Solvents prepared from natural terpenes (menthol and thymol), as H-bond acceptors, and a series of organic acids (chain lengths of 8, 10, and 14 C atoms), as H-bond donors, were characterized and tested as reaction media for liquid–liquid extraction purposes. Due to their high hydrophobicity, they seem to be promising alternatives to conventional (nonpolar and toxic) solvents, since they possess relatively less toxic, less volatile, and consequently, more environmentally friendly characteristics. Assuming that the equilibrium is established between solvent and analyte during a ligandless procedure, it can be concluded that those nonpolar solvents can efficiently extract nonpolar analytes from the aqueous environment. Previous investigations showed a wide range of applications, including their use as solvents in extractions of metal cations, small molecules, and bioactive compounds for food and pharmaceutical applications. In this work, hydrophobic solvents based on natural terpenes, which showed chemical stability and desirable physicochemical and thermal properties, were chosen as potential reaction media in the liquid–liquid extraction (LLE) procedure for Pb(II) removal from aqueous solutions. Low viscosities and high hydrophobicities of prepared solvents were confirmed as desirable properties for their application. Extraction parameters were optimized, and chosen solvents were applied. The results showed satisfactory extraction efficiencies in simple and fast procedures, followed by low solvent consumption. The best results (98%) were obtained by the thymol-based solvent, thymol–decanoic acid (Thy-DecA) 1:1, followed by L-menthol-based solvents: menthol–octanoic acid (Men-OctA) 1:1 with 97% and menthol–decanoic acid (Men-DecA) 1:1 with 94.3% efficiency.

Inflammatory bowel disease (IBD), encompassing Crohn's disease (CD) and ulcerative colitis (UC), necessitates effective management strategies. This study aims to evaluate the real-world efficacy of vedolizumab, a newer biological therapy, in treating IBD in Bosnia and Herzegovina. A retrospective observational study was conducted across 6 medical centers, involving 139 IBD patients, 76 with UC and 63 with CD. Patients were assessed for clinical remission and other outcomes at the 26-week mark post vedolizumab treatment initiation. At 26 weeks, clinical remission was achieved in 82.9% of UC patients and 85.7% of CD patients. Mucosal healing was observed in 38.1% of CD patients. The efficacy of vedolizumab did not significantly differ based on prior anti-tumor necrosis factor (TNF) exposure. Notably, the clinical scoring tools for predicting vedolizumab response showed limited applicability in this cohort. Vedolizumab demonstrated high efficacy in treating both UC and CD in a real-world settings in Bosnia and Herzegovina, underscoring its potential as a significant therapeutic option in IBD management.

Background: The accurate delineation of ablation zones (AZs) is crucial for assessing radiofrequency ablation (RFA) therapy’s efficacy. Manual measurement, the current standard, is subject to variability and potential inaccuracies. Aim: This study aims to assess the effectiveness of Artificial Intelligence (AI) in automating AZ measurements in ultrasound images and compare its accuracy with manual measurements in ultrasound images. Methods: An in vitro study was conducted using chicken breast and liver samples subjected to bipolar RFA. Ultrasound images were captured every 15 s, with the AI model Mask2Former trained for AZ segmentation. The measurements were compared across all methods, focusing on short-axis (SA) metrics. Results: We performed 308 RFA procedures, generating 7275 ultrasound images across liver and chicken breast tissues. Manual and AI measurement comparisons for ablation zone diameters revealed no significant differences, with correlation coefficients exceeding 0.96 in both tissues (p < 0.001). Bland–Altman plots and a Deming regression analysis demonstrated a very close alignment between AI predictions and manual measurements, with the average difference between the two methods being −0.259 and −0.243 mm, for bovine liver and chicken breast tissue, respectively. Conclusion: The study validates the Mask2Former model as a promising tool for automating AZ measurement in RFA research, offering a significant step towards reducing manual measurement variability.

Oncologic treatment has recently undergone substantial therapeutic paradigm shifts, from classical tumor-specific and biomarker-agnostic approaches to more molecular, biomarker-specific, and tumor-agnostic. Tumor-type (histology) agnostic drugs work across cancer types and present a novel shift in precision oncology. Compared with traditional cancer therapies, this novel approach implies molecularly informed treatment strategies and enables targeted treatment regardless of tumor histology (type). Such drugs are usually utilized in small clinical cohorts with diverse tumor types sharing a common genomic event (molecular biomarker). One of the key elements of this approach is the presence of a common biomarker across many tumor types. Biomarker predicts response to the targeted drugs, as well as deciphers potential resistance mechanisms. Read more in the PDF.

Building on previous work, this paper extends the modeling of political structures from simplicial complexes to hypergraphs. This allows the analysis of more complex political dynamics where agents who are willing to form coalitions contain subsets that would not necessarily form coalitions themselves. We extend topological constructions such as wedge, cone, and collapse from simplicial complexes to hypergraphs and use them to study mergers, mediators, and power delegation in political structures. Concepts such as agent viability and system stability are generalized to the hypergraph context, alongside the introduction of the notion of local viability. Additionally, we use embedded homology of hypergraphs to analyze power concentration within political systems. Along the way, we introduce some new notions within the hypergraph framework that are of independent interest.

This Letter reports the device and material investigations of enhancement-mode p-GaN-gate AlGaN/GaN high electron mobility transistors (HEMTs) for Venus exploration and other harsh environment applications. The GaN transistor in this work was subjected to prolonged exposure (11 days) in a simulated Venus environment (460 °C, 94 bar, complete chemical environment including CO2/N2/SO2). The mechanisms affecting the transistor performance and structural integrity in harsh environment were analyzed using a variety of experimental, simulation, and modeling techniques, including in situ electrical measurement (e.g., burn-in) and advanced microscopy (e.g., structural deformation). Through transistor, Transmission Line Method (TLM), and Hall-effect measurements vs temperature, it is revealed that the mobility decrease is the primary cause of reduction of on-state performance of this GaN transistor at high temperature. Material analysis of the device under test (DUT) confirmed the absence of foreign elements from the Venus atmosphere. No inter-diffusion of the elements (including the gate metal) was observed. The insights of this work are broadly applicable to the future design, fabrication, and deployment of robust III-N devices for harsh environment operation.

Background: A subset of developmental disorders (DD) is characterized by disease-specific genome-wide methylation changes. These episignatures inform about underlying pathogenic mechanisms and can be used to assess the pathogenicity of genomic variants as well as confirm clinical diagnoses. Currently, episignature detection requires the use of indirect methylation profiling microarrays. We hypothesized that long-read whole genome sequencing would not only enable the detection of single nucleotide variants and structural variants but also episignatures. Methods: Genome-wide nanopore sequencing was performed in forty controls and twenty patients with confirmed or suspected episignature-associated DD, representing thirteen distinct diseases. Following variant and methylome calling, hierarchical clustering and dimensional reduction were used to determine the compatibility with microarray-based episignatures. Subsequently, we developed a support vector machine for each DD. Results: Nanopore sequencing based methylome patterns were concordant with microarray-based episignatures. Our classifier identified episignatures in 17/20 disease samples and none in the control samples. The remaining three patient samples were classified as controls by both our classifier and a commercial microarray assay. In addition, we identified all underlying pathogenic single nucleotide and structural variants and showed haplotype-aware skewed X-inactivation evaluation directs clinical interpretation. Conclusion: This proof-of-concept study demonstrates nanopore sequencing enables concurrent haplotyped genomic and epigenomic analyses.

This paper investigates an autonomous discrete-time glycolytic oscillator model with a unique positive equilibrium point which exhibits chaos in the sense of Li–Yorke in a certain region of the parameters. We use Marotto’s theorem to prove the existence of chaos by finding a snap-back repeller. The illustration of the results is presented by using numerical simulations.

Aim: This study aimed to identify and analyze the top 100 most cited digital health and mobile health (m-health) publications. It could aid researchers in the identification of promising new research avenues, additionally supporting the establishment of international scientific collaboration between interdisciplinary research groups with demonstrated achievements in the area of interest. Methods: On 30th August, 2023, the Web of Science Core Collection (WOSCC) electronic database was queried to identify the top 100 most cited digital health papers with a comprehensive search string. From the initial search, 106 papers were identified. After screening for relevance, six papers were excluded, resulting in the final list of the top 100 papers. The basic bibliographic data was directly extracted from WOSCC using its “Analyze” and “Create Citation Report” functions. The complete records of the top 100 papers were downloaded and imported into a bibliometric software called VOSviewer (version 1.6.19) to generate an author keyword map and author collaboration map. Results: The top 100 papers on digital health received a total of 49,653 citations. Over half of them (n = 55) were published during 2013–2017. Among these 100 papers, 59 were original articles, 36 were reviews, 4 were editorial materials, and 1 was a proceeding paper. All papers were written in English. The University of London and the University of California system were the most represented affiliations. The USA and the UK were the most represented countries. The Journal of Medical Internet Research was the most represented journal. Several diseases and health conditions were identified as a focus of these works, including anxiety, depression, diabetes mellitus, cardiovascular diseases, and coronavirus disease 2019 (COVID-19). Conclusions: The findings underscore key areas of focus in the field and prominent contributors, providing a roadmap for future research in digital and m-health.

Placing wind turbines within large migration flyways, such as the North Sea basin, can contribute to the decline of vulnerable migratory bird populations by increasing mortality through collisions. Curtailment of wind turbines limited to short periods with intense migration can minimize these negative impacts, and near‐term bird migration forecasts can inform such decisions. Although near‐term forecasts are usually created with long‐term datasets, the pace of environmental alteration due to wind energy calls for the urgent development of conservation measures that rely on existing data, even when it does not have long temporal coverage. Here, we use 5 years of tracking bird radar data collected off the western Dutch coast, weather and phenological variables to develop seasonal near‐term forecasts of low‐altitude nocturnal bird migration over the southern North Sea. Overall, the models explained 71% of the variance and correctly predicted migration intensity above or below a threshold for intense hourly migration in more than 80% of hours in both seasons. However, the percentage of correctly predicted intense migration hours (top 5% of hours with the most intense migration) was low, likely due to the short‐term dataset and their rare occurrence. We, therefore, advise careful consideration of a curtailment threshold to achieve optimal results. Synthesis and applications: Near‐term forecasts of migration fluxes evaluated against measurements can be used to define curtailment thresholds for offshore wind energy. We show that to minimize collision risk for 50% of migrants, if predicted correctly, curtailments should be applied during 18 h in spring and 26 in autumn in the focal year of model assessments, resulting in an estimated annual wind energy loss of 0.12%. Drawing from the Dutch curtailment framework, which pioneered the ‘international first’ offshore curtailment, we argue that using forecasts developed from limited temporal datasets alongside expert insight and data‐driven policies can expedite conservation efforts in a rapidly changing world. This approach is particularly valuable in light of increasing interannual variability in weather conditions.