Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session S04: COVID II: Physics of COVID-19 and PandemicsFocus Recordings Available
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Sponsoring Units: DBIO GMED Chair: Karissa Sanbonmatsu, Los Alamos Natl Lab Room: McCormick Place W-176C |
Thursday, March 17, 2022 8:00AM - 8:12AM |
S04.00001: A noise model allows quantitative interpretation of immune responses at repertoire scale Christopher Joel Russo, Andreas Mayer, Ned S Wingreen Longitudinal repertoire sequencing allows for the measurement of the dynamics of adaptive immune responses at scale. However, disentangling the true dynamics from sampling noise remains a major challenge. Here, we have built a mechanistic statistical model, which we validated against replicate data, that captures the multiple steps in the measurement process. Our model identifies the broad distribution of the number of mRNAs contributed by single cells as a parsimonious explanation for the observed overdispersed read counts. This mechanistic insight naturally leads to efficient computational methods for identifying significantly expanding lymphocyte clones. We apply these methods to investigate T cell clonal dynamics following Yellow Fever vaccination and acute SARS-CoV-2 infection, and contrast our findings with predictions of simple dynamical models. |
Thursday, March 17, 2022 8:12AM - 8:24AM |
S04.00002: Evolution of Covid-like viruses under the influence of therapeutics Pancy Lwin, Moumita Das, Barbara A Jones This paper builds on previous works [1][2] of quasi-species dynamics models that elucidate the life cycle of viruses, and that emphasize the need for the study of therapeutics and their effects on the virus population. These works show the existence of a phase shift between different viral strategies. In the light of the current Covid-19 pandemic, interest in the genetic variability of the virus and its role in developing antivirals and vaccines has been rising. Here, we present our study of the role of therapeutics in three critical phases of the viral life cycle: infection, reproduction process, and fecundity. We found an interesting linear relation of the viral load as a function of the fecundity and a power law with the reproductive rate of the virus. In contrast, the number of viruses in the cell changes in an unexpected way with a change in the infection rate of the virus. Using this simplified model of the virus and its evolution and mutation, we highlight the possible effectiveness of therapeutics based on the part of the life cycle being influenced. |
Thursday, March 17, 2022 8:24AM - 8:36AM |
S04.00003: Spatial and Temporal Stability of UV-C Sources Power Density in 254 nm Fluorescent Tubes Versus 260-280 nm Light-Emitting Diodes for Pathogen Eradication for Reliable UV-C Sterilization Yash V Soni, Kush Patel, Ashwin Suresh, Ajay Taduri, Shreyash Prakash, Nimith Gurijala, Vishesh Amin, Siddarth Jandhyala, Pranav Penmatcha, Aarush Thinakaran, Wesley Peng, Sri Swaminathan, Hemanth Yalahanka, Nicole Herbots Due to the SARS-CoV-2 pandemic and looming threat of other pandemics, stable, safe and reliable eradication of pathogen needs are at an all-time high. UV-C (100-280 nm) irradiation kills quickly pathogens compared to UV-A (315-400 nm), which is 1,000 times less effective and UVB (280-315 nm), 100 times. 254 to 265 nm UV-C optimal for sterilization, damages DNA and RNA in air and water, to a kill rate > 99.99%. But different sources of UV-C vary in the stability of their power density PD. In this work, the PD of identical 253.7 nm UV-C fluorescent tubes are found to average variation of 25% if measured weekly for three short 60 s sterilization cycles. Two out of three UVC tubes lost > 90% output in 4 months. But identical sets of four 260-280 nm UVC LED with similar output average PD variation of < 12.5% and do not decrease after 4 months. 1 mL of calibrated pathogen solutions with 100 M CFU of Lacto B. A. and E. Coli. were applied on sterile slides and irradiated with both types of sources. Conventional epifluorescence microscopy and serial dilutions were used to measure kill rate along with a new technology, InnovaBug™, using epi-fluorescence macroscopy of DNA/RNA over an of 20x 50 mm 2 to detect and count pathogens in min. |
Thursday, March 17, 2022 8:36AM - 8:48AM |
S04.00004: Bad vibrations: Quantum tunnelling in the context of SARS-CoV-2 infection Francesco Petruccione, Betony Adams, Ilya Sinayskiy Quantum biology, the application of quantum theory to the study of living systems, is often focused on charge transfer. The first evidence for quantum effects in enzymes focused on tunnelling and a great deal of effort has gone into investigating the movement of energy and charge in photosynthesis. Environment assisted tunnelling has also been suggested to be the mechanism by which olfaction works. We consider whether the progress made in these contexts might be applied to the context of SARS-CoV-2 infection. We propose that quantum biology might offer essential new insights into the problem, especially with regards to the important first step of virus-host invasion. ACE2 enzymes are implicated in the invasion of host cells by the SARS-CoV-2 virus. Receptors such as olfactory receptors also appear to be disrupted by COVID-19. Building on these observations we investigate the evidence that quantum tunnelling might be important in the context of infection with SARS-CoV-2. We illustrate this with a simple open quantum systems model relating the vibronic mode of the viral spike protein to the likelihood of charge transfer in an idealised receptor. Our results demonstrate distinct parameter regimes in which spike protein vibronic mode enhances electron transport. |
Thursday, March 17, 2022 8:48AM - 9:00AM |
S04.00005: Functional proteins synthesis, refolding and surface active palladium nano-thin-film sensors development for virus sensing and anti-infectious drugs screening Chia-Ching Chang, Chia-Yu Chang, Lik-Voon Kiew, Sheng-Yu Huang, Pei-Wen Wang, Yen-Chen Chen, Yi-Xuan Huang, Shin-Ru Shih, Dar-Bin Shieh In COVID-19 pandemics era, a rapid, specific and sensitive sensing platform is highly desired. By combining molecular biology, thermodynamics nanotechnology processes, both virus spike proteins and human ACE2 receptors have been recombinant synthesized and refolded into functional state via over-critical refolding process. Furthermore, a 20 nm in thickness, a surface-active Pd nano-thin-film (NTF) on PET substrate has been developed by pulse DC sputtering process. This Pd nano-thin film contained unique nano-islands and nano-edges. These nanostructures made bio-molecules which bound to the working electrodes directly within 20 mins. Due to the unique Pd nano-thin film structure the Raman signal of protein sample with 0.8 μg can be detected. This ultrasensitive detection of Raman spectroscopy signals at low sample amounts in the current analysis may be attributed to the induction of a local surface plasmon resonance (LSPR) and an enhanced surface electric field phenomena. Furthermore,this unique Pd-NTF could be used as electrochemical spectroscopy probe. By using this sensing system both wild type and mutant SARS CoV-2 virus can be detected within 21 min. Furthermore, the drugs which can block the virus infections can be screened too. The limit of detection (LOD) of these biosensors were as low as 1 ~4 μg per-test in 1 microliter. At the same time, these sensors can also be used to screen other infectious disease and drugs. |
Thursday, March 17, 2022 9:00AM - 9:12AM |
S04.00006: Rational policy design for epidemics Simon K Schnyder, John J Molina, Ryoichi Yamamoto, Matthew S Turner We study the optimal control of an epidemic by governments and individuals using a Hamiltonian approach. Assuming that government and individuals optimise (potentially different) value functions, we show how subsidies and taxes can be used by governments to exactly align individuals’ decision making with government preferences. To capture the limited capacity of the health care system we include a term that increases sharply when the fraction of infected exceeds a threshold. |
Thursday, March 17, 2022 9:12AM - 9:24AM |
S04.00007: Nash Neural Networks John J Molina, Simon K Schnyder, Matthew S Turner, Ryoichi Yamamoto We introduce Nash Neural Networks (N3) to learn the cost functions that determine how rational individuals behave within a differential game with a Nash equilibrium. The N3 are constructed to respect the Hamiltonian equations that would be derived from the (unknown) utility, together with any dynamical constraints on the state variables of the system. For this, we build on recently developed Lagrangian/Hamiltonian Neural Networks, which have successfully been used to learn Lagrangians/Hamiltonians from dynamical data, while respecting the symmetries and conservation laws of the system. Thus, models trained on our N3 respect the game dynamics and are able to learn the utility in an unsupervised manner. We apply these N3 to an epidemic, in order to infer how the individuals react and contribute to the evolution of the disease, using social distancing as a proxy for the control variable in the underlying utility optimization problem. In this study, we focus on artificial data generated from an explicit solution of the Hamiltonian equations for the optimal control of an SIR model. We use the N3 formalism to recover the hidden utility underlying these solutions. We believe this approach will have wider applications for inferring utilities from behavioral data. |
Thursday, March 17, 2022 9:24AM - 9:36AM |
S04.00008: A new approach for extracting network information from protein dynamics Jenny Y Liu, Sinan Keten, Luis N A Increased knowledge about protein structures has increased interest in molecular dynamics simulations to study function. To analyze these simulations, proteins are modeled as networks to take advantage of well-developed methods from network science. Protein networks are often constructed from correlation measures. Yet, it is clear in network science that solving the inverse problem reconstructs network interactions. Thus, we apply this inverse approach to the dynamics of protein dihedral angles, a system of internal coordinates that avoids the structural alignment artifacts. Using the well-characterized adhesion protein, FimH, we show that our method identifies networks that are physically interpretable and robust. In FimH, we detect differences in inferred networks consistent with the allosteric pathway sites. Next, we use our approach to detect dynamical differences, despite structural similarity, for two other adhesion proteins: Siglec-8 in the immune system and the SARS-CoV-2 spike protein. Our approach enables us, for example, to validate a new mechanism to explain the stability of a Siglec-8 binding pocket loop. Thus, using an inverse approach to extract a protein network makes it tractable to apply analysis techniques, e.g. community detection, without edge pruning. |
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