Pepper immunity against Ralstonia solanacearum is positively regulated by CaWRKY3 through modulation of different WRKY transcription factors.

BACKGROUND: Several WRKY transcription factors (TFs), including CaWRKY6, CaWRKY22, CaWRKY27, and CaWRKY40 are known to govern the resistance of pepper (Capsicum annuum L.) plants to Ralstonia solanacearum infestation (RSI) and other abiotic stresses. However, the molecular mechanisms underlying these processes remain elusive. METHODS: This study functionally described CaWRKY3 for its role in pepper immunity against RSI. The roles of phytohormones in mediating the expression levels of CaWRKY3 were investigated by subjecting pepper plants to 1 mM salicylic acid (SA), 100 µM methyl jasmonate (MeJA), and 100 µM ethylene (ETH) at 4-leaf stage. A virus-induced gene silencing (VIGS) approach based on the Tobacco Rattle Virus (TRV) was used to silence CaWRKY3 in pepper, and transiently over-expressed to infer its role against RSI. RESULTS: Phytohormones and RSI increased CaWRKY3 transcription. The transcriptions of defense-associated marker genes, including CaNPR1, CaPR1, CaDEF1, and CaHIR1 were decreased in VIGS experiment, which made pepper less resistant to RSI. Significant hypersensitive (HR)-like cell death, H2O2 buildup, and transcriptional up-regulation of immunological marker genes were noticed in pepper when CaWRKY3 was transiently overexpressed. Transcriptional activity of CaWRKY3 was increased with overexpression of CaWRKY6, CaWRKY22, CaWRKY27, and CaWRKY40, and vice versa. In contrast, Pseudomonas syringae pv tomato DC3000 (Pst DC3000) was easily repelled by the innate immune system of transgenic Arabidopsis thaliana that overexpressed CaWRKY3. The transcriptions of defense-related marker genes like AtPR1, AtPR2, and AtNPR1 were increased in CaWRKY3-overexpressing transgenic A. thaliana plants. CONCLUSION: It is concluded that CaWRKY3 favorably regulates phytohormone-mediated synergistic signaling, which controls cell death in plant and immunity of pepper plant against bacterial infections.

GhiPLATZ17 and GhiPLATZ22, zinc-dependent DNA-binding transcription factors, promote salt tolerance in upland cotton.

KEY MESSAGE: The utilization of transcriptome analysis, functional validation, VIGS, and DAB techniques have provided evidence that GhiPLATZ17 and GhiPLATZ22 play a pivotal role in improving the salt tolerance of upland cotton. PLATZ (Plant AT-rich sequences and zinc-binding proteins) are known to be key regulators in plant growth, development, and response to salt stress. In this study, we comprehensively analyzed the PLATZ family in ten cotton species in response to salinity stress. Gossypium herbaceum boasts 25 distinct PLATZ genes, paralleled by 24 in G. raimondii, 25 in G. arboreum, 46 in G. hirsutum, 48 in G. barbadense, 43 in G. tomentosum, 67 in G. mustelinum, 60 in G. darwinii, 46 in G. ekmanianum, and a total of 53 PLATZ genes attributed to G. stephensii. The PLATZ gene family shed light on the hybridization and allopolyploidy events that occurred during the evolutionary history of allotetraploid cotton. Ka/Ks analysis suggested that the PLATZ gene family underwent intense purifying selection during cotton evolution. Analysis of synteny and gene collinearity revealed a complex pattern of segmental and dispersed duplication events to expand PLATZ genes in cotton. Cis-acting elements and gene expressions revealed that GhiPLATZ exhibited salt stress resistance. Transcriptome analysis, functional validation, virus-induced gene silencing (VIGS), and diaminobenzidine staining (DAB) demonstrated that GhiPLATZ17 and GhiPLATZ22 enhance salt tolerance in upland cotton. The study can potentially advance our understanding of identifying salt-resistant genes in cotton.

Results of the 2023 ISBI challenge to reduce GABA-edited MRS acquisition time.

PURPOSE: Use a conference challenge format to compare machine learning-based gamma-aminobutyric acid (GABA)-edited magnetic resonance spectroscopy (MRS) reconstruction models using one-quarter of the transients typically acquired during a complete scan. METHODS: There were three tracks: Track 1: simulated data, Track 2: identical acquisition parameters with in vivo data, and Track 3: different acquisition parameters with in vivo data. The mean squared error, signal-to-noise ratio, linewidth, and a proposed shape score metric were used to quantify model performance. Challenge organizers provided open access to a baseline model, simulated noise-free data, guides for adding synthetic noise, and in vivo data. RESULTS: Three submissions were compared. A covariance matrix convolutional neural network model was most successful for Track 1. A vision transformer model operating on a spectrogram data representation was most successful for Tracks 2 and 3. Deep learning (DL) reconstructions with 80 transients achieved equivalent or better SNR, linewidth and fit error compared to conventional 320 transient reconstructions. However, some DL models optimized linewidth and SNR without actually improving overall spectral quality, indicating a need for more robust metrics. CONCLUSION: DL-based reconstruction pipelines have the promise to reduce the number of transients required for GABA-edited MRS.

Laser energy partitioning in nanosecond pulsed laser-induced air breakdown: effect of incident laser energy.

Air breakdown is generated by a 1064 nm nanosecond pulsed laser beam, and laser energy deposited in the breakdown (E d), transmitted through the plasma region (E t) and carried away by the shock wave (E s) is estimated for the incident laser energy (E i) range of 60-273 mJ. The E d is approximately 85% of E i at 60 mJ, rapidly increasing to 92% at 102 mJ. The shock wave front velocity and radius are measured as a function of E i and propagation distance. The shock wave velocity nicely follows the v∝E i0.3 trend predicted by the laser-supported detonation wave model. The Sedov-Taylor theory is used to estimate E s, which rapidly increases with E i, but E i to E s conversion linearly decreases from 83% to 48%. At lower values of E i, most of the laser energy is carried away by the shock wave, whereas the laser energy used in plasma heating or released in the form of electromagnetic and thermal radiation becomes important at higher laser energies. This implies that laser energy partitioning is highly dependent on the value of incident laser energy. These findings provide important insights into the fundamental physics of air breakdown and will be useful in a variety of applications such as laser-induced breakdown spectroscopy, laser ignition, and laser propulsion.

Genetic characterization of flowering and phytochrome genes in peanut (Arachis hypogaea L.) for early maturity.

BACKGROUND: Peanut (Arachis hypogaea L.) production and cropping pattern is highly influenced by the climatic factors including temperature and rain pattern fluctuations. It is one of the most important cash crop in the rain fed areas of Pakistan and its production, under changing climatic conditions, that can be improved by developing short duration varieties. The present study was based on the molecular characterization of the maturity associated gene families in the peanut under two light conditions. METHODS AND RESULTS: Genomic analysis based on the in silico study of important gene families for early maturity associated attributes like flowering time, their pattern, duration and photoperiodism was done for a comprehensive mapping of maturity related genes. Phytochromes genes Phy A, Phy B and Phy E and flowering genes FT2a, Ft5a and COL2 were selected for in silico characterization for protein based analysis including Multiple Sequence Alignment (MSA), and Neighbor Joining (NJ) tree. MSA and NJ trees of the peanut with Arabidopsis thaliana and Glycine max showed a clear picture of the phylogenetic relationship on the basis of selected gene proteins. Expression profile of phytochrome and flowering genes revealed that photoperiod conditions i.e. short and long days, have great influence on the Phy A, Phy B and Phy E, Ft2a, FT5a and COL2 gene expression pattern. In current study, the relative expression of all studied genes was found higher in short day light condition at flower initiation stage of the plants than in the long light day condition with exception of COL2 gene protein. CONCLUSIONS: The molecular characterization based on the in silico study of the particular genes and qPCR based gene expression profiling of the selected genes provided an evidence of the role of these genes and their comparative analysis under two photoperiodic conditions.

Characterization of functional genes GS3 and GW2 and their effect on the grain size of various landraces of rice (Oryza sativa).

BACKGROUND: Grain size is an essential factor of grain quality and yield in rice. The genetic studies have substantially contributed to enhancing yield and maintaining a good quality of rice. The two major genes GS3 (a negative regulator of grain length) and GW2 (a negative regulator of grain width) with functional mutation play a significant role in controlling the grain size of rice. METHODS AND RESULTS: In the study, 17 different widely grown Pakistani landraces of various genetic and geographic backgrounds were evaluated for grain phenotypic traits (1000-grain weight, length, width, and thickness) and also screened for genotypic mutation in GS3 and GW2 genes. Phenotypic data revealed the range for grain weight from 16.86 g (Lateefy) to 26.91 g (PS2), grain length ranged from 7.27 mm (JP-5) to 12.18 mm (PS2), grain width ranged from 2.01 mm (Lateefy) to 3.51 mm (JP5), and grain thickness ranged from 1.79 mm to 2.19. Correlation revealed a negative and significant correlation between grain width and length. There was no significant correlation between grain length and 1000-grain weight and grain width. LSD test displayed that the means of three variables grain length, grain width, and 1000-grain weight were statistically different from one another except grain width and grain breadth. Fifteen accessions carried the domesticated allele of GS3 while JP5 and Fakhr-e-Malakand carried the dominant allele. Similarly, fifteen accessions carried the dominant allele of GW2 while JP-5 and Fakhr-e-Malakand carried the mutant allele. CONCLUSIONS: The study shows that the mutant alleles of both genes are of significance to pyramid them in any breeding program. However, just incorporating favorable alleles is not the sole solution for improving the grain size. Therefore, further elucidation of GS3 and GW2 genes regulatory network, their interaction, trade-off, and pathways will better coordinate their marker-assisted selection in the future breeding program. Additionally, the study concluded that the selection of grain size was not dependent on 1000-grain weight in the selected germplasm.

Effective multiscale deep learning model for COVID19 segmentation tasks: A further step towards helping radiologist.

Infection by the SARS-CoV-2 leading to COVID-19 disease is still rising and techniques to either diagnose or evaluate the disease are still thoroughly investigated. The use of CT as a complementary tool to other biological tests is still under scrutiny as the CT scans are prone to many false positives as other lung diseases display similar characteristics on CT scans. However, fully investigating CT images is of tremendous interest to better understand the disease progression and therefore thousands of scans need to be segmented by radiologists to study infected areas. Over the last year, many deep learning models for segmenting CT-lungs were developed. Unfortunately, the lack of large and shared annotated multicentric datasets led to models that were either under-tested (small dataset) or not properly compared (own metrics, none shared dataset), often leading to poor generalization performance. To address, these issues, we developed a model that uses a multiscale and multilevel feature extraction strategy for COVID19 segmentation and extensively validated it on several datasets to assess its generalization capability for other segmentation tasks on similar organs. The proposed model uses a novel encoder and decoder with a proposed kernel-based atrous spatial pyramid pooling module that is used at the bottom of the model to extract small features with a multistage skip connection concatenation approach. The results proved that our proposed model could be applied on a small-scale dataset and still produce generalizable performances on other segmentation tasks. The proposed model produced an efficient Dice score of 90% on a 100 cases dataset, 95% on the NSCLC dataset, 88.49% on the COVID19 dataset, and 97.33 on the StructSeg 2019 dataset as compared to existing state-of-the-art models. The proposed solution could be used for COVID19 segmentation in clinic applications. The source code is publicly available at https://github.com/RespectKnowledge/Mutiscale-based-Covid-_segmentation-usingDeep-Learning-models.

Progressive ShallowNet for large scale dynamic and spontaneous facial behaviour analysis in children.

COVID-19 has severely disrupted every aspect of society and left negative impact on our life. Resisting the temptation in engaging face-to-face social connection is not as easy as we imagine. Breaking ties within social circle makes us lonely and isolated, that in turns increase the likelihood of depression related disease and even can leads to death by increasing the chance of heart disease. Not only adults, children's are equally impacted where the contribution of emotional competence to social competence has long term implications. Early identification skill for facial behaviour emotions, deficits, and expression may help to prevent the low social functioning. Deficits in young children's ability to differentiate human emotions can leads to social functioning impairment. However, the existing work focus on adult emotions recognition mostly and ignores emotion recognition in children. By considering the working of pyramidal cells in the cerebral cortex, in this paper, we present progressive lightweight shallow learning for the classification by efficiently utilizing the skip-connection for spontaneous facial behaviour recognition in children. Unlike earlier deep neural networks, we limit the alternative path for the gradient at the earlier part of the network by increase gradually with the depth of the network. Progressive ShallowNet is not only able to explore more feature space but also resolve the over-fitting issue for smaller data, due to limiting the residual path locally, making the network vulnerable to perturbations. We have conducted extensive experiments on benchmark facial behaviour analysis in children that showed significant performance gain comparatively.

Chromium Induces Toxicity at Different Phenotypic, Physiological, Biochemical, and Ultrastructural Levels in Sweet Potato (Ipomoea batatas L.) Plants.

Crop productivity is enormously exposed to different environmental stresses, among which chromium (Cr) stress raises considerable concerns and causes a serious threat to plant growth. This study explored the toxic effect of Cr on sweet potato plants. Plants were hydroponically grown, and treatments of 0, 25, 50, 100, and 200 µM Cr were applied for seven days. This study exhibited that a low level of Cr treatment (25 µM) enhanced the growth, biomass, photosynthesis, osmolytes, antioxidants, and enzyme activities. However, significant deleterious effects in growth, biomass, photosynthetic attributes, antioxidants, and enzymes were observed at higher levels of Cr treatment. The remarkable reduction in plant growth traits was associated with the over-accumulation of H2O2 and MDA contents (410% and 577%, respectively) under the highest rate of Cr (200 µM). Under 200 µM Cr, the uptake in the roots were 27.4 mg kg-1 DW, while in shoots were 11 mg kg-1 DW with the highest translocation rate from root to shoot was 0.40. The results showed that the higher accumulation of Cr negatively correlated with the phenotypic and physiological parameters. It may be proposed that Cr toxicity causes oxidative damage as sustained by augmented lipid peroxidation, reactive oxygen species, and reduced photosynthetic rate, chlorophyll, and stomatal traits. The chloroplastic ultrastructure was damaged, and more apparent damage and size reduction were observed at higher Cr levels. Furthermore, aggregated Cr concentration positively correlates with the increase of osmolytes and superoxide dismutase (SOD) activity in the leaves of sweet potato. Moreover, improved osmolytes and SOD do not help protect sweet potato against high Cr stress. Overall, these findings will improve the understanding of the defense mechanisms of sweet potato to Cr stress.

The Remediation in Enzyme's Activities in Plants: Tea Waste as a Modifier to Improve the Efficiency of Growth of Helianthus annuus in Contaminated Soil.

The remediation in plant enzymatic activities in Cd-contaminated soil was monitored through tea waste. Tea is an extensively used beverage worldwide with the release of a high quantity of tea waste utilized in the growing condition of Helianthus annuus on Cd metal contaminated soil. The study was a plan for the natural environmental condition in the greenhouse. For this purpose, four sets of plants were cultivated in triplicate and marked as (i) control, (ii) Cd stress plants, (iii) dry tea waste and Cd stress, and (iv) fresh tea waste and Cd stress. The improved efficiency of biochemical reactions in plants under Cd stress with tea waste treatment was the consequence of blocking Cd movement in the soil through adsorption on tea waste, showing that the tea waste effectively controls the mobility of Cd from the soil to the roots of the plants. Scan electron microscopy (SEM) validates the recovery of the leaves of the plants. The remediation of plant growth and enzyme activities such as amylase, peroxidase, nitrate reductase (NR), and nitrite reductase (NiR) under Cd metal-contaminated soil through tea waste was investigated. The source of tea waste in contaminated soil resulted in the recovery of the photosynthetic process and an improvement in amylase, NR, NiR, and peroxidase activities, thereby resulting in the recovery of pigments coupled with an increase in the biomass of the plants. It was suggested that tea waste acts as a good biosorbent of Cd and energy provider to the plants for normal enzyme activity under Cd stress and may be used by farmers in the future for safe and healthy crops as a cost-effective technology.

The Development of a Green Innovative Bioactive Film for Industrial Application as a New Emerging Technology to Protect the Quality of Fruits.

Today, the most significant challenge encountered by food manufacturers is degradation in the food quality during storage, which is countered by expensive packing, which causes enormous monetary and environmental costs. Edible packaging is a potential alternative for protecting food quality and improving shelf life by delaying microbial growth and providing moisture and gas barrier properties. For the first time, the current article reports the preparation of the new films from Ditriterpenoids and Secomeliacins isolated from Melia azedarach (Dharek) Azadirachta indica plants to protect the quality of fruits. After evaluating these films, their mechanical, specific respirational, coating crystal elongation, elastic, water vapor transmission rate (WVTR), film thickness, and nanoindentation test properties are applied to apple fruit for several storage periods: 0, 3, 6, 9 days. The fruits were evaluated for postharvest quality by screening several essential phytochemical, physiological responses under film coating and storage conditions. It was observed that prepared films were highly active during storage periods. Coated fruits showed improved quality due to the protection of the film, which lowered the transmission rate and enhanced the diffusion rate, followed by an increase in the shelf life. The coating crystals were higher in Film-5 and lower activity in untreated films. It was observed that the application of films through dipping was a simple technique at a laboratory scale, whereas extrusion and spraying were preferred on a commercial scale. The phytochemicals screening of treated fruits during the storage period showed that a maximum of eight important bioactive compounds were present in fruits after the treatment of films. It was resolved that new active films (1-5) were helpful in the effective maintenance of fruit quality and all essential compounds during storage periods. It was concluded that these films could be helpful for fruits growers and the processing industry to maintain fruit quality during the storage period as a new emerging technology.

Isolation and Identification of Bioactive Compounds from Bidens spp. Using HPLC-DAD and GC-MS Analysis and Their Biological Activity as Anticancer Molecules.

The genus Bidens a member of family Compositae, is widely documented as an ethno-medicinally important genus of plants. In the present study, anticancer potential of three ethno-medicinally important species i.e., B. bipinnata, B. biternata and B. pilosa were tested. For in-vitro evaluation, an MTT (Thiazolyl blue tetrazolium bromide) assay was performed against cervical cancer cells (HeLa), hepatocellular carcinoma (HepG), and adenocarcinoma human alveolar basal epithelial cells (A549). For in vivo evaluation, Artemia salina, Danio rerio, and Caenorhabditis elegans were used. Among all the tested extracts, the ethanol extract of B. biternata appeared to have highest anticancer activity, and the compounds responsible for this activity were identified to be Tris (2,4-di-tert-butylphenyl), 4-hydroxy-2,4'-dimethoxychalcone, and 2,4-di-tert-butylphenol. This is the first report of the isolation of Tris (2,4-di-tert-butylphenyl) phosphate from the genus Bidens and the first report of 4-hydroxy-2,4'-dimethoxychalcone and 2,4-di-tert-butylphenol from B. biternata. Among the isolated compounds, 4-hydroxy-2,4'-dimethoxychalcone showed the highest anticancer activity with an LD50 value of 236.7 µg/mL. Therefore, this compound carries promising potential for being established as a pharmaceutical for chemoprevention and chemotherapy.

Isolation, Characterization and Anticancer Activity of Two Bioactive Compounds from Arisaema flavum (Forssk.) Schott.

Medicinal plants play important role in the public health sector worldwide. Natural products from medicinal plants are sources of unlimited opportunities for new drug leads because of their unique chemical diversity. Researchers have focused on exploring herbal products as potential sources for the treatment of cancer, cardiac and infectious diseases. Arisaema flavum (Forssk.) is an important medicinal plant found in the northwest Himalayan regions of Pakistan. It is a poisonous plant and is used as a remedy against snake bites and scorpion stings. In this study, two bioactive compounds were isolated from Arisaema flavum (Forssk.) and their anticancer activity was evaluated against human breast cancer cell line MCF-7 using an MTT assay. The crude extract of Arisaema flavum (Forssk.) was subjected to fractionation using different organic solvents in increasing order of polarity. The fraction indicating maximum activity was then taken for isolation of bioactive compounds using various chromatographic and spectroscopic techniques such as column chromatography, thin-layer chromatography (TLC), gas chromatography−mass spectrometry (GC-MS), Fourier transform infrared spectroscopy (FTIR) and nuclear magnetic resonance spectroscopy (NMR). Crude extract of Arisaema flavum (Forssk.), as well as various fractions extracted in different solvents such as n-hexane, chloroform and ethyl acetate, were tested against human breast cancer cell line MCF-7 using an MTT assay. The crude extract exhibited significant dose-dependent anticancer activity with a maximum activity of 78.6% at 500 µg/mL concentration. Two compounds, hexadecanoic acid ethyl ester with molecular formula C18H36O7 and molar mass 284 and 5-Oxo-19 propyl-docosanoic acid methyl ester with molecular formula C26H50O3 and molecular mass 410, were isolated from chloroform fraction. These compounds were tested against the MCF-7cell line for cytotoxic activity and exhibited a significant (p < 0.00l) decrease in cell numbers for MCF-7 cells with IC50 of 25 µM after 48 h of treatment. Results indicated that Arisaema flavum (Forssk.) possesses compounds with cytotoxic activity that can further be exploited to develop anticancer formulations.

Effective Approaches to Fetal Brain Segmentation in MRI and Gestational Age Estimation by Utilizing a Multiview Deep Inception Residual Network and Radiomics.

To completely comprehend neurodevelopment in healthy and congenitally abnormal fetuses, quantitative analysis of the human fetal brain is essential. This analysis requires the use of automatic multi-tissue fetal brain segmentation techniques. This paper proposes an end-to-end automatic yet effective method for a multi-tissue fetal brain segmentation model called IRMMNET. It includes a inception residual encoder block (EB) and a dense spatial attention (DSAM) block, which facilitate the extraction of multi-scale fetal-brain-tissue-relevant information from multi-view MRI images, enhance the feature reuse, and substantially reduce the number of parameters of the segmentation model. Additionally, we propose three methods for predicting gestational age (GA)-GA prediction by using a 3D autoencoder, GA prediction using radiomics features, and GA prediction using the IRMMNET segmentation model's encoder. Our experiments were performed on a dataset of 80 pathological and non-pathological magnetic resonance fetal brain volume reconstructions across a range of gestational ages (20 to 33 weeks) that were manually segmented into seven different tissue categories. The results showed that the proposed fetal brain segmentation model achieved a Dice score of 0.791±0.18, outperforming the state-of-the-art methods. The radiomics-based GA prediction methods achieved the best results (RMSE: 1.42). We also demonstrated the generalization capabilities of the proposed methods for tasks such as head and neck tumor segmentation and the prediction of patients' survival days.

Impact of heat stress responsive factors on growth and physiology of cotton (Gossypium hirsutum L.).

Pakistan ranked highest with reference to average temperatures in cotton growing areas of the world. The heat waves are becoming more intense and unpredictable due to climate change. Identification of heat tolerant genotypes requires comprehensive screening using molecular, physiological and morphological analysis. Heat shock proteins play an important role in tolerance against heat stress. In the current study, eight heat stress responsive factors, proteins and genes (HSFA2, GHSP26, GHPP2A, HSP101, HSC70-1, HSP3, APX1 and ANNAT8) were evaluated morphologically and physiologically for their role in heat stress tolerance. For this purpose, cotton crop was grown at two temperature conditions i.e. normal weather and heat stress at 45 °C. For molecular analysis, genotypes were screened for the presence or absence of heat shock protein genes. Physiological analysis of genotypes was conducted to assess net photosynthesis, stomatal conductance, transpiration rate, leaf-air temperature and cell membrane stability under control as well as high temperature. The traits photosynthesis, cell membrane stability, leaf-air temperature and number of heat stress responsive factors in each genotypes showed a strong correlation with boll retention percentage under heat stress. The genotypes with maximum heat shock protein genes such as Cyto-177, MNH-886, VH-305 and Cyto-515 showed increased photosynthesis, stomatal conductance, negative leaf-air temperature and high boll retention percentage under heat stress condition. These varieties may be used as heat tolerant breeding material.

Genome-wide identification and characterization of HSP70 gene family in four species of cotton.

Heat shock proteins (HSPs) are important elements of the cellular group of molecular chaperones. Specifically, HSP70 proteins protect cells from being damaged when plants are exposed to environmental stresses. These proteins are catalysts that manage the correct folding of other proteins, and they play a key role in the development of tolerance against biotic and abiotic stresses. In the present study, 113 HSP70 genes were retrieved from the available genome assemblies of four cotton species, including Gossypium hirsutum, G. barbadense, G. arboreum, and G. raimondii. The HSP70 genes were clustered into 11 subfamilies based on phylogeny. One hundred and nine (109) gene duplications were found across these four species. Localization of genes revealed that several HSP70 genes reside in the cytoplasm. Synonymous and non-synonymous substitution rates revealed that functional segregation of HSP70 genes in cotton is due to purifying selection. Furthermore, HSP70 genes in cotton are expressed constitutively during developmental stages. These findings are valuable to understand the complex mechanism of HSP70 gene regulation that occurs in signaling pathways in response to plant stress.

Identification of Raf-Like Kinases B Subfamily Genes in Gossypium Species Revealed GhRAF42 Enhanced Salt Tolerance in Cotton.

Salinity is a critical abiotic factor that significantly reduces agricultural production. Cotton is an important fiber crop and a pioneer on saline soil, hence genetic architecture that underpins salt tolerance should be thoroughly investigated. The Raf-like kinase B-subfamily (RAF) genes were discovered to regulate the salt stress response in cotton plants. However, understanding the RAFs in cotton, such as Enhanced Disease Resistance 1 and Constitutive Triple Response 1 kinase, remains a mystery. This study obtained 29, 28, 56, and 54 RAF genes from G. arboreum, G. raimondii, G. hirsutum, and G. barbadense, respectively. The RAF gene family described allopolyploidy and hybridization events in allotetraploid cotton evolutionary connections. Ka/Ks analysis advocates that cotton evolution was subjected to an intense purifying selection of the RAF gene family. Interestingly, integrated analysis of synteny and gene collinearity suggested dispersed and segmental duplication events involved in the extension of RAFs in cotton. Transcriptome studies, functional validation, and virus-induced gene silencing on salt treatments revealed that GhRAF42 is engaged in salt tolerance in upland cotton. This research might lead to a better understanding of the role of RAFs in plants and the identification of suitable candidate salt-tolerant genes for cotton breeding.

Using HPLC-DAD and GC-MS Analysis Isolation and Identification of Anticandida Compounds from Gui Zhen Cao Herbs (Genus Bidens): An Important Chinese Medicinal Formulation.

Gui Zhen Cao is an herbal formulation that has been documented in Chinese traditional medicine as a remedy for diarrhea, dysentery, inflammation, and toxicity. The sources of this formulation (Bidens pilosa L., Bidens biternata (Lour.) Merr. & Sherff, Bidens bipinnata L.) are also listed in ethnomedicinal reports all over the world. In this study, all these plants are tested for in vitro anticandida activity. A quantitative evaluation of the phytochemicals in all these plants indicated that their vegetative parts are rich in tannins, saponins, oxalates, cyanogenic glycoside and lipids; moreover, the roots have high percentages of alkaloids, flavonoids, and phenols. The results indicated significant anticandida activity, especially for the hexane extract of B. bipinnata leaves which inhibited C. albicans (42.54%), C. glabrata (46.98%), C. tropicalis (50.89%), C. krusei (40.56%), and C. orthopsilosis (50.24%). The extract was subjected to silica gel chromatography and 220 fractions were obtained. Purification by High Performance Liquid Chromatography with Diode-Array Detection (HPLC-DAD) and Gas Chromatography tandem Mass Spectrometry (GC-MS/MS) analysis led to the identification of two anticandida compounds: dehydroabietic and linoleic acid having an inhibition of 85 and 92%, respectively.

Analysis of Peganum harmala, Melia azedarach and Morus alba extracts against six lethal human cancer cells and oxidative stress along with chemical characterization through advance Fourier Transform and Nuclear Magnetic Resonance spectroscopic methods towards green chemotherapeutic agents.

Traditional medicines implicate consumption of plant crude extracts, which may consist of extensive phytochemical diversity. Overall, the most biologically active extract of Peganum harmala (seeds) exhibited significant cytotoxic activity on Artemia salina with LC50 value of 61.547 µg/mL, while P. harmala (roots) [LC50 = 124.229 µg/mL] and M. azedarach (fruits) [LC50 = 147.813 µg/mL] showed moderate cytotoxic potential. P. harmala (seeds) extract also showed the maximum antitumor potential with 52.278 µg/mL LC50. Branches of P. harmala and Morus alba were not active in both bioassays. These outcomes were further reinforced by the levels of phenolics and flavonoids checked against gallic acid and quercetin equivalents, respectively, by standard curves. Current study aims to isolate, structurally characterize and analyze the bioactive compound from plant extracts by using chromatographic and spectrophotometric techniques. Bioactivity guided isolation of extracts led to the isolation of PH-HM-16 from ethyl acetate fraction P. harmala seeds. Chemical structure of PH-HM-16 was elucidated by ESI-MS, 1H NMR, 13C NMR, HSQC and IR spectrum. The results demonstrated significant positive anticancer activities against six human cancer cell lines assessed through MTT cancer cell growth inhibition assay. PH-HM-16 was most effective against prostate cancer cell lines [IC50 = 17.63 µg/mL] followed by breast cancer cell line MCF7 [IC50 value of 41.81 µg/mL]. IC50 value of PH-HM-16 against human myeloid leukemia cell line HL-60 and human colorectal tumor cells HCT-116 was observed as 68.77 µg/mL and 71.54 µg/mL respectively. The IC 50 value of PH-HM-16 compound was not significant against human gastric cancer SGC-7901 (111.89 µg/mL) and human lung adenocarcinoma epithelial cell line A549 (176.04 µg/mL). Isolated bioactive metabolite PH-HM-16 possesses significant antitumor potential so this could be the first step to develop an effective anticancer agent. Hence, this compound represents a promising potential to be chemically standardized or developed into pharmaceuticals for the chemoprevention and/or the treatment of certain types of cancer, especially as adjuvant phytotherapeutics in conventional chemotherapy.

Automatic eye blink artifact removal for EEG based on a sparse coding technique for assessing major mental disorders.

In the electroencephalogram recorded data are often confounded with artifacts, especially in the case of eye blinks. Different methods for artifact detection and removal are discussed in the literature, including automatic detection and removal. Here, an automatic method of eye blink detection and correction is proposed where sparse coding is used for an electroencephalogram dataset. In this method, a hybrid dictionary based on a ridgelet transformation is used to capture prominent features by analyzing independent components extracted from a different number of electroencephalogram channels. In this study, the proposed method has been tested and validated with five different datasets for artifact detection and correction. Results show that the proposed technique is promising as it successfully extracted the exact locations of eye blinking artifacts. The accuracy of the method (automatic detection) is 89.6% which represents a better estimate than that obtained by an extreme machine learning classifier.