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Aged cells have declined regenerative ability when subjected to environmental insult. Here we elucidate the mechanism by which mechanical stimulus induces hair regeneration at the microenvironmental regulation level using the hair plucking and organoid culture models. We observed that the skin cells harvested from post-plucking day 3 (PPD3) have the best self-organizing ability during skin organoid culture and have the highest hair regeneration upon transplantation. By bulk RNA sequencing (RNA-seq) and single-cell RNA-seq analysis and in situ hybridization, we identified that the chemokine signaling pathway genes including CCL2 are significantly increased in the skin at PPD3 and in skin organoid cultures. Immunostaining shows that the PPD3 skin epithelial cells have increased multipotency, which is verified by the ability to self-organize to form epidermal aggregates during organoid culture. By adding CCL2 recombinant protein to the organoid culture using an environmental reprogramming protocol, we observed the PPD0 adult skin cells, which lose their regenerative ability can self-organize in organoid culture and regenerate hair follicles robustly upon transplantation. Our study demonstrates that CCL2 functions in immune regulation of hair regeneration under mechanical stimulus, and enhances cell multipotency during organoid culture. This provides a therapeutic potential for future clinical application.

Gait authentication as a technique that can continuously provide identity recognition on mobile devices for security has been investigated by academics in the community for decades. However, most of the existing work achieves insufficient generalization to complex real-world environments due to the complexity of the noisy real-world gait data. To address this limitation, we propose an intelligent Implicit Real-time Gait Authentication (IRGA) system based on Deep Neural Networks (DNNs) for enhancing the adaptability of gait authentication in practice. In the proposed system, the gait data (whether with complex interference signals) will first be processed sequentially by the imperceptible collection module and data preprocessing module for improving data quality. In order to illustrate and verify the suitability of our proposal, we provide analysis of the impact of individual gait changes on data feature distribution. Finally, a fusion neural network composed of a Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) is designed to perform feature extraction and user authentication. We evaluate the proposed IRGA system in heterogeneous complex scenarios and present start-of-the-art comparisons on three datasets. Extensive experiments demonstrate that the IRGA system achieves improved performance simultaneously in several different metrics.

The increasing use of high-value carbon fibre in composites is linked with increasing waste generation. A simple and feasible chopped/hot-press method was proposed for multiple recycled carbon fibre-reinforced thermoplastic composites. The effect of regeneration times on the tension and impact properties of carbon fibre-reinforced polypropylene thermoplastic composites was investigated experimentally. The results showed that the r1-CFRTP specimen decreased by 69.34% in tensile strength and 48.66 % in tensile modulus compared with v-CFRTP. However, its tensile properties were improved with the increase of regeneration times (before 3 times). The impact strength of r2-CFRTP and r3-CFRTP is 12.65%, 20.85% higher than v-CFRTP, while r1-CFRTP and r4-CFRTP are 8.02% and 7.06% lower than v-CFRTP. When the third regeneration makes relatively excellent mechanical properties for recycled carbon fibre/PP composite, the chopped/hot-press method is a meaningful attempt at recycling and reusing the thermoplastic composites.

As a sequel to \cite{Licollapsing}, we study Calabi-Yau metrics collapsing along a holomorphic fibration over a Riemann surface. Assuming at worst canonical singular fibres, we prove a uniform diameter bound for all fibres in the suitable rescaling. This has consequences on the geometry around the singular fibres.

Background: Amyloid-β protein precursor (AβPP) is enriched in neurons. However, the mechanism underlying AβPP regulation of neuronal activity is poorly understood. Potassium channels are critically involved in neuronal excitability. In hippocampus, A-type potassium channels are highly expressed and involved in determining neuronal spiking. Objective: We explored hippocampal local field potential (LFP) and spiking in the presence and absence of AβPP, and the potential involvement of an A-type potassium channel. Methods: We used in vivo extracellular recording and whole-cell patch-clamp recording to determine neuronal activity, current density of A-type potassium currents, and western blot to detect changes in related protein levels. Results: Abnormal LFP was observed in AβPP–/– mice, including reduced beta and gamma power, and increased epsilon and ripple power. The firing rate of glutamatergic neurons reduced significantly, in line with an increased action potential rheobase. Given that A-type potassium channels regulate neuronal firing, we measured the protein levels and function of two major A-type potassium channels and found that the post-transcriptional level of Kv1.4, but not Kv4.2, was significantly increased in the AβPP–/– mice. This resulted in a marked increase in the peak time of A-type transient outward potassium currents in both glutamatergic and gamma-aminobutyric acid-ergic (GABAergic) neurons. Furthermore, a mechanistic experiment using human embryonic kidney 293 (HEK293) cells revealed that the AβPP deficiency-induced increase in Kv1.4 may not involve protein-protein interaction between AβPP and Kv1.4. Conclusion: This study suggests that AβPP modulates neuronal firing and oscillatory activity in the hippocampus, and Kv1.4 may be involved in mediating the modulation.

Background: Chronic rhinosinusitis (CRS) is a common inflammatory disease in otolaryngology, mainly manifested as nasal congestion, nasal discharge, facial pain/pressure, and smell disorder. CRS with nasal polyps (CRSwNP), an important phenotype of CRS, has a high recurrence rate even after receiving corticosteroids and/or functional endoscopic sinus surgery. In recent years, clinicians have focused on the application of biological agents in CRSwNP. However, it has not reached a consensus on the timing and selection of biologics for the treatment of CRS so far. Summary: We reviewed the previous studies of biologics in CRS and summarized the indications, contraindications, efficacy assessment, prognosis, and adverse effects of biologics. Also, we evaluated the treatment response and adverse reactions of dupilumab, omalizumab, and mepolizumab in the management of CRS and made recommendations. Key Messages: Dupilumab, omalizumab, and mepolizumab have been approved for the treatment of CRSwNP by the US Food and Drug Administration. Type 2 and eosinophilic inflammation, need for systemic steroids or contraindication to systemic steroids, significantly impaired quality of life, anosmia, and comorbid asthma are required for the use of biologics. Based on current evidence, dupilumab has the prominent advantage in improving quality of life and reducing the risk of comorbid asthma in CRSwNP among the approved monoclonal antibodies. Most patients tolerate biological agents well in general with few major or severe adverse effects. Biologics have provided more options for severe uncontrolled CRSwNP patients or patients who refuse to have surgery. In the future, more novel biologics will be assessed in high-quality clinical trials and applied clinically.

Early exposure to symbolic media, such as pictures, drawings, paintings, photos, and videos, is common in western countries. Modern picture books coexist with electronic storybooks and other digital literature, expanding the environment in which young children develop and learn. Since the advent of new technologies, recommendations for kids' use of these gadgets have been covered in numerous papers. Young children and adults can engage in social interaction through picture books, which creates a wonderful chance for learning and teaching. This paper makes an analysis on children’s digital story book reading behavior. Initially, the features (considered questions) are clustered using k means clustering model. In order to analyze the children’s digital story book reading behavior, the questions are made on different drivers such as (i) Characteristics of story book, (ii) Interaction level and (iii) Child learning ability level. The questions are analyzed based upon the responses obtained from 100 respondents with 46 males and 54 females. Here, the study is done using ANOVA, regression analysis along with MSE, correlation and variance computation. Based upon the clustering outputs, the regression analysis is made on correlation and covariance metrics.