Approximate parameter inference in systems biology using gradient matching: a comparative evaluation

Background

A challenging problem in current systems biology is that of parameter inference in biological pathways expressed as coupled ordinary differential equations (ODEs). Conventional methods that repeatedly numerically solve the ODEs have large associated computational costs. Aimed at reducing this cost, new concepts using gradient matching have been proposed, which bypass the need for numerical integration. This paper presents a recently established adaptive gradient matching approach, using Gaussian processes (GPs), combined with a parallel tempering scheme, and conducts a comparative evaluation with current state-of-the-art methods used for parameter inference in ODEs. Among these contemporary methods is a technique based on reproducing kernel Hilbert spaces (RKHS). This has previously shown promising results for parameter estimation, but under lax experimental settings. We look at a range of scenarios to test the robustness of this method. We also change the approach of inferring the penalty parameter from AIC to cross validation to improve the stability of the method.

Methods

Methodology for the recently proposed adaptive gradient matching method using GPs, upon which we build our new method, is provided. Details of a competing method using RKHS are also described here.

Results

We conduct a comparative analysis for the methods described in this paper, using two benchmark ODE systems. The analyses are repeated under different experimental settings, to observe the sensitivity of the techniques.

Conclusions

Our study reveals that for known noise variance, our proposed method based on GPs and parallel tempering achieves overall the best performance. When the noise variance is unknown, the RKHS method proves to be more robust.

     

Phenotypic Characteristics and Fatty Acid Composition of Seeds from Different Herbaceous Peony Species Native to China

Herbaceous peony has been widely cultivated in China due to its substantial ornamental and medicinal value. In the present study, the phenotypic characteristics, total fatty acid (FA) content, and nine FA compositions of herbaceous peony seeds from 14 populations belonging to six species and one subspecies were determined by normal test and gas chromatography/mass spectrometry (GC/MS). The results showed that the phenotypic characteristics of seeds varied dramatically among species. The concentrations of five major FAs in seed oils were as follows: linoleic acid (173.95–236.51 μg/mg), linolenic acid (227.82–302.71 μg/mg), oleic acid (135.32–208.81 μg/mg), stearic acid (6.52–11.7 μg/mg), and palmitic acid (30.67–47.64 μg/mg). Correlation analysis demonstrated that oleic acid had the highest partial correlation coefficient with total FAs and might be applied to develop a model of phenotypic characteristics. FAs were significantly influenced by the following environmental factors: latitude, elevation, and annual average temperature. Based on the FA levels in the seed oils, clustering analysis divided 14 populations into two clusters. It was found that the average contents of oleic acid, linoleic acid, and total FAs in cluster I (147.16 μg/mg, 200.31 μg/mg, and 671.24 μg/mg, respectively) were significantly lower than those in cluster II (196.65 μg/mg, 220.16 μg/mg, and 741.78 μg/mg, respectively). Cluster I was perfectly consistent with subsect. Foliolatae, while cluster II was in good agreement with subsect. Dissectifoliae. Therefore, the FA composition of wild herbaceous peony seed oil might be used as a chemotaxonomic marker.     

High Energy Density Polymer Dielectrics Interlayered by Assembled Boron Nitride Nanosheets

Polymer dielectrics such as poly(vinylidene fluoride) (PVDF) have drawn tremendous attention in high energy density capacitors because of their high dielectric constant and ease of processing. However, the discharged energy density attained with these materials is restrained by the inferior breakdown strength and electric resistivity. Herein, PVDF composite films with a nanosized interlayer of assembled boron nitride nanosheets (BNNSs) that is aligned along the in‐plane direction are prepared through a simple layer‐by‐layer solution‐casting process. Compared to the pristine PVDF, the composite films show remarkably suppressed leakage current, resulting in a high breakdown strength and a superior energy density which are 136% and 275%, respectively, that of the pristine PVDF. The experimental results and computational simulations reveal that the compact and successive interlayer of assembled BNNSs can largely mitigate the local field distortion and block the propagation of electrical treeing, which is advantageous over the conventional dielectric polymer nanocomposites. Notably, unlike the previous dielectric polymer nanocomposites that are usually incorporated with a high volume fraction of nanofillers, i.e., 5–10 vol%, the present composites contain only an extremely low content of nanfillers, e.g., 0.16 vol%. These findings offer a novel paradigm for fabricating high energy density and high efficiency polymer dielectrics.     

An Efficient Separator with Low Li‐Ion Diffusion Energy Barrier Resolving Feeble Conductivity for Practical Lithium–Sulfur Batteries

Due to unprecedented features including high‐energy density, low cost, and light weight, lithium–sulfur batteries have been proposed as a promising successor of lithium‐ion batteries. However, unresolved detrimental low Li‐ion transport rates in traditional carbon materials lead to large energy barrier in high sulfur loading batteries, which prevents the lithium–sulfur batteries from commercialization. In this report, to overcome the challenge of increasing both the cycling stability and areal capacity, a metallic oxide composite (NiCo₂O₄@rGO) is designed to enable a robust separator with low energy barrier for Li‐ion diffusion and simultaneously provide abundant active sites for the catalytic conversion of the polar polysulfides. With a high sulfur‐loading of 6 mg cm^?2 and low sulfur/electrolyte ratio of 10, the assembled batteries deliver an initial capacity of 5.04 mAh cm^?2 as well as capacity retention of 92% after 400 cycles. The metallic oxide composite NiCo₂O₄@rGO/PP separator with low Li‐ion diffusion energy barrier opens up the opportunity for lithium–sulfur batteries to achieve long‐cycle, cost‐effective operation toward wide applications in electric vehicles and electronic devices.     

2D Layered Double Hydroxides for Oxygen Evolution Reaction: From Fundamental Design to Application

The oxygen evolution reaction (OER) has aroused extensive interest from materials scientists in the past decade by virtue of its great significance in the energy storage/conversion systems such as water splitting, rechargeable metal–air batteries, carbon dioxide (CO₂) reduction, and fuel cells. Among all the materials capable of catalyzing OER, layered double hydroxides (LDHs) stand out as one of the most effective electrocatalysts owing to their compositional and structural flexibility as well as the tenability and the simplicity of their preparation process. For this reason, numerous efforts have been dedicated to adjusting the structure, forming the well‐defined morphology, and developing the preparation methods of LDHs to promote their electrocatalytic performance. In this article, recent advances in the rational design of LDH‐based electrocatalysts toward OER are summarized. Specifically, various tactics for the synthetic methods, as well as structural and composition regulations of LDHs, are further highlighted, followed by a discussion on the influential factors for OER performance. Finally, the remaining challenges to investigate and improve the catalyzing ability of LDH electrocatalysts are stated to indicate possible future development of LDHs.     

Leveraging plant hydraulics to yield predictive and dynamic plant leaf allocation in vegetation models with climate change

Plant functional traits provide a link in process‐based vegetation models between plant‐level physiology and ecosystem‐level responses. Recent advances in physiological understanding and computational efficiency have allowed for the incorporation of plant hydraulic processes in large‐scale vegetation models. However, a more mechanistic representation of water limitation that determines ecosystem responses to plant water stress necessitates a re‐evaluation of trait‐based constraints for plant carbon allocation, particularly allocation to leaf area. In this review, we examine model representations of plant allocation to leaves, which is often empirically set by plant functional type‐specific allometric relationships. We analyze the evolution of the representation of leaf allocation in models of different scales and complexities. We show the impacts of leaf allocation strategy on plant carbon uptake in the context of recent advancements in modeling hydraulic processes. Finally, we posit that deriving allometry from first principles using mechanistic hydraulic processes is possible and should become standard practice, rather than using prescribed allometries. The representation of allocation as an emergent property of scarce resource constraints is likely to be critical to representing how global change processes impact future ecosystem dynamics and carbon fluxes and may reduce the number of poorly constrained parameters in vegetation models.     

Structure-activity relationships study of neolamellarin A and its analogues as hypoxia inducible factor-1 (HIF-1) inhibitors

The novel marine pyrrole alkaloid neolamellarin A derived from sponge has been shown to inhibit hypoxia-induced HIF-1 activity. In this work, we designed and synthesized neolamellarin A and its series of derivatives by a convergent synthetic strategy. The HIF-1 inhibitory activity and cytotoxicity of these compounds were evaluated in Hela cells by dual-luciferase reporter gene assay and MTT assay, respectively. The results showed that neolamellarin A 1 (IC₅₀ = 10.8 ± 1.0 μM) and derivative 2b (IC₅₀ = 11.9 ± 3.6 μM) had the best HIF-1 inhibitory activity and low cytotoxicity. Our SAR research focused on the effects of key regions aliphatic carbon chain length, aromatic ring substituents and C-7 substituent on biological activity, providing a basis for the subsequent research on the development of novel pyrrole alkaloids as HIF-1 inhibitors and design of small molecule probes for target protein identification.     

Design,synthesis and evaluation of novel (S)-tryptamine derivatives containing an allyl group and an aryl sulfonamide unit as anticancer agents

A series of (S)-tryptamine derivatives containing an allyl group and an aryl sulfonamide unit were designed, synthesized and evaluated for their potential application as anticancer agents. The structures of the synthesized compounds were characterized by ¹H NMR, ¹³C NMR and ESI-MS spectral analyses. The target compounds were evaluated for their in vitro cytotoxicity against HepG2, HeLa, CNE1 and A549 human cancer cell lines. Some of the synthesized compounds showed moderate to good anticancer activities against four selected cancer cell lines, among of which 6ag was found to be the most active analogue possessing IC₅₀ values 16.5–18.7?μM. Further mechanism studies revealed that compound 6ag could significantly induce HepG2 cell cycle arrest at G1 phase, promote cell apoptosis, and inhibit the colony formation as well.