Structural studies using 500 MHz 1H NMR spectroscopy on Bam H1 recognition site d(GGATCC)2 in solution at 19 degrees is reported. The resonances from the sugar ring and base protons have been assigned from the 2D-COSY and NOESY spectra. Analyses of the NOESY cross-peaks between the base protons H8/H6 and sugar protons H2'/H2", H3' reveal that the nucleotide units G2, A3 and C6 adopt (C3'-endo, chi = 200 degrees-220 degrees) conformation while G1, T4 and C5 exhibit (C2'-endo, chi = 240 degrees-260 degrees) conformation. NMR data clearly suggest that the two strands of d(GGATCC)2 are conformationally equivalent and there is a structural two-fold between the two A-T pairs. The above information and the NOESY data are used to generate a structural model of d(GGATCC)2. The important features are: (i) G1-G2 stack, the site of cleavage, shows an alternation in sugar pucker i.e. C2'-endo, C3'-endo as in a B-A junction, (ii) G2-A3 stack adopts a mini A-DNA, both the sugars being C3'-endo, (iii) A3-T4 stack, the site of two-fold, displays an A-B junction with alternation in sugar pucker as C3'-endo, C2'-endo, (iv) T4-C5 stack adopts a mini B-DNA both the sugars being C2'-endo and (v) C5-C6 stack exhibits a B-A junction with C2'-endo, C3'-endo sugar puckers. Thus, our studies demonstrate that conformational microheterogeneity with a structural two fold, is present in the Bam H1 recognition site.
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Rev Neurosci
January 2025
557765 Network of Neurosurgery and Artificial Intelligence (NONAI), Universal Scientific Education and Research Network (USERN ), Tehran, Iran.
The recognition and classification of facial expressions using artificial intelligence (AI) presents a promising avenue for early detection and monitoring of neurodegenerative disorders. This narrative review critically examines the current state of AI-driven facial expression analysis in the context of neurodegenerative diseases, such as Alzheimer's and Parkinson's. We discuss the potential of AI techniques, including deep learning and computer vision, to accurately interpret and categorize subtle changes in facial expressions associated with these pathological conditions.
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December 2024
From the Department of Neurology (B.A.M.), University of Michigan Medical School, Ann Arbor; and Department of Neurology (V.F.), University of Colorado Anschutz Medical Campus, Aurora.
Charcot-Marie-Tooth disease (CMT) encompasses a diverse group of genetic forms of inherited peripheral neuropathy and stands as the most common hereditary neurologic disease worldwide. At present, no disease-modifying treatments exist for any form of CMT. However, promising therapeutic strategies are rapidly emerging, necessitating careful consideration of clinical outcome assessments (COAs) and clinical trial design.
View Article and Find Full Text PDFAdv Mater
January 2025
Max Planck Institute for Sustainable Materials, Max-Planck-Straße 1, 40237, Düsseldorf, Germany.
Phase transformations and crystallographic defects are two essential tools to drive innovations in materials. Bulk materials design via tuning chemical compositions is systematized using phase diagrams. It is shown here that the same thermodynamic concept can be applied to manipulate the chemistry at defects.
View Article and Find Full Text PDFEntropy (Basel)
October 2024
School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China.
To lighten the workload of train drivers and enhance railway transportation safety, a novel and intelligent method for railway turnout identification is investigated based on semantic segmentation. More specifically, a railway turnout scene perception (RTSP) dataset is constructed and annotated manually in this paper, wherein the innovative concept of side rails is introduced as part of the labeling process. After that, based on the work of Deeplabv3+, combined with a lightweight design and an attention mechanism, a railway turnout identification network (RTINet) is proposed.
View Article and Find Full Text PDFNat Commun
September 2024
Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK.
The ATP-independent chaperone SurA protects unfolded outer membrane proteins (OMPs) from aggregation in the periplasm of Gram-negative bacteria, and delivers them to the β-barrel assembly machinery (BAM) for folding into the outer membrane (OM). Precisely how SurA recognises and binds its different OMP clients remains unclear. Escherichia coli SurA comprises three domains: a core and two PPIase domains (P1 and P2).
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