Chemokines and their receptors show a strong relationship with poor clinical outcomes in various cancers. However, their underlying mechanisms remain to be fully elucidated. In our research, we found C-C chemokine receptor 7 (CCR7) and its ligand chemokine ligand 21 (CCL21) were abnormally abundant in oral squamous cell carcinoma (OSCC) tissues, and CCR7 expression was correlated with poor prognosis of OSCC. After exogenous CCL21 stimulation, epithelial-mesenchymal transition (EMT) was promoted in OSCC cells, and cancer stem cell-related markers CD133, CD44, BMI1, ALDH1A1, and OCT4 increased. The migration, invasion, tumorsphere formation, and colony formation abilities of OSCC cells were enhanced, indicating that the stemness of OSCC cells was also improved. The knockdown and overexpression of CCR7 efficiently affected the CCL21-induced EMT and stemness of OSCC cells. When treated with CCL21, the phospho-JAK2 and phospho-STAT3 markedly increased. The inhibitor of the Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) significantly suppressed CCL21-induced EMT and stemness of OSCC cells. In conclusion, CCL21/CCR7 axis regulated EMT progress and promoted the stemness of OSCC by activating the JAK2/STAT3 signaling pathway. CCL21/CCR7 might be an effective target for OSCC prevention and treatment.

We propose a novel metal artifact reduction method based on a fractional-order curvature driven diffusion model for X-ray computed tomography. Our method treats projection data with metal regions as a damaged image and uses the fractional-order curvature-driven diffusion model to recover the lost information caused by the metal region. The numerical scheme for our method is also analyzed. We use the peak signal-to-noise ratio as a reference measure. The simulation results demonstrate that our method achieves better performance than existing projection interpolation methods, including linear interpolation and total variation.

Currently, the shortage of red components and easy aging of organic silicone still remain challenges for high-power phosphor-converted warm white light-emitting diodes (w-LEDs). Aiming to alleviate these issues, phosphor-in-glass (PiG), fabricated by co-sintering red- and yellow-emitting phosphors and low-melting glass, has been regarded as a promising color converter for w-LEDs. In this study, a Li,Mn co-doped SrMgAlO red phosphor was synthesized via a conventional solid-state reaction. The as-prepared phosphor exhibits a deep red emission, ascribed to Mn:E→A spin-forbidden transition in the range of 600-700 nm with a narrow-band full width at half maximum of 55 nm, and provides an ideal broadband excitation extending from 250 to 530 nm. Impressively, the Li additive used as charge compensation was beneficial to enhance the Mn luminescence by allowing more Mn to replace Al. Furthermore, the developed SrMgAlO:Mn,Li red phosphor and commercial YAG:Ce yellow phosphor co-doped inorganic PiG were successfully fabricated as color converters to substitute organic silicone. The w-LED was fabricated by combining an InGaN blue LED chip with a PiG plate. Importantly, the constructed w-LEDs exhibited superior optical performance and tuned chromaticity feature with the correlated color temperature evolved from bluish cool white (6903 K) to yellowish warm white (3717 K), and the color rendering index increased from 69.4 to 85.5, meeting the requirements for indoor lighting.

Background Studies suggest Porphyromonas gingivalis (Pg) increased the incidence of oral squamous cell carcinoma (OSCC). However, fimA genotypes distribution of Pg, the origination of Pg in tissue, and its prognostic value are inconclusive. We aimed to investigate the frequency of fimA genotypes in OSCC patients, study the association between Pg and OSCC, and explore the prognostic value of Pg. Methods The abundance of Pg in saliva from the OSCC group and the OSCC-free group was analysed by qPCR. The presence of Pg was explored in OSCC tissue and para-cancerous tissue by in situ hybridization. The frequency of fimA genotypes in saliva and OSCC tissue was determined by PCR, then PCR products were sequenced and compared. Clinical data were extracted, and patients followed up for a median period of 23 months. Clinicopathological variables were compared with the abundance of Pg using Pearson Chi-square test or Fisher’s exact test. The disease-free survival (DFS) rate was calculated by Kaplan–Meier method with log-rank tests. Results Comparing the OSCC-free group, 95 patients with OSCC showed a high abundance of Pg in saliva (P = 0.033), and OSCC tissue showed strong in situ expression of Pg compared with paired normal tissue. Patients with OSCC showed a dominant distribution of Pg with genotype I + Ib (21.1%), II (31.6%), and IV (21.1%). FimA genotypes detected in saliva were in accordance with those in OSCC tissue, there was, moreover, a significant similarity in amplified Pg fragments. Of the 94 responsive OSCC patients, the recurrence rate was 26.6% (25/94). Overabundance of Pg in saliva showed advanced pathologic staging (P = 0.008), longer disease-free time (P = 0.029) and lower recurrence rate (P = 0.033). The overabundance of Pg in saliva was associated with improved disease-free survival (P = 0.049). Conclusions This study indicated that Pg might involve in the pathogenesis of OSCC, Pg carrying fimA I, Ib, II, and IV were prevalent genotypes in patients with OSCC, the provenance of Pg in OSCC tissue might be from the salivary microbial reservoir, and the abundance of Pg in saliva might consider as a favorable potential prognostic indicator in OSCC.

This paper proposes a vessel active contour model based on local intensity weighting and a vessel vector field. Firstly, the energy function we define is evaluated along the evolving curve instead of all image points, and the function value at each point on the curve is based on the interior and exterior weighted means in a local neighborhood of the point, which is good for dealing with the intensity inhomogeneity. Secondly, a vascular vector field derived from a vesselness measure is employed to guide the contour to evolve along the vessel central skeleton into thin and weak vessels. Thirdly, an automatic initialization method that makes the model converge rapidly is developed, and it avoids repeated trails in conventional local region active contour models. Finally, a speed-up strategy is implemented by labeling the steadily evolved points, and it avoids the repeated computation of these points in the subsequent iterations. Experiments using synthetic and real vessel images validate the proposed model. Comparisons with the localized active contour model, local binary fitting model, and vascular active contour model show that the proposed model is more accurate, efficient, and suitable for extraction of the vessel tree from different medical images.