Control of transcription presides over a vast array of biological processes, including those mediated by gene regulatory circuits that exhibit multistability. Within these circuits, two- and three-gene network motifs are particularly critical to the repertoire of metabolic and developmental pathways. Theoretical models of these circuits, however, often vary parameters such as dissociation constants, transcription rates, and degradation rates without specifying precisely how these parameters are controlled biologically. In this study, we examine the role of effector molecules, which can alter the concentrations of the active transcription factors that control regulation, and are ubiquitous in regulatory processes across many biological settings. We specifically consider allosteric regulation in the context of extending the standard bistable switch to three-gene networks, and explore the rich multistable dynamics exhibited in these architectures as a function of effector concentrations. We then analyze how the dynamics evolve under various interpretations of regulatory circuit mechanics, underlying inducer activity, and perturbations thereof. Notably, the biological mechanism by which we model effector control over dual-function proteins transforms not only the phenotypic trend of dynamic tuning but also the set of available dynamic regimes. In this way, we determine key parameters and regulatory features that drive phenotypic decisions, and offer an experimentally tunable structure for encoding inducible multistable behavior arising from both single and dual-function allosteric transcription factors.
Enzyme kinetics has historically been described by deterministic models, with the Michaelis-Menten (MM) equation serving as a paradigm. However, recent experimental and theoretical advances have made it clear that stochastic fluctuations, particularly at low copy numbers or single-enzyme levels, can profoundly impact reaction outcomes. In this paper, we present a comprehensive view of enzyme kinetics from both deterministic and stochastic perspectives. We begin by deriving the classical Michaelis-Menten equation under the quasi-steady-state assumption (QSSA) and discuss its validity. We then formulate the corresponding stochastic model via the chemical master equation (CME) and illustrate how the Gillespie algorithm can simulate single-molecule events and briefly use Kampen's system-size expansion to justify our simulation methods. Through extended computational analyses -- including variance calculations, phase-plane exploration, and parameter sensitivity -- we highlight how deterministic and stochastic predictions coincide in certain limits but can diverge in small systems. We further incorporate case studies from single-enzyme turnover experiments and cellular contexts to showcase the real-world implications of noise. Taken together, our results underscore the necessity of a multifaceted modeling strategy, whereby one can switch between deterministic methods and stochastic realism to gain a fuller understanding of enzyme kinetics at different scales.
Hadeel Elayan, Samar Elmaadawy, Andrew W. Eckford
et al.
Proteins can be regarded as thermal nanosensors in an intra-body network. Upon being stimulated by Terahertz (THz) frequencies that match their vibrational modes, protein molecules experience resonant absorption and dissipate their energy as heat, undergoing a thermal process. This paper aims to analyze the effect of THz signaling on the protein heat dissipation mechanism. We therefore deploy a mathematical framework based on the heat diffusion model to characterize how proteins absorb THz-electromagnetic (EM) energy from the stimulating EM fields and subsequently release this energy as heat to their immediate surroundings. We also conduct a parametric study to explain the impact of the signal power, pulse duration, and interparticle distance on the protein thermal analysis. In addition, we demonstrate the relationship between the change in temperature and the opening probability of thermally-gated ion channels. Our results indicate that a controlled temperature change can be achieved in an intra-body environment by exciting protein particles at their resonant frequencies. We further verify our results numerically using COMSOL Multiphysics and introduce an experimental framework that assesses the effects of THz radiation on protein particles. We conclude that under controlled heating, protein molecules can serve as hotspots that impact thermally-gated ion channels. Through the presented work, we infer that the heating process can be engineered on different time and length scales by controlling the THz-EM signal input.
We demonstrate a wideband-tunable Q-switched fiber laser exploiting a graphene saturable absorber. We get ∼2 μs pulses, tunable between 1522 and 1555 nm with up to ∼40 nJ energy. This is a simple and low-cost light source for metrology, environmental sensing, and biomedical diagnostics.
We continue to study 5d N = 1 supersymmetric field theories and their compactifications on a circle through brane configurations. We develop a model, which we call (p,q) Webs, which enables simple geometrical computations to reproduce the known results, and facilitates further study. The physical concepts of field theory are transparent in this picture, offering an interpretation for global symmetries, local symmetries, the effective (running) coupling, the Coulomb and Higgs branches, the monopole tensions, and the mass of BPS particles. A rule for the dimension of the Coulomb branch is found by introducing Grid Diagrams. Some known classifications of field theories are reproduced. In addition to the study of the vacuum manifold we develop methods to determine the BPS spectrum. Some states, such as quarks, correspond to instantons inside the 5-brane which we call strips. In general, these may not be identified with (p,q) strings. We describe how a strip can bend out of a 5-brane, becoming a string. A general BPS state corresponds to a Web of strings and strips. For special values of the string coupling a few strips can combine and leave the 5-brane as a string.
Ordering of the frustrated classical Heisenberg model on the triangular lattice with an incommensurate spiral structure is studied under magnetic fields by means of a mean-field analysis and a Monte Carlo simulation. Several types of multiple-q states including the Skyrmion-lattice state is observed in addition to the standard single-q state. In contrast to the Dzyaloshinskii-Moriya interaction driven system, the present model allows both Skyrmions and anti-Skyrmions, together with a new thermodynamic phase where Skyrmion and anti-Skyrmion lattices form a domain state.
We describe the polarization topology of the vector beams emerging from a patterned birefringent liquid crystal plate with a topological charge q at its center (q-plate). The polarization topological structures for different q-plates and different input polarization states have been studied experimentally by measuring the Stokes parameters point-by-point in the beam transverse plane. Furthermore, we used a tuned q=1/2-plate to generate cylindrical vector beams with radial or azimuthal polarizations, with the possibility of switching dynamically between these two cases by simply changing the linear polarization of the input beam.
Abstract:This paper is a direct continuation of [1] where we began the study of the integrable structures in Conformal Field Theory. We show here how to construct the operators ${\bf Q}_{\pm}(\lambda)$ which act in the highest weight Virasoro module and commute for different values of the parameter λ. These operators appear to be the CFT analogs of the Q - matrix of Baxter [2], in particular they satisfy Baxter's famous T- Q equation. We also show that under natural assumptions about analytic properties of the operators as the functions of λ the Baxter's relation allows one to derive the nonlinear integral equations of Destri-de Vega (DDV) [3] for the eigenvalues of the Q-operators. We then use the DDV equation to obtain the asymptotic expansions of the Q - operators at large λ; it is remarkable that unlike the expansions of the T operators of [1], the asymptotic series for Q(λ) contains the “dual” nonlocal Integrals of Motion along with the local ones. We also discuss an intriguing relation between the vacuum eigenvalues of the Q - operators and the stationary transport properties in the boundary sine-Gordon model. On this basis we propose a number of new exact results about finite voltage charge transport through the point contact in the quantum Hall system.
AbstractProtein structure–function relationship serves as the primary learning outcome in any undergraduate biochemistry course. We expanded the protein structure–function exploration, PSFE initiative during COVID‐19 to provide more effective and engaging experience to our undergraduates in biochemistry and independent research courses. Multiple alignments of protein sequences provided crucial insight into sequence conservation across many species and thus allow identification of those sections of the sequence most critical to protein function. We used Anabaena Sensory Rhodopsin, ASR its transducer, ASRT and downstream novel kinase gene products of Anabaena PCC 7120 to seek their alignment with homologs in available database. Pymol served an opportunity to achieve this goal (interactive learning during lab session and stimulation of course content discussion) in interesting ways. The PSFE initiative expansion continued during pandemic using online/hybrid modality. Initially model examples all helical ASR and beta‐sheet ASRT were introduced to connect and integrate our ongoing research interest into classroom activities. Subsequently, undergraduates in biochemistry course were assigned a homolog of model proteins any particular protein of students choice to study and characterize using Pymol in semester. During first phase, each undergraduate worked independently using established guidelines. Student's exploration progress was periodically reviewed in pilot phase with majority of students who perceived it as challenging task successfully completed the assignment. Using the PyMol application to reinforce visual understanding of protein structure was highly satisfying experience that greatly enriched undergraduates understanding and appreciation. This article reports a session from the virtual international 2021 IUBMB/ASBMB workshop, “Teaching Science on BigData.”
Recent studies emphasized the necessity to identify key (human) biological processes and pathways targeted by the Coronaviridae family of viruses, especially SARS-CoV-2. COVID-19 caused up to 33-55\% death rates in COVID-19 patients with malignant neoplasms and Alzheimer's disease. Given this scenario, we identified biological processes and pathways which are most likely affected by COVID-19. The associations between various diseases and human genes known to interact with viruses from Coronaviridae family were obtained from the IntAct COVID-19 data set annotated with DisGeNET data. We constructed the disease-gene network to identify genes that are involved in various comorbid diseased states. Communities from the disease-gene network through Louvain method were identified and functional enrichment through over-representation analysis methodology was used to discover significant biological processes and pathways shared between COVID-19 and other diseases. The IntAct COVID-19 data set comprised of 828 human genes and 10,473 diseases that together constituted nodes in the disease-gene network. Each of the 70,210 edges connects a human gene with an associated disease. The top 10 genes linked to most number of diseases were VEGFA, BCL2, CTNNB1, ALB, COX2, AGT, HLA-A, HMOX1, FGT2 and COMT. The most vulnerable group of patients thus discovered had comorbid conditions such as carcinomas, malignant neoplasms and Alzheimer's disease. Finally, we identified 37 potentially useful biological processes and pathways for improved therapies.
Three-dimensional volumetric imaging of cells allows for in situ visualization, thus preserving contextual insights into cellular processes. Despite recent advances in machine learning methods, morphological analysis of sub-nuclear structures have proven challenging due to both the shallow contrast profile and the technical limitation in feature detection. Here, we present a convolutional neural network, supervised deep learning-based approach which can identify sub-nuclear structures with 90% accuracy. We develop and apply this model to C. elegans gonads imaged using focused ion beam milling combined with scanning electron microscopy resulting in the accurate identification and segmentation of all sub-nuclear structures including entire chromosomes. We discuss in depth the architecture, parameterization, and optimization of the deep learning model, as well as provide evaluation metrics to assess the quality of the network prediction. Lastly, we highlight specific aspects of the model that can be optimized for its broad application to other volumetric imaging data as well as in situ cryo-electron tomography.
SUMMARY The 2007–2009 human Q fever epidemic in The Netherlands attracted attention due to its magnitude and duration. The current epidemic and the historical background of Q fever in The Netherlands are reviewed according to national and international publications. Seroprevalence studies suggest that Q fever was endemic in The Netherlands several decades before the disease was diagnosed in dairy goats and dairy sheep. This was in 2005 and the increase in humans started in 2007. Q fever abortions were registered on 30 dairy goat and dairy sheep farms between 2005 and 2009. A total of 3523 human cases were notified between 2007 and 2009. Proximity to aborting small ruminants and high numbers of susceptible humans are probably the main causes of the human Q fever outbreak in The Netherlands. In general good monitoring and surveillance systems are necessary to assess the real magnitude of Q fever.
The vast majority of work on waveguide-coupled resonators focuses on decreasing losses in the waveguide and coupling region. Here we present fully integrated resonators based on an ultralow-loss Si3N4 waveguide platform. By tailoring the directional coupler excitation to the resonators, we are able to achieve lower loss single-mode coupling to multimode waveguide widths compared to straight bus waveguide directional couplers. This allows us to demonstrate record-high integrated waveguide coupled intrinsic quality factor (Qint) values of 81 million at a 9.65 mm bend radius, with a future direction to both stronger and lower loss waveguide–resonator coupling. This result opens up integration possibilities for narrow linewidth integrated diode lasers, low noise feedback systems, microwave photonic research, and the ultrastable timing reference community.