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Isolation and characterization of novel bacteriophages targeting Stenotrophomonas maltophilia
Abstract Stenotrophomonas maltophilia is a bacterium often resistant to antibiotics and is a significant cause of nosocomial infections, particularly in immunocompromised patients. Phage therapy has shown promise as a potential treatment for such difficult-to-treat bacterial infections, but research on phages targeting this bacterium is very limited. In this study, we isolated 34 phages using four clinical strains of S. maltophilia and evaluated their infectivity and bactericidal activity. While some phages infected all four strains, many exhibited strain-specific infectivity. We investigated the bacterial growth curves in response to three phages, named Yut1, Yut2, and Yut4, and found that all phages exhibited potent lytic activity against the clinical strains even at low doses. Genome analysis found that the phages did not carry any lysogeny genes, virulence factors, or antibiotic resistance genes, suggesting their high potential as therapeutic phages. Furthermore, phylogenetic analysis suggested that Yut1 and Yut4 belong to a novel phage lineage. These results highlight the therapeutic potential of our novel phages to combat the growing antibiotic resistance problem.
Environmental cues rather than quality of supplemented pollen drive the foraging behaviour of honey bees during avocado pollination
Balancing complexity and accuracy for defect detection on filters with an improved RT-DETR
Lysosomal free sialic acid storage disorder iPSC-derived neural cells display altered glycosphingolipid metabolism
Abstract Lysosomal free sialic acid storage disorder (FSASD) is a rare neurodegenerative disease caused by biallelic mutations in SLC17A5, encoding the lysosomal sialic acid exporter, SLC17A5 (sialin). While the involvement of oligodendroglia in FSASD pathogenesis is established, the roles of other neural cell types remain elusive. In this study, we utilized radial glial cells (iRGCs), immature and mature astrocytes (iIAs and iMAs, respectively), and cortical neurons (iCNs) differentiated from induced pluripotent stem cells (iPSCs) derived from two individuals with FSASD, alongside two independent healthy donors for comparison. We employed a multifaceted profiling approach, including the assessment of cellular glycosphingolipids (GSLs), transcriptomics focused on GSL metabolism genes, and 4-methylumbelliferone-based lysosomal enzyme activity measurements. Our findings revealed significant elevations in free sialic acid levels across all FSASD cell types, indicating that iPSCs and derived iRGCs, iIAs, iMAs and iCNs may be used to model FSASD in vitro. We observed significant alterations in the abundance of specific GSL species, predominantly in mature astrocytes, with fewer changes in other cell types. Transcriptomic analyses uncovered differential expression of genes involved in GSL catabolism, including those encoding glycohydrolases. Enzyme assays corroborated the transcriptomic findings, showing heightened glycohydrolase activities, particularly in mature astrocytes. Collectively, these data may help refine our understanding of neural cell phenotypes and potential contributors to selective vulnerability in FSASD.
Up-regulation of blood-circulating TIM-4-expressing monocytes and potential diagnostic biomarker sTIM-4 in primary liver cancer
A comprehensive analysis of health-related quality of life in thyroid cancer patients using the THYCA-24 questionnaire
FDRL: a data-driven algorithm for forecasting subsidence velocities in Himalayas using conventional and traditional soil features
Cow dung waste as an eco-friendly adsorbent for Alizarin Red S dye removal
Complete spatiotemporal quantification of cardiac motion in mice through multi-view magnetic resonance imaging and super-resolution reconstruction
Abstract Background: Structural indices of cardiac diseases estimated via cardiac magnetic resonance imaging (CMR) have shown promise as early-stage markers. Despite the growing popularity of CMR-based myocardial strain calculations, measures of complete spatiotemporal strains (i.e., three-dimensional strains over the cardiac cycle) remain elusive, especially in mice. The high metabolic rates and rapid cardiac motion affect high-resolution imaging, thus compromising strain accuracy. We hypothesize that a super-resolution reconstruction (SRR) framework that combines low-resolution scans at multiple orientations will enhance the reliability of complete spatiotemporal strains in mice. Methods: Multi-view cine CMR comprising short- and long-axis (SA and LA) fast low angle shot scans were obtained in a cohort of wild-type-mice (n = 5) and a diabetic mouse (n = 1). The “SRR in CMR” approach, consisting of tissue-class -specific scattered data interpolation, was used to generate full four-dimensional (4D) images of high spatial resolution. Image registration using the diffeomorphic demons algorithm was applied to quantify complete spatiotemporal motion in terms of 4D myocardial strains. The effects of SRR on CMR quality were verified in all mice through image metrics, namely, root mean squared error (MSE) and structural similarity index. Strain calculations were validated against an in silico heart model phantom through MSE analysis, followed by investigations of strain accuracy and reproducibility for all mice using MSE and coefficient of variation analyses. Results: SRR-derived strains were validated against a kinematic benchmark established through the in-silico heart model phantom. Improvements in global strain accuracy were confirmed in both in-plane (radial and circumferential) and through-plane (longitudinal) strains. Mouse-specific SRR provided near isotropic spatial resolution, high structural similarity, and minimal loss of contrast, which led to overall improvements in strain reproducibility and intra-cohort homogeneity in wild-type mice, with global longitudinal strain lying of ≈-14%. Conclusions: A comprehensive methodology was presented to quantify complete and reproducible myocardial deformation, aiding in the much-needed standardization of complete spatiotemporal strain analysis in small animals.
Experimental and predictive analysis of deep eutectic solvent gel membranes for efficient CO2 separation
Abstract The capture of Carbon Dioxide (CO2) is very relevant nowadays as global warming hits its peak. The separation of CO2 using membranes has received wide recognition by researchers because of its energy efficiency. Various Ionic Liquid supported membranes have been proven effective in this regard; however, their higher cost and toxicity are limitations, which opens possibilities for Deep Eutectic Solvents (DES). This work explains how DES gel membrane fabrication separates CO2 from CO2/CH4 mixtures. DES, composed of choline chloride and glycerol, is mixed with Pebax1657 polymer, and Polyvinylidene fluoride sheets are used as supports for casting. Fourier transform infrared spectroscopy has been used to confirm the synthesis of DES. X-ray Diffraction and Scanning Electron Microscopy analysis were used to analyse the membrane structure and cross-section. The physicochemical properties of DES are measured at a temperature range from 293.15 to 343.15 K. Pure and mixed gas permeabilities of CO2 and CH4 with increased pressure have been calculated. The highest permeability values obtained for pure and mixed gas CO2 were 138.98 Barrer and 93.17 Barrer, respectively. Density Functional Theory (DFT) is also applied to predict the interaction energy between DES and gas molecules. The efficacy of the DES-gel membrane was evaluated against other DES-supported liquid Membranes, revealing that DES may serve as a viable substitute for hazardous and costly ionic liquids.