The Virulence Polysaccharide of Salmonella Typhi Suppresses Activation of Rho Family GTPases to Limit Inflammatory Responses From Epithelial Cells

Vi capsular polysaccharide (Vi) is a major virulence factor of human typhoid-causing pathogen Salmonella enterica serovar Typhi (S. Typhi). It distinguishes S. Typhi from closely related non-typhoidal Salmonella serovars such as S. Typhimurium which do not normally cause systemic infection in humans. Vi not only forms a capsule around S. Typhi but it is also readily released from this pathogen. We have previously reported that Vi targets prohibitin to inhibit cellular responses activated through immune receptors. Here, we show that engagement of membrane prohibitin with Vi prevents Salmonella-induced activation of small Rho-family GTPases, Rac1, and Cdc42, and suppresses actin cytoskeletal rearrangements resulting in reduced invasion and highly subdued inflammatory responses. Cells infected with S. Typhimurium in the presence of Vi show poor activation of NF-kB and MAP-kinase pathways of intracellular signaling. Treatment with Vi brings about redistribution of Rac-1, prohibitin, and ganglioside GM1 in membrane raft domains. Vi-mediated interference with activation of Rho-family GTPases represents a previously unrecognized mechanism by which S. Typhi can limit its invasion and alarming of the host

Extraction and Characterization of Nanocellulose from Wheat Straw: Facile Approach

The environmental concern occurs due to the extreme use of synthetic materials that have been fortified to develop innovative, multifunctional, and sustainable materials using copious lignocellulosic biomass. In this present study, work was done on the extraction of nanocellulose from wheat straw, and found that wheat straw is an admirable source of cellulose. Chemical processes were used to isolate the cellulose and remove unwanted lignin and hemicellulose from wheat straw followed by sonication, cryo-crushing, and magnetic stirring to achieve nanocellulose. The observed amount of cellulose (36.1%), hemicellulose (30.3%), lignin (17%), and ash content (9.2%) of raw wheat straw. Structural, morphological, and thermal characterization were estimated from FTIR, XRD, FESEM, TEM, DSC, TGA, and AFM for the identification and characterization of extracted cellulose from wheat straw. FTIR showed that the peaks at wavelength 1430.50 cm-1 and 1638.41 cm-1 both show that cellulose is present in the extracted nanocellulose.  Extracted nanocellulose was crystalline and had a 68.96% Crystallinity Index. Morphological analysis, FESEM showed that the untreated wheat straw has an irregular porous structure but the extracted nanocellulose has a regular shape having straight fibers connected. TEM analysis showed that the extracted nanocellulose has a spherical shape structure connected, showing the regular shape, the obtained spherical shape regulates the nanocellulose for further applications. Thermal degradation was observed using TGA which shows that the nanocellulose decomposition was observed around 3600C. AFM determination shows a bell-shaped structure on a smooth surface with a particle height of 3.2 nm and the mean roughness of 110.4 nm was obtained from the extracted nanocellulose. Extracted nanocellulose has a particle size of 58.77 nm

Structural and Morphological Characterization of Nanocellulose Extracted from Cotton Straw Residue

This study is focused on the synthesis and characterization of cotton straw residue. Nanocellulose was synthesized by chemical method and followed by ultrasonication and cryocrushing. The results of the present study show that the cotton straw residue consists of lignin (27%), hemicellulose (15%), cellulose (32%), and ash content  (2.3%). Nanocellulose was characterized by FTIR, XRD, FESEM, TEM, DSC, TGA, and AFM.  Two aromatic rings were observed at wavelength 1650.47cm-1 and  1436.53 cm-1 which indicates that there is a presence of cellulose in the prepared sample which was characterized by FTIR. The structural analysis shows that the material was amorphous and the nanocellulose crystallinity is 23 %. The morphological analysis using FESEM indicates even elongated fiber with a smooth surface and it contains pore in the nanocellulose of cotton residue. TEM analysis indicates that nanocellulose has an irregular shape with a circular rod-like structure of different sizes. The enthalpy of nanocellulose changes at 168.48℃ due to endothermic transition. TGA results show that the nanocellulose is degraded in the temperature range 300-355℃ and low thermal stability was observed during the experiment. AFM  result shows the needle shape particle ( root square mean roughness = 0.1738nm) and the size of nanocellulose was observed 7.1 nm

Application of FTA technology for sampling, recovery and molecular characterization of viral pathogens and virus-derived transgenes from plant tissues

BACKGROUND: Plant viral diseases present major constraints to crop production. Effective sampling of the viruses infecting plants is required to facilitate their molecular study and is essential for the development of crop protection and improvement programs. Retaining integrity of viral pathogens within sampled plant tissues is often a limiting factor in this process, most especially when sample sizes are large and when operating in developing counties and regions remote from laboratory facilities. FTA is a paper-based system designed to fix and store nucleic acids directly from fresh tissues pressed into the treated paper. We report here the use of FTA as an effective technology for sampling and retrieval of DNA and RNA viruses from plant tissues and their subsequent molecular analysis. RESULTS: DNA and RNA viruses were successfully recovered from leaf tissues of maize, cassava, tomato and tobacco pressed into FTA(® )Classic Cards. Viral nucleic acids eluted from FTA cards were found to be suitable for diagnostic molecular analysis by PCR-based techniques and restriction analysis, and for cloning and nucleotide sequencing in a manner equivalent to that offered by tradition isolation methods. Efficacy of the technology was demonstrated both from sampled greenhouse-grown plants and from leaf presses taken from crop plants growing in farmer's fields in East Africa. In addition, FTA technology was shown to be suitable for recovery of viral-derived transgene sequences integrated into the plant genome. CONCLUSION: Results demonstrate that FTA is a practical, economical and sensitive method for sampling, storage and retrieval of viral pathogens and plant genomic sequences, when working under controlled conditions and in the field. Application of this technology has the potential to significantly increase ability to bring modern analytical techniques to bear on the viral pathogens infecting crop plants

Concurrent Overexpression of OsGS1;1 and OsGS2 Genes in Transgenic Rice (Oryza sativa L.): Impact on Tolerance to Abiotic Stresses

Glutamine synthetase (GS) is a key enzyme involved in the nitrogen metabolism of higher plants. Abiotic stresses have adverse effects on crop production and pose a serious threat to global food security. GS activity and expression is known to be significantly modulated by various abiotic stresses. However, very few transgenic overexpression studies of GS have studied its impact on abiotic stress tolerance. GS is also the target enzyme of the broad spectrum herbicide Glufosinate (active ingredient: phosphinothricin). In this study, we investigated the effect of concurrent overexpression of the rice cytosolic GS1 (OsGS1;1) and chloroplastic GS2 (OsGS2) genes in transgenic rice on its tolerance to abiotic stresses and the herbicide Glufosinate. Our results demonstrate that the co-overexpression of OsGS1;1 and OsGS2 isoforms in transgenic rice plants enhanced its tolerance to osmotic and salinity stress at the seedling stage. The transgenic lines maintained significantly higher fresh weight, chlorophyll content, and relative water content than wild type (wt) and null segregant (ns) controls, under both osmotic and salinity stress. The OsGS1;1/OsGS2 co-overexpressing transgenic plants accumulated higher levels of proline but showed lower electrolyte leakage and had lower malondialdehyde (MDA) content under the stress treatments. The transgenic lines showed considerably enhanced photosynthetic and agronomic performance under drought and salinity stress imposed during the reproductive stage, as compared to wt and ns control plants. The grain filling rates of the transgenic rice plants under reproductive stage drought stress (64.6 ± 4.7%) and salinity stress (58.2 ± 4.5%) were significantly higher than control plants, thereby leading to higher yields under these abiotic stress conditions. Preliminary analysis also revealed that the transgenic lines had improved tolerance to methyl viologen induced photo-oxidative stress. Taken together, our results demonstrate that the concurrent overexpression of OsGS1;1 and OsGS2 isoforms in rice enhanced physiological tolerance and agronomic performance under adverse abiotic stress conditions, apparently acting through multiple mechanistic routes. The transgenic rice plants also showed limited tolerance to the herbicide Glufosinate. The advantages and limitations of glutamine synthetase overexpression in crop plants, along with future strategies to overcome these limitations for utilization in crop improvement have also been discussed briefly

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing