Weighted allocations, their concomitant-based estimators, and asymptotics

Various members of the class of weighted insurance premiums and risk capital allocation rules have been researched from a number of perspectives. Corresponding formulas in the case of parametric families of distributions have been derived, and they have played a pivotal role when establishing parametric statistical inference in the area. Non-parametric inference results have also been derived in special cases such as the tail conditional expectation, distortion risk measure, and several members of the class of weighted premiums. For weighted allocation rules, however, non-parametric inference results have not yet been adequately developed. In the present paper, therefore, we put forward empirical estimators for the weighted allocation rules and establish their consistency and asymptotic normality under practically sound conditions. Intricate statistical considerations rely on the theory of induced order statistics, known as concomitants.Comment: 20 page

Lithium-containing S-PRG fillers promoted the wound healing process of pulp tissues through activation of Wnt/β-catenin signaling pathway

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Protein S100-A7 derived from digested dentin is a critical molecule for dentin pulp regeneration

Dentin consists of inorganic hard tissue and organic dentin matrix components (DMCs). Various kinds of bioactive molecules are included in DMCs and some of them can be released after digestion by endogenous matrix metalloproteinases (MMPs) in the caries region. Digested DMCs induced by MMP20 have been reported to promote pulpal wound healing processes, but the released critical molecules responsible for this phenomenon are unclear. Here, we identified protein S100-A7 as a critical molecule for pulpal healing in digested DMCs by comprehensive proteomic approaches and following pulp capping experiments in rat molars. In addition, immunohistochemical results indicated the specific distribution of S100-A7 and receptor for advanced glycation end-products (RAGE) as receptor for S100-A7 in the early stage of the pulpal healing process, and following accumulation of CD146-positive stem cells in wounded pulp. Our findings indicate that protein S100-A7 released from dentin by MMP20 might play a key role in dentin pulp regeneration

Effect of Heparan Sulfate on Vasculogenesis and Dentinogenesis of Dental Pulp Stem Cells

Li A., Sasaki J.I., Huang H., et al. Effect of Heparan Sulfate on Vasculogenesis and Dentinogenesis of Dental Pulp Stem Cells. Journal of Endodontics , (2024); https://doi.org/10.1016/j.joen.2024.04.015.Introduction: Heparan sulfate (HS) is a major component of dental pulp tissue. We previously reported that inhibiting HS biosynthesis impedes endothelial differentiation of dental pulp stem cells (DPSCs). However, the underlying mechanisms by which exogenous HS induces DPSC differentiation and pulp tissue regeneration remain unknown. This study explores the impact of exogenous HS on vasculogenesis and dentinogenesis of DPSCs both in vitro and in vivo. Methods: Human-derived DPSCs were cultured in endothelial and odontogenic differentiation media and treated with HS. Endothelial differentiation of DPSCs was investigated by real-time polymerase chain reaction and capillary sprouting assay. Odontogenic differentiation was assessed through real-time polymerase chain reaction and detection of mineralized dentin-like deposition. Additionally, the influence of HS on pulp tissue was assessed with a direct pulp capping model, in which HS was delivered to exposed pulp tissue in rats. Gelatin sponges were loaded with either phosphate-buffered saline or 101–102 μg/mL HS and placed onto the pulp tissue. Following a 28-day period, tissues were investigated by histological analysis and micro–computed tomography imaging. Results: HS treatment markedly increased expression levels of key endothelial and odontogenic genes, enhanced the formation of capillary-like structures, and promoted the deposition of mineralized matrices. Treatment of exposed pulp tissue with HS in the in vivo pulp capping study induced formation of capillaries and reparative dentin. Conclusions: Exogenous HS effectively promoted vasculogenesis and dentinogenesis of DPSCs in vitro and induced reparative dentin formation in vivo, highlighting its therapeutic potential for pulp capping treatment

Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer with Deep Learning

Objective. To develop an artificial intelligence method predicting lymph node metastasis (LNM) for patients with colorectal cancer (CRC). Impact Statement. A novel interpretable multimodal AI-based method to predict LNM for CRC patients by integrating information of pathological images and serum tumor-specific biomarkers. Introduction. Preoperative diagnosis of LNM is essential in treatment planning for CRC patients. Existing radiology imaging and genomic tests approaches are either unreliable or too costly. Methods. A total of 1338 patients were recruited, where 1128 patients from one centre were included as the discovery cohort and 210 patients from other two centres were involved as the external validation cohort. We developed a Multimodal Multiple Instance Learning (MMIL) model to learn latent features from pathological images and then jointly integrated the clinical biomarker features for predicting LNM status. The heatmaps of the obtained MMIL model were generated for model interpretation. Results. The MMIL model outperformed preoperative radiology-imaging diagnosis and yielded high area under the curve (AUCs) of 0.926, 0.878, 0.809, and 0.857 for patients with stage T1, T2, T3, and T4 CRC, on the discovery cohort. On the external cohort, it obtained AUCs of 0.855, 0.832, 0.691, and 0.792, respectively (T1-T4), which indicates its prediction accuracy and potential adaptability among multiple centres. Conclusion. The MMIL model showed the potential in the early diagnosis of LNM by referring to pathological images and tumor-specific biomarkers, which is easily accessed in different institutes. We revealed the histomorphologic features determining the LNM prediction indicating the model ability to learn informative latent features

Изучение смачиваемости твёрдых тел методом математического моделирования контактных углов

Статья посвящена обсуждению метода измерения краевых углов поверхности с использованием математического моделирования контура изображений сидячих капель. Полученные результаты позволяют использовать предложенный метод, не прибегая к значительным изменениям в экспериментальной части измерений

Frequent alterations in cytoskeleton remodelling genes in primary and metastatic lung adenocarcinomas

The landscape of genetic alterations in lung adenocarcinoma derived from Asian patients is largely uncharacterized. Here we present an integrated genomic and transcriptomic analysis of 335 primary lung adenocarcinomas and 35 corresponding lymph node metastases from Chinese patients. Altogether 13 significantly mutated genes are identified, including the most commonly mutated gene TP53 and novel mutation targets such as RHPN2, GLI3 and MRC2. TP53 mutations are furthermore significantly enriched in tumours from patients harbouring metastases. Genes regulating cytoskeleton remodelling processes are also frequently altered, especially in metastatic samples, of which the high expression level of IQGAP3 is identified as a marker for poor prognosis. Our study represents the first large-scale sequencing effort on lung adenocarcinoma in Asian patients and provides a comprehensive mutational landscape for both primary and metastatic tumours. This may thus form a basis for personalized medical care and shed light on the molecular pathogenesis of metastatic lung adenocarcinoma