Evaluation of serum levels of irisin, tumor necrosis factor and some biochemical variables in males with prostate cancer in Baghdad City.

Prostate cancer is the most common type after the age of fifty. It affects males and affects the prostate gland, which protects the function of sperm by producing semen. The current study was designed to evaluate prostate cancer infection effects on some biomarkers such as irisin, Tumor necrosis factor-TNF-α, prostate acid phosphates -PAP, Glutathione-GSH, malondialdehyde-MDA, urea, and creatinine.

Efficacy of non -thermal pressure plasma versus other modalities for disinfection of primary root canals.

Background: Endodontic treatment aims in the preservation of extremely carious primary teeth. For root canal therapy to be successful, root canals must be properly prepared and effectively irrigated .Therefore, it is necessary to select the proper root canal disinfection method to preserve the primary tooth.

Optimized molecule detection in localization microscopy with selected false positive probability.

Single-molecule localization microscopy (SMLM) allows imaging beyond the diffraction limit. Detection of molecules is a crucial initial step in SMLM. False positive detections, which are not quantitatively controlled in current methods, are a source of artifacts that affect the entire SMLM analysis pipeline.

Northern Scandinavian mountains supported by a low-grade eclogitic crustal keel.

Plate tectonics predicts that mountain ranges form by tectono-magmatic processes at plate boundaries, but high topography is often observed along passive margins far from any plate boundary. The high topography of the Scandes range at the Atlantic coast of Fennoscandia is traditionally assumed isostatically supported by variation in crustal density and thickness. Here we demonstrate, by our Silverroad seismic profile, that the constantly ~44 km thick crust instead is homogenous above the Moho, and Pn-velocity abruptly change from 7.

DNA-binding affinity and specificity determine the phenotypic diversity in BCL11B-related disorders.

BCL11B is a Cys2-His2 zinc-finger (C2H2-ZnF) domain-containing, DNA-binding, transcription factor with established roles in the development of various organs and tissues, primarily the immune and nervous systems. BCL11B germline variants have been associated with a variety of developmental syndromes. However, genotype-phenotype correlations along with pathophysiologic mechanisms of selected variants mostly remain elusive.

Rye secalin isolates to develop reference materials for gluten detection.

Gluten-free products must not contain more than 20 mg/kg of gluten to be safe for consumption by celiac disease patients. Almost all analytical methods are calibrated to wheat, wheat gluten or gliadin, and there is no rye-specific reference material available. The aim of this study was to assess the effect of the harvest year on rye gluten composition and to generate distinct rye isolates to serve as calibration standards.

Neural invasion severity is a strong predictor of local recurrence in pancreatic ductal adenocarcinoma.

Background: In pancreatic ductal adenocarcinoma, neural invasion is being increasingly recognized as an unfavorable predictor of patient outcomes. Neural invasion severity seems to have a stronger clinical impact on patient prognosis than neural invasion status alone. Therefore, this study aims to assess the impact of severity of neural invasion on overall survival and disease-free survival in pancreatic ductal adenocarcinoma.

Ecology of prophage-like elements in Bacillus subtilis at global and local geographical scales.

Prophages constitute a substantial portion of bacterial genomes, yet their effects on hosts remain poorly understood. We examine the abundance, distribution, and activity of prophages in Bacillus subtilis using computational and laboratory analyses. Genome sequences from the NCBI database and riverbank soil isolates reveal prophages primarily related to mobile genetic elements in laboratory strains.

Growth modeling of the European grayling (Thymallus thymallus L.) in a large alpine river based on age-at-length, mark-recapture, and length-frequency data.

Animal growth is a fundamental component of population dynamics, which is closely tied to mortality, fecundity, and maturation. As a result, estimating growth often serves as the basis of population assessments. In fish, analysing growth typically involves fitting a growth model to age-at-length data derived from counting growth rings in calcified structures.

A New Approach for Infrared Temperature Measurement Sensor Systems and Temperature Control for Domestic Induction Hobs.

The accurate measurement of cooking vessel temperatures in induction hobs is crucial for ensuring optimal cooking performance and safety. To achieve this, improvements in existing measurement methods such as thermocouples, thermistors, and infrared (IR) temperature sensors are being explored. However, traditional IR sensors are sensitive to interference from the heated glass ceramic, severely affecting accuracy.

Geotechnical Assessment of Foundation Stability for Preserving the Agrippa Monument at the Acropolis of Athens.

This study focuses on the geotechnical evaluation of the foundation conditions of the Agrippa Monument at the Acropolis of Athens, aiming to propose interventions to improve stability and reduce associated risks. The assessment reveals highly uneven foundation conditions beneath the monument. A thorough collection of bibliographic references and geotechnical surveys was conducted, classifying geomaterials into engineering-geological units and evaluating critical parameters for geotechnical design.

Vibration Control of Flexible Launch Vehicles Using Fiber Bragg Grating Sensor Arrays.

The effects of mechanical vibrations on control system stability could be significant in control systems designed on the assumption of rigid-body dynamics, such as launch vehicles. Vibrational loads can also cause damage to launch vehicles due to fatigue or excitation of structural resonances. This paper investigates a method to control structural vibrations in real time using a finite number of strain measurements from a fiber Bragg grating (FBG) sensor array.

The Realization of a Three-Dimensional Temperature Measurement System with a Two-Dimensional Sensor Array and the Demonstration of the Deformation Effect of Gravity on the Heating Patterns.

Electric heaters are widely used owing to their portability, fast heating, single-focus heating, and energy efficiency advantages. Manufacturers provide customers with information on the power consumption and energy efficiency classes of heaters but do not provide any information on heating patterns. Knowing the heating pattern enables users to select the correct heater, which has a significant effect on comfort, health, energy efficiency, industrial process performance, plant growth, and climate change.

Performance Improvement with Reduced Number of Channels in Motor Imagery BCI System.

Classifying Motor Imaging (MI) Electroencephalogram (EEG) signals is of vital importance for Brain-Computer Interface (BCI) systems, but challenges remain. A key challenge is to reduce the number of channels to improve flexibility, portability, and computational efficiency, especially in multi-class scenarios where more channels are needed for accurate classification. This study demonstrates that combining Electrooculogram (EOG) channels with a reduced set of EEG channels is more effective than relying on a large number of EEG channels alone.

A Comparative Analysis of Explainable Artificial Intelligence Models for Electric Field Strength Prediction over Eight European Cities.

The widespread propagation of wireless communication devices, from smartphones and tablets to Internet of Things (IoT) systems, has become an integral part of modern life. However, the expansion of wireless technology has also raised public concern about the potential health risks associated with prolonged exposure to electromagnetic fields. Our objective is to determine the optimal machine learning model for constructing electric field strength maps across urban areas, enhancing the field of environmental monitoring with the aid of sensor-based data collection.

Advanced Brain Tumor Classification in MR Images Using Transfer Learning and Pre-Trained Deep CNN Models.

Background/objectives: Brain tumor classification is a crucial task in medical diagnostics, as early and accurate detection can significantly improve patient outcomes. This study investigates the effectiveness of pre-trained deep learning models in classifying brain MRI images into four categories: Glioma, Meningioma, Pituitary, and No Tumor, aiming to enhance the diagnostic process through automation.

Methods: A publicly available Brain Tumor MRI dataset containing 7023 images was used in this research.

Superior Anti-Tumor Response After Microbeam and Minibeam Radiation Therapy in a Lung Cancer Mouse Model.

Objectives: The present study aimed to compare the tumor growth delay between conventional radiotherapy (CRT) and the spatially fractionated modalities of microbeam radiation therapy (MRT) and minibeam radiation therapy (MBRT). In addition, we also determined the influence of beam width and the peak-to-valley dose ratio (PVDR) on tumor regrowth.

Methods: A549, a human non-small-cell lung cancer cell line, was implanted subcutaneously into the hind leg of female CD1 mice.

Introducing and Validating the Multiphasic Evidential Decision-Making Matrix (MedMax) for Clinical Management in Patients with Intrahepatic Cholangiocarcinoma.

Despite the significant advancements of liver surgery in the last few decades, the survival rate of patients with liver and pancreatic cancers has improved by only 10% in 30 years. Precision medicine offers a patient-centered approach, which, when combined with machine learning, could enhance decision making and treatment outcomes in surgical management of ihCC. This study aims to develop a decision support model to optimize treatment strategies for patients with ihCC, a prevalent primary liver cancer.

Deep Learning for Melanoma Detection: A Deep Learning Approach to Differentiating Malignant Melanoma from Benign Melanocytic Nevi.

: Melanoma, an aggressive form of skin cancer, accounts for a significant proportion of skin-cancer-related deaths worldwide. Early and accurate differentiation between melanoma and benign melanocytic nevi is critical for improving survival rates but remains challenging because of diagnostic variability. Convolutional neural networks (CNNs) have shown promise in automating melanoma detection with accuracy comparable to expert dermatologists.

Molecular Detection of and at Different Stages of Wine Production.

and belong to acetic acid bacteria (AAB), associated with wine spoilage. The timely detection of AAB, thought essential for their control, is however challenging due to the difficulties of their isolation. Thus, it would be advantageous to detect them using molecular methods at all stages of winemaking and storage.

Celiac Disease, Gluten-Free Diet, and Eating Disorders: From Bench to Bedside.

Celiac disease (CD) and eating disorders (EDs) are complex chronic conditions in adolescents, sharing symptoms such as weight change, malnutrition, and gastrointestinal symptoms. CD, an autoimmune disorder triggered by gluten ingestion, is managed through a strict gluten-free diet that can unintentionally foster disordered eating behaviors due to dietary restrictions. Conversely, EDs may mask and complicate CD symptoms, leading to diagnostic delays and treatment challenges.

Effect of Brewers' Spent Grain Addition to a Fermented Form on Dough Rheological Properties from Different Triticale Flour Cultivars.

Triticale grains and brewers' spent grain (BSG) can be new sources to develop food products. From a socio-economical point of view, this fact is important since triticale is easily adapted to the climatic changes and BSG is a low-cost material which may lead to a "zero-waste" desiderate. In this study, dough rheological properties obtained from different triticale cultivars (Ingen 33, Ingen 35, Ingen 54, and Ingen 93) cultivated in the Republic of Moldova and BSG in a fermented form (BSF) in an addition level of 10% and 17.

The Influence of Rice Types and Boiling Time on Glycemic Index: An In Vivo Evaluation Using the ISO 2010 Method.

Effective blood glucose management is essential for individuals with type 1 diabetes, particularly when dietary adjustments involve staple foods like rice. As a primary carbohydrate worldwide, rice significantly influences the glycemic index (GI) based on its type and cooking method. This study investigated the impact of rice type and boiling duration on the GI in healthy adults using an in vivo approach aligned with ISO 2010 standards.