Çalışkan Bilgin, Gülizar

Loading...
Profile Picture
Name Variants
Caliskan, Gulizar
Bilgin, Gülizar Çalışkan
Caliskan Bilgin, Gulizar
Caliskan, Guelizar
Çalışkan, Gülizar
Job Title
Email Address
gulizar.caliskan@ieu.edu.tr
Main Affiliation
05.08. Genetics and Bioengineering
Status
Current Staff
Website
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

11

SUSTAINABLE CITIES AND COMMUNITIES
SUSTAINABLE CITIES AND COMMUNITIES Logo

0

Research Products

4

QUALITY EDUCATION
QUALITY EDUCATION Logo

0

Research Products

8

DECENT WORK AND ECONOMIC GROWTH
DECENT WORK AND ECONOMIC GROWTH Logo

0

Research Products

12

RESPONSIBLE CONSUMPTION AND PRODUCTION
RESPONSIBLE CONSUMPTION AND PRODUCTION Logo

0

Research Products

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
INDUSTRY, INNOVATION AND INFRASTRUCTURE Logo

1

Research Products

15

LIFE ON LAND
LIFE ON LAND Logo

0

Research Products

6

CLEAN WATER AND SANITATION
CLEAN WATER AND SANITATION Logo

0

Research Products

1

NO POVERTY
NO POVERTY Logo

0

Research Products

7

AFFORDABLE AND CLEAN ENERGY
AFFORDABLE AND CLEAN ENERGY Logo

0

Research Products

10

REDUCED INEQUALITIES
REDUCED INEQUALITIES Logo

0

Research Products

14

LIFE BELOW WATER
LIFE BELOW WATER Logo

0

Research Products

2

ZERO HUNGER
ZERO HUNGER Logo

0

Research Products

13

CLIMATE ACTION
CLIMATE ACTION Logo

0

Research Products

5

GENDER EQUALITY
GENDER EQUALITY Logo

0

Research Products

16

PEACE, JUSTICE AND STRONG INSTITUTIONS
PEACE, JUSTICE AND STRONG INSTITUTIONS Logo

0

Research Products

17

PARTNERSHIPS FOR THE GOALS
PARTNERSHIPS FOR THE GOALS Logo

0

Research Products

3

GOOD HEALTH AND WELL-BEING
GOOD HEALTH AND WELL-BEING Logo

3

Research Products
Documents

13

Citations

197

h-index

5

Documents

13

Citations

161

Scholarly Output

13

Articles

7

Views / Downloads

34/55

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

53

Scopus Citation Count

72

WoS h-index

4

Scopus h-index

5

Patents

0

Projects

0

WoS Citations per Publication

4.08

Scopus Citations per Publication

5.54

Open Access Source

4

Supervised Theses

0

Google Analytics Visitor Traffic

JournalCount
Proceedıngs of the Internatıonal Conference on Medıcal And Bıologıcal Engıneerıng, Cmbebıh 20192
Asia-Pacific Journal of Chemical Engineering2
Tıp Teknolojılerı Kongresı (Tıptekno'21)2
IFMBE Proceedings1
2024 Medical Technologies Congress -- OCT 10-12, 2024 -- Bodrum, TURKIYE1
Current Page: 1 / 2

Scopus Quartile Distribution

Competency Cloud

GCRIS Competency Cloud

Scholarly Output Search Results

Now showing 1 - 10 of 13
  • Article
    Citation - WoS: 25
    Citation - Scopus: 28
    Green Synthesis and Characterization of Titanium Nanoparticles Using Microalga, Phaeodactylum Tricornutum
    (Taylor & Francis Inc, 2022) Çalışkan, Gülizar; Mutaf, Tuğçe; Agba, Hasan Cenk; Elibol, Murat
    Nanoparticles synthesized from microalgae offer a newly discovered process that is open to improvement. In this study supernatant of Phaeodactylum tricornutum (P. tricornutum) culture was used for this purpose. Firstly, the effects of some variables, namely titanium concentrations, titanium:supernatant ratio, pH, incubation time, and mixing speed on nanoparticle synthesis were investigated by using statistical design method in shaken culture as well as bioreactor. The average nanoparticle size synthesized in optimum conditions which were pH 7.5 with 300 rpm for 1 h was found as 50 nm. In the second part, nanoparticles were coated with a chitosan solution to protect their stability and increase their potential. Therefore, the antimicrobial activity showed a reasonable effect on these nanoparticles coated with chitosan. Nanoparticles produced had interestingly shown 99% antistatic properties. According to the cytotoxicity test, these nanoparticles showed a high cytotoxic effect on different cancer cell lines. The results obtained in the present study can be considered promising outcomes for possible future antimicrobial, biogenic and antistatic studies particularly in biomedical applications.
  • Article
    Optimization and Characterization of Aspirin- and Ibuprofen-Loaded Lipid-Based Nanoparticle Synthesis for Antibacterial Activity and Cytotoxic Effect
    (Wiley, 2025) Caliskan, Gulizar; Ergonul, Smyrna; Cansu, Zuhal Naz; Kaplan, Busra
    Lipid-based nanoparticles (LNPs) are favored for drug delivery because of their low toxicity, high biocompatibility, ability to self-assemble into nanoparticles, and ability to enhance drug bioavailability, thereby improving drug release modulation and pharmacokinetics. In this study, the regional palm fruit extract and thyme oil were used as an oil source for the synthesis of LNPs with/without drugs. The Design Expert statistical software program, Central Composite Design (CCD) method was used to optimize the effect of drug:lipid ratio (1:3-1:7), drug type (ibuprofen or aspirin) and incubation time (5-15 min) on encapsulation efficiency (EE%), and antibacterial activity. The maximum EE% of 94% was achieved using ibuprofen at a drug:lipid ratio of 1:7 with a 5-min incubation time. Physicochemical characterization showed the inclusion of both aspirin and ibuprofen imparted a strong negative charge (up to -15 mV) and yielded average sizes ranging from 180 to 560 nm. Furthermore, ibuprofen- and aspirin-loaded LNPs exhibited promising cytotoxic effects on the hepatocarcinoma cell line (Huh7), showing 50% and 70% viability at a concentration of 50 mu M, respectively. Ultimately, the demonstrated efficacy of palmitic acid-incorporated LNP formulations suggests a significant potential for these optimized carriers to improve the therapeutic efficacy of antitumor drugs in clinical applications.
  • Article
    Citation - WoS: 3
    Metal Nanopartiküllerin Mikroalgler Aracılığı ile Yeşil Sentezi
    (2023) Mutaf, Tuğçe; Çalışkan Bilgin, Gülizar; Öncel, Suphi; Elibol, Murat
    Yeşil sentez olarak adlandırılan, nanopartiküllerin biyolojik kaynaklar aracılığı ile sentezlenmesine olan ilgi son yıllarda artış göstermiştir. Bunun temel nedeni geleneksel yöntemler olan fiziksel ve kimyasal yöntemlerde indirgeyici ve stabilize edici ajanlar olarak yüksek miktarlarda toksik kimyasala ihtiyaç duyuluyor olmasıdır. Daha çevre dostu ve insan sağlığı için tehdit oluşturmayan bitki, fungus, bakteri, alg gibi organizmalar yeşil nanopartikül sentezi için alternatif kaynaklardır. Sucul mikroorganizmalar olan mikroalgler üretmiş oldukları proteinler, vitaminler, pigmentler, yağ asitleri, hücre içi- hücre dışı polisakkaritler gibi fonksiyonel özelliğe sahip metabolitler sayesinde uzun yıllardır gıda, kozmetik ve ilaç endüstrilerinde formülasyonlara eklenmektedir. Bunların yanı sıra, son yıllarda yapılan çalışmalarla nanopartikül sentezinde de yüksek potansiyele sahip oldukları görülmüştür. Özellikle metal iyonlarının depolanmasını ve detoksifikasyonunu yapabildiklerinden ve metal iyonlarını elementel hale indirgeyen hücre içi ve hücre dışı metabolitlerce zengin olduklarından, metal nanopartiküllerin sentezi için yüksek potansiyele sahiptirler. Son yıllarda mikroalglerden nanopartikül sentezine odaklanmış olan yayın sayısı artmış ve pek çok mikroalg türünün gümüş, altın, titanyum, çinko, demir vb. metal nanopartikülleri hücre içi ve hücre dışı yollarla sentezleme potansiyeli araştırılmıştır. Bu derleme makale kapsamında, nanopartikül sentezi için çalışılmış olan mikroalg ve siyanobakteri türleri, kullanılan farklı sentez yöntemleri, nanopartiküllerin sentez mekanizması, temel karakterizasyon yöntemleri ve yeşil sentezle üretilen nanopartiküllerin antimikrobiyal aktivitelerine odaklanılmıştır
  • Article
    Green Synthesized Silver Nanoparticles in Two Stages: Box Behnken Design To Machine Learning
    (Taylor & Francis Inc, 2024) Çalışkan, Gülizar; Kumluca Topallı, Ayca
    In order to solve the modeling issues due to data scarcity problems in the disciplines utilizing statistical approximations, a novel two-stage idea is proposed. As a use case, nanoparticle biosynthesis was selected, for which an environmentally friendly process is of vital importance. First, Box Behnken Design was used for experimental setup, quadratic model formulation and data generation. The second stage consists of Machine Learning, in which the data generated in the previous stage were fed into a Neural Network to determine the relationship between the parameters. Obtained results showed that the proposed combined strategy provided better nanoparticle size estimations than the statistical approach alone. In the absence of publicly available databases, data generation using experimental design and machine learning, as proposed here, could be a faster, lower-cost, and greener solution. Our proposed method can be applied to a wide range of biotechnology and bioengineering applications with significant advanced knowledge.
  • Conference Object
    Nanopartikül Biyosentezinde Ortalama Çap Tahmini ve Optimizasyonu için Yanıt Yüzeyi Yöntemi ve Makine Öğreniminin Birleştirilmesi
    (IEEE, 2024) Çalışkan Bilgin, Gülizar; Topalli, Ayca Kumluca; Kilic, Tugce Mutaf; Elibol, Murat
    The synthesis of nanoparticles from biological sources by green synthesis method and production optimization studies are increasing in popularity today. However, the variability of biological source and environmental effects in such processes leads to different morphology and functionality in the final product. In this study, microalgae was used as a bioreduction agent in nanoparticle synthesis and analyses of the harmonic mean particle diameter of FeSO4 concentration and its ratio with microalgae medium were carried out in particle synthesis. In this two-stage study, the experimental design was carried out first, and the particle diameters obtained by data generation were developed by machine learning. The error rates at both stages were compared and improvements were recorded. As a result, a new low-cost, fast, simple and environmentally friendly approach was introduced to solve the data insufficiency problem and used in particle diameter estimation. The results obtained showed that the proposed combined strategy provides better nanoparticle size estimates than the statistical approach alone. The proposed method is applicable to a wide range of biotechnology and bioengineering applications with significant advanced knowledge.
  • Conference Object
    Citation - WoS: 2
    Citation - Scopus: 7
    Prediction of Sleep Apnea Using Eeg Signals and Machine Learning Algorithms
    (IEEE, 2021) Onargan, Aysu; Gavcar, Busra; Çalışkan, Gülizar; Akan, Aydin
    A lot of research has been done on sleep disorders from past to present. Sleep apnea, which we frequently encounter today, is one of the important sleep disorders that threaten human life. This situation that occurs during sleep also affects the daily life of the individual. Obstructive sleep apnea syndrome (OSAS) is a respiratory tract disorder with a prevalence of almost 4% in men and approximately 2% in women [1]. Snoring and OSA, which are among the breathing problems during sleep, are among the conditions caused by the insufficiency of breathing [2]. The aim of our study is to determine whether the person has OSA by analyzing electroencephalogram (EEG) signals. As we know, many physiological and biological activities occur during sleep. In order to observe these activities, we record the electrical activity that occur in our brain. Thanks to the EEG, we transform these activities into digital data. In this project, EEG signals recorded from 4 patients during sleep were processed on MATLAB. Sleep recordings of different sleep zones marked by the doctor are segmented. The data in the segments are divided into 3 headings as pre-apnea, moment of apnea and post- apnea. The data were processed with signal analysis methods such as empirical mode decomposition (EMD) and intrinsic mode functions (IMFs) were extracted. Attributes were obtained from IMFs again on MATLAB. These features are used for classification in advanced machine learning algorithms as pre-apnea and apnea moment as a set of 2 and as a set of 3 as pre-apnea, apnea moment and postapnea. Using the method, we mentioned provides a practical and fast diagnostic process for patients and doctors in our project. In this project, which aims to accelerate the treatment and diagnosis process in order to support the health of patients, it is aimed to classify OSA by analyzing EEG signals. As a result of our project, the accuracy values of the 2-set are between 47.5% and 71.9%, and the accuracy values of the 3-set are between 33.8% - 63.1%.
  • Conference Object
    Endemic Inula Viscosa (l.) Extracts and Their Potential for Both Biosynthesizing Silver Nanoparticles and Anti-Microbial Activity
    (Springer Science and Business Media Deutschland GmbH, 2024) Ozbey, B.O.; Çalışkan Bilgin, Gülizar
    Green synthesis has recently become one of the most popular methods, as it is both low-budget and environmentally friendly. One of the important considerations in green synthesis is to perform an optimization study because it is necessary to understand how different application conditions (pH, incubation time, metal concentration, etc.) can affect the formation of nanoparticles with different morphology and efficiency, underlining the need for optimization of the process. In this study, firstly the endemic Inula Viscosa (L.) plant, popularly known as cancer grass, was extracted using distillation method. Then, silver nanoparticle (AgNPs) biosynthesis was carried out using the extract of Inula Viscosa (L.) plant. Their physicochemical characterization was conducted using Fourier-transformed infrared spectroscopy (FTIR), UV-visible spectrophotometry (UV-Vis), Scanning Electron Microscopy (SEM), and Dynamic Light Scattering (DLS). The time, pH, and AgNO3 concentration, which affect the characteristic and morphological properties of AgNPs, were optimized with the Box Behnken Design (BBD) method, with statistical and experimental design determined by means of a Design Expert statistical software program. The disk diffusion method was also implemented and optimized to increase antimicrobial activity. The study determined the optimal levels of AgNPs, which were green synthesized by Inula Viscosa (L.), provided proof of its antimicrobial properties, and demonstrated their potential to be used as a low-budget aid to new generation clinical treatment methods. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 7
    Green Synthesis of Titanium Nanoparticles Using a Sustainable Microalgal Metabolite Solution for Potential Biotechnological Activities
    (Wiley, 2023) Mutaf, Tugce; Çalışkan, Gülizar; Özel, Hulki; Akağaç, Gülşah; Öncel, Suphi S.; Elibol, Murat
    In this study, green synthesis of titanium nanoparticles using liquids metabolites of microalgae, Porphyridium cruentum, was performed to evaluate potential biotechnological activity. The rising rates of multidrug-resistant bacteria and the number of cancer patients are driving the search for novel antimicrobial and anticancer agents to combat this threat. In recent years, with the increasing number of studies, nanomaterials are starting to be better understood and are emerging as a solution to this problem. Especially, green synthesized nanoparticles with anticancer, antioxidant, and antimicrobial activities have potential in biomedical applications because of their eco-friendly and biocompatible nature. Scanning electron microscopy (SEM) images revealed that spherical shaped Ti-NPs' size ranged from 62 to 133 nm. This study aimed to assess the effectiveness of antibacterial activity of Ti-NPs and chitosan-coated Ti-NPs against Escherichia coli and Staphylococcus aureus using disc diffusion assay. It demonstrated the concentration-dependent cytotoxic effect of Ti-NPs of human prostate adenocarcinoma (PC-3), human alveolar adenocarcinoma (A549), and human mammary gland adenocarcinoma (MDA-MB) cancer cell lines. This present study shows promising outcomes for possible future applications of synthesized Ti-NPs as a novel antibacterial and cytotoxic agent for biomedical applications such as drug delivery, biosensor, and hyperthermia.
  • Conference Object
    Citation - WoS: 13
    Citation - Scopus: 20
    Green Synthesis of Metal Nanoparticles Using Microalga Galdieria Sp.
    (Springer, 2020) Çalışkan, Gülizar; Mutaf, Tuğçe; Oncel, Suphi Surisvan; Elibol, Murat
    Green synthesis of nanoparticles has recently been a preferred method since it offers useful approaches such as non-toxic, biocompatible, environmentally friendly, cost-effective, stable product and trustable alternative processes compared to other methods. Various biological sources such as plant, algae, fungus and bacteria are widely used in biological synthesis of nanoparticles. Algae are more adapted organisms compared to the others for having high growth rate and biomass productivity, high heavy metal accumulation capacity, etc. Nanoparticles can be used in various area such as antimicrobial, antifungal, antioxidant agent, admixture of biosensor and drug transport/release, also diagnosis and treatment systems. Since each organism has different biochemical composition and metabolic pathways, their synthesized nanoparticles are going to show various characteristics and application area. In this study, silver, iron (II) and zinc nanoparticles were produced by using microalga Galdieria sp. The synthesized nanoparticles were characterized by using UV visible spectroscopy, Fourier transform infrared spectroscopy (FTIR) and zeta sizer. Antimicrobial activity against gram negative and gram-positive bacteria was also examined throughout the study. In conclusion, the potential of this biogenic nanoparticle was discussed.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 5
    Biogenic Nanoparticle Synthesis Using Marine Alga Schizochytrium Sp.
    (Springer, 2020) Mutaf, Tuğçe; Çalışkan, Gülizar; Meydan, Cafer; Oncel, Suphi Surisvan; Elibol, Murat
    Nanotechnology is one of the most promising science and technology discipline that targets to bring new solutions for many applications in biotechnology, biomedical, energy and cosmetic industry by improving particles and devices scale of nanometers. Various sized and shaped nanoparticles can be synthesized by several methods. Up to now, scientists prefer physical and chemical fabrication of nanoparticles. But, these methods contain use of toxic, expensive and non-environmentalist solvents, reducing and stabilising agents. For a sustainable science, there is a necessity development of more eco-friendly, cost-effective and trustable alternative processes. In this context, using biological sources as reaction agent, have a strong potential. Plants, bacteria, fungi are essential biological sources for transformation of metals to nanoparticles. Many researchers focus on fungi and bacteriological potential in nanofabrication whereas algae are highly intriguing biological systems in nanotechnological approach. Some of cyanobacteria and algae have previously been used to synthesize intracellular or extracellular metal nanoparticles. Most of the research concentrate especially on gold and silver nanoparticle production from algae. In this work; bioreduction of silver, zinc and iron metals have been investigated using culture supernatant of marine algae Schizochytrium sp. For characterization of nanoparticles, UV visible spectroscopy, zeta sizer were used. Nanoparticle size was determined by zeta sizer and particles' surface plasmon resonance band detected by UV-Visible Spectroscopy.