts.

Aminocarbonylation Reaction Using a Pd-Sn Heterobimetallic Catalyst: Three-Component Coupling for Direct Access of the Amide Functionality.

A heterobimetallic "Pd-Sn" catalyst, namely, PdCl(PPh3)2SnCl3, efficiently catalyzes the aminocarbonylation reaction of aryl iodides with amines under the atmospheric pressure of CO in the absence of a base and additive. Primary, secondary, and alkyl amines all afforded the corresponding amides in good to excellent yields with high selectivity. A broad range of functional groups were tolerated. The method was further extended to the synthesis of biologically active isoindoline-1,3-diones in the presence of triethylamine. A mechanism is proposed for the reaction.

Identification of influential weather parameters and seasonal drought prediction in Bangladesh using machine learning algorithm.

Droughts pose a severe environmental risk in countries that rely heavily on agriculture, resulting in heightened levels of concern regarding food security and livelihood enhancement. Bangladesh is highly susceptible to environmental hazards, with droughts further exacerbating the precarious situation for its 170 million inhabitants. Therefore, we are endeavouring to highlight the identification of the relative importance of climatic attributes and the estimation of the seasonal intensity and frequency of droughts in Bangladesh. With a period of forty years (1981-2020) of weather data, sophisticated machine learning (ML) methods were employed to classify 35 agroclimatic regions into dry or wet conditions using nine weather parameters, as determined by the Standardized Precipitation Evapotranspiration Index (SPEI). Out of 24 ML algorithms, the four best ML methods, ranger, bagEarth, support vector machine, and random forest (RF) have been identified for the prediction of multi-scale drought indices. The RF classifier and the Boruta algorithms shows that water balance, precipitation, maximum and minimum temperature have a higher influence on drought intensity and occurrence across Bangladesh. The trend of spatio-temporal analysis indicates, drought intensity has decreased over time, but return time has increased. There was significant variation in changing the spatial nature of drought intensity. Spatially, the drought intensity shifted from the northern to central and southern zones of Bangladesh, which had an adverse impact on crop production and the livelihood of rural and urban households. So, this precise study has important implications for the understanding of drought prediction and how to best mitigate its impacts. Additionally, the study emphasizes the need for better collaboration between relevant stakeholders, such as policymakers, researchers, communities, and local actors, to develop effective adaptation strategies and increase monitoring of weather conditions for the meticulous management of droughts in Bangladesh.

SOG1 and BRCA1 Interdependently Regulate RAD54 Expression for Repairing Salinity-Induced DNA Double-Strand Breaks in Arabidopsis.

As sessile organisms, land plants experience various forms of environmental stresses throughout their life span. Therefore, plants have developed extensive and complicated defense mechanisms, including a robust DNA damage response (DDR) and DNA repair systems for maintaining genome integrity. In Arabidopsis, the NAC [NO APICAL MERISTEM (NAM), ARABIDOPSIS TRANSCRIPTION ACTIVATION FACTOR (ATAF), CUP-SHAPED COTYLEDON (CUC)] domain family transcription factor SUPPRESSOR OF GAMMA RESPONSE 1 (SOG1) plays an important role in regulating DDR. Here, we show that SOG1 plays a key role in regulating the repair of salinity-induced DNA double-strand breaks (DSBs) via the homologous recombination (HR) pathway in Arabidopsis. The sog1-1 mutant seedlings display a considerably slower rate of repair of salinity-induced DSBs. Accumulation of SOG1 protein increases in wild-type Arabidopsis under salinity stress, and it enhances the expression of HR pathway-related genes, including RAD51, RAD54 and BReast CAncer gene 1 (BRCA1), respectively, as found in SOG1 overexpression lines. SOG1 binds specifically to the AtRAD54 promoter at the 5'-(N)4GTCAA(N)3C-3' consensus sequence and positively regulates its expression under salinity stress. The phenotypic responses of sog1-1/atrad54 double mutants suggest that SOG1 functions upstream of RAD54, and both these genes are essential in regulating DDR under salinity stress. Furthermore, SOG1 interacts directly with BRCA1, an important component of the HR-mediated DSB repair pathway in plants, where BRCA1 appears to facilitate the binding of SOG1 to the RAD54 promoter. At the genetic level, SOG1 and BRCA1 function interdependently in modulating RAD54 expression under salinity-induced DNA damage. Together, our results suggest that SOG1 regulates the repair of salinity-induced DSBs via the HR-mediated pathway through genetic interactions with RAD54 and BRCA1 in Arabidopsis.

A Pd-Sn heterobimetallic catalyst for carbonylative Suzuki, Sonogashira and aminocarbonylation reactions using chloroform as a CO surrogate.

Herein, we report a heterobimetallic Pd-Sn catalyst for the carbonylative Suzuki coupling, aminocarbonylation reaction, and carbonylative Sonogashira coupling of aryl halides with boronic acids, amines, and aromatic alkynes leading to a three-component coupling reaction using in situ generated carbon monoxide. Under the optimized reaction conditions, a variety of bisaryl ketones, amides, and aromatic ynones have been synthesized in moderate to good yields in a one-pot fashion. The reported catalyst has wide reaction scope with good functional group tolerance.

Mapping and decoding cortical engagement during motor imagery, mental arithmetic, and silent word generation using MEG.

Accurate quantification of cortical engagement during mental imagery tasks remains a challenging brain-imaging problem with immediate relevance to developing brain-computer interfaces. We analyzed magnetoencephalography (MEG) data from 18 individuals completing cued motor imagery, mental arithmetic, and silent word generation tasks. Participants imagined movements of both hands (HANDS) and both feet (FEET), subtracted two numbers (SUB), and silently generated words (WORD). The task-related cortical engagement was inferred from beta band (17-25 Hz) power decrements estimated using a frequency-resolved beamforming method. In the hands and feet motor imagery tasks, beta power consistently decreased in premotor and motor areas. In the word and subtraction tasks, beta-power decrements showed engagements in language and arithmetic processing within the temporal, parietal, and inferior frontal regions. A support vector machine classification of beta power decrements yielded high accuracy rates of 74 and 68% for classifying motor-imagery (HANDS vs. FEET) and cognitive (WORD vs. SUB) tasks, respectively. From the motor-versus-nonmotor contrasts, excellent accuracy rates of 85 and 80% were observed for hands-versus-word and hands-versus-sub, respectively. A multivariate Gaussian-process classifier provided an accuracy rate of 60% for the four-way (HANDS-FEET-WORD-SUB) classification problem. Individual task performance was revealed by within-subject correlations of beta-decrements. Beta-power decrements are helpful metrics for mapping and decoding cortical engagement during mental processes in the absence of sensory stimuli or overt behavioral outputs. Markers derived based on beta decrements may be suitable for rehabilitation purposes, to characterize motor or cognitive impairments, or to treat patients recovering from a cerebral stroke.

Advanced biotechnological strategies towards the development of crops with enhanced micronutrient content.

Micronutrients are essential mineral elements required for both plant and human development.An integrated system involving soil, climatic conditions, and types of crop plants determines the level of micronutrient acquisition and utilization. Most of the staple food crops consumed globally predominantly include the cereal grains, tubers and roots, respectively and in many cases, particularly in the resource-poor countries they are grown in nutrient-deficient soils. These situations frequently lead to micronutrient deficiency in crops. Moreover, crop plants with micronutrient deficiency also show high level of susceptibility to various abiotic and biotic stress factors. Apart from this, climate change and soil pollution severely affect the accumulation of micronutrients, such as zinc (Zn), iron (Fe), selenium (Se), manganese (Mn), and copper (Cu) in food crops. Therefore, overcoming the issue of micronutrient deficiency in staple crops and to achieve the adequate level of food production with enriched nutrient value is one of the major global challenges at present. Conventional breeding approaches are not adequate to feed the increasing global population with nutrient-rich staple food crops. To address these issues, alongside traditional approaches, genetic modification strategies have been adopted during the past couple of years in order to enhance the transport, production, enrichment and bioavailability of micronutrients in staple crops. Recent advances in agricultural biotechnology and genome editing approaches have shown promising response in the development of micronutrient enriched biofortified crops. This review highlights the current advancement of our knowledge on the possible implications of various biotechnological tools for the enrichment and enhancement of bioavailability of micronutrients in crops.

Exposure to Low UV-B Dose Induces DNA Double-Strand Breaks Mediated Onset of Endoreduplication in Vigna radiata (L.) R. Wilczek Seedlings.

Multiple lines of evidence indicate that solar UV-B light acts as an important environmental signal in plants, regulating various cellular and metabolic activities, gene expression, growth and development. Here, we show that low levels of UV-B (4.0 kJ m-2) significantly influence plant response during early seedling development in the tropical legume crop Vigna radiata (L.) R. Wilczek. Exposure to low doses of UV-B showed relatively less growth inhibition yet remarkably enhanced lateral root formation in seedlings. Both low and high (8.0 kJ m-2) doses of UV-B treatment induced DNA double-strand breaks and activated the SOG1-related ATM-ATR-mediated DNA damage response pathway. These effects led to G2-M-phase arrest with a compromised expression of the key cell cycle regulators, including CDKB1;1, CDKB2;1 and CYCB1;1, respectively. However, along with these effects, imbibitional exposure of seeds to a low UV-B dose resulted in enhanced accumulation of FZR1/CCS52A, E2Fa and WEE1 kinase and prominent induction of endoreduplication in 7-day-old seedlings. Low dose of UV-B mediated phenotypical responses, while the onset of endoreduplication appeared to be regulated at least in part via UV-B induced reactive oxygen species accumulation. Transcriptome analyses further revealed a network of co-regulated genes associated with DNA repair, cell cycle regulation and oxidative stress response pathways that are activated upon exposure to low doses of UV-B.

An Insight Into the Mechanism of Plant Organelle Genome Maintenance and Implications of Organelle Genome in Crop Improvement: An Update.

Besides the nuclear genome, plants possess two small extra chromosomal genomes in mitochondria and chloroplast, respectively, which contribute a small fraction of the organelles' proteome. Both mitochondrial and chloroplast DNA have originated endosymbiotically and most of their prokaryotic genes were either lost or transferred to the nuclear genome through endosymbiotic gene transfer during the course of evolution. Due to their immobile nature, plant nuclear and organellar genomes face continuous threat from diverse exogenous agents as well as some reactive by-products or intermediates released from various endogenous metabolic pathways. These factors eventually affect the overall plant growth and development and finally productivity. The detailed mechanism of DNA damage response and repair following accumulation of various forms of DNA lesions, including single and double-strand breaks (SSBs and DSBs) have been well documented for the nuclear genome and now it has been extended to the organelles also. Recently, it has been shown that both mitochondria and chloroplast possess a counterpart of most of the nuclear DNA damage repair pathways and share remarkable similarities with different damage repair proteins present in the nucleus. Among various repair pathways, homologous recombination (HR) is crucial for the repair as well as the evolution of organellar genomes. Along with the repair pathways, various other factors, such as the MSH1 and WHIRLY family proteins, WHY1, WHY2, and WHY3 are also known to be involved in maintaining low mutation rates and structural integrity of mitochondrial and chloroplast genome. SOG1, the central regulator in DNA damage response in plants, has also been found to mediate endoreduplication and cell-cycle progression through chloroplast to nucleus retrograde signaling in response to chloroplast genome instability. Various proteins associated with the maintenance of genome stability are targeted to both nuclear and organellar compartments, establishing communication between organelles as well as organelles and nucleus. Therefore, understanding the mechanism of DNA damage repair and inter compartmental crosstalk mechanism in various sub-cellular organelles following induction of DNA damage and identification of key components of such signaling cascades may eventually be translated into strategies for crop improvement under abiotic and genotoxic stress conditions. This review mainly highlights the current understanding as well as the importance of different aspects of organelle genome maintenance mechanisms in higher plants.

An insight into understanding the coupling between homologous recombination mediated DNA repair and chromatin remodeling mechanisms in plant genome: an update.

Plants, with their obligatory immobility, are vastly exposed to a wide range of environmental agents and also various endogenous processes, which frequently cause damage to DNA and impose genotoxic stress. These factors subsequently increase genome instability, thus affecting plant growth and productivity. Therefore, to survive under frequent and extreme environmental stress conditions, plants have developed highly efficient and powerful defense mechanisms to repair the damages in the genome for maintaining genome stability. Such multi-dimensional signaling response, activated in presence of damage in the DNA, is collectively known as DNA Damage Response (DDR). DDR plays a crucial role in the remarkably efficient detection, signaling, and repair of damages in the genome for maintaining plant genome stability and normal growth responses. Like other highly advanced eukaryotic systems, chromatin dynamics play a key role in regulating cell cycle progression in plants through remarkable orchestration of environmental and developmental signals. The regulation of chromatin architecture and nucleosomal organization in DDR is mainly modulated by the ATP dependent chromatin remodelers (ACRs), chromatin modifiers, and histone chaperones. ACRs are mainly responsible for transcriptional regulation of several homologous recombination (HR) repair genes in plants under genotoxic stress. The HR-based repair of DNA damage has been considered as the most error-free mechanism of repair and represents one of the essential sources of genetic diversity and new allelic combinations in plants. The initiation of DDR signaling and DNA damage repair pathway requires recruitment of epigenetic modifiers for remodeling of the damaged chromatin while accumulating evidence has shown that chromatin remodeling and DDR share part of the similar signaling pathway through the altered epigenetic status of the associated chromatin region. In this review, we have integrated information to provide an overview on the association between chromatin remodeling mediated regulation of chromatin structure stability and DDR signaling in plants, with emphasis on the scope of the utilization of the available knowledge for the improvement of plant health and productivity.Abbreviation: ADH: Alcohol Dehydrogenase; AGO2: Argonaute 2; ARP: Actin-Related Protein; ASF:1- Anti-Silencing Function-1; ATM: Ataxia Telangiectasia Mutated; ATR: ATM and Rad3- Related; AtSWI3c: Arabidopsis thaliana Switch 3c; ATXR5: Arabidopsis Trithorax-Related5; ATXR6: Arabidopsis Trithorax-Related6; BER: Base Excision Repair; BRCA1: Breast Cancer Associated 1; BRM: BRAHMA; BRU1: BRUSHY1; CAF:1- Chromatin Assembly Factor-1; CHD: Chromodomain Helicase DNA; CHR5: Chromatin Remodeling Protein 5; CHR11/17: Chromatin Remodeling Protein 11/17; CIPK11- CBL- Interacting Protein Kinase 11; CLF: Curly Leaf; CMT3: Chromomethylase 3; COR15A: Cold Regulated 15A; COR47: Cold Regulated 47; CRISPR: Clustered Regulatory Interspaced Short Palindromic Repeats; DDM1: Decreased DNA Methylation1; DRR: DNA Repair and Recombination; DSBs: Double-Strand Breaks; DDR: DNA Damage Response; EXO1: Exonuclease 1; FAS1/2: Fasciata1/2; FACT: Facilitates Chromatin Transcription; FT: Flowering Locus T; GMI1: Gamma-Irradiation And Mitomycin C Induced 1; HAC1: Histone Acetyltransferase of the CBP Family 1; HAM1: Histone Acetyltransferase of the MYST Family 1; HAM2: Histone Acetyltransferase of the MYST Family 2; HAF1: Histone Acetyltransferase of the TAF Family 1; HAT: Histone Acetyl Transferase; HDA1: Histone Deacetylase 1; HDA6: Histone Deacetylase 6; HIRA: Histone Regulatory Homolog A; HR- Homologous recombination; HAS: Helicase SANT Associated; HSS: HAND-SLANT-SLIDE; ICE1: Inducer of CBF Expression 1; INO80: Inositol Requiring Mutant 80; ISW1: Imitation Switch 1; KIN1/2: Kinase 1 /2; MET1: Methyltransferase 1; MET2: Methyltransferase 2; MINU: MINUSCULE; MMS: Methyl Methane Sulfonate; MMS21: Methyl Methane Sulfonate Sensitivity 21; MRN: MRE11, RAD50 and NBS1; MSI1: Multicopy Suppressor Of Ira1; NAP1: Nucleosome Assembly Protein 1; NRP1/NRP2: NAP1-Related Protein; NER: Nucleotide Excision Repair; NHEJ: Non-Homologous End Joining; PARP1: Poly-ADP Ribose Polymerase; PIE1: Photoperiod Independent Early Flowering 1; PIKK: Phosphoinositide 3-Kinase-Like Kinase; PKL: PICKLE; PKR1/2: PICKLE Related 1/2; RAD: Radiation Sensitive Mutant; RD22: Responsive To Desiccation 22; RD29A: Responsive To Desiccation 29A; ROS: Reactive Oxygen Species; ROS1: Repressor of Silencing 1; RPA1E: Replication Protein A 1E; SANT: Swi3, Ada2, N-Cor and TFIIIB; SEP3: SEPALLATA3; SCC3: Sister Chromatid Cohesion Protein 3; SMC1: Structural Maintenance of Chromosomes Protein 1; SMC3: Structural Maintenance of Chromosomes Protein 3; SOG1: Suppressor of Gamma Response 1; SWC6: SWR1 Complex Subunit 6; SWR1: SWI2/SNF2-Related 1; SYD: SPLAYED; SMC5: Structural Maintenance of Chromosome 5; SWI/SNF: Switch/Sucrose Non-Fermentable; TALENs: Transcription Activators Like Effector Nucleases; TRRAP: Transformation/Transactivation Domain-Associated Protein; ZFNs: Zinc Finger Nucleases.

SOG1 transcription factor promotes the onset of endoreduplication under salinity stress in Arabidopsis.

As like in mammalian system, the DNA damage responsive cell cycle checkpoint functions play crucial role for maintenance of genome stability in plants through repairing of damages in DNA and induction of programmed cell death or endoreduplication by extensive regulation of progression of cell cycle. ATM and ATR (ATAXIA-TELANGIECTASIA-MUTATED and -RAD3-RELATED) function as sensor kinases and play key role in the transmission of DNA damage signals to the downstream components of cell cycle regulatory network. The plant-specific NAC domain family transcription factor SOG1 (SUPPRESSOR OF GAMMA RESPONSE 1) plays crucial role in transducing signals from both ATM and ATR in presence of double strand breaks (DSBs) in the genome and found to play crucial role in the regulation of key genes involved in cell cycle progression, DNA damage repair, endoreduplication and programmed cell death. Here we report that Arabidopsis exposed to high salinity shows generation of oxidative stress induced DSBs along with the concomitant induction of endoreduplication, displaying increased cell size and DNA ploidy level without any change in chromosome number. These responses were significantly prominent in SOG1 overexpression line than wild-type Arabidopsis, while sog1 mutant lines showed much compromised induction of endoreduplication under salinity stress. We have found that both ATM-SOG1 and ATR-SOG1 pathways are involved in the salinity mediated induction of endoreduplication. SOG1was found to promote G2-M phase arrest in Arabidopsis under salinity stress by downregulating the expression of the key cell cycle regulators, including CDKB1;1, CDKB2;1, and CYCB1;1, while upregulating the expression of WEE1 kinase, CCS52A and E2Fa, which act as important regulators for induction of endoreduplication. Our results suggest that Arabidopsis undergoes endoreduplicative cycle in response to salinity induced DSBs, showcasing an adaptive response in plants under salinity stress.

A magnetoencephalography dataset for motor and cognitive imagery-based brain-computer interface.

Recent advancements in magnetoencephalography (MEG)-based brain-computer interfaces (BCIs) have shown great potential. However, the performance of current MEG-BCI systems is still inadequate and one of the main reasons for this is the unavailability of open-source MEG-BCI datasets. MEG systems are expensive and hence MEG datasets are not readily available for researchers to develop effective and efficient BCI-related signal processing algorithms. In this work, we release a 306-channel MEG-BCI data recorded at 1KHz sampling frequency during four mental imagery tasks (i.e. hand imagery, feet imagery, subtraction imagery, and word generation imagery). The dataset contains two sessions of MEG recordings performed on separate days from 17 healthy participants using a typical BCI imagery paradigm. The current dataset will be the only publicly available MEG imagery BCI dataset as per our knowledge. The dataset can be used by the scientific community towards the development of novel pattern recognition machine learning methods to detect brain activities related to motor imagery and cognitive imagery tasks using MEG signals.

The N-terminal MYB domains affect the stability and folding aspects of Arabidopsis thaliana MYB4 transcription factor under thermal stress.

The MYB4 transcription factor, a member of R2R3-type subfamily of MYB domain protein, plays a key role in the regulation of accumulation of UV-B absorbing phenylpropanoids in Arabidopsis. Although UV-B and thermal stress generate some common stress response, the effect of elevated temperature on the conformational stability of MYB4 remains limited. This study describes the folding and aggregation properties of Arabidopsis MYB4 protein under thermal stress condition. Circular dichroism spectral studies and Bis-ANS binding assays have indicated that the removal of the N-terminal MYB domain affects the structural conformation of the protein and disrupts surface hydrophobic binding sites at higher temperature. Urea-induced equilibrium unfolding studies revealed that the removal of the N-terminal region lowers the thermodynamic stability of MYB4 at elevated temperature. Tryptophan fluorescence spectral pattern and both in vitro and in vivo aggregation studies have revealed the importance of the N-terminal second MYB domain encompassing the N-terminal 62-116 amino acid residues in regulating MYB4 protein stability at higher temperature. On the other hand, comparison of the growth response of wild-type Arabidopsis and atmyb4 mutant line have suggested that MYB4 may not directly affect plant response under thermal stress condition and only marginal role of MYB4 in controlling thermomorphogenesis in Arabidopsis. Interestingly, immunoprecipitation studies have revealed that HSP90 specifically interacts with MYB4 in vivo at the endogenous level, indicating the possible role of HSP90 in governing the stability of MYB4 at elevated temperature in Arabidopsis.

Deep Learning Based Inter-subject Continuous Decoding of Motor Imagery for Practical Brain-Computer Interfaces.

Inter-subject transfer learning is a long-standing problem in brain-computer interfaces (BCIs) and has not yet been fully realized due to high inter-subject variability in the brain signals related to motor imagery (MI). The recent success of deep learning-based algorithms in classifying different brain signals warrants further exploration to determine whether it is feasible for the inter-subject continuous decoding of MI signals to provide contingent neurofeedback which is important for neurorehabilitative BCI designs. In this paper, we have shown how a convolutional neural network (CNN) based deep learning framework can be used for inter-subject continuous decoding of MI related electroencephalographic (EEG) signals using the novel concept of Mega Blocks for adapting the network against inter-subject variabilities. These Mega Blocks have the capacity to repeat a specific architectural block several times such as one or more convolutional layers in a single Mega Block. The parameters of such Mega Blocks can be optimized using Bayesian hyperparameter optimization. The results, obtained on the publicly available BCI competition IV-2b dataset, yields an average inter-subject continuous decoding accuracy of 71.49% (κ = 0.42) and 70.84% (κ = 0.42) for two different training methods such as adaptive moment estimation (Adam) and stochastic gradient descent (SGDM), respectively, in 7 out of 9 subjects. Our results show for the first time that it is feasible to use CNN based architectures for inter-subject continuous decoding with a sufficient level of accuracy for developing calibration-free MI-BCIs for practical purposes.