Bone regeneration originates from proliferation and differentiation of osteoprogenitors via either endochondral or intramembranous ossification; and the regeneration capacities decline with age and estrogen loss. Maxillary sinus floor lifting (MSFL) is a commonly used surgical procedure for guiding bone regeneration in maxilla. Radiographic analysis of 1210 clinical cases of maxilla bone regeneration after MSFL revealed that the intrasinus osteogenic efficacy was independent of age and gender, however; and this might be related to the Schneiderian membrane that lines the sinus cavity. In view of the particularity of this biological process, our present study aimed to elucidate the underlying mechanism of MSFL-induced bone regeneration. We first established a murine model to simulate the clinical MSFL. By single-cell RNA-sequencing and flow cytometry-based bulk RNA-sequencing, we identified a novel Krt14+Ctsk+ subset of cells that display both epithelial and mesenchymal properties and the transcriptomic feature of osteoprogenitors. Dual recombinases-mediated lineage tracing and loss-of-function analyses showed that these Krt14+Ctsk+ progenitors contribute to both MSFL-induced osteogenesis and physiological bone homeostasis by differentiating into Krt14–Ctsk+ descendants which show robust osteogenic capacity. In addition, we detected a similar population of Krt14+Ctsk+ cells in human samples of Schneiderian membrane, which show a highly similar osteogenic potential and transcriptomic feature to the corresponding cells in mice. The identification of this Krt14+Ctsk+ population, featured by osteoprogenitor characteristics and dual epithelial–mesenchymal properties, provides new insight into the understanding of bone regeneration and may open more possibilities for clinical applications.

This paper is concerned with the intermittent fault detection problem for a class of discrete-time linear systems with output dead-zone. Dead-zone phenomenon exists in many real practical systems due to the employment of low-cost commercial off-the-shelf sensors. Two Bernoulli random variables are utilized to model the dead-zone effect and a variant formation of Tobit Kalman filter is brought forward to generate a residual that can indicate the occurrence of an intermittent fault. A numerical example is presented to demonstrate the effectiveness and applicability of the proposed technique. The statistical performance of the technique is illustrated as well.

Background Postsurgical evaluation of sinus floor elevation regularly involves linear measurements of the elevated volumes in the cone beam computed tomography (CBCT) images. The accuracy of measurements could be compromised due to ill‐defined sinus floor outline if implants are placed simultaneously. Purpose The aim was to examine a CBCT superimposition method to improve the measurement accuracy. Materials and Methods Twenty patients who received transalveolar sinus floor elevation with immediate implantation were enrolled. CBCTs before and after surgery were transformed into digital imaging and communications in medicine format and imported into the Dolphin Imaging software. Voxel‐based superimposition was automated to merge the files. In the superimposed image, parameters including alveolar bone height, protruded implant length, and total elevated height were measured. The superimposition and measurements were performed independently by two examiners and in two timepoints with 1‐week time interval. We used intraclass correlation coefficient (ICC) to analyze the interexaminer and intraexaminer agreements. Results Of measured parameters, the mean of difference between two timepoints ranged from 0.18 to 0.26 mm by examiner 1, and from 0.16 to 0.20 mm by examiner 2. ICCs were equal or greater than 0.98, indicating perfect intraexaminer agreement. For interexaminer reliability, the largest mean of difference was 0.27 mm in measuring alveolar bone height between two examiners. ICCs were greater than 0.98, showing perfect interexaminer agreement. Conclusions The voxel‐based superimposition of pre‐ and post‐surgical CBCT images with Dolphin Imaging is an effective and reliable way for linear measurements so as to assess the surgical outcome. There is minimal effect on reproducibility of measured data by different timepoints or performers.

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