Synthesis and Evaluation of Cytotoxic Activity of RuCp(II) Complexes Bearing (Iso)nicotinic Acid Based Ligands.

Background/objectives: Cancer remains one of the major challenges of our century. Organometallic ruthenium complexes are gaining recognition as a highly promising group of compounds in the development of cancer treatments.

Methods: Building on the auspicious results obtained for [Ru(η-CH)(PPh)(bipy)][CFSO] (TM34), our focus has shifted to examining the effects of incorporating bioactive ligands into the TM34 framework, particularly within the cyclopentadienyl ring.

A Simple Machine Learning-Based Quantitative Structure-Activity Relationship Model for Predicting pIC Inhibition Values of FLT3 Tyrosine Kinase.

Acute myeloid leukemia (AML) presents significant therapeutic challenges, particularly in cases driven by mutations in the FLT3 tyrosine kinase. This study aimed to develop a robust and user-friendly machine learning-based quantitative structure-activity relationship (QSAR) model to predict the inhibitory potency (pIC values) of FLT3 inhibitors, addressing the limitations of previous models in dataset size, diversity, and predictive accuracy. Using a dataset which was 14 times larger than those employed in prior studies (1350 compounds with 1269 molecular descriptors), we trained a random forest regressor, chosen due to its superior predictive performance and resistance to overfitting.

Antistaphylococcal Triazole-Based Molecular Hybrids: Design, Synthesis and Activity.

Background: In the era of resistance, the design and search for new "small" molecules with a narrow spectrum of activity that target a protein or enzyme specific to a certain bacterium with high selectivity and minimal side effects remains an urgent problem of medicinal chemistry. In this regard, we developed and successfully implemented a strategy for the search for new hybrid molecules, namely, the not broadly known [2-(3-R-1-[1,2,4]-triazol-5-yl)phenyl]amines. They can act as "building blocks" and allow for the introduction of certain structural motifs into the desired final products in order to enhance the antistaphylococcal effect.

Chemical Characterization and Differential Lipid-Modulating Effects of Selected Plant Extracts from Côa Valley (Portugal) in a Cell Model for Liver Steatosis.

Background/objectives: Côa Valley, located in the northeast of Portugal, harbors more than 500 medicinal plant species. Among them, four species stand out due to their traditional uses: Desf. (hemorrhages, urethritis, hepatitis), L.

GnRH Peptide Antagonist: Comparative Analysis of Chemistry and Formulation with Implications for Clinical Safety and Efficacy.

Overexpression of the gonadotropin-releasing hormone receptor (GnRH-R) plays a vital role in the advancement of reproductive malignancies such as ovarian, endometrial, and prostate cancer. Peptidomimetic GnRH antagonists are a substantial therapeutic development, providing fast and reversible suppression of gonadotropins by directly blocking GnRH-R. Unlike typical GnRH agonists, these antagonists prevent the early hormonal flare, have a faster onset of action, and have a lower risk of cardiovascular problems.

Evaluation of Prediction Models for the Capping and Breaking Force of Tablets Using Machine Learning Tools in Wet Granulation Commercial-Scale Pharmaceutical Manufacturing.

: This study aimed to establish a predictive model for critical quality attributes (CQAs) related to tablet integrity, including tablet breaking force (TBF), friability, and capping occurrence, using machine learning-based models and nondestructive experimental data. : The machine learning-based models were trained on data to predict the CQAs of metformin HCl (MF)-containing tablets using a commercial-scale wet granulation process, and five models were each compared for regression and classification. We identified eight input variables associated with the process and material parameters that control the tableting outcome using feature importance analysis.

Ivermectin Strengthens Paclitaxel Effectiveness in High-Grade Serous Carcinoma in 3D Cell Cultures.

Background: Chemoresistance is a major obstacle in high-grade serous carcinoma (HGSC) treatment. Although many patients initially respond to chemotherapy, the majority of them relapse due to Carboplatin and Paclitaxel resistance. Drug repurposing has surfaced as a potentially effective strategy that works synergically with standard chemotherapy to bypass chemoresistance.

A Conserved Di-Lysine Motif in the E2 Transactivation Domain Regulates MmuPV1 Replication and Disease Progression.

The papillomavirus E2 protein regulates the transcription, replication, and segregation of viral episomes within the host cell. A multitude of post-translational modifications have been identified which control E2 functions. A highly conserved di-lysine motif within the transactivation domain (TAD) has been shown to regulate the normal functions of the E2 proteins of BPV-1, SfPV1, HPV-16, and HPV-31.

HIV Drug Resistance Profile in Clients Experiencing Treatment Failure After the Transition to a Dolutegravir-Based First-Line Antiretroviral Treatment Regimen in Mozambique.

Real-world data on HIV drug resistance (HIVDR) after transitioning to tenofovir disoproxil fumarate/lamivudine/dolutegravir (TLD) are limited. We assessed HIVDR rates and patterns in clients with virological failure (VF) after switching from an NNRTI-based regimen to TLD. A cross-sectional study was conducted in Gaza, Mozambique (August 2021-February 2022), including adults on first-line ART for ≥12 months who transitioned to TLD and had unsuppressed viral load (VL) ≥ 1000 copies/mL six months post-transition.

The Evaluation of Antibacterial Coatings Against Commonly Found Pathogenic Bacteria in the Environment-Implications for Environmental Safety and Infection Prevention.

Microorganisms, including pathogens that cause skin, respiratory, and urinary tract infections, are widespread in our environment. Despite routine cleaning with bleach and disinfectants, the transmission of pathogens still occurs, leading to potential infectious diseases. This study aimed to determine the antibacterial effect of two coating formulas against common environmental pathogens like , , , , sp.

Ticks and Tick-Borne Pathogens in Wild Animals and Birds from Two Rehabilitation Facilities in Greece.

Ticks are temporary ectoparasites that serve as vectors for a wide range of pathogens affecting both wildlife and humans. In Greece, research on the prevalence of tick-borne pathogens in wildlife is limited. This study investigates the presence of pathogens, including spp.

Cloud/VPN-Based Remote Control of a Modular Production System Assisted by a Mobile Cyber-Physical Robotic System-Digital Twin Approach.

This paper deals with a "digital twin" (DT) approach for processing, reprocessing, and scrapping (P/R/S) technology running on a modular production system (MPS) assisted by a mobile cyber-physical robotic system (MCPRS). The main hardware architecture consists of four line-shaped workstations (WSs), a wheeled mobile robot (WMR) equipped with a robotic manipulator (RM) and a mobile visual servoing system (MVSS) mounted on the end effector. The system architecture integrates a hierarchical control system where each of the four WSs, in the MPS, is controlled by a Programable Logic Controller (PLC), all connected via Profibus DP to a central PLC.

Research on Fire Detection of Cotton Picker Based on Improved Algorithm.

According to the physical characteristics of cotton and the work characteristics of cotton pickers in the field, during the picking process, there is a risk of cotton combustion. The cotton picker working environment is complex, cotton ignition can be hidden, and fire is difficult to detect. Therefore, in this study, we designed an improved algorithm for multi-sensor data fusion; built a cotton picker fire detection system by using infrared temperature sensors, CO sensors, and the upper computer; and proposed a BP neural network model based on improved mutation operator hybrid gray wolf optimizer and particle swarm optimization (MGWO-PSO) algorithm based on the BP neural network model.

Virtual Node-Driven Cloud-Edge Collaborative Resource Scheduling for Surveillance with Visual Sensors.

For public security purposes, distributed surveillance systems are widely deployed in key areas. These systems comprise visual sensors, edge computing boxes, and cloud servers. Resource scheduling algorithms are critical to ensure such systems' robustness and efficiency.

Internal Integrated Temperature Sensor for Lithium-Ion Batteries.

Lithium-ion batteries represent a significant component of the field of energy storage, with a diverse range of applications in consumer electronics, portable devices, and numerous other fields. In view of the growing concerns about the safety of batteries, it is of the utmost importance to develop a sensor that is capable of accurately monitoring the internal temperature of lithium-ion batteries. External sensors are subject to the necessity for additional space and ancillary equipment.

Time Series Data Augmentation for Energy Consumption Data Based on Improved TimeGAN.

Predicting the time series energy consumption data of manufacturing processes can optimize energy management efficiency and reduce maintenance costs for enterprises. Using deep learning algorithms to establish prediction models for sensor data is an effective approach; however, the performance of these models is significantly influenced by the quantity and quality of the training data. In real production environments, the amount of time series data that can be collected during the manufacturing process is limited, which can lead to a decline in model performance.

Dynamic Interferometry for Freeform Surface Measurement Based on Machine Learning-Configured Deformable Mirror.

Optical freeform surfaces are widely used in imaging and non-imaging systems due to their high design freedom. In freeform surface manufacturing and assembly, dynamic freeform surface measurement that can guide the next operation remains a challenge. To meet this urgent need, we propose a dynamic interferometric method based on a machine learning-configured deformable mirror (DM).

Automated Volumetric Milling Area Planning for Acoustic Neuroma Surgery via Evolutionary Multi-Objective Optimization.

Mastoidectomy is critical in acoustic neuroma surgery, where precise planning of the bone milling area is essential for surgical navigation. The complexity of representing the irregular volumetric area and the presence of high-risk structures (e.g.

A New Self-Made 16-Channel Capacitive Electrocardiography System: An Investigation and Validation for Non-Contact Electrodes.

Generally, the electrocardiography (ECG) system plays an important role in preventing and diagnosing heart diseases. To further improve the amenity and convenience of using an ECG system, we built a customized capacitive electrocardiography (cECG) system with one wet electrode, sixteen non-contact electrodes, two ADS1299 chips, and one STM32F303-based microcontroller unit (MCU). This new cECG system could acquire, save, and display the ECG data in real time.

Benzo[1,2-b:6,5-b']dithiophene-4,5-diamine: A New Fluorescent Probe for the High-Sensitivity and Real-Time Visual Monitoring of Phosgene.

The detection of highly toxic chemicals such as phosgene is crucial for addressing the severe threats to human health and public safety posed by terrorist attacks and industrial mishaps. However, timely and precise monitoring of phosgene at a low cost remains a significant challenge. This work is the first to report a novel fluorescent system based on the Intramolecular Charge Transfer (ICT) effect, which can rapidly detect phosgene in both solution and gas phases with high sensitivity by integrating a benzo[1,2-b:6,5-b']dithiophene-4,5-diamine (BDTA) probe.

Fine-Grained Building Classification in Rural Areas Based on GF-7 Data.

Building type information is widely used in various fields, such as disaster management, urbanization studies, and population modelling. Few studies have been conducted on fine-grained building classification in rural areas using China's Gaofen-7 (GF-7) high-resolution stereo mapping satellite data. In this study, we employed a two-stage method combining supervised classification and unsupervised clustering to classify buildings in the rural area of Pingquan, northern China, based on building footprints, building heights, and multispectral information extracted from GF-7 data.

Development of a Mobile Laser Measurement System for Subway Tunnel Deformation Detection.

In recent years, mobile laser measurement systems have markedly enhanced the capabilities of deformation detection and defect identification within metro tunnels, attributed to their superior efficiency, precision, and versatility. Nevertheless, challenges persist, including substantial equipment costs, inadequate after-sales support, technological barriers, and limitations in customization. This paper develops a mobile laser measurement system that has been specifically developed for the purpose of detecting deformation in metro tunnels.

Studies on the High-Power Piezoelectric Property Measurement Methods and Decoupling the Power and Temperature Effects on PZT-5H.

For those piezoelectric materials that operate under high-power conditions, the piezoelectric and dielectric properties obtained under small signal conditions cannot be directly applied to high-power transducers. There are three mainstream high-power characterization methods: the constant voltage method, the constant current method, and the transient method. In this study, we developed and verified a combined impedance method that integrated the advantages of the constant voltage and current methods, along with an improved transient method, for high-power testing of PZT-5H piezoelectric ceramics.

PC-YOLO11s: A Lightweight and Effective Feature Extraction Method for Small Target Image Detection.

Compared with conventional targets, small objects often face challenges such as smaller size, lower resolution, weaker contrast, and more background interference, making their detection more difficult. To address this issue, this paper proposes an improved small object detection method based on the YOLO11 model-PC-YOLO11s. The core innovation of PC-YOLO11s lies in the optimization of the detection network structure, which includes the following aspects: Firstly, PC-YOLO11s has adjusted the hierarchical structure of the detection network and added a P2 layer specifically for small object detection.

Calibration of Low-Cost Capacitive Soil Moisture Sensors for Irrigation Management Applications.

The calibration of capacitive soil moisture sensors is an essential step towards their integration into smart solutions. This study investigates the calibration of a widely used low-cost capacitive soil moisture sensor (SKU:SEN0193, DFRobot, Shanghai, China) in a loamy silt soil typically found in the Puglia region of Italy. The calibration function was derived from a random sample of 12 sensors, with three soil sample replicas per sensor, each of which had one of five gravimetric soil moisture contents, from relatively dry (5%) to full saturation (40%).