The effective enhancement of information in 3D small-world networks of biological neuronal cells.

The cardiovascular system, the kidney, or the brain, are examples of complex systems - where the properties of the systems arise because of the layout of cells in those systems. One way to characterize systems is using networks, where elements and interactions of the systems are represented as nodes and links of a graph. Network's topology can be, in turn, measured by the small-world coefficient. Small world networks feature increased clustering and shorter paths compared to random or periodic networks of the same size. This suggests that systems with small world attributes can also efficiently transport signals, nutrients, or information within their body. While several reports in literature have illustrated that real biological systems are small-world, yet little is known about how information varies as a function of the small-world-ness (sw) of three dimensional graphs. Here, we used a model of the brain to estimate quantitatively the information processed in 3D networks. In the model, nodes of the graph are neuronal units capable to receive, integrate and transmit signals to other neurons of the system in parallel. The information encoded in the signals was then extracted using the techniques of information theory. In simulations where the topology of networks of400nodes was varied over large intervals, we found that in the0-9swrange information scales linearly with the small world coefficient, with a five-fold increase. Results of the paper and review of the existing literature on model organisms suggest that a small-world architecture may offer an evolutionary advantage to biological systems.

Surely you are joking, Mr Docking!

In the wake of recent COVID-19 pandemics scientists around the world rushed to deliver numerous CADD (Computer-Aided Drug Discovery) methods and tools that could be reliably used to discover novel drug candidates against the SARS-CoV-2 virus. With that, there emerged a trend of a significant democratization of CADD that contributed to the rapid development of various COVID-19 drug candidates currently undergoing different stages of validation. On the other hand, this democratization also inadvertently led to the surge rapidly performed molecular docking studies to nominate multiple scores of novel drug candidates supported by computational arguments only. Albeit driven by best intentions, most of such studies also did not follow best practices in the field that require experience and expertise learned through multiple rigorously designed benchmarking studies and rigorous experimental validation. In this Viewpoint we reflect on recent disbalance between small number of rigorous and comprehensive studies and the proliferation of purely computational studies enabled by the ease of docking software availability. We further elaborate on the hyped oversale of CADD methods' ability to rapidly yield viable drug candidates and reiterate the critical importance of rigor and adherence to the best practices of CADD in view of recent emergence of AI and Big Data in the field.

A review of modeling pesticides in freshwaters: Current status, progress achieved and desirable improvements.

This study comprises a critical review of modeling of pesticides in surface waters. The aim was to update the status of the use of models to simulate the fate of pesticides from diffuse sources. ISI papers were selected on Scopus and the information concerning the study areas, type of pesticides (herbicides, fungicides and insecticides), the model, and the methodology adopted (i.e., calibration and/or validation, spatial and temporal scales) were analyzed. The studies were carried out in Europe (55.5%), North America (22.3%), Asia (13.9%) and South America (8.3%). The Soil and Water Assessment Tool proved to be the most used model (45.95%). Herbicides were the most modeled pesticides (71.4%), followed by insecticides (18.2%) and fungicides (10.4%). The main herbicides modeled were atrazine, metolachlor, isoproturon, glyphosate, and acetochlor. Insecticides such as chlorpyrifos and metaldehyde. Chlorothalonil, and fungicides (i.e., tebuconazole) were the most widely investigated. Based on published studies, it was found that modeling approaches for assessing the fate of pesticides are constantly evolving and the model algorithms work well with diverse watershed conditions, management strategies, and pesticide properties. Several papers reported concentrations of pesticides exceeding ecotoxicological thresholds revealing that water contamination with pesticides used in agriculture and urban areas is a priority issue of current global concern.

The small world coefficient 4.8 ± 1 optimizes information processing in 2D neuronal networks.

Small world networks have recently attracted much attention because of their unique properties. Mounting evidence suggests that communication is optimized in networks with a small world topology. However, despite the relevance of the argument, little is known about the effective enhancement of information in similar graphs. Here, we provide a quantitative estimate of the efficiency of small world networks. We used a model of the brain in which neurons are described as agents that integrate the signals from other neurons and generate an output that spreads in the system. We then used the Shannon Information Entropy to decode those signals and compute the information transported in the grid as a function of its small-world-ness ([Formula: see text]), of the length ([Formula: see text]) and frequency ([Formula: see text]) of the originating stimulus. In numerical simulations in which [Formula: see text] was varied between [Formula: see text] and [Formula: see text] we found that, for certain values of [Formula: see text] and [Formula: see text], communication is enhanced up to [Formula: see text] times compared to unstructured systems of the same size. Moreover, we found that the information processing capacity of a system steadily increases with [Formula: see text] until the value [Formula: see text], independently on [Formula: see text] and [Formula: see text]. After this threshold, the performance degrades with [Formula: see text] and there is no convenience in increasing indefinitely the number of active links in the system. Supported by the findings of the work and in analogy with the exergy in thermodynamics, we introduce the concept of exordic systems: a system is exordic if it is topologically biased to transmit information efficiently.

Time dependent adhesion of cells on nanorough surfaces.

Understanding and controlling the mechanisms of cell adhesion to nanomaterials is essential in tissue engineering, regenerative medicine, the development of experimental models for the study of neurodegenerative diseases. Nonetheless, despite the great many of studies that have examined how cells interact with nanoscale surfaces, little is known about the temporal dimension of the process of adhesion. In a previous work, Decuzzi and Ferrari, by examining how the energy of a cell changes while binding to a nanoscale surface, determined a criterion to decide whether nanoroughness can either enhance or retard cell adhesion. While accurate, however their model template disregards the time variable. Here, starting from the work of Decuzzi and Ferrari, we have developed a mathematical model based on chemotaxis that describes how cells adhere to a nanorough surface over time. Relaxing the originating constraint of a fixed density of ligand molecules expressed by the cell membrane, we show that the strength of adhesion depends on time and that, for certain values of the model parameters, a cell can arrive to establish a stable adhesion to a substrate even if the process of binding is initially energetically unfavourable. We show that, for a cell-membrane stiffness of 10kPa, an initial density of receptors of 500bonds/µm2, a specific and non-specific energy density of adhesion of 10-5J/m2 and 10-7J/m2, and roughness in the low nanometer range, cell adhesion forces can be completely activated from few seconds to some tens of minutes from the initial contact with the surface.

A practical approach for gmp-compliant validation of real-time PCR method for mycoplasma detection in human mesenchymal stromal cells as advanced therapy medicinal product.

BACKGROUND: Manufacturing of human Mesenchymal Stromal Cells as advanced therapy medicinal product (ATMP) for clinical use involves an ex vivo expansion, which leads to a risk of contamination by microbiological agents. Even if manufacturing under Good Manufacturing Practice (GMP) license minimizes this risk, contamination of cell cultures by mycoplasmas still represents a widespread problem. Furthermore, the absence of mycoplasma contamination represents one of ATMPs release criteria. Since July 2007, European Pharmacopoeia (EuPh) offers the possibility to replace official mycoplasma detection methods with Nucleic Acid Amplification techniques, after suitable validation. As an Italian authorized Cell Factory, we developed an in-house GMP-compliant validation of real-time PCR method for mycoplasma detection in human Mesenchymal Stromal Cells, according to EuPh sec. 2.6.7 and International Conference on Harmonization Q2. MATERIALS AND METHODS: The study was performed in compliance with GMP international requirements with MycoSEQ™ Mycoplasma Detection Assay (Thermofisher) on QuantStudio5 real-Time PCR (Applied Biosystems). Assay validation was developed to evaluate sensitivity, interferences matrix-related, specificity and robustness. RESULTS: MycoSEQ™ Mycoplasma Detection Assay has been successfully validated on human Mesenchymal Stromal Cells as results comply with validation protocol acceptance criteria. CONCLUSIONS: MycoSEQ™ Mycoplasma Detection Assay is a fast, sensitive and specific PCR-based Nucleic Acid Test assay that can be used as an alternative to official mycoplasma test methods for lot release of human Mesenchymal Stromal Cells as advanced therapy medicinal product (ATMP). Moreover, our study underlines the presence of interference on real-time PCR reaction due to matrix composition, pointing out a practical approach for method validation (i.e interference removal).

Molecular Evolution of Antigen-Processing Genes in Salamanders: Do They Coevolve with MHC Class I Genes?

Proteins encoded by antigen-processing genes (APGs) prepare antigens for presentation by the major histocompatibility complex class I (MHC I) molecules. Coevolution between APGs and MHC I genes has been proposed as the ancestral gnathostome condition. The hypothesis predicts a single highly expressed MHC I gene and tight linkage between APGs and MHC I. In addition, APGs should evolve under positive selection, a consequence of the adaptive evolution in MHC I. The presence of multiple highly expressed MHC I genes in some teleosts, birds, and urodeles appears incompatible with the coevolution hypothesis. Here, we use urodele amphibians to test two key expectations derived from the coevolution hypothesis: 1) the linkage between APGs and MHC I was studied in Lissotriton newts and 2) the evidence for adaptive evolution in APGs was assessed using 42 urodele species comprising 21 genera from seven families. We demonstrated that five APGs (PSMB8, PSMB9, TAP1, TAP2, and TAPBP) are tightly linked (<0.5 cM) to MHC I. Although all APGs showed some codons under episodic positive selection, we did not find a pervasive signal of positive selection expected under the coevolution hypothesis. Gene duplications, putative gene losses, and divergent allelic lineages detected in some APGs demonstrate considerable evolutionary dynamics of APGs in salamanders. Overall, our results indicate that if coevolution between APGs and MHC I occurred in urodeles, it would be more complex than envisaged in the original formulation of the hypothesis.

Connecting high-throughput biodiversity inventories: Opportunities for a site-based genomic framework for global integration and synthesis.

High-throughput sequencing (HTS) is increasingly being used for the characterization and monitoring of biodiversity. If applied in a structured way, across broad geographical scales, it offers the potential for a much deeper understanding of global biodiversity through the integration of massive quantities of molecular inventory data generated independently at local, regional and global scales. The universality, reliability and efficiency of HTS data can potentially facilitate the seamless linking of data among species assemblages from different sites, at different hierarchical levels of diversity, for any taxonomic group and regardless of prior taxonomic knowledge. However, collective international efforts are required to optimally exploit the potential of site-based HTS data for global integration and synthesis, efforts that at present are limited to the microbial domain. To contribute to the development of an analogous strategy for the nonmicrobial terrestrial domain, an international symposium entitled "Next Generation Biodiversity Monitoring" was held in November 2019 in Nicosia (Cyprus). The symposium brought together evolutionary geneticists, ecologists and biodiversity scientists involved in diverse regional and global initiatives using HTS as a core tool for biodiversity assessment. In this review, we summarize the consensus that emerged from the 3-day symposium. We converged on the opinion that an effective terrestrial Genomic Observatories network for global biodiversity integration and synthesis should be spatially led and strategically united under the umbrella of the metabarcoding approach. Subsequently, we outline an HTS-based strategy to collectively build an integrative framework for site-based biodiversity data generation.

Cardiogenic shock and acute kidney injury: the rule rather than the exception.

Cardiogenic shock (CS) is a life-threatening condition of poor end-organ perfusion, caused by any cardiovascular disease resulting in a severe depression of cardiac output. Despite recent advances in replacement therapies, the outcome of CS is still poor, and its management depends more on empirical decisions rather than on evidence-based strategies. By its side, acute kidney injury (AKI) is a frequent complication of CS, resulting in the onset of a cardiorenal syndrome. The combination of CS with AKI depicts a worse clinical scenario and holds a worse prognosis. Many factors can lead to acute renal impairment in the setting of CS, either for natural disease progression or for iatrogenic causes. This review aims at collecting the current evidence-based acknowledgments in epidemiology, pathophysiology, clinical features, diagnosis, and management of CS with AKI. We also attempted to highlight the major gaps in evidence as well as to point out possible strategies to improve the outcome.

Cell aggregation on nanorough surfaces.

The ability to control adhesion and the spatial organization of cells over nanoscale surfaces is essential in tissue engineering, regenerative medicine, the growth of organoids and spheroids as an in-vitro-model of human development and disease. Nonetheless, despite the several different works that have explored the influence of nanotopography on cell adhesion and clustering, little is known about how the forces arising from membrane conformational change developing during cell adaptation to a nanorough surface, and the cell-cell adhesion forces, interact to guide cell assembly. Here, starting from the works of Decuzzi and Ferrari, who examined how the energy of a cell varies while adhering to a nanoscale surface, and of Armstrong and collaborators, who developed a continuous model of cell-cell adhesion and morphogenesis, we provide a description of how nanotopography can modulate cellular clustering. In simulations where the parameters of the model were varied over large intervals, we found that nanoroughness may induce cell aggregation from a homogenous, uniform state, also for weak cell-cell adhesion. Results of the model are relevant in bio-engineering and biomedical nanotechnology, and may be of interest for those involved in the design and fabrication of biomaterials and scaffolds for tissue formation and repair.

Publisher Correction: Cortical-like mini-columns of neuronal cells on zinc oxide nanowire surfaces.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Global conservation of species' niches.

Environmental change is rapidly accelerating, and many species will need to adapt to survive1. Ensuring that protected areas cover populations across a broad range of environmental conditions could safeguard the processes that lead to such adaptations1-3. However, international conservation policies have largely neglected these considerations when setting targets for the expansion of protected areas4. Here we show that-of 19,937 vertebrate species globally5-8-the representation of environmental conditions across their habitats in protected areas (hereafter, niche representation) is inadequate for 4,836 (93.1%) amphibian, 8,653 (89.5%) bird and 4,608 (90.9%) terrestrial mammal species. Expanding existing protected areas to cover these gaps would encompass 33.8% of the total land surface-exceeding the current target of 17% that has been adopted by governments. Priority locations for expanding the system of protected areas to improve niche representation occur in global biodiversity hotspots9, including Colombia, Papua New Guinea, South Africa and southwest China, as well as across most of the major land masses of the Earth. Conversely, we also show that planning for the expansion of protected areas without explicitly considering environmental conditions would marginally reduce the land area required to 30.7%, but that this would lead to inadequate niche representation for 7,798 (39.1%) species. As the governments of the world prepare to renegotiate global conservation targets, policymakers have the opportunity to help to maintain the adaptive potential of species by considering niche representation within protected areas1,2.

A nanomechanical model enables comprehensive characterization of biological tissues in ultrasound imaging.

Sonography, elastography, sonoelastography are ultrasound imaging techniques commonly used in the clinical practice for the diagnosis of many pathological conditions. These highly reliable, non-invasive methods use high frequency, elastic pressure waves (ultrasounds) to interrogate the internal structure of biological tissues and organs, and the continuum mechanics hypothesis to reconstruct, from the output of the system, the biophysical characteristics of the samples. Nevertheless, continuum mechanics disregards the discrete nature of tissues and organs, resulting in an inability for the model to describe some important tissue biophysical characteristics such as the cell size and their spatial layout. Here, we used the theory of doublet mechanics - a discrete nano-mechanical field theory - to model the propagation of ultrasounds in a multilayered biological tissue. We found that the output of the model exhibits a very high sensitivity to the macro and micro characteristics of the tissue, including cell size. We used results from the model to correlate the internal structure of the samples to the reflection coefficient, i.e. the continuum level response of the system. This model, and its more sophisticated evolutions that will be developed over time, can complement traditional ultrasound imaging, and provide ways to analyze non-invasively living tissues with a resolution inaccessible to conventional techniques of analysis, including positron emission tomography, computer tomography, and magnetic resonance.

An all-electron study of the low-lying excited states and optical constants of Al2O3 in the range 5-80 eV.

This paper reports calculated energies and electronic structures of O(2p), O(2s) and Al(2p) excited states in bulk [Formula: see text]-Al2O3, at the [Formula: see text] and [Formula: see text] surfaces and in the presence of O vacancy defects, obtained from all-electron HF, B3LYP, GGA and LDA calculations based on a recently described direct [Formula: see text]-SCF approach (Mackrodt et al 2018 J. Phys.: Condens. Matter 30 495901). The closely related frequency-dependent optical constants derived from B3LYP calculations within the CPHF/DF framework are also reported, where both sets of results are shown to compare favourably with the experimental spectra. The differences between the directly calculated excited state energies, which in [Formula: see text]-Al2O3 are equal to the leading excitation edges, based on the four functionals, are substantially less than the differences between the corresponding (ground state) band gaps, as reported previously for AFII NiO (Mackrodt et al 2018 J. Phys.: Condens. Matter 30 495901). For the B3LYP functional, these energies are 8.7 eV, 12.5 eV and 73.7 eV for the O(2p), O(2s) and Al(2p) excitations respectively. The O(2p) edge is predicted to be degenerate, with distinct excitations from O(2p) states that are parallel to and perpendicular to the c-axis, in agreement with the reported spectra (Tomiki et al 1993 J. Phys. Soc. Japan 62 573). Detailed analyses of the charge and spin distributions in the four bulk excited states indicate that these are essentially charge-transfer excitonic, with acceptor sites at the nearest neighbour positions. Despite the close proximity of the O([Formula: see text]) and O(2p[Formula: see text]) excited state energies, the charge and spin distributions are predicted to be quite different.

Cortical-like mini-columns of neuronal cells on zinc oxide nanowire surfaces.

A long-standing goal of neuroscience is a theory that explains the formation of the minicolumns in the cerebral cortex. Minicolumns are the elementary computational units of the mature neocortex. Here, we use zinc oxide nanowires with controlled topography as substrates for neural-cell growth. We observe that neuronal cells form networks where the networks characteristics exhibit a high sensitivity to the topography of the nanowires. For certain values of nanowires density and fractal dimension, neuronal networks express small world attributes, with enhanced information flows. We observe that neurons in these networks congregate in superclusters of approximately 200 neurons. We demonstrate that this number is not coincidental: the maximum number of cells in a supercluster is limited by the competition between the binding energy between cells, adhesion to the substrate, and the kinetic energy of the system. Since cortical minicolumns have similar size, similar anatomical and topological characteristics of neuronal superclusters on nanowires surfaces, we conjecture that the formation of cortical minicolumns is likewise guided by the interplay between energy minimization, information optimization and topology. For the first time, we provide a clear account of the mechanisms of formation of the minicolumns in the brain.

Relating the rate of growth of metal nanoparticles to cluster size distribution in electroless deposition.

Electroless deposition on patterned silicon substrates enables the formation of metal nanomaterials with tight control over their size and shape. In the technique, metal ions are transported by diffusion from a solution to the active sites of an autocatalytic substrate where they are reduced as metals upon contact. Here, using diffusion limited aggregation models and numerical simulations, we derived relationships that correlate the cluster size distribution to the total mass of deposited particles. We found that the ratio ξ between the rates of growth of two different metals depends on the ratio γ between the rates of growth of clusters formed by those metals through the linearity law ξ = 14(γ - 1). We then validated the model using experiments. Different from other methods, the model derives k using as input the geometry of metal nanoparticle clusters, decoded by SEM or AFM images of samples, and a known reference.

Superhydrophobic lab-on-chip measures secretome protonation state and provides a personalized risk assessment of sporadic tumour.

Secretome of primary cultures is an accessible source of biological markers compared to more complex and less decipherable mixtures such as serum or plasma. The protonation state (PS) of secretome reflects the metabolism of cells and can be used for cancer early detection. Here, we demonstrate a superhydrophobic organic electrochemical device that measures PS in a drop of secretome derived from liquid biopsies. Using data from the sensor and principal component analysis (PCA), we developed algorithms able to efficiently discriminate tumour patients from non-tumour patients. We then validated the results using mass spectrometry and biochemical analysis of samples. For the 36 patients across three independent cohorts, the method identified tumour patients with high sensitivity and identification as high as 100% (no false positives) with declared subjects at-risk, for sporadic cancer onset, by intermediate values of PS. This assay could impact on cancer risk management, individual's diagnosis and/or help clarify risk in healthy populations.

Diet shifts by adult flightless dung beetles Circellium bacchus, revealed using DNA metabarcoding, reflect complex life histories.

Life history changes may change resource use. Such shifts are not well understood in the dung beetles, despite recognised differences in larval and adult feeding ability. We use the flightless dung beetle Circellium bacchus to explore such shifts, identifying dung sources of adults using DNA metabarcoding, and comparing these with published accounts of larval dung sources. C. bacchus is traditionally considered to specialise on the dung of large herbivores for both larval and adult feeding. We successfully extracted mammal DNA from 151 adult C. bacchus fecal samples, representing 16 mammal species (ranging from elephants to small rodents), many of which are hitherto undescribed in the diet. Adult C. bacchus showed clear dung source preferences, especially for large herbivores inhabiting dense-cover vegetation. Our approach also confirmed the presence of cryptic taxa in the study area, and we propose that this may be used for biodiversity survey and monitoring purposes. Murid rodent feces were the most commonly fed-upon dung source (77.5%) for adult C. bacchus, differing markedly from the large and megaherbivore dung sources used for larval rearing. These findings support the hypothesis of life history-specific shifts in resource use in dung beetles, and reveal a hitherto unsuspected, but ecologically important, role of these dung beetles in consuming rodent feces. The differences in feeding abilities of the larval and adult life history stages have profound consequences for their resource use and foraging strategies, and hence the ecological role of dung beetles. This principle and its ecological consequences should be explored in other scarabaeids.