Search Results (865)

Background: Core laboratory chemistry analyzers typically use plasma and serum samples, while blood gas instruments use whole blood for electrolyte and metabolite tests. Due to high costs to back up the core lab chemistry analyzers, especially in the remote small community hospitals, we have verified the interchangeability of serum/plasma electrolytes and metabolites on blood gas instruments (GEM4000 and Radiometer ABL90) vs. chemistry analyzers. In this study, we sought to extend the investigation to another blood gas device—Radiometer ABL837. Methods: One plasma separator tube and one serum separator tube were drawn from 20 apparently healthy individuals and outpatients and 20 intensive care unit patients. All the samples were run on Roche Cobas8000, and then were run on three Radiometer ABL837 analyzers for sodium (Na⁺), potassium (K⁺), chloride (Cl⁻), glucose, lactate (plasma only), and creatinine parameters. Paired measurements between the ABL837 and Cobas8000 were compared, and their difference were assessed for statistical and clinical significance. Results: ABL837 demonstrated statistical significance (p < 0.05) vs. Cobas8000 on all the plasma and serum parameters. However, no parameter differences were found when comparing the plasma/serum results on ABL837 to those on Cobas8000, indicating that none were clinically significant. ABL837 also demonstrated good–excellent correlations with Cobas8000 on all the parameters. Conclusions: When comparing metabolite and electrolyte values with plasma and serum sample types, the ABL837 blood gas instruments and Cobas 8000 chemistry analyzer are interchangeable. These data proves that ABL837 can be used as a backup for a chemistry analyzer in measuring plasma and serum electrolyte and metabolite concentrations. Full article

Thermodynamic simulations of fluid–rock interactions provide valuable insights into mineral deposit formation mechanisms. This study investigates the Pulang porphyry Cu-Au deposit in the Sanjiang Tethys Orogen, employing both Gibbs energy minimization (GEM) and the Law of mass action (LMA) method to understand alteration overprinting and metal precipitation. The modeling results suggest that the ore-forming fluid related to potassic alteration was initially oxidized (ΔFMQ = +3.54~+3.26) with a near-neutral pH (pH = 5.0~7.0). Continued fluid–rock interactions, combined with the input of reduced groundwater, resulted in a decrease in both pH (4.8~6.1) and redox potential (ΔFMQ~+1), leading to the precipitation of propylitic alteration minerals and pyrrhotite. As temperature further decreased, fluids associated with phyllic alteration showed a slight increase in pH (5.8~6.0) and redox potential (ΔFMQ = +2). The intense superposition of propylitic and phyllic alteration on the potassic alteration zone is attributed to the rapid temperature decline in the magmatic–hydrothermal system, triggering fluid collapse and reflux. Mo, mainly transported as HMoO₄⁻ and MoO₄⁻², precipitated in the high-temperature range; Cu, carried primarily by CuCl complexes (CuCl₄⁻³, CuCl₂⁻, CuCl), precipitated over intermediate to high temperatures; and Au, transported as Au-S complexes (Au(HS)₂⁻, AuHS), precipitated from intermediate to low temperatures. This study demonstrates that fluid–rock interactions alone can account for the observed sequence of alteration and mineralization in porphyry systems. Full article

In recent years, amino-gem-bisphosphonic acids and their esters have been considered a family of compounds of great chemical and pharmacological interest due to their important biological properties and their value as key synthons in the synthesis of more complex molecules with biological interest. This explains why several research groups are interested in developing new methods for the preparation of these compounds. Therefore, we would like to report here a summary of the synthetic strategies published in the last fifteen years for the synthesis of acyclic and heterocyclic α-, β- and γ-amino-gem-bisphosphonates, as well as their application in the preparation of selected compounds of chemical and pharmacological interest. This information can be of general knowledge to researchers working in this area, as it provides the starting point for new methods and applications of these compounds. Full article

Identifying correspondences of road segments in different road networks, namely road-network matching, is an essential task for road network-centric data processing such as data integration of road networks and data quality assessment of crowd-sourced road networks. Traditional road-network matching usually relies on feature engineering and parameter selection of the geometry and topology of road networks for similarity measurement, resulting in poor performance when dealing with dense and irregular road network structures. Recent development of graph neural networks (GNNs) has demonstrated unsupervised modeling power on road network data, which learn the embedded vector representation of road networks through spatial feature induction and topology-based neighbor aggregation. However, weighting spatial information on the node feature alone fails to give full play to the expressive power of GNNs. To this end, this paper proposes a Spatial Pattern-aware Graph EMbedding learning method for road-network matching, named SP-GEM, which explores the idea of spatially-explicit modeling by identifying spatial patterns in neighbor aggregation. Firstly, a road graph is constructed from the road network data, and geometric, topological features are extracted as node features of the road graph. Then, four spatial patterns, including grid, high branching degree, irregular grid, and circuitous, are modelled in a sector-based road neighborhood for road embedding. Finally, the similarity of road embedding is used to find data correspondences between road networks. We conduct an algorithmic accuracy test to verify the effectiveness of SP-GEM on OSM and Tele Atlas data. The algorithmic accuracy experiments show that SP-GEM improves the matching accuracy and recall by at least 6.7% and 10.2% among the baselines, with high matching success rate (>70%), and improves the matching accuracy and recall by at least 17.7% and 17.0%, compared to the baseline GNNs, without spatially-explicit modeling. Further embedding analysis also verifies the effectiveness of the induction of spatial patterns. This study not only provides an effective and practical algorithm for road-network matching, but also serves as a test bed in exploring the role of spatially-explicit modeling in GNN-based road network modeling. The experimental performances of SP-GEM illuminate the path to develop GeoEmbedding services for geospatial applications. Full article

In modern multi-core processors, memory request latency critically constrains overall performance. Prefetching, a promising technique, mitigates memory access latency by pre-loading data into faster cache structures. However, existing core-side prefetchers lack visibility to the DRAM state and may issue suboptimal requests, while conventional memory-side prefetchers often default to simple next-line policies that miss complex access patterns. We propose a comprehensive memory-side prefetch optimization scheme, which includes a prefetcher that utilizes advanced prefetching algorithms and an optimization module. Our prefetcher is capable of detecting more complex memory access patterns, thereby improving both prefetch accuracy and coverage. Additionally, considering the characteristics of DRAM memory access, the optimization module minimizes the negative impact of prefetch requests on DRAM by enhancing coordination with memory operations. Additionally, our prefetcher works in synergy with core-side prefetchers to deliver superior overall performance. Simulation results using Gem5 and SPEC CPU2017 workloads show that our approach delivers an average performance improvement of 10.5% and reduces memory access latency by 61%. Our prefetcher also operates in conjunction with core-side prefetchers to form a multi-level prefetching hierarchy, enabling further performance gains through coordinated and complementary prefetching strategies. Full article

Background/Objective: Cerivastatin (Cer), a cholesterol-lowering statin, was withdrawn from the market due to fatal cases of rhabdomyolysis, particularly when co-administered with gemfibrozil (Gem), a strong CYP2C8 inhibitor. However, the pharmacokinetic (PK) mechanisms underlying these adverse events remain unclear. This study investigates the impact of drug–drug interactions (DDIs) involving Gem and itraconazole (Itr), a potent CYP3A4 inhibitor, on plasma concentrations of Cer and its major metabolites—M23, M1, and cerivastatin lactone (Cer-L)—with a focus on the risk of excessive Cer-L accumulation. Methods: We applied a newly developed Metabolite-Linked Model that simultaneously characterizes parent drug and metabolite kinetics by estimating metabolite formation fractions (f_M) and elimination rate constants (K_eM). The model was calibrated using observed DDI data from Cer + Gem and Cer + Itr scenarios and then used to predict outcomes in an untested Cer + Gem + Itr combination. Results: The model accurately reproduced observed metabolite profiles in single-inhibitor DDIs. Predicted AUCR values for Cer-L were 4.2 (Cer + Gem) and 2.1 (Cer + Itr), with reduced K_eM indicating CYP2C8 and CYP3A4 as primary elimination pathways. In the dual-inhibitor scenario, Cer-L AUCR reached ~70—far exceeding that of the parent drug—suggesting severe clearance impairment and toxic accumulation. Conclusions: Dual inhibition of CYP2C8 and CYP3A4 may cause dangerously elevated Cer-L levels, contributing to Cer-associated rhabdomyolysis. This modeling approach offers a powerful framework for evaluating DDI risks involving active or toxic metabolites, supporting safer drug development and regulatory assessment. Full article

The main goal of this study is to present future changes in various precipitation indices at a kilometer-scale resolution for Bulgaria on an annual and seasonal basis. Numerical simulations were conducted using the Non-Hydrostatic Regional Climate Model version 4 (RegCM4-NH) following the Coordinated Regional Climate Downscaling Experiment Flagship Pilot Study protocol for three 10-year periods (1995–2004, 2041–2050, and 2090–2099), with horizontal grid resolutions of 15 km and 3 km, on the petascale supercomputer HPC Discoverer at Sofia Tech Park. Data from the Hadley Centre Global Environment Model version 2 (HadGEM2-ES), based on the Representative Concentration Pathway 8.5 (RCP8.5) scenario, were used as boundary conditions for the regional climate model (RCM) simulations, which were subsequently downscaled to the kilometer-scale (3 km) simulations using a one-way nesting approach. High-resolution model data were compared with high-resolution observational datasets as well as lower-resolution (15 km) data. Future changes in precipitation indices were analyzed on both annual and seasonal scales, including mean daily and hourly precipitation, the frequency and intensity of wet days (>1 mm/day) and wet hours (>0.1 mm/hour), extreme daily precipitation (99th percentile, p99), and extreme hourly precipitation (99.9th percentile, p99.9) for both future periods. Additionally, changes in near-surface (2 m) temperature and surface snow amount were also presented. There is no substantial difference in projected temperature change between the resolutions. A positive trend in annual mean precipitation is expected in the near future. Extreme precipitation (p99 and p99.9) is projected to increase in spring and winter, accompanied by a rise in daily and hourly precipitation intensity across both future periods. An increase in surface snow amount is observed in the central Danubian Plain, Thracian Lowland, and parts of the Rila and Pirin mountains for the near-future period. However, surface snow amount is expected to decrease by the end of the century. Full article

Pancreatic cancer is the third leading cause of cancer-related death in the US. First-line chemotherapy regimens for pancreatic ductal adenocarcinoma (PDAC) include FOLFIRINOX or gemcitabine (Gem) with or without paclitaxel (Ptx); however, 5-year survival with these regimens remains poor. Previous work has demonstrated protein arginine methyltransferase 5 (PRMT5) to be a promising therapeutic target in combination with Gem for the treatment of PDAC; however, these findings have yet to be confirmed in relevant preclinical models of PDAC. To test the possibility of PRMT5 as a viable therapeutic target, clinically relevant orthotopic and metastatic patient-derived xenograft (PDX) mouse models of PDAC growth were utilized to evaluate the effect of PRMT5 knockout (KO) or pharmacologic inhibition on treatment with Gem alone or Gem with Ptx. Primary endpoints included tumor volume, tumor weight, or metastatic tumor burden as appropriate. The results showed that Gem-treated PRMT5 KO tumors exhibited decreased growth and were smaller in size compared to Gem-treated wild-type (WT) tumors. Similarly, the Gem-treated PRMT5 KO metastatic burden was lower than the Gem-treated WT metastatic burden. The addition of a PRMT5 pharmacologic inhibitor to Gem and Ptx therapy resulted in a lower final tumor weight and fewer metastatic tumors. The depletion of PRMT5 results in increased DNA damage in response to Gem and Ptx treatment. Thus, PRMT5 genetic depletion or inhibition in combination with Gem-based therapy improved the response in primary and metastatic PDAC in clinically relevant mouse models, suggesting that PRMT5 is a viable therapeutic target for combination therapy in PDAC. Full article

Mesenchymal stem cells (MSCs) have recently shown great promise as potential anticancer drug delivery carriers. MSCs exhibit tropism to inflammatory sites, such as tumor beds, and resistance to chemotherapeutics. The aim of this study was to examine the efficacy of gemcitabine (GEM) conjugated with flurbiprofen (FLU) as a potential agent enhancing the GEM cytotoxic effect. Pancreatic cancer cell lines (PCCs), including PANC-1, AsPC-1, and BxPC-3, were studied meticulously. Moreover, the usefulness of bone-marrow-derived mesenchymal stem cells (BM-MSCs) treated with GEM and FLU, and the conditioned media from above these cells (CM) as elements supporting the in vitro action of GEM, inducing apoptosis, necrosis, and inhibiting the cell cycle, was tested. The results showed that CM-GEM exhibited higher cytotoxicity towards the selected PCCs compared to GEM alone. Furthermore, the obtained data revealed lower sensitivity of these cells to treatment, which promotes the utilization of BM-MSCs as potential drug carriers. Based on the presented findings, it seems that applying FLU in the antiproliferative effect of GEM might be regarded as an effective strategy in the therapy of pancreatic cancer, especially in the inhibition of proliferation and induction of cancer cell death. Full article

Increasing concern over climate change has made Carbon Capture and Storage (CCS) an important tool. Operators use deep geologic reservoirs as a form of favorable geological storage for long-term CO₂ sequestration. However, the success of CCS hinges on the integrity of wells penetrating these formations, particularly legacy wells, which often exhibit significant uncertainties regarding cement tops in the annular space between the casing and formation, especially around or below the primary seal. Misalignment of cement plugs with the primary seal increases the risk of CO₂ migrating beyond the seal, potentially creating pathways for fluid flow into upper formations, including underground sources of drinking water (USDW). These wells may not be leaking but might fail to meet the legal requirements of some federal and state agencies such as the Environmental Protection Agency (EPA), Railroad Commission of Texas (RRC), California CalGEM, and Pennsylvania DEP. This review evaluates the impact of CO₂ exposure on cement and casing integrity including the fluid transport mechanisms, fracture behaviors, and operational stresses such as cyclic loading. Findings revealed that slow fluid circulation and confining pressure, primarily from overburden stress, promote self-sealing through mineral precipitation and elastic crack closure, enhancing well integrity. Sustained casing pressure can be a good indicator of well integrity status. While full-physics models provide accurate leakage prediction, surrogate models offer faster results as risk assessment tools. Comprehensive data collection on wellbore conditions, cement and casing properties, and environmental factors is essential to enhance predictive models, refine risk assessments, and develop effective remediation strategies for the long-term success of CCS projects. Full article

Background/Objectives: Drug resistance and severe side effects caused by gemcitabine (Gem) and cisplatin (CDDP) are common. This study aimed to investigate the combined effects of CU4c and Gem or CDDP on lung cancer cells in vitro and in nude mouse xenograft models. Methods: Antiproliferative activity and drug interaction were evaluated using MTT and Chou–Talalay methods, respectively. Apoptosis induction and cell cycle arrest were analyzed by flow cytometry. The expression levels of proteins were evaluated by Western blot analysis. The HDAC-inhibitory activity of CU4c was confirmed in vitro, in silico, and in A549 cells. Results: CU4c inhibited the proliferation of A549 cells in a dose- and time-dependent manner but had little effect on the growth of noncancerous Vero cells. CU4c synergistically enhanced the antiproliferative activities of CDDP (at 24 h) and Gem (at 48 and 72 h) against A549 cells. Combined CU4c and CDDP notably inhibited A549 proliferation by triggering cell cycle arrest at S and G2/M phases at 24 h with elevated levels of p21 and p53 proteins. Combined CU4c and Gem induced cell cycle arrest at both the S and G2/M phases at 48 h via upregulating the expression of the p21 protein. CU4c enhanced the apoptotic effects of CDDP and Gem by increasing the Bax/Bcl-2 ratio, pERK1/2, and Ac-H3 levels. Combined CU4c and Gem significantly reduced tumor growth while minimizing visceral organ damage in animal study. Conclusions: These results suggest that CU4c enhances the anticancer activity of CDDP and Gem and reduces the toxicity of Gem in animal studies. Full article

Background: Correct assessment of resting metabolic rate (RMR) is fundamental for estimating total energy expenditure in both clinical nutrition and sports sciences research. Various methods have been proposed for RMR determination, including predictive equations, isotopic dilution techniques, and indirect calorimetry. Over the past two decades, portable gas analyzers have emerged as promising alternatives, offering more accessible and cost-effective solutions for metabolic assessment. However, evidence regarding their validity remains inconsistent, particularly across diverse populations and varying metabolic assessment protocols. Methods: This systematic review was conducted in May 2025 using the PubMed, Web of Science, and EBSCO databases, following the PRISMA-DTA guidelines, and included observational studies with the objective of examining the available evidence regarding the validity of portable gas analyzers to determine RMR in humans. The methodological quality of each study was assessed using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Results: From an initial pool of 230 studies, 16 met the eligibility criteria. The findings revealed notable variability in measurement validity among devices, mainly influenced by device model, population characteristics, and methodological factors. While portable analyzers such as FitMate and Q-NRG exhibited high validity, MedGem exhibited systematic biases, particularly in individuals with higher adiposity, leading to RMR overestimations. Conclusions: The main results demonstrated the critical need for rigorous validation of portable gas analyzers before their implementation in clinical and research settings to ensure their applicability across diverse populations and metabolic assessments. Full article

This study evaluated the prevalence of aflatoxin M1 (AFM1) in milk marketed in Tirana, Albania, along with dietary exposure and associated potential health risks. The World Health Organization has categorized Albania in cluster G02 of GEMS/FOOD, highlighting that milk is a staple in the Albanian diet, which points to a possible health risk. A total of 141 milk samples, comprising both Ultra-High Temperature (UHT) and pasteurized types, were collected from local markets in Tirana and analyzed from March 2023 to February 2024. The determination of AFM1 levels was carried out using High-Pressure Liquid Chromatography with a Fluorescence Detector (HPLC-FLD), a precise and dependable technique for identifying and measuring aflatoxins in food products. Aflatoxin M1 was found in 62.4% of the milk samples, with 26.2% surpassing the European Union’s maximum residue levels (MRL). The mean AFM1 concentrations were 58.8 ± 95.8 ng/kg, reaching a maximum level of 399.0 ng/kg. The Estimated Daily Intake (EDI) for various groups—toddlers, children, adolescents, and adults—was determined to be 2.161, 1.297, 0.519, and 0.370 ng/kg of body weight per day, respectively. The Hazard Index (HI), derived from the AFM1 exposure for four population groups, was 10.81 (toddlers), 6.48 (children), 2.59 (adolescents), and 1.85 (adults). The Margin of Exposure (MoE) was 1.85, 3.08, 7.71, and 10.81, respectively. The incidence of hepatocellular carcinoma (HCC) per 100,000 people in the four groups was 0.034, 0.021, 0.008, and 0.006, respectively. The study is the first comprehensive evaluation of AFM1 prevalence, highlighting the potential risks associated with milk consumption, as milk is a dietary staple in Albanian households. It addresses a critical public health concern regarding aflatoxin M1 (AFM1) contamination in milk consumed in Tirana, Albania, by highlighting the need for ongoing monitoring, regulatory measures, and educational outreach to enhance food safety and safeguard public health in Albania, as well as in other regions facing similar concerns. Full article

Calendula (Calendula officinalis L.), an edible and medicinal flower, faces challenges in yield uniformity and quality stability under open-field cultivation. Plant factories with artificial lighting (PFALs) are highly controlled systems that enable year-round production, efficient resource use, and consistent crop quality, making them promising for the cultivation for calendula. To optimize calendula cultivation in PFALs, this study investigates the effects of far-red (FR) light and nutrient solution modification on calendula growth, flowering, and nutrient use efficiency (NUE). The experiment was conducted using a dwarf calendula cultivar, ‘Orange Gem’. After transplanting, seedlings were subjected to a 2 × 3 factorial design comprising white (W) and end-of-day far-red (EOD-FR) lighting, in combination with three ammonium (NH₄⁺) levels (1/3×, 1×, and 3× of the Enshi formula). The EOD-FR lighting and the increase in the NH₄⁺ level resulted in taller plants and earlier first flower appearance. The shoot fresh and dry weight, the number of flowers, and the flower yield also increased under the higher NH₄⁺ concentration, regardless of the light treatment. The 3× NH₄⁺ treatment tended to enhance the nutrient absorption, leading to the highest nutrient use efficiency (NUE) based on the flower yield. These findings suggest that the application of EOD-FR lighting and high NH₄⁺ in nutrient solution can improve calendula productivity and resource-use efficiency in PFALs. Full article

Carbon Capture and Storage (CCS) is a critical strategy for reducing CO₂ emissions from hard-to-abate sectors. Reliable and efficient reservoir simulation tools are essential for supporting the safe and effective deployment of CCS projects. This study presents a twofold contribution to CCS modeling in saline aquifers: (1) the validation of the Black Oil Model (BoM) as a computationally efficient alternative to compositional simulators, and (2) a systematic assessment of the impact of grid resolution on plume prediction accuracy. The BoM was benchmarked against three commercial compositional simulators—Eclipse E300, CMG-GEM, and TNavigator. The comparison focused on key aspects of CO₂ storage operations, including plume evolution to assess containment and storage security, as well as injection safety and efficiency through pressure and saturation profile analysis, evaluated across both the injection and the post-closure monitoring phases. The BoM successfully reproduced plume extent and CO₂ saturation distributions, with mean deviations of 3% during injection, 5% during post-closure, and an overall average of 4% across the entire project duration. Additionally, simulation times were reduced by a factor of four compared to compositional models. These results confirm the BoM’s practical utility as a robust and efficient tool for CO₂ storage simulation. In parallel, the study investigated the influence of vertical and lateral grid resolutions/coarsening on the accuracy of CO₂ modeling. Seven models were developed and evaluated using a hybrid qualitative–quantitative framework, consistent with the BoM validation methodology. Vertical resolution was found to be particularly critical during the monitoring phase. While a 5 m resolution proved adequate during injection, deviations in plume shape and magnitude during post-injection increased to an average of 15% compared to a fine 2 m vertical resolution model, highlighting the necessity of fine vertical discretization (≤2 m) to capture gravity-driven plume dynamics during the monitoring phase. Conversely, lateral grid resolution had a stronger effect during the injection phase. A lateral cell size of 150 m was required for accurate plume prediction, with 200 m remaining moderately acceptable for early-phase assessment and prospect ranking, whereas coarser lateral grids led to significant underestimation of plume spread and dissolution extent. These findings demonstrate that the BoM, when combined with informed grid resolution strategies, enables accurate and computationally efficient simulation of CO₂ storage in saline aquifers. The study provides practical guidelines for fluid model selection and spatial discretization, offering critical input to subsurface experts involved in CCS project development, monitoring design, and regulatory compliance. Full article