Subcutaneous Angioleiomyoma: Clinical and Sonographic Features With Histopathologic Correlation.

OBJECTIVES: To investigate clinical and sonographic features of subcutaneous angioleiomyoma with histopathologic correlation. METHODS: Clinical features of 141 cases and sonographic appearances of 33 cases of histopathologically proven subcutaneous angioleiomyoma were retrospectively reviewed. Clinical information included patient age, sex, tumor location, and symptoms. Sonographic features included tumor size, location, contour, margin, component, echogenicity, calcifications, and vascularity. Sonograms were analyzed with histopathologic correlation by a single radiologist and a single pathologist. RESULTS: Clinical features of the 141 cases of angioleiomyoma included the following: 78.0% of the cases (110 of 141) were on the lower leg or ankle; 55.3% of the patients (78 of 141) had pain at the tumor location; the female-to-male ratio was 1.61:1.00, and most cases occurred in patients in the third through sixth decades. Sonographic features of the 33 cases of angioleiomyoma included the following: 85.0% of the cases (28 of 33) were smaller than 20 mm; 94.0% to 97.0% were solid, oval, parallel to the skin, well defined, and homogeneously hypoechoic and without calcifications; 75.8% (25 of 33) were superficially located, close to or in contact with the dermis; and 39.4% (13 of 33) showed low or moderate internal vascularity. CONCLUSIONS: Typical clinical and sonographic features of angioleiomyoma may include a female patient with a painful lower leg or ankle subcutaneous mass, a superficial location, especially in contact with the dermis, a small size (<20 mm), an oval shape, a parallel orientation to the skin, well-defined margins, complete solid components, homogeneous hypoechogenicity, low or moderate vascular density, and absence of calcifications.

Bibliometric analysis of artificial intelligence and optical coherence tomography images: research hotspots and frontiers.

AIM: To explore the latest application of artificial intelligence (AI) in optical coherence tomography (OCT) images, and to analyze the current research status of AI in OCT, and discuss the future research trend. METHODS: On June 1, 2023, a bibliometric analysis of the Web of Science Core Collection was performed in order to explore the utilization of AI in OCT imagery. Key parameters such as papers, countries/regions, citations, databases, organizations, keywords, journal names, and research hotspots were extracted and then visualized employing the VOSviewer and CiteSpace V bibliometric platforms. RESULTS: Fifty-five nations reported studies on AI biotechnology and its application in analyzing OCT images. The United States was the country with the largest number of published papers. Furthermore, 197 institutions worldwide provided published articles, where University of London had more publications than the rest. The reference clusters from the study could be divided into four categories: thickness and eyes, diabetic retinopathy (DR), images and segmentation, and OCT classification. CONCLUSION: The latest hot topics and future directions in this field are identified, and the dynamic evolution of AI-based OCT imaging are outlined. AI-based OCT imaging holds great potential for revolutionizing clinical care.

Pre-trained language model augmented adversarial training network for Chinese clinical event detection.

Clinical event detection (CED) is a hot topic and essential task in medical artificial intelligence, which has attracted the attention from academia and industry over the recent years. However, most studies focus on English clinical narratives. Owing to the limitation of annotated Chinese medical corpus, there is a lack of relevant research about Chinese clinical narratives. The existing methods ignore the importance of contextual information in semantic understanding. Therefore, it is urgent to research multilingual clinical event detection. In this paper, we present a novel encoder-decoder structure based on pre-trained language model for Chinese CED task, which integrates contextual representations into Chinese character embeddings to assist model in semantic understanding. Compared with existing methods, our proposed strategy can help model harvest a language inferential skill. Besides, we introduce the punitive weight to adjust the proportion of loss on each category for coping with class imbalance problem. To evaluate the effectiveness of our proposed model, we conduct a range of experiments on test set of our manually annotated corpus. We compare overall performance of our proposed model with baseline models on our manually annotated corpus. Experimental results demonstrate that our proposed model achieves the best precision of 83.73%, recall of 86.56% and F1-score of 85.12%. Moreover, we also evaluate the performance of our proposed model with baseline models on minority category samples. We discover that our proposed model obtains a significant increase on minority category samples.

Identification of Novel EXT Mutations in Patients with Hereditary Multiple Exostoses Using Whole-Exome Sequencing.

OBJECTIVE: To find novel potential gene mutations other than EXT1 and EXT2 mutations, to expand the mutational spectrum of EXT and to explore the correlation between clinical outcome and genotype in patients with hereditary multiple exostoses (HME). METHODS: The study recruited seven families diagnosed with multiple osteochondromas (MO). Family histories and clinical information were collected in detail through comprehensive physical and image examination. Patients with deformities and functional limitations were classified as "severe" and the remaining without functional limitations were classified as "mild," in accordance with previous study. Whole-exome sequencing (WES) was performed on a total of 13 affected individuals, 1 available unaffected relative, and 10 healthy unrelated individuals. Sanger sequencing was used to validate the screened mutations. Finally, the structural change in protein caused by pathogenic mutations was analyzed using information from the relevant database online and we attempted to correlate clinical phenotype with genotype in patients with HME. RESULTS: Other than EXT1 and EXT2, no novel potential gene mutations were found through WES. We identified nine heterozygous mutations in EXT1 or EXT2. Of these mutations, four have not been reported previously. These are c.996delT in exon 2 of EXT1 (family 1), c.544C > T in exon 3 of EXT2 (family 2), c.1171C > T in exon 7 of EXT2 (family 5), and c.823- 824delAA in exon 5 of EXT1 (family 7). The other five mutations have already been reported in previous works. It was surprising that we found two mutation sites, in exon 2 and exon 5, respectively, of EXT1 in 1 patient diagnosed with MO, when his father had two mutation sites, in exon 6 and exon 5, respectively, of EXT1 and EXT2 (family 4). In addition, 1 patient showed degeneration, while his father only exhibited slight symptoms (family 7). In our study, among 51 affected patients in seven families, the sex ratio (male vs female) was 58.9% (n = 30) vs 41.2% (n = 21). Male patients seemed to show more severe symptoms compared to females, but because the sample was small, we did not obtain statistically significance results. CONCLUSION: Whole-exome sequencing to screen pathogenic gene mutations was applied successfully. Although no third-gene mutation associated with HME was found, a total of nine mutations across EXT1 and EXT2 were identified, four of which are novel. Our results expand the mutational spectrum of EXT and can be used in genetic counseling and prenatal diagnosis for patients with MO.

Medical assertion classification in Chinese EMRs using attention enhanced neural network.

Electronic medical records (EMRs), such as hospital discharge summaries, contain a wealth of information only expressed in natural language. Automated methods for extracting information from these records must be able to recognize medical concepts in text and their semantic context. A contextual property critical to reason on information from EMRs is the doctor's belief status or assertion of the patient's medical problem. Research on the medical assertion classification (MAC) can establish the foundation for various health data analyses and clinical applications. However, previous MAC studies are mainly based on traditional machine learning methods which mostly require manually constructed features and the original unlabeled data cannot be easily and effectively applied to classification or classification tasks. Furthermore, external medical knowledge such as various medical dictionary bases, which provides rich explain and definition information about medical entity, is rarely utilized in existing neural network models of medical information extraction. In this study, we propose a deep neural network architecture enhanced by medical knowledge attention layer through combining GRU neural network with CNN model to classify the assertion type of medical problem such as disease and symptom in Chinese EMRs. The attention layer in the model is applied to integrate entity representations learned from medical dictionary bases as query for encoding. Experimental results on own manually annotated corpus indicate our approach achieves better performance compared to existing methods.

Targeting LncRNA-MALAT1 suppresses the progression of osteosarcoma by altering the expression and localization of ß-catenin.

Osteosarcoma (OS), which affects adolescents especially during a growth spurt, has the highest incidence of any primary malignant bone tumour, and a high rate of early metastasis leading to a very poor prognosis. In recent years, non-coding RNAs, especially long non-coding RNAs (lncRNAs) have attracted more and more attention as novel epigenetic regulators in a variety of tumours, including OS. Most recently, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) was found to play an important role in OS progression by modulating the enhancers of zeste homolog 2 (EZH2). Furthermore, MALAT1 could inhibit the expression of E-cadherin and promote the expression of ß-catenin, and this phenomenon might be the outcome of MALAT1-induced EZH2 activation. In this study, we investigated the vital function of MALAT1 in the progression of OS and its potential leading mechanism, altering the expression and localization of ß-catenin via epigenetic transcriptional regulation by interacting with EZH2. With the help of MALAT1 silencing using small interfering RNAs (siRNAs), the loss of E-cadherin of MNNG/HOS cells was rescued, and the abnormal expression and localization of ß-catenin were corrected at the same time. Overall, our research showed promising potential for new treatment strategies based on epigenetic regulation targeting MALAT1, which will not only coordinate with the patient's immune system, but also eliminate OS in conjunction with chemotherapy.

Targeting the long noncoding RNA MALAT1 blocks the pro-angiogenic effects of osteosarcoma and suppresses tumour growth.

Osteosarcoma (OS), the commonest primary malignant tumour originating from bone, affects a substantial number of people, mostly during adolescent growth, and leads to a very poor prognosis as a result of the high rate of early metastases. Consequently, there is urgent demand for a novel treatment for this disease. There are growing concerns focused on OS-induced pro-angiogenic effects, but to date, the mechanism of OS-induced pro-angiogenesis is still insufficiently well-understood. Long noncoding RNAs (lncRNAs) have attracted increasing interest due to their strong correlation with a variety of diseases and their powerful capacity for epigenetic regulation. Recently, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), a lncRNA, has been discovered to be closely related to OS progression and hypoxia responses which are associated with angiogenesis. In this study, we confirm that MALAT1 induces pro-angiogenic effects, and demonstrate that the underlying mechanism involves a MALAT1/mechanistic target of rapamycin (mTOR)/hypoxia inducible factor-1α (HIF-1α) loop. With the help of chemically-modified small interfering RNAs targeting MALAT1 (siMALAT1), we confirm that siMALAT could provide a potential strategy to block the abnormally active OS-induced pro-angiogenic effect, and ultimately successfully suppress progression of OS tumours.

Increased expression of lncRNA HULC indicates a poor prognosis and promotes cell metastasis in osteosarcoma.

INTRODUCTION: Long non-coding RNAs (lncRNAs) are aberrantly expressed in many diseases including cancer. LncRNA HULC (highly up-regulated in liver cancer) has recently been revealed to be involved in hepatocellular carcinoma development and progression. However, the role and function of HULC in human osteosarcoma remains unknown. METHODS: LncRNA HULC expression in osteosarcoma tissues and cell lines was detected by quantitative real-time PCR. Then, the association of HULC level with survival of osteosarcoma patients was performed by the Kaplan-Meier and Cox proportional regression analyses. Furthermore, the effects of HULC on tumorigenicity of osteosarcoma cells were evaluated by in vitro assays. RESULTS: In the present study, we demonstrated that HULC was significantly up-regulated in osteosarcoma tissues and cell lines compared with normal controls, and over-expression of HULC was correlated with clinical stage and distant metastasis. Moreover, higher HULC expression was associated with shorter overall survival of osteosarcoma patients. Furthermore, decreased expression of HULC markedly suppressed osteosarcoma cell proliferation, migration, and invasion. CONCLUSIONS: Our results indicated that HULC is a novel molecule involved in osteosarcoma progression, which may provide a new marker of poor prognosis and a potential therapeutic target for osteosarcoma intervention.

Association between TGF-ß1 +869C/T polymorphism and fracture risk: a meta-analysis.

The association between TGF-ß1 +869C/T polymorphism and risk of fractures remained controversial. Therefore, we performed this meta-analysis to investigate this association. We searched PubMed, EMBASE, and Wangfang databases for studies before Aug 2014. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to calculate the strength of association. A total of ten studies were included in this meta-analysis. TGF-ß1 +869C/T polymorphism was associated with a significantly increased risk of fracture (OR=1.41; 95% CI, 1.20-1.65; I(2) =0%). In the subgroup analysis according to gender, women was significantly associated with risk of fracture (OR=1.44; 95% CI, 1.20-1.73; I(2) =4%). In the subgroup analysis by race, Asians (OR=1.43; 95% CI, 1.06-1.92; I(2) =0%) and Caucasians (OR=1.44; 95% CI, 1.13-1.85; I(2) =15%) showed increased fracture risk. Our meta-analysis suggested that the TGF-ß1 +869C/T polymorphism may be a risk factor for developing fracture.

Antitumor activity of histone deacetylase inhibitor trichostatin A in osteosarcoma cells.

BACKGROUND: Histone deacetylase (HDAC) inhibitors have been reported to induce cell growth arrest, apoptosis and differentiation of tumor cells. The present study aimed to examine the effects of trichostatin A (TSA), one such inhibitor, on the cell cycle, apoptosis and invasiveness of osteosarcoma cells. METHODS: MG- 63 cells were treated with TSA at various concentrations. Then, cell growth and apoptosis were determined by 3-(4, 5-dimethyl-2-thiazolyl)-2H-tetrazolium bromide (MTT) and TUNEL assays, respectively; cell cycling was assessed by flow cytometry; invasion assays were performed with the transwell Boyden Chamber system. RESULTS: MTT assays revealed that TSA significantly inhibited the growth of MG-63 cells in a concentration and time dependent manner. TSA treated cells demonstrated morphological changes indicative of apoptosis and TUNEL assays revealed increased apoptosis of MG-63 cells after TSA treatment. Flow cytometry showed that TSA arrested the cell cycle in G1/G2 phase and annexin V positive apoptotic cells increased markedly. In addition, the invasiveness of MG-63 cells was inhibited by TSA in a concentration dependent manner. CONCLUSION: Our findings demonstrate that TSA inhibits the proliferation, induces apoptosis and inhibits invasiveness of osteosarcoma cells in vitro. HDAC inhibitors may thus have promise to become new therapeutic agents against osteosarcoma.