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Enregistrement W1488676333 · doi:10.1002/bkcs.10245

Spectral Changes in Infrared and Raman Spectra of Mice Serum Exposed to Gamma Radiation

2015· article· en· W1488676333 sur OpenAlexaboutno aff
Yeonju Park, Yujing Chen, Mooryeong Seo, J. Cho, Yu‐Jin Jung, Young Mee Jung

Notice bibliographique

RevueBulletin of the Korean Chemical Society · 2015
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueSpectroscopy Techniques in Biomedical and Chemical Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésRaman spectroscopyRadiationInfraredSpectral lineChemistryRadiochemistryNuclear magnetic resonanceMaterials sciencePhysicsOpticsAstronomy

Résumé

récupéré en direct d'OpenAlex

Acute radiation syndrome (ARS) is the collection of biological hazardous effects that present within 24 h of exposure to high amounts of ionizing radiation. Exposure to ionizing radiation causes cellular degradation via damage to the biomolecules, including DNA, inside cells. The damage to DNA and other key molecules affects the ability to perform normal cell division and thus leads to severe health problems. The symptoms can begin within 1 or 2 h and may last for several months. Therefore, ARS is defined as clinical manifestations that include a prodromal stage that can progress to hematopoietic, gastrointestinal, cutaneous or central nervous system syndrome.1 Given that the onset and type of symptoms depend on the radiation dose, three to four clinical stages of severity ranges are classified. Generally, patients can be cured naturally when they are exposed to less than 1.5 Gy, a relatively small dose. Exposure to more than 2 Gy produces clinical ARS. Exposure to less than 5 Gy can strongly affect the hematopoietic system, which is very sensitive, and this effect decreases the number of lymphocytes in blood depending on the radiation dose. In addition, a high dose of radiation of more than 8 Gy increases the mortality rate, even for patients who receive intensive care treatment. Relatively large doses can result in gastrointestinal and neurological effects and rapid death.2 Because ARS symptoms are diverse and nonspecific, ARS cannot be diagnosed easily. In the absence of neurovascular symptoms, the signs and symptoms that are used to make a diagnosis as ARS rarely appear until 24 or 48 h after the radiation exposure. Usually, the lymphocyte count within the first 24–48 h and the first symptoms of vomiting and nausea are indicators used to make the diagnosis and determine the prognosis of ARS. Measuring an absolute lymphocyte count is the quickest and easiest laboratory test that will provide an estimate of the exposure. Although other clinical and biological methods have been developed, few approaches have been introduced that can assess the severity of ARS damage.3 Therefore, to successfully treat ARS and prolong the life of subjects with ARS, it is essential and important to develop a more rapid and easier technique for diagnosing ARS after radiation exposure without the patient history. In this study, for the early detection of ARS, we used vibrational spectroscopy to examine the serum of mice within 24 h exposure to gamma radiation. Infrared (IR) and Raman spectroscopy techniques can elucidate the structural changes of damaged proteins when cells or animals have been exposed to radiation. IR spectroscopy is a very useful tool to investigate the structural changes of proteins.4-7 The analysis of IR spectra of protein secondary structure is mostly based on the amide I region. Here, we only focused on analyzing the amide I band of IR spectra, in which the correlation between structure and spectra is the most well-established. Raman spectra are rich in signatures from side-chain vibrations and from vibrations of the polypeptide backbone; therefore, these spectra facilitate discussions of changes.8-11 Raman spectra can thus provide alternative and often complementary information to that of IR spectra. Figure 1 shows the IR spectra of mouse serum before and after 10 Gy of radiation exposure and the secondary derivative of the IR spectra. The IR spectra before and after the radiation exposure are very similar; thus, a clear interpretation of the irradiation-induced spectral changes is not possible. In addition, the broad amide I band at approximately 1646 cm−1 is the highly overlapped bands, making it difficult to identify the spectral changes that correspond to changes in the secondary structure of proteins. To distinguish the subtle spectral changes after radiation exposure, the secondary derivatives of the IR spectra were analyzed. As shown in Figure 1, in the secondary derivatives of the IR spectra, there are two distinct bands in the amide I region. These two bands at 1653 and 1631 cm−1 that are resolved in the secondary derivatives of the IR spectra are assigned to the α-helical and β-sheet regions, respectively, of protein.12-14 The relative intensity ratio of these two bands, I 1650/I 1630, in the IR spectra before and after radiation exposure are 1.95 and 2.98, respectively. The intensity of the α-helix band increases more than that of the β-sheet band after the mouse is exposed to gamma radiation. This finding demonstrates that the protein secondary structure in mouse serum changes under radiation exposure. Therefore, this increase in the relative intensity ratio I 1650/I 1630 may provide evidence of ARS, which can be used for the early detection of ARS. To identify the additional features that could be used to detect ARS in mice within 24 h of exposure gamma radiation, we also analyzed the Raman spectra of the mouse serum before and after radiation exposure. The corresponding Raman spectra are shown in Figure 2. The intensities of bands at 2930, 1562, and 1002 cm−1, which are contributed to the CH stretching modes, tryptophan, and phenylalanine, respectively, of proteins increase after radiation exposure.15-18 The relative intensity ratio of these bands, I 2930/I 2889 and I 1562/I 1547, in the Raman spectra increase after radiation exposure. Furthermore, a band at 1339 cm−1 is assigned to tryptophan of proteins and the relative intensity ratio of bands, I 1339/I 1374, in the Raman spectra increases after radiation exposure. These results clearly show that the protein structure of mouse serum changes after radiation exposure, indicating the cell damage caused by the radiation exposure. Sudden exposure of human populations to radiation in accidental situations, terror, or warfare has the potential to result in substantial morbidity. The protection against and diagnosis and treatment of such hazardous circumstances are essential topics of research. A rapid and precise assessment of the severity of the damage after radiation exposure could be helpful for treating patients and decreasing the mortality. In this study, we examined the spectral changes of both IR and Raman spectra to detect the degree of radiation injury. The characteristic IR and Raman bands are crucial for the early detection of ARS. This result can provide new insight into evaluating the degree of damage in mammals after radiation exposure. To our knowledge, this analysis is the first to use the IR and Raman spectra of animal body fluids after exposure to gamma irradiation for the early detection of ARS, although many studies have been reported biological approaches for diagnosing ARS in patients. For better detection of ARS damage, we are investigating a quantitative analysis of the degree of radiation exposure damage in organisms as a function of the dose of gamma irradiation using IR and Raman spectroscopy. The results will be reported elsewhere. Male C57BL/6 mice were purchased from Nara Biotech (Pyeong-Taek, Korea) at 6–8 weeks of age. All mice used in this study were handled in accordance with the guidelines approved by the Institutional Animal Care and Use Committee of Kangwon National University. Mice were irradiated by whole-body irradiation (10 Gy; dose rate of 0.6 Gy/min) using a Cesium-137 Gammacell unit (Gammacell 3000 Elan; Best Theratronics Ltd, Kanata, ON, Canada). After 30 min to 1 h of irradiation, the mice were anesthetized, and then blood was drawn from the heart by cardiac puncture. The total blood sample in a heparinized tube was centrifuged at 12 000 rpm for 15 min, and then, the plasma was isolated. The FTIR spectra were obtained on a Nicolet 6700 FT-IR spectrometer (Marietta, OH, USA) equipped with a liquid nitrogen-cooled MCT detector. For each spectrum, 1024 scans with a spectral resolution of 4 cm−1 were collected. For the ATR measurements, a drop aliquot of either the protein solution or water was placed on the surface of a diamond crystal plate (face angle: 45°; Pike Technologies, Inc., Fitchburg, WI, USA). The temperature of the sample during scanning was kept constant at 25 °C. For the IR spectra, both baseline correction by means of a linear function and normalization to a constant total area in the analyzed region were performed. The Raman spectra were recorded using a Jobin Yvon/HORIBA LabRam ARAMIS Raman spectrometer (Villeneuve-d'Ascq, France). Radiation from a diode pumped solid state laser (532 nm) was used as the excitation source. Raman scattering was detected at using a 180° geometry and a multichannel air-cooled (−70 °C) charge-coupled device (CCD) camera (1024 × 256 pixels). The typical exposure time for each Raman measurement in this study was 20 s for one acquisition. All Raman spectra were also measured at 25 °C. Both baseline correction by means of a linear function and normalization using a standard band at 674 cm−1 were performed for the Raman spectra. This study supported by the National Research Foundation of Korea (NRF) grant funded by the Ministry of Science, ICT and future Planning (No. 2014M2B2A9030381). The authors thank the Central Laboratory of Kangwon National University for the measurements of Raman spectra.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,022
Score d'incertitude au seuil0,361

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,013
Tête enseignante GPT0,269
Écart entre enseignants0,256 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission1
Résumé présentoui

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