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This study enhances the molecular analysis of bitumen by transitioning from traditional chemical descriptors, such as SARA (Saturates, Aromatics, Resins, and Asphaltenes) fractions and elemental compositions, to specific force field atom types in Molecular Dynamics (MD) models. This shift improves the precision in predicting material properties critical for bituminous material characterization. Machine Learning Models (MLMs) were developed to use these atom types as input features, inherently reflecting fundamental chemical characteristics. Trained on data from over 1,770 LAMMPS simulations of diverse bitumen types and conditions, these MLMs enable the prediction of properties like density, heat capacity, solubility parameters, and thermal expansion coefficients without the need for additional MD simulations. The models utilize 30 chemical descriptors corresponding to specific atom types in the PCFF force field, which collectively account for over 95% of the influence on these properties. By accurately predicting fundamental, thermodynamic, and kinetic properties, the use of MLMs and force field atom types allows researchers to efficiently tweak the chemical nature of organic molecules and mixtures to achieve desired properties. With near-instantaneous prediction times, these MLMs offer valuable insights for advancing bitumen research in the construction and petroleum industries, reducing the need for more intensive simulation techniques.

ABSTRACTHeteroresistance to antifungal agents poses a significant challenge in the treatment of fungal infections. Currently, the absence of established methods for detecting and measuring heteroresistance impedes progress in understanding this phenomenon in fungal pathogens. In response to this gap, we present a comprehensive set of new and optimized methods designed to detect and quantify azole heteroresistance in Candida albicans. Here, we define two primary assays for measuring heteroresistance: population analysis profiling, based on growth on solid medium, and single-cell assays, based on growth in liquid culture. We observe good correlations between the measurements obtained with liquid and solid assays, validating their utility for studying azole heteroresistance. We also highlight that disk diffusion assays could serve as an additional tool for the rapid detection of heteroresistance. These methods collectively provide a versatile toolkit for researchers seeking to assess heteroresistance in C. albicans. They also serve as a critical step forward in the characterization of antifungal heteroresistance, providing a framework for investigating this phenomenon in diverse fungal species and in the context of other antifungal agents. Ultimately, these advancements will enhance our ability to effectively measure antifungal drug responses and combat fungal infections.IMPORTANCEHeteroresistance involves varying antimicrobial susceptibility within a clonal population. This phenomenon allows the survival of rare resistant subpopulations during drug treatment, significantly complicating the effective management of infections. However, the absence of established detection methods hampers progress in understanding this phenomenon in human fungal pathogens. We propose a comprehensive toolkit to address this gap in the yeast Candida albicans, encompassing population analysis profiling, single-cell assays, and disk diffusion assays. By providing robust and correlated measurements through both solid and liquid assays, this work will provide a framework for broader applications across clinically relevant Candida species. These methods will enhance our ability to understand this phenomenon and the failure of antifungal therapy.

This paper presents a United Atom (UA) force field for simulating hydrocarbon molecules in bituminous materials, integrating explicit hydrogens into beads with their parent atom. This method simplifies all-atom molecular models, significantly accelerating Molecular Dynamics (MD) simulations of bitumen by 10 to 100 times. Key advantages include halving the particle count, eliminating complex hydrogen interactions, and decreasing the degrees of freedom of the molecules. Developed by mapping forces from an all-atom model to the centers of mass of UA model beads, the force field ensures accurate replication of energies, forces, and molecular conformations, mirroring properties like pressure and density. It features 17 bead types and 287 interaction types, encompassing various hydrocarbon molecules. The UA force field's stability, surpassing all-atom models, is a notable achievement. This stability, stemming from smoother potential energy surfaces, leads to consistent property measurements and improved stress tensor accuracy. It enables the extension of MD simulations to larger spatiotemporal scales, crucial for understanding complex phenomena such as phase separation in bituminous materials. This foundational work sets the stage for future developments, including refining parameters and introducing new bead types, to enhance the modeling capabilities of the force field, thereby advancing the application and understanding of bituminous materials.

Conventional Molecular Dynamics (MD) models of bitumen are built by homogeneously mixing molecules in a volume without considering that the molecules in bitumen are known to exhibit phase behavior and form distinctive molecular arrangements. These are known to have a significant impact in the behavior of bitumen, and considering their existence is paramount in producing improved representations of bitumen using computational models. This study explores whether MD models of bitumen that are conventionally assumed to be in equilibrium can still undergo significant phase separation over considerably long simulation times. It also aims to establish a more formal pathway to build and study models with highly heterogeneous arrangements of their molecules. Moreover, it aims to evaluate whether the presence of distinct morphologies have a significant impact in numerous physical properties of bitumen. The study shows that conventional and widely used models of bitumen exhibit significant molecular rearrangements over long times (>360 ns). It also shows that building heterogeneous morphologies is possible and result in energetically favorable conformations. Moreover, it proves that studying properties regularly used to validate MD models of bitumen (e.g., density) are insufficient in assessing the impact of different morphologies; more thorough methods are required to evaluate them.

Stent thrombosis (ST) is a catastrophic event and efforts to reduce its incidence by altering blood-stent interactions are longstanding. A new electret coating technology that produces long-lasting negative charge on stent surface could make them intrinsically resistant to thrombosis. We assessed the thrombogenicity of stents using an annular perfusion model with confocal microscopy, and determined the efficacy of electret coating technology to confer thrombo-resistant properties to standard stents. Using an annular perfusion chamber, Bare Metal Stent (BMS), standard uncoated DES (DES), and Electret-coated DES (e-DES) were exposed to human blood under arterial flow conditions. Deposits of fibrinogen and platelets on the stent surface were analyzed using immunofluorescence staining and confocal microscopy. Surface coverage by fibrinogen and platelets and the deposit/aggregate size were quantified using computerized morphometric analysis. The experimental methodology produced consistent, quantifiable results. Area of stent surface covered by fibrinogen and platelets and the average size of the deposits/aggregates were lowest for e-DES and highest on BMS, with DES in the middle. The size of fibrinogen–deposits showed no differences between the stents. The testing methodology used in our study successfully demonstrated that electret coating confers significant antithrombotic property to DES stents. These findings warrant confirmation in a larger study.

Legacy persistent organic pollutants (POPs) such as polychlorinated biphenyls (PCBs) are chemicals that undergo long-range transport to the Arctic. These chemicals possess endocrine disruptive properties raising concerns for development and reproduction. Here, we report the relationship between concentrations of testosterone (T) and persistent organic pollutant (POPs) in 40 East Greenland male polar bears (Ursus maritimus) sampled during January to September 1999–2001. The mean ± standard concentrations of blood T were 0.31 ± 0.49 (mean ± SD) ng/mL in juveniles/subadults (n = 22) and 3.58 ± 7.45 ng/mL in adults (n = 18). The ∑POP concentrations (mean ± SD) in adipose tissue were 8139 ± 2990 ng/g lipid weight (lw) in juveniles/subadults and 11,037 ± 3950 ng/g lw in adult males, respectively, of which Σpolychlorinated biphenyls (ΣPCBs) were found in highest concentrations. The variation in T concentrations explained by sampling date (season), biometrics and adipose tissue POP concentrations was explored using redundancy analysis (RDA). The results showed that age, body length, and adipose lipid content in adult males contributed (p = 0.02) to the variation in POP concentrations. However, although some significant relationships between individual organochlorine contaminants and T concentrations in both juveniles/subadults and adult polar bears were identified, no significant relationships (p = 0.32) between T and POP concentrations were identified by the RDAs. Our results suggest that confounders such as biometrics and reproductive status may mask the endocrine disruptive effects that POPs have on blood T levels in male polar bears, demonstrating why it can be difficult to detect effects on wildlife populations.

To clarify the proper role of values in science, focusing on controversial expert responses to Covid-19, this article examines the status of (in)convenient hypotheses. Polarizing cases like health experts downplaying mask efficacy to save resources for healthcare workers, or scientists dismissing “accidental lab leak” hypotheses in view of potential xenophobia, plausibly involve modifying evidential standards for (in)convenient claims. Societies could accept that scientists handle (in)convenient claims just like nonscientists, and give experts less political power. Or societies could hold scientists to a higher bar, by expecting them not to modify evidential standards to avoid costs only incidentally tied to error.

Cardiovascular disease (CVD) is a major cause of death and disability worldwide. A real need exists in the development of new, improved therapeutic methods for treating CVD, while major advances in nanotechnology have opened new avenues in this field. In this paper, we report the use of gold nanoparticles (GNPs) coated with high-density lipoprotein (HDL) (GNP-HDL) for the simultaneous detection and therapy of unstable plaques. Based on the well-known HDL cardiovascular protection, by promoting the reverse cholesterol transport (RCT), injured rat carotids, as a model for unstable plaques, were injected with the GNP-HDL. Noninvasive detection of the plaques 24 h post the GNP injection was enabled using the diffusion reflection (DR) method, indicating that the GNP-HDL particles had accumulated in the injured site. Pathology and noninvasive CT measurements proved the recovery of the injured artery treated with the GNP-HDL. The DR of the GNP-HDL presented a simple and highly sensitive method at a low cost, resulting in simultaneous specific unstable plaque diagnosis and recovery.