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  1. Article ; Online: Editorial: Insights in neuropathic pain: 2022.

    Shan, Leyan / Selvarajah, Dinesh / Wang, Zilong

    Frontiers in pain research (Lausanne, Switzerland)

    2023  Volume 4, Page(s) 1232025

    Language English
    Publishing date 2023-06-14
    Publishing country Switzerland
    Document type Editorial
    ISSN 2673-561X
    ISSN (online) 2673-561X
    DOI 10.3389/fpain.2023.1232025
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Deep Learning Classification of Treatment Response in Diabetic Painful Neuropathy: A Combined Machine Learning and Magnetic Resonance Neuroimaging Methodological Study.

    Teh, Kevin / Armitage, Paul / Tesfaye, Solomon / Selvarajah, Dinesh

    Neuroinformatics

    2022  Volume 21, Issue 1, Page(s) 35–43

    Abstract: Functional magnetic resonance imaging (fMRI) has been shown successfully to assess and stratify patients with painful diabetic peripheral neuropathy (pDPN). This supports the idea of using neuroimaging as a mechanism-based technique to individualise ... ...

    Abstract Functional magnetic resonance imaging (fMRI) has been shown successfully to assess and stratify patients with painful diabetic peripheral neuropathy (pDPN). This supports the idea of using neuroimaging as a mechanism-based technique to individualise therapy for patients with painful DPN. The aim of this study was to use deep learning to predict treatment response in patients with pDPN using resting state functional imaging (rs-fMRI). We divided 43 painful pDPN patients into responders and non-responders to lidocaine treatment (responders n = 29 and non-responders n = 14). We used rs-fMRI to extract functional connectivity features, using group independent component analysis (gICA), and performed automated treatment response deep learning classification with three-dimensional convolutional neural networks (3D-CNN). Using gICA we achieved an area under the receiver operating characteristic curve (AUC) of 96.60% and F1-Score of 95% in a ten-fold cross validation (CV) experiment using our described 3D-CNN algorithm. To our knowledge, this is the first study utilising deep learning methods to classify treatment response in pDPN.
    MeSH term(s) Humans ; Deep Learning ; Diabetic Neuropathies/diagnostic imaging ; Diabetic Neuropathies/drug therapy ; Magnetic Resonance Imaging/methods ; Neuroimaging/methods ; Machine Learning ; Magnetic Resonance Spectroscopy ; Diabetes Mellitus
    Language English
    Publishing date 2022-08-26
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2111941-7
    ISSN 1559-0089 ; 1539-2791
    ISSN (online) 1559-0089
    ISSN 1539-2791
    DOI 10.1007/s12021-022-09603-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: The Treatment of Painful Diabetic Neuropathy.

    Sloan, Gordon / Alam, Uazman / Selvarajah, Dinesh / Tesfaye, Solomon

    Current diabetes reviews

    2021  Volume 18, Issue 5, Page(s) e070721194556

    Abstract: Painful diabetic peripheral neuropathy (painful-DPN) is a highly prevalent and disabling condition, affecting up to one-third of patients with diabetes. This condition can have a profound impact resulting in a poor quality of life, disruption of ... ...

    Abstract Painful diabetic peripheral neuropathy (painful-DPN) is a highly prevalent and disabling condition, affecting up to one-third of patients with diabetes. This condition can have a profound impact resulting in a poor quality of life, disruption of employment, impaired sleep, and poor mental health with an excess of depression and anxiety. The management of painful-DPN poses a great challenge. Unfortunately, currently there are no Food and Drug Administration (USA) approved disease-modifying treatments for diabetic peripheral neuropathy (DPN) as trials of putative pathogenetic treatments have failed at phase 3 clinical trial stage. Therefore, the focus of managing painful- DPN other than improving glycaemic control and cardiovascular risk factor modification is treating symptoms. The recommended treatments based on expert international consensus for painful- DPN have remained essentially unchanged for the last decade. Both the serotonin re-uptake inhibitor (SNRI) duloxetine and α2δ ligand pregabalin have the most robust evidence for treating painful-DPN. The weak opioids (e.g. tapentadol and tramadol, both of which have an SNRI effect), tricyclic antidepressants such as amitriptyline and α2δ ligand gabapentin are also widely recommended and prescribed agents. Opioids (except tramadol and tapentadol), should be prescribed with caution in view of the lack of definitive data surrounding efficacy, concerns surrounding addiction and adverse events. Recently, emerging therapies have gained local licenses, including the α2δ ligand mirogabalin (Japan) and the high dose 8% capsaicin patch (FDA and Europe). The management of refractory painful-DPN is difficult; specialist pain services may offer off-label therapies (e.g. botulinum toxin, intravenous lidocaine and spinal cord stimulation), although there is limited clinical trial evidence supporting their use. Additionally, despite combination therapy being commonly used clinically, there is little evidence supporting this practise. There is a need for further clinical trials to assess novel therapeutic agents, optimal combination therapy and existing agents to determine which are the most effective for the treatment of painful-DPN. This article reviews the evidence for the treatment of painful-DPN, including emerging treatment strategies such as novel compounds and stratification of patients according to individual characteristics (e.g. pain phenotype, neuroimaging and genotype) to improve treatment responses.
    MeSH term(s) Analgesics, Opioid/therapeutic use ; Diabetes Mellitus/drug therapy ; Diabetic Neuropathies/diagnosis ; Humans ; Ligands ; NAD/therapeutic use ; Pain/drug therapy ; Quality of Life ; Serotonin and Noradrenaline Reuptake Inhibitors/therapeutic use ; Tapentadol/therapeutic use ; Tramadol/therapeutic use
    Chemical Substances Analgesics, Opioid ; Ligands ; Serotonin and Noradrenaline Reuptake Inhibitors ; NAD (0U46U6E8UK) ; Tramadol (39J1LGJ30J) ; Tapentadol (H8A007M585)
    Language English
    Publishing date 2021-07-08
    Publishing country United Arab Emirates
    Document type Journal Article ; Review
    ISSN 1875-6417
    ISSN (online) 1875-6417
    DOI 10.2174/1573399817666210707112413
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Pathogenesis, diagnosis and clinical management of diabetic sensorimotor peripheral neuropathy.

    Sloan, Gordon / Selvarajah, Dinesh / Tesfaye, Solomon

    Nature reviews. Endocrinology

    2021  Volume 17, Issue 7, Page(s) 400–420

    Abstract: Diabetic sensorimotor peripheral neuropathy (DSPN) is a serious complication of diabetes mellitus and is associated with increased mortality, lower-limb amputations and distressing painful neuropathic symptoms (painful DSPN). Our understanding of the ... ...

    Abstract Diabetic sensorimotor peripheral neuropathy (DSPN) is a serious complication of diabetes mellitus and is associated with increased mortality, lower-limb amputations and distressing painful neuropathic symptoms (painful DSPN). Our understanding of the pathophysiology of the disease has largely been derived from animal models, which have identified key potential mechanisms. However, effective therapies in preclinical models have not translated into clinical trials and we have no universally accepted disease-modifying treatments. Moreover, the condition is generally diagnosed late when irreversible nerve damage has already taken place. Innovative point-of-care devices have great potential to enable the early diagnosis of DSPN when the condition might be more amenable to treatment. The management of painful DSPN remains less than optimal; however, studies suggest that a mechanism-based approach might offer an enhanced benefit in certain pain phenotypes. The management of patients with DSPN involves the control of individualized cardiometabolic targets, a multidisciplinary approach aimed at the prevention and management of foot complications, and the timely diagnosis and management of neuropathic pain. Here, we discuss the latest advances in the mechanisms of DSPN and painful DSPN, originating both from the periphery and the central nervous system, as well as the emerging diagnostics and treatments.
    MeSH term(s) Amputation/mortality ; Amputation/statistics & numerical data ; Animals ; Diabetic Neuropathies/diagnosis ; Diabetic Neuropathies/etiology ; Diabetic Neuropathies/mortality ; Diabetic Neuropathies/therapy ; Humans ; Neuralgia/diagnosis ; Neuralgia/etiology ; Neuralgia/mortality ; Neuralgia/therapy ; Neuromuscular Diseases/diagnosis ; Neuromuscular Diseases/etiology ; Neuromuscular Diseases/mortality ; Neuromuscular Diseases/therapy ; Peripheral Nervous System Diseases/diagnosis ; Peripheral Nervous System Diseases/etiology ; Peripheral Nervous System Diseases/mortality ; Peripheral Nervous System Diseases/therapy
    Language English
    Publishing date 2021-05-28
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 2489381-X
    ISSN 1759-5037 ; 1759-5029
    ISSN (online) 1759-5037
    ISSN 1759-5029
    DOI 10.1038/s41574-021-00496-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Higher Sensory Cortical Energy Metabolism in Painful Diabetic Neuropathy: Evidence From a Cerebral Magnetic Resonance Spectroscopy Study.

    Sloan, Gordon / Anton, Adriana / Caunt, Sharon / Wilkinson, Iain / Selvarajah, Dinesh / Tesfaye, Solomon

    Diabetes

    2023  Volume 72, Issue 7, Page(s) 1028–1034

    Abstract: Alterations in the resting-state functional connectivity and hyperperfusion of pain processing areas of the brain have been demonstrated in painful diabetic peripheral neuropathy (DPN). However, the mechanisms underlying these abnormalities are poorly ... ...

    Abstract Alterations in the resting-state functional connectivity and hyperperfusion of pain processing areas of the brain have been demonstrated in painful diabetic peripheral neuropathy (DPN). However, the mechanisms underlying these abnormalities are poorly understood; thus there is good rationale to explore whether there is higher energy consumption in the pain processing areas of the brain. We performed a 31P magnetic resonance spectroscopy study to explore cellular energy usage (bioenergetics) in the primary somatosensory (S1) cortex in a well-characterized cohort of participants with painful and painless DPN. S1 phosphocreatine (PCr):ATP, a measure of energy consumption, was significantly reduced in painful compared with painless DPN. This is indicative of greater S1 cortical energy consumption in painful DPN. Furthermore, S1 PCr:ATP correlated with pain intensity during the MRI. S1 PCr:ATP was also significantly lower in painful-DPN individuals with moderate/severe pain compared with those with low pain. To our knowledge, this is the first study to demonstrate higher S1 cortical energy metabolism in painful compared with painless DPN. Moreover, the relationship between PCr:ATP and neuropathic pain measures shows that S1 bioenergetics is related to the severity of neuropathic pain. S1 cortical energetics may represent a biomarker of painful DPN and could have the potential to serve as a target for therapeutic interventions.
    Article highlights: Energy consumption within the primary somatosensory cortex appears to be greater in painful compared with painless diabetic peripheral neuropathy. The measure of energy metabolism, PCr:ATP, within the somatosensory cortex correlated with pain intensity and was lower in those with moderate/severe compared with low pain. To our knowledge. this is the first study to indicate higher cortical energy metabolism in painful compared with painless diabetic peripheral neuropathy, and thus has the potential to act as a biomarker for clinical pain trials.
    MeSH term(s) Humans ; Diabetic Neuropathies ; Neuralgia/pathology ; Magnetic Resonance Imaging/methods ; Magnetic Resonance Spectroscopy ; Biomarkers ; Adenosine Triphosphate ; Diabetes Mellitus
    Chemical Substances Biomarkers ; Adenosine Triphosphate (8L70Q75FXE)
    Language English
    Publishing date 2023-04-14
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 80085-5
    ISSN 1939-327X ; 0012-1797
    ISSN (online) 1939-327X
    ISSN 0012-1797
    DOI 10.2337/db23-0051
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Who really benefits from drug combinations and long titrations for pain? - Authors' reply.

    Tesfaye, Solomon / Sloan, Gordon / White, David / Bradburn, Mike / Bouhassira, Didier / Selvarajah, Dinesh

    Lancet (London, England)

    2023  Volume 401, Issue 10372, Page(s) 192–193

    MeSH term(s) Humans ; Pain ; Drug Combinations
    Chemical Substances Drug Combinations
    Language English
    Publishing date 2023-01-16
    Publishing country England
    Document type Letter ; Comment
    ZDB-ID 3306-6
    ISSN 1474-547X ; 0023-7507 ; 0140-6736
    ISSN (online) 1474-547X
    ISSN 0023-7507 ; 0140-6736
    DOI 10.1016/S0140-6736(23)00057-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Preservation of thalamic neuronal function may be a prerequisite for pain perception in diabetic neuropathy: A magnetic resonance spectroscopy study.

    Gandhi, Rajiv / Selvarajah, Dinesh / Sloan, Gordon / Greig, Marni / Wilkinson, Iain D / Shaw, Pamela J / Griffiths, Paul / Tesfaye, Solomon

    Frontiers in pain research (Lausanne, Switzerland)

    2023  Volume 3, Page(s) 1086887

    Abstract: Introduction: In this study, we used proton Magnetic Resonance Spectroscopy (1H-MRS) to determine the neuronal function in the thalamus and primary somatosensory (S1) cortex in different subgroups of DPN, including subclinical- and painful-DPN.: ... ...

    Abstract Introduction: In this study, we used proton Magnetic Resonance Spectroscopy (1H-MRS) to determine the neuronal function in the thalamus and primary somatosensory (S1) cortex in different subgroups of DPN, including subclinical- and painful-DPN.
    Method: One-hundred and ten people with type 1 diabetes [20 without DPN (no-DPN); 30 with subclinical-DPN; 30 with painful-DPN; and 30 with painless-DPN] and 20 healthy volunteers, all of whom were right-handed men, were recruited and underwent detailed clinical and neurophysiological assessments. Participants underwent Magnetic Resonance Imaging at 1.5 Tesla with two 1H-MRS spectra obtained from 8 ml cubic volume voxels: one placed within left thalamus to encompass the ventro-posterior lateral sub-nucleus and another within the S1 cortex.
    Results: In the thalamus, participants with painless-DPN had a significantly lower NAA:Cr ratio [1.55 + 0.22 (mean ± SD)] compared to all other groups [HV (1.80 ± 0.23), no-DPN (1.85 ± 0.20), sub-clinical DPN (1.79 ± 0.23), painful-DPN (1.75 ± 0.19), ANOVA
    Conclusion: In this largest cerebral MRS study in DPN, thalamic neuronal dysfunction was found in advanced painless-DPN with preservation of function in subclinical- and painful-DPN. Furthermore, there was a preservation of neuronal function within the S1 cortex in all subgroups of DPN. Therefore, there may be a proximo-distal gradient to central nervous system alterations in painless-DPN, with thalamic neuronal dysfunction occurring only in established DPN. Moreover, these results further highlight the manifestation of cerebral alterations between painful- and painless-DPN whereby preservation of thalamic function may be a prerequisite for neuropathic pain in DPN.
    Language English
    Publishing date 2023-01-06
    Publishing country Switzerland
    Document type Journal Article
    ISSN 2673-561X
    ISSN (online) 2673-561X
    DOI 10.3389/fpain.2022.1086887
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Brain alterations in regions associated with end-organ diabetic microvascular disease in diabetes mellitus: A UK Biobank study.

    Burgess, Jamie / de Bezenac, Christophe / Keller, Simon S / Frank, Bernhard / Petropoulos, Ioannis N / Garcia-Finana, Marta / Jackson, Timothy L / Kirthi, Varo / Cuthbertson, Daniel J / Selvarajah, Dinesh / Tesfaye, Solomon / Alam, Uazman

    Diabetes/metabolism research and reviews

    2024  Volume 40, Issue 2, Page(s) e3772

    Abstract: Background: Diabetes mellitus (DM) is associated with structural grey matter alterations in the brain, including changes in the somatosensory and pain processing regions seen in association with diabetic peripheral neuropathy. In this case-controlled ... ...

    Abstract Background: Diabetes mellitus (DM) is associated with structural grey matter alterations in the brain, including changes in the somatosensory and pain processing regions seen in association with diabetic peripheral neuropathy. In this case-controlled biobank study, we aimed to ascertain differences in grey and white matter anatomy in people with DM compared with non-diabetic controls (NDC).
    Methods: This study utilises the UK Biobank prospective, population-based, multicentre study of UK residents. Participants with diabetes and age/gender-matched controls without diabetes were selected in a three-to-one ratio. We excluded people with underlying neurological/neurodegenerative disease. Whole brain, cortical, and subcortical volumes (188 regions) were compared between participants with diabetes against NDC corrected for age, sex, and intracranial volume using univariate regression models, with adjustment for multiple comparisons. Diffusion tensor imaging analysis of fractional anisotropy (FA) was performed along the length of 50 white matter tracts.
    Results: We included 2404 eligible participants who underwent brain magnetic resonance imaging (NDC, n = 1803 and DM, n = 601). Participants with DM had a mean (±standard deviation) diagnostic duration of 18 ± 11 years, with adequate glycaemic control (HbA1
    Interpretation: This analysis suggests that anatomic differences in brain regions are present in a cohort with adequately controlled glycaemia without prevalent microvascular disease when compared with volunteers without diabetes. We hypothesise that these differences may predate overt end-organ damage and complications such as diabetic neuropathy and retinopathy. Central nervous system alterations/neuroplasticity may occur early in the natural history of microvascular complications; therefore, brain imaging should be considered in future mechanistic and interventional studies of DM.
    MeSH term(s) Humans ; Diffusion Tensor Imaging/methods ; Prospective Studies ; Neurodegenerative Diseases/pathology ; Biological Specimen Banks ; UK Biobank ; Brain/diagnostic imaging ; Brain/pathology ; Magnetic Resonance Imaging/methods ; Diabetes Mellitus/epidemiology ; Diabetes Mellitus/pathology ; Pain/pathology
    Language English
    Publishing date 2024-02-16
    Publishing country England
    Document type Multicenter Study ; Journal Article
    ZDB-ID 1470192-3
    ISSN 1520-7560 ; 1520-7552
    ISSN (online) 1520-7560
    ISSN 1520-7552
    DOI 10.1002/dmrr.3772
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  9. Article ; Online: The Effects of Type 1 Diabetes and Diabetic Peripheral Neuropathy on the Musculoskeletal System: A Case-Control Study.

    Vilaca, Tatiane / Paggiosi, Margaret / Walsh, Jennifer S / Selvarajah, Dinesh / Eastell, Richard

    Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research

    2021  Volume 36, Issue 6, Page(s) 1048–1059

    Abstract: Fracture risk is increased in type 1 diabetes (T1D). Diabetic neuropathy might contribute to this increased risk directly through effects on bone turnover and indirectly through effects on balance, muscle strength, and gait. We compared patients with T1D ...

    Abstract Fracture risk is increased in type 1 diabetes (T1D). Diabetic neuropathy might contribute to this increased risk directly through effects on bone turnover and indirectly through effects on balance, muscle strength, and gait. We compared patients with T1D with (T1DN+, n = 20) and without (T1DN-, n = 20) distal symmetric sensorimotor polyneuropathy and controls (n = 20). We assessed areal bone mineral density (aBMD) and appendicular muscle mass by dual-energy X-ray absorptiometry, microarchitecture by high-resolution peripheral quantitative tomography at the standard ultra-distal site and at an exploratory 14% bone length site at the tibia and radius, bone turnover markers, and muscle strength, gait, and balance by Short Physical Performance Battery (SPPB). At the standard ultra-distal site, tibial cortical porosity was 56% higher in T1DN+ compared with T1DN- (p = .009) and correlated positively with the severity of neuropathy (Toronto Clinical Neuropathy Score; r = 0.347, p = .028) and negatively with nerve conduction amplitude and velocity (r = -0.386, p = .015 and r = -0.358, p = .025, respectively). Similar negative correlations were also observed at the radius (r = -0.484, p = .006 and r = -0.446, p = .012, respectively). At the exploratory 14% offset site (less distal), we found higher trabecular volumetric BMD (tibia 25%, p = .024; radius 46%, p = .017), trabecular bone volume (tibia 25%, p = .023; radius 46%, p = .017), and trabecular number (tibia 22%, p = .014; radius 30%, p = .010) in T1DN- compared with controls. Both CTX and PINP were lower in participants with TD1 compared with controls. No difference was found in aBMD and appendicular muscle mass. T1DN+ had worse performance in the SPPB compared with T1DN- and control. In summary, neuropathy was associated with cortical porosity and worse performance in physical tests. Our findings suggest that bone structure does not fully explain the rate of fractures in T1D. We conclude that the increase in the risk of fractures in T1D is multifactorial with both skeletal and non-skeletal contributions. © 2021 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
    MeSH term(s) Absorptiometry, Photon ; Bone Density ; Case-Control Studies ; Diabetes Mellitus, Type 1/complications ; Diabetic Neuropathies/diagnostic imaging ; Humans ; Radius ; Tibia
    Language English
    Publishing date 2021-04-06
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 632783-7
    ISSN 1523-4681 ; 0884-0431
    ISSN (online) 1523-4681
    ISSN 0884-0431
    DOI 10.1002/jbmr.4271
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  10. Article ; Online: Imbalanced learning: Improving classification of diabetic neuropathy from magnetic resonance imaging.

    Teh, Kevin / Armitage, Paul / Tesfaye, Solomon / Selvarajah, Dinesh / Wilkinson, Iain D

    PloS one

    2020  Volume 15, Issue 12, Page(s) e0243907

    Abstract: One of the fundamental challenges when dealing with medical imaging datasets is class imbalance. Class imbalance happens where an instance in the class of interest is relatively low, when compared to the rest of the data. This study aims to apply ... ...

    Abstract One of the fundamental challenges when dealing with medical imaging datasets is class imbalance. Class imbalance happens where an instance in the class of interest is relatively low, when compared to the rest of the data. This study aims to apply oversampling strategies in an attempt to balance the classes and improve classification performance. We evaluated four different classifiers from k-nearest neighbors (k-NN), support vector machine (SVM), multilayer perceptron (MLP) and decision trees (DT) with 73 oversampling strategies. In this work, we used imbalanced learning oversampling techniques to improve classification in datasets that are distinctively sparser and clustered. This work reports the best oversampling and classifier combinations and concludes that the usage of oversampling methods always outperforms no oversampling strategies hence improving the classification results.
    MeSH term(s) Algorithms ; Decision Trees ; Diabetes Mellitus/classification ; Diabetes Mellitus/diagnostic imaging ; Diabetes Mellitus/pathology ; Diabetic Neuropathies/classification ; Diabetic Neuropathies/diagnostic imaging ; Diabetic Neuropathies/pathology ; Female ; Humans ; Machine Learning ; Magnetic Resonance Imaging ; Male ; Neuroimaging/methods ; Support Vector Machine
    Language English
    Publishing date 2020-12-15
    Publishing country United States
    Document type Journal Article
    ISSN 1932-6203
    ISSN (online) 1932-6203
    DOI 10.1371/journal.pone.0243907
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