Electrical Diuretics: Lateral Epidural Stimulation of Dorsal Roots to Increase Diuresis.

Background: Stimulating diuresis is crucial in heart failure (HF) treatment. Diuretic resistance develops in approximately 30% to 45% of patients with HF.

Objective: We investigated the feasibility and safety of lateral epidural stimulation (LES) to enhance diuresis by stimulating renal afferent sensory nerves.

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Farmakogenomika to dziedzina z pogranicza farmacji i genomiki. Zajmuje się ona badaniem wpływu występujących u pacjenta wariantów genów związanych z metabolizmem leków na jego reakcję na konkretny lek. Rolą testów farmakogenomicznych jest określenie tempa metabolizmu leków i wykorzystanie tej informacji w praktyce klinicznej.

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Rak jelita grubego (RJG) jest jednym z najczęściej rozpoznawanych nowotworów złośliwych: co roku notowane jest około 1,9 miliona nowych przypadków. Pomimo opracowania metod umożliwiających jego wykrywanie na początkowym etapie choroby i wprowadzenia nowych, skuteczniejszych terapii, RJG plasuje się na drugim miejscu wśród przyczyn zgonów wywołanych nowotworami. Wyniki najnowszych badań podkreślają rolę transporterów kwasów tłuszczowych, tj.

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Wzrastająca liczba ludności, kurczące sią areały uprawne i zmiany klimatyczne skłaniają do poszukiwania nowych rozwiązań w rolnictwie. W zrównoważonym podejściu rolnictwo powinno opierać się podnoszeniu jakości i ilości plonów przy zachowaniu bioróżnorodności i ochrony środowiska naturalnego. Nanotechnologia, obecna w wielu dziedzinach życia, stwarza możliwości wspierania rozwoju zrównoważonego rolnictwa na wielu płaszczyznach.

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Rak trzustki jest często występującym nowotworem o bardzo złych rokowaniach i agresywnym przebiegu. Podstawową przyczyn wysoce niekorzystnych rokowań pacjentów z rakiem trzustki jest jego długotrwale bezobjawowy rozwój, co powoduje postawienie diagnozy na etapie znacznego zaawansowania procesu nowotworowego. Pomimo szeroko zakrojonych badań nad uskutecznieniem diagnostyki i leczenia tego nowotworu, przeżywalność pacjentów wzrasta powoli i nieznacznie.

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Prostaglandyny są hormonami występującymi niemal we wszystkich ssaczych tkankach. Jako cząsteczki sygnałowe odgrywają one kluczową rolę w regulacji wielu procesów fizjologicznych, m. in.

Has COVID-19 Affected the Course of Chickenpox in Children?

Objectives Of The Study: The aim of this study was to assess the impact of the COVID-19 pandemic on the epidemiology and clinical course of chickenpox in children based on 6 years of self-reported observations.

Material And Methods: The medical records of 350 patients under 18 years of age hospitalised in the Department of Paediatrics, Infectious Diseases, and Hepatology between 1 January 2018 to 31 December 2023 were analysed retrospectively.

Results: During the analysed period, 350 children were hospitalised due to chickenpox, the fewest in the pandemic period, the greatest number in 2023.

Public Awareness and Willingness to Vaccinate Against Herpes Zoster: A Nationwide Cross-Sectional Study in Poland.

Objectives: Herpes zoster (HZ), caused by varicella zoster virus reactivation, affects a significant portion of the population, leading to substantial morbidity. Vaccination is highly effective in preventing HZ, yet awareness and uptake remain low. This study assessed awareness and willingness to vaccinate against HZ in Poland following the introduction of a reimbursement policy.

Analysis of Implementation Strategies for Nationwide HPV Vaccination Programs Across European Union Countries.

Background/objectives: Human papillomavirus (HPV) vaccination programs play a critical role in the primary prevention of HPV-related diseases, including cervical cancer. However, the principles governing the implementation of these programs vary across European Union (EU) countries. The objective of this study was to analyze and compare the strategies for implementing HPV vaccination programs across the EU, with a focus on access, vaccine selection, and procurement processes.

The Impact of Vaccinations Against Respiratory Infections on the Prognosis in Heart Failure Patients.

Heart failure (HF) affects 64 million people worldwide and is one of the most prevalent causes of hospitalization in adults. Infection is believed to be one of the potential triggers that may facilitate HF decompensation and the need for hospitalization. Therefore, it seems crucial to safeguard against such a situation.

Correction: Almadhor et al. AI-Driven Framework for Recognition of Guava Plant Diseases through Machine Learning from DSLR Camera Sensor Based High Resolution Imagery. 2021, , 3830.

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Correction: Sage et al. Hybridization of Acoustic and Visual Features of Polish Sibilants Produced by Children for Computer Speech Diagnosis. 2024, , 5360.

In the original publication [...

Analysis of Stability and Variability in Sensor Readings from a Vehicle Weigh-in-Motion Station.

This study presents a detailed analysis of the stability of weigh-in-motion sensors used at vehicle weighing stations. The objective of this research was a long-term assessment of reading variability, with a particular focus on the sensors' application in automated measurement stations. These investigations constitute a critical component of modern traffic management systems and vehicle overload control.

Emerging Trends in the Integration of Smart Sensor Technologies in Structural Health Monitoring: A Contemporary Perspective.

In recent years, civil engineering has increasingly embraced communication tools for automation, with sensors playing a pivotal role, especially in structural health monitoring (SHM). These sensors enable precise data acquisition, measuring parameters like force, displacement, and temperature and transmit data for timely interventions to prevent failures. This approach reduces reliance on manual inspections, offering more accurate outcomes.

Machine Learning Recognizes Stages of Parkinson's Disease Using Magnetic Resonance Imaging.

Neurodegenerative diseases (NDs), such as Alzheimer's disease (AD) and Parkinson's disease (PD), are debilitating conditions that affect millions worldwide, and the number of cases is expected to rise significantly in the coming years. Because early detection is crucial for effective intervention strategies, this study investigates whether the structural analysis of selected brain regions, including volumes and their spatial relationships obtained from regular T1-weighted MRI scans ( = 168, PPMI database), can model stages of PD using standard machine learning (ML) techniques. Thus, diverse ML models, including Logistic Regression, Random Forest, Support Vector Classifier, and Rough Sets, were trained and evaluated.

High-Resolution Single-Pixel Imaging of Spatially Sparse Objects: Real-Time Imaging in the Near-Infrared and Visible Wavelength Ranges Enhanced with Iterative Processing or Deep Learning.

We demonstrate high-resolution single-pixel imaging (SPI) in the visible and near-infrared wavelength ranges using an SPI framework that incorporates a novel, dedicated sampling scheme and a reconstruction algorithm optimized for the rapid imaging of highly sparse scenes at the native digital micromirror device (DMD) resolution of 1024 × 768. The reconstruction algorithm consists of two stages. In the first stage, the vector of SPI measurements is multiplied by the generalized inverse of the measurement matrix.

A Case Study on EEG Signal Correlation Towards Potential Epileptic Foci Triangulation.

The precise localization of epileptic foci with the help of EEG or iEEG signals is still a clinical challenge with current methodology, especially if the foci are not close to individual electrodes. On the research side, dipole reconstruction for focus localization is a topic of recent and current developments. Relatively low numbers of recording electrodes cause ill-posed and ill-conditioned problems in the inversion of lead-field matrices to calculate the focus location.

Signal Detection by Sensors and Determination of Friction Coefficient During Brake Lining Movement.

This article presents a laboratory device by which the course of two signals can be detected using two types of sensors-strain gauges and the DEWESoft DS-NET measuring apparatus. The values of the coefficient of friction of the brake lining when moving against the rotating shell of the brake drum were determined from the physical quantities sensed by tensometric sensors and transformed into electrical quantities. The friction coefficient of the brake lining on the circumference of the rotating brake disc shell can be calculated from the known values measured by the sensors, the design dimensions of the brake, and the revolutions of the rotating parts system.

The Application and Optimisation of a Neural Network PID Controller for Trajectory Tracking Using UAVs.

This paper considers the problem of flying a UAV along a given trajectory at speeds close to the speed of sound and above. A novel pitch channel control system is presented using the example of a trajectory with rapid and large changes in flight height. The control system uses a proportional-integral-differential (PID) controller, whose gains were first determined using the Ziegler-Nichols II method.

Development of Inductive Current Transformer 400/5/1 of Class 0.2S for Frequency Range 50 Hz-5 kHz.

This paper is devoted to the development of a window-type inductive current transformer (iCT) with a rated primary current equal to 400 A and two secondary windings with rated currents of 5 A and 1 A. Its novelty concerns the presentation of this process in the case of an iCT with a 0.2S accuracy class ensured not only for a sinusoidal current of a frequency of 50 Hz but also for the transformation of distorted current in the harmonic frequency range from 50 Hz to 5 kHz.

Optimization of Imaging Reconnaissance Systems Using Super-Resolution: Efficiency Analysis in Interference Conditions.

Image reconnaissance systems are critical in modern applications, where the ability to accurately detect and identify objects is crucial. However, distortions in real-world operational conditions, such as motion blur, noise, and compression artifacts, often degrade image quality, affecting the performance of detection systems. This study analyzed the impact of super-resolution (SR) technology, in particular, the Real-ESRGAN model, on the performance of a detection model under disturbed conditions.

Simultaneous Temperature and Relative Humidity Measurement Using Machine Learning in Rayleigh-Based Optical Frequency Domain Reflectometry.

This paper presents, for the first time to the best of our knowledge, simultaneous temperature and relative humidity (RH) measurement using a machine learning (ML) model in Rayleigh-based Optical Frequency Domain Reflectometry (OFDR). The sensor unit consists of two segments: bare and polyimide-coated fibers, each with different sensitivities to temperature. The polyimide-coated fiber is RH-sensitive, unlike the bare fiber.

Measurement Properties of Wearable Kinematic-Based Data Collection Systems to Evaluate Ball Kicking in Soccer: A Systematic Review with Evidence Gap Map.

Kinematic assessment of ball kicking may require significant human effort (e.g., traditional vision-based tracking systems).

Amperometric Biosensor Based on Glutamate Oxidase to Determine Ast Activity.

This work presents the development of an amperometric biosensor for detecting aspartate aminotransferase (AST) activity in biological fluids using a platinum disk electrode as the working transducer. Optimal concentrations of substrates (aspartate, α-ketoglutarate) and the coenzyme (pyridoxal phosphate) were determined to ensure efficient biosensor operation. A semi-permeable poly-m-phenylenediamine membrane was applied to enhance selectivity against electroactive interferents.

The Influence of Polylactic Acid Filament Moisture Content on Dust Emissions in 3D Printing Process.

This paper presents the results of a study on the effect of moisture content in polylactic acid (PLA) filaments on dust emissions during incremental manufacturing. The tests were conducted in a customised chamber using a standard 3D printer, and Plantower PMS3003 sensors were used to monitor air quality by measuring PM1, PM2.5 and PM10 concentrations.