Browse Articles

Using failure mode and effects analysis for risk management of anesthetic and class I psychotropic drugs in inpatient pharmacy: a pilot study

AGTS: Novel automated generation of smart contract test suites for Hyperledger Fabric

Effects of diamond nanoparticle surface composition and the sp3/sp2 carbon ratio on tumor proangiogenic potential in vitro

Abstract The high proangiogenic potential of tumors is often associated with poor prognosis due to increased invasiveness and malignancy. Diamond nanoparticles (NDs) are considered a promising anti-tumor agent with anti-angiogenic properties; however, their activity is strictly connected with their physicochemical parameters and surface chemical composition. One of the main factors characterizing detonation NDs is the sp2 surface carbon content, which can determine the character of nanoparticle–cell interaction. The primary objective of this study was to investigate the influence of different types of NDs on the proangiogenic potential of tumor cells distinguished by phenotype and invasiveness. NDs with a high sp3/sp2 carbon ratio decreased the levels of crucial proangiogenic proteins secreted by T98G and HepG2 cells (IL-6, IL-8, ANG, TIMPs, and ANGPTs). Moreover, a lower sp2 carbon content on the surface of NDs reduced oxidative stress in both mesenchymal T98G and epithelial HepG2 tumor cells and affected the NF-κB activation state in a cell-specific manner. Modified NDs, by affecting the tumor cell secretome composition, indirectly inhibited endothelial cell migration and tube formation, demonstrating high cell type specificity. Taken together, the results presented here indicate the significance of the surface parameters of NDs in the indirect regulation of cellular signaling and the microenvironment.

Experimental research on the feasibility of phosphogypsum-enzyme induced carbonate precipitation (EICP) solidified loess

In vivo variability of MRI radiomics features in prostate lesions assessed by a test-retest study with repositioning

Abstract Despite academic success, radiomics-based machine learning algorithms have not reached clinical practice, partially due to limited repeatability/reproducibility. To address this issue, this work aims to identify a stable subset of radiomics features in prostate MRI for radiomics modelling. A prospective study was conducted in 43 patients who received a clinical MRI examination and a research exam with repetition of T2-weighted and two different diffusion-weighted imaging (DWI) sequences with repositioning in between. Radiomics feature (RF) extraction was performed from MRI segmentations accounting for intra-rater and inter-rater effects, and three different image normalization methods were compared. Stability of RFs was assessed using the concordance correlation coefficient (CCC) for different comparisons: rater effects, inter-scan (before and after repositioning) and inter-sequence (between the two diffusion-weighted sequences) variability. In total, only 64 out of 321 (~ 20%) extracted features demonstrated stability, defined as CCC ≥ 0.75 in all settings (5 high-b value, 7 ADC- and 52 T2-derived features). For DWI, primarily intensity-based features proved stable with no shape feature passing the CCC threshold. T2-weighted images possessed the largest number of stable features with multiple shape (7), intensity-based (7) and texture features (28). Z-score normalization for high-b value images and muscle-normalization for T2-weighted images were identified as suitable.

Prevalence, safety, and role of nicotine pouches in smoking cessation among smokers and the public in Saudi Arabia

Design and analysis of capacitive pressure sensor with L shaped electrode for enhanced sensitivity

Abstract Accurate pressure measurement is essential across a wide range of fields, including engineering, healthcare, and transportation. This paper presents the design and development of a novel capacitive pressure sensor featuring an extended measurement range and a large pressure application area compared to the parallel plate capacitor configuration. The main innovation lies in the shape and structure of the L shaped electrode which enhances the operational range in terms of the displacement, increased surface area. The sensor exhibits enhanced sensitivity and operational efficiency, making it well suited for diverse applications. The sensor is modeled and simulated in COMSOL MULTIPHYSICS environment to validate its functionality under varying pressure. The electric field distribution, change in capacitance and change in displacement are measurable from the simulation. The sensor is capable of bidirectional making it suitable for the measurement of differential pressure. The proposed sensor simulation results achieve an 11% improvement in both sensitivity and range over conventional parallel plate designs. Furthermore, its ability to operate as a bidirectional device highlights its adaptability and potential for integration into advanced sensing systems.

Alternating movement strategies of a tropical raptor

Abstract The majority of raptor species reside in the tropics, yet very little is known about their movement ecology. However, quantifying movement behavior can provide otherwise elusive information on resource needs, habitat selection, and ecological constraints, which is important for understanding ecological patterns and the management of species of conservation concern. On the Island of Hawai‘i, Hawai‘i, USA, the endemic ‘Io, or Hawaiian Hawk (Buteo solitarius), is a species of conservation concern that little is known of their movement ecology, yet they are dependent on a fragmented and rapidly changing environment. We tracked 15 individuals for up to 18 months across a diverse landscape on the eastern side of the island. We found that all ‘Io occupied a relatively small geographic area, their place of residency, where they spent all or most of their time. However, 10 individuals also exhibited an alternative movement pattern, where individuals repeatedly commuted back and forth between their place of residency to another, geographically disjunct location. These commuter periods, which could last from 24–180 days, were characterized by frequent (9–259) movements, with individual trips lasting 4–77 h away from their place of residency and 12–47 h in between commuter trips. In most cases, individuals went to the same non-contiguous commuting destination, even across multiple commuting sessions, indicating high fidelity to commuting locations. The ‘Io is a forest adapted Buteo but occurs across a diverse landscape from forest to agriculture lands to urban areas. Habitat selection analysis indicated high individual variation among different birds, but generally a preference for forest patches at localized levels. The discovery of the alternative commuting strategy for many ‘Io represents a cryptic movement pattern in the species, demonstrating the power of small, long-lived Global Position System tracking devices to track movement and providing important insights into the ecology of a tropical island raptor.

Blood pressure levels are higher in individuals with type 1 diabetes mellitus compared to healthy subjects during exercise stress test

Association between temperature rise from climate normal and sleep quality

Association between neutrophil percentage to albumin ratio and cardiovascular disease in the metabolic syndrome population

Association between the psychological frailty index and stroke: a cohort study from CHARLS

Design of a liquid cooled battery thermal management system using neural networks, cheetah optimizer and salp swarm algorithm

PENC: a predictive-estimative nonlinear control framework for robust target tracking of fixed-wing UAVs in complex urban environments

Microbial and nutrient enrichments in Brine and Nilas during the first 24 h of open water lead refreezing

Functional discrimination of CSF from Alzheimer’s patients in a brain on chip platform

Deep nested U-structure network with frequency attention for building semantic segmentation

Protein hydrolysates derived from residual after polysaccharide extraction of Chlorella vulgaris biomass improves yield and quality of baby leaf lettuce

Research on the impact of transportation infrastructure construction on urban sustainable development

Integrating 7-day D-dimer exposure into deep vein thrombosis risk prediction after gastrointestinal surgery

Abstract Deep vein thrombosis (DVT) is a serious complication following gastrointestinal surgery. While D-dimer is a widely used biomarker for thrombosis, its postoperative specificity is limited due to inflammatory interference. This study introduces a novel cumulative metric—7-day D-dimer exposure (7dDDE)—to quantify perioperative coagulation burden. We retrospectively analyzed 525 patients undergoing gastrointestinal surgery, performed propensity score matching, and constructed a multivariable logistic regression model incorporating 7dDDE and other clinical variables. Model performance was evaluated using ROC curves, decision curve analysis, calibration plots, SHAP values, and a nomogram. Additionally, a linear mixed-effects model assessed D-dimer trajectories over time. The results demonstrated that 7dDDE was independently associated with postoperative DVT and was the most influential predictor in the model. The model showed good discrimination and clinical utility. Longitudinal analysis further revealed significant differences in D-dimer dynamics between DVT and non-DVT groups, even after adjustment for confounders. These findings support the use of 7dDDE as a robust biomarker for thrombotic risk stratification and highlight the importance of integrating temporal biomarker patterns into perioperative DVT prediction.