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Similar activity patterns may arise from model neural networks with distinct coupling properties and individual unit dynamics. These similar patterns may, however, respond differently to parameter variations and, specifically, to tuning of inputs that represent control signals. In this work, we analyze the responses resulting from modulation of a localized input in each of three classes of model neural networks that have been recognized in the literature for their capacity to produce robust three-phase rhythms: coupled fast-slow oscillators, near-heteroclinic oscillators, and threshold-linear networks. Triphasic rhythms, in which each phase consists of a prolonged activation of a corresponding subgroup of neurons followed by a fast transition to another phase, represent a fundamental activity pattern observed across a range of central pattern generators underlying behaviors critical to survival, including respiration, locomotion, and feeding. To perform our analysis, we extend the recently developed local timing response curve (lTRC), which allows us to characterize the timing effects due to perturbations, and we complement our lTRC approach with model-specific dynamical systems analysis. Interestingly, we observe disparate effects of similar perturbations across distinct model classes. Thus, this work provides an analytical framework for studying control of oscillations in nonlinear dynamical systems, and may help guide model selection in future efforts to study systems exhibiting triphasic rhythmic activity., Comment: 49 pages, 21 figures, 8 tables

Background Colorectal cancer (CRC) patients with different molecular phenotypes, including microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and somatic mutations in BRAF and KRAS gene, vary in treatment response and prognosis. However, molecular phenotyping under adequate quality control in a community-based setting may be difficult. We aimed to build the nomograms based on easily accessible clinicopathological characteristics to predict molecular phenotypes. Methods Three hundred and six patients with pathologically confirmed stage I-IV CRC were included in the cohort. The assays for MSI, CIMP, and mutations in BRAF and KRAS gene were performed using resected tumor samples. The candidate predictors were identified from clinicopathological variables using multivariate Logistic regression analyses to construct the nomograms that could predict each molecular phenotype. Results The incidences of MSI, CIMP, BRAF mutation and KRAS mutation were 25.3% (72/285), 2.5% (7/270), 3.4% (10/293), and 34.8% (96/276) respectively. In the multivariate Logistic analysis, poor differentiation and high neutrophil/lymphocyte ratio (NLR) were independently associated with MSI; poor differentiation, high NLR and high carcinoembryonic antigen/tumor size ratio (CSR) were independently associated with CIMP; poor differentiation, lymphovascular invasion and high CSR were independently associated with BRAF mutation; poor differentiation, proximal tumor, mucinous tumor and high NLR were independently associated with KRAS mutation. Four nomograms for MSI, CIMP, BRAF mutation and KRAS mutation were developed based on these independent predictors, the C-indexes of which were 61.22% (95% CI: 60.28-62.16%), 95.57% (95% CI: 95.20-95.94%), 83.56% (95% CI: 81.54-85.58%), and 69.12% (95% CI: 68.30-69.94%) respectively. Conclusion We established four nomograms using easily accessible variables that could well predict the presence of MSI, CIMP, BRAF mutation and KRAS mutation in CRC patients.

Size-resolved hygroscopic growth factors of urban aerosol during a haze episode were measured using a Humidified Tandem Differential Mobility Analyzer (HTDMA) (gm(RH)). These factors were also derived from size-resolved particulate chemical composition combined with the κ-Kohler theory (gκ(RH)) and the thermodynamic model ISORROPIA-II running in forward mode (giso-f(RH)) and reverse mode (giso-r(RH)), respectively. In terms of agreement among these hygroscopic growth factors, gκ(RH) matched gm(RH) best, followed by giso-r(RH). In contrast, giso-f(RH) demonstrated a poorer agreement with gm(RH). The good consistency among gm(RH), gκ(RH), and giso-r(RH) was because they only focus on the physical hygroscopic process, whereas giso-f(RH) contains not only the direct influence of relative humidity (RH) on particle size but also the influence of gaseous precursor on the particle chemical composition, which indirectly affects the hygroscopicity of the particles. In this sense, size-resolved gκ(RH) and giso-r(RH) in a wide size range are more adequate to investigate the impact of RH on light scattering and aerosol radiative forcing. At RH = 80%, gκ(RH) for accumulation mode particles was 1.30–1.45 on polluted days and higher than that on clean days (1.2–1.3). Whereas on both polluted and clean days, gκ(RH) of ultrafine and coarse mode particles were generally lower than 1.25. The strong hygroscopicity of accumulation mode particles observed on polluted days can deteriorate visibility due to their high extinction efficiency.

Homeostasis occurs in a control system when a quantity remains approximately constant as a parameter, representing an external perturbation, varies over some range. Golubitsky and Stewart (J Math Biol 74(1-2):387-407, 2017) developed a notion of infinitesimal homeostasis for equilibrium systems using singularity theory. Rhythmic physiological systems (breathing, locomotion, feeding) maintain homeostasis through control of large-amplitude limit cycles rather than equilibrium points. Here we take an initial step to study (infinitesimal) homeostasis for limit-cycle systems in terms of the average of a quantity taken around the limit cycle. We apply the "infinitesimal shape response curve" (iSRC) introduced by Wang et al. (SIAM J Appl Dyn Syst 82(7):1-43, 2021) to study infinitesimal homeostasis for limit-cycle systems in terms of the mean value of a quantity of interest, averaged around the limit cycle. Using the iSRC, which captures the linearized shape displacement of an oscillator upon a static perturbation, we provide a formula for the derivative of the averaged quantity with respect to the control parameter. Our expression allows one to identify homeostasis points for limit cycle systems in the averaging sense. We demonstrate in the Hodgkin-Huxley model and in a metabolic regulatory network model that the iSRC-based method provides an accurate representation of the sensitivity of averaged quantities.

Air pollution is the result of enormous emissions and unfavorable meteorological conditions. The role of meteorology, particularly extremely unfavorable meteorological events (EUMEs), in processing atmospheric PM

We investigate a simple model for motor pattern generation that combines central pattern generator (CPG) dynamics with a sensory feedback (FB) mechanism. Our CPG comprises a half-center oscillator with conductance-based Morris-Lecar model neurons. Output from the CPG drives a push-pull motor system with biomechanics based on experimental data. A sensory feedback conductance from the muscles allows modulation of the CPG activity. We consider parameters under which the isolated CPG system has either "escape" or "release" dynamics, and we study both inhibitory and excitatory feedback conductances. We find that increasing the FB conductance relative to the CPG conductance makes the system more robust against external perturbations, but more susceptible to internal noise. Conversely, increasing the CPG conductance relative to the FB conductance has the opposite effects. We find that the "closed-loop" system, with sensory feedback in place, exhibits a richer repertoire of behaviors than the "open-loop" system, with motion determined entirely by the CPG dynamics. Moreover, we find that purely feedback-driven motor patterns, analogous to a chain reflex, occur only in the inhibition-mediated system. Finally, for pattern generation systems with inhibition-mediated sensory feedback, we find that the distinction between escape- and release-mediated CPG mechanisms is diminished in the presence of internal noise. Our observations support an anti-reductionist view of neuromotor physiology: Understanding mechanisms of robust motor control requires studying not only the central pattern generator circuit in isolation, but the intact closed-loop system as a whole.

Air pollution is the result of enormous emissions and unfavorable meteorological conditions. The role of meteorology, particularly extremely unfavorable meteorological events (EUMEs), in processing atmospheric PM2.5 pollution has not been fully addressed. This work examined the variations of PM2.5 mass and its chemical components associated with various meteorological parameters and three EUMEs based on meteorological observations and analysis combined with one-year long in situ measurement in 2018 in the suburban area of Tianjin, China. Analysis shows that the polluted days in 2018 were mostly related to the increase in sulfate, nitrate, and ammonium (SNA). Temperature between -2 to 13 °C is more favorable for the formation of SNA, while high temperature exceeding 28 °C is favorable for the formation of organic carbon and sulfate. Most of the ions and carbon components showed significant increase in concentrations when relative humidity exceeded 80%. The maximum decreasing rate of PM2.5 concentrations due to increase in wind speed and planetary boundary height could be 15.35 μg m-3 (m s-1)-1, and 34.37 μg m-3 (100 m)-1, respectively. EUMEs showed significant impacts on PM2.5 components, in which PM2.5 concentrations showed the most significant increase under temperature inversion (TI) events, and surface-based TI (SBTI) events usually have much stronger impacts on PM2.5 concentrations than elevated TI (ELTI). Nitrate was found to be the most sensitive component to EUMEs, especially under multiple EUMEs. The synthetic effects of multiple EUMEs could result in an increase of nitrate by 35.53 μg m-3 (523.3%). In addition, OC and sulfate are more sensitive to heat wave events. Our analysis provides improved understanding of the formation of PM2.5 pollution with respect to meteorology, particularly EUMEs. Based on such information, more attention may be needed on the collaborative prediction of EUMEs and air pollution episodes.

Based on published literature and typical profiles from the Nankai University source library, a total of 3326 chemical profiles of the main primary sources of ambient particulate matter (PM) across China from 1987 to 2017 are investigated and reviewed to trace the evolution of their main components and identify the main influencing factors concerning their evolution. In general, the source chemical profiles are varied with respect to their sources and are influenced by different sampling methods. The most complicated profiles are likely attributed to coal combustion (CC) and industrial emissions (IE). The profiles of vehicle emissions (VE) are dominated by organic carbon (OC) and elemental carbon (EC), and vary due to the changing standards of sulfur and additives in gasoline and diesel as well as the sampling methods used. In addition to the sampling methods used, the profiles of biomass burning (BB) and cooking emissions (CE) are also impacted by the different biofuel categories and cooking types, respectively. The variations of the chemical profiles of different sources, and the homogeneity of the subtype source profiles within the same source category are examined using uncertainty analysis and cluster analysis. As a result, a relatively large variation is found in the source profiles of CC, VE, IE, and BB, indicating that these sources urgently require the establishment of local profiles due to their high uncertainties. The results presented highlight the need for further investigation of more specific markers (e.g., isotopes, organic compounds, and gaseous precursors), in addition to routinely measured components, in order to properly discriminate sources. Although the chemical profiles of the main sources have been previously reported in the literature, it should be noted that some of these chemical profiles are currently out of date and need to be updated immediately. Additionally, in the future, specific focus should be placed on the source profile subtypes, especially with respect to local IE in China.