The Clostridium thermocellum celI gene, coding for endoglucanase I (CelI), consists of an open reading frame (ORF) of 2640 nucleotides and codes for a protein of M(r) 98531. The ORF was confirmed as celI by comparing the N-terminal sequence of purified recombinant CelI with that deduced from the nucleotide sequence. CelI hydrolysed lichenan and carboxymethylcellulose, but was principally active against barley beta-glucan. It exhibited significant sequence identity with subfamily E2 endoglucanases, and by analogy with others in this group contains a catalytic domain of around 500 residues located in the N-terminal half of the protein. The C-terminal region of CelI was highly homologous with the cellulose-binding domain of the non-catalytic cellulosome subunit, S1. A repeated segment, previously shown to be highly conserved in xylanase Z and in other endoglucanases from C. thermocellum, was absent from CelI. Antiserum raised against purified recombinant CelI cross-reacted with proteins contained in the cellulosomes of two strains of C. thermocellu, suggesting that CelI is either a component of the cellulosome or is homologous to other cellulosome proteins. A second gene, located upstream of celI, consisted of an ORF of 1671 nucleotides, coding for a protein of M(r) 61042. Based on its homology with the Escherichia coli tar gene product, the polypeptide encoded by the second gene is tentatively identified as a sensory transducer.
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http://dx.doi.org/10.1099/00221287-139-2-307 | DOI Listing |
PLOS Digit Health
March 2025
Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America.
This paper introduces the Team Card (TC) as a protocol to address harmful biases in the development of clinical artificial intelligence (AI) systems by emphasizing the often-overlooked role of researchers' positionality. While harmful bias in medical AI, particularly in Clinical Decision Support (CDS) tools, is frequently attributed to issues of data quality, this limited framing neglects how researchers' worldviews-shaped by their training, backgrounds, and experiences-can influence AI design and deployment. These unexamined subjectivities can create epistemic limitations, amplifying biases and increasing the risk of inequitable applications in clinical settings.
View Article and Find Full Text PDFHeliyon
February 2025
DISAFA, University of Turin, Grugliasco, Italy.
In organo-mineral fertilizers (OMFs) with low organic carbon (C) final content, the organic fraction enhances the mineral fraction efficiency. Therefore, a high-quality organic fraction is crucial. While geogenic materials like peat have been used extensively for producing high-quality OMFs, exploring alternative organic sources such as biowastes can add circular value to these fertilizers.
View Article and Find Full Text PDFFluid-structure interaction (FSI) can be key in the generation of accurate digital replica of cardiovascular systems. To personalize these models, however, several patient-specific parameters need to be measured, which can be challenging to accomplish in a non-invasive manner. Alternatively, the cardiac kinematics of the patient can be extracted from imaging data and then directly imposed as a dynamic boundary condition in the computational model, also incorporating temporal and spatial measurement errors.
View Article and Find Full Text PDFJ Clin Med
February 2025
BioCardioLab, U.O.C. Bioingegneria, Fondazione Toscana Gabriele Monasterio, 54100 Massa, Italy.
Penetrating aortic ulcer (PAU) is an acute aortic syndrome characterized by a high rupture risk. There are several PAU-treatment procedures indicated for the management of this pathology associated with different effects on vessel morphology and hemodynamics. A deep evaluation of the different types of treatment may be helpful in decision making.
View Article and Find Full Text PDFPLoS Med
February 2025
Department of Gastroenterology and Hepatology, Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America.
Background: An accurate prognostic tool is essential to aid clinical decision-making (e.g., patient triage) and to advance personalized medicine.
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