Cancer progression is an evolutionary process shaped by both deterministic and stochastic forces. Multi-region and single-cell sequencing of tumors enable high-resolution reconstruction of the ...mutational history of each tumor and highlight the extensive diversity across tumors and patients. Resolving the interactions among mutations and recovering recurrent evolutionary processes may offer greater opportunities for successful therapeutic strategies. To this end, we present a novel probabilistic framework, called TreeMHN, for the joint inference of exclusivity patterns and recurrent trajectories from a cohort of intra-tumor phylogenetic trees. Through simulations, we show that TreeMHN outperforms existing alternatives that can only focus on one aspect of the task. By analyzing datasets of blood, lung, and breast cancers, we find the most likely evolutionary trajectories and mutational patterns, consistent with and enriching our current understanding of tumorigenesis. Moreover, TreeMHN facilitates the prediction of tumor evolution and provides probabilistic measures on the next mutational events given a tumor tree, a prerequisite for evolution-guided treatment strategies.
Stretchable strain sensors have aroused great interest for their application in human activity recognition, health monitoring, and soft robotics. For various scenarios involving the application of ...different strain ranges, specific sensitivities need to be developed, due to a trade‐off between sensor sensitivity and stretchability. Traditional stretchable strain sensors are developed based on conductive sensing materials and still lack the function of customizable sensitivity. A novel strategy of mechanocombinatorics is proposed to screen the sensor sensitivity based on mechanically heterogeneous substrates. Strain redistribution over substrates is optimized by mechanics and structure parameters, which gives rise to customizable sensitivity. As a proof of concept, a local illumination method is used to fabricate heterogeneous substrates with customizable mechanics and structure parameters. A library of mechanocombinatorial strain sensors is created for extracting the specific sensitivity. Thus, not only is an effective strategy for screening of sensor sensitivity demonstrated, but a contribution to the mechanocombinatorial strategy for personalized stretchable electronics is also made.
A novel strategy of mechanocombinatorics is developed to screen the sensitivity of stretchable strain sensors. Mechanically heterogeneous substrates, defined as substrates comprising low and high modulus regions, are incorporated into strain sensors. Strain distributions over substrates are controlled by combined parameters of mechanics and structure. A library of strain sensors based on heterogeneous substrates is created for screening of sensitivity.
Accurate glioma grading before surgery is of the utmost importance in treatment planning and prognosis prediction. But previous studies on magnetic resonance imaging (MRI) images were not effective ...enough. According to the remarkable performance of convolutional neural network (CNN) in medical domain, we hypothesized that a deep learning algorithm can achieve high accuracy in distinguishing the World Health Organization (WHO) low grade and high grade gliomas.
One hundred and thirteen glioma patients were retrospectively included. Tumor images were segmented with a rectangular region of interest (ROI), which contained about 80% of the tumor. Then, 20% data were randomly selected and leaved out at patient-level as test dataset. AlexNet and GoogLeNet were both trained from scratch and fine-tuned from models that pre-trained on the large scale natural image database, ImageNet, to magnetic resonance images. The classification task was evaluated with five-fold cross-validation (CV) on patient-level split.
The performance measures, including validation accuracy, test accuracy and test area under curve (AUC), averaged from five-fold CV of GoogLeNet which trained from scratch were 0.867, 0.909, and 0.939, respectively. With transfer learning and fine-tuning, better performances were obtained for both AlexNet and GoogLeNet, especially for AlexNet. Meanwhile, GoogLeNet performed better than AlexNet no matter trained from scratch or learned from pre-trained model.
In conclusion, we demonstrated that the application of CNN, especially trained with transfer learning and fine-tuning, to preoperative glioma grading improves the performance, compared with either the performance of traditional machine learning method based on hand-crafted features, or even the CNNs trained from scratch.
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•The honeycomb patterns of varied sizes are fabricated to evaluate bacterial responses.•The selective adhesion of the bacteria is observed on the honeycomb patterns.•The 1μm honeycomb ...patterns displayed remarkable anti-bacterial property.•Mechanism 1: the 1μm patterns provide less favorable adhesion sites to bacteria.•Mechanism 2: the 1μm patterns provide stronger physical confinement to bacteria.
It is a great challenge to construct a persistent bacteria-resistant surface even though it has been demonstrated that several surface features might be used to control bacterial behavior, including surface topography. In this study, we develop micro-scale honeycomb-like patterns of different sizes (0.5–10μm) as well as a flat area as the control on a single platform to evaluate the bacterial adhesion and growth. Bacteria strains, Escherichia coli and Staphylococcus aureus with two distinct shapes (rod and sphere) are cultured on the platforms, with the patterned surface-up and surface-down in the culture medium. The results demonstrate that the 1μm patterns remarkably reduce bacterial adhesion and growth while suppressing bacterial colonization when compared to the flat surface. The selective adhesion of the bacterial cells on the patterns reveals that the bacterial adhesion is cooperatively mediated by maximizing the cell-substrate contact area and minimizing the cell deformation, from a thermodynamic point of view. Moreover, study of bacterial behaviors on the surface-up vs. surface-down samples shows that gravity does not apparently affect the spatial distribution of the adherent cells although it indeed facilitates bacterial adhesion. Furthermore, the experimental results suggest that two major factors, i.e. the availability of energetically favorable adhesion sites and the physical confinements, contribute to the anti-bacterial nature of the honeycomb-like patterns.
The global pandemic of coronavirus disease 2019 (COVID-19) is a disaster for human society. A convenient and reliable neutralization assay is very important for the development of vaccines and novel ...drugs. In this study, a G protein-deficient vesicular stomatitis virus (VSVdG) bearing a truncated spike protein (S with C-terminal 18 amino acid truncation) was compared to that bearing the full-length spike protein of SARS-CoV-2 and showed much higher efficiency. A neutralization assay was established based on VSV-SARS-CoV-2-Sdel18 pseudovirus and hACE2-overexpressing BHK21 cells (BHK21-hACE2 cells). The experimental results can be obtained by automatically counting the number of EGFP-positive cells at 12 h after infection, making the assay convenient and high-throughput. The serum neutralizing titer measured by the VSV-SARS-CoV-2-Sdel18 pseudovirus assay has a good correlation with that measured by the wild type SARS-CoV-2 assay. Seven neutralizing monoclonal antibodies targeting the receptor binding domain (RBD) of the SARS-CoV-2 S protein were obtained. This efficient and reliable pseudovirus assay model could facilitate the development of new drugs and vaccines.
In this work, carbon fiber (CF)-reinforced polypropylene (PP) composites were prepared by melt processing with maleic anhydride-grafted polypropylene as compatibilizer. The mechanical properties and ...crystallization behaviors of the resulting composites were investigated detailedly. The interfacial compatibility of CRP composites was fine and CF dispersed in PP matrix homogeneously. CF played a nucleation agent for the crystallization of PP. The crystallization temperature increased with increasing CF content. Carbon fibers could act as the heterogeneous nucleation agent for PP, which would decrease the activation energy of crystallization, shorten the crystallization time and raise the crystallization rate dramatically. The original spherulite morphology of neat PP was also destroyed by CF. CF exhibited obvious reinforcing effects on PP matrix and improved the mechanical properties of PP materials. The tensile strength and flexural strength were increased over 100% with 20 mass% CF.
The genus Alisma contains 11 species distributed worldwide, of which at least two species (A. orientale Sam. Juzep. and A. plantago‐aquatica Linn.) have been used as common herbal medicines. ...Secondary metabolites obtained from the genus Alisma are considered to be the material basis for the various biological functions and medicinal applications. In this review, we mainly focused on the recent investigations of secondary metabolites from plants of the genus Alisma and their biological activities, with the highlighting on the diversity of the chemical structures, the biosynthesis of interesting secondary metabolites, the biological activities, and the relationships between structures and bioactivities.
An ensemble of surrogate models with high robustness and accuracy can effectively avoid the difficult choice of surrogate model. However, most of the existing ensembles of surrogate models are ...constructed with static sampling methods. In this paper, we propose an ensemble of adaptive surrogate models by applying adaptive sampling strategy based on expected local errors. In the proposed method, local error expectations of the surrogate models are calculated. Then according to local error expectations, the new sample points are added within the dominating radius of the samples. Constructed by the RBF and Kriging models, the ensemble of adaptive surrogate models is proposed by combining the adaptive sampling strategy. The benchmark test functions and an application problem that deals with driving arm base of palletizing robot show that the proposed method can effectively improve the global and local prediction accuracy of the surrogate model.
The substitution of Zn in hydroxyapatite (HA) crystals was examined via comprehensive characterization techniques. Nanosized HA crystals were synthesized by the wet chemical method in aqueous ...solutions including various amounts of Zn ions. X-ray fluorescent spectroscopy was used to examine the amount of Zn in the HA precipitates. Scanning electron microscopy and high-resolution transmission electron microscopy were employed to examine the effects of Zn on the morphology and crystal size of the precipitates. Conventional powder X-ray diffraction and the Rietveld refinement method revealed the apatite lattice parameters and phase changes with the inclusion of Zn. The results indicated that Zn ions partially substituted for Ca ions in the apatite structure. They were not simply adsorbed on the apatite surface or in the amorphous phase. The precipitates maintained the apatite phase up to a Zn:(Zn
+
Ca) ratio of 15–20
mol.% in the solution. Pure HA was well crystallized and the crystals had regular shapes, whereas the Zn-substituted apatite crystals became irregular and formed agglomerates. The lattice parameters,
a and
c, decreased at a Zn:(Zn
+
Ca) ratio of 10
mol.%.
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