Chemotherapy-related cognitive impairment and kidney dysfunction

Cancer and kidney diseases (KD) intersect in many ways resulting in worse outcomes. Both conditions are correlated with cognitive impairment, which can be exacerbated in cancer patients by known effects of many antineoplastic drugs on cognition, leading to a phenomenon known as chemotherapy-related cognitive impairment (CRCI). This manifests as poor attention span, disturbed short-term memory, and general mental sluggishness. This literature review explores CRCI and investigates the potential impact of KD on this phenomenon. Additionally, we highlight the shared pathogenetic mechanisms (including neurotoxicity, neuroinflammation, oxidative stress, vascular disease, electrolyte, and acid-base imbalances), clinical presentation and imaging findings between cognitive impairment in KD and CRCI. The disruption of the blood-brain barrier might be a key mechanism for increased brain permeability to anticancer drugs in nephropathic patients with cancer. Based on existing knowledge, we found a potential for heightened neurotoxicity of antineoplastic drugs and a synergistic potentiation of cognitive impairment in cancer patients with KD. However, further translational research is urgently required to validate this hypothesis.Funding agency: European Cooperation in Science and Technology (COST) Grant number: CA1912

A comparative analysis of the liver retraction with long surgical gauze in three-port sleeve gastrectomy and the four-port nathanson retractor technique

Background: This study evaluated the long surgical gauze (SurG) technique as a liver retraction method in laparoscopic sleeve gastrectomy (LSG). Traditional methods involve the Nathanson retractor, associated with ischemia and necrosis complications. In addition, these techniques require an additional trocar with an incision that increases postoperative pain. Our aim, therefore, was to reduce such complications through the use of SurG and evaluate recovery and outcome implications. Methods: In this retrospective study, patients who underwent laparoscopic sleeve gastrectomy (LSG) between January and December 2023 were divided into two groups based on the liver retraction method used: NR or SurG. Demographic data, surgery times, postoperative liver enzyme levels (AST, ALT), C-reactive protein (CRP), pain scores, and analgesic use (VAS) were collected from medical records and statistically analyzed. Results: The SurG group demonstrated significantly lower postoperative pain scores and reduced analgesic use compared to the NR group (p < 0.001). Additionally, liver enzyme levels (AST, ALT, CRP) were lower in the SurG group, indicating less liver stress. Early mobilization was achieved more quickly in the SurG group, aligning with Enhanced Recovery After Surgery (ERAS) protocols. However, the SurG method showed some limitations during the dissection of the greater curvature due to the narrower field of view. Conclusions: The long surgical gauze method provides a viable alternative to the Nathanson retractor, offering advantages such as less postoperative pain, reduced liver stress, and quicker mobilization. Despite some technical limitations, this method can improve patient outcomes in sleeve gastrectomy

European Oral Research

Purpose The primary objective of this investigation is to evaluate the clinical and radiographic findings of mineral trioxide aggregate (MTA) and Biodentine (BD) as pulpotomy agents in primary molars. Materials and Methods Two hundred primary molars (N=200) were treated with pulpotomy. Clinical and radiographic outcomes, including both successes and failures, were documented throughout a 36-month follow-up period. Statistical analyses were performed using the Fisher Exact, McNemar, and Chi-Square tests. Results No statistically significant differences in success rates were found between the 1-, 3-, 6-, 24-, and 36-month assessments for each material when evaluated independently. However, at the twelfth month, the clinical and radiographic success rates for MTA (98% and 92%, respectively) were significantly higher than those for BD (90% and 80%, respectively) with a p-value of less than 0.05. Conclusion In this study, MTA demonstrated greater success than BD at 36 months. Nevertheless, higher quality randomized controlled trials with longer follow-up periods are necessary to obtain more reliable results

Permanent Magnet Synchronous Generator (BLDC) Generator Supported with Wind Turbine and Enhanced with Control Pitch Angle

The permanent magnet synchronous generator (BLDC) based on a wind energy conversion system was mathematically modeled in this work. The principle of operation of a wind energy conversion system based on a BLDC with trapezoidal EMF includes (mechanical, power electronics, and electrical parts) are described. The lightweight specific of the chosen form for the blades on the turbine has been developed and a numerical model of wind turbines has been assembled that encompasses the mechanical and lightweight processes that occur in the installation. New methods of control for the angle of incident β of a wind turbine to improve its output at low wind speeds and speed control of a BLDC engine to boost its effectiveness have been developed using PI controllers and reliable Simulink applications. Last but not least, the turbine potential efficiency can be expressed as follows: the optimum level of values of tip accelerate ratio about 8.2, the maximum torque value id determined about 0.065 and the maximum value of the estimated power coefficients (CP) for this turbine is 0.48 meaning that it works at its highest efficiency possible of 48%

Cholinergic system in patients with chronic kidney disease: cognitive and renal implications

CONNECT Action (Cognitive Decline in Nephro-Neurology European Cooperative Target): Giovambattista Capasso, Alexandre Andrade, Mustafa Arici, Maie Bachmann, Matthew Bailey, Michelangela Barbieri, Mickaël Bobot, Annette Bruchfeld, Inga Arune-Bumblyte, Daiva Rastenytė, Antonello Calcutta, Giovanna Capolongo, Sol Carriazo, Michele Ceccarelli, Adrian Constantin Covic, Ananya De, Pilar Delgado, Nicole Endlich, Matthias Endres, Fabrizio Esposito, Michele Farisco, Quentin Faucher, Ana Carina Ferreira, Andreja Figurek, Denis Fouque, Casper Franssen, Ivo Fridolin, Sebastian Frische, Liliana Garneata, Loreto Gesualdo, Konstantinos Giannakou, Olivier Godefroy, Aleksandra Golenia, Dimitrios Goumenos, Eugenio Gutiérrez Jiménez, Gaye Hafez, Ewout Hoorn, Pedro Henrique Imenez Silva, Raafiah Izhar, Dearbhla Kelly, Shelli Kesler, Aleksandra Klimkowicz-Mrowiec, Samuel Knauss, Justina Kurganaite, Hélène Levassort, Sophie Liabeuf, Jolanta Malyszko, Laila-Yasmin Mani, Gianvito Martino, Ziad Massy, Christopher Mayer, Armida Mucci, Alma Mutevelic-Turkovic, Rikke Nielsen, Dorothea Nitsch, Alberto Ortiz, Vasileios Panagiotopoulos, Despoina Karasavvidou, Giuseppe Paolisso, Bojana Pejušković, Marion Pepin, Alessandra Perna, Andrea Perrottelli, Vesna Pešić, Pasquale Pezzella, Merita Rroji Molla, Ivan Rychlík, Giorgos Sakkas, Mariadelina Simeoni, Maria José Soler Romeo, Goce Spasovski, Ana Starčević, Gioacchino Tedeschi, Francesco Trevisani, Robert Unwin, Evgueniy Vazelov, Carsten Alexander Wagner, Franca Wagner, Christoph Wanner, Andrzej Wiecek, Hong Xu, Miriam Zacchia, Lefteris Zacharia, Irene Zecchino, Carmine Zoccali, Francesco Mattace-Raso, Karl-Hans Endlich, Norberto Perico, Giuseppe Remuzzi, Francesco Trepiccione, Mark Okusa, Vincenzo Di Marzo, Peter Blankestijn, Kai-Uwe Eckardt, Maximilian Konig, Ron Gansevoort, Hassan Askari, Brian Hansen, Sunna Snaedal, Elena Cuiban, Edoardo Caporusso, Vincenzina Lo Re, Jonathan Roiser, Kerry Rosenberg, Alvino Bisecco, Laura Denby, Onkar Prakash Kulkarni, Kumar Sharma, Subrata Debnath, Afaf Jaafar, Anna Capasso, Michele Mulholland, Biruh Workeneh, Anna Iervolino, Simon Fraser, Isabelle Frey-Wagner, Annachiara Pastore, Romaldas Mačiulaitis, Antonio De Donato, Ana FarinhaCholinergic synapses are widespread throughout the human central nervous system. Their high density in the thalamus, neocortex, limbic system, and striatum suggests that cholinergic transmission plays a vital role in memory, attention, learning and other higher cognitive functions. As a result, the brain's cholinergic system occupies a central position in research on normal cognition and age-related cognitive decline, including dementias such as Alzheimer's disease. In addition to its role in the brain, neuronal cholinergic pathways are essential for the physiological regulation of bodily organs, including the kidneys, through the parasympathetic branch of the peripheral nervous system. Chronic kidney disease (CKD) is a non-communicable disease with a global prevalence of approximately 10%. Cognitive impairment is common among patients with CKD, with reported prevalence rates ranging from 30% to 60%, depending on definitions and assessment methods used. Given the importance of the cholinergic system in cognitive processes, it may be a key area of focus for evaluating cognitive function in this population. In this current narrative review, we will first examine evidence linking the cholinergic system to cognitive functions; with a specific focus on drugs that affect this system. we will then discuss the potential implications of cholinergic function in patients with CKD

One step synthesis of tryptophan-isatin carbon nano dots and bio-applications as multifunctional nanoplatforms

The development of natural molecule-derived carbon nano dots (CNDs) marks a significant advancement in biocompatible and sustainable nanomaterials. Tryptophan, capable of crossing the blood-brain barrier (BBB), serves as a precursor to numerous pharmacologically active compounds, while isatin and its derivatives have demonstrated anti-tumor effects, including against brain cancers. This study aimed to synthesize fluorescent CNDs from tryptophan-isatin hybrid precursor and explore their applications in glioblastoma treatment. These CNDs were characterized using techniques such as TEM, SEM-EDS, FTIR, XPS, Raman spectroscopy and UV-Vis spectrophotometry. In vitro tests using the U-87 glioblastoma cell line evaluated cell viability, affinity, and BBB permeability. The CNDs, between 4 and 7 nm in size, exhibited blue and green fluorescence, with no cytotoxic effects observed at concentrations up to 25 µg/mL. The highest BBB permeability rate was determined as 4.3 × 10⁻⁵ cm/s. Additionally, the CNDs demonstrated radiotherapeutic properties, leading to a 51 % reduction in cell viability. This research contributes to nanomedicine by introducing a novel biocompatible material with potential for targeted brain cancer imaging and therapy, while also suggesting broader applications beyond glioblastoma

Investigation of the tissue equivalence of typical 3D-printing materials for application in internal dosimetry using monte carlo simulations

This study evaluates the dosimetric accuracy of PLA and ABS 3D-printed phantoms compared to real tissues using Monte Carlo simulations in radionuclide therapy. Materials and methods: A phantom representing average liver and lung volumes, with a 10 mm tumor mimic in the liver, was simulated for radioembolization using 1 mCi Tc-99 m and 1 mCi Y-90. The dose distribution (DD) was compared across PLA, ABS, and real organ densities. Results: For Tc-99 m, PLA showed a + 5.6% DD difference in the liver, and ABS showed - 35.3% and - 40.9% differences in the lungs. For Y-90, PLA had a + 1.7% DD difference in the liver, while ABS showed - 34.2% and - 34.9% differences in the lungs. Conclusion: In MC simulation, PLA is suitable for representing high-density tissues, while ABS is appropriate for simulating moderately low-density tissues

Intrusion detection system in wireless sensor networks using machine learning

Current industrial control systems are increasingly integrating with corporate Internet technology networks in order to fully utilize the abundant resources available on the Internet. The growing connection between industrial control systems and the internet has made them a desirable choice. Industrial control systems are in need of significant protection due to being a common target for a range of cyber-attacks. The use of the Internet of Things is currently increasing across industries due to its efficiency, and the Internet of Things is facing a security challenge. This document gives an overview of the intrusion detection system and the methods of the intrusion detection system. The purpose of this document is to examine intrusion detection methods and present the best method based on studies. Experimental results show that this system uses a combination of machine learning methods for high performance

Smart Energy Management in Green Cloud Computing using Machine Learning Algorithms

Cloud computing has many advantages as well as some disadvantages. An internet connection is required to use Cloud Computing. In other words, it is not possible to access the data in cases without internet. Cloud Computing can provide infrastructure services, platform services and software services to individuals with any device connected to the internet. If the connection speed is low when there is internet, the data transmission is also slower. In this context, it may not be practical for individuals or institutions to benefit from Cloud Computing in places where internet connection is low, limited, or absent. A new technology was obtained in this study; this method depends on deep learning and machine learning techniques applied to detect the attacks in the cloud computing-based systems. The suggested method compared with many traditional machine learning techniques. © 2025, American Scientific Publishing Group (ASPG). All rights reserved

OPTIMIZING ROAD SAFETY: THE ROLE OF GEOGRAPHIC INFORMATION SYSTEMS (GIS) IN TRAFFIC ACCIDENT ANALYSIS AND PREDICTION

This study investigates the application of Geographic Information Systems (GIS) in traffic accident analysis and prediction. By integrating GIS with deep learning techniques, the research highlights how spatial data management and analysis can enhance road safety. Key objectives include identifying accident hotspots, optimizing traffic control systems, and improving emergency response. The methodology involves a comprehensive review of existing literature, emphasizing GIS's role in data integration, spatial analysis, and predictive modeling. Findings demonstrate that GIS significantly contributes to understanding traffic patterns, predicting accidents, and formulating targeted safety interventions. Challenges such as data complexity, real-time processing, and model interpretability are addressed, offering future directions for leveraging GIS in road safety management. The study concludes that GIS, combined with advanced analytics, presents a powerful tool for reducing traffic accidents and enhancing overall traffic safety