Exact Sciences (United States)

Venoms contain toxins that are increasingly recognized as valuable sources of biologically active compounds. In this study, we examined the biochemical and biophysical properties of PLA₂, CRISP, and SVMP fractions isolated from Naja ashei venom with the detailed description of their interactions with cell membranes. By integrating these results with our previous analysis of the 3FTx fractions, we provide a broad and coherent overview of the most relevant protein components in N. ashei venom. Experiments were performed on two cancer cell lines with distinct membrane architectures: HL-60 (leukemia) and SK-N-SH (neuroblastoma). These lines differ particularly in membrane cholesterol content and in the saturation level of hydrophobic lipid parts. Our results enabled a comparative assessment of how each protein fraction modulates the mechanical and electrostatic properties of both model and native membranes. In agreement with predictions derived from model lipid systems, leukemia cell membranes were more susceptible to toxin-induced damage than neuroblastoma membranes, likely owing to their higher proportion of unsaturated lipids. Physicochemical analyses confirmed that the isolated PLA2, CRISP, and SVMP fractions alter key membrane parameters, including stiffness, elasticity, lipid-protein interactions, and the net charge of the polar headgroup region. Importantly, this work provides new insights into the membrane-level effects of SVMP and CRISP proteins, which have been less comprehensively studied compared with well characterized 3FTx and PLA₂ families. These results reveal distinct, cell membrane–dependent responses to N. ashei venom proteins and justify further basic research to better understand their action with cells.

Arterial hypertension remains a leading global risk factor for cardiovascular mortality. The traditional de novo drug discovery pipeline is hindered by exorbitant costs and prolonged developmental timelines. Drug repurposing-identifying new therapeutic indications for existing approved drugs-presents a highly efficient alternative. This methodological essay critically evaluates the implementation of completely open-source computational workflows for in silico drug repurposing against key hypertensive targets, such as the Angiotensin-Converting Enzyme (ACE) and the Angiotensin II Type 1 Receptor (AT1R). We systematically dissect a generalized Computer-Aided Drug Design (CADD) pipeline utilizing freely available software: RDKit for cheminformatics library preparation, AutoDock Vina for high-throughput virtual screening (HTVS), and GROMACS for molecular dynamics (MD) trajectory analysis. Consolidating literature data, we demonstrate how open-source automation frameworks (like KNIME and Python/Jupyter) democratize pharmacological research, enabling academic laboratories to execute complex polypharmacological screenings. Our analysis highlights that open-source pipelines can achieve hit-identification accuracies comparable to proprietary software, reducing computational screening costs by 100% while compressing the preclinical target validation timeline by over 60%.

This study presents the synthesis, characterization, and theoretical investigation of 5-benzoyl-2-(2,5-dimethylphenyl)-4-hydroxy-6-phenylpyridazin-3(2H)-one (BDP) to confirm its structural identity, properties, and potential applications in various fields. Experimental characterization techniques included FT-IR, Raman, UV-visible,1H, and 13C NMR spectroscopy. Theoretical studies were conducted using the Gaussian 09 software with Density Functional Theory (DFT), employing the B3LYP functional and 6–31G (d, p) basis sets. Computational analyses encompassed optimized geometrical structures, UV-Vis spectra, Natural Bond Orbital (NBO) analysis, and harmonic vibrational frequencies, with vibrational spectra interpretation assisted by the Vibrational Energy Distribution Analysis (VEDA4) program. NBO analysis confirmed the presence of intramolecular interactions such as electron delocalization and conjugative effects, while HOMO-LUMO energy calculations and molecular electrostatic potential (MEP) demonstrated charge transfer within BDP. Experimental and theoretical results were found to be in excellent agreement. The antibacterial activity of BDP was evaluated using the well diffusion method against Gram-positive and Gram-negative bacteria, with results indicating that BDP exhibited higher antibacterial activity than standard reference drugs. Furthermore, molecular docking studies assessed BDP’s binding affinity to active sites of Staphylococcus aureus (PDB ID: 2W9S) and Escherichia coli (PDB ID: 1WXH). The docking results revealed strong interactions via hydrogen bonding and hydrophobic interactions, highlighting BDP’s potential as a broad-spectrum antibacterial agent. Overall, this study demonstrates the promising structural, chemical, and biological properties of BDP, supporting its future application in antibacterial therapies.

Understanding particulate pollution in Eastern Mediterranean (EM) cities is challenging due to the combined influence of local urban emissions, marine aerosols, and long-range transported desert dust. Conventional surface-based measurements often fail to detect lofted dust layers, while satellite-derived Aerosol Optical Depth (AOD) provides only column-integrated information, limiting its ability to represent near-surface PM2.5 (fine particulate matter 2.5 micrometres or less in diameter) concentrations. Here, we combine five years of ground-based lidar observations with high resolution satellite AOD retrievals, PM2.5 measurements and meteorological data over the EM to investigate aerosol layering, source contributions, and column-to-surface relationships across three contrasting urban environments: regional background, urban traffic and semi-indoor sites located along highway/railroad. Lidar profiling identifies ten distinct aerosol layering types, from shallow anthropogenic layers to deep mixed structures composed of desert dust, marine aerosols, and urban pollution. We find that the AOD-PM2.5 relationship is strongly regime-dependent, and the degree of column-surface coupling varies sharply across the three urban environments. Machine-learning models that incorporate vertical lidar features significantly improve PM2.5 predictions across all sites, outperforming models without vertical information. Overall, our results demonstrate that reliable urban PM2.5 assessment requires explicit consideration of vertical aerosol structure. Integrating lidar-derived features enhances the interpretation of satellite AOD and improves urban exposure estimates in complex EM atmospheres.

Abstract Multi-cancer early detection (MCED) tests can detect several cancer types and stages. We previously developed a methylation and protein (MP V1) MCED classifier. In this study, we present a refined MP V2 classifier, developed by evaluating model architectures that improved performance in prospectively enrolled case-control cohorts under standard testing conditions. The newly developed MP V2 classifier was trained to be more generalizable and achieve increased early-stage sensitivity at a target specificity of ≥97.0%. MP V1 and MP V2 classifier performances were compared using a previously described test set, and MP V2 performance was also evaluated in a new independent clinical validation set. Compared to MP V1, the MP V2 classifier demonstrated a 7.3% increase in overall sensitivity, with sensitivity increases of 7.6%, 9.2%, and 8.3% for stages I, II, and stages I/II, respectively, in the intended use (breast and prostate cancers excluded) test set. In an independent validation intended use set, the MP V2 classifier showed an overall sensitivity of 55.6%, with sensitivities of 26.8%, 42.9%, and 34.8% for stages I, II, and stages I/II, respectively. In a case-control setting, the MP V2 classifier offered improved sensitivity for early-stage cancers at a lower specificity target.

ABSTRACT Invasive species are a major driver of biodiversity loss in protected areas (PAs), yet their impacts in aquatic environments are less well documented. This study investigated the occurrence and distribution of nonnative freshwater fish in federal PAs in Brazil. We analyzed governmental records of nonnative freshwater fish in federal PAs managed by ICMBio up to 2025. A total of 56 nonnative species (38 translocated and 18 introduced) were recorded in 108 PAs, of which 51 were designated as integral protection units and 57 as sustainable use units. Among the introduced species, Oreochromis niloticus and Coptodon rendalli had the highest number of records, and introduced species exhibited a broader spatial distribution than translocated species. Introduced species were also more prevalent in Environmental Protection Areas and National Forests than in Extractive Reserves, suggesting that certain PA categories may be more susceptible to fish introductions. The Amazon basin was the primary source of translocated species, reinforcing its role as a donor region for fish introductions across Brazil. Introduction pathways differed between groups: Introduced species were mainly associated with aquaculture and sport fisheries, whereas translocated species were largely linked to sport fisheries and interbasin connectivity. These findings underscore the urgency of targeted management strategies to curb further introductions and safeguard freshwater biodiversity within PAs. Strengthening PAs' effectiveness will require stricter regulations, improved enforcement and specifically designed strategies to manage nonnative species dispersal.

Abstract Early Adoption of Molecular Residual Disease Testing in Breast Cancer Patients using Real World Data Authors: Ning Yan Gu1, Kohli M2, Stephen J Noga1, Quang A. Le1, Rodriguez-Silva J2, Barhoush Y2, Batchu L2, Gebra Cuyun Carter11Exact Sciences, Madison, WI, USA; 2STATinMED LLC., Dallas, TXWord count: 2765/3400 characters OBJECTIVE: Testing for molecular residual disease (MRD) via circulating tumor DNA (ctDNA) biomarker is an emerging practice in cancer treatment and disease recurrence detection. This study aims to assess the early adoption of MRD for patients diagnosed with breast cancer (BC) using real-world data. METHODS: A national multi-payer medical and pharmacy claims data (STATinMED RWD Insights) with nearly 80% of the US healthcare system was used. Data were extracted for female patients aged ≥18 years between January 1, 2015, and November 30, 2023. Index date was defined as the first date of BC diagnosis. Included patients were required to have continuous enrollment for a minimum of 12 months pre-index, 30 days post-index, and had ≥1 inpatient or ≥2 outpatient BC claims (ICD-9-CM: 174x, 175x; ICD-10-CM: C50x). Patients were excluded if they had metastasized disease, other cancers (not including non-melanoma skin cancers), any BC treatment, or had evidence of pregnancy during the 12-month baseline period. Proxies were used to determine BC subtype and cancer stage. MRD utilization was identified from the index date to study end time and/or patients’ death. Multivariate logistic regression was used to identify predictors of the MRD test adoption. RESULTS: Among 652,463 eligible patients (mean age: 65.4 years), 815 (0.12%) had evidence of MRD testing, the first one was in 2021, increased in 2022, and continued to the study end date of November 30th, 2023, with most of the MRD testing occurred in 2023 (n=748, 91.8%). The mean follow-up time per patient was 38.76 months (SD: 26.57) with a median follow-up per patient of 29.70 months. The mean age of MRD tested patients was 62.7 years; 67.7% were White; 60.1% were non-Hispanic; 36.0% had a college education; 51.4% had Medicare; 27.3% had an income below $25,000 and 55.5% resided in the Southern United States. Categorizing the subtype, 65.2% had HR+/HER2- BC, 23.3% had triple-negative BC (TNBC), and 9.5% had HR+/HER2+ BC. During the study time frame, 60.9% of patients received only one MRD test, 23.1% received two, 8.3% received three and the remaining 7.7% of patients received four or more MRD tests, for up to 10 MRD tests. The mean number of MRD tests per patient was 1.72 (SD: 1.27). Among the 815 MRD-tested patients, 392 (48%) had evidence of breast-conserving surgery (BCS). Of those 392 patients, 5 (1.3%) received MRD testing before the BCS and 387 (98.7%) received MRD test after the BCS. For every BC subtype, the average time between tests was > 80 days between the 1st and 2nd tests, > 70 days between the 2nd and 3rd tests, with shorter intervening times for additional MRD tests conducted during study period. Based on the multivariate logistic regression, key factors associated with the receipt or adoption of MRD test included younger age, advanced BC stage, BC subtype, and patients’ residence region. CONCLUSION: This descriptive analysis using real-world data offers insights into the early adoption of the MRD testing among BC patients in the United States. The real-world evidence showcased an upward adoption trajectory during the study period and there were variations in early utilization patterns. Findings herein provide hypothesis generating opportunities for future investigations. Key Words: 1. Molecular residual disease 2. MRD testing 3. ctDNA 4. Breast cancer 5. Real world data Citation Format: N. Gu, M. Kohli, S. J. Noga, Q. A. Le, J. Rodriguez-Silva, Y. Barhoush, L. Batchu, G. C. Carter. Early Adoption of Molecular Residual Disease Testing in Breast Cancer Patients using Real World Data [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-04-01.

This study explores the implementation of an interdisciplinary teaching approach in primary teacher education, using ocean-related topics as a vehicle to integrate natural sciences, mathematics, and language learning. Conducted with preservice teachers in southern Chile, the research employed a pretest–posttest design, project-based learning activities, and semistructured interviews to examine changes in participants’ conceptions of interdisciplinarity, knowledge about the oceans, and capacity to design interdisciplinary tasks. The findings indicate a marked shift from a limited understanding of interdisciplinarity toward its recognition as a pedagogical strategy to foster critical thinking and meaningfully connect multiple subjects. The participants demonstrated increased awareness of the oceans’ ecological and climatic significance, improved ability to link ocean phenomena with core curricular areas, and enhanced skills in creating context-based, innovative learning activities. The analysis also identified key facilitators and obstacles influencing the adoption of interdisciplinary approaches. These findings offer actionable insights for improving interdisciplinary teacher education programs and can inform the design of similar initiatives in diverse educational contexts worldwide.

This study investigates exact solitary wave solutions of the modified Camassa–Holm (mCH) and modified Kuramoto–Sivashinsky (mKS) equations, which are fundamental in fluid dynamics, nonlinear optics, and quantum mechanics. Solutions are obtained using the [Formula: see text]-expansion neural network analytical method, a hybrid approach that integrates the symbolic capability of neural networks (NNs) with [Formula: see text]-expansion method, enabling the direct construction of analytical exact solutions without relying on classical transformations. The method yields a rich variety of soliton structures in trigonometric, hyperbolic, and rational forms, including periodic, bright, dark, V-shaped, kink, and singular kink solitons. The dynamics are illustrated through 2D, 3D with density surface, and polar plots, providing clear physical insights. The results demonstrate the efficiency and versatility of the method in capturing complex nonlinear behaviors and suggest potential applications in nonlinear wave propagation in fluid dynamics, plasma physics, optical communications, and biological systems.