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      Imbalances in the eye lens proteome are linked to cataract formation

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          NIH Image to ImageJ: 25 years of image analysis

          For the past twenty five years the NIH family of imaging software, NIH Image and ImageJ have been pioneers as open tools for scientific image analysis. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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            Probability-based protein identification by searching sequence databases using mass spectrometry data

            Several algorithms have been described in the literature for protein identification by searching a sequence database using mass spectrometry data. In some approaches, the experimental data are peptide molecular weights from the digestion of a protein by an enzyme. Other approaches use tandem mass spectrometry (MS/MS) data from one or more peptides. Still others combine mass data with amino acid sequence data. We present results from a new computer program, Mascot, which integrates all three types of search. The scoring algorithm is probability based, which has a number of advantages: (i) A simple rule can be used to judge whether a result is significant or not. This is particularly useful in guarding against false positives. (ii) Scores can be compared with those from other types of search, such as sequence homology. (iii) Search parameters can be readily optimised by iteration. The strengths and limitations of probability-based scoring are discussed, particularly in the context of high throughput, fully automated protein identification.
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              Age-related nuclear cataract-oxidation is the key.

              Age is by far the biggest risk factor for cataract, and it is sometimes assumed that cataract is simply an amplification of this aging process. This appears not to be the case, since the lens changes associated with aging and cataract are distinct. Oxidation is the hallmark of age-related nuclear (ARN) cataract. Loss of protein sulfhydryl groups, and the oxidation of methionine residues, are progressive and increase as the cataract worsens until >90% of cysteine and half the methionine residues are oxidised in the most advanced form. By contrast, there may be no significant oxidation of proteins in the centre of the lens with advancing age, even past age 80. The key factor in preventing oxidation seems to be the concentration of nuclear glutathione (GSH). Provided that nuclear GSH levels can be maintained above 2 mm, it appears that significant protein oxidation and posttranslational modification by reactive small molecules, such as ascorbate or UV filter degradation products, is not observed. Adequate coupling of the metabolically-active cortex, the source of antioxidants such as GSH, to the quiescent nucleus, is crucial especially since it would appear that the cortex remains viable in old lenses, and even possibly in ARN cataract lenses. Therefore it is vital to understand the reason for the onset of the lens barrier. This barrier, which becomes apparent in middle age, acts to impede the flow of small molecules between the cortex and the nucleus. The barrier, rather than nuclear compaction (which is not observed in human lenses), may contribute to the lowered concentration of GSH in the lens nucleus after middle age. By extending the residence time within the lens centre, the barrier also facilitates the decomposition of intrinsically unstable metabolites and may exacerbate the formation of H(2)O(2) in the nucleus. This hypothesis, which is based on the generation of reactive oxygen species and reactive molecules within the nucleus itself, shifts the focus away from theories for cataract that postulated a primary role for oxidants generated outside of the lens. Unfortunately, due to marked variability in the lenses of different species, there appears at present to be no ideal animal model system for studying human ARN cataract.
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                Journal
                Nature Structural & Molecular Biology
                Nat Struct Mol Biol
                Springer Science and Business Media LLC
                1545-9993
                1545-9985
                January 11 2021
                Article
                10.1038/s41594-020-00543-9
                33432246
                a017a860-682b-4761-880d-1b407e100198
                © 2021

                http://www.springer.com/tdm

                http://www.springer.com/tdm

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