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المبتكرون
يلخص الكتاب مساهمات العديد من المبدعين الذين حققوا اختراقات محورية في تكنولوجيا الكمبيوتر وتطبيقاته - من أول مبرمج للكمبيوتر في العالم، وأدا لوفليس، وألان تورينج في مجال الذكاء الاصطناعي، من خلال عصر المعلومات في الوقت الحاضر. على الرغم من أن كتابه يركز على الأفراد، إلا أن إيزاكسون يذكر القراء بأن الابتكارات غالبًا ما تكون نتاج تعاون جماعي. من بين المبتكرين الذين ناقشهم هذا الكتاب تشارلز باباج، آدا لوفليس، فانيفار بوش، كونراد زوس، آلان تورينج، غريس هوبر، جون ماوشلي، جون فون نيومان، جي سي آر ليكلايدر، دوغ إنجيلبارت، روبرت نويس من إنتل، بيل غيتس وبول ألين من مايكروسوفت، ستيف وزنياك وستيف جوبز من أبل وتيم بيرنرز لي ولاري بيج من جوجل وجيمي ويلز من ويكيبيديا ولي فيلسنشتاين من أوسبورن.
BOOK
Catalyst: Fast and flexible modeling of reaction networks
We introduce Catalyst.jl, a flexible and feature-filled Julia library for modeling and high-performance simulation of chemical reaction networks (CRNs). Catalyst supports simulating stochastic chemical kinetics (jump process), chemical Langevin equation (stochastic differential equation), and reaction rate equation (ordinary differential equation) representations for CRNs. Through comprehensive benchmarks, we demonstrate that Catalyst simulation runtimes are often one to two orders of magnitude faster than other popular tools. More broadly, Catalyst acts as both a domain-specific language and an intermediate representation for symbolically encoding CRN models as Julia-native objects. This enables a pipeline of symbolically specifying, analyzing, and modifying CRNs; converting Catalyst models to symbolic representations of concrete mathematical models; and generating compiled code for numerical solvers. Leveraging ModelingToolkit.jl and Symbolics.jl, Catalyst models can be analyzed, simplified, and compiled into optimized representations for use in numerical solvers. Finally, we demonstrate Catalyst’s broad extensibility and composability by highlighting how it can compose with a variety of Julia libraries, and how existing open-source biological modeling projects have extended its intermediate representation.
Journal Article
THE REACTION-DIFFUSION MASTER EQUATION AS AN ASYMPTOTIC APPROXIMATION OF DIFFUSION TO A SMALL TARGET
The reaction-diffusion master equation (RDME) has recently been used as a model for biological systems in which both noise in the chemical reaction process and diffusion in space of the reacting molecules is important. In the RDME, space is partitioned by a mesh into a collection of voxels. There is an unanswered question as to how solutions depend on the mesh spacing. To have confidence in using the RDME to draw conclusions about biological systems, we would like to know that it approximates a reasonable physical model for appropriately chosen mesh spacings. This issue is investigated by studying the dependence on mesh spacing of solutions to the RDME in for the bimolecular reaction A + B → Ø, with one molecule of species A and one molecule of species B present initially. We prove that in the continuum limit the molecules never react and simply diffuse relative to each other. Nevertheless, we show that the RDME with nonzero lattice spacing yields an asymptotic approximation to a specific spatially continuous diffusion limited reaction (SCDLR) model. We demonstrate that for realistic biological parameters it is possible to find mesh spacings such that the relative error between asymptotic approximations to the solutions of the RDME and the SCDLR models is less than one percent.
Journal Article
Strong intracellular signal inactivation produces sharper and more robust signaling from cell membrane to nucleus
For a chemical signal to propagate across a cell, it must navigate a tortuous environment involving a variety of organelle barriers. In this work we study mathematical models for a basic chemical signal, the arrival times at the nuclear membrane of proteins that are activated at the cell membrane and diffuse throughout the cytosol. Organelle surfaces within human B cells are reconstructed from soft X-ray tomographic images, and modeled as reflecting barriers to the molecules’ diffusion. We show that signal inactivation sharpens signals, reducing variability in the arrival time at the nuclear membrane. Inactivation can also compensate for an observed slowdown in signal propagation induced by the presence of organelle barriers, leading to arrival times at the nuclear membrane that are comparable to models in which the cytosol is treated as an open, empty region. In the limit of strong signal inactivation this is achieved by filtering out molecules that traverse non-geodesic paths.
Journal Article
Correction: Catalyst: Fast and flexible modeling of reaction networks
The benchmarks were run on the multi-state (Multistate, 9 species and 18 reactions [47]), multi-site (Multisite 2, 66 species and 288 reactions [48]), epidermal growth factor receptor signalling (Egfr_net, 356 species and 3749 reactions [49]), B-cell receptor (1122 species and 24388 reactions [50]), and high-affinity human IgE receptor signalling (Fceri_gamma2, 3744 species and 58276 reactions [51]) models. (a-e) Benchmarks of deterministic RRE ODE simulations of the five models. While this figure only contains the most performant methods, a full list of methods investigated can be found in Section B in S1 Text, with their results described in Figs A and B in S1 Text. (f-j) Benchmarks of stochastic chemical kinetics SSA simulations of the five models. For full details on benchmarks, see Section 4.1. https://doi.org/10.1371/journal.pcbi.1013175.g003 The first and corresponding author has also added a branch to the repository hosting the corrected scripts for generating all figures presented in [1], as well as for carrying out the benchmarks.
Journal Article
Does Self Myofascial Release of the Plantar Fascia Improve Static Balance Scores in Collegiate Women Athletes?
Methods: 15 college-aged female athletes (age 19.4 + 1.06 yrs; height 165.13 + 6.25 cm; mass 66.03 + 15.7 kg; body mass index 24.05 + 5.23) volunteered for this investigation. Discussion: Previous research has demonstrated SMR can be effective for improving static and dynamic balance scores on female athletes using a foam roller on the quadriceps, hamstrings, and calves for 2 minutes at a similar pain tolerance. Brief intermittent use of SMR on connective tissue has been demonstrated by previous literature to increase athletic performance markers in female college athletes.
Journal Article
The molecular reach of antibodies crucially underpins their viral neutralisation capacity
Key functions of antibodies, such as viral neutralisation, depend on high-affinity binding. However, viral neutralisation poorly correlates with antigen affinity for reasons that have been unclear. Here, we use a new mechanistic model of bivalent binding to study >45 patient-isolated IgG1 antibodies interacting with SARS-CoV-2 RBD surfaces. The model provides the standard monovalent affinity/kinetics and new bivalent parameters, including the molecular reach: the maximum antigen separation enabling bivalent binding. We find large variations in these parameters across antibodies, including reach variations (22–46 nm) that exceed the physical antibody size (~15 nm). By using antigens of different physical sizes, we show that these large molecular reaches are the result of both the antibody and antigen sizes. Although viral neutralisation correlates poorly with affinity, a striking correlation is observed with molecular reach. Indeed, the molecular reach explains differences in neutralisation for antibodies binding with the same affinity to the same RBD-epitope. Thus, antibodies within an isotype class binding the same antigen can display differences in molecular reach, substantially modulating their binding and functional properties.
Researchers developed an accurate model to analyse bivalent antibody binding. By analysing many SARS-CoV-2-specific antibodies, they found that their molecular reach can predict their neutralisation potency.
Journal Article
The influence of volume exclusion by chromatin on the time required to find specific DNA binding sites by diffusion
Within the nuclei of eukaryotic cells, the density of chromatin is nonuniform. We study the influence of this nonuniform density, which we derive from microscopic images [Schermelleh L, et al. (2008) Science 320: 1332-1336], on the diffusion of proteins within the nucleus, under the hypothesis that chromatin density is proportional to an effective potential that tends to exclude the diffusing protein from regions of high chromatin density. The constant of proportionality, which we call the volume exclusivity of chromatin, is a model parameter that we can tune to study the influence of such volume exclusivity on the random time required for a diffusing particle to find its target. We consider randomly chosen binding sites located in regions of low (20th-30th percentile) chromatin density, and we compute the median time to find such a binding site by a protein that enters the nucleus at a randomly chosen nuclear pore. As the volume exclusivity of chromatin increases from zero, we find that the median time needed to reach the target binding site at first decreases to a minimum, and then increases again as the volume exclusivity of chromatin increases further. Random permutation of the voxel values of chromatin density abolishes the minimum, thus demonstrating that the speedup seen with increasing volume exclusivity at low to moderate volume exclusivity is dependent upon the spatial structure of chromatin within the nucleus.
Journal Article
An Unstructured Mesh Reaction-Drift-Diffusion Master Equation with Reversible Reactions
We develop a convergent reaction-drift-diffusion master equation (CRDDME) to facilitate the study of reaction processes in which spatial transport is influenced by drift due to one-body potential fields within general domain geometries. The generalized CRDDME is obtained through two steps. We first derive an unstructured grid jump process approximation for reversible diffusions, enabling the simulation of drift-diffusion processes where the drift arises due to a conservative field that biases particle motion. Leveraging the Edge-Averaged Finite Element method, our approach preserves detailed balance of drift-diffusion fluxes at equilibrium, and preserves an equilibrium Gibbs-Boltzmann distribution for particles undergoing drift-diffusion on the unstructured mesh. We next formulate a spatially-continuous volume reactivity particle-based reaction-drift-diffusion model for reversible reactions of the form
A
+
B
↔
C
. A finite volume discretization is used to generate jump process approximations to reaction terms in this model. The discretization is developed to ensure the combined reaction-drift-diffusion jump process approximation is consistent with detailed balance of reaction fluxes holding at equilibrium, along with supporting a discrete version of the continuous equilibrium state. The new CRDDME model represents a continuous-time discrete-space jump process approximation to the underlying volume reactivity model. We demonstrate the convergence and accuracy of the new CRDDME through a number of numerical examples, and illustrate its use on an idealized model for membrane protein receptor dynamics in T cell signaling.
Journal Article