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Katalaz Enzim Aktivite Ölçüm Yöntemleri: Literatürdeki Mevcut Yaklaşımlar, Karşılaştırmalar ve Yeni Perspektifler

Yıl 2026, Cilt: 9 Sayı: 2, 1204 - 1218, 16.03.2026
https://doi.org/10.47495/okufbed.1704381
https://izlik.org/JA64KP26CZ

Öz

Katalaz enzimi, hidrojen peroksidi su ve oksijene parçalayarak oksidatif stresi düzenleyen kritik bir antioksidan enzimdir. Memeliler, bitkiler ve aerobik organizmalarda yaygın olarak bulunur ve özellikle eritrositler, karaciğer ve böbrekte yüksek konsantrasyonlarda yer alır. Tetramerik bir yapıya sahip olan katalazın NADPH bağlı formu, oksidatif inaktivasyona karşı korunmasını sağlamaktadır. Bu çalışmada, katalaz aktivitesini belirlemeye yönelik spektrofotometrik, kolorimetrik, elektroanalitik, titrimetrik, kemilüminesans ve jel bazlı yöntemler karşılaştırılmıştır. Her yöntemin avantajları, dezavantajları ve kullanım alanları detaylı şekilde değerlendirilmiş, daha hassas ve güvenilir ölçüm teknikleri geliştirmek için öneriler sunulmuştur. Ayrıca, yapay zeka ve makine öğrenmesi destekli analizlerin katalaz aktivitesi ölçümlerinde nasıl kullanılabileceği ele alınmıştır. Makine öğrenmesi tabanlı regresyon modellerinin büyük veri kümelerinden yararlanarak katalaz aktivitesini tahmin edebileceği ve ölçüm hassasiyetini artırabileceği öne sürülmüştür. Bu derleme, katalaz aktivite ölçüm yöntemlerinin mevcut durumunu kapsamlı bir şekilde inceleyerek gelecekteki çalışmalar için yeni perspektifler sunmaktadır.

Kaynakça

  • Abbas A., Alroobaea R., Krichen M., Rubaiee S., Vimal S., Almansour FM. Blockchain-assisted secured data management framework for health information analysis based on Internet of Medical Things. Personal and Ubiquitous Computing 2024; 28(1): 59-72.
  • Anjum NA., Sharma P., Gill SS., Hasanuzzaman M., Khan EA., Kachhap K. Catalase and ascorbate peroxidase—Representative H2O2-detoxifying heme enzymes in plants. Environmental Science and Pollution Research 2016; 23(19): 19002-19029.
  • Aravapally PSN., Chandrasekar N., Verma A., Shah RP. Strategic approaches to assess and quantify the oxidative stress biomarkers in complex biological systems. Bioanalysis 2025; 1-14.
  • Boriskin P., Deviatkin A., Nikitin A., Pavlova O., Toropovskiy A. Relationship of catalase activity distribution in serum and tissues of small experimental animals. IOP Conf Ser: Earth Environ Sci 2019; 403(1): 012113.
  • Bukowska B., Chajdys A., Duda W., Duchnowicz P. Catalase activity in human erythrocytes: Effect of phenoxyherbicides and their metabolites. Cell Biology International 2000; 24(10): 705-711.
  • Burton GJ., Jauniaux E. Oxidative stress. Best Practice & Research Clinical Obstetrics & Gynaecology 2011; 25(3): 287-299.
  • Calabrese EJ., Canada AT. Catalase: Its role in xenobiotic detoxification. Pharmacology & Therapeutics 1989; 44(2): 297-307.
  • Chakraborty A. Development of a deep learning-enhanced chemiluminescence method for trace formaldehyde detection in water samples. Trans Comput Sci Methods 2025; 5(2).
  • Coremen M., Turkyilmaz IB., Us H., Us AS., Celik S., Ozel AE. Lupeol inhibits pesticides induced hepatotoxicity via reducing oxidative stress and inflammatory markers in rats. Food Chem Toxicol 2022; 164: 113068.
  • Dakal TC., Xu C., Kumar A. Advanced computational tools, artificial intelligence and machine-learning approaches in gut microbiota and biomarker identification. Front Med Technol 2025; 6: 1434799.
  • Das A., Paul P., Raj M., Sarkar A., De A., Banerjee T. Chemiluminescence-based biosensor: From principle to its applications. In: Fundamentals of Biosensors in Healthcare. Elsevier 2025: 315-336.
  • Das A., Prajapati P. Navigating pharmaceuticals: Microfluidic devices in analytical and formulation sciences. Discover Chemistry 2025; 2(1): 49.
  • Davidovic LM., Laketic D., Cumic J., Jordanova E., Pantic I. Application of artificial intelligence for detection of chemico-biological interactions associated with oxidative stress and DNA damage. Chem Biol Interact 2021; 345: 109533.
  • Farman AA., Hadwan MH. Simple kinetic method for assessing catalase activity in biological samples. MethodsX 2021; 8: 101434.
  • Gao S., Wang J., Miao Z., Zhao X., Zhang Y., Du W, et al. Artificial intelligence enhanced microfluidic system for multiplexed point-of-care-testing of biological thiols. Talanta 2025; 127619.
  • Ghavamipour F., Sajedi RH., Khajeh K. A chemiluminescence-based catalase assay using H2O2-sensitive CdTe quantum dots. Microchim Acta 2018; 185: 1-8.
  • Glorieux C., Zamocky M., Sandoval JM., Verrax J., Calderon PB. Regulation of catalase expression in healthy and cancerous cells. Free Radic Biol Med 2015; 87: 84-97.
  • Goth L. A simple method for determination of serum catalase activity and revision of reference range. Clin Chim Acta 1991; 196(2-3): 143-151.
  • Góth L., Rass P., Páy A. Catalase enzyme mutations and their association with diseases. Mol Diagn 2004; 8: 141-149.
  • Grilo LF., Martins JD., Cavallaro CH., Nathanielsz PW., Oliveira PJ., Pereira SP. Development of a 96-well based assay for kinetic determination of catalase enzymatic-activity in biological samples. Toxicol In Vitro 2020; 69: 104996.
  • Guliy OI., Dykman LA. Prospects for the use of nanozyme-based electrochemical and colorimetric sensors for antibiotic detection. Talanta 2025; 286: 127524.
  • Guo M., Tian S., Wang W., Xie L., Xu H., Huang K. Biomimetic leaves with immobilized catalase for machine learning-enabled validating fresh produce sanitation processes. Food Res Int 2024; 179: 114028.
  • Hadwan MH. Simple spectrophotometric assay for measuring catalase activity in biological tissues. BMC Biochem 2018; 19(1): 7.
  • Hadwan MH., Hussein MJ., Mohammed RM., Hadwan AM., Al-Kawaz SH., Al-Obaidy SS. An improved method for measuring catalase activity in biological samples. Biol Methods Protoc 2024; 9(1): bpae015.
  • Hadwan MH., Ali SK. New spectrophotometric assay for assessments of catalase activity in biological samples. Anal Biochem 2018; 542: 29-33.
  • Hamza TA., Hadwan MH. New spectrophotometric method for the assessment of catalase enzyme activity in biological tissues. Curr Anal Chem 2020; 16(8): 1054-1062.
  • Henle ES., Linn S. Formation, prevention, and repair of DNA damage by iron/hydrogen peroxide. J Biol Chem 1997; 272(31): 19095-19098.
  • Imlay JA., Chin SM., Linn S. Toxic DNA damage by hydrogen peroxide through the Fenton reaction in vivo and in vitro. Science 1988; 240(4852): 640-642.
  • Kirkman HN., Gaetani GF. Catalase: A tetrameric enzyme with four tightly bound molecules of NADPH. Proc Natl Acad Sci USA 1984; 81(14): 4343-4347.
  • Krishna H., Avinash K., Shivakumar A., Al-Tayar NGS., Shrestha AK. A quantitative method for the detection and validation of catalase activity at physiological concentration in human serum, plasma and erythrocytes. Spectrochim Acta A Mol Biomol Spectrosc 2021; 251: 119358.
  • Li W., Han L., Li D., Pu Z. High-frequency ultrasound based microfluidic chip for high-sensitive and quick-response electrochemical biosensing. Sens Actuators B Chem 2025; 427: 137204.
  • Martemucci G., Costagliola C., Mariano M, D’Andrea L., Napolitano P., D’Alessandro AG. Free radical properties, source and targets, antioxidant consumption and health. Oxygen 2022; 2(2): 48-78.
  • McIntyre RS., Cha DS., Jerrell JM., Swardfager W., Kim RD., Costa LG. Advancing biomarker research: Utilizing ‘Big Data’ approaches for the characterization and prevention of bipolar disorder. Bipolar Disord 2014; 16(5): 531-547.
  • Özyürek M., Bektaşoğlu B., Güçlü K., Apak R. Hydroxyl radical scavenging assay of phenolics and flavonoids with a modified cupric reducing antioxidant capacity (CUPRAC) method using catalase for hydrogen peroxide degradation. Anal Chim Acta 2008; 616(2): 196-206.
  • Pantic I., Paunovic J., Pejic S, Drakulic D., Todorovic A., Stankovic S. Artificial intelligence approaches to the biochemistry of oxidative stress: Current state of the art. Chem Biol Interact 2022; 358: 109888.
  • Ranaweera CB., Senadeera S., Peiris DHS., Fernando DTK. Assessment of in vitro anti-inflammatory activity: A comprehensive review of methods, advantages, and limitations. 2025.
  • Salimi A., Noorbakhsh A., Ghadermarz M. Direct electrochemistry and electrocatalytic activity of catalase incorporated onto multiwall carbon nanotubes-modified glassy carbon electrode. Anal Biochem 2005; 344(1): 16-24.
  • Saputra HA., Karim MM. Enzymatic and enzyme‐free electrochemical lactate sensors: A review of the recent developments. Electrochem Sci Adv 2025; 5(1): e202400021.
  • Sethu N., Premchandra P., Kolhe SB., Kulkarni MB., Vyas R. An integrated microfluidic device driven by an automated system for precise detection of antibiotics in water. Sens Actuators A Phys 2025; 388: 116474.
  • Sies H., Berndt C., Jones DP. Oxidative stress. Annu Rev Biochem 2017; 86(1): 715-748.
  • Storz G., Imlayt JA. Oxidative stress. Curr Opin Microbiol 1999; 2(2): 188-194.
  • Sun J., Duan S., Xu W., He W., Li T., Liu S. fully automated paper-based smartphone-assisted microfluidic chemiluminescence sample-to-result immunoassay platform. Anal Chim Acta 2025; 344013.
  • Tan J., Gao Y., Liang Z., Cao W., Pomeroy MJ., Huo Y. 3D-GLCM CNN: A 3-dimensional gray-level co-occurrence matrix-based CNN model for polyp classification via CT colonography. IEEE Trans Med Imaging 2019; 39(6): 2013-2024.
  • Van Der Vliet A., Janssen‐Heininger YMW. Hydrogen peroxide as a damage signal in tissue injury and inflammation: Murderer, mediator, or messenger? J Cell Biochem 2014; 115(3): 427-435.
  • Vetrano AM., Heck De., Mariano TM., Mishin V., Laskin DL., Laskin JD. Characterization of the oxidase activity in mammalian catalase. J Biol Chem 2005; 280(42): 35372-35381.
  • Wang B., Zhang X., Fang W., Rovira C., Shaik S. How do metalloproteins tame the Fenton reaction and utilize •OH radicals in constructive manners? Acc Chem Res 2022; 55(16): 2280-2290.
  • Wang GIJ., Fung DYC. Significance of bacterial catalase in food microbiology: A review. J Food Saf 1986; 8(1): 47-67.
  • Wang Y., Branicky R., Noë A., Hekimi S. Superoxide dismutases: Dual roles in controlling ROS damage and regulating ROS signaling. J Cell Biol 2018; 217(6): 1915-1928.
  • Wang Y., Han S., Wang Y., Liang Q., Luo W. Artificial intelligence technology assists enzyme prediction and rational design. J Agric Food Chem 2025; 73(12): 7065-7073.
  • Weydert CJ., Cullen JJ. Measurement of superoxide dismutase, catalase and glutathione peroxidase in cultured cells and tissue. Nat Protoc 2010; 5(1): 51-66.
  • Yaqoob I., Salah K., Jayaraman R., Al-Hammadi Y. Blockchain for healthcare data management: Opportunities, challenges, and future recommendations. Neural Comput Appl 2022; 1-16.
  • Zane P., Gieschen H, Kersten E, Mathias N, Ollier C, Johansson P, et al. In vivo models and decision trees for formulation development in early drug development: A review. Eur J Pharm Biopharm 2019; 142: 222-231.
  • Zhao MX., Wen JL., Wang L., Wang XP., Chen TS. Intracellular catalase activity instead of glutathione level dominates the resistance of cells to reactive oxygen species. Cell Stress Chaperones 2019; 24(3): 609-619.

Catalase Enzyme Activity Measurement Methods: Current Approaches, Comparisons, and New Perspectives in the Literature

Yıl 2026, Cilt: 9 Sayı: 2, 1204 - 1218, 16.03.2026
https://doi.org/10.47495/okufbed.1704381
https://izlik.org/JA64KP26CZ

Öz

Catalase is a critical antioxidant enzyme that regulates oxidative stress by breaking down hydrogen peroxide into water and oxygen. It is commonly found in mammals, plants, and aerobic organisms, with particularly high concentrations in erythrocytes, the liver, and kidneys. The NADPH-bound form of catalase, which has a tetrameric structure, protects the enzyme from oxidative inactivation. This study compared spectrophotometric, colorimetric, electroanalytical, titrimetric, chemiluminescence-based, and gel-based methods for determining catalase activity. Each method's advantages, disadvantages, and application areas were evaluated in detail, and suggestions were presented for developing more sensitive and reliable measurement techniques. In addition, the potential use of artificial intelligence and machine learning-supported analyses in measuring catalase activity was discussed. It was proposed that machine learning-based regression models could utilize large datasets to predict catalase activity and enhance measurement accuracy. This review comprehensively examines the current state of catalase activity measurement methods and offers new perspectives for future research.

Kaynakça

  • Abbas A., Alroobaea R., Krichen M., Rubaiee S., Vimal S., Almansour FM. Blockchain-assisted secured data management framework for health information analysis based on Internet of Medical Things. Personal and Ubiquitous Computing 2024; 28(1): 59-72.
  • Anjum NA., Sharma P., Gill SS., Hasanuzzaman M., Khan EA., Kachhap K. Catalase and ascorbate peroxidase—Representative H2O2-detoxifying heme enzymes in plants. Environmental Science and Pollution Research 2016; 23(19): 19002-19029.
  • Aravapally PSN., Chandrasekar N., Verma A., Shah RP. Strategic approaches to assess and quantify the oxidative stress biomarkers in complex biological systems. Bioanalysis 2025; 1-14.
  • Boriskin P., Deviatkin A., Nikitin A., Pavlova O., Toropovskiy A. Relationship of catalase activity distribution in serum and tissues of small experimental animals. IOP Conf Ser: Earth Environ Sci 2019; 403(1): 012113.
  • Bukowska B., Chajdys A., Duda W., Duchnowicz P. Catalase activity in human erythrocytes: Effect of phenoxyherbicides and their metabolites. Cell Biology International 2000; 24(10): 705-711.
  • Burton GJ., Jauniaux E. Oxidative stress. Best Practice & Research Clinical Obstetrics & Gynaecology 2011; 25(3): 287-299.
  • Calabrese EJ., Canada AT. Catalase: Its role in xenobiotic detoxification. Pharmacology & Therapeutics 1989; 44(2): 297-307.
  • Chakraborty A. Development of a deep learning-enhanced chemiluminescence method for trace formaldehyde detection in water samples. Trans Comput Sci Methods 2025; 5(2).
  • Coremen M., Turkyilmaz IB., Us H., Us AS., Celik S., Ozel AE. Lupeol inhibits pesticides induced hepatotoxicity via reducing oxidative stress and inflammatory markers in rats. Food Chem Toxicol 2022; 164: 113068.
  • Dakal TC., Xu C., Kumar A. Advanced computational tools, artificial intelligence and machine-learning approaches in gut microbiota and biomarker identification. Front Med Technol 2025; 6: 1434799.
  • Das A., Paul P., Raj M., Sarkar A., De A., Banerjee T. Chemiluminescence-based biosensor: From principle to its applications. In: Fundamentals of Biosensors in Healthcare. Elsevier 2025: 315-336.
  • Das A., Prajapati P. Navigating pharmaceuticals: Microfluidic devices in analytical and formulation sciences. Discover Chemistry 2025; 2(1): 49.
  • Davidovic LM., Laketic D., Cumic J., Jordanova E., Pantic I. Application of artificial intelligence for detection of chemico-biological interactions associated with oxidative stress and DNA damage. Chem Biol Interact 2021; 345: 109533.
  • Farman AA., Hadwan MH. Simple kinetic method for assessing catalase activity in biological samples. MethodsX 2021; 8: 101434.
  • Gao S., Wang J., Miao Z., Zhao X., Zhang Y., Du W, et al. Artificial intelligence enhanced microfluidic system for multiplexed point-of-care-testing of biological thiols. Talanta 2025; 127619.
  • Ghavamipour F., Sajedi RH., Khajeh K. A chemiluminescence-based catalase assay using H2O2-sensitive CdTe quantum dots. Microchim Acta 2018; 185: 1-8.
  • Glorieux C., Zamocky M., Sandoval JM., Verrax J., Calderon PB. Regulation of catalase expression in healthy and cancerous cells. Free Radic Biol Med 2015; 87: 84-97.
  • Goth L. A simple method for determination of serum catalase activity and revision of reference range. Clin Chim Acta 1991; 196(2-3): 143-151.
  • Góth L., Rass P., Páy A. Catalase enzyme mutations and their association with diseases. Mol Diagn 2004; 8: 141-149.
  • Grilo LF., Martins JD., Cavallaro CH., Nathanielsz PW., Oliveira PJ., Pereira SP. Development of a 96-well based assay for kinetic determination of catalase enzymatic-activity in biological samples. Toxicol In Vitro 2020; 69: 104996.
  • Guliy OI., Dykman LA. Prospects for the use of nanozyme-based electrochemical and colorimetric sensors for antibiotic detection. Talanta 2025; 286: 127524.
  • Guo M., Tian S., Wang W., Xie L., Xu H., Huang K. Biomimetic leaves with immobilized catalase for machine learning-enabled validating fresh produce sanitation processes. Food Res Int 2024; 179: 114028.
  • Hadwan MH. Simple spectrophotometric assay for measuring catalase activity in biological tissues. BMC Biochem 2018; 19(1): 7.
  • Hadwan MH., Hussein MJ., Mohammed RM., Hadwan AM., Al-Kawaz SH., Al-Obaidy SS. An improved method for measuring catalase activity in biological samples. Biol Methods Protoc 2024; 9(1): bpae015.
  • Hadwan MH., Ali SK. New spectrophotometric assay for assessments of catalase activity in biological samples. Anal Biochem 2018; 542: 29-33.
  • Hamza TA., Hadwan MH. New spectrophotometric method for the assessment of catalase enzyme activity in biological tissues. Curr Anal Chem 2020; 16(8): 1054-1062.
  • Henle ES., Linn S. Formation, prevention, and repair of DNA damage by iron/hydrogen peroxide. J Biol Chem 1997; 272(31): 19095-19098.
  • Imlay JA., Chin SM., Linn S. Toxic DNA damage by hydrogen peroxide through the Fenton reaction in vivo and in vitro. Science 1988; 240(4852): 640-642.
  • Kirkman HN., Gaetani GF. Catalase: A tetrameric enzyme with four tightly bound molecules of NADPH. Proc Natl Acad Sci USA 1984; 81(14): 4343-4347.
  • Krishna H., Avinash K., Shivakumar A., Al-Tayar NGS., Shrestha AK. A quantitative method for the detection and validation of catalase activity at physiological concentration in human serum, plasma and erythrocytes. Spectrochim Acta A Mol Biomol Spectrosc 2021; 251: 119358.
  • Li W., Han L., Li D., Pu Z. High-frequency ultrasound based microfluidic chip for high-sensitive and quick-response electrochemical biosensing. Sens Actuators B Chem 2025; 427: 137204.
  • Martemucci G., Costagliola C., Mariano M, D’Andrea L., Napolitano P., D’Alessandro AG. Free radical properties, source and targets, antioxidant consumption and health. Oxygen 2022; 2(2): 48-78.
  • McIntyre RS., Cha DS., Jerrell JM., Swardfager W., Kim RD., Costa LG. Advancing biomarker research: Utilizing ‘Big Data’ approaches for the characterization and prevention of bipolar disorder. Bipolar Disord 2014; 16(5): 531-547.
  • Özyürek M., Bektaşoğlu B., Güçlü K., Apak R. Hydroxyl radical scavenging assay of phenolics and flavonoids with a modified cupric reducing antioxidant capacity (CUPRAC) method using catalase for hydrogen peroxide degradation. Anal Chim Acta 2008; 616(2): 196-206.
  • Pantic I., Paunovic J., Pejic S, Drakulic D., Todorovic A., Stankovic S. Artificial intelligence approaches to the biochemistry of oxidative stress: Current state of the art. Chem Biol Interact 2022; 358: 109888.
  • Ranaweera CB., Senadeera S., Peiris DHS., Fernando DTK. Assessment of in vitro anti-inflammatory activity: A comprehensive review of methods, advantages, and limitations. 2025.
  • Salimi A., Noorbakhsh A., Ghadermarz M. Direct electrochemistry and electrocatalytic activity of catalase incorporated onto multiwall carbon nanotubes-modified glassy carbon electrode. Anal Biochem 2005; 344(1): 16-24.
  • Saputra HA., Karim MM. Enzymatic and enzyme‐free electrochemical lactate sensors: A review of the recent developments. Electrochem Sci Adv 2025; 5(1): e202400021.
  • Sethu N., Premchandra P., Kolhe SB., Kulkarni MB., Vyas R. An integrated microfluidic device driven by an automated system for precise detection of antibiotics in water. Sens Actuators A Phys 2025; 388: 116474.
  • Sies H., Berndt C., Jones DP. Oxidative stress. Annu Rev Biochem 2017; 86(1): 715-748.
  • Storz G., Imlayt JA. Oxidative stress. Curr Opin Microbiol 1999; 2(2): 188-194.
  • Sun J., Duan S., Xu W., He W., Li T., Liu S. fully automated paper-based smartphone-assisted microfluidic chemiluminescence sample-to-result immunoassay platform. Anal Chim Acta 2025; 344013.
  • Tan J., Gao Y., Liang Z., Cao W., Pomeroy MJ., Huo Y. 3D-GLCM CNN: A 3-dimensional gray-level co-occurrence matrix-based CNN model for polyp classification via CT colonography. IEEE Trans Med Imaging 2019; 39(6): 2013-2024.
  • Van Der Vliet A., Janssen‐Heininger YMW. Hydrogen peroxide as a damage signal in tissue injury and inflammation: Murderer, mediator, or messenger? J Cell Biochem 2014; 115(3): 427-435.
  • Vetrano AM., Heck De., Mariano TM., Mishin V., Laskin DL., Laskin JD. Characterization of the oxidase activity in mammalian catalase. J Biol Chem 2005; 280(42): 35372-35381.
  • Wang B., Zhang X., Fang W., Rovira C., Shaik S. How do metalloproteins tame the Fenton reaction and utilize •OH radicals in constructive manners? Acc Chem Res 2022; 55(16): 2280-2290.
  • Wang GIJ., Fung DYC. Significance of bacterial catalase in food microbiology: A review. J Food Saf 1986; 8(1): 47-67.
  • Wang Y., Branicky R., Noë A., Hekimi S. Superoxide dismutases: Dual roles in controlling ROS damage and regulating ROS signaling. J Cell Biol 2018; 217(6): 1915-1928.
  • Wang Y., Han S., Wang Y., Liang Q., Luo W. Artificial intelligence technology assists enzyme prediction and rational design. J Agric Food Chem 2025; 73(12): 7065-7073.
  • Weydert CJ., Cullen JJ. Measurement of superoxide dismutase, catalase and glutathione peroxidase in cultured cells and tissue. Nat Protoc 2010; 5(1): 51-66.
  • Yaqoob I., Salah K., Jayaraman R., Al-Hammadi Y. Blockchain for healthcare data management: Opportunities, challenges, and future recommendations. Neural Comput Appl 2022; 1-16.
  • Zane P., Gieschen H, Kersten E, Mathias N, Ollier C, Johansson P, et al. In vivo models and decision trees for formulation development in early drug development: A review. Eur J Pharm Biopharm 2019; 142: 222-231.
  • Zhao MX., Wen JL., Wang L., Wang XP., Chen TS. Intracellular catalase activity instead of glutathione level dominates the resistance of cells to reactive oxygen species. Cell Stress Chaperones 2019; 24(3): 609-619.
Toplam 53 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Biyokimya ve Hücre Biyolojisi (Diğer)
Bölüm Derleme
Yazarlar

Meryem Sena Akkuş 0000-0003-2550-550X

Ceylan Bal 0000-0002-1678-1281

Gönderilme Tarihi 22 Mayıs 2025
Kabul Tarihi 22 Ekim 2025
Yayımlanma Tarihi 16 Mart 2026
DOI https://doi.org/10.47495/okufbed.1704381
IZ https://izlik.org/JA64KP26CZ
Yayımlandığı Sayı Yıl 2026 Cilt: 9 Sayı: 2

Kaynak Göster

APA Akkuş, M. S., & Bal, C. (2026). Katalaz Enzim Aktivite Ölçüm Yöntemleri: Literatürdeki Mevcut Yaklaşımlar, Karşılaştırmalar ve Yeni Perspektifler. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 9(2), 1204-1218. https://doi.org/10.47495/okufbed.1704381
AMA 1.Akkuş MS, Bal C. Katalaz Enzim Aktivite Ölçüm Yöntemleri: Literatürdeki Mevcut Yaklaşımlar, Karşılaştırmalar ve Yeni Perspektifler. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 2026;9(2):1204-1218. doi:10.47495/okufbed.1704381
Chicago Akkuş, Meryem Sena, ve Ceylan Bal. 2026. “Katalaz Enzim Aktivite Ölçüm Yöntemleri: Literatürdeki Mevcut Yaklaşımlar, Karşılaştırmalar ve Yeni Perspektifler”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 9 (2): 1204-18. https://doi.org/10.47495/okufbed.1704381.
EndNote Akkuş MS, Bal C (01 Mart 2026) Katalaz Enzim Aktivite Ölçüm Yöntemleri: Literatürdeki Mevcut Yaklaşımlar, Karşılaştırmalar ve Yeni Perspektifler. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 9 2 1204–1218.
IEEE [1]M. S. Akkuş ve C. Bal, “Katalaz Enzim Aktivite Ölçüm Yöntemleri: Literatürdeki Mevcut Yaklaşımlar, Karşılaştırmalar ve Yeni Perspektifler”, Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 9, sy 2, ss. 1204–1218, Mar. 2026, doi: 10.47495/okufbed.1704381.
ISNAD Akkuş, Meryem Sena - Bal, Ceylan. “Katalaz Enzim Aktivite Ölçüm Yöntemleri: Literatürdeki Mevcut Yaklaşımlar, Karşılaştırmalar ve Yeni Perspektifler”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 9/2 (01 Mart 2026): 1204-1218. https://doi.org/10.47495/okufbed.1704381.
JAMA 1.Akkuş MS, Bal C. Katalaz Enzim Aktivite Ölçüm Yöntemleri: Literatürdeki Mevcut Yaklaşımlar, Karşılaştırmalar ve Yeni Perspektifler. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 2026;9:1204–1218.
MLA Akkuş, Meryem Sena, ve Ceylan Bal. “Katalaz Enzim Aktivite Ölçüm Yöntemleri: Literatürdeki Mevcut Yaklaşımlar, Karşılaştırmalar ve Yeni Perspektifler”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 9, sy 2, Mart 2026, ss. 1204-18, doi:10.47495/okufbed.1704381.
Vancouver 1.Meryem Sena Akkuş, Ceylan Bal. Katalaz Enzim Aktivite Ölçüm Yöntemleri: Literatürdeki Mevcut Yaklaşımlar, Karşılaştırmalar ve Yeni Perspektifler. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 01 Mart 2026;9(2):1204-18. doi:10.47495/okufbed.1704381

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