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Needs and early response towards internally displaced people in Hatay Province in the aftermath of the 2023 earthquake in Turkey
Get PDFArticle number : 1706Background: On 06 February 2023, an extreme earthquake affected Hatay province in Turkey. The immediate response consisted of medical teams focusing on traumatology and immediate trauma related care. In the intermediate time period, after days to weeks, more primary health care was needed for displaced populations in tent shelters and in surrounding villages. We are describing the results of a needs assessment intervention and health services provided by an international non-governmental organization. Methods: Mobile teams circulated to displaced populations in peripheral locations. Fourty-two representatives of communities were interviewed for rapid needs assessment. After triaging and identification of needs, mobile medical units offered primary health care services. Data was collected digitally, directly by the healthcare workers on basic demographics and health conditions. We are reporting a descriptive overview of the data. Results: Communities showed different degrees and dimensions of need, such as entirely lacking health services, or missing sanitary facilities. Populations in the communities increased in most sites. From 16 February to 06 April 2023, 3,027 patients were attended to. The majority of our beneficiaries were female (61.0%) and of Turkish origin (66.9%). Children under the age of 18 accounted for 41.3%. The most reported health findings were upper respiratory infections (24.9%) and scabies (9.7%). In 68 patients, a primary diagnosis of a mental health condition was made. Conclusions: In the intermediate response after an earthquake-driven disaster, primary healthcare provision becomes a crucial element of humanitarian support. Massive displacement into crowded tent shelters lead to respiratory conditions and contagious ectoparasitism. Organizations engaging in this context need to be prepared accordingly, not the least by sufficient stock keeping
IOT Environment and Related Technologies For Monitoring with Deep Learning Methods
No full textConference name : 7th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, ICHORA 2025
Conference city : Ankara
Conference date : 23 May 2025 - 24 May 2025
Conference code : 209351In the domain of monitoring and surveillance applications, the combination of Internet of Things (IoT) and Deep Learning (DL) techniques has initiated a paradigm shift. This study investigates the complex ecology of the IoT, including its associated technologies, and highlights the critical role of DL in enhancing monitoring capabilities. IoT ecosystems, which are comprised of a large number of networked devices, generate massive datasets that present difficulties for conventional analytical methods in terms of effective analysis. Due to its ability to autonomously extract intricate features and patterns from vast amounts of data, DL is an attractive solution for this challenge. This extensive study intends to investigate the synergistic relationship between the IoT and DL, shedding light on the various aspects of monitoring in this specific environment. This research examines IoT technologies, including sensors, communication protocols, and data aggregation procedures. These components serve as the basis for data collection in monitoring applications. In addition, we investigate the concept of deep linking, a protocol that facilitates seamless device interactions within the IoT ecosystem. This paper examines the application of deep learning algorithms to activity monitoring, borrowing inspiration from the human brain's operation. There are two major categories of deep learning methods: discriminative and generative approaches. These methods have been demonstrated to improve the precision and effectiveness of monitoring systems. In IoT monitoring, Convolutional Neural Networks (CNNs) for image analysis and Recurrent Neural Networks (RNNs) for sequential data are examples of the versatility of DL. Moreover, we emphasise the use of hybrid DL methodologies, including Deep Autoencoders, Deep Belief Networks, as well as Ensemble of DL Networks. These approaches effectively integrate the advantages of discriminative and generative models to enhance the results of monitoring processes. In addition, offers a comprehensive analysis of the IoT and DL, emphasising their transformative impact on monitoring and surveillance capabilities. The integration of the data-intensive environment of the IoT with the advanced learning experiences of deep learning has the potential to revolutionise our understanding and application of monitoring techniques in multiple fields
Optimizing stress ulcer prophylaxis practices and reducing associated costs in intensive care units: a non-randomized controlled study
Get PDFObjective: This study evaluated the use of stress ulcer prophylaxis (SUP), assessed the costs associated with inappropriate use, and highlighted the impact of clinical pharmacists on improving adherence to the SUP guidelines. Method: A prospective, non-randomized controlled study was carried out in two intensive care units (ICUs) of a training and research hospital between 1 June 2023 and 1 December 2023. Routine care services were provided for the observation group (OG) patients. In the guideline group (GG) patients, SUP management and routine care were performed according to ASHP guidelines. The physician and clinical pharmacist jointly evaluated the patients to determine the suitability of their SUP indications. Adherence rates to ASHP guidelines and the costs associated with nonadherence were evaluated. Results: A total of 196 patients were included in the study: 121 in the OG and 75 in the GG. A total of 54.6% of the patients were male, and the reason for hospitalization was mainly surgery (52.6%). SUP use was higher in OG (100%) than in GG (42.6%) (p < 0.001). The indication rate according to the ASHP guidelines was significantly higher in the GG group (100%) than in the OG group (54.5%) (p < 0.001). Dosage form adherence was significantly lower in the OG (0%) than in the GG (100%) (p < 0.001). The costs associated with proton pump inhibitor use for inappropriate indications and incorrect dosage forms were 0 (p < 0.001) and 0 (p < 0.001) in OG and GG, respectively. Overall, cost savings of $327 were achieved in the GG group. Conclusion: Inappropriate SUP use is common in the ICUs. Adequate adherence to guidelines and proactive involvement of clinical pharmacists may reduce inappropriate SUP in ICUs and the associated costs
Investigation of APOE2 rs7412 and APOA2 rs5082, APOA5 rs662799 and MTHFR rs1801133 Polymorphisms in Diabetic Obese and Non-Obese Diabetic Groups in Turkey
No full textAbstract: Obesity caused by an abnormal increase in adiposyte, is linked to type 2 diabetes. Diabetes is a metabolic-disease that is caused by insulin-deficiency. Type 2 diabetes is a serious implication of obesity and genetic polymorphisms. Apolipoprotein E2 (APOE2)(rs7412), Apolipoprotein A2 (APOA2) (rs5082), Apolipoprotein A5 (APOA5) (rs662799), Methylenetetrahydrofolate reductase (MTHFR) (rs1801133) polymorphisms which were determined to play role in the development of obesity and diabetes, were evaluated with the RT-qPZR in the study. We included 99 diabetic obese and 99 diabetic non-obese people. We investigated the effect of obesity on variants of all gene polymorphisms in diabetic patients. As a result, APOA2, APOE2 polymorphisms were significant, APOA5, MTHFR polymorphisms were not significant in genotype/allele frequency between groups. APOA2 CC-homozygous carriers had high low-density-lipoprotein-c, glucose, body-mass-index in diabetic-obese patients. APOE2 C-allele carriers had significantly high-Triglyceride and low high-density-lipoprotein versus TT-genotype in non-obese diabetic patients. The present study was first in the Turkey population and evaluates the polymorphisms of genes indicated in diabetic patients
The unseen struggle-depression and associated factors in geriatric cancer patients
Get PDFArticle number : 1603515Background: The objective of this study was to investigate the frequency of depression and its associations, rather than causal relationships, in patients aged 65 years and older receiving chemotherapy, using the Geriatric Depression Scale (GDS). Methods: This prospective study was conducted between January 2023 and December 2023 at Ankara Etlik City Hospital, including 501 chemotherapy patients aged 65 years and older. Patients receiving only oral therapy, those under palliative care, those with brain metastases, or those with insufficient cognitive functionality were excluded. Demographic and clinical data were collected from medical records. Depression was assessed using the 15-item Yesavage Geriatric Depression Scale (GDS), with scores ≥5 indicating high depression symptoms. Results: Among the 501 patients included in the study, 204 (40.7%) were female, with a median age of 69 years (range: 65–84 years). A total of 214 patients (42.7%) had high depressive symptom scores (GDS ≥ 5). A multivariable logistic regression analysis identified the following as independent predictors of depression: being female (odds ratio (OR): 1.481, 95% confidence interval (CI): 1.011–2.168, p = 0.04), body mass index (BMI) ≥ 21 (OR: 1.665, 95% CI: 1.081–2.564, p = 0.02), higher pain scores (OR: 1.269, 95% CI: 1.122–1.436, p < 0.001), insomnia (OR: 1.626, 95% CI: 1.109–2.384, p = 0.01), and weak social support (OR: 2.004, 95% CI: 1.046–3.839, p = 0.03). Conclusion: Our study highlights the high prevalence of depressive symptoms among geriatric cancer patients. In this population, early diagnosis and management of depression, with particular attention to independent risk factors such as pain and insomnia, as well as strengthening social support mechanisms, may be crucial for enhancing quality of life and improving treatment adherence
The antimicrobial mechanisms of inorganic nanoparticles
No full textThe antimicrobial activity of nanomaterials, especially metallic nanoparticles, has gained noticeable global attention due to their broad-spectrum biocidal performance and compatibility with various delivery methods, besides the need for innovative antimicrobial agents that can effectively overcome drug-resistant pathogenic infections. The biological activity of these nanoparticles (NPs) is sufficiently distinct from synthetic antibiotics, providing a complementary pathway for microorganism inactivation. Even though numerous studies have investigated the bactericidal activities of NPs, the antibacterial mechanisms are not fully understood due to NPs diversity. This chapter will focus on several prominent pathways that govern the antibacterial performance of NPs, including their physico-chemical interference with cell wall functions, generation of reactive oxygen species, the release of toxic ions, disruption of cell signaling, and prevention of DNA replication. These pathways are discussed concerning key determinants of the NP bioactivity, such as their size, shape, and the properties of the medium
Comprehensive analysis and machine learning-based solutions for drift behavior in ambient Atomic Force Microscope conditions
No full textArticle number : 111678
CODEN : EAAIEThis study outlines the effectiveness of combining numerical methods, Computer Vision (CV) and Machine Learning (ML) approaches to analyze and predict drift behavior in high-resolution Atomic Force Microscope (AFM) scanning procedures. Using Long Short-Term Memory (LSTM) models for time series analysis and the Light Gradient Boosting Machine (LightGBM) algorithm for predictive modeling, significant progress was achieved in understanding the dynamic and variable nature of drift and mitigating its impact on scanning. The models demonstrated a robust predictive capability, achieving approximately 94% accuracy in drift predictions. The study emphasizes the nonstationary characteristics of drift and demonstrates how the selection of features directly related to the target variable enhances the efficiency of the model and enables adaptive real-time correction. These findings confirm the predictive strength of the models and highlight the potential for integrating ML predictions with real-time feedback mechanisms to improve the resolution and stability of AFM imaging in both scientific and industrial applications.Funding agency : Yaşar University
Grant number : BAP14
Visuo-spatial learning and memory deficits in C57BL/6 mice following postnatal ethanol exposure
No full textCODEN : AJDABBackground: Postnatal alcohol exposure impairs the development of the central nervous system, including the visual system. The behavioral consequences of such exposure on visual function remain poorly understood. Objectives: In this study, we investigated the effects of postnatal ethanol exposure on visuospatial learning and memory in C57BL/6 mice. Methods: Ethanol (3.0 g/kg) was administered via intubation on postnatal days 3–20. Controls received intubation only or no intervention. Pups were assigned to alcohol-treated (A, n = 11), intubation control (IC, n = 11), or non-intubated control (C, n = 9) groups. At three months, mice underwent the Novel Object Recognition (NOR) test and a visual water task. The NOR test measured recognition memory and exploratory behavior. The visual water task assessed visual acuity using sinusoidal gratings presented on monitors. Mice were trained over 17 days to associate a grating with a hidden platform, and visual acuity thresholds were determined based on performance at varying spatial frequencies. Results: Alcohol-exposed mice showed significant deficits in recognition memory and visual acuity. No group differences in body weight were observed. However, alcohol-treated mice displayed reduced exploration of novel objects (p =.0085, R2 = 0.29) and lower visual acuity thresholds at higher spatial frequencies (p =.048, R2 = 0.24). Conclusion: These findings demonstrate that early postnatal alcohol exposure can lead to lasting impairments in visual-cognitive functions. Given their similarity to deficits seen in children with Fetal Alcohol Spectrum Disorders (FASD), our results suggest the importance of early behavioral and visual assessments in children with suspected prenatal or early postnatal alcohol exposure.Funding agency : Altınbaş University Research Council.
Grant number : PB2017-BAHAR-TIP-
Perceived Paternal Acceptance-Rejection as a Mediator of the Association Between Perceived Maternal Acceptance-Rejection and Psychological Adjustment: Effect of Gender
Get PDFThe present study explores the mediating role of perceived paternal acceptance-rejection on the association between perceived maternal acceptance-rejection and psychological adjustment and its gender-related facets among 551 secondary school students aged 11 to 15. Results suggest paternal acceptance-rejection partially mediates this relationship for both genders, impacting positive self-adequacy, emotional responsiveness, and positive worldview. It partially mediates hostility and emotional stability for females and fully mediates for males. However, it does not affect self-esteem for either gender
A Bioactive Emulgel Formulation of Equisetum telmateia Ehrh. Methanol Extract: Integrating Antioxidant Activity, Skin Enzyme Inhibition, and Permeation Kinetics
Get PDFArticle number : 662Equisetum telmateia Ehrh. (great horsetail) belongs to the Equisetaceae family and its aerial parts have been traditionally used for skin conditions and to achieve healthy and resilient skin, nails, and hair. This study aimed to evaluate the inhibition of skin-related enzymes by, the antioxidant capacity of, and the phytochemical composition of E. telmateia. Additionally, a novel emulgel was formulated from the main methanolic extract and characterized in terms of pH, viscosity, determination of content quantification, textural profile analysis, and spreadability. After the characterization studies, in vitro release and ex vivo permeation and penetration studies were performed. Firstly, the dried aerial parts of E. telmateia were macerated in methanol, followed by partitioning with solvents of increasing polarity: n-hexane, chloroform, ethyl acetate, and n-butanol. Antioxidant activity was assessed using DPPH, FRAP, CUPRAC, and TOAC assays, while enzyme inhibition was analyzed for collagenase, elastase, hyaluronidase, and tyrosinase. LC-MS/MS analysis identified 53 phytochemical compounds. Protocatechuic acid, the main phenolic compound, was quantitatively analyzed in each subfraction by HPTLC. The in vitro release studies showed sustained release of the reference substance (protocatechuic acid) and the kinetic modeling of the release was fitted to the Higuchi model. The ex vivo permeation and penetration studies showed that the formulation exhibited a retention of 3.06 ± 0.21 µg.cm−2 after 24 h, whereas the suspended extract demonstrated a skin retention of 1.28 ± 0.47 µg.cm−2. Both the extracts and the formulated emulgel exhibited inhibitory effects on skin-related enzymes. Our finding suggested that E. telmateia might be a valuable ingredient for wrinkle care and skin-regenerating cosmetics