Search Results (8,454)

Background and Objectives: The worldwide incidence of renal cell carcinoma (RCC) rose by 22% between 2012 and 2022. In Australia, RCC accounted for 2.8% of all cancer diagnoses and contributing to 1.8% of cancer-related deaths. Identification of RCC biomarkers may aid in diagnosis and management. Methods: A systematic review of immunohistochemical markers of RCC studies published between 1990 and 2019 was undertaken to select candidate biomarkers of RCC. Immunohistochemical staining of 73 clear cell RCC tumors and paired normal tissue was undertaken using selected markers. Semi-quantitative and quantitative analysis of staining intensity between paired samples was undertaken to evaluate utility as potential biomarkers, using Chi-square tests and paired t-tests for analysis. As an exploratory analysis, staining intensity was also compared on clinical/demographic variables using linear and logistic regression. Results: There were 123 candidate biomarkers identified in 91 studies. Four candidate markers were selected for further investigation: aminopeptidase A (APA)/cluster of differentiation (CD)249, aminopeptidase N (APN)/CD13, gamma-glutamyl transferase (GGT), and neuron-specific enolase (NSE). APA, GGT, and APN all demonstrated reduced staining intensity in the tumor compared with normal tissue (p < 0.001 for all). NSE demonstrated a statistically significant increase in expression in tumor compared with normal tissue (p < 0.001), and this was more pronounced in patients aged >60 years (p = 0.038). Conclusions: The utility of APA, APN, and GGT as diagnostic biomarkers in clear cell RCC is limited. NSE may have some role as a biomarker for clear cell RCC, particularly among older patients; however, further investigation is required. Full article

Background/Objectives: Understanding the stabilization mechanisms of amino acid conformations in different solvent environments is crucial for elucidating biomolecular interactions and crystallization processes. This study presents a comprehensive computational investigation of glycine, the simplest amino acid, in both its canonical and zwitterionic forms when interacting with dimethyl sulfoxide (DMSO) molecules. Methods: Using density functional theory (DFT) calculations at the B3LYP/6-311++G(d,p) level with empirical dispersion corrections, we examined the conformational landscape of glycine–DMSO clusters with one and two DMSO molecules, as well as implicit solvent calculations, and compared them with analogous water clusters. Results: Our results demonstrate that while a single water molecule is insufficient to stabilize the zwitterionic form of glycine, one DMSO molecule successfully stabilizes this form through specific interactions between the S=O and the methyl groups of DMSO and the NH₃⁺ and the oxoanion group of zwitterionic glycine, respectively. Topological analysis of the electron density using QTAIM and NCI methods reveals the nature of these interactions. When comparing the relative stability between canonical and zwitterionic forms, we found that two DMSO molecules significantly reduce the energy gap to approximately 12 kJ mol⁻¹, suggesting that increasing DMSO coordination could potentially invert this stability. Implicit solvent calculations indicate that in pure DMSO medium, the zwitterionic form becomes more stable below 150 K, while remaining less stable at room temperature, contrasting with aqueous environments where the zwitterionic form predominates. Conclusions: These findings provide valuable insights into DMSO’s unique role in biomolecular stabilization and have implications for protein crystallization protocols where DMSO is commonly used as a co-solvent. Full article

Cone Penetration Tests with pore pressure measurements (CPTu) are widely used in geotechnical site investigations due to their high-resolution profiling capabilities. However, traditional interpretation methods—such as the Soil Behavior Type Index ($I_c$)—often fail to capture the internal heterogeneity typical of mining tailings deposits. This study presents a machine learning-based approach to enhance stratigraphic interpretation from CPTu data. Four unsupervised clustering algorithms—k-means, DBSCAN, MeanShift, and Affinity Propagation—were evaluated using a dataset of 12 CPTu soundings collected over a 19-year period from an iron tailings dam in Brazil. Clustering performance was assessed through visual inspection, stratigraphic consistency, and comparison with $I_c$-based profiles. k-means and MeanShift produced the most consistent stratigraphic segmentation, clearly delineating depositional layers, consolidated zones, and transitions linked to dam raising. In contrast, DBSCAN and Affinity Propagation either over-fragmented or failed to identify meaningful structures. The results demonstrate that clustering methods can reveal behavioral trends not detected by $I_c$ alone, offering a complementary perspective for understanding depositional and mechanical evolution in tailings. Integrating clustering outputs with conventional geotechnical indices improves the interpretability of CPTu profiles, supporting more informed geomechanical modeling, dam monitoring, and design. The approach provides a replicable methodology for data-rich environments with high spatial and temporal variability. Full article

Voltage-gated Ca²⁺ channels (VGCCs) are regulated by four CaVβ subunits (CaVβ1–CaVβ4), each showing specific expression patterns in excitable cells. While primarily known for regulating VGCC function, CaVβ proteins also have channel-independent roles, including gene expression modulation. Among these, CaVβ1 is expressed in skeletal muscle as multiple isoforms. The adult isoform, CaVβ1D, localizes at the triad and modulates CaV1 activity during Excitation–Contraction Coupling (ECC). In this study, we investigated the lesser-known embryonic/perinatal CaVβ1 isoforms and their roles in neuromuscular junction (NMJ) formation, maturation, and maintenance. We found that CaVβ1 isoform expression is developmentally regulated through differential promoter activation. Specifically, CaVβ1A is expressed in embryonic muscle and reactivated in denervated adult muscle, alongside the known CaVβ1E isoform. Nerve injury in adult muscle triggers a shift in promoter usage, resulting in re-expression of embryonic/perinatal Cacnb1A and Cacnb1E transcripts. Functional analyses using aneural agrin-induced AChR clustering on primary myotubes demonstrated that these isoforms contribute to NMJ formation. Additionally, their expression during early post-natal development is essential for NMJ maturation and long-term maintenance. These findings reveal previously unrecognized roles of CaVβ1 isoforms beyond VGCC regulation, highlighting their significance in neuromuscular system development and homeostasis. Full article

The successful deployment of sustainable building construction (SBC) is connected to sound knowledge sharing. Concerning SBC, knowledge sharing has been identified to directly and indirectly increase innovation, environmental performance, cost saving, regulatory compliance awareness and so on. The necessity of enhancing SBC practice globally has been emphasised by earlier research. Consequently, this study aims to investigate knowledge-sharing elements to enhance SBC in South Africa (SA). Utilising a questionnaire survey, this study elicited data from 281 professionals in the built environment. Data analysis was performed with “descriptive statistics”, the “Kruskal–Wallis H-test”, and “principal component analysis” to determine the principal knowledge-sharing features (KSFs). This study found that “creating public awareness of sustainable practices”, the “content of SBC training, raising awareness of green building products”, “SBC integration in professional certifications”, an “information hub or repository for sustainable construction”, and “mentoring younger professionals in sustainable practices” are the most critical KSFs for SBC deployment. These formed a central cluster, the Green Education Initiative and Eco-Awareness Alliance. The results achieved a reliability test value of 0.956. It was concluded that to embrace the full adoption of SBC, corporate involvement is critical, and all stakeholders must embrace the sustainability paradigm. It is recommended that the principal knowledge-sharing features revealed in this study should be carefully considered to help construction stakeholders in fostering knowledge sharing for a sustainable built environment. Full article

The rhythm of epileptiform activity occurs in various brain injuries (ischemia, stroke, concussion, mechanical damage, AD, PD). The epileptiform rhythm is accompanied by periodic Ca²⁺ pulses, which are necessary for the neurotransmitter release, the repair of damaged connections between neurons, and the growth of new projections. The duration and amplitude of these pulses depend on intracellular calcium-binding proteins. The effect of the synthetic fast calcium buffer BAPTA on the epileptiform activity of neurons induced by the GABA(A)-receptor inhibitor, bicuculline, was investigated in a 14-DIV rat hippocampal culture. In the epileptiform activity mode, neurons periodically synchronously generate action potential (AP) bursts in the form of paroxysmal depolarization shift (PDS) clusters and their corresponding high-amplitude Ca²⁺ pulses. Changes in the paroxysmal activity and Ca²⁺ pulses were recorded continuously for 10–11 min as BAPTA accumulated. It was shown that during BAPTA accumulation, transformation of neuronal patch activity occurs. Moreover, GABAergic and glutamatergic neurons respond differently to the presence of calcium buffer. Experiments were performed on two populations of neurons: a population of GABAergic neurons that responded selectively to ATPA, a calcium-permeable GluK1 kainate receptor agonist, and a population of glutamatergic neurons with a large amplitude of cluster depolarization (greater than −20 mV). These neurons made up the majority of neurons. In the population of GABAergic neurons, during BAPTA accumulation, the amplitude of PDS clusters decreases, which leads to a switch from the PDS mode to the classical burst mode with an increase in the electrical activity of the neuron. In glutamatergic neurons, the duration of PDS clusters decreased during BAPTA accumulation. However, the amplitude changed little. The data obtained showed that endogenous calcium-binding proteins play a significant role in switching the epileptiform rhythm to the recovery rhythm and perform a neuroprotective function by reducing the duration of impulses in excitatory neurons and the amplitude of impulses in inhibitory neurons. Full article

The growing concern over environmental sustainability has intensified the focus on consumers’ perceptions of eco-friendly food packaging, especially among younger generations. This study aims to investigate the attitudes, preferences, and barriers faced by Greek university students regarding sustainable food packaging, a demographic considered pivotal for driving future consumption trends. An online questionnaire assessing perceptions, preferences, and behaviours related to sustainable packaging was administered to students, with responses measured on a five-point Likert scale. Three hundred and sixty-four students took part in this survey, with the majority (60%) of them being female. Principal component analysis was employed to identify underlying factors influencing perceptions, and k-means cluster analysis revealed two consumer segments: “Innovatives”, including one hundred and ninety-eight participants (54%), who demonstrate strong environmental awareness and willingness to adopt sustainable behaviours, and “Sceptics”, including one hundred sixty-six participants (46%), who show moderate engagement and remain cautious in their choices. Convenience, affordability, and clear product communication emerged as significant factors shaping student preferences. The findings suggest that targeted educational campaigns and transparent information are essential to converting positive attitudes into consistent purchasing behaviours. This research provides valuable insights for policymakers and marketers looking to design effective sustainability strategies tailored to the student population. Full article

Climate change has a significant negative impact on agriculture and food production. This trend requires technological development and the adaptation of new technologies in both the grapevine production and winemaking sectors. High temperatures and heat accumulation during the growing season result in faster ripening and a higher sugar content, leading to a higher alcohol content during fermentation. The negative consequences are an imbalanced wine character and consumer reluctance, as lower alcoholic beverages are now in high demand. Over the last decade, several methods have been developed to handle this impact and reduce the alcohol content of wines. In this study, we used the MASTERMIND^® REMOVE membrane-based dealcoholization system to reduce the alcohol concentration in of Pinot gris wines from 12.02% v/v to 10.69% v/v and to investigate the effect on analytical parameters in three steps (0.5%, 1%, and 1.5% reductions) along the treatment. To evaluate the impact of the partial alcohol reduction and identify correlations between the wine chemical parameters, data were analyzed with ANOVA, PCA, multivariate linear regression and cluster analysis. The results showed that except for the extract, sugar content and proline content, the treatment had a significant effect on the chemical parameters. Both free and total SO₂ levels were significantly reduced as well as volatile acid, glycerol and succinic acid levels. It must be highlighted that some parameters were not differing significantly between the untreated and the final wine, while the change was statistically verified in the intermediate steps of the partial alcohol reduction. This was the case for example for n-Propanol, i-Amylalcohol, Acetaldehyde, and Ethyl acetate. The multivariate linear regression model explained 18.84% of the total variance, indicating a modest but meaningful relationship between the alcohol content and the investigated analytical parameters. Our results showed that even if the applied instrument significantly modified some of the wine chemical parameters, those changes would not influence significantly the wine sensory attributes. Full article

The Guinea Pig X Virus (GPXV), a newly identified gammaherpesvirus, provides an opportunity to study viral evolution and host–virus dynamics. This study characterizes the GPXV genome and investigates its phylogenetic relationships and divergence from related viruses through comparative genomic and phylogenetic analyses. Virus propagation was conducted in Vero cells, followed by genomic DNA extraction and pan-herpesvirus nested PCR. Sanger sequencing filled gaps in the initial genome assembly, and whole-genome sequencing was performed using the Illumina MiSeq platform. Phylogenetic analyses focused on ORF8 (glycoprotein B), ORF9 (DNA polymerase catalytic subunit), ORF50 (RTA: replication and transcription activator), and ORF73 (LANA: latency-associated nuclear antigen). Results showed that GPXV ORFs showed variable evolutionary relationships with other gammaherpesviruses, including divergence from primate-associated viruses and clustering with bovine and rodent viruses. In addition to phylogenetics, a comprehensive comparative analysis of protein-coding genes between GPXV and the previously described Guinea Pig Herpes-Like Virus (GPHLV) revealed divergence. Twenty-four non-ORF genomic features were unique to GPXV, while 62 shared ORFs exhibited low to high sequence divergence. These findings highlight GPXV’s distinct evolutionary trajectory and its potential role as a model for studying host-specific adaptations and gammaherpesvirus diversity. Full article

This article investigates the macroeconomic and labor market conditions that shape the adoption of artificial intelligence (AI) technologies among large firms in Europe. Based on panel data econometrics and supervised machine learning techniques, we estimate how public health spending, access to credit, export activity, gross capital formation, inflation, openness to trade, and labor market structure influence the share of firms that adopt at least one AI technology. The research covers all 28 EU members between 2018 and 2023. We employ a set of robustness checks using a combination of fixed-effects, random-effects, and dynamic panel data specifications supported by Clustering and supervised learning techniques. We find that AI adoption is linked to higher GDP per capita, healthcare spending, inflation, and openness to trade but lower levels of credit, exports, and capital formation. Labor markets with higher proportions of salaried work, service occupations, and self-employment are linked to AI diffusion, while unemployment and vulnerable work are detractors. Cluster analysis identifies groups of EU members with similar adoption patterns that are usually underpinned by stronger economic and institutional fundamentals. The results collectively suggest that AI diffusion is shaped not only by technological preparedness and capabilities to invest but by inclusive macroeconomic conditions and equitable labor institutions. Targeted policy measures can accelerate the equitable adoption of AI technologies within the European industrial economy. Full article

The advanced determination of the type (foreshock–aftershock–swarm) of an ongoing seismic cluster is quite challenging; only retrospective solutions have thus far been proposed. In the period of January–March 2025, a seismic cluster, recorded between Santorini volcano and Amorgos Island, South Aegean Sea, caused considerable social concern. A rapid increase in both the seismicity rate and the earthquake magnitudes was noted until the mainshock of M_L = 5.3 on 10 February; afterwards, activity gradually diminished. Fault-plane solutions indicated SW-NE normal faulting. The epicenters moved with a mean velocity of ~0.72 km/day from SW to NE up to the mainshock area at a distance of ~25 km. Crucial questions publicly emerged during the cluster. Was it a foreshock–aftershock activity or a swarm of possibly volcanic origin? We performed real-time discrimination of the cluster type based on a daily re-evaluation of the space–time–magnitude changes and their significance relative to background seismicity using earthquake statistics and the topological metric betweenness centrality. Our findings were periodically documented during the ongoing cluster starting from the fourth cluster day (2 February 2025), at which point we determined that it was a foreshock and not a case of seismic swarm. The third day after the M_L = 5.3 mainshock, a typical aftershock decay was detected. The observed foreshock properties favored a cascade mechanism, likely facilitated by non-volcanic material softening and the likely subdiffusion processes in a dense fault network. This mechanism was possibly combined with an aseismic nucleation process if transient geodetic deformation was present. No significant aftershock expansion towards the NE was noted, possibly due to the presence of a geometrical fault barrier east of the Anydros Ridge. The 2025 activity offered an excellent opportunity to investigate deciphering the type of ongoing seismicity cluster for real-time discrimination between foreshocks, aftershocks, and swarms. Full article

Ulcerative colitis (UC) is a chronic inflammatory bowel disease associated with disrupted lipid metabolism. This study aimed to uncover novel molecular subtypes and biomarkers by integrating sphingolipid metabolism-related genes (SMGs) with machine learning approaches. Using data from the GEO and GeneCards databases, 29 UC-related SMGs were identified. Consensus clustering was employed to define distinct molecular subtypes of UC, and a diagnostic model was developed through various machine learning algorithms. Further analyses—including functional enrichment, transcription factor prediction, single-cell localization, potential drug screening, molecular docking, and molecular dynamics simulations—were conducted to investigate the underlying mechanisms and therapeutic prospects of the identified genes in UC. The analysis revealed two molecular subtypes of UC: C1 (metabolically dysregulated) and C2 (immune-enriched). A diagnostic model based on three key genes demonstrated high accuracy in both the training and validation cohorts. Moreover, the transcription factor FOXA2 was predicted to regulate the expression of all three genes simultaneously. Notably, mebendazole and NVP-TAE226 emerged as promising therapeutic agents for UC. In conclusion, SMGs are integral to UC molecular subtyping and immune microenvironment modulation, presenting a novel framework for precision diagnosis and targeted treatment of UC. Full article

While there are studies on bicycle crashes, no study has investigated the spatial analysis of fatal and injury bicycle crashes in the state of Ohio. This study fills this gap in the literature by mapping and investigating the bicycle crash-prone areas in the state. It analyzes fatal and injury bicycle crashes from 2014 to 2023 by utilizing four exploratory spatial data analysis techniques: nearest neighbor index, global Moran’s I index, hotspot and cold spot analysis, and local Moran’s I index at the state, county, census tract, and block group levels. Results vary slightly across techniques and spatial scales but consistently show that bicycle crash locations are clustered statewide, particularly in the state’s major metropolitan areas such as Columbus, Cincinnati, Toledo, Cleveland, and Akron. These urban centers have emerged as hotspots, indicating a higher vulnerability to bicycle crashes. While global Moran’s I analysis at the county level does not reveal significant spatial autocorrelation, a strong positive autocorrelation is observed at both the census tract (p = 0.01) and block group (p = 0.00) levels, indicating significant high clustering, signifying that finer geographical units yield more robust results. Identifying specific hotspots and vulnerable areas provides valuable insights for policymakers and urban planners to implement effective safety measures and improve conditions for non-motorized road users in Ohio. The study highlights the need for targeted mitigation strategies in high-risk areas, including comprehensive safety measures, infrastructure improvements, policy changes, and community-focused initiatives to reduce crash risk and create safer environments for cyclists throughout Ohio’s urban fabric. Full article

The Sichuan Basin is a natural-gas-exploiting area with intensive agriculture activities. However, the spatial and temporal distribution of atmospheric methane concentration and the relationships with intensive agriculture and natural gas extraction activities are not well investigated. In this study, a long-term (2003–2021) dataset of column-averaged dry-air mole fraction of methane (XCH₄) over the Sichuan Basin and adjacent regions was built by integrating multi-satellite remote sensing data (SCIAMACHY, GOSAT, Sentinel-5P), which was calibrated using ground station data. The results show a strong correlation and consistency (R = 0.88) between the ground station and satellite observations. The atmospheric CH₄ concentration of the Sichuan Basin showed an overall higher level (around 20 ppb) than that of the whole of China and an increasing trend in the rates, from around 2.27 ppb to 10.44 ppb per year between 2003 and 2021. The atmospheric CH₄ concentration of the Sichuan Basin also exhibits clear seasonal changes (higher in the summer and autumn and lower in the winter and spring) with a clustered geographical distribution. Agricultural activities and natural gas extraction contribute significantly to atmospheric methane concentrations in the study area, which should be considered in carbon emission management. This study provides an effective way to investigate the spatiotemporal distribution of atmospheric CH₄ concentration and related factors at a regional scale with natural and human influences using multi-source satellite remote sensing data. Full article

Tianshanhong (TSH), black tea products originating from the Ningde Tianshan Mountain, has gained significant recognition in the market. However, the chemical characteristics contributing to the flavor of TSH have not yet been reported. To systematically investigate the non-volatile and volatile compounds in TSH, four grades of TSH were evaluated using national standard sensory methods, revealing that overall quality improved with higher grades. Based on the detection of ultra-performance liquid chromatography–mass spectrometry (UPLC-MS), the content of ester-type catechins was relatively high and decreased with lower grades. A total of 19 amino acids (AAs) were clustered, among them, three amino acids, L-Theanine (L-Thea), Arg, and GABA, showed highly significant correlations with the refreshing taste of TSH. Notably, the content of Arg had the highest correlation with TSH grade, with a coefficient of 0.976 (p < 0.01). According to gas chromatography mass spectrometry (GC-MS) analysis, a total of 861 kinds of volatile compounds were detected, with 282 identified and aroma-active compounds across grades selected using the PLS model. Methyl salicylate and geraniol were particularly notable, showing strong correlations with TSH grades at 0.975 and 0.987 (p < 0.01), respectively. Our findings show that non-volatile and volatile compounds can rationally grade TSH and help understand its flavor quality. Full article