Hydrophilic nanoparticles that kill bacteria while sparing mammalian cells reveal the antibiotic role of nanostructures

To dissect the antibiotic role of nanostructures from chemical moieties belligerent to both bacterial and mammalian cells, here we show the antimicrobial activity and cytotoxicity of nanoparticle-pinched polymer brushes (NPPBs) consisting of chemically inert silica nanospheres of systematically varied diameters covalently grafted with hydrophilic polymer brushes that are non-toxic and non-bactericidal. Assembly of the hydrophilic polymers into nanostructured NPPBs doesn’t alter their amicability with mammalian cells, but it incurs a transformation of their antimicrobial potential against bacteria, including clinical multidrug-resistant strains, that depends critically on the nanoparticle sizes. The acquired antimicrobial potency intensifies with small nanoparticles but subsides quickly with large ones. We identify a threshold size (dsilica ~ 50 nm) only beneath which NPPBs remodel bacteria-mimicking membrane into 2D columnar phase, the epitome of membrane pore formation. This study illuminates nanoengineering as a viable approach to develop nanoantibiotics that kill bacteria upon contact yet remain nontoxic when engulfed by mammalian cells.

Evidence of a Threshold Size for Norwegian Campsites and Its Dynamic Growth Process Implications—Does Gibrat’s Law Hold?

Although campsites are an important segment of the tourist sector, few applied articles have analyzed their growth path and tested Gibrat’s Law for firms within this industry. This knowledge can be of importance to the authorities when analyzing the regional impacts of growth in this sector. With government statistics from the last decade, we use a GMM framework to test the stricter version of Gibrat’s Law, which consist of three parts: the campsites’ growth trend, how they carry over success and failure, and how volatile their size is. The first and third part are rejected for Norwegian campsites, leading to a rejection of Gibrat’s Law. To see if firms of different sizes follow different dynamics, we split the sample in three parts. Here, we find evidence of a threshold size, as large campsites follow a fundamentally different dynamic than small and medium campsites. Specifically, large campsites gain no stability in revenue by further increases in size, whereas they carry over success/failure across years. The opposite is true for the rest of the sector. Gibrat’s Law is rejected on at least one count for each of the sub-samples. Lastly, we supplement the analysis with economy-wide and firm-specific variables to test further hypotheses.

The stochastic dynamics of early epidemics: probability of establishment, initial growth rate, and infection cluster size at first detection

Emerging epidemics and local infection clusters are initially prone to stochastic effects that can substantially impact the early epidemic trajectory. While numerous studies are devoted to the deterministic regime of an established epidemic, mathematical descriptions of the initial phase of epidemic growth are comparatively rarer. Here, we review existing mathematical results on the size of the epidemic over time, and derive new results to elucidate the early dynamics of an infection cluster started by a single infected individual. We show that the initial growth of epidemics that eventually take off is accelerated by stochasticity. As an application, we compute the distribution of the first detection time of an infected individual in an infection cluster depending on testing effort, and estimate that the SARS-CoV-2 variant of concern Alpha detected in September 2020 first appeared in the UK early August 2020. We also compute a minimal testing frequency to detect clusters before they exceed a given threshold size. These results improve our theoretical understanding of early epidemics and will be useful for the study and control of local infectious disease clusters.

Price cap regulation and water quality

A number of studies suggest that price cap regulation may reduce the quality of the regulated good. This paper analyzes the impact on drinking water quality of a shift from cost-of-service to price cap regulation in Denmark, using a balanced panel of drinking water companies, for the period 2008 to 2016. The price cap was introduced in 2011 for companies above a certain threshold size. We exploit this quasi-experimental setting to estimate the impact of the shift in regulation using a regression discontinuity difference-in-differences approach. Our measure of drinking water quality is based on results from a compulsory surveillance drinking water testing program, which investigates whether or not water samples contain a level of microbiological content that exceeds limit values. More specifically, we compare the change over time in water quality for a treatment group of 113 companies regulated with price caps that have a size close to the threshold size for being regulated, with the change in drinking water quality for a control group of 282 companies that are below but close to the threshold size. We find that the shift in regulation has not caused a reduction in drinking water quality in Denmark.

Nanoparticle Size Threshold for Magnetic Agglomeration and Associated Hyperthermia Performance

The likelihood of magnetic nanoparticles to agglomerate is usually estimated through the ratio between magnetic dipole-dipole and thermal energies, thus neglecting the fact that, depending on the magnitude of the magnetic anisotropy constant (K), the particle moment may fluctuate internally and thus undermine the agglomeration process. Based on the comparison between the involved timescales, we study in this work how the threshold size for magnetic agglomeration (daggl) varies depending on the K value. Our results suggest that small variations in K-due to, e.g., shape contribution, might shift daggl by a few nm. A comparison with the usual superparamagnetism estimation is provided, as well as with the energy competition approach. In addition, based on the key role of the anisotropy in the hyperthermia performance, we also analyse the associated heating capability, as non-agglomerated particles would be of high interest for the application.

“Axonal Length Determines distinct homeostatic phenotypes in human iPSC derived motor neurons on a bioengineered platform”

Stem cell-based experimental platforms for neuroscience can effectively model key mechanistic aspects of human development and disease. However, conventional culture systems often overlook the engineering constraints that cells face in vivo. This is particularly relevant for neurons covering long range connections such as spinal motor neurons (MNs). The axons of these neurons extend up to 1m in length and require a complex interplay of mechanisms to maintain cellular homeostasis. It follows that shorter axons in conventional cultures may not faithfully capture important aspects of their longer counterparts. Here we directly address this issue by establishing a bioengineered platform to assemble arrays of human axons ranging from micrometers to centimeters, permitting systematic investigation of the effects of length on human axonal biology for the first time. With this approach, we reveal a link between length and metabolism in human MNs in vitro, where axons above a “threshold” size induce specific molecular adaptations in cytoskeleton composition, functional properties, local translation and mitochondrial homeostasis. Our findings specifically demonstrate the existence of a length-dependent mechanism that switches homeostatic processes within human MNs in order to sustain long axons. Our findings have critical implications for in vitro modelling of several neurodegenerative disorders and reinforce the importance of modelling cell shape and biophysical constraints with fidelity and precision in vitro.

How to Measure the Urban Park Cooling Island? A Perspective of Absolute and Relative Indicators Using Remote Sensing and Buffer Analysis

Urban parks have been proven to cool the surrounding environment, and can thus mitigate the urban heat island to an extent by forming a park cooling island. However, a comprehensive understanding of the mechanism of park cooling islands is still required. Therefore, we studied 32 urban parks in Jinan, China and proposed absolute and relative indicators to depict the detailed features of the park cooling island. High-spatial-resolution GF-2 images were used to obtain the land cover of parks, and Landsat 8 TIR images were used to examine the thermal environment by applying buffer analysis. Linear statistical models were developed to explore the relationships between park characteristics and the park cooling island. The results showed that the average land surface temperature (LST) of urban parks was approximately 3.6 °C lower than that of the study area, with the largest temperature difference of 7.84 °C occurring during summer daytime, while the average park cooling area was approximately 120.68 ha. The park cooling island could be classified into four categories—regular, declined, increased, and others—based on the changing features of the surrounding LSTs. Park area (PA), park perimeter (PP), water area proportion (WAP), and park shape index (PSI) were significantly negatively correlated with the park LST. We also found that WAP, PP, and greenness (characterized by the normalized difference vegetation index (NDVI)) were three important factors that determined the park cooling island. However, the relationship between PA and the park cooling island was complex, as the results indicated that only parks larger than a threshold size (20 ha in our study) would provide a larger cooling effect with the increase in park size. In this case, increasing the NDVI of the parks by planting more vegetation would be a more sustainable and effective solution to form a stronger park cooling island.

A Bayesian updating of crack distributions in steam generator tubes

The structural failure of steam generator tubes is a common problem that can a ect the availability and safety of nuclear power plants. To minimize the probability of occurrence of failure, it is needed to implement maintenance strategies such as periodic nondestructive inspections of tubes. Thus, a tube is repaired or plugged whenever it has detected a crack which a threshold size is overtaken. In general, uncertainties and errors in crack sizes are associated with the nondestructive inspections. These uncertainties and errors should be appropriately characterized to estimate the actual crack distribution. This work proposes a Bayesian approach for updating crack distributions, which in turn allows computing the failure probability of steam generator tubes at current and future times. The failure criterion is based on plastic collapse phenomenon, and the failure probability is computed by using the Monte-Carlo simulation. The failure probability at current and future times is in good agreement with the ones presented in the literature.

Between-host dynamics (Epidemiology)

Epidemiology is the population dynamics of host–parasite systems. The spread of an infective disease is analysed with several tools. The SIR model (susceptible, infected, recovered hosts) is a standard model, with the basic reproductive number (R 0) as a characteristic. Diseases, in general, spread if R 0 > 1, which suggests a threshold size for host populations, and also for endemic maintenance or periodic outbreaks. Furthermore, spatial heterogeneity or the distribution of infections among hosts affects an epidemic. Individual-based models can follow the fate of infections more closely. Network analysis provides insights into transmission and contact rates. Models also describe the epidemics of vectored diseases, or of macroparasitic infections. Molecular epidemiology uses genetic markers or genomes to follow the spread of an infectious disease; phylodynamics reconstructs transmission chains, especially for viral diseases. Immunoepidemiology studies how immune defences affect an epidemic and identifies immunological markers for the study of infectious disease dynamics.

Adipocyte death triggers a pro-inflammatory response and induces metabolic activation of resident macrophages

A chronic low-grade inflammation within adipose tissue (AT) seems to be the link between obesity and some of its associated diseases. One hallmark of this AT inflammation is the accumulation of AT macrophages (ATMs) around dead or dying adipocytes, forming so-called crown-like structures (CLS). To investigate the dynamics of CLS and their direct impact on the activation state of ATMs, we established a laser injury model to deplete individual adipocytes in living AT from double reporter mice (GFP-labeled ATMs and tdTomato-labeled adipocytes). Hence, we were able to detect early ATM-adipocyte interactions by live imaging and to determine a precise timeline for CLS formation after adipocyte death. Further, our data indicate metabolic activation and increased lipid metabolism in ATMs upon forming CLS. Most importantly, adipocyte death, even in lean animals under homeostatic conditions, leads to a locally confined inflammation, which is in sharp contrast to other tissues. We identified cell size as cause for the described pro-inflammatory response, as the size of adipocytes is above a critical threshold size for efferocytosis, a process for anti-inflammatory removal of dead cells during tissue homeostasis. Finally, experiments on parabiotic mice verified that adipocyte death leads to a pro-inflammatory response of resident ATMs in vivo, without significant recruitment of blood monocytes. Our data indicate that adipocyte death triggers a unique degradation process and locally induces a metabolically activated ATM phenotype that is globally observed with obesity.