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Comparison of antibacterial and antifungal efficacy of self-assembling peptide P11-4 with different remineralization agents: an in-vitro microbiological study
No full textBackground: The aim of this study is to evaluate the effect of self-assembling peptide (SAP) P11-4 on the Streptococcus mutans American Type Culture Collection (ATCC) 10449, Lactobacillus casei ATCC 11578 and Candida albicans ATCC 60193 and to compare the antibacterial and antifungal activity with different remineralisation agents. Methods: This in-vitro microbiological study was performed with five independent groups (G1. Chlorhexidine Gel (Best Dental, Istanbul, Turkey), G2. Profluorid Varnish (R) (VOCO GmbH, Cuxhaven, Germany), G3. CurodontTM Protect (Credentis AG, Windisch, Switzerland), G4. Tooth MousseTM (GC Corporation, Tokyo, Japan) and G5. MI Paste Plus (GC Corporation, Tokyo, Japan)). The antimicrobial activities of the samples were evaluated according to 24-hour time kill assay against S. mutans, L. casei and C. albicans. Results: The control, Group 1-Chlorhexidine gel, had the strongest antibacterial activity against all of the tested microorganisms. The results showed that Group 4-Tooth MousseTM was the most effective remineralization agent with the best antimicrobial activity against S. mutans and C. albicans, followed behind respectively with Group 5-MI Paste Plus, Group 3-CurodontTM Protect, and Group 2-Profluorid Varnish (R). Group 5-MI Paste Plus demonstrated the most effective antibacterial activity against L. casei. Group 4-Tooth MousseTM, Group 2-Profluorid Varnish (R), and Group 3-CurodontTM Protect were afterwards in order. Conclusions: SAP P11-4 can be used as an antimicrobial agent to prevent opportunistic fungal infections as well as to prevent and halt the progression of incipient lesions
Preoperative cardiology consultations for geriatric patients with hip fractures rarely provide additional recommendations and are associated with prolonged hospital stays and delayed surgery: a retrospective case control study (2024) 50:3217-3222)
No full text[Abstract Not Acaileble
Effects of Different Seeding Rates on Growth Performance, Yield, and Quality of Calendula officinalis L. in Mediterranean Conditions
No full text"Calendula officinalis L., commonly known as pot marigold and a member of the Asteraceae family, is widely used in cosmetics, medicine, and pharmacy due to its rich bioactive compounds. This study investigated the effects of varied seeding rates on the growth, yield, and quality of Calendula officinalis L. in Mediterranean climates, focusing on morphological, quality, and agronomic characteristics, including seed and biological yield. The research was conducted at the experimental fields of the Ege University, Faculty of Agriculture, Department of Field Crops, over two growing seasons (2019–2020 and 2020–2021). The experiment followed a randomized complete block design with a factorial arrangement, incorporating three replicates. The factors included (a) year (2020 and 2021) and (b) five seeding rates (5, 10, 15, 25, and 35 kg ha?¹). Results indicated that seeding rate significantly impacted agronomic yield. While plant density per m² increased with higher seeding rates, there was a decline in plant branching, plant height, seed yield, biological yield, fresh flower yield, and dried flower yield at higher seeding rates. The optimum seeding rate for achieving high flower and seed yields was determined to be 10 kg ha?¹. Rainfall during the flowering period was found to be critical for maximizing drug flower and seed yield, highlighting the importance of careful consideration of seeding percentage and precipitation to achieve the optimum yield of C. officinalis. © 2025 Elsevier B.V., All rights reserved
Olgu Sunumu: Uzamış Deliryum Tremens
No full textDelirium tremens represents the most severe condition of alcohol withdrawal, with the associated highest mortality rate. The primary treatment for cases of delirium tremens consists of benzodiazepines. Within the literature, prolonged cases of delirium tremens have been identified that do not respond to high-dose benzodiazepine treatments or respond late. Different treatment modalities, such as propofol, dexmedetomidine, and parenteral antipsychotic administrations, are being attempted in the management of these cases. In this case, a case of prolonged delirium tremens with insufficient response to benzodiazepine treatment will be presented. © 2025 Elsevier B.V., All rights reserved
Epilepsili çocuklarda bilişsel fonksiyonlara solunumsal kas performansının etkisi: Glimfatik sistem aktivasyonu ve nöropeptidler ile izlemi
No full textAmaç: Epilepsi tanısı almış çocuklarda inspiratuar kas eğitiminin (İKE); bilişsel fonksiyon, nöron spesifik enolaz (NSE), nöropeptid Y (NPY) ve sinir büyüme faktörü (NGF) düzeyleri ile glimfatik sistem üzerindeki etkisini incelemektir. Yöntem: Araştırma, Ege Üniversitesi Tıp Fakültesi Çocuk Hastanesi'nin Pediatrik Nöroloji Anabilim Dalı'nda, epilepsi tanısı ile takip edilen 8-17 yaş aralığındaki 20 hasta ile yürütüldü. Katılımcılar, eğitim ve kontrol olmak üzere iki gruba ayrıldı. Katılımcıların demografik bilgileri kaydedildi. Solunum kas kuvveti, ağız basıncı ölçüm cihazı (mikro-RPM) ile; solunum fonksiyon testi (SFT), taşınabilir spirometre (Cosmed Pony FX, İtalya) ile; bilişsel fonksiyonlar ise Sayı Dizisi Öğrenme Testi (SDÖT) ile değerlendirildi. NPY, NGF ve NSE düzeyleri, enzim bağlı immünosorbent testi (ELISA) ile incelendi. Glimfatik sistem aktivitesi, perivasküler boşluk boyunca difüzyon tensör görüntüleme analizi (DTG-ALPS) indeksi kullanılarak değerlendirildi. Eğitim grubu, farmakolojik tedaviye ek olarak 8 hafta boyunca, haftada 7 gün, maksimal inspiratuar basınç (MIP) değerlerinin %30'unda Threshold IMT cihazı ile inspiratuar kas eğitimi aldı. Kontrol grubu ise yalnızca farmakolojik tedavi ile takip edildi. Gruplar, tedavi öncesinde ve sonrasında olmak üzere iki kez değerlendirildi. Bulgular: Eğitim grubunun yaş ortalaması 10,50±2,67 yıl, kontrol grubunun yaş ortalaması ise 9,60±2,63 yıl olarak belirlendi. Eğitim grubunun %50'si kız, %50'si erkek, kontrol grubunun ise %40'ı kız, %60'ı erkekti. Grup içi analizlerde, tedavi öncesi ve sonrası ortalama solunum kas kuvveti değerlerinde istatistiksel olarak anlamlı bir artış gözlendi (p0.05). Buna rağmen, eğitim grubunun tedavi sonrası ortalama solunum kas kuvveti değerleri kontrol grubununkinden daha yüksekti. Gruplar arası karşılaştırmalarda, tedavi sonrası SFT alt parametrelerinden FVC%, FEV1% ve FEV1/FVC% değerlerinde ve biyokimyasal analizde yer alan NPY değerinde istatistiksel olarak anlamlı fark bulundu (p0.05). Sonuç: İnspiratuar kas eğitiminin, bilişsel fonksiyonlar ve glimfatik sistem aktivasyonu üzerinde olumlu etkileri olduğu gösterildi. Fizyoterapi yöntemleri ile farmakolojik tedavinin entegrasyonu ise, nöbetlerin yol açtığı bilişsel bozukluklar ve solunum problemlerinin iyileştirilmesinde olumlu sonuçlar verdi. Bu multidisipliner yaklaşım, epilepsi hastalığının yönetimi açısından etkili bir stratejidir. Fizyoterapi ve farmakolojik tedavilerin entegrasyonu, epilepsiye bağlı bilişsel bozuklukların iyileştirilmesine yönelik yeni bir tedavi perspektifi sunmaktadır. Aynı zamanda, solunum fonksiyonlarının iyileştirilmesi ve glimfatik sistemin aktive edilmesi, tedavi sürecine dahil edilerek epilepsi hastalarının yaşam kalitesini artırma potansiyeline sahiptir.Objective: This study aimed to investigate the effect of inspiratory muscle training (IMT) on cognitive function, neuron-specific enolase (NSE), neuropeptide Y (NPY), nerve growth factor (NGF) levels, and the glymphatic system in children diagnosed with epilepsy. Method: The study was conducted with 20 patients aged between 8-17 years who were followed up with a diagnosis of epilepsy at the Department of Paediatric Neurology, Ege University Medical Faculty Children's Hospital. Participants were divided into experimental and control groups. Demographic information of the participants was recorded. Respiratory muscle strength was assessed using a mouth pressure measurement device (micro-RPM), pulmonary function was evaluated with a portable spirometer (Cosmed Pony FX, Italy), and cognitive functions were measured using the Serial Digit Learning Test (SDLT). NPY, NGF, and NSE levels were analyzed using enzyme-linked immunosorbent assay (ELISA). Glymphatic system activity was assessed using the diffusion tensor imaging analysis of the perivascular space (DTI-ALPS) index. The experimental group received inspiratory muscle training with the Threshold IMT device at 30% of maximal inspiratory pressure (MIP) for 8 weeks, 7 days a week, in addition to pharmacological treatment. The control group was followed with pharmacological treatment alone. Both groups were assessed twice: before and after the intervention. Results: The mean age of the experimental group was 10.50±2.67 years, while the mean age of the control group was 9.60±2.63 years. The experimental group consisted of 50% girls and 50% boys, whereas the control group consisted of 40% girls and 60% boys. In within-group analyses, a statistically significant increase was observed in the mean respiratory muscle strength values before and after treatment (p0.05). Nevertheless, the post-treatment mean respiratory muscle strength values of the experimental group were higher than those of the control group. In between-group comparisons, a statistically significant difference was found in the post-treatment PFT sub-parameters FVC%, FEV1%, and FEV1/FVC% values, as well as in the NPY value from the biochemical analysis (p0.05). Conclusion: Inspiratory muscle training has been shown to have positive effects on cognitive functions and glymphatic system activation. The integration of physiotherapy methods with pharmacological treatment yielded positive results in improving cognitive impairments and respiratory problems caused by seizures. This multidisciplinary approach is an effective strategy in the management of epilepsy. The integration of physiotherapy and pharmacological treatments provides a new treatment perspective for improving cognitive impairments related to epilepsy. Additionally, the improvement of respiratory functions and activation of the glymphatic system, when incorporated into the treatment process, has the potential to enhance the quality of life of epilepsy patients
HbA1c tayinine yönelik moleküler baskılı polimerler ve yapay zeka destekli nanobiyosensör geliştirilmesi
No full textDiyabet, küresel sağlık sorunlarının başında gelmekte olup, uzun dönemli glukoz seviyelerinin takibi hastalığın tanı ve yönetiminde hayati önem taşımaktadır. Glikozile hemoglobin (HbA1c), son 2-3 aylık ortalama kan şekeri düzeylerini yansıtan güvenilir bir biyobelirteçtir. Ancak geleneksel yöntemlerle yapılan HbA1c ölçümleri, zaman alıcı ve yüksek maliyetli analiz prosedürleri gerektirmektedir. Bu nedenle, daha hızlı, hassas ve taşınabilir tanı sistemlerine ihtiyaç duyulmaktadır. Bu tez çalışmasında, HbA1c’nin seçici tanınması ve düşük konsantrasyonlarda tespiti amacıyla moleküler baskılama teknolojisine dayalı makine öğrenimi ile entegre elektrokimyasal nanosensör geliştirilmesi hedeflenmiştir. Çalışmada, HbA1c’ye özgü moleküler baskılanmış nanopolimerler, metil metakrilat (MMA) fonksiyonel monomeri kullanılarak oluşturulan ön kompleks ile surfaktan içermeyen emülsiyon polimerizasyonu yöntemiyle sentezlenmiştir. HbA1c hedef molekülü, polimerizasyon sürecinde şablon olarak görev yapmış ve sonrasında uzaklaştırılarak özgül tanıma boşlukları oluşturulmuştur. Elde edilen nanopolimerler, SPC elektrot yüzeyine immobilize edilerek elektrokimyasal analizler için fonksiyonel hale getirilmiştir. Nanopolimerlerin morfolojik ve kimyasal karakterizasyonu Fourier Dönüşümlü Kızılötesi Spektroskopisi (FTIR), Taramalı Elektron Mikroskobu (SEM) ve ZETA Boyut ve Potansiyel analizi ile yapılmış; ortalama partikül boyutunun 319.7 nm aralığında ve küresel morfolojide olduğu belirlenmiştir. Bağlama deneyleri, baskılanmış nanopolimerin HbA1c’ye yüksek seçicilikle bağlandığını ve maksimum bağlama kapasitesinin 565 mg HbA1c/mg polimer olduğunu göstermiştir. Baskılanmamış polimere kıyasla seçicilik yaklaşık 7,23 kat artmıştır. Elektrokimyasal analizlerde DPV (-0.2 V–+0.6 V, 60 mV/s tarama hızı) teknikleri kullanılmış, sensörün LoD ve LoQ değerleri sırasıyla 0,76 μM ve 2,31 μM olarak hesaplanmıştır. Ayrıca çalışmada, sensörden elde edilen elektrokimyasal verilerin sınıflandırılması ve yorumlanması amacıyla yedi farklı makine öğrenmesi (ML) algoritması uygulanmıştır. Modellerin performansları karşılaştırılmış; eğitim (train) ve test verileri üzerindeki sonuçlar değerlendirilerek aşırı öğrenme riski göz önünde bulundurulmuştur. Ayrıca, 5 katlı çapraz doğrulama (k-fold crossvalidation) yöntemi ile modellerin genellenebilirliği analiz edilmiştir. Yapılan analizler sonucunda, CatBoost algoritması en yüksek doğruluk ve sınıflandırma başarımını göstermiştir. Bu entegrasyon, sensör platformunun düşük sinyalli verilerde dahi doğru yorumlama yeteneğini artırarak tanı güvenilirliğini desteklemiştir. Sonuç olarak, bu tez kapsamında geliştirilen HbA1c-baskılı elektrokimyasal nanosensör; seçicilik, düşük tespit sınırı, geniş lineer çalışma aralığı ve tekrar kullanılabilirlik gibi performans parametreleri doğrultusunda değerlendirilmiş; makine öğrenmesi tabanlı veri işleme yaklaşımları ile sistem çıktılarının otomatikleştirilmesi yoluyla sensörün veri analiz kapasitesinin artırılması amaçlanmıştır. Bu bağlamda geliştirilen sistem, biyolojik örneklerde HbA1c tayini için yeni nesil bir tanı platformu olarak öne çıkmaktadır.Diabetes ranks among the leading global health challenges, with long-term glucose monitoring being critical for disease diagnosis and management. Glycated hemoglobin (HbA1c) serves as a reliable biomarker reflecting average blood glucose levels over the preceding 2–3 months. However, conventional methods for HbA1c quantification are time-consuming and involve costly analytical procedures. Therefore, there is a pressing need for rapid, sensitive, and portable diagnostic systems. This thesis aims to develop a molecularly imprinted electrochemical nanosensor integrated with machine learning for selective recognition and detection of HbA1c at low concentrations. In this study, molecularly imprinted nanopolymers specific to HbA1c were synthesized via surfactant-free emulsion polymerization using methyl methacrylate (MMA) as the functional monomer to form a pre-complex. HbA1c served as the template molecule during polymerization and was subsequently removed to create selective recognition sites. The resulting nanopolymers were immobilized onto the surface of screen-printed carbon (SPC) electrodes to enable electrochemical analysis. Morphological and chemical characterizations of the nanopolymers were conducted using Fourier Transform Infrared Spectroskopy (FTIR), Scanning Electron Microskopy (SEM), and ZETA size and potential analysis. The nanopolymers exhibited an average particle size within the 319.7 nm range and spherical morphology. Binding assays demonstrated high selectivity of the imprinted nanopolymer toward HbA1c, with a maximum binding capacity (Qmax) of 565 mg HbA1c per mg polymer. Compared to the non-imprinted control polymer, selectivity was enhanced by approximately 7.23-fold. Electrochemical analyses employed differential pulse voltammetry (DPV) within the potential window of -0.2 V to +0.6 V at a scan rate of 60 mV/s, alongside cyclic voltammetry (CV) to monitor electrode surface changes. The sensor exhibited a limit of detection (LoD) and limit of quantification (LoQ) of 0.76 μM and 2.31 μM, respectively. Additionally, seven different machine learning (ML) algorithms were applied to classify and interpret the electrochemical data obtained from the sensor. Model performances were compared based on training and test datasets with overfitting risk assessment. Furthermore, 5-fold cross-validation was performed to evaluate model generalizability. Among the models, the CatBoost algorithm demonstrated the highest accuracy and classification performance. This integration enhanced the sensor platform’s capability to accurately interpret lowsignal data, thereby improving diagnostic reliability. In conclusion, the developed HbA1c-imprinted electrochemical nanosensor was evaluated in terms of selectivity, low detection limit, wide linear range, and reusability. By incorporating machine learning-based data processing approaches for automated output interpretation, the sensor’s analytical capacity was significantly enhanced. The proposed system represents a novel nextgeneration diagnostic platform for HbA1c determination in biological samples
Optimal power flow using kepler optimization algorithm for active power loss analysis in island mode: A case study
No full textGrowth in electricity grids, environmental awareness, and power reliability requirements necessitate the development of solutions for single- and multi-objective Optimal Power Flow (OPF) problems, emphasizing the need for effective optimization algorithms. In literature, both classical optimization techniques and metaheuristic algorithm-based methods have been proposed to solve the OPF problem. Studies are typically conducted on the test systems. Additionally, the applicability of these methods to real systems is also of great importance. In this study, the Kepler Optimization Algorithm (KOA), was applied to solve the OPF problem not only on test systems but also, for the first time in the literature, on a real system operating in island mode to determine its optimal operating points. First, KOA's performance was evaluated for various objective functions on the IEEE 30, IEEE 57, and IEEE 118 bus test systems. Using the KOA, results were obtained for single- and multi-objective functions, including fuel cost, active power loss, emission, and voltage deviation, either individually or all together. The same objective functions were also solved using the Golf Optimization Algorithm (GOA) and Whale Optimization Algorithm (WOA) using the population and iteration parameters, and the results were compared with those obtained using KOA. KOA demonstrated superior performance compared to GOA and WOA in all objective functions across the three test systems. Additionally, the results were compared with other numerous methods proposed in the literature to assess KOA's performance. The findings indicated that KOA obtained better performance in most of the objective functions. Finally, the KOA was used on a real 22-bus system operating in island mode to evaluate its performance. For this real system, results of 6563.724 $/h fuel cost, 0.1283 MW active power loss, and 0.0498 p.u. voltage deviation were obtained, indicating that KOA could be effectively utilized in real systems. © 2025 Elsevier B.V., All rights reserved
Low-mass Eclipsing Binaries KIC 4908495, KIC 6466939, and KIC 9474485: Isolated Pre-main-sequence Systems?
No full textWe present a detailed analysis of three Kepler eclipsing binaries, KIC 4908495, KIC 6466939, and KIC 9474485. Our analysis reveals that these systems are composed of components possessing a lower mass than our Sun with slight subsolar metallicities. Individual analysis of the evolutionary status of each system interestingly suggests that all component stars in all three systems are pre-main-sequence (PMS) stars that have already developed a radiative core and are on the way to the zero-age main sequence in the Hertzsprung-Russell diagram. Estimated ages are 25 +/- 5, 22 +/- 6 and 25 +/- 15 Myr for KIC 4908495, KIC 6466939 and KIC 9474485, respectively. However, none of these systems is a cluster or association member, indicating that the targets might be isolated eclipsing binaries possessing PMS components. Kepler light curves show noticeable wave-like variability at out-of-eclipse parts, suggesting a considerable magnetic activity manifesting as the rotational modulation of cool surface spots or spot groups. Projected rotational velocities of the components and amplitude spectrum of out-of-eclipse variability suggest either asynchronous rotation of the component stars or the surface differential rotation of the magnetically active component.NASA Science Mission DirectorateWe thank the anonymous referee for insightful and constructive criticism that improved the scientific quality of the manuscript. We also thank Dr. OEmuer Cak & imath;rl & imath; and Dr. Bar & imath;s Hoyman for the fruitful discussion on the technical details of MCMC analysis. This research made use of NASA's Astrophysics Data System Bibliographic Services and SIMBAD database, operated at CDS, Strasbourg, France. This research made use of Lightkurve, a Python package for Kepler and TESS data analysis. This paper includes data collected by the Kepler mission. Funding for the Kepler mission is provided by the NASA Science Mission Directorate
Sınıf Öğretmenlerinin Görüşlerine Göre Helikopter Anne-Baba Davranışlarının Çocuklarının Eğitim ?Sürecine Yansımalarının İncelenmesi
No full textAlthough it is necessary and important for parents to take part in their children's education process, overdoing this behaviour may have negative consequences. The aim of this study is to examine the reflections of helicopter parenting behaviours on the educational process of their children according to the views of primary school teachers. The research was designed as a case study, one of the qualitative research designs. The study group of the research was determined by the easily accessible case sampling method. In this context, the study group consisted of 22 primary school teachers working in six primary schools in Samsun in the 2022-2023 academic year. A semi-structured interview form developed by the researchers was used to collect the data. The data obtained from the interviews were analysed by content analysis. As a result of the research, it was found that helicopter parents were perceived as interventionist, overprotective and controlling, and that they harmed the child's development of independence, decision-making, responsibility and self-confidence. In addition, teachers' suggestions on this issue were put forward.Çocuklarının eğitimi açısından anne babaların onların eğitim sürecinde yer almaları gerekli ve önemli olmakla birlikte, ?bunda aşırıya kaçmaları olumsuz sonuçlar doğurabilmektedir. Bu araştırmanın amacı, sınıf öğretmenlerinin görüşlerine ?göre, helikopter anne baba davranışlarının çocuklarının eğitim sürecine yansımalarını incelemektir. Araştırma, nitel ?araştırma desenlerinden durum çalışması ile tasarlanmıştır. Araştırmanın çalışma grubu, kolay ulaşılabilir durum ?örnekleme yöntemiyle belirlenmiştir. Bu bağlamda çalışma grubu 2022-2023 eğitim öğretim yılında Samsun’da ?bulunan altı ilkokulda görev yapan 22 sınıf öğretmeninden oluşturulmuştur. Verilerin toplanmasında ?araştırmacılar tarafından geliştirilen yarı yapılandırılmış görüşme formu kullanılmıştır. Yapılan görüşmelerden elde ?edilen veriler içerik analizi ile analiz edilmiştir. Araştırmanın sonucunda, helikopter anne baba kavramının müdahaleci, ?aşırı korumacı ve kontrolcü olarak algılandığı ve çocuğun bağımsızlık, karar verme, sorumluluk ve özgüven gelişimine ?zarar verdiği yönünde bazı tespitlerde bulunulmuştur. Ayrıca, öğretmenlerin bu konudaki önerileri ortaya konmuştur.
Energy Consumption Modeling and Flight Time Analysis of Micro Drones
No full textAutonomous aerial vehicles have emerged as revolutionary technology with a wide range of applications in different areas. One of the interesting drone types is miniature or lightweight micro drones which have palm-size small dimensions. Due to their small size, micro drones can navigate confined spaces and reach inaccessible areas, providing valuable data and insights. However, the small size of these drones limits their ability to carry heavy equipment, including batteries and many sensors. Increasing the flight time of micro drones using limited energy sources is a challenging task that requires advanced hardware technologies and efficient software methods. In this paper, we propose a voltage-based regression model to estimate the energy consumption and flight time of micro drones, using sampled voltage data obtained from experimental evaluations in ground, take-off, hovering, and flying modes. The mean absolute error of the proposed regression models is less than 0.3 V for all flying modes. The results from 150 second flight tests indicated an estimated total energy consumption of 2000 J, corresponding to an average power of 13.3 W. The unit mass power consumption was calculated as 0.38 W/g, highlighting the suitability of miniature UAVs for energy-constrained tasks. Also, the experiments showed that due to the voltage drop of the batteries, the drones cannot fly anymore when the battery energy drops to about 50% of the total battery capacity. These results emphasize the importance of lightweight high capacity batteries for developing micro drones.Scientific and Technological Research Council of Turkiye (TUBITAK) [121E500]; TUBITAK through Directorate of Science Fellowships and Grant Programmes (BIdot;DEB) 2211-C ProgramThis work was supported by the Scientific and Technological Research Council of Turkiye (TUBITAK) under Grant 121E500. The work of Nusin Akram was supported by TUBITAK through Directorate of Science Fellowships and Grant Programmes (B & Idot;DEB) 2211-C Program