Synergistic Antibacterial Effects of Metallic Nanoparticle Combinations

© The Author(s) 2019.Metallic nanoparticles have unique antimicrobial properties that make them suitable for use within medical and pharmaceutical devices to prevent the spread of infection in healthcare. The use of nanoparticles in healthcare is on the increase with silver being used in many devices. However, not all metallic nanoparticles can target and kill all disease-causing bacteria. To overcome this, a combination of several different metallic nanoparticles were used in this study to compare effects of multiple metallic nanoparticles when in combination than when used singly, as single elemental nanoparticles (SENPs), against two common hospital acquired pathogens (Staphylococcus aureus and Pseudomonas. aeruginosa). Flow cytometry LIVE/DEAD assay was used to determine rates of cell death within a bacterial population when exposed to the nanoparticles. Results were analysed using linear models to compare effectiveness of three different metallic nanoparticles, tungsten carbide (WC), silver (Ag) and copper (Cu), in combination and separately. Results show that when the nanoparticles are placed in combination (NPCs), antimicrobial effects significantly increase than when compared with SENPs (P < 0.01). This study demonstrates that certain metallic nanoparticles can be used in combination to improve the antimicrobial efficiency in destroying morphologically distinct pathogens within the healthcare and pharmaceutical industry.Peer reviewe

Using geographically weighted regression to explore the spatially heterogeneous spread of bovine tuberculosis in England and Wales

An understanding of the factors that affect the spread of endemic bovine tuberculosis (bTB) is critical for the development of measures to stop and reverse this spread. Analyses of spatial data need to account for the inherent spatial heterogeneity within the data, or else spatial autocorrelation can lead to an overestimate of the significance of variables. This study used three methods of analysis—least-squares linear regression with a spatial autocorrelation term, geographically weighted regression (GWR) and boosted regression tree (BRT) analysis—to identify the factors that influence the spread of endemic bTB at a local level in England and Wales. The linear regression and GWR methods demonstrated the importance of accounting for spatial differences in risk factors for bTB, and showed some consistency in the identification of certain factors related to flooding, disease history and the presence of multiple genotypes of bTB. This is the first attempt to explore the factors associated with the spread of endemic bTB in England and Wales using GWR. This technique improves on least-squares linear regression approaches by identifying regional differences in the factors associated with bTB spread. However, interpretation of these complex regional differences is difficult and the approach does not lend itself to predictive models which are likely to be of more value to policy makers. Methods such as BRT may be more suited to such a task. Here we have demonstrated that GWR and BRT can produce comparable outputs

Sudden cardiac death and pump failure death prediction in chronic heart failure by combining ECG and clinical markers in an integrated risk model

BACKGROUND: Sudden cardiac death (SCD) and pump failure death (PFD) are common endpoints in chronic heart failure (CHF) patients, but prevention strategies are different. Currently used tools to specifically predict these endpoints are limited. We developed risk models to specifically assess SCD and PFD risk in CHF by combining ECG markers and clinical variables. METHODS: The relation of clinical and ECG markers with SCD and PFD risk was assessed in 597 patients enrolled in the MUSIC (MUerte Súbita en Insuficiencia Cardiaca) study. ECG indices included: turbulence slope (TS), reflecting autonomic dysfunction; T-wave alternans (TWA), reflecting ventricular repolarization instability; and T-peak-to-end restitution (ΔαTpe) and T-wave morphology restitution (TMR), both reflecting changes in dispersion of repolarization due to heart rate changes. Standard clinical indices were also included. RESULTS: The indices with the greatest SCD prognostic impact were gender, New York Heart Association (NYHA) class, left ventricular ejection fraction, TWA, ΔαTpe and TMR. For PFD, the indices were diabetes, NYHA class, ΔαTpe and TS. Using a model with only clinical variables, the hazard ratios (HRs) for SCD and PFD for patients in the high-risk group (fifth quintile of risk score) with respect to patients in the low-risk group (first and second quintiles of risk score) were both greater than 4. HRs for SCD and PFD increased to 9 and 11 when using a model including only ECG markers, and to 14 and 13, when combining clinical and ECG markers. CONCLUSION: The inclusion of ECG markers capturing complementary pro-arrhythmic and pump failure mechanisms into risk models based only on standard clinical variables substantially improves prediction of SCD and PFD in CHF patients

Structure Sensitivity and Evolution of Nickel-Bearing Nitrogen-Doped Carbons in the Electrochemical Reduction of CO2

The emergence of nickel single atoms on nitrogen-doped carbons as high-performance catalysts amenable to rationalization due to their well-defined structure could lead to applicable technologies for the electrocatalytic CO2 reduction reaction (eCO2RR). However, real materials are unlikely to display a uniform site structure, which limits the scope of current efforts focused on idealized models for future implementation. Here, we prepare distinct nickel entities (single atoms or nanoparticles) on nitrogen-doped carbons and evaluate them in eCO2RR. Single atoms demonstrate a characteristic high selectivity to CO. However, this is not altered by the presence of metal nanoparticles formed upon reducing the nitrogen content of the carrier. In contrast, nanoparticles incorporated via a colloidal route promote the parasitic hydrogen evolution reaction. In these systems, the CO selectivity evolves upon repeated exposure to potential, reaching values comparable to single atoms. By introducing CO stripping voltammetry as a characterization tool for this class of materials, we identify a decreased metallic surface, suggesting that the nanoparticle surface is altered by CO. The findings highlight the critical role of dynamic effects in catalyst design for eCO2RR

The Antiquity and Evolutionary History of Social Behavior in Bees

A long-standing controversy in bee social evolution concerns whether highly eusocial behavior has evolved once or twice within the corbiculate Apidae. Corbiculate bees include the highly eusocial honey bees and stingless bees, the primitively eusocial bumble bees, and the predominantly solitary or communal orchid bees. Here we use a model-based approach to reconstruct the evolutionary history of eusociality and date the antiquity of eusocial behavior in apid bees, using a recent molecular phylogeny of the Apidae. We conclude that eusociality evolved once in the common ancestor of the corbiculate Apidae, advanced eusociality evolved independently in the honey and stingless bees, and that eusociality was lost in the orchid bees. Fossil-calibrated divergence time estimates reveal that eusociality first evolved at least 87 Mya (78 to 95 Mya) in the corbiculates, much earlier than in other groups of bees with less complex social behavior. These results provide a robust new evolutionary framework for studies of the organization and genetic basis of social behavior in honey bees and their relatives

Multiple populations in globular clusters. Lessons learned from the Milky Way globular clusters

Recent progress in studies of globular clusters has shown that they are not simple stellar populations, being rather made of multiple generations. Evidence stems both from photometry and spectroscopy. A new paradigm is then arising for the formation of massive star clusters, which includes several episodes of star formation. While this provides an explanation for several features of globular clusters, including the second parameter problem, it also opens new perspectives about the relation between globular clusters and the halo of our Galaxy, and by extension of all populations with a high specific frequency of globular clusters, such as, e.g., giant elliptical galaxies. We review progress in this area, focusing on the most recent studies. Several points remain to be properly understood, in particular those concerning the nature of the polluters producing the abundance pattern in the clusters and the typical timescale, the range of cluster masses where this phenomenon is active, and the relation between globular clusters and other satellites of our Galaxy.Comment: In press (The Astronomy and Astrophysics Review

An indirect immunofluorescence antibody test employing whole eggs as the antigen for the diagnosis of abdominal angiostrongyliasis

Abdominal angiostrongyliasis is a potentially fatal zoonotic disease with a broad geographical distribution throughout Central and South America. This study assessed the performance of Angiostrongylus costaricensis eggs as the antigen in an indirect immunofluorescence assay for the determination of parasite-specific IgG and IgG1 antibodies. For prevalence studies, an IgG antibody titre > 16 was identified as the diagnostic threshold with the best performance, providing 93.7% sensitivity and 84.6% specificity. Cross reactivity was evaluated with 65 additional samples from patients with other known parasitic infections. Cross reactivity was observed only in samples from individuals infected with Strongyloides stercoralis. For clinical diagnosis, we recommend the determination of IgG only as a screening test. IgG1 determination may be used to increase the specificity of the results for patients with a positive screening test

Elucidation of Metal Local Environments in Single‐Atom Catalysts Based on Carbon Nitrides

The ability to tailor the properties of metal centers in single-atom heterogeneous catalysts depends on the availability of advanced approaches for characterization of their structure. Except for specific host materials with well-defined metal adsorption sites, determining the local atomic environment remains a crucial challenge, often relying heavily on simulations. This article reports an advanced analysis of platinum atoms stabilized on poly(triazine imide), a nanocrystalline form of carbon nitride. The approach discriminates the distribution of surface coordination sites in the host, the evolution of metal coordination at different stages during the synthesis of the material, and the potential locations of metal atoms within the lattice. Consistent with density functional theory predictions, simultaneous high-resolution imaging in high-angle annular dark field and bright field modes experimentally confirms the preferred localization of platinum in-plane in the corners of the triangular cavities. X-ray absorption spectroscopy (XAS), X-ray photoelectron spectroscopy (XPS), and dynamic nuclear polarization enhanced 15N nuclear magnetic resonance (DNP-NMR) spectroscopies coupled with density functional theory (DFT) simulations reveal that the predominant metal species comprise Pt(II) bound to three nitrogen atoms and one chlorine atom inside the coordination sites. The findings, which narrow the gap between experimental and theoretical elucidation, contribute to the improved structural understanding and provide a benchmark for exploring the speciation of single-atom catalysts based on carbon nitrides

A Computational Approach to Understand In Vitro Alveolar Morphogenesis

Primary human alveolar type II (AT II) epithelial cells maintained in Matrigel cultures form alveolar-like cysts (ALCs) using a cytogenesis mechanism that is different from that of other studied epithelial cell types: neither proliferation nor death is involved. During ALC formation, AT II cells engage simultaneously in fundamentally different, but not fully characterized activities. Mechanisms enabling these activities and the roles they play during different process stages are virtually unknown. Identifying, characterizing, and understanding the activities and mechanisms are essential to achieving deeper insight into this fundamental feature of morphogenesis. That deeper insight is needed to answer important questions. When and how does an AT cell choose to switch from one activity to another? Why does it choose one action rather than another? We report obtaining plausible answers using a rigorous, multi-attribute modeling and simulation approach that leveraged earlier efforts by using new, agent and object-oriented capabilities. We discovered a set of cell-level operating principles that enabled in silico cells to self-organize and generate systemic cystogenesis phenomena that are quantitatively indistinguishable from those observed in vitro. Success required that the cell components be quasi-autonomous. As simulation time advances, each in silico cell autonomously updates its environment information to reclassify its condition. It then uses the axiomatic operating principles to execute just one action for each possible condition. The quasi-autonomous actions of individual in silico cells were sufficient for developing stable cyst-like structures. The results strengthen in silico to in vitro mappings at three levels: mechanisms, behaviors, and operating principles, thereby achieving a degree of validation and enabling answering the questions posed. We suggest that the in silico operating principles presented may have a biological counterpart and that a semiquantitative mapping exists between in silico causal events and in vitro causal events

The CAPN10 Gene Is Associated with Insulin Resistance Phenotypes in the Spanish Population

Cardiovascular disease is the leading cause of morbidity and mortality in the industrialized world. Familial aggregation of cardiovascular risk factors is a frequent finding, but genetic factors affecting its presentation are still poorly understood. The calpain 10 gene (CAPN10) has been associated with type 2 diabetes (T2DM), a complex metabolic disorder with increased risk of cardiovascular disease. Moreover, the CAPN10 gene has been associated with the presence of metabolic syndrome (MS) in T2DM and in polycystic ovary syndrome (PCOS). In this work, we have analysed whether the polymorphisms UCSNP44, -43, -19 and -63 are related to several cardiovascular risk factors in the context of MS. Molecular analysis of CAPN10 gene was performed in 899 individuals randomly chosen from a cross-sectional population-based epidemiological survey. We have found that CAPN10 gene in our population is mainly associated with two indicators of the presence of insulin resistance: glucose levels two hours after a 75-g oral glucose tolerance test (OGTT) and HOMA values, although cholesterol levels and blood pressure values are also influenced by CAPN10 variants. In addition, the 1221/1121 haplogenotype is under-represented in individuals that fulfil the International Diabetes Federation (IDF) diagnostic criteria for MS. Our results suggest that CAPN10 gene is associated with insulin resistance phenotypes in the Spanish population