Spatial transition tensor of single cells.

Spatial transcriptomics and messenger RNA splicing encode extensive spatiotemporal information for cell states and transitions. The current lineage-inference methods either lack spatial dynamics for state transition or cannot capture different dynamics associated with multiple cell states and transition paths. Here we present spatial transition tensor (STT), a method that uses messenger RNA splicing and spatial transcriptomes through a multiscale dynamical model to characterize multistability in space. By learning a four-dimensional transition tensor and spatial-constrained random walk, STT reconstructs cell-state-specific dynamics and spatial state transitions via both short-time local tensor streamlines between cells and long-time transition paths among attractors. Benchmarking and applications of STT on several transcriptome datasets via multiple technologies on epithelial-mesenchymal transitions, blood development, spatially resolved mouse brain and chicken heart development, indicate STT's capability in recovering cell-state-specific dynamics and their associated genes not seen using existing methods. Overall, STT provides a consistent multiscale description of single-cell transcriptome data across multiple spatiotemporal scales.

Histologically resolved multiomics enables precise molecular profiling of human intratumor heterogeneity.

Both the composition of cell types and their spatial distribution in a tissue play a critical role in cellular function, organ development, and disease progression. For example, intratumor heterogeneity and the distribution of transcriptional and genetic events in single cells drive the genesis and development of cancer. However, it can be challenging to fully characterize the molecular profile of cells in a tissue with high spatial resolution because microscopy has limited ability to extract comprehensive genomic information, and the spatial resolution of genomic techniques tends to be limited by dissection. There is a growing need for tools that can be used to explore the relationship between histological features, gene expression patterns, and spatially correlated genomic alterations in healthy and diseased tissue samples. Here, we present a technique that combines label-free histology with spatially resolved multiomics in unfixed and unstained tissue sections. This approach leverages stimulated Raman scattering microscopy to provide chemical contrast that reveals histological tissue architecture, allowing for high-resolution in situ laser microdissection of regions of interests. These microtissue samples are then processed for DNA and RNA sequencing to identify unique genetic profiles that correspond to distinct anatomical regions. We demonstrate the capabilities of this technique by mapping gene expression and copy number alterations to histologically defined regions in human oral squamous cell carcinoma (OSCC). Our approach provides complementary insights in tumorigenesis and offers an integrative tool for macroscale cancer tissues with spatial multiomics assessments.

Unraveling the key role of chromatin structure in cancer development through epigenetic landscape characterization of oral cancer.

Epigenetic alterations, such as those in chromatin structure and DNA methylation, have been extensively studied in a number of tumor types. But oral cancer, particularly oral adenocarcinoma, has received far less attention. Here, we combined laser-capture microdissection and muti-omics mini-bulk sequencing to systematically characterize the epigenetic landscape of oral cancer, including chromatin architecture, DNA methylation, H3K27me3 modification, and gene expression. In carcinogenesis, tumor cells exhibit reorganized chromatin spatial structures, including compromised compartment structures and altered gene-gene interaction networks. Notably, some structural alterations are observed in phenotypically non-malignant paracancerous but not in normal cells. We developed transformer models to identify the cancer propensity of individual genome loci, thereby determining the carcinogenic status of each sample. Insights into cancer epigenetic landscapes provide evidence that chromatin reorganization is an important hallmark of oral cancer progression, which is also linked with genomic alterations and DNA methylation reprogramming. In particular, regions of frequent copy number alternations in cancer cells are associated with strong spatial insulation in both cancer and normal samples. Aberrant methylation reprogramming in oral squamous cell carcinomas is closely related to chromatin structure and H3K27me3 signals, which are further influenced by intrinsic sequence properties. Our findings indicate that structural changes are both significant and conserved in two distinct types of oral cancer, closely linked to transcriptomic alterations and cancer development. Notably, the structural changes remain markedly evident in oral adenocarcinoma despite the considerably lower incidence of genomic copy number alterations and lesser extent of methylation alterations compared to squamous cell carcinoma. We expect that the comprehensive analysis of epigenetic reprogramming of different types and subtypes of primary oral tumors can provide additional guidance to the design of novel detection and therapy for oral cancer.

Integrating single-cell datasets with ambiguous batch information by incorporating molecular network features.

With the rapid development of single-cell sequencing techniques, several large-scale cell atlas projects have been launched across the world. However, it is still challenging to integrate single-cell RNA-seq (scRNA-seq) datasets with diverse tissue sources, developmental stages and/or few overlaps, due to the ambiguity in determining the batch information, which is particularly important for current batch-effect correction methods. Here, we present SCORE, a simple network-based integration methodology, which incorporates curated molecular network features to infer cellular states and generate a unified workflow for integrating scRNA-seq datasets. Validating on real single-cell datasets, we showed that regardless of batch information, SCORE outperforms existing methods in accuracy, robustness, scalability and data integration.

Differences in the landscape of colonized microorganisms in different oral potentially malignant disorders and squamous cell carcinoma: a multi-group comparative study.

BACKGROUND: The role of microbes in diseases, especially cancer, has garnered significant attention. However, research on the oral microbiota in oral potentially malignant disorders (OPMDs) remains limited. Our study investigates microbial communities in OPMDs. MATERIALS AND METHODS: Oral biopsies from19 oral leukoplakia (OLK) patients, 19 proliferative verrucous leukoplakia (PVL) patients, 19 oral lichen planus (OLP) patients, and 19 oral lichenoid lesions (OLL) patients were obtained. 15 SCC specimens were also collected from PVL patients. Healthy individuals served as controls, and DNA was extracted from their paraffin-embedded tissues. 2bRAD-M sequencing generated taxonomic profiles. Alpha and beta diversity analyses, along with Linear Discriminant Analysis effect size analysis, were conducted. RESULTS: Our results showed the microbial richness and diversity were significantly different among groups, with PVL-SCC resembling controls, while OLK exhibited the highest richness. Each disease group displayed unique microbial compositions, with distinct dominant bacterial species. Noteworthy alterations during PVL-SCC progression included a decline in Fusobacterium periodonticum and an elevation in Prevotella oris. CONCLUSIONS: Different disease groups exhibited distinct dominant bacterial species and microbial compositions. These findings offer promise in elucidating the underlying mechanisms of this disease.

Clinicopathological characteristics and diagnostic accuracy of BRAF mutations in ameloblastoma: A Bayesian network analysis.

OBJECTIVE: This Bayesian network meta-analysis was performed to analyze the associations between clinicopathological characteristics and BRAF mutations in ameloblastoma (AM) patients and to evaluate the diagnostic accuracy. MATERIALS AND METHODS: Four electronic databases were searched from 2010 to 2024. The search terms used were specific to BRAF and AM. Observational studies or randomized controlled trials were considered eligible. The incidence of BRAF mutation and corresponding clinicopathological features in AM patients were subjected to Bayesian network analyses and diagnostic accuracy evaluation. RESULTS: A total of 937 AM patients from 20 studies were included. The pooled prevalence of BRAF mutations in AM patients was 72%. According to the Bayesian network analysis, BRAF mutations are more likely to occur in younger (odds ratio [OR], 2.3; credible interval [CrI]: 1.2-4.5), mandible site (OR, 3.6; 95% CrI: 2.7-5.2), and unicystic (OR, 1.6; 95% CrI: 1.1-2.4) AM patients. Similarly, higher diagnostic accuracy was found in the younger, mandible, and unicystic AM groups. CONCLUSIONS: The incidence, risk, and diagnostic accuracy of BRAF mutation in AM were greater in younger patients, those with mandible involvement, and those with unicystic AM than in patients with other clinicopathological features. In addition, there was a strong concordance in the diagnostic accuracy between molecular tests and immunohistochemical analysis.

CT-based radiomics analysis of different machine learning models for differentiating gnathic fibrous dysplasia and ossifying fibroma.

OBJECTIVE: In this study, our aim was to develop and validate the effectiveness of diverse radiomic models for distinguishing between gnathic fibrous dysplasia (FD) and ossifying fibroma (OF) before surgery. MATERIALS AND METHODS: We enrolled 220 patients with confirmed FD or OF. We extracted radiomic features from nonenhanced CT images. Following dimensionality reduction and feature selection, we constructed radiomic models using logistic regression, support vector machine, random forest, light gradient boosting machine, and eXtreme gradient boosting. We then identified the best radiomic model using receiver operating characteristic (ROC) curve analysis. After combining radiomics features with clinical features, we developed a comprehensive model. ROC curve and decision curve analysis (DCA) demonstrated the models' robustness and clinical value. RESULTS: We extracted 1834 radiomic features from CT images, reduced them to eight valuable features, and achieved high predictive efficiency, with area under curves (AUC) exceeding 0.95 for all the models. Ultimately, our combined model, which integrates radiomic and clinical data, displayed superior discriminatory ability (AUC: training cohort 0.970; test cohort 0.967). DCA highlighted its optimal clinical efficacy. CONCLUSION: Our combined model effectively differentiates between FD and OF, offering a noninvasive and efficient approach to clinical decision-making.

Correlation between gene polymorphism and adverse reactions of high-dose methotrexate in osteosarcoma patients: a systematic review and meta-analysis.

OBJECTIVE: We aimed to provide a reference based on evidence for an individualized clinical medication of high-dose methotrexate (HD-MTX) in osteosarcoma patients by evaluating the effect of gene polymorphism on adverse reactions of HD-MTX usage. METHODS: Several databases were combed for research on the association between gene polymorphisms and adverse reactions to HD-MTX up to January 2023. A meta-analysis and/or descriptive analysis on the incidence of HD-MTX-related adverse reactions were conducted by using clinical studies meeting inclusion criteria. RESULTS: Twelve studies involving 889 patients were included. There were 8, 6, 5, and 4 studies related to MTHFR C677T, MTHFR A1298C, RFC1 G80A, and MDR1 C3435T polymorphisms, respectively. The results of the meta-analysis showed that the MTHFR C677T polymorphism was associated with G3-4 hepatotoxicity, G3-4 nephrotoxicity, G3-4 gastrointestinal toxicity, and G3-4 mucositis under the recessive genetic model (MM vs. Mm/mm). Limited research showed that MTHFR C677T was associated with G3-4 nephrotoxicity in the allelic genetic model (M vs. m). MTHFR A1298C polymorphism was associated with a decreased risk of adverse reactions to HD-MTX usage, without statistical significance. This review's descriptive analysis showed no significant correlation between the RFC1 G80A, and MDR1 C3435T polymorphism and adverse reactions of HD-MTX. CONCLUSION: The MTHFR C677T mutation may enhance the risk of HD-MTX adverse reactions in osteosarcoma patients. Existing studies have not found a significant correlation between the MTHFR A1298C, RFC1 G80A, and MDR1 C3435T polymorphism and adverse reactions caused by HD-MTX. Lastly, this conclusion was limited because of few studies.

Burden of heart failure in Asia, 1990-2019: findings from the Global Burden of Disease Study 2019.

OBJECTIVES: Heart failure (HF) is on the rise as a global health problem, but information on its burden in Asia is limited. This study aimed to assess the burden, trends, and underlying causes of HF in the Asian region. STUDY DESIGN AND METHODS: Data on HF in Asia from 1990 to 2019, including prevalence, years lived with disability (YLD), and underlying causes, were extracted from the Global Burden of Diseases 2019. The cases, the age-standardized prevalence, and the YLD were compared between the age groups, the sexes, the sociodemographic index, and the locations. The proportion of age-standardized prevalence rates of HF attributable to 16 underlying causes was also analyzed. RESULTS: In 2019, the age-standardized prevalence rate of HF per 100,000 persons in Asia was 722.45 (95% uncertainty interval [UI]: 591.97-891.64), with an estimated 31.89 million cases (95% UI: 25.94-39.25). From 1990 to 2019, the prevalence of age-standardized HF in Asia decreased by 4.51%, reflecting the global trend (-7.06%). Age-standardized YLD rates of HF exhibited patterns similar to prevalence rates. Among Asian countries, China had the highest age-standardized prevalence rate, followed by Kuwait and Jordan. Hypertensive heart disease was the leading cause of HF, followed by ischemic heart disease and rheumatic heart disease. CONCLUSIONS: Although the burden of HF in Asia showed a gradual decline between 1990 and 2019, it remains a significant health challenge that requires increased attention. Regional disparities in HF burden are evident, emphasizing the need for urgent prevention and control measures at the regional and national levels.

Adaptive Weighted Data Fusion for Line Structured Light and Photometric Stereo Measurement System.

Line structured light (LSL) measurement systems can obtain high accuracy profiles, but the overall clarity relies greatly on the sampling interval of the scanning process. Photometric stereo (PS), on the other hand, is sensitive to tiny features but has poor geometrical accuracy. Cooperative measurement with these two methods is an effective way to ensure precision and clarity results. In this paper, an LSL-PS cooperative measurement system is brought out. The calibration methods used in the LSL and PS measurement system are given. Then, a data fusion algorithm with adaptive weights is proposed, where an error function that contains the 3D point cloud matching error and normal vector error is established. The weights, which are based on the angles of adjacent normal vectors, are also added to the error function. Afterward, the fusion results can be obtained by solving linear equations. From the experimental results, it can be seen that the proposed method has the advantages of both the LSL and PS methods. The 3D reconstruction results have the merits of high accuracy and high clarity.

Determination and Ecological Risk Assessment of Quinolone Antibiotics in Drinking and Environmental Waters Using Fully Automated Disk-Based SPE Coupled with UPLC-MS/MS.

Quinolone antibiotics (QNs) contamination in the aquatic environment is a global public health issue considering their resistance and mobility. In this study, a simple, efficient, and sensitive method was developed for the accurate quantification of fifteen QNs in water using automated disk-based solid-phase extraction (SPE) coupled with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). By utilizing a 3M SDB-XC disk to enrich QNs from a 1000 mL water sample, the detection limits were improved to 0.008-0.055 ng/L due to the satisfactory enrichment factors of 897-1136, but only requiring about 60 min per six samples. The linearity of the method ranged from 0.05 to 100 µg/L for the 15 QNs, with correlation coefficients of 0.9992-0.9999, and the recoveries were in the range of 81-114%, with relative standard deviations of 0.2-13.3% (n = 6). The developed method was applicable for the quantification of trace QNs at low ng/L levels in drinking and environmental waters. The results showed that no QNs were detected in tap water, while three and four QNs were detected in the river water of Zhoushan and the seawater of Daiquyang and Yueqing Bay, East China, respectively, with a total concentration of 1.600-8.511 ng/L and 1.651-16.421 ng/L, respectively. Among the detected QNs, ofloxacin (OFL) was the predominant compound in river water, while enrofloxacin (ENR) was predominant in seawater. The risk quotient (RQ) results revealed that QNs posed a low risk to crustaceans and fish, but a low-to-medium risk to algae, and OFL presented the main ecological risk factor in river water, while ENR and CIP in seawater. Overall, the proposed automated disk-based SPE-UPLC-MS/MS method is highly efficient and sensitive, making it suitable for routine analysis of QNs in drinking and environmental waters.

Rapid Determination of Tetracyclines in Drinking and Environmental Waters Using Fully Automatic Solid-Phase Extraction with Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry.

The abuse and irrational use of tetracyclines (TCs) in human medicine and animal husbandry has become a serious concern, affecting the ecological environment and human health. The aim of this study was to develop a sensitive and selective method using fully automatic solid-phase extraction coupled with ultra-performance liquid chromatography-tandem mass spectrometry for the determination of twelve TCs in water. Four isotope-labeled internal standards for TCs were used to correct matrix effects. Several parameters affecting extraction efficiency were systematically optimized, and the optimum experimental conditions found were 1.0 L water sample with 0.5 g/L Na2EDTA (pH 3.0) extracted and enriched by CNW HLB cartridge and eluted by 4 mL of acetone:methanol (v/v, 1:1). The enrichment factors were up to 798-1059 but only requiring about 60 min per six samples. Under the optimized conditions, the linearity of the method ranged from 0.2 to 100 µg/L for 12 TCs, the detection limits were as low as 0.01-0.15 ng/L, and the recoveries were in the range of 70%-118%, with relative standard deviations less than 15%. The developed method can be successfully utilized for the determination of 12 TCs in pure water, tap water, river water, and mariculture seawater. In summary, three and six TCs were detected in river water and mariculture seawater, respectively, with total concentrations of 0.074-0.520 ng/L (mean 0.248 ng/L) and 0.792-58.369 ng/L (12.629 ng/L), respectively. Tetracycline (TC) and oxytetracycline (OTC) were the dominant TCs in river water, while doxytetracycline (DXC) and OTC were dominant in mariculture seawater.

Development of a Pathomics-Based Model for the Prediction of Malignant Transformation in Oral Leukoplakia.

Accurate prognostic stratification of oral leukoplakia (OLK) with risk of malignant transformation into oral squamous cell carcinoma is crucial. We developed an objective and powerful pathomics-based model for the prediction of malignant transformation in OLK using hematoxylin and eosin (H&E)-stained images. In total, 759 H&E-stained images from multicenter cohorts were included. A training set (n = 489), validation set (n = 196), and testing set (n = 74) were used for model development. Four deep learning methods were used to train and validate the model constructed using H&E-stained images. Pathomics features generated through deep learning combined with machine learning algorithms were used to develop a pathomics-based model. Immunohistochemical staining of Ki67, p53, and PD-L1 was used to interpret the black box of the model. Pathomics-based models predicted the malignant transformation of OLK (validation set area under curve [AUC], 0.899; testing set AUC, 0.813) and significantly identified high-risk and low-risk populations. The prediction performance of malignant transformation from dysplasia grading (validation set AUC, 0.743) was lower than that of the pathomics-based model. The expressions of Ki67, p53, and PD-L1 were correlated with various pathomics features. The pathomics-based model accurately predicted the malignant transformation of OLK and may be useful for the objective and rapid assessment of the prognosis of patients with OLK.

Comparison of the histopathological characteristics of diffuse sclerosing osteomyelitis of the mandible, chronic suppurative osteomyelitis, and craniofacial fibrous dysplasia.

BACKGROUND: There are relatively few reports on the histopathological characteristics of diffuse sclerosing osteomyelitis of the mandible (DSOM), which is difficult to distinguish from chronic suppurative osteomyelitis (CSO) and craniofacial fibrous dysplasia (CFD). This study aimed to summarize and compare the histopathological characteristics of DSOM, CFD, and CSO. MATERIALS AND METHODS: In this study, hematoxylin and eosin-stained sections of patients with DSOM, CSO, and CFD at the Peking University Hospital of Stomatology from 2015 to 2020 were retrieved. The histopathological characteristics were summarized, including new bone formation, inflammatory cell infiltration, bone trabecular morphology, osteoclasts, sequestrum, bacterial mass, and calcified spherules, similar to cementicles. The histopathological characteristics of DSOM, CSO, and CFD were compared, and the results were statistically analyzed. RESULTS: In total, 50, 13, and 10 patients with DSOM, CSO, and CFD were included in this study, respectively. In terms of new bone formation, both DSOM and CSO showed reactive bone formation (p = 1), whereas CFD mainly showed fiber osteogenesis (p < 0.001). The inflammatory cells of DSOM were mainly lymphocytes and plasma cells, whereas those of CSO were mainly lymphocytes and neutrophils (p < 0.001), and there was usually no inflammatory cell infiltration in the CFD specimens (p < 0.001). DSOM, CSO, and CFD showed irregular bone trabeculae (p = 0.045, p = 0.703) and active osteoclasts (p1 = 0.189, p2 = 0.256). DSOM showed a small amount of bacterial mass but no sequestrum; neither of which was found in CFD (p = 1, p = 1), but it was common in CSO (p = 0.011 and p = 0.025). DSOM and CSO showed smooth and regular basophilic lines (p = 0.308), whereas CFD showed a rough and irregular basophilic line (p < 0.001). CONCLUSIONS: The histopathological characteristics of the three diseases were partly similar, but there were evident differences. The main differences are the type of new bone formation, types and distribution of inflammatory cells, and presence of sequestrum and bacterial masses. These differences will help clinicians diagnose DSOM.

PTCH/SMO gene mutations in odontogenic keratocysts and drug interventions.

BACKGROUND: Odontogenic keratocysts (OKCs) are odontogenic jaw lesions that cause destruction and dysfunction of the jawbone. OKCs can be sporadic or associated with nevoid basic cell carcinoma syndrome (NBCCS). However, the factors that initiate OKCs and the mechanism of cyst formation remain unclear. Here, we investigated the impact of PTCH1 and SMO mutations on disease progression, as well as the effects of sonic hedgehog (SHH) signaling pathway inhibitors GDC-0449 and GANT61 on OKC fibroblasts. METHODS: Eight sporadic OKC fibroblasts without gene mutations were used as the control, and six NBCCS-related fibroblasts were cultured in vitro. The effect of PTCH1 non-truncated mutation 3499G>A (p.G1167R) and SMO c.2081C>G (p.P694R) mutation on OKC fibroblast proliferation was examined by EdU assay. CCK8 and wound-healing assays detected the effects of OKC fibroblasts carrying PTCH1 c.3499G>A (p.G1167R) and SMO c.2081C>G (p.P694R) mutations on the proliferation and migration of HaCaT cells after co-culture. Quantitative real-time PCR detected the effects of GDC-0449 or GANT61 on the SHH signaling pathway in NBCCS-related OKCs with PTCH1 truncated mutations and PTCH1 c.3499G>A (p.G1167R) and/or SMO c.2081C>G (p.P694R) mutations. RESULTS: PTCH1 c.3499G>A (p.G1167R) and SMO c.2081C>G (p.P694R) promoted the proliferation of OKC fibroblasts. The proliferation and migration of HaCaT cells were affected by NBCCS-related OKC fibroblasts carrying PTCH1 c.3499G>A (p.G1167R) and SMO c.2081C>G (p.P694R) mutations. GDC-0449 significantly inhibited the SHH signaling pathway in NBCCS-related OKC fibroblasts with PTCH1 truncated mutations. An NBCCS-related OKC carrying PTCH1 c.3499G>A (p.G1167R) and SMO c.2081C>G (p.P694R) mutations were resistant to GDC-0449 but inhibited by GANT61. CONCLUSIONS: Genetic mutations in OKC fibroblasts may affect the biological behavior of epithelial and stromal cells and cause disease. GDC-0449 could be used to treat OKCs, especially NBCCS-related OKCs with PTCH1 truncated mutations. SMO c.2081C>G (p.P694R) may lead to resistance to GDC-0449; however, GANT61 may be used as an alternative inhibitor.

The preliminary exploration of immune microenvironment in oral leukoplakia concomitant with oral submucosal fibrosis: A comparative immunohistochemical study.

BACKGROUND: Oral leukoplakia concomitant with oral submucous fibrosis is a high-risk oral potentially malignant disorder, but little is known about its immune microenvironment. METHODS: Thirty samples of oral leukoplakia concomitant with oral submucous fibrosis, 30 oral leukoplakia samples, and 30 oral submucous fibrosis samples were collected from two hospitals. Immunohistochemistry was performed to analyze expression of T cell biomarkers [CD3, CD4, CD8, and Forkhead box P3 (Foxp3)], a B cell biomarker (CD20), macrophage biomarkers (CD68 and CD163), an immune inhibitory receptor ligand (PD-L1), and Ki-67. RESULTS: The numbers of CD3+ (p < 0.001), CD4+ (p = 0.018), and CD8+ (p = 0.031) cells in oral leukoplakia concomitant with oral submucous fibrosis were less than those in oral leukoplakia. The number of CD4+ cells (p = 0.035) in oral leukoplakia concomitant with oral leukoplakia was higher than that in oral submucous fibrosis. More CD3+ (p < 0.001), CD4+ (p < 0.001), Foxp3+ (p = 0.019), and CD163+ (p = 0.029) cells were found in oral leukoplakia than in oral submucous fibrosis. CONCLUSION: Various levels of immune infiltration were observed among oral leukoplakia concomitant with oral submucous fibrosis, oral leukoplakia, and oral submucous fibrosis. Characterization of the immune microenvironment may contribute to personalized immunotherapy.

Nonlinear phase error correction method based on multi-grayscale coding.

Fringe projection profilometry is a non-contact and highly efficient 3D measurement technique widely used in various applications. However, the nonlinear intensity response of digital projectors affects measurement accuracy. While increasing the number of fringe projections can reduce the errors caused by nonlinear problems, it significantly prolongs the measurement time. In order to improve both accuracy and speed simultaneously, a nonlinear phase error correction method based on multi-grayscale coding is proposed. The intensity response curve of the system is fitted by the grayscale images, and then the grayscale values of the phase-shifting fringe images are corrected to reduce the nonlinear error. In order to reduce the number of fringe projections and speed up the measurement, the multi-grayscale coding method is used to divide the phase interval by the order of the gray values of the same pixel in multiple grayscale images. The experimental results validate the efficacy of the proposed multi-grayscale coding method. An accurate phase calculation is achieved, and a single reconstruction can be achieved with only seven photos. After the nonlinear correction, the phase accuracy of the three-step phase-shifting algorithm is increased by 50.77%, and the reconstruction accuracy of the standard ball is increased by 46.38%.

Notch activation promotes bone metastasis via SPARC inhibition in adenoid cystic carcinoma.

OBJECTIVES: We aimed to investigate bone metastasis induced by Notch signalling pathway dysregulation and to demonstrate that SPARC is a potential therapeutic target in adenoid cystic carcinoma (AdCC) with Notch dysregulation. MATERIALS AND METHODS: This retrospective study enrolled 144 AdCC patients. RNA-sequencing and enrichment analyses were performed using 32 AdCC samples. Osteonectin/SPARC and the Notch activation indicator Notch intracellular domain (NICD) were detected using immunohistochemistry. Cell proliferation and migration assays were conducted using stably NICD over-expressing cells. The effect of SPARC on osteoclast differentiation in NICD cells was investigated using western blotting, quantitative reverse transcription PCR, tartrate-resistant acid phosphatase staining and resorption assays. RESULTS: RNA-sequencing analysis showed that genes down-regulated in Notch-mutant AdCCs, such as SPARC, were enriched in ossification and osteoblast differentiation. Most (75/110, 68.2%) Notch1-wild-type AdCCs showed SPARC over-expression, whereas 30 out of 34 (88.2%) Notch1-mutant tumours showed low SPARC expression. SPARC over-expression was then found negatively to be correlated with NICD expression in 144 AdCCs. NICD over-expression promoted cell growth, migration and osteoclast differentiation, which could be partly reversed by exogenous SPARC. CONCLUSIONS: Notch activation in AdCC contributes to bone metastasis through SPARC inhibition. The study results suggest that SPARC may represent a prognostic biomarker and potential therapeutic target.

Architectural and cytological features of epithelial dysplasia associated with transformation risk.

OBJECTIVES: This study explored associations between histological features of dysplasia and malignant transformation, as well as genomic copy number alterations. MATERIALS AND METHODS: Overall, 201 samples were collected from patients of oral leukoplakia. The associations of dysplastic features with malignant transformation and copy number alterations were investigated by Cox proportional hazards regression analysis and the Mann-Whitney U-test. RESULTS: Eight individual histological features, such as irregular epithelial stratification (p = 0.001), mitoses high in epithelium (p = 0.033), extension of changes along minor gland ducts (p < 0.001), etc., were associated with greater risk of malignant transformation. A model including histological features and age showed good performance for predicting malignant transformation (area under receiver operating characteristic curve: 0.806). Irregular epithelial stratification (p = 0.007), abnormal nuclear shape (p = 0.005), abnormal cell size (p = 0.004), etc. were associated with greater genomic instability. CONCLUSIONS: A Cox proportional hazards model using eight histological features and patient age reliably predicted the malignant potential of oral epithelial dysplasia. Identification of these histological features closely related to malignant transformation may aid the management of oral potentially malignant disorders and early detection of oral squamous cell carcinoma.

Causal association between heart failure and bone mineral density: Insights from a two-sample bidirectional Mendelian randomization study.

In recent times, the association between HF and BMD has attracted enormous interest in the scientific community. However, published epidemiological observational studies on the relationship between HF and BMD remain inconclusive. Herein, we evaluated from the analytical perspective a two-sample bidirectional MR study to analyze the causal association between HF and BMD using a summary-level GWAS Catalog. To select instrumental SNPs strongly associated with exposure, we took a series of rigorous quality control steps at the time of analysis. The causal MR assessment of HF on the risk of BMD was performed first and then in the opposite direction. To make the conclusions more reliable and robust, the fixed-effects IVW, weighted median-based method, MR-Egger, simple mode and weighted mode were utilized. A maximum likelihood model was also used if necessary. MR-Egger regression, IVW "leave-one-out" sensitivity analysis, MR-PRESSO, MR-Egger intercept test and Cochran's Q statistic methods were used to assess heterogeneity and pleiotropy. Our MR studies supported a meaningful causal association between HF and TB-BMD (IVW: OR = 0.78, 95% CI: 0.68-0.87, p = 0.00588). At the same time, we did not find a significant causal relationship between HF and FA-BMD, FN-BMD or LS-BMD. No significant causal relationships between BMD and HF were observed. This bidirectional MR analysis suggested a causal association of HF with only low TB-BMD, while the reverse causality hypothesis was not found. Studies of the prevention and treatment of total bone mineral density decline in patients with heart failure need to be performed.