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Gao XY, Zhou CX, Li HM, Cheng M, Chen D, Li ZY, Feng B, Song J. Correlation between cerebral neurotransmitters levels by proton magnetic resonance spectroscopy and HbA1c in patients with type 2 diabetes. World J Diabetes 2024; 15:1263-1271. [PMID: 38983812 PMCID: PMC11229970 DOI: 10.4239/wjd.v15.i6.1263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 03/28/2024] [Accepted: 04/24/2024] [Indexed: 06/11/2024] Open
Abstract
BACKGROUND Cognitive dysfunction is the main manifestation of central neuropathy. Although cognitive impairments tend to be overlooked in patients with diabetes mellitus (DM), there is a growing body of evidence linking DM to cognitive dysfunction. Hyperglycemia is closely related to neurological abnormalities, while often disregarded in clinical practice. Changes in cerebral neurotransmitter levels are associated with a variety of neurological abnormalities and may be closely related to blood glucose control in patients with type 2 DM (T2DM). AIM To evaluate the concentrations of cerebral neurotransmitters in T2DM patients exhibiting different hemoglobin A1c (HbA1c) levels. METHODS A total of 130 T2DM patients were enrolled at the Department of Endocrinology of Shanghai East Hospital. The participants were divided into four groups according to their HbA1c levels using the interquartile method, namely Q1 (< 7.875%), Q2 (7.875%-9.050%), Q3 (9.050%-11.200%) and Q4 (≥ 11.200%). Clinical data were collected and measured, including age, height, weight, neck/waist/hip circumferences, blood pressure, comorbidities, duration of DM, and biochemical indicators. Meanwhile, neurotransmitters in the left hippocampus and left brainstem area were detected by proton magnetic resonance spectroscopy. RESULTS The HbA1c level was significantly associated with urinary microalbumin (mALB), triglyceride, low-density lipoprotein cholesterol (LDL-C), homeostasis model assessment of insulin resistance (HOMA-IR), and beta cell function (HOMA-β), N-acetylaspartate/creatine (NAA/Cr), and NAA/choline (NAA/Cho). Spearman correlation analysis showed that mALB, LDL-C, HOMA-IR and NAA/Cr in the left brainstem area were positively correlated with the level of HbA1c (P < 0.05), whereas HOMA-β was negatively correlated with the HbA1c level (P < 0.05). Ordered multiple logistic regression analysis showed that NAA/Cho [Odds ratio (OR): 1.608, 95% confidence interval (95%CI): 1.004-2.578, P < 0.05], LDL-C (OR: 1.627, 95%CI: 1.119-2.370, P < 0.05), and HOMA-IR (OR: 1.107, 95%CI: 1.031-1.188, P < 0.01) were independent predictors of poor glycemic control. CONCLUSION The cerebral neurotransmitter concentrations in the left brainstem area in patients with T2DM are closely related to glycemic control, which may be the basis for the changes in cognitive function in diabetic patients.
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Affiliation(s)
- Xiang-Yu Gao
- Department of Endocrinology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China
- Department of Endocrinology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao 266000, Shandong Province, China
| | - Chen-Xia Zhou
- Department of Endocrinology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China
| | - Hong-Mei Li
- Department of Endocrinology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China
| | - Min Cheng
- Department of Immunization Program, Huangdao District Center for Disease Prevention and Control, Qingdao 266400, Shandong Province, China
| | - Da Chen
- Department of Endocrinology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China
| | - Zi-Yi Li
- Department of Endocrinology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China
| | - Bo Feng
- Department of Endocrinology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China
| | - Jun Song
- Department of Endocrinology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China
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Abraham A, Jose R, Farooqui N, Mayer J, Ahmad J, Satti Z, Jacob TJ, Syed F, Toma M. The Role of ArtificiaI Intelligence in Brain Tumor Diagnosis: An Evaluation of a Machine Learning Model. Cureus 2024; 16:e61483. [PMID: 38952601 PMCID: PMC11215798 DOI: 10.7759/cureus.61483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/01/2024] [Indexed: 07/03/2024] Open
Abstract
This research study explores of the effectiveness of a machine learning image classification model in the accurate identification of various types of brain tumors. The types of tumors under consideration in this study are gliomas, meningiomas, and pituitary tumors. These are some of the most common types of brain tumors and pose significant challenges in terms of accurate diagnosis and treatment. The machine learning model that is the focus of this study is built on the Google Teachable Machine platform (Alphabet Inc., Mountain View, CA). The Google Teachable Machine is a machine learning image classification platform that is built from Tensorflow, a popular open-source platform for machine learning. The Google Teachable Machine model was specifically evaluated for its ability to differentiate between normal brains and the aforementioned types of tumors in MRI images. MRI images are a common tool in the diagnosis of brain tumors, but the challenge lies in the accurate classification of the tumors. This is where the machine learning model comes into play. The model is trained to recognize patterns in the MRI images that correspond to the different types of tumors. The performance of the machine learning model was assessed using several metrics. These include precision, recall, and F1 score. These metrics were generated from a confusion matrix analysis and performance graphs. A confusion matrix is a table that is often used to describe the performance of a classification model. Precision is a measure of the model's ability to correctly identify positive instances among all instances it identified as positive. Recall, on the other hand, measures the model's ability to correctly identify positive instances among all actual positive instances. The F1 score is a measure that combines precision and recall providing a single metric for model performance. The results of the study were promising. The Google Teachable Machine model demonstrated high performance, with accuracy, precision, recall, and F1 scores ranging between 0.84 and 1.00. This suggests that the model is highly effective in accurately classifying the different types of brain tumors. This study provides insights into the potential of machine learning models in the accurate classification of brain tumors. The findings of this study lay the groundwork for further research in this area and have implications for the diagnosis and treatment of brain tumors. The study also highlights the potential of machine learning in enhancing the field of medical imaging and diagnosis. With the increasing complexity and volume of medical data, machine learning models like the one evaluated in this study could play a crucial role in improving the accuracy and efficiency of diagnoses. Furthermore, the study underscores the importance of continued research and development in this field to further refine these models and overcome any potential limitations or challenges. Overall, the study contributes to the field of medical imaging and machine learning and sets the stage for future research and advancements in this area.
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Affiliation(s)
- Adriel Abraham
- Department of Internal Medicine, New York Institute of Technology College of Osteopathic Medicine, New York, USA
| | - Rejath Jose
- Department of Internal Medicine, New York Institute of Technology College of Osteopathic Medicine, New York, USA
| | - Nabeel Farooqui
- Department of Computer and Information Science, University of Pennsylvania School of Engineering and Applied Science, Philadelphia, USA
| | - Jonathan Mayer
- Department of Clinical Sciences, New York Institute of Technology College of Osteopathic Medicine, New York, USA
| | - Jawad Ahmad
- Department of Clinical Sciences, New York Institute of Technology College of Osteopathic Medicine, New York, USA
| | - Zain Satti
- Department of Clinical Sciences, New York Institute of Technology College of Osteopathic Medicine, New York, USA
| | - Thomas J Jacob
- Department of Internal Medicine, New York Institute of Technology College of Osteopathic Medicine, New York, USA
| | - Faiz Syed
- Department of Internal Medicine, New York Institute of Technology College of Osteopathic Medicine, New York, USA
| | - Milan Toma
- Department of Osteopathic Manipulative Medicine, New York Institute of Technology College of Osteopathic Medicine, New York, USA
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Zhou X, Yang Y, Zhu F, Chen X, Zhu Y, Gui T, Li Y, Xue Q. Neurometabolic and Brain Functional Alterations Associated with Cognitive Impairment in Patients with Myasthenia Gravis: A Combined 1H-MRS and fMRI Study. Neuroscience 2024; 544:12-27. [PMID: 38423165 DOI: 10.1016/j.neuroscience.2024.02.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 01/04/2024] [Accepted: 02/20/2024] [Indexed: 03/02/2024]
Abstract
Whether patients with myasthenia gravis (MG) exhibit cognitive impairment is controversial. Also the underlying mechanisms are unknown. We aimed to investigate alterations in cognitive function, neurometabolite levels, and brain function in patients with MG and to explore the associations between abnormal regional brain functional activity, neurometabolite concentrations in the MPFC and left thalamus, and cognitive activity in patients with MG. Neuropsychological tests, proton magnetic resonance spectroscopy, and resting-state functional magnetic resonance imaging were performed on 41 patients with MG and 45 race-, sex-, age-, and education-matched healthy controls (HCs). The results suggest that MG is accompanied by cognitive decline, as indicated by global cognitive function, visual-spatial function, language, memory, abnormalities in regional brain functional activity, and neurometabolite alterations (including GABA, NAA, and Cho) in the medial prefrontal cortex (MPFC) and left thalamus. Cognitive impairment in patients with MG may be related to abnormal regional brain functional activity and changes in neurometabolites, and regional brain functional activity may be modulated by specific neurometabolites.
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Affiliation(s)
- Xiaoling Zhou
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215000, China; Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu 215000, China
| | - Yang Yang
- Department of Radiology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, Jiangsu 214000, China
| | - Feng Zhu
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215000, China
| | - Xiang Chen
- Department of Radiology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215000, China
| | - Yunfei Zhu
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215000, China
| | - Tiantian Gui
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215000, China
| | - Yonggang Li
- Department of Radiology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215000, China.
| | - Qun Xue
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215000, China.
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Peng Y, Zhang Z, He L, Li C, Liu M. NMR spectroscopy for metabolomics in the living system: recent progress and future challenges. Anal Bioanal Chem 2024; 416:2319-2334. [PMID: 38240793 PMCID: PMC10950998 DOI: 10.1007/s00216-024-05137-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 12/08/2023] [Accepted: 01/10/2024] [Indexed: 03/21/2024]
Abstract
Metabolism is a fundamental process that underlies human health and diseases. Nuclear magnetic resonance (NMR) techniques offer a powerful approach to identify metabolic processes and track the flux of metabolites at the molecular level in living systems. An in vitro study through in-cell NMR tracks metabolites in real time and investigates protein structures and dynamics in a state close to their most natural environment. This technique characterizes metabolites and proteins involved in metabolic pathways in prokaryotic and eukaryotic cells. In vivo magnetic resonance spectroscopy (MRS) enables whole-organism metabolic monitoring by visualizing the spatial distribution of metabolites and targeted proteins. One limitation of these NMR techniques is the sensitivity, for which a possible improved approach is through isotopic enrichment or hyperpolarization methods, including dynamic nuclear polarization (DNP) and parahydrogen-induced polarization (PHIP). DNP involves the transfer of high polarization from electronic spins of radicals to surrounding nuclear spins for signal enhancements, allowing the detection of low-abundance metabolites and real-time monitoring of metabolic activities. PHIP enables the transfer of nuclear spin polarization from parahydrogen to other nuclei for signal enhancements, particularly in proton NMR, and has been applied in studies of enzymatic reactions and cell signaling. This review provides an overview of in-cell NMR, in vivo MRS, and hyperpolarization techniques, highlighting their applications in metabolic studies and discussing challenges and future perspectives.
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Affiliation(s)
- Yun Peng
- State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, National Center for Magnetic Resonance in Wuhan, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, China
| | - Zeting Zhang
- State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, National Center for Magnetic Resonance in Wuhan, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, China
| | - Lichun He
- State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, National Center for Magnetic Resonance in Wuhan, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, China
| | - Conggang Li
- State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, National Center for Magnetic Resonance in Wuhan, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, China
| | - Maili Liu
- State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, National Center for Magnetic Resonance in Wuhan, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, China.
- Optics Valley Laboratory, Wuhan, 430074, Hubei, China.
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Zhang Q, Liu X, Gao S, Yan S, Li A, Wei Z, Han S, Hou Y, Li X, Cao D, Yue J. Multimodal magnetic resonance imaging on brain structure and function changes in vascular cognitive impairment without dementia. Front Aging Neurosci 2023; 15:1278390. [PMID: 38035274 PMCID: PMC10687453 DOI: 10.3389/fnagi.2023.1278390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 10/23/2023] [Indexed: 12/02/2023] Open
Abstract
Vascular cognitive impairment not dementia (VCIND) is one of the three subtypes of vascular cognitive impairment (VCI), with cognitive dysfunction and symptoms ranging between normal cognitive function and vascular dementia. The specific mechanisms underlying VCIND are still not fully understood, and there is a lack of specific diagnostic markers in clinical practice. With the rapid development of magnetic resonance imaging (MRI) technology, structural MRI (sMRI) and functional MRI (fMRI) have become effective methods for exploring the neurobiological mechanisms of VCIND and have made continuous progress. This article provides a comprehensive overview of the research progress in VCIND using multimodal MRI, including sMRI, diffusion tensor imaging, resting-state fMRI, and magnetic resonance spectroscopy. By integrating findings from these multiple modalities, this study presents a novel perspective on the neuropathological mechanisms underlying VCIND. It not only highlights the importance of multimodal MRI in unraveling the complex nature of VCIND but also lays the foundation for future research examining the relationship between brain structure, function, and cognitive impairment in VCIND. These new perspectives and strategies ultimately hold the potential to contribute to the development of more effective diagnostic tools and therapeutic interventions for VCIND.
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Affiliation(s)
- Qinhong Zhang
- Shenzhen Frontiers in Chinese Medicine Research Co., Ltd., Shenzhen, China
- Department of Acupuncture and Moxibustion, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Xiao Liu
- Department of Pediatrics, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Shenglan Gao
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Shiyan Yan
- School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China
| | - Ang Li
- Servier (Beijing) Pharmaceutical Research and Development Co., Ltd., Beijing, China
| | - Zeyi Wei
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Shengwang Han
- Third Ward of Rehabilitation Department, Second Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Yu Hou
- Department of Gynecology, Harbin Traditional Chinese Medicine Hospital, Harbin, China
| | - Xiaoling Li
- Division of CT and MRI, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Danna Cao
- Division of CT and MRI, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Jinhuan Yue
- Shenzhen Frontiers in Chinese Medicine Research Co., Ltd., Shenzhen, China
- Department of Acupuncture and Moxibustion, Vitality University, Hayward, CA, United States
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6
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Autoimmune Hepatitis and Fibrosis. J Clin Med 2023; 12:jcm12051979. [PMID: 36902767 PMCID: PMC10004701 DOI: 10.3390/jcm12051979] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 02/16/2023] [Accepted: 02/27/2023] [Indexed: 03/06/2023] Open
Abstract
Autoimmune hepatitis (AIH) is a chronic immune-inflammatory disease of the liver, generally considered a rare condition. The clinical manifestation is extremely varied and can range from paucisymptomatic forms to severe hepatitis. Chronic liver damage causes activation of hepatic and inflammatory cells leading to inflammation and oxidative stress through the production of mediators. This results in increased collagen production and extracellular matrix deposition leading to fibrosis and even cirrhosis. The gold standard for the diagnosis of fibrosis is liver biopsy; however, there are serum biomarkers, scoring systems, and radiological methods useful for diagnosis and staging. The goal of AIH treatment is to suppress fibrotic and inflammatory activities in the liver to prevent disease progression and achieve complete remission. Therapy involves the use of classic steroidal anti-inflammatory drugs and immunosuppressants, but in recent years scientific research has focused on several new alternative drugs for AIH that will be discussed in the review.
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Bai JW, Qiu SQ, Zhang GJ. Molecular and functional imaging in cancer-targeted therapy: current applications and future directions. Signal Transduct Target Ther 2023; 8:89. [PMID: 36849435 PMCID: PMC9971190 DOI: 10.1038/s41392-023-01366-y] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 01/19/2023] [Accepted: 02/14/2023] [Indexed: 03/01/2023] Open
Abstract
Targeted anticancer drugs block cancer cell growth by interfering with specific signaling pathways vital to carcinogenesis and tumor growth rather than harming all rapidly dividing cells as in cytotoxic chemotherapy. The Response Evaluation Criteria in Solid Tumor (RECIST) system has been used to assess tumor response to therapy via changes in the size of target lesions as measured by calipers, conventional anatomically based imaging modalities such as computed tomography (CT), and magnetic resonance imaging (MRI), and other imaging methods. However, RECIST is sometimes inaccurate in assessing the efficacy of targeted therapy drugs because of the poor correlation between tumor size and treatment-induced tumor necrosis or shrinkage. This approach might also result in delayed identification of response when the therapy does confer a reduction in tumor size. Innovative molecular imaging techniques have rapidly gained importance in the dawning era of targeted therapy as they can visualize, characterize, and quantify biological processes at the cellular, subcellular, or even molecular level rather than at the anatomical level. This review summarizes different targeted cell signaling pathways, various molecular imaging techniques, and developed probes. Moreover, the application of molecular imaging for evaluating treatment response and related clinical outcome is also systematically outlined. In the future, more attention should be paid to promoting the clinical translation of molecular imaging in evaluating the sensitivity to targeted therapy with biocompatible probes. In particular, multimodal imaging technologies incorporating advanced artificial intelligence should be developed to comprehensively and accurately assess cancer-targeted therapy, in addition to RECIST-based methods.
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Affiliation(s)
- Jing-Wen Bai
- Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Xiamen Key Laboratory of Endocrine-Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Xiamen Research Center of Clinical Medicine in Breast and Thyroid Cancers, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Department of Medical Oncology, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Cancer Research Center of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
| | - Si-Qi Qiu
- Diagnosis and Treatment Center of Breast Diseases, Clinical Research Center, Shantou Central Hospital, 515041, Shantou, China
- Guangdong Provincial Key Laboratory for Breast Cancer Diagnosis and Treatment, Shantou University Medical College, 515041, Shantou, China
| | - Guo-Jun Zhang
- Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
- Xiamen Key Laboratory of Endocrine-Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
- Xiamen Research Center of Clinical Medicine in Breast and Thyroid Cancers, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
- Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
- Cancer Research Center of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
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Optimizing Dacarbazine Therapy: Design of a Laser-Triggered Delivery System Based on β-Cyclodextrin and Plasmonic Gold Nanoparticles. Pharmaceutics 2023; 15:pharmaceutics15020458. [PMID: 36839779 PMCID: PMC9960602 DOI: 10.3390/pharmaceutics15020458] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Revised: 01/21/2023] [Accepted: 01/27/2023] [Indexed: 01/31/2023] Open
Abstract
Dacarbazine (DB) is an antineoplastic drug extensively used in cancer therapy. However, present limitations on its performance are related to its low solubility, instability, and non-specificity. To overcome these drawbacks, DB was included in β-cyclodextrin (βCD), which increased its aqueous solubility and stability. This new βCD@DB complex has been associated with plasmonic gold nanoparticles (AuNPs), and polyethylene glycol (PEG) has been added in the process to increase the colloidal stability and biocompatibility. Different techniques revealed that DB allows for a dynamic inclusion into βCD, with an association constant of 80 M-1 and a degree of solubilization of 0.023, where βCD showed a loading capacity of 16%. The partial exposure of the NH2 group in the included DB allows its interaction with AuNPs, with a loading efficiency of 99%. The PEG-AuNPs-βCD@DB nanosystem exhibits an optical plasmonic absorption at 525 nm, a surface charge of -29 mV, and an average size of 12 nm. Finally, laser irradiation assays showed that DB can be released from this platform in a controlled manner over time, reaching a concentration of 56 μg/mL (43% of the initially loaded amount), which, added to the previous data, validates its potential for drug delivery applications. Therefore, the novel nanosystem based on βCD, AuNPs, and PEG is a promising candidate as a new nanocarrier for DB.
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Steg A, Oczkowicz M, Smołucha G. Omics as a Tool to Help Determine the Effectiveness of Supplements. Nutrients 2022; 14:nu14245305. [PMID: 36558464 PMCID: PMC9784029 DOI: 10.3390/nu14245305] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 12/07/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022] Open
Abstract
There has been considerable interest in dietary supplements in the last two decades. Companies are releasing new specifics at an alarming pace, while dietary supplements are one of the less-studied substances released for public consumption. However, access to state-of-the-art and high-throughput techniques, such as the ones used in omics, make it possible to check the impact of a substance on human transcriptome or proteome and provide answers to whether its use is reasonable and beneficial. In this review, the main domains of omics are briefly introduced. The review focuses on the three most widely used omics techniques: NGS, LC-MS, NMR, and their usefulness in studying dietary supplements. Examples of studies are described for some of the most commonly supplemented substances, such as vitamins: D, E, A, and plant extracts: resveratrol, green tea, ginseng, and curcumin extract. Techniques used in omics have proven to be useful in studying dietary supplements. NGS techniques are helpful in identifying pathways that change upon supplementation and determining polymorphisms or conditions that qualify for the necessity of a given supplementation. LC-MS techniques are used to establish the serum content of supplemented a compound and its effects on metabolites. Both LC-MS and NMR help establish the actual composition of a compound, its primary and secondary metabolites, and its potential toxicity. Moreover, NMR techniques determine what conditions affect the effectiveness of supplementation.
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Xiao S, Yang Z, Su T, Gong J, Huang L, Wang Y. Functional and structural brain abnormalities in posttraumatic stress disorder: A multimodal meta-analysis of neuroimaging studies. J Psychiatr Res 2022; 155:153-162. [PMID: 36029627 DOI: 10.1016/j.jpsychires.2022.08.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 08/09/2022] [Accepted: 08/15/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Numerous resting-state functional and structural studies have revealed that many brain regions are involved in the pathogenesis of posttraumatic stress disorder (PTSD), but their findings have been inconsistent. Moreover, there has no study explored the functional and structural alterations across languages in PTSD. METHODS A meta-analysis of whole-brain on the amplitude of low-frequency fluctuation (ALFF) and voxel-based morphometry (VBM) studies that explored alterations in the spontaneous functional brain activity and grey matter volume (GMV) in PTSD patients across languages by using the Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) software. RESULTS A total of 15 studies (19 datasets) comprising 577 PTSD patients and 499 HCs for ALFF, and 27 studies (31 datasets) comprising 539 PTSD patients and 693 HCs for VBM were included. Overall, PTSD patients across languages displayed decreased ALFF in the in the left amygdala. For VBM meta-analysis, PTSD patients across languages displayed reduced GMV in the bilateral anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), striatum, insula, superior temporal gyrus, left postcentral gyrus, and occipital gyrus. CONCLUSIONS The multimodal meta-analysis suggest that PTSD patients showed similar pattern of aberrant resting-state functional brain activity and structure mainly in the amygdala, suggesting that structural deficits might underlie alterations in function. In addition, some regions exhibited only structural abnormalities in PTSD, including the ACC/mPFC, striatum, insula, primary visual, auditory and sensorimotor cortices. Moreover, consistent alterations in PTSD patients across languages may draw attention to the disparity in multi-cultural considerations in psychiatric research and further understanding the neurophysiopathology of PTSD.
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Affiliation(s)
- Shu Xiao
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Zibin Yang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Ting Su
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Jiaying Gong
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China; Department of Radiology, Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510655, China
| | - Li Huang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China.
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Medrano-Escalada Y, Plaza-Manzano G, Fernández-de-las-Peñas C, Valera-Calero JA. Structural, Functional and Neurochemical Cortical Brain Changes Associated with Chronic Low Back Pain. Tomography 2022; 8:2153-2163. [PMID: 36136876 PMCID: PMC9498382 DOI: 10.3390/tomography8050180] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 08/16/2022] [Accepted: 08/22/2022] [Indexed: 12/19/2022] Open
Abstract
Chronic low back pain (CLBP) is one of the most prevalent musculoskeletal disorders, being one of the leading contributors to disability worldwide and involving an important economic and social burden. Up to 90% of CLBP is non-specific (not associated with specific injuries), with a chronicity expectation estimated at 10%. Currently, motivational and emotional central circuits are being investigated due to their role in CLBP persistency and chronification. Therefore, this narrative review aimed to summarize the evidence regarding the cortical brain changes described for proposing novel multidisciplinary approaches. Novel advances in neuroimaging techniques demonstrated structural (e.g., decrease in the grey matter located at the dorsolateral prefrontal cortex), functional (e.g., connectivity impairments in those areas involved in pain processing), and neurochemical changes (e.g., decrease in cerebral metabolites). In addition, significant changes were found in the primary somatosensory and motor cortex, contributing to the alteration of low back muscles activation and function.
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Affiliation(s)
| | - Gustavo Plaza-Manzano
- Department of Radiology, Rehabilitation and Physiotherapy, Universidad Complutense de Madrid, 28040 Madrid, Spain
- Grupo InPhysio, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain
- Correspondence: ; Tel.: +34-913-941-545
| | - César Fernández-de-las-Peñas
- Department of Physical Therapy, Occupational Therapy, Rehabilitation and Physical Medicine, Universidad Rey Juan Carlos, 28922 Alcorcón, Spain
- Clínica e Investigación en Fisioterapia, Terapia Manual, Punción Seca y Ejercicio Terapéutico, Universidad Rey Juan Carlos, 28922 Alcorcón, Spain
| | - Juan Antonio Valera-Calero
- VALTRADOFI Research Group, Department of Physiotherapy, Faculty of Health, Universidad Camilo José Cela, Villanueva de la Cañada, 28692 Madrid, Spain
- Department of Physiotherapy, Faculty of Health, Universidad Camilo José Cela, Villanueva de la Cañada, 28692 Madrid, Spain
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12
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Meng F, Yang Y, Jin G. Research Progress on MRI for White Matter Hyperintensity of Presumed Vascular Origin and Cognitive Impairment. Front Neurol 2022; 13:865920. [PMID: 35873763 PMCID: PMC9301233 DOI: 10.3389/fneur.2022.865920] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 06/14/2022] [Indexed: 11/17/2022] Open
Abstract
White matter hyperintensity of presumed vascular origin (WMH) is a common medical imaging manifestation in the brains of middle-aged and elderly individuals. WMH can lead to cognitive decline and an increased risk of cognitive impairment and dementia. However, the pathogenesis of cognitive impairment in patients with WMH remains unclear. WMH increases the risk of cognitive impairment, the nature and severity of which depend on lesion volume and location and the patient's cognitive reserve. Abnormal changes in microstructure, cerebral blood flow, metabolites, and resting brain function are observed in patients with WMH with cognitive impairment. Magnetic resonance imaging (MRI) is an indispensable tool for detecting WMH, and novel MRI techniques have emerged as the key approaches for exploring WMH and cognitive impairment. This article provides an overview of the association between WMH and cognitive impairment and the application of dynamic contrast-enhanced MRI, structural MRI, diffusion tensor imaging, 3D-arterial spin labeling, intravoxel incoherent motion, magnetic resonance spectroscopy, and resting-state functional MRI for examining WMH and cognitive impairment.
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Affiliation(s)
- Fanhua Meng
- North China University of Science and Technology, Tangshan, China
| | - Ying Yang
- Department of Radiology, China Emergency General Hospital, Beijing, China
| | - Guangwei Jin
- Department of Radiology, China Emergency General Hospital, Beijing, China
- *Correspondence: Guangwei Jin
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13
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Sosa-Moscoso B, Ullauri C, Chiriboga JD, Silva P, Haro F, Leon-Rojas JE. Magnetic Resonance Spectroscopy and Bipolar Disorder: How Feasible Is This Pairing? Cureus 2022; 14:e23690. [PMID: 35505758 PMCID: PMC9056012 DOI: 10.7759/cureus.23690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/31/2022] [Indexed: 11/29/2022] Open
Abstract
Bipolar disorder is a psychiatric disorder that affects a significant part of the world's population; however, its diagnosis is difficult, mainly because of the lack of biomarkers and objective tests that aid the clinical evaluation. Proton magnetic resonance spectroscopy (MRS) is a tool that is relatively unused in the medical field. Its application arises from conventional magnetic resonance, and allows non-invasive, in vivo, the study of various metabolites and compounds in the human brain. This method may allow the assessment of neurobiochemical alterations in bipolar patients. One of the main advantages of this study type is the simplicity in its use since it only needs a standard magnetic resonator. All these characteristics make it an attractive diagnostic tool that can be used anywhere, including in low-middle-income countries. In conclusion, MRS has potential as a diagnostic tool for bipolar disorder; nevertheless, using it for this purpose still requires additional steps.
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14
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Bandopadhyay R, Singh T, Ghoneim MM, Alshehri S, Angelopoulou E, Paudel YN, Piperi C, Ahmad J, Alhakamy NA, Alfaleh MA, Mishra A. Recent Developments in Diagnosis of Epilepsy: Scope of MicroRNA and Technological Advancements. BIOLOGY 2021; 10:1097. [PMID: 34827090 PMCID: PMC8615191 DOI: 10.3390/biology10111097] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 10/21/2021] [Accepted: 10/21/2021] [Indexed: 12/18/2022]
Abstract
Epilepsy is one of the most common neurological disorders, characterized by recurrent seizures, resulting from abnormally synchronized episodic neuronal discharges. Around 70 million people worldwide are suffering from epilepsy. The available antiepileptic medications are capable of controlling seizures in around 60-70% of patients, while the rest remain refractory. Poor seizure control is often associated with neuro-psychiatric comorbidities, mainly including memory impairment, depression, psychosis, neurodegeneration, motor impairment, neuroendocrine dysfunction, etc., resulting in poor prognosis. Effective treatment relies on early and correct detection of epileptic foci. Although there are currently a few well-established diagnostic techniques for epilepsy, they lack accuracy and cannot be applied to patients who are unsupportive or harbor metallic implants. Since a single test result from one of these techniques does not provide complete information about the epileptic foci, it is necessary to develop novel diagnostic tools. Herein, we provide a comprehensive overview of the current diagnostic tools of epilepsy, including electroencephalography (EEG) as well as structural and functional neuroimaging. We further discuss recent trends and advances in the diagnosis of epilepsy that will enable more effective diagnosis and clinical management of patients.
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Affiliation(s)
- Ritam Bandopadhyay
- Department of Pharmacology, School of Pharmaceutical Sciences, Lovely Professional University, Phagwara 144411, Punjab, India;
| | - Tanveer Singh
- Department of Neuroscience and Experimental Therapeutics, College of Medicine, Texas A&M University Health Science Center, Bryan, TX 77807, USA;
| | - Mohammed M. Ghoneim
- Department of Pharmacy Practice, College of Pharmacy, AlMaarefa University, Ad Diriyah 13713, Saudi Arabia;
| | - Sultan Alshehri
- Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia;
| | - Efthalia Angelopoulou
- Department of Biological Chemistry, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (E.A.); (C.P.)
| | - Yam Nath Paudel
- Neuropharmacology Research Strength, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Bandar Sunway, Subang Jaya 47500, Selangor, Malaysia;
| | - Christina Piperi
- Department of Biological Chemistry, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (E.A.); (C.P.)
| | - Javed Ahmad
- Department of Pharmaceutics, College of Pharmacy, Najran University, Najran 11001, Saudi Arabia;
| | - Nabil A. Alhakamy
- Department of Pharmaceutics, Faculty of Pharmacy, King Abdulaziz University, Jeddah 21589, Saudi Arabia; (N.A.A.); (M.A.A.)
| | - Mohamed A. Alfaleh
- Department of Pharmaceutics, Faculty of Pharmacy, King Abdulaziz University, Jeddah 21589, Saudi Arabia; (N.A.A.); (M.A.A.)
- Vaccines and Immunotherapy Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Awanish Mishra
- Department of Pharmacology, School of Pharmaceutical Sciences, Lovely Professional University, Phagwara 144411, Punjab, India;
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER)—Guwahati, Changsari, Guwahati 781101, Assam, India
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15
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Letertre MPM, Giraudeau P, de Tullio P. Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives. Front Mol Biosci 2021; 8:698337. [PMID: 34616770 PMCID: PMC8488110 DOI: 10.3389/fmolb.2021.698337] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 08/30/2021] [Indexed: 12/12/2022] Open
Abstract
Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.
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Affiliation(s)
| | | | - Pascal de Tullio
- Metabolomics Group, Center for Interdisciplinary Research of Medicine (CIRM), Department of Pharmacy, Université de Liège, Liège, Belgique
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16
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Markicevic M, Savvateev I, Grimm C, Zerbi V. Emerging imaging methods to study whole-brain function in rodent models. Transl Psychiatry 2021; 11:457. [PMID: 34482367 PMCID: PMC8418612 DOI: 10.1038/s41398-021-01575-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 08/05/2021] [Accepted: 08/23/2021] [Indexed: 02/07/2023] Open
Abstract
In the past decade, the idea that single populations of neurons support cognition and behavior has gradually given way to the realization that connectivity matters and that complex behavior results from interactions between remote yet anatomically connected areas that form specialized networks. In parallel, innovation in brain imaging techniques has led to the availability of a broad set of imaging tools to characterize the functional organization of complex networks. However, each of these tools poses significant technical challenges and faces limitations, which require careful consideration of their underlying anatomical, physiological, and physical specificity. In this review, we focus on emerging methods for measuring spontaneous or evoked activity in the brain. We discuss methods that can measure large-scale brain activity (directly or indirectly) with a relatively high temporal resolution, from milliseconds to seconds. We further focus on methods designed for studying the mammalian brain in preclinical models, specifically in mice and rats. This field has seen a great deal of innovation in recent years, facilitated by concomitant innovation in gene-editing techniques and the possibility of more invasive recordings. This review aims to give an overview of currently available preclinical imaging methods and an outlook on future developments. This information is suitable for educational purposes and for assisting scientists in choosing the appropriate method for their own research question.
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Affiliation(s)
- Marija Markicevic
- Neural Control of Movement Lab, HEST, ETH Zürich, Zürich, Switzerland
- Neuroscience Center Zurich, University and ETH Zürich, Zürich, Switzerland
| | - Iurii Savvateev
- Neural Control of Movement Lab, HEST, ETH Zürich, Zürich, Switzerland
- Neuroscience Center Zurich, University and ETH Zürich, Zürich, Switzerland
- Decision Neuroscience Lab, HEST, ETH Zürich, Zürich, Switzerland
| | - Christina Grimm
- Neural Control of Movement Lab, HEST, ETH Zürich, Zürich, Switzerland
- Neuroscience Center Zurich, University and ETH Zürich, Zürich, Switzerland
| | - Valerio Zerbi
- Neural Control of Movement Lab, HEST, ETH Zürich, Zürich, Switzerland.
- Neuroscience Center Zurich, University and ETH Zürich, Zürich, Switzerland.
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17
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Balthazar CF, Guimarães JT, Rocha RS, Pimentel TC, Neto RP, Tavares MIB, Graça JS, Alves Filho EG, Freitas MQ, Esmerino EA, Granato D, Rodrigues S, Raices RS, Silva MC, Sant’Ana AS, Cruz AG. Nuclear magnetic resonance as an analytical tool for monitoring the quality and authenticity of dairy foods. Trends Food Sci Technol 2021. [DOI: 10.1016/j.tifs.2020.12.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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18
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Ryl PSJ, Bohlke-Schneider M, Lenz S, Fischer L, Budzinski L, Stuiver M, Mendes MML, Sinn L, O'Reilly FJ, Rappsilber J. In Situ Structural Restraints from Cross-Linking Mass Spectrometry in Human Mitochondria. J Proteome Res 2019; 19:327-336. [PMID: 31746214 PMCID: PMC7010328 DOI: 10.1021/acs.jproteome.9b00541] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The field of structural biology is increasingly focusing on studying proteins in situ, i.e., in their greater biological context. Cross-linking mass spectrometry (CLMS) is contributing to this effort, typically through the use of mass spectrometry (MS)-cleavable cross-linkers. Here, we apply the popular noncleavable cross-linker disuccinimidyl suberate (DSS) to human mitochondria and identify 5518 distance restraints between protein residues. Each distance restraint on proteins or their interactions provides structural information within mitochondria. Comparing these restraints to protein data bank (PDB)-deposited structures and comparative models reveals novel protein conformations. Our data suggest, among others, substrates and protein flexibility of mitochondrial heat shock proteins. Through this study, we bring forward two central points for the progression of CLMS towards large-scale in situ structural biology: First, clustered conflicts of cross-link data reveal in situ protein conformation states in contrast to error-rich individual conflicts. Second, noncleavable cross-linkers are compatible with proteome-wide studies.
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Affiliation(s)
- Petra S J Ryl
- Bioanalytics, Institute of Biotechnology , Technische Universität Berlin , 13355 Berlin , Germany
| | - Michael Bohlke-Schneider
- Bioanalytics, Institute of Biotechnology , Technische Universität Berlin , 13355 Berlin , Germany
| | - Swantje Lenz
- Bioanalytics, Institute of Biotechnology , Technische Universität Berlin , 13355 Berlin , Germany
| | - Lutz Fischer
- Bioanalytics, Institute of Biotechnology , Technische Universität Berlin , 13355 Berlin , Germany.,Wellcome Centre for Cell Biology, School of Biological Sciences , University of Edinburgh , Edinburgh EH9 3BF , Scotland , United Kingdom
| | - Lisa Budzinski
- Bioanalytics, Institute of Biotechnology , Technische Universität Berlin , 13355 Berlin , Germany
| | - Marchel Stuiver
- Bioanalytics, Institute of Biotechnology , Technische Universität Berlin , 13355 Berlin , Germany
| | - Marta M L Mendes
- Bioanalytics, Institute of Biotechnology , Technische Universität Berlin , 13355 Berlin , Germany
| | - Ludwig Sinn
- Bioanalytics, Institute of Biotechnology , Technische Universität Berlin , 13355 Berlin , Germany
| | - Francis J O'Reilly
- Bioanalytics, Institute of Biotechnology , Technische Universität Berlin , 13355 Berlin , Germany
| | - Juri Rappsilber
- Bioanalytics, Institute of Biotechnology , Technische Universität Berlin , 13355 Berlin , Germany.,Wellcome Centre for Cell Biology, School of Biological Sciences , University of Edinburgh , Edinburgh EH9 3BF , Scotland , United Kingdom
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