Analysis of the airflow features and ventilation efficiency of an Ultra-Clean-Air operating theatre by qDNS simulations and experimental validation.

Ultra-Clean-Air (UCA) operating theatres aim to minimise surgical instrument contamination and wound infection through high flow rates of ultra-clean air, reducing the presence of Microbe Carrying Particles (MCPs). This study investigates the airflow patterns and ventilation characteristics of a UCA operating theatre (OT) under standard ventilation system operating conditions, considering both empty and partially occupied scenarios. Utilising a precise computational model, quasi-Direct Numerical Simulations (qDNS) were conducted to delineate flow velocity profiles, energy spectra, distributions of turbulent kinetic energy, energy dissipation rate, local Kolmogorov scales, and pressure-based coherent structures. These results were also complemented by a tracer gas decay analysis following ASHRAE standard guidelines. Simulations showed that contrary to the intended laminar regime, the OT's geometry inherently fosters a predominantly turbulent airflow, sustained until evacuation through the exhaust vents, and facilitating recirculation zones irrespective of occupancy level. Notably, the occupied scenario demonstrated superior ventilation efficiency, a phenomenon attributed to enhanced kinetic energy induced by the additional obstructions. The findings underscore the critical role of UCA-OT design in mitigating MCP dissemination, highlighting the potential to augment the design to optimise airflow across a broader theatre spectrum, thereby diminishing recirculation zones and consequently reducing the propensity for Surgical Site Infections (SSIs). The study advocates for design refinements to harness the turbulent dynamics beneficially, steering towards a safer surgical environment.

Part II: A new perspective for modeling the bone remodeling process: Biology, mechanics, and pathologies.

In this paper, we explore the effects of biological (pathological) and mechanical damage on bone tissue within a benchmark model. Using the Finite Element Methodology, we analyze and numerically test the model's components, capabilities, and performance under physiologically and pathologically relevant conditions. Our findings demonstrate the model's effectiveness in simulating bone remodeling processes and self-repair mechanisms for micro-damage induced by biological internal conditions and mechanical external ones within bone tissue. This article is the second part of a series, where the first part presented the mathematical model and the biological and physical significance of the terms used in a simplified benchmark model. It explored the bone remodeling model's application, implementation, and results under physiological conditions.

Tumor growth for remodeling process: A 2D approach.

This paper aims to present a comprehensive framework for coupling tumor-bone remodeling processes in a 2-dimensional geometry. This is achieved by introducing a bio-inspired damage that represents the growing tumor, which subsequently affects the main populations involved in the remodeling process, namely, osteoclasts, osteoblasts, and bone tissue. The model is constructed using a set of differential equations based on the Komarova's and Ayati's models, modified to incorporate the bio-inspired damage that may result in tumor mass formation. Three distinct models were developed. The first two models are based on the Komarova's governing equations, with one demonstrating an osteolytic behavior and the second one an osteoblastic model. The third model is a variation of Ayati's model, where the bio-inspired damage is induced through the paracrine and autocrine parameters, exhibiting an osteolytic behavior. The obtained results are consistent with existing literature, leading us to believe that our in-silico experiments will serve as a cornerstone for paving the way towards targeted interventions and personalized treatment strategies, ultimately improving the quality of life for those affected by these conditions.

A unified framework of cell population dynamics and mechanical stimulus using a discrete approach in bone remodelling.

Multiphysics models have become a key tool in understanding the way different phenomenon are related in bone remodeling and various approaches have been proposed, yet, to the best of the author's knowledge there is no model able to link a cell population model with a mechanical stimulus model using a discrete approach, which allows for an easy implementation. This article couples two classical models, the cell population model from Komarova and the Nackenhorst model in a 2D domain, where correlations between the mechanical loading and the cell population dynamics can be established, furthermore the effect of different paracrine and autocrine regulators is seen on the overall density of a portion of trabecular bone. A discretization is performed using frame 1D finite elements, representing the trabecular structure. The Nackenhorst model is implemented by using the finite element method to calculate the strain energy as the main mechanical stimulus that determines the bone mass density evolution in time. This density is normalized to be added to the bone mass percentage proposed by the Komarova model, where coupling terms have been added as well that guarantee a stable response. In the simulations, the equations were solved employing the finite element method with a user subroutine implemented in ABAQUS (2017) and by applying a direct formulation. The methodology presented can model the cell dynamics occurring in bone remodelling in accordance with the asynchronous nature of this process, yet allowing to differentiate zones with higher density, the main trabecular groups are obtained for the proximal femur. Finally, the model is tested in pathological cases, such as osteoporosis and osteopetrosis, yielding results similar to the pathology behavior. Furthermore, the discrete modelling technique is shown to be of use in this particular application.

A simple and effective 1D-element discrete-based method for computational bone remodeling.

In-silico models applied to bone remodeling are widely used to investigate bone mechanics, bone diseases, bone-implant interactions, and also the effect of treatments of bone pathologies. This article proposes a new methodology to solve the bone remodeling problem using one-dimensional (1D) elements to discretize trabecular structures more efficiently for 2D and 3D domains. An Euler integration scheme is coupled with the momentum equations to obtain the evolution of material density at each step. For the simulations, the equations were solved by using the finite element method, and two benchmark tests were solved varying mesh parameters. Proximal femur and calcaneus bone were selected as study cases given the vast research available on the topology of these bones, and compared with the anatomical features of trabecular bone reported in the literature. The presented methodology has proven to be efficient in optimizing topologies of lattice structures; It can predict the trend of formation patterns of the main trabecular groups from two different cancellous bones (femur and calcaneus) using domains set up by discrete elements as a starting point. Preliminary results confirm that the proposed approach is suitable and useful in bone remodeling problems leading to a considerable computational cost reduction. Characteristics similar to those encountered in topological optimization algorithms were identified in the benchmark tests as well, showing the viability of the proposed approach in other applications such as bio-inspired design.

Unexpected crosslinking and diglycation as advanced glycation end-products from glyoxal.

Glyoxal-derived advanced glycation end-products (AGEs) are formed in physiological systems affecting protein/peptide function and structure. These AGEs are generated during aging and chronic diseases such as diabetes and are considered arginine glycating agents. Thus, the study of glyoxal-derived AGEs in lysine residues and amino acid competition is addressed here using acetylated and non-acetylated undecapeptides, with one arginine and one lysine residue available for glycation. Tandem mass spectrometry results from a Fourier transform ion cyclotron resonance mass spectrometer showed glycated species at both the arginine and lysine residues. One species with the mass addition of 116.01096 Da is formed at the arginine residue. A possible structure is proposed to explain this finding (Nδ-[2-(dihydroxymethyl)-2H,3aH,4H,6aH-[1,3]dioxolo[5,6-d]imidazolin-5-yl]-L-ornithine-derived AGE). The second species corresponded to intramolecular crosslink involving the lysine residue and its presence is checked with ion-mobility mass spectrometry.

Study of an unusual advanced glycation end-product (AGE) derived from glyoxal using mass spectrometry.

Glycation is a post-translational modification (PTM) that affects the physiological properties of peptides and proteins. In particular, during hyperglycaemia, glycation by α-dicarbonyl compounds generate α-dicarbonyl-derived glycation products also called α-dicarbonyl-derived advanced glycation end products. Glycation by the α-dicarbonyl compound known as glyoxal was studied in model peptides by MS/MS using a Fourier transform ion cyclotron resonance mass spectrometer. An unusual type of glyoxal-derived AGE with a mass addition of 21.98436 Da is reported in peptides containing combinations of two arginine-two lysine, and one arginine-three lysine amino acid residues. Electron capture dissociation and collisionally activated dissociation results supported that the unusual glyoxal-derived AGE is formed at the guanidino group of arginine, and a possible structure is proposed to illustrate the 21.9843 Da mass addition.

Tandem mass spectrometry for the study of glyoxal-derived advanced glycation end-products (AGEs) in peptides.

RATIONALE: The post-translational modification known as glycation affects the physiological properties of peptides and proteins. Glycation is particularly important during hyperglycaemia where α-dicarbonyl compounds are generated. These compounds react with proteins to generate α-dicarbonyl-derived glycation products, which are correlated with diabetic complications such as nephropathy, retinopathy, and neuropathy, among others. One of these α-dicarbonyl compounds is ethanedial, also known as glyoxal. Thereby, glyoxal binding to protein/peptides is studied by electron capture dissociation (ECD) and collisionally activated dissociation (CAD). METHODS: Acetylated and non-acetylated undecapeptides containing one lysine and one arginine susceptible of glycation were reacted with glyoxal under pseudo-physiological and MeOH/H2O (50:50) conditions. Two types of glyoxal-derived AGEs were fragmented by ECD and CAD using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS). RESULTS: Reaction with glyoxal under different reaction conditions showed the addition of C2O and C2H2O2, which corresponded to a net increase on the peptide mass of 39.9949 Da and 58.0055 Da, respectively. The binding site was assigned within an error <1 ppm, using ECD and CAD. The results indicated that both types of glyoxal-derived AGEs are formed at the side chain of arginine located in position 3. CONCLUSIONS: Types and binding sites of glyoxal-derived AGEs were investigated in peptides containing one arginine-one lysine using FTICRMS. Two net mass additions to the mass of the peptide were assigned as C2O and C2H2O2, which were located at the arginine side chain. In addition, these mass additions (C2O and C2H2O2) observed in the peptides were unaffected by different reaction conditions.

Modelo computacional preliminar de la formación de la superficie cerebral / Preliminary computation form of the cerebral surface development

La corteza cerebral es una lámina gris, formada por cuerpos de neuronas, que cubre los hemisferios cerebrales y cuyo grosor varía de 1,25 mm en el lóbulo occipital a 4 mm en el lóbulo anterior. Debido a los numerosos pliegues que presenta, la superficie cerebral es unas 30 veces mayor que la superficie del cráneo. Estos pliegues forman las circunvoluciones cerebrales, surcos y fisuras y delimitan áreas con funciones determinadas, divididas en cinco lóbulos. La formación de las circunvoluciones puede variar entre individuos y constituyen una característica importante de la formación del cerebro. Estos patrones se pueden representar, de forma matemática, como patrones de Turing. En este artículo se desarrolla un modelo fenomenológico que describe la formación de los patrones de las circunvoluciones que ocurren en la corteza cerebral mediante ecuaciones de reacción difusión con parámetros en el espacio de Turing. Para estudiar la formación de patrones se resuelven varios ejemplos numéricos sobre geometrías simplificadas de un cerebro. Para la solución numérica se utilizó el método de los elementos finitos en conjunto con el método de Newton-Raphson. Los ejemplos numéricos muestran que el modelo puede representar la formación de los pliegues de la corteza cerebral y reproducir patologías de la formación de las circunvoluciones, tales como polimicrogiria y lisencefalia.

Cerebral cortex is a gray layer including neuron bodies covering the cerebral hemispheres and whose thickness fluctuates from 1.25 mm in the occipital lobule to 4 mm in the anterior lobule. Due to the many folds present, la cerebral surface is a thirty times greater than the cranial surface. These folds create the cerebral convolutions, grooves and fissures defining areas with determined functions, divided into five lobules. La convolutions formation may to vary among subjects and are an important characteristic of brain formation. These patterns may be represented in a mathematical way like Turing patterns. The aim of present paper was to design a phenomenological model describing the formation of convolutions patterns occurring in the cerebral cortex by means of diffusion reaction equations with parameters in the Turing space. To study la formation of patterns it is necessary to solve some numerical examples on simplified geometries of a brain. For numerical solution authors used the finite elements method together with the Newton-Raphson method. The numerical examples demonstrate that this model may to represent the folds formation in the cerebral cortex and to reproduce pathologies of the convolutions formation, such as the polymicrogyria and lissencephalous.