The PML1-WDR5 axis regulates H3K4me3 marks and promotes stemness of estrogen receptor-positive breast cancer.

The alternative splicing of PML precursor mRNA gives rise to various PML isoforms, yet their expression profile in breast cancer cells remains uncharted. We discovered that PML1 is the most abundant isoform in all breast cancer subtypes, and its expression is associated with unfavorable prognosis in estrogen receptor-positive (ER+) breast cancers. PML depletion reduces cell proliferation, invasion, and stemness, while heterologous PML1 expression augments these processes and fuels tumor growth and resistance to fulvestrant, an FDA-approved drug for ER+ breast cancer, in a mouse model. Moreover, PML1, rather than the well-known tumor suppressor isoform PML4, rescues the proliferation of PML knockdown cells. ChIP-seq analysis reveals significant overlap between PML-, ER-, and Myc-bound promoters, suggesting their coordinated regulation of target gene expression, including genes involved in breast cancer stem cells (BCSCs), such as JAG1, KLF4, YAP1, SNAI1, and MYC. Loss of PML reduces BCSC-related gene expression, and exogenous PML1 expression elevates their expression. Consistently, PML1 restores the association of PML with these promoters in PML-depleted cells. We identified a novel association between PML1 and WDR5, a key component of H3K4 methyltransferase (HMTs) complexes that catalyze H3K4me1 and H3K4me3. ChIP-seq analyses showed that the loss of PML1 reduces H3K4me3 in numerous loci, including BCSC-associated gene promoters. Additionally, PML1, not PML4, re-establishes the H3K4me3 mark on these promoters in PML-depleted cells. Significantly, PML1 is essential for recruiting WDR5, MLL1, and MLL2 to these gene promoters. Inactivating WDR5 by knockdown or inhibitors phenocopies the effects of PML1 loss, reducing BCSC-related gene expression and tumorsphere formation and enhancing fulvestrant's anticancer activity. Our findings challenge the conventional understanding of PML as a tumor suppressor, redefine its role as a promoter of tumor growth in breast cancer, and offer new insights into the unique roles of PML isoforms in breast cancer.

Improving Image Segmentation with Contextual and Structural Similarity.

Deep learning models for medical image segmentation are usually trained with voxel-wise losses, e.g., cross-entropy loss, focusing on unary supervision without considering inter-voxel relationships. This oversight potentially leads to semantically inconsistent predictions. Here, we propose a contextual similarity loss (CSL) and a structural similarity loss (SSL) to explicitly and efficiently incorporate inter-voxel relationships for improved performance. The CSL promotes consistency in predicted object categories for each image sub-region compared to ground truth. The SSL enforces compatibility between the predictions of voxel pairs by computing pair-wise distances between them, ensuring that voxels of the same class are close together whereas those from different classes are separated by a wide margin in the distribution space. The effectiveness of the CSL and SSL is evaluated using a clinical cone-beam computed tomography (CBCT) dataset of patients with various craniomaxillofacial (CMF) deformities and a public pancreas dataset. Experimental results show that the CSL and SSL outperform state-of-the-art regional loss functions in preserving segmentation semantics.

A community challenge to predict clinical outcomes after immune checkpoint blockade in non-small cell lung cancer.

BACKGROUND: Predictive biomarkers of immune checkpoint inhibitor (ICI) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. METHODS: Participants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. RESULTS: A total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The best-performing models showed improved predictive power over reference variables, including TMB or PD-L1. CONCLUSIONS: This DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICI clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICI efficacy. TRIAL REGISTRATION: CheckMate 026; NCT02041533, registered January 22, 2014. CheckMate 227; NCT02477826, registered June 23, 2015.

Multi-object distance determination by analysis of CoC variation for dynamic structured light.

A multi-object distance determination method can be achieved by 932 nm structured light with one camera as the data receiver. The structured light generated by a liquid crystal on silicon spatial light modulator (LCoS-SLM) facilitates dynamic image projection on targets. A series of moving light strip images were captured and collected for data analysis. This method lifted the limitation of single-object distance determination and the limitation of the angle requirement between the camera and the light source in the triangulation method. The average error of this method was approximately 3% in the range of 700 mm to 1900 mm away from LCoS-SLM without further optimization. It provides a potential compact design for indoor multi-object distance determination in the future.

Comparison of the physical, thermal, and biological effects on implant bone site when using either zirconia or stainless-steel drill for implant bone site preparation.

BACKGROUND/PURPOSE: Zirconia has been a popular material in dental implantology with good biocompatibility. But few research focused on its application in implant drills. This study aimed to investigate the physical, thermal, and biological effects on using the zirconia and stainless-steel drills for implant bone site preparation. METHODS: We performed a series of experiments to evaluate the physical wearing properties of zirconia and stainless-steel drills of identical diameter and similar shape. During the implant site preparation thermal test, we subjected both drills onto a resin-embedded bone, utilizing a thermal couple device without irrigation. Moreover, we conducted a cell study by collecting bone cells in vivo while preparing the implant site with both tested drills. The cell activity was evaluated through cell proliferation colorimetric analysis (XTT) and alkaline phosphatase (ALP) activity measurements. RESULTS: The zirconia drill outperforms the stainless-steel drill in terms of requiring less force, maintaining stability over repeated cutting tests, and generating lower temperatures during drilling (stainless-steel drill: 45.48 ± 1.31 °C; zirconia-coated drill: 32.98 ± 1.21 °C, P = 0.000247). Meanwhile, both types of drills show similar results in XTT colorimetric analysis and ALP activity test. CONCLUSION: The thermal effect study is more favorable for using the zirconia drill than the stainless-steel drill for bone preparation. Cytological analysis indicate that the zirconia drill produces a similar impact on bone cells activity as the stainless-steel drill. Therefore, we conclude that the zirconia drills offer a good cutting effect similar to currently available stainless-steel drills in various aspects.

A cross-sectional study for prevalence and risk factors of peri-implant marginal bone loss.

STATEMENT OF PROBLEM: Progressive peri-implant marginal bone loss and peri-implantitis have become a growing problem, but cross-sectional studies on their prevalence and risk factors are sparse. PURPOSE: The purpose of this cross-sectional clinical study was to investigate the prevalence of peri-implant marginal bone loss (MBL) and to identify systemic and local risk factors. MATERIAL AND METHODS: All adult patients who had received dental implants at the National Taiwan University Hospital (NTUH) during 2009 or 2010 were included. Their medical records were collected from the NTUH-integrative Medical Database. Consecutive follow-up radiographs were accessed for severity of MBL. The influence of each factor on MBL was estimated by using generalized estimating equations (GEEs). RESULTS: A total of 732 participants with 1873 implants were analyzed (mean follow-up: 5.30 years). The prevalence of MBL was 59.15% at the individual level and 49.55% at the implant level. The risk indicators identified for the presence of MBL were follow-up period of more than 2 years, diagnosis of diabetes within 12 months, radiation therapy (2 years after implant placement), implant location at maxillary canine (compared with mandibular molar), and implants from the Nobel Biocare brands (Brånemark System and NobelActive). A second multivariate GEE model confirmed the association of progressive MBL with implant location at the maxillary canine and mandibular incisor and implant brand or design. CONCLUSIONS: The identified risk indicators for MBL were longer follow-up period, diagnosis of diabetes, radiation therapy, implant location at maxillary canine, and implant brand or design.

Sirtuin 6 ameliorates arthritis through modulating cyclic AMP-responsive element binding protein/CCN1/cyclooxygenase 2 pathway in osteoblasts.

INTRODUCTION: CCN1 is an immediate-early gene product pivotal for arthritis progression. We have previously shown that sirtuin 6 (SIRT6) inhibited hypoxia-induced CCN1 expression in osteoblasts. Herein we examined the contribution of cyclic AMP-responsive element binding protein (CREB)/CRE to this suppressive action and the influence of CCN1 on cyclooxygenase (COX) 2 synthesis. MATERIALS AND METHODS: MC3T3-E1 murine osteoblasts were cultured under normoxia (21% oxygen) or hypoxia (2% oxygen). Expressions of CCN1, phospho-CREB (Ser133), COX2 and relevant kinases were assessed by Western blot. SIRT6 was overexpressed in cultured osteoblasts and arthritic joints by a lentiviral-based technique. Activities of CCN1 gene promoter constructs were examined by luciferase reporter assay. Interaction between CREB and CCN1 promoter was assessed by chromatin immunoprecipitation (ChIP). Collagen-induced arthritis (CIA) was established in 20 rats to evaluate the effects of SIRT6 therapy on osteoblastic expressions of phospho-CREB, CCN1 and COX2. RESULTS: SIRT6 suppressed hypoxia-enhanced CCN1 expression and CREB phosphorylation. Attenuation of calcium/calmodulin-dependent protein kinase II (CaMKII) may be responsible for SIRT6-induced CREB inhibition. CRE at - 286 bp upstream of the ATG start codon was essential for CCN1 expression under hypoxia and SIRT6 reduced hypoxia-stimulated CREB/CRE interaction. Forced expression of CREB rescued SIRT6-suppressed CCN1 synthesis. CCN1 induced COX2 expression in osteoblasts. In rat CIA, the therapeutic effect of SIRT6 was accompanied by decreases in osteoblastic expressions of phospho-CREB, CCN1 and COX2. CONCLUSION: Our study indicated that the benefits of SIRT6 to inflammatory arthritis and bone resorption are at least partially derived from its modulation of CREB/CCN1/COX2 pathway in osteoblasts.

The PML1-WDR5 axis regulates H3K4me3 marks and promotes stemness of estrogen receptor-positive breast cancer.

The alternative splicing of PML precursor mRNA gives rise to various PML isoforms, yet their expression profile in breast cancer cells remains uncharted. We discovered that PML1 is the most abundant isoform in all breast cancer subtypes, and its expression is associated with unfavorable prognosis in estrogen receptor-positive (ER+) breast cancers. PML depletion reduces cell proliferation, invasion, and stemness, while heterologous PML1 expression augments these processes and fuels tumor growth and resistance to fulvestrant, an FDA-approved drug for ER + breast cancer, in a mouse model. Moreover, PML1, rather than the well-known tumor suppressor isoform PML4, rescues the proliferation of PML knockdown cells. ChIP-seq analysis reveals significant overlap between PML-, ER-, and Myc-bound promoters, suggesting their coordinated regulation of target gene expression, including genes involved in breast cancer stem cells (BCSCs), such as JAG1, KLF4, YAP1, SNAI1, and MYC. Loss of PML reduces BCSC-related gene expression, and exogenous PML1 expression elevates their expression. Consistently, PML1 restores the association of PML with these promoters in PML-depleted cells. We identified a novel association between PML1 and WDR5, a key component of H3K4 methyltransferase (HMTs) complexes that catalyze H3K4me1 and H3K4me3. ChIP-seq analyses showed that the loss of PML1 reduces H3K4me3 in numerous loci, including BCSC-associated gene promoters. Additionally, PML1, not PML4, re-establishes the H3K4me3 mark on these promoters in PML-depleted cells. Significantly, PML1 is essential for recruiting WDR5, MLL1, and MLL2 to these gene promoters. Inactivating WDR5 by knockdown or inhibitors phenocopies the effects of PML1 loss, reducing BCSC-related gene expression and tumorsphere formation and enhancing fulvestrant's anticancer activity. Our findings challenge the conventional understanding of PML as a tumor suppressor, redefine its role as a promoter of tumor growth in breast cancer and offer new insights into the unique roles of PML isoforms in breast cancer.

Multiomics Strategy Reveals the Mechanism of Action and Ameliorating Effect of Deer Velvet Antler Water Extracts on DSS-Induced Colitis.

Velvet antler is a precious traditional Chinese medicine used for thousands of years. This study investigated the anti-colitis effects of water extracts of Formosan sambar deer (SVAE) and red deer (RVAE) to identify the possible mechanisms and the bioactive compounds using a dextran sulfate sodium (DSS)-induced colitis mouse model. The mechanism of action and the ameliorating effects of SVAE and RVAE on DSS-induced colitis were evaluated using a mouse model. Ultra-high performance liquid chromatography-mass/mass and gas chromatography-mass/mass were applied to identify the bioactive components of the SVAE and RVAE water extracts. The results revealed that both high-dose SVAE and RVAE could ameliorate the symptoms of colitis due to reduced systemic inflammatory responses, enhanced intestinal barrier integrity by restoration of tight junction proteins, and improved gut dysbiosis. The potentially bioactive components of SVAE and RVAE were identified as small molecules (<3 kDa). Further identification by untargeted metabolomics analysis suggested that l-carnitine, hypoxanthine, adrenic acid, creatinine, gamma-aminobutyric-lysine, oleic acid, glycine, poly-γ-glutamic acid, and eicosapentaenoic acid in VAWEs might be involved in ameliorating the symptoms of colitis. This study provided evidence for the potential usage of SVAE and RVAE as anti-colitis agents.

Metformin Reduces Bone Resorption in Apical Periodontitis Through Regulation of Osteoblast and Osteoclast Differentiation.

INTRODUCTION: We have previously demonstrated that auxiliary metformin therapy promotes healing of apical periodontitis. Here we aimed to investigate the effects of metformin on osteoblast differentiation and osteoclast formation in cultured cells and rat apical periodontitis. METHODS: Murine pre-osteoblasts MC3T3-E1 and macrophages RAW264.7 were cultured under hypoxia (2% oxygen) or normoxia (21% oxygen) and stimulated with receptor activator of nuclear factor-κB ligand (RANKL) when indicated. Metformin was added to the cultures to evaluate its anti-hypoxic effects. Expressions of osteoblast differentiation regulator runt-related transcription factor 2 (RUNX2), RANKL, and osteoclast marker tartrate-resistant acid phosphatase (TRAP) were assessed by Western blot. Apical periodontitis was induced in mandibular first molars of 10 Sprague-Dawley rats. Root canal therapy with or without metformin supplement was performed. Periapical bone resorption was measured by micro-computed tomography. Immunohistochemistry was used to examine RUNX2, RANKL, and TRAP expressions. RESULTS: Hypoxia suppressed RUNX2 expression and enhanced RANKL synthesis in pre-osteoblasts. TRAP production increased in macrophages after hypoxia and/or RANKL stimulation. Metformin reversed hypoxia-induced RUNX2 suppression and RANKL synthesis in pre-osteoblasts. Metformin also inhibited hypoxia and RANKL-enhanced TRAP synthesis in macrophages. Intracanal metformin diminished bone loss in rat apical periodontitis. Comparing with vehicle control, cells lining bone surfaces in metformin-treated lesions had significantly stronger expression of RUNX2 and decreased synthesis of RANKL and TRAP. CONCLUSIONS: Alleviation of bone resorption by intracanal metformin was associated with enhanced osteoblast differentiation and diminished osteoclast formation in rat apical periodontitis. Our results endorsed the role of metformin as an effective medicament for inflammatory bone diseases.

Cholesterol twists the transmembrane Di-Gly region of amyloid-precursor protein.

Nearly 95% of Alzheimer's disease (AD) occurs sporadically without genetic linkage. Aging, hypertension, high cholesterol content, and diabetes are known nongenomic risk factors of AD. Aggregation of Aß peptides is an initial event of AD pathogenesis. Aß peptides are catabolic products of a type I membrane protein called amyloid precursor protein (APP). Aß40 is the major product, whereas the 2-residue-longer version, Aß42, induces amyloid plaque formation in the AD brain. Since cholesterol content is one risk factor for sporadic AD, we aimed to explore whether cholesterol in the membrane affects the structure of the APP transmembrane region, thereby modulating the γ-secretase cutting behavior. Here, we synthesized several peptides containing the APP transmembrane region (sequence 693-726, corresponding to the Aß22-55 sequence) with one or two Cys mutations for spin labeling. We performed three electron spin resonance experiments to examine the structural changes of the peptides in liposomes composed of dioleoyl phosphatidylcholine and different cholesterol content. Our results show that cholesterol increases membrane thickness by 10% and peptide length accordingly. We identified that the di-glycine region of Aß36-40 (sequence VGGVV) exhibits the most profound change in response to cholesterol compared with other segments, explaining how the presence of cholesterol affects the γ-secretase cutting site. This study provides spectroscopic evidence showing how cholesterol modulates the structure of the APP transmembrane region in a lipid bilayer.

FAM20A mutations and transcriptome analyses of dental pulp tissues of enamel renal syndrome.

AIM: Biallelic loss-of-function FAM20A mutations cause amelogenesis imperfecta (AI) type IG, better known as enamel renal syndrome (ERS), characterized by severe enamel hypoplasia, delayed/failed tooth eruption, intrapulpal calcifications, gingival hyperplasia and nephrocalcinosis. FAM20A binds to FAM20C, the Golgi casein kinase (GCK) and potentiates its function to phosphorylate secreted proteins critical for biomineralization. While many FAM20A pathogenic mutations have been reported, the pathogeneses of orodental anomalies in ERS remain to be elucidated. This study aimed to identify disease-causing mutations for patients with ERS phenotypes and to discern the molecular mechanism underlying ERS intrapulpal calcifications. METHODOLOGY: Phenotypic characterization and whole exome analyses were conducted for 8 families and 2 sporadic cases with hypoplastic AI. A minigene assay was performed to investigate the molecular consequences of a FAM20A splice-site variant. RNA sequencing followed by transcription profiling and gene ontology (GO) analyses were carried out for dental pulp tissues of ERS and the control. RESULTS: Biallelic FAM20A mutations were demonstrated for each affected individual, including 7 novel pathogenic variants: c.590-5T>A, c.625T>A (p.Cys209Ser), c.771del (p.Gln258Argfs*28), c.832_835delinsTGTCCGACGGTGTCCGACGGTGTC CA (p.Val278Cysfs*29), c.1232G>A (p.Arg411Gln), c.1297A>G (p.Arg433Gly) and c.1351del (p.Gln451Serfs*4). The c.590-5T>A splice-site mutation caused Exon 3 skipping, which resulted in an in-frame deletion of a unique region of the FAM20A protein, p.(Asp197_Ile214delinsVal). Analyses of differentially expressed genes in ERS pulp tissues demonstrated that genes involved in biomineralization, particularly dentinogenesis, were significantly upregulated, such as DSPP, MMP9, MMP20 and WNT10A. Enrichment analyses indicated overrepresentation of gene sets associated with BMP and SMAD signalling pathways. In contrast, GO terms related to inflammation and axon development were underrepresented. Among BMP signalling genes, BMP agonists GDF7, GDF15, BMP3, BMP8A, BMP8B, BMP4 and BMP6 were upregulated, while BMP antagonists GREM1, BMPER and VWC2 showed decreased expression in ERS dental pulp tissues. CONCLUSIONS: Upregulation of BMP signalling underlies intrapulpal calcifications in ERS. FAM20A plays an essential role in pulp tissue homeostasis and prevention of ectopic mineralization in soft tissues. This critical function probably depends upon MGP (matrix Gla protein), a potent mineralization inhibitor that must be properly phosphorylated by FAM20A-FAM20C kinase complex.

Novel Robotic Arm Working-Area AI Protection System.

From traditionally handmade items to the ability of people to use machines to process and even to human-robot collaboration, there are many risks. Traditional manual lathes and milling machines, sophisticated robotic arms, and computer numerical control (CNC) operations are quite dangerous. To ensure the safety of workers in automated factories, a novel and efficient warning-range algorithm is proposed to determine whether a person is in the warning range, introducing YOLOv4 tiny-object detection algorithms to improve the accuracy of determining objects. The results are displayed on a stack light and sent through an M-JPEG streaming server so that the detected image can be displayed through the browser. According to the experimental results of this system installed on a robotic arm workstation, it is proved that it can ensure recognition reaches 97%. When a person enters the dangerous range of the working robotic arm, the arm can be stopped within about 50 ms, which will effectively improve the safety of its use.

Prediction of biphasic separation in CO2 absorption using a molecular surface information-based machine learning model.

Carbon dioxide capture technologies have become a focus to overcome global warming. Biphasic absorbents are one of the promising approaches for energy-saving CO2 capture processes. These biphasic absorbents are mainly composed of a mixed solvent composed of alkanolamine and organic solvents like glycol ether or alcohol. However, screening experiments of the mixed-solvent absorbents are required to search for biphasic absorbents due to their complicated phase behavior. In this work, we developed a prediction method for the phase states of the mixed-solvent absorbents using a quantum calculation and machine learning models, including random forest, logistic regression, and support vector machine models. There are 61 mixed-solvent absorbents containing alkanolamine/glycol ether or alcohol in the dataset. The machine learning models successfully predicted the phase states of the mixed-solvent absorbents before and after CO2 absorption with accuracies of more than 90%. Furthermore, we analyzed the contributions of explanatory variables for prediction using the learned model. As a result, we found that molecular surface charge of the amine species is more important than those of the other organic solvents to determine the phase behaviors during CO2 absorption.

Decoronation-induced infected alveolar socket defect rat model for ridge preservation.

Current rat alveolar ridge preservation models have not been well standardized. In this study, we proposed decoronation-induced infected alveolar socket model of rat. The bilateral maxillary first molars (M1) of twenty-four rats were decoronized or extracted. After 2, 6, 10, and 14 weeks, bone and soft tissue changes at M1 and periodontal conditions of maxillary second (M2) and third molars (M3) were evaluated by micro-computed tomography and histological analysis. Additional eighteen rats with standardized size defects were grafted with Bio-Oss Collagen to compare with unmanipulated contralateral side. Decoronation preserved greater bone and soft tissue dimensions at M1, provided larger three-dimensional (3D) bone contour volume, but also promoted periodontal breakdown of M2 Histological results showed intense inflammatory cell infiltrations and severe bone resorption within M1 socket and at mesial aspect of M2. The critical dimensions to accommodate largest standardized defect at M1 were 2.2-2.3 mm at vertical bone height and 2.8-3.2 mm at alveolar crestal width. Bio-Oss Collagen could not fully preserve buccal or palatal bone height but could be beneficial in preserving ridge width in large alveolar defects. Collectively, if periodontally-involved alveolar bone defect is preferred, we suggest extracting M1 roots 6 weeks after decoronation to allow periodontitis to occur at M2. If standardized critical dimension defect is preferred, we suggest extracting M1 roots 2 weeks after decoronation, and creating defect in the middle of M1 site with size no larger than 2.7 mm diameter to its full depth.

Metformin-Incorporated Gelatin/Nano-Hydroxyapatite Scaffolds Promotes Bone Regeneration in Critical Size Rat Alveolar Bone Defect Model.

In this study, we fabricated gelatin/nano-hydroxyapatite/metformin scaffold (GHMS) and compared its effectiveness in bone regeneration with extraction-only, Sinbone, and Bio-Oss Collagen® groups in a critical size rat alveolar bone defect model. GHMS was synthesized by co-precipitating calcium hydroxide and orthophosphoric acid within gelatin solution, incorporating metformin, and cross-linked by microbial transglutaminase. The morphology, characterization, and biocompatibility of scaffold were examined. The in vitro effects of GHMS on osteogenic gene and protein expressions were evaluated. In vivo bone formation was assessed in a critical size rat alveolar bone defect model with micro-computed tomography and histological examination by comparing GHMS with extraction-only, Sinbone, and Bio-Oss Collagen®. The synthesized GHMS had a highly interconnected porous structure with a mean pore size of 81.85 ± 13.8 µm. GHMS exhibited good biocompatibility; promoted ALPL, RUNX2, SP7, BGLAP, SPARC and Col1a1 gene expressions; and upregulated the synthesis of osteogenic proteins, including osteonectin, osteocalcin, and collagen type I. In critical size rat alveolar bone defects, GHMS showed superior bone regeneration compared to extraction-only, Sinbone, and Bio-Oss Collagen® groups as manifested by greater alveolar ridge preservation, while more bone formation with a lower percentage of connective tissue and residual scaffold at the defect sites grafted with GHMS in histological staining. The GHMS presented in this study may be used as a potential bone substitute to regenerate alveolar bone. The good biocompatibility, relatively fast degradation, interconnected pores allowing vascularization, and higher bioactivity properties of the components of the GHMS (gelatin, nHA, and metformin) may contribute to direct osteogenesis.

Varying coefficient frailty models with applications in single molecular experiments.

Motivated by an analysis of single molecular experiments in the study of T-cell signaling, a new model called varying coefficient frailty model with local linear estimation is proposed. Frailty models have been extensively studied, but extensions to nonconstant coefficients are limited to spline-based methods that tend to produce estimation bias near the boundary. To address this problem, we introduce a local polynomial kernel smoothing technique with a modified expectation-maximization algorithm to estimate the unknown parameters. Theoretical properties of the estimators, including their unbiased property near the boundary, are derived along with discussions on the asymptotic bias-variance trade-off. The finite sample performance is examined by simulation studies, and comparisons with existing spline-based approaches are conducted to show the potential advantages of the proposed approach. The proposed method is implemented for the analysis of T-cell signaling. The fitted varying coefficient model provides a rigorous quantification of an early and rapid impact on T-cell signaling from the accumulation of bond lifetime, which can shed new light on the fundamental understanding of how T cells initiate immune responses.

The Relationships among Sport Participation Level, Flow Experience, Perceived Health Status and Depression Level of College Students.

The purpose of this study was to examine the relationships between sport participation level, flow, perceived health status and depression using gender and grades as control variables of college students in Taiwan. Based on previous research, the study established the proposed model: using sport participation level and flow experience as predicting variables, perceived health status and depression as dependent variables, and gender and grades as control variables. A total of 700 structured questionnaires were distributed to college students using convenience sampling among seven universities in Taiwan with a valid return rate of 86.5%. Structural equation modeling was used to test the relationships among the above-mentioned variables. The study found: 1. Male students had higher self-rated health perception than female students. 2. Students with higher grades perceived higher levels of depression than those with lower grades. 3. Among all variables, the level of sport participation had a positive predicting power of perceived health status and a negative predicting power of depression level; perceived health status had a negative predicting power of depression; while flow had no moderating effect among sport participation level, perceived health status and depression. In the model, the predicting variables had a predicting power of 0.58 (R2) for depression, indicating a good model. Conclusions and implications were made according to the findings of the study.

Fast and Accurate Craniomaxillofacial Landmark Detection via 3D Faster R-CNN.

Automatic craniomaxillofacial (CMF) landmark localization from cone-beam computed tomography (CBCT) images is challenging, considering that 1) the number of landmarks in the images may change due to varying deformities and traumatic defects, and 2) the CBCT images used in clinical practice are typically large. In this paper, we propose a two-stage, coarse-to-fine deep learning method to tackle these challenges with both speed and accuracy in mind. Specifically, we first use a 3D faster R-CNN to roughly locate landmarks in down-sampled CBCT images that have varying numbers of landmarks. By converting the landmark point detection problem to a generic object detection problem, our 3D faster R-CNN is formulated to detect virtual, fixed-size objects in small boxes with centers indicating the approximate locations of the landmarks. Based on the rough landmark locations, we then crop 3D patches from the high-resolution images and send them to a multi-scale UNet for the regression of heatmaps, from which the refined landmark locations are finally derived. We evaluated the proposed approach by detecting up to 18 landmarks on a real clinical dataset of CMF CBCT images with various conditions. Experiments show that our approach achieves state-of-the-art accuracy of 0.89 ± 0.64mm in an average time of 26.2 seconds per volume.