Accurate prediction of discontinuous crack paths in random porous media via a generative deep learning model.

Pore structures provide extra freedoms for the design of porous media, leading to desirable properties, such as high catalytic rate, energy storage efficiency, and specific strength. This unfortunately makes the porous media susceptible to failure. Deep understanding of the failure mechanism in microstructures is a key to customizing high-performance crack-resistant porous media. However, solving the fracture problem of the porous materials is computationally intractable due to the highly complicated configurations of microstructures. To bridge the structural configurations and fracture responses of random porous media, a unique generative deep learning model is developed. A two-step strategy is proposed to deconstruct the fracture process, which sequentially corresponds to elastic deformation and crack propagation. The geometry of microstructure is translated into a scalar of elastic field as an intermediate variable, and then, the crack path is predicted. The neural network precisely characterizes the strong interactions among pore structures, the multiscale behaviors of fracture, and the discontinuous essence of crack propagation. Crack paths in random porous media are accurately predicted by simply inputting the images of targets, without inputting any additional input physical information. The prediction model enjoys an outstanding performance with a prediction accuracy of 90.25% and possesses a robust generalization capability. The accuracy of the present model is a record so far, and the prediction is accomplished within a second. This study opens an avenue to high-throughput evaluation of the fracture behaviors of heterogeneous materials with complex geometries.

Hippo cooperates with p53 to maintain foregut homeostasis and suppress the malignant transformation of foregut basal progenitor cells.

Basal progenitor cells serve as a stem cell pool to maintain the homeostasis of the epithelium of the foregut, including the esophagus and the forestomach. Aberrant genetic regulation in these cells can lead to carcinogenesis, such as squamous cell carcinoma (SCC). However, the underlying molecular mechanisms regulating the function of basal progenitor cells remain largely unknown. Here, we use mouse models to reveal that Hippo signaling is required for maintaining the homeostasis of the foregut epithelium and cooperates with p53 to repress the initiation of foregut SCC. Deletion of Mst1/2 in mice leads to epithelial overgrowth in both the esophagus and forestomach. Further molecular studies find that Mst1/2-deficiency promotes epithelial growth by enhancing basal cell proliferation in a Yes-associated protein (Yap)-dependent manner. Moreover, Mst1/2 deficiency accelerates the onset of foregut SCC in a carcinogen-induced foregut SCC mouse model, depending on Yap. Significantly, a combined deletion of Mst1/2 and p53 in basal progenitor cells sufficiently drives the initiation of foregut SCC. Therefore, our studies shed light on the collaborative role of Hippo signaling and p53 in maintaining squamous epithelial homeostasis while suppressing malignant transformation of basal stem cells within the foregut.

Mechanics Modeling of Hierarchical Wrinkle Structures from the Sequential Release of Prestrain.

Three-dimensional (3D) hierarchical wrinkles can be generated on prestrained thermoplastic substrates by sequential cycles of skin layer growth followed by the release of prestrain. However, no mechanics models have explained the formation of multigenerational nanostructures using this nanofabrication process. This article describes an analytical model that can represent multiscale wrinkles with arbitrary numbers of generations. Structural features including wrinkle wavelengths and amplitudes on the nanoscale that are predicted by minimizing the total deformation energy of the system. The calculated wavelengths in each generation are in good agreement with experiment. Our mathematical approach provides design principles for achieving multigenerational hierarchical structures.

A case-control study of selenoprotein genes polymorphisms and autoimmune thyroid diseases in a Chinese population.

BACKGROUND: Selenium is an essential trace and there is a high selenium concentration in the thyroid gland. Selenium deficiency may impair the thyroid function. The aim of this study was to investigate the association between three selenoprotein genes polymorphisms and autoimmune thyroid diseases. METHODS: We genotyped six single-nucleotide polymorphisms (SNPs), rs6865453 in selenoprotein P gene (SELENOP), rs713041 rs2074451 rs3746165 in glutathione peroxidase 4 gene (GPX4) and rs28665122 and rs7178239 in selenoprotein S gene (SELENOS) by MassARRAY system using the chip-based matrix-assisted laser desorption ionization time-of-flight mass spectrometry technology in 1060 patients with autoimmune thyroid diseases and 938 healthy controls. RESULTS: Major alleles in rs6865453 of SELENOP, rs713041, rs2074451, rs3746165 of GPX4 decreased while the major allele C in rs28665122 of SELENOS increased in AITD patients than in the control. The allele C and genotype CC in rs7178239 of SELENOS showed different trend in GD and HT patients when compared with the control. All the distribution difference showed nonsignificant. Analysis according to clinical features including ophthalmopathy, hypothyroidism and family history came out to be negative either. CONCLUSIONS: Our findings suggest non-association between three selenoprotein genes and AITD, conflicting to the positive result in another population. Different selenium nutrition status in different populations may contribute to conflicting results, the contribution of genetic variants in AITD mechanism may be another reason.

Imbalance of Th17/Treg in Different Subtypes of Autoimmune Thyroid Diseases.

AIMS: To clarify the imbalance of Th17/Treg in different subtypes of autoimmune thyroid diseases (AITDs) including Graves' disease(GD), Hashimoto's thyroiditis(HT) and Graves' ophthalmopathy (GO). METHODS: 47 patients with AITD (including 16 GD, 15 HT, and 16 GO) and 12 healthy controls were enrolled in this study. The percentages of Th17 and Treg cells, the ratio of Th17/Treg, as well as their related transcription factors RORγt and Foxp3 mRNA in peripheral blood mononuclear cells (PBMCs) were measured by flow cytometry and real-time quantitative PCR Results: Compared with those in control group, the percentage of CD4+IL-17+T cell(Th17) and the mRNA expression of its transcription factor RORγt were higher in PBMCs of AITDs (P<0.05), particularly in HT subgroup (P<0.01). The percentage of CD4+Foxp3+T (Treg) cells and its transcription factor Foxp3 mRNA were significantly decreased in PBMCs of GD (P<0.05). In addition, the ratio of Th17/Treg was elevated in AITD group and GO subgroup (P<0.01). In GO subgroup, the patients with clinical activity score (CAS) above 4.5 had higher percentages of Th17 than those with CAS ranging from 3 to 4.5 (P<0.05). CONCLUSION: Increased Th17 lymphocytes may play a more important role in the pathogenesis of HT and GO while decreased Treg may be greatly involved in GD.

Hippo signaling cooperates with p53 to regulate lung airway mucous cell metaplasia.

Airway mucous cell metaplasia is a significant feature of many chronic airway diseases, such as chronic obstructive pulmonary disease (COPD), cystic fibrosis, and asthma. However, the mechanisms underlying this process remain poorly understood. Here, we employ in vivo mouse genetic models to demonstrate that Hippo and p53 cooperate to modulate the differentiation of club cells into goblet cells. We reveal that ablation of Mst1 and Mst1 (Mst1/2), the core components of Hippo signaling, significantly reduces mucous metaplasia in the lung airways in a lipopolysaccharide (LPS)-induced lung inflammation murine model while promoting club cell proliferation in a Yap-dependent manner. Additionally, we show that deleting Mst1/2 is sufficient to suppress p53 deficiency-mediated goblet cell metaplasia. Finally, single-cell RNA analysis reveals a downregulation of Yap and p53 signaling in goblet cells in the human airways. These findings underscore the important role of Hippo and p53 signaling in regulating airway mucous metaplasia.

Jag1/2 maintain esophageal homeostasis and suppress foregut tumorigenesis by restricting the basal progenitor cell pool.

Basal progenitor cells are crucial for maintaining foregut (the esophagus and forestomach) homeostasis. When their function is dysregulated, it can promote inflammation and tumorigenesis. However, the mechanisms underlying these processes remain largely unclear. Here, we employ genetic mouse models to reveal that Jag1/2 regulate esophageal homeostasis and foregut tumorigenesis by modulating the function of basal progenitor cells. Deletion of Jag1/2 in mice disrupts esophageal and forestomach epithelial homeostasis. Mechanistically, Jag1/2 deficiency impairs activation of Notch signaling, leading to reduced squamous epithelial differentiation and expansion of basal progenitor cells. Moreover, Jag1/2 deficiency exacerbates the deoxycholic acid (DCA)-induced squamous epithelial injury and accelerates the initiation of squamous cell carcinoma (SCC) in the forestomach. Importantly, expression levels of JAG1/2 are lower in the early stages of human esophageal squamous cell carcinoma (ESCC) carcinogenesis. Collectively, our study demonstrates that Jag1/2 are important for maintaining esophageal and forestomach homeostasis and the onset of foregut SCC.

Hyperspectral image spectral-spatial classification via weighted Laplacian smoothing constraint-based sparse representation.

As a powerful tool in hyperspectral image (HSI) classification, sparse representation has gained much attention in recent years owing to its detailed representation of features. In particular, the results of the joint use of spatial and spectral information has been widely applied to HSI classification. However, dealing with the spatial relationship between pixels is a nontrivial task. This paper proposes a new spatial-spectral combined classification method that considers the boundaries of adjacent features in the HSI. Based on the proposed method, a smoothing-constraint Laplacian vector is constructed, which consists of the interest pixel and its four nearest neighbors through their weighting factor. Then, a novel large-block sparse dictionary is developed for simultaneous orthogonal matching pursuit. Our proposed method can obtain a better accuracy of HSI classification on three real HSI datasets than the existing spectral-spatial HSI classifiers. Finally, the experimental results are presented to verify the effectiveness and superiority of the proposed method.

Needle-shaped ultrathin piezoelectric microsystem for guided tissue targeting via mechanical sensing.

Needles for percutaneous biopsies of tumour tissue can be guided by ultrasound or computed tomography. However, despite best imaging practices and operator experience, high rates of inadequate tissue sampling, especially for small lesions, are common. Here, we introduce a needle-shaped ultrathin piezoelectric microsystem that can be injected or mounted directly onto conventional biopsy needles and used to distinguish abnormal tissue during the capture of biopsy samples, through quantitative real-time measurements of variations in tissue modulus. Using well-characterized synthetic soft materials, explanted tissues and animal models, we establish experimentally and theoretically the fundamental operating principles of the microsystem, as well as key considerations in materials choices and device designs. Through systematic tests on human livers with cancerous lesions, we demonstrate that the piezoelectric microsystem provides quantitative agreement with magnetic resonance elastography, the clinical gold standard for the measurement of tissue modulus. The piezoelectric microsystem provides a foundation for the design of tools for the rapid, modulus-based characterization of tissues.

Computational models for the determination of depth-dependent mechanical properties of skin with a soft, flexible measurement device.

Conformal modulus sensors (CMS) incorporate PZT nanoribbons as mechanical actuators and sensors to achieve reversible conformal contact with the human skin for non-invasive, in vivo measurements of skin modulus. An analytic model presented in this paper yields expressions that connect the sensor output voltage to the Young moduli of the epidermis and dermis, the thickness of the epidermis, as well as the material and geometrical parameters of the CMS device itself and its encapsulation layer. Results from the model agree well with in vitro experiments on bilayer structures of poly(dimethylsiloxane). These results provide a means to determine the skin moduli (epidermis and dermis) and the thickness of the epidermis from in vivo measurements of human skin.