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      Recent advances and new perspectives in mitochondrial dysfunction

      editorial
      1 , , 2 , , 3 ,
      Scientific Reports
      Nature Publishing Group UK
      Biochemistry, Biomarkers

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          Abstract

          In the last decade, there has been an increased appreciation for mitochondria as central hubs in diverse processes, such as cellular energy, immunity, and signal transduction. As such, we have become aware that mitochondrial dysfunction underlies many diseases, including primary (mutations in genes encoding mitochondrial proteins) and secondary mitochondrial diseases (mutations in non-mitochondrial genes critical for mitochondrial biology), as well as complex diseases with mitochondrial dysfunction (chronic or degenerative diseases). Evidence suggests that mitochondrial dysfunction may often precede other pathological signs in these disorders, further modulated by genetics, environment, and lifestyle.

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          Dermatologist-level classification of skin cancer with deep neural networks

          Skin cancer, the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy and histopathological examination. Automated classification of skin lesions using images is a challenging task owing to the fine-grained variability in the appearance of skin lesions. Deep convolutional neural networks (CNNs) show potential for general and highly variable tasks across many fine-grained object categories. Here we demonstrate classification of skin lesions using a single CNN, trained end-to-end from images directly, using only pixels and disease labels as inputs. We train a CNN using a dataset of 129,450 clinical images—two orders of magnitude larger than previous datasets—consisting of 2,032 different diseases. We test its performance against 21 board-certified dermatologists on biopsy-proven clinical images with two critical binary classification use cases: keratinocyte carcinomas versus benign seborrheic keratoses; and malignant melanomas versus benign nevi. The first case represents the identification of the most common cancers, the second represents the identification of the deadliest skin cancer. The CNN achieves performance on par with all tested experts across both tasks, demonstrating an artificial intelligence capable of classifying skin cancer with a level of competence comparable to dermatologists. Outfitted with deep neural networks, mobile devices can potentially extend the reach of dermatologists outside of the clinic. It is projected that 6.3 billion smartphone subscriptions will exist by the year 2021 (ref. 13) and can therefore potentially provide low-cost universal access to vital diagnostic care.
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            Molecular Mechanisms of TDP-43 Misfolding and Pathology in Amyotrophic Lateral Sclerosis

            TAR DNA binding protein 43 (TDP-43) is a versatile RNA/DNA binding protein involved in RNA-related metabolism. Hyper-phosphorylated and ubiquitinated TDP-43 deposits act as inclusion bodies in the brain and spinal cord of patients with the motor neuron diseases: amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). While the majority of ALS cases (90–95%) are sporadic (sALS), among familial ALS cases 5–10% involve the inheritance of mutations in the TARDBP gene and the remaining (90–95%) are due to mutations in other genes such as: C9ORF72, SOD1, FUS, and NEK1 etc. Strikingly however, the majority of sporadic ALS patients (up to 97%) also contain the TDP-43 protein deposited in the neuronal inclusions, which suggests of its pivotal role in the ALS pathology. Thus, unraveling the molecular mechanisms of the TDP-43 pathology seems central to the ALS therapeutics, hence, we comprehensively review the current understanding of the TDP-43's pathology in ALS. We discuss the roles of TDP-43's mutations, its cytoplasmic mis-localization and aberrant post-translational modifications in ALS. Also, we evaluate TDP-43's amyloid-like in vitro aggregation, its physiological vs. pathological oligomerization in vivo, liquid-liquid phase separation (LLPS), and potential prion-like propagation propensity of the TDP-43 inclusions. Finally, we describe the various evolving TDP-43-induced toxicity mechanisms, such as the impairment of endocytosis and mitotoxicity etc. and also discuss the emerging strategies toward TDP-43 disaggregation and ALS therapeutics.
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              Use of Artificial Intelligence and Deep Neural Networks in Evaluation of Patients With Electrocardiographically Concealed Long QT Syndrome From the Surface 12-Lead Electrocardiogram

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                Author and article information

                Contributors
                cgiulivi@ucdavis.edu
                kzhang@med.wayne.edu
                harakawa@ncc.go.jp
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                17 May 2023
                17 May 2023
                2023
                : 13
                : 7977
                Affiliations
                [1 ]GRID grid.27860.3b, ISNI 0000 0004 1936 9684, School of Veterinary Medicine, University of California at Davis and The MIND Institute, , University of California Davis, ; Davis, CA USA
                [2 ]GRID grid.254444.7, ISNI 0000 0001 1456 7807, Center for Molecular Medicine and Genetics, , Wayne State University School of Medicine, ; Detroit, USA
                [3 ]GRID grid.272242.3, ISNI 0000 0001 2168 5385, Division of Cancer Biology, , National Cancer Center Research Institute, ; Tokyo, Japan
                Author information
                http://orcid.org/0000-0003-1033-7435
                Article
                34624
                10.1038/s41598-023-34624-8
                10192368
                37198256
                adb1f46a-4c82-48a6-8d06-0a6a242ccc4e
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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                © Springer Nature Limited 2023

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                biochemistry,biomarkers
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                biochemistry, biomarkers

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