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Objective To assess the concordance of tumour grade in specimens obtained from diagnostic cystoscopic biopsy and transurethral resection of bladder tumour (TURBT) and explore the risk factors of upgrading. Methods The medical records of 205 outpatients who underwent diagnostic cystoscopic biopsy before initial TURBT were retrospectively reviewed. Comparative analysis of the tumour grade of biopsy and operation specimens was performed. Tumour grade changing from low-grade (LG) to high-grade (HG) with or without variant histology was defined as upgrading. Univariate and multivariate logistic regression analyses were performed to identify the risk factors of upgrading. Results For the 205 patients, the concordance of tumour grade between biopsy and operation was 0.639. The concordance for patients who were preoperatively diagnosed with LG and HG was 0.504 and 0.912, respectively. Univariate and multivariate logistic regression analyses showed that older age, tumour multifocality, high neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and low lymphocyte-to-monocyte ratio (LMR) were significantly associated with upgrading (odds ratio [OR] ranging from 0.412 to 4.364). The area under the curve of the different multivariate models was improved from 0.752 to 0.821, and decision curve analysis demonstrated a high net benefit when NLR, LMR, and PLR were added. Moreover, the nomogram was well calibrated. Conclusions Diagnostic cystoscopic biopsy may not accurately represent the true grade of new bladder cancer, especially for outpatients with LG. Moreover, older age, tumour multifocality, high NLR, PLR, and low LMR are risk factors of upgrading, and systemic inflammatory markers improve the predictive ability.

The upregulation of programmed death-ligand 1 (PD-L1) and epidermal growth factor receptor 2 (HER2) may play a role in gastric adenocarcinoma (GAC).To study PD-L1 and HER-2 expression and prognosis in GAC.PD-L1 and HER2 expression was determined in tumor tissues of 75 patients with GAC. The correlations between PD-L1, HER2 expression, and clinicopathological factors were analyzed.The positive expression rate for PD-L1 was 57.3% (43/75) and the HER2 over-expression rate was 17.3% (13/75). PD-L1 expression negatively correlated with the grade of GAC differentiation (r =-0.26, P0.05). Approximately 85% of HER2-positive GACs were found to be PD-L1-positive and PD-L1 expression positively correlated with HER2 overexpression. The TNM stage and combined HER2 and PD-L1 expression were independent prognostic factors affecting the survival of patients with GAC. The median overall survival and recurrence-free survival of groups I (HER2 overexpression and PD-L1 positive), II (HER2 overexpression and PD-L1 negative), III (No HER2 overexpression and PD-L1 positive) and IV (No HER2 overexpression and PD-L1 negative) were (47 (17-77), 15 (0-44), 81 (62-101), and 78 (60-98) months, respectively.PD-L1 expression is upregulated in more than half of patients with GAC. Anti-PD-L1 treatment combined with anti-HER2 therapy may benefit patients with locally advanced GAC with HER2 overexpression.

Lithium/carbon fluoride (Li/CFx) batteries have been widely researched due to their high theoretical specific energy. To create a high-performance electrode, the fluorinated hard carbon (FHC) is prepared by direct gas-phase fluorination. It has a high F/C ratio of 0.95 based on the gravimetric method. Selecting hard carbon (HC) with a high surface area as the carbon source allows for FHC to achieve suitable interlayer spacing and specific surface area, as well as abundant pore structures to facilitate rapid lithium ion transportation. Additionally, a composite of graphene and carbon nanotubes (CNTs) is coated on the surface of FHC, enhancing electron transport speed. The resulting FHC&C exhibits a very high energy density of 1256 Wh kg−1 and an excellent power density of 72,929 W kg−1 at a high rate of 40 C. Moreover, compared to commercial CFx, FHC&C exhibits higher energy and power densities, thus presenting a promising practical application prospect.

With the development of active safety technology, effort has gradually shifted to preventing or minimizing car crashes. Automatic Emergency Braking Technology (AEB) can avoid accidents by warning and even automatic braking, but there is a contradiction between the accompanying occupant out-of-position and traditional passive safety design. In addition, the 2025 version of C-NCAP plans to add neck injury assessment requirements for AEB [1]. In order to study the kinematic response of the occupant's neck under AEB, a neck finite element model with active muscle force is established in this paper. Firstly, the open-source THOR-50M neck geometric model is used for finite element discretization. Secondly, the neck FE model of THOR-50M is verified through the qualification procedure of the NHTSA standard. Thirdly, according to the geometric features of human neck muscles in Zygote Body database, the neck muscle parameters are preliminarily determined. Finally, the neck muscle parameters are corrected based on the occupant out-of-position test under AEB conditions. The benchmarking results show the model can truly reflect the head and neck movements of the occupants under AEB conditions. The neck FE model developed in this work can be used for the development and test evaluation of intelligent occupant restraint systems.

The traditional finite element method (FEM) could only provide acceptable numerical solutions for the Helmholtz equation in the relatively small wave number range due to numerical dispersion errors. For the relatively large wave numbers, the corresponding FE solutions are never adequately reliable. With the aim to enhance the numerical performance of the FEM in tackling the Helmholtz equation, in this work an extrinsic enriched FEM (EFEM) is proposed to reduce the inherent numerical dispersion errors in the standard FEM solutions. In this extrinsic EFEM, the standard linear approximation space in the linear FEM is enriched extrinsically by using the polynomial and trigonometric functions. The construction of this enriched approximation space is realized based on the partition of unity concept and the highly oscillating features of the Helmholtz equation in relatively large wave numbers can be effectively captured by the employed specially-designed enrichment functions. A number of typical numerical examples are considered to examine the ability of this extrinsic EFEM to control the dispersion error for solving Helmholtz problems. From the obtained numerical results, it is found that this extrinsic EFEM behaves much better than the standard FEM in suppressing the numerical dispersion effects and could provide much more accurate numerical results. In addition, this extrinsic EFEM also possesses higher convergence rate than the conventional FEM. More importantly, the formulation of this extrinsic EFEM can be formulated quite easily without adding the extra nodes. Therefore, the present extrinsic EFEM can be regarded as a competitive alternative to the traditional finite element approach in dealing with the Helmholtz equation in relatively high frequency ranges.

To prepare high-permittivity composite materials for dielectrically functional gradient materials (d-FGMs) by the stereolithographic 3D-printing technique, three ceramic powders (i.e., alumina, barium titanate, and strontium titanate) are selected as functional fillers for a UV-curable resin matrix. The viscosity and UV curing depth of the uncured slurry are tested for feasibility of 3D printing. Comprehensive electrical properties, including volume resistivity, permittivity, dielectric loss, and breakdown strength of the cured composites are measured. The effects of the filler types, morphologies, particle sizes, and volume fractions on the UV curing characteristics of the slurry and dielectric properties of cured composites are systematically analyzed. The experimental results show that spherical fillers with large particle sizes, smooth surfaces, and high permittivity are conducive for reducing the slurry viscosity, increasing curing depth and adjusting the composite’s permittivity over a wide range. We believe that the proposed strategy for material system establishment can improve the 3D printability of high-permittivity composites and promote other applications of the d-FGMs by the stereolithography technique.

Polymer dielectrics are widely used as insulation in electronic and electrical equipment. The charge transport process in polymer dielectrics under a high electric field, which is considered to result in electrical aging and even breakdown of equipment insulation, has attracted considerable attention. Based on a localized charge transfer model, the charge transport mechanism for typical silicone rubber (SR) insulating materials was studied by multiscale methods. A model of silicone rubber oligomers under standard conditions was generated by classical molecular dynamics. The frontier molecular orbitals and projected density of states for the SR oligomer were obtained via quantum chemistry methods. The electronic coupling, reorganization energy, and free energy difference for both electron and hole transfer processes between adjacent SR molecules in the molecular dynamics model were calculated. Both hole transfer and electron transfer in SR conform to an intermolecular hopping mechanism due to their high intramolecular reorganization energy and low intermolecular electronic coupling. The results of normal mode analysis for reorganization energy indicate that the high-temperature approximation holds for charge transport in SR around or above room temperature. The charge transfer trajectory and charge mobility in SR were simulated based on kinetic Monte Carlo simulations. The hole and electron mobilities at room temperature were calculated to be 7.24 × 10

ObjectiveBesides breast and gastric cancer, HER2 amplification/mutation are also found in lung adenocarcinoma (LUAD). However, the correlation between HER2 variations and the phenotype of immunogenicity and tumor immune microenvironment (TIME) in LUAD compared with breast and gastric cancer has yet to be fully elucidated.MethodsWe integrated public databases (discovery set) and internal data (validated set) of 288 patients representing three distinct HER2-altered tumors. Genomic data were used to identify somatic mutations, copy number variations, and calculate tumor mutational burden (TMB) and microsatellite instability score. RNA sequencing was conducted to estimate immune gene signatures and contents of tumor-infiltrating immune cell populations. Finally, IHC was used to determine PD-L1 expression and the tumoral-infiltration of immune cells in 50 HER2-variant tumor specimens with no prior therapeutic regimens.ResultsCompared with HER2-amplified breast and gastric cancers, patients with HER2-amplified LUAD showed higher immunogenicity, mainly manifested in immune checkpoints expression and tissue/blood TMB. Additionally, HER2-amplified LUAD exhibited an inflamed TIME with remarkably increased genes encoding HLAs, T-cell activity and immune cell-type, and accompanied with tumor‐infiltrating lymphocytes. In LUAD, patients with HER2 amplification possessed higher tissue TMB than HER2 mutation, whereas no difference was observed in PD-L1 expression. HER2 amplification (primary) was associated with significantly higher PD-L1 expression and TMB than acquired HER2 amplification after resistance to EGFR-TKIs.ConclusionPatients with HER2-amplified LUAD have better immunogenicity and/or an inflamed TIME among HER2-aberrant tumors. Our study may provide clues for establishing the benefits and uses of ICIs for patients with this disease.

Several optimization algorithms based on the Back Propagation (BP) neural network are often used to improve the fitting accuracy of GNSS height anomaly. However, the performance and applicability of these algorithms have not been systematically studied. This study takes two kinds of GNSS/leveling points with different spatial distributions as examples, evaluates the performance and applicability of commonly used genetic algorithm (GA), simulated annealing algorithm (SA), particle swarm optimization (PSO), and the latest sparrow search algorithm (SSA) methods in improving the fitting accuracy of BP neural network. Additionally, this study also attempts to add the input data related to terrain for the first time to analyze whether it can improve the fitting accuracy under uneven point distribution. Results show that these optimization algorithms can significantly improve the accuracy and stability of the BP neural network fitting results, and PSO and SSA methods indicate the best improvement. Additionally, when the distribution of fitting points is uneven, adding appropriate input data can also effectively improve the reliability of the BP neural network.

Cellulose insulating paper is widely used in the power industry for its good electrical insulating properties. Moisture sharply increases its conductivity, which directly leads to the weakening of insulation performance and greatly increases the risk of subsequent electric field distortion and insulation breakdown. This paper focuses on the microscopic mechanism of moisture changing the characteristics of charge transport in cellulose insulation and attempts to reveal the related conductivity mechanism. To achieve this purpose, microscopic and macroscopic perspectives are integrated and several simulation and experimental methods are utilized comprehensively. The molecular dynamics simulation results showed that most water molecules in damped cellulose were individually and uniformly adsorbed on the hydroxyl groups by hydrogen bond, and the quantum chemistry computation results showed that the lowest unoccupied molecular orbital more appeared on the water molecule and the corresponding density of state increased. Then, experimentally, it was confirmed that the trap energy level decreased by the thermally stimulated current method. On this basis, the promotion effect of moisture on charge transport is predicted and verified by polarization and depolarization current methods. As the moisture content increased, more charge carriers escaped from the trap by hopping and participated in long-range continuous charge motion. Therefore, after dampness, the current of cellulose insulating paper increased exponentially with the increase in electric field strength, which was consistent with the hopping conductivity mechanism.

Chromium (Cr) and the emission of its compounds into the environment have caused long-term environmental contamination. In this study, the modes of occurrence of Cr in low-rank coal and their thermal stability in pyrolysis were investigated by sequential chemical extraction (SCE), single-component samples (SCS) pyrolysis, and thermochemical equilibrium simulation. The results showed that organic matter, aluminosilicate, and carbonate were the dominant modes of occurrence of Cr in low-rank coal. The modes of occurrence and chlorine (Cl) content affected the volatilization of Cr in coal. The characteristic release temperature range of Cr bounded to aluminosilicate was >600 °C and 400–600 °C for Cr bounded to a disulfide. Cr bounded to organic matter almost released completely before 600 °C. Cl enhanced the volatility of Cr and reduced its release temperature in Cr bounded to aluminosilicate. The simulation showed the content of gas products was very low, mainly chlorides. While the content of solid products, sulfides, and oxides, was much higher than gas products, showing their high thermal stability. The sulfides and oxides in chars were closely related to the carbonate and aluminosilicate bound form of Cr. The results of the equilibrium simulation were consistent with the experimental results.

The impacts of carrier type on anammox community assembly, species interactions and nitrogen conversion were studied in this work. It was found that in addition to shared species with higher abundance, different carrier types recruited rare species by imposing selection pressure. Results from co-occurrence networks revealed that carrier type strongly influenced interactions between keystone species inhabiting within anammox biofilm through potentially inducing niche differences. Overall, elastic cubic sponges would lead to closer cooperation between different populations, whereas plastic hollow cylinders would trigger fiercer competition. Meanwhile, the results based on metagenomics sequencing showed carrier type significantly affected nitrogen conversion related genes abundances, and higher reads number was detected on the elastic cubic sponges. The information obtained in this work could provide some valuable information for the selection and optimization of carrier type in the anammox process.

Fused deposition modeling (FDM) has demonstrated its effectiveness in the additive manufacturing (AM) field thanks to its numerous merits, such as low cost and ease of implementation. Polymeric polylactic acid (PLA) has been widely used in FDM attributed to its recyclable, renewable, degradable and biocompatible characteristics. However, the material properties of polymeric materials can be largely affected by temperature and strain rate; and the mechanical behavior of polymer printed by FDM are fairly different from those manufactured by traditional technology. In this study, uniaxial tensile tests of the PLA specimens printed by FDM are performed under different strain rates and temperatures. For the first time, the digital image correlation (DIC) technique is employed to capture the surface strain of the AM specimens under loading, allowing us to quantify thermal stress concentration in the FDM printed polymer. Significant strain localization induced by the embrittlement of PLA is identified by the DIC system. The scanning electron microscope (SEM) technique is used to characterize the failure modes and failure mechanisms of the printed PLA samples. With increasing strain rate or decreasing temperature, the ductile to brittle failure modes can be observed by SEM. The modified Zener model is developed here to predict the stress–strain responses accounting for the combined effects of strain rate and temperature with proper modeling accuracy. The Cowper–Symonds material model is also employed to describe the effect of the strain rate on yield strength with a maximum 3.2% relative error between the experimental results and the theoretical model. Further, the yield strength, failure strain and Young's modulus show a strong linear correlation with temperature. This study is anticipated to provide an effective and precise material model for the mechanical analysis of composite structural components made by the additive manufacturing process.

Background: We aimed to study the mechanism of sacral nerve injury caused by sacral fractures and the relationship between nerve decompression and nerve function.Methods: First, we observed the anatomical features of lumbosacral nerve root region in Sprague-Dawley rats. Next, the rats were divided into the sham, 10 g, 30 g, and 60 g groups for electrophysiological studies on nerve root constriction injury. Then we studied the biomechanical properties of rat nerve roots, lumbosacral trunk, and sacrum. Finally, we established a finite element analysis model of sacral nerve roots injury in rats and determined the correlation between sacral deformation and the degree of sacral nerve roots injury.Result: Anatomical study showed L5 constitutes sciatic nerve, the length of the L5 nerve root is 3.67 ± 0.15 mm, which is suitable for electrophysiological research on nerve root compression injury. After a series of electrophysiological study of L5 nerve roots, our results showed that nerve root function was almost unaffected at a low degree of compression (10 g). Nerve root function loss began at 30 g compression, and was severe at 60 g compression. The degree of neurological loss was therefore positively correlated with the degree of compression. Combining biomechanical testing of the lumbosacral nerve roots, finite element analysis and neuroelectrophysiological research, we concluded when the sacral foramina deformation is >22.94%, the sacral nerves lose function. When the compression exceeds 33.16%, early recovery of nerve function is difficult even after decompression.Conclusion: In this study, we found that the neurological loss was positively correlated with the degree of compression. After early decompression, nerve root function recovery is possible after moderate compression; however, in severe compression group, the nerve function would not recover. Furthermore, FEA was used to simulate nerve compression during sacral fracture, as well as calculate force loading on nerve with different deformation rates. The relationship between sacral fractures and neurological loss can be analyzed in combination with neurophysiological test results.

Besides breast and gastric cancer,We integrated public databases (discovery set) and internal data (validated set) of 288 patients representing three distinctCompared withPatients with

Objectives: The soaring demand for endometrial cancer screening has exposed a huge shortage of cytopathologists worldwide. To address this problem, our study set out to establish an artificial intelligence system that automatically recognizes and diagnoses pathological images of endometrial cell clumps (ECCs). Methods: We used Li Brush to acquire endometrial cells from patients. Liquid-based cytology technology was used to provide slides. The slides were scanned and divided into malignant and benign groups. We proposed two (a U-net segmentation and a DenseNet classification) networks to identify images. Another four classification networks were used for comparison tests. Results: A total of 113 (42 malignant and 71 benign) endometrial samples were collected, and a dataset containing 15,913 images was constructed. A total of 39,000 ECCs patches were obtained by the segmentation network. Then, 26,880 and 11,520 patches were used for training and testing, respectively. On the premise that the training set reached 100%, the testing set gained 93.5% accuracy, 92.2% specificity, and 92.0% sensitivity. The remaining 600 malignant patches were used for verification. Conclusions: An artificial intelligence system was successfully built to classify malignant and benign ECCs.

Tumor infiltration pattern (INF) and tumor origin site were reported to significantly affect the prognosis of gastric cancer (GC), while the immune status under these contexts is not clear. In this study, we correlated the density and phenotype of tumor-infiltrating lymphocytes (TILs) with INF and the tumor origin site to reflect the biological behavior of tumors from a new perspective and also determined their effects on overall survival (OS) and other related clinicopathological features in archival samples of 147 gastric cancers with 10-year follow-up data. We found that the INFc growth pattern (an invasive growth without a distinct border) of GC lacked immune cell infiltration, particularly the cytotoxic T cells and their activated form. It is also significantly associated with an unfavorable prognosis (P < 0.001) and proximal site (P = 0.001), positive lymph node metastasis (P = 0.002), and later tumor–node–metastasis stage (P < 0.001). Moreover, the density and sub-type of TILs infiltration were significantly different in disparate differentiated areas for the tumor tissue with INFb. Compared with distal gastric cancer, proximal gastric cancers were prone to grow in an INFc pattern (P = 0.001) and infiltrated with fewer TILs, experiencing a shorter survival time (P = 0.013). Multivariate analysis showed that only the INF and the density of TILs were demonstrated to be the independent prognostic factors of OS for the GC. We concluded that GC with an aggressive growth pattern arising from proximal sites always had a weak immune response and resulted in a poor prognosis. The interaction between them and their synergistic or antagonistic effects in the development of tumors need to be further studied. This study opens up a new perspective for research on the biological behavior of the tumor.

Most current vision-based fatigue detection methods don’t have high-performance and robust face detector. They detect driver fatigue using single detection feature and cannot achieve real-time efficiency on edge computing devices. Aimed at solving these problems, this paper proposes a driver fatigue detection system based on convolutional neural network that can run in real-time on edge computing devices. The system firstly uses the proposed face detection network LittleFace to locate the face and classify the face into two states: small yaw angle state “normal” and large yaw angle state “distract.” Secondly, the speed-optimized SDM algorithm is conducted only in the face region of the “normal” state to deal with the problem that the face alignment accuracy decreases at large angle profile, and the “distract” state is used to detect driver distraction. Finally, feature parameters EAR, MAR and head pitch angle are calculated from the obtained landmarks and used to detect driver fatigue respectively. Comprehensive experiments are conducted to evaluate the proposed system and the results show its practicality and superiority. Our face detection network LittleFace can achieve 88.53% mAP on AFLW test set at 58 FPS on the edge computing device Nvidia Jetson Nano. Evaluation results on YawDD, 300 W, and DriverEyes show the average detection accuracy of the proposed system can reach 89.55%.

The 0.2% strain offset approach is mostly used to calculate the yield stress and serves as an efficient method for cross-lab comparisons of measured material properties. However, it is difficult to accurately determine the yield of the bone. Especially when computational models require accurate material parameters, clarification of the yield point is needed. We tested 24 cortical specimens harvested from six bovine femora in three-point bending mode, and 11 bovine femoral cortical specimens in the tensile mode. The Young's modulus and yield stress for each specimen derived from the specimen-specific finite element (FE) optimization method was regarded as the most ideal constitutive parameter. Then, the strain offset optimization method was used to find the strain offset closest to the ideal yield stress for the 24 specimens. The results showed that the 0 strain offsets underestimated (- 25%) the yield stress in bending and tensile tests, while the 0.2% strain offsets overestimated the yield stress (+ 65%) in three-point bending tests. Instead, the yield stress determined by 0.007 and 0.05% strain offset for bending and tensile loading respectively, can effectively characterize the biomechanical responses of the bone, thereby helping to build an accurate FE model.

Suppressor of Ty 16 (Spt16) is a component of the facilitates chromatin transcription (FACT) complex, which is a histone chaperone and involved in gene transcription, DNA replication, and DNA repair. Previous studies showed that FACT is highly expressed in cancer, and cancer cells are more reliant on FACT than normal cells. However, the relationship between Spt16 and lung cancer remains unclear. In this study, we explored the functions of Spt16 in lung cancer cells. The effects of Spt16 on lung cancer cell proliferation, cell cycle progression, apoptosis, migration, and invasion were examined. We found that knockdown of Spt16 led to obvious decreases of both Rb and MCM7, and further activated the DNA damage response (DDR) pathway. In addition, a novel micro‐RNA, miR‐1227‐5p, directly targeted the 3′‐UTR of Spt16 and regulated the mRNA levels of Spt16. Furthermore, we found that CBL0137, the functional inhibitor of FACT, showed similar effects as loss of Spt16. Together, our data indicated that Spt16 is likely to be an essential regulator for lung cancer malignancy and is negatively regulated by miR‐1227‐5p., In this study, we examined the functions of suppressor of Ty 16 (Spt16) in lung cancer cells. We showed that Spt16 is upregulated in lung cancers and is correlated with the poor prognosis of lung cancer patients. Knockdown of Spt16 in lung cancer cells inhibited the proliferation and metastasis of lung cancer cells both in vitro and in vivo. We also determined a novel mechanism for the regulation of Spt16 expression by miRNA‐1227‐5p.

Tumor-promoting inflammation is a hallmark of cancer and is highly associated with tumor progression, angiogenesis, and metastasis. Tumor-associated macrophages (TAMs) are major drivers of tumor-promoting inflammation, but due to the complexity of the tumor microenvironment, the detailed regulatory mechanisms are still under investigation. Here, we investigated a novel role for transglutaminase 2 (TGM2) in the development of tumor-promoting inflammation and recruitment of TAMs to gastric cancer (GC) tissues. When estimated by array comparative genomic hybridization and droplet digital PCR, the copy numbers of the TGM2 gene were amplified in 13.6% (14/103) of GC patients and positively associated with TGM2 expression. Gene set enrichment analysis of expression microarray data for GC samples with high or low TGM2 expression showed that increased TGM2 expression was associated with tumor-promoting inflammation in GC. In addition, the expression of TGM2 was correlated with the expression of markers for macrophages, neutrophils, blood vessels, and lymphatic vessels. Overexpression of TGM2 in GC cells augmented the IL-1β-induced secretion of macrophage-recruiting chemokines and NF-κB activation. TGM2 protein levels were associated with the expression levels of the macrophage marker CD163 in human GC tissue samples. Moreover, GC patients with high expression of TGM2 had a worse prognosis than those with low expression of TGM2. These results suggest TGM2 as a novel regulator of the tumor microenvironment of GC and provide a promising target for constraining tumor-promoting inflammation., Stomach cancer: Enzyme promotes problematic inflammation An enzyme linked to harmful inflammation that promotes tumor growth could be a target for stomach cancer treatment. The expression of the enzyme transglutaminase 2 (TGM2) has been shown to increase in several types of cancer, but its precise role has been unclear. Sung-Yup Cho at Seoul National University College of Medicine, Korea and co-workers measured copy numbers and expression levels of TGM2 in gastric cancer cell lines and in tissue samples from patients undergoing gastrectomy. They found that higher levels of TGM2 were closely associated with increases in various genes that promote the recruitment and activity of tumor-associated macrophages, malfunctioning white blood cells that drive tumor-promoting inflammation. In addition, stomach cancer patients with higher expression of TGM2 had poorer prognoses, indicating the potential therapeutic value of targeting this enzyme.

Visceral angiosarcomas are rare malignant tumors with poor prognosis. The pathogenesis remains unclear. Herein, we describe the morphological, immunohistochemical, and C-MYC status of a series of visceral angiosarcomas. We evaluated the clinicopathologic and C-MYC status of visceral angiosarcomas (n = 12) and compared them to a control series of angiosarcomas arising in cutaneous (n = 15) and soft tissue structures (n = 15). Clinical follow-up data were obtained for all patients and exhibited high metastasis and mortality rates. Malignant endothelial cells displayed a range of morphological features including nonepithelioid, epithelioid, and mixed features, forming vasoformative (n = 6), solid (n = 4) or mixed (n = 2) architectures. Epithelioid morphology was present in 4/12 tumors. Mitoses ranged from 3 to 60 per 10 high-power fields. Necrosis was observed in 10/12 tumors. By immunohistochemistry, all angiosarcomas expressed at least 2 markers of endothelial differentiation, including CD31, CD34, vWF, ERG, and Fli-1. Eight cases of C-MYC amplification and 5 cases of C-MYC translocation were detected. Our data showed that visceral angiosarcoma is more common in women, and the clinical presentations of patient age and tumor size were significantly different between the study and control groups. No significant difference in staining between the visceral angiosarcoma and control groups was observed for endothelial markers, while different C-MYC statuses were detected.

The study of histopathological phenotypes is vital for cancer research and medicine as it links molecular mechanisms to disease prognosis. It typically involves integration of heterogenous histopathological features in whole-slide images (WSI) to objectively characterize a histopathological phenotype. However, the large-scale implementation of phenotype characterization has been hindered by the fragmentation of histopathological features, resulting from the lack of a standardized format and a controlled vocabulary for structured and unambiguous representation of semantics in WSIs. To fill this gap, we propose the Histopathology Markup Language (HistoML), a representation language along with a controlled vocabulary (Histopathology Ontology) based on Semantic Web technologies. Multiscale features within a WSI, from single-cell features to mesoscopic features, could be represented using HistoML which is a crucial step towards the goal of making WSIs findable, accessible, interoperable and reusable (FAIR). We pilot HistoML in representing WSIs of kidney cancer as well as thyroid carcinoma and exemplify the uses of HistoML representations in semantic queries to demonstrate the potential of HistoML-powered applications for phenotype characterization.