Intelligent diagnostic model for pterygium by combining attention mechanism and MobileNetV2.

AIM: To evaluate the application of an intelligent diagnostic model for pterygium. METHODS: For intelligent diagnosis of pterygium, the attention mechanisms-SENet, ECANet, CBAM, and Self-Attention-were fused with the lightweight MobileNetV2 model structure to construct a tri-classification model. The study used 1220 images of three types of anterior ocular segments of the pterygium provided by the Eye Hospital of Nanjing Medical University. Conventional classification models-VGG16, ResNet50, MobileNetV2, and EfficientNetB7-were trained on the same dataset for comparison. To evaluate model performance in terms of accuracy, Kappa value, test time, sensitivity, specificity, the area under curve (AUC), and visual heat map, 470 test images of the anterior segment of the pterygium were used. RESULTS: The accuracy of the MobileNetV2+Self-Attention model with 281 MB in model size was 92.77%, and the Kappa value of the model was 88.92%. The testing time using the model was 9ms/image in the server and 138ms/image in the local computer. The sensitivity, specificity, and AUC for the diagnosis of pterygium using normal anterior segment images were 99.47%, 100%, and 100%, respectively; using anterior segment images in the observation period were 88.30%, 95.32%, and 96.70%, respectively; and using the anterior segment images in the surgery period were 88.18%, 94.44%, and 97.30%, respectively. CONCLUSION: The developed model is lightweight and can be used not only for detection but also for assessing the severity of pterygium.

Artificial intelligence assisted pterygium diagnosis: current status and perspectives.

Pterygium is a prevalent ocular disease that can cause discomfort and vision impairment. Early and accurate diagnosis is essential for effective management. Recently, artificial intelligence (AI) has shown promising potential in assisting clinicians with pterygium diagnosis. This paper provides an overview of AI-assisted pterygium diagnosis, including the AI techniques used such as machine learning, deep learning, and computer vision. Furthermore, recent studies that have evaluated the diagnostic performance of AI-based systems for pterygium detection, classification and segmentation were summarized. The advantages and limitations of AI-assisted pterygium diagnosis and discuss potential future developments in this field were also analyzed. The review aims to provide insights into the current state-of-the-art of AI and its potential applications in pterygium diagnosis, which may facilitate the development of more efficient and accurate diagnostic tools for this common ocular disease.

Research on classification method of high myopic maculopathy based on retinal fundus images and optimized ALFA-Mix active learning algorithm.

AIM: To conduct a classification study of high myopic maculopathy (HMM) using limited datasets, including tessellated fundus, diffuse chorioretinal atrophy, patchy chorioretinal atrophy, and macular atrophy, and minimize annotation costs, and to optimize the ALFA-Mix active learning algorithm and apply it to HMM classification. METHODS: The optimized ALFA-Mix algorithm (ALFA-Mix+) was compared with five algorithms, including ALFA-Mix. Four models, including ResNet18, were established. Each algorithm was combined with four models for experiments on the HMM dataset. Each experiment consisted of 20 active learning rounds, with 100 images selected per round. The algorithm was evaluated by comparing the number of rounds in which ALFA-Mix+ outperformed other algorithms. Finally, this study employed six models, including EfficientFormer, to classify HMM. The best-performing model among these models was selected as the baseline model and combined with the ALFA-Mix+ algorithm to achieve satisfactory classification results with a small dataset. RESULTS: ALFA-Mix+ outperforms other algorithms with an average superiority of 16.6, 14.75, 16.8, and 16.7 rounds in terms of accuracy, sensitivity, specificity, and Kappa value, respectively. This study conducted experiments on classifying HMM using several advanced deep learning models with a complete training set of 4252 images. The EfficientFormer achieved the best results with an accuracy, sensitivity, specificity, and Kappa value of 0.8821, 0.8334, 0.9693, and 0.8339, respectively. Therefore, by combining ALFA-Mix+ with EfficientFormer, this study achieved results with an accuracy, sensitivity, specificity, and Kappa value of 0.8964, 0.8643, 0.9721, and 0.8537, respectively. CONCLUSION: The ALFA-Mix+ algorithm reduces the required samples without compromising accuracy. Compared to other algorithms, ALFA-Mix+ outperforms in more rounds of experiments. It effectively selects valuable samples compared to other algorithms. In HMM classification, combining ALFA-Mix+ with EfficientFormer enhances model performance, further demonstrating the effectiveness of ALFA-Mix+.

Role of the mucin-like glycoprotein FCGBP in mucosal immunity and cancer.

IgGFc-binding protein (FCGBP) is a mucin first detected in the intestinal epithelium. It plays an important role in innate mucosal epithelial defense, tumor metastasis, and tumor immunity. FCGBP forms disulfide-linked heterodimers with mucin-2 and members of the trefoil factor family. These formed complexes inhibit bacterial attachment to mucosal surfaces, affect the motility of pathogens, and support their clearance. Altered FCGBP expression levels may be important in the pathologic processes of Crohn's disease and ulcerative colitis. FCGBP is also involved in regulating the infiltration of immune cells into tumor microenvironments. Thus, the molecule is a valuable marker of tumor prognosis. This review summarizes the functional relevance and role of FCGBP in immune responses and disease development, and highlights the potential role in diagnosis and predicting tumor prognosis.

Attitudes of medical workers in China toward artificial intelligence in ophthalmology: a comparative survey.

BACKGROUND: In the development of artificial intelligence in ophthalmology, the ophthalmic AI-related recognition issues are prominent, but there is a lack of research into people's familiarity with and their attitudes toward ophthalmic AI. This survey aims to assess medical workers' and other professional technicians' familiarity with, attitudes toward, and concerns about AI in ophthalmology. METHODS: This is a cross-sectional study design study. An electronic questionnaire was designed through the app Questionnaire Star, and was sent to respondents through WeChat, China's version of Facebook or WhatsApp. The participation was voluntary and anonymous. The questionnaire consisted of four parts, namely the respondents' background, their basic understanding of AI, their attitudes toward AI, and their concerns about AI. A total of 562 respondents were counted, with 562 valid questionnaires returned. The results of the questionnaires are displayed in an Excel 2003 form. RESULTS: There were 291 medical workers and 271 other professional technicians completed the questionnaire. About 1/3 of the respondents understood AI and ophthalmic AI. The percentages of people who understood ophthalmic AI among medical workers and other professional technicians were about 42.6 % and 15.6 %, respectively. About 66.0 % of the respondents thought that AI in ophthalmology would partly replace doctors, about 59.07 % having a relatively high acceptance level of ophthalmic AI. Meanwhile, among those with AI in ophthalmology application experiences (30.6 %), above 70 % of respondents held a full acceptance attitude toward AI in ophthalmology. The respondents expressed medical ethics concerns about AI in ophthalmology. And among the respondents who understood AI in ophthalmology, almost all the people said that there was a need to increase the study of medical ethics issues in the ophthalmic AI field. CONCLUSIONS: The survey results revealed that the medical workers had a higher understanding level of AI in ophthalmology than other professional technicians, making it necessary to popularize ophthalmic AI education among other professional technicians. Most of the respondents did not have any experience in ophthalmic AI but generally had a relatively high acceptance level of AI in ophthalmology, and there was a need to strengthen research into medical ethics issues.

Five-Category Intelligent Auxiliary Diagnosis Model of Common Fundus Diseases Based on Fundus Images.

Purpose: The discrepancy of the number between ophthalmologists and patients in China is large. Retinal vein occlusion (RVO), high myopia, glaucoma, and diabetic retinopathy (DR) are common fundus diseases. Therefore, in this study, a five-category intelligent auxiliary diagnosis model for common fundus diseases is proposed; the model's area of focus is marked. Methods: A total of 2000 fundus images were collected; 3 different 5-category intelligent auxiliary diagnosis models for common fundus diseases were trained via different transfer learning and image preprocessing techniques. A total of 1134 fundus images were used for testing. The clinical diagnostic results were compared with the diagnostic results. The main evaluation indicators included sensitivity, specificity, F1-score, area under the concentration-time curve (AUC), 95% confidence interval (CI), kappa, and accuracy. The interpretation methods were used to obtain the model's area of focus in the fundus image. Results: The accuracy rates of the 3 intelligent auxiliary diagnosis models on the 1134 fundus images were all above 90%, the kappa values were all above 88%, the diagnosis consistency was good, and the AUC approached 0.90. For the 4 common fundus diseases, the best results of sensitivity, specificity, and F1-scores of the 3 models were 88.27%, 97.12%, and 84.02%; 89.94%, 99.52%, and 93.90%; 95.24%, 96.43%, and 85.11%; and 88.24%, 98.21%, and 89.55%, respectively. Conclusions: This study designed a five-category intelligent auxiliary diagnosis model for common fundus diseases. It can be used to obtain the diagnostic category of fundus images and the model's area of focus. Translational Relevance: This study will help the primary doctors to provide effective services to all ophthalmologic patients.

Comparison of the effects of deep and moderate neuromuscular block on respiratory system compliance and surgical space conditions during robot-assisted laparoscopic radical prostatectomy: a randomized clinical study.

OBJECTIVE: Robot-assisted radical prostatectomy (RARP) requires pneumoperitoneum (Pnp) and a steep head-down position that may disturb respiratory system compliance (Crs) during surgery. Our aim was to compare the effects of different degrees of neuromuscular block (NMB) on Crs with the same Pnp pressure during RARP. METHODS: One hundred patients who underwent RARP were enrolled and randomly allocated to a deep or moderate NMB group with 50 patients in each group. Rocuronium was administered to both groups: in the moderate NMB group to maintain 1-2 responses to train-of-four (TOF) stimulation; and in the deep NMB group to maintain no response to TOF stimulation and 1-2 responses in the post-tetanic count. Pnp pressure in both groups was 10 mmHg (1 mmHg=133.3 Pa). Peak inspiratory pressure (Ppeak), mean pressure (Pmean), Crs, and airway resistance (Raw) were recorded after anesthesia induction and at 0, 30, 60, and 90 min of Pnp and post-Pnp. Surgical space conditions were evaluated after the procedure on a 4-point scale. RESULTS: Immediately after the Pnp, Ppeak, Pmean, and Raw significantly increased, while Crs decreased and persisted during Pnp in both groups. The results did not significantly differ between the two groups at any of the time points. There was no difference in surgical space conditions between groups. Body movements occurred in 14 cases in the moderate NMB group and in one case in the deep NMB group, and all occurred during obturator lymphadenectomy. A significant difference between the two groups was observed. CONCLUSIONS: Under the same Pnp pressure in RARP, deep and moderate NMBs resulted in similar changes in Crs, and in other respiratory mechanics and surgical space conditions. However, deep NMB significantly reduced body movements during surgery.

An Evaluation System of Fundus Photograph-Based Intelligent Diagnostic Technology for Diabetic Retinopathy and Applicability for Research.

INTRODUCTION: In April 2018, the US Food and Drug Administration (FDA) approved the world's first artificial intelligence (AI) medical device for detecting diabetic retinopathy (DR), the IDx-DR. However, there is a lack of evaluation systems for DR intelligent diagnostic technology. METHODS: Five hundred color fundus photographs of diabetic patients were selected. DR severity varied from grade 0 to 4, with 100 photographs for each grade. Following that, these were diagnosed by both ophthalmologists and the intelligent technology, the results of which were compared by applying the evaluation system. The system includes primary, intermediate, and advanced evaluations, of which the intermediate evaluation incorporated two methods. Main evaluation indicators were sensitivity, specificity, and kappa value. RESULTS: The AI technology diagnosed 93 photographs with no DR, 107 with mild non-proliferative DR (NPDR), 107 with moderate NPDR, 108 with severe NPDR, and 85 with proliferative DR (PDR). The sensitivity, specificity, and kappa value of the AI diagnoses in the primary evaluation were 98.8%, 88.0%, and 0.89, respectively. According to method 1 of the intermediate evaluation, the sensitivity of AI diagnosis was 98.0%, specificity 97.0%, and the kappa value 0.95. In method 2 of the intermediate evaluation, the sensitivity of AI diagnosis was 95.5%, the specificity 99.3%, and kappa value 0.95. In the advanced evaluation, the kappa value of the intelligent diagnosis was 0.86. CONCLUSIONS: This article proposes an evaluation system for color fundus photograph-based intelligent diagnostic technology of DR and demonstrates an application of this system in a clinical setting. The results from this evaluation system serve as the basis for the selection of scenarios in which DR intelligent diagnostic technology can be applied.

Relationship between genetic variation in the α2A-adrenergic receptor and the cardiovascular effects of dexmedetomidine in the Chinese Han population.

There are differences in individual cardiovascular responses to the administration of dexmedetomidine, a highly selective α2A-adrenergic receptor (ADRA2A) agonist. The aim of this study was to investigate ADRA2A gene polymorphisms in the Chinese Han population and their association with the cardiovascular response to intravenous dexmedetomidine infusion. Sixty elective surgery patients of Chinese Han nationality were administered 1 µg/kg dexmedetomidine intravenously over 10 min as a premedication. ADRA2A C-1291G and A1780G polymorphism status was determined in these patients, and their relationships to changes in blood pressure and heart rate after dexmedetomidine administration were analyzed. There were neither significant differences in systolic or diastolic blood pressure changes in individuals with different A1780G and C-1291G genotypes after dexmedetomidine administration, nor in heart rates among the different A1780G genotypes. However, there were significant differences in changes in heart rates in patients with different C-1291G genotypes. There were no significant differences in the sedative effects of dexmedetomidine among different A1780G and C-1291G genotypes. Logistic regression revealed that the C-1291G polymorphism was associated with differential decreases in heart rate after intravenous infusion of dexmedetomidine. These findings indicate that the ADRA2A C-1291G polymorphism can affect heart rate changes in patients after intravenous infusion of dexmedetomidine.

miR-27b-3p is Involved in Doxorubicin Resistance of Human Anaplastic Thyroid Cancer Cells via Targeting Peroxisome Proliferator-Activated Receptor Gamma.

Chemotherapy is one of the most effective forms of cancer treatment. It has been widely used in the treatment of various malignant tumours. To investigate molecular mechanisms responsible for the chemoresistance of anaplastic thyroid cancer (ATC), we established the doxorubicin (Dox) resistance of human ATC SW1736 and 8305C cells and named them SW1736/Dox and 8305C/Dox, respectively. We evaluated the expression of various micro-RNAs (miRNAs) between control and Dox-resistant ATC cells and found that the expression of miR-27b-3p was significantly increased in Dox-resistant ATC cells. Targeted inhibition of miR-27b can increase the sensitivity of SW1736/Dox and 8305C/Dox cells. Bioinformatics analysis revealed that miR-27b can directly target peroxisome proliferator-activated receptor gamma (PPARγ) within the 3' untranslated region (UTR). This was proved by the results that miR-27b-3p down-regulated the protein and mRNA levels of PPARγ. While the mutant in the core binding sites of PPARγ abolished miR-27b-3p-induced down-regulation of luciferase activity. Over-expression of PPARγ can increase the Dox sensitivity of SW1736/Dox and 8305C/Dox cells. Basic fibroblast growth factor (bFGF) might be involved in miR-27b-3p/PPARγ-regulated Dox resistance of ATC cells. The activation of p65 nuclear factor-κB (NF-κB) regulated the up-regulation of miR-27b-3p in Dox-resistant ATC cells. Collectively, our data revealed that miR-27b-3p/PPARγ is involved in the Dox resistance of human ATC cells. It suggested that targeted inhibition of miR-27b-3p might be helpful to overcome the drug resistance of ATC cells.

miRNA­148a inhibits cell growth of papillary thyroid cancer through STAT3 and PI3K/AKT signaling pathways.

The function of miRNA­148a in lymphatic metastases of papillary thyroid cancer and its mechanism were tested. In this investigation, miRNA­148a expression of lymphatic metastases of papillary thyroid cancer patients was inhibited, compared with normal group. We found that miRNA­148a overexpression was effectively reduced cell cell proliferation and metastases, and induced apoptosis of papillary thyroid cancer in vitro. Overexpression of miRNA­148a significantly induced Bax protein expression and caspase­3/9 levels, and suppressed phosphorylation STAT3 (p­STAT3), PI3K and p­Akt protein expression of papillary thyroid cancer in vitro. Next, si­STAT3, could inhibit p­STAT3 protein expression, reducing cell-cell proliferation and metastases, and inducing apoptosis of papillary thyroid cancer following miRNA­148a overexpression. Then, the PI3K inhibitor was able to inhibit PI3K and p­Akt protein expression, reduced cell cell proliferation and metastases, and induced apoptosis of papillary thyroid cancer following miRNA­148a overexpression. Taken together, our results suggest that miRNA­148a inhibits lymphatic metastases of papillary thyroid cancer through STAT3 and PI3K/AKT signaling pathways.

miR-10b exerts oncogenic activity in human hepatocellular carcinoma cells by targeting expression of CUB and sushi multiple domains 1 (CSMD1).

BACKGROUND: Hepatocellular carcinoma (HCC) is a lethal disease, while the precise underlying molecular mechanisms of HCC pathogenesis remain to be defined. MicroRNA (miRNA), a class of non-coding small RNAs, can post-transcriptionally regulate gene expression. Altered miRNA expression has been reported in HCCs. This study assessed expression and the oncogenic activity of miRNA-10b (miR-10b) in HCC. METHODS: Forty-five paired human HCC and adjacent non-tumor tissues were collected for qRT-PCR and immunohistochemistry analysis of miR-10b and CUB and Sushi multiple domains 1 (CSMD1), respectively. We analyzed the clinicopathological data from these patients to further determine if there was an association between miR-10b and CSMD1. HCC cell lines were used to assess the effects of miR-10b mimics or inhibitors on cell viability, migration, invasion, cell cycle distribution, and colony formation. Luciferase assay was used to assess miR-10b binding to the 3'-untranslated region (3'-UTR) of CSMD1. RESULTS: miR-10b was highly expressed in HCC tissues compared to normal tissues. In vitro, overexpression of miR-10b enhanced HCC cell viability, migration, and invasion; whereas, downregulation of miR-10b expression suppressed these properties in HCC cells. Injection of miR-10b mimics into tumor cell xenografts also promoted xenograft growth in nude mice. Bioinformatics and luciferase reporter assay demonstrated that CSMD1 was the target gene of miR-10b. Immunocytochemical, immunohistochemical, and qRT-PCR data indicated that miR-10b decreased CSMD1 expression in HCC cells. CONCLUSIONS: We showed that miR-10b is overexpressed in HCC tissues and miR-10b mimics promoted HCC cell viability and invasion via targeting CSMD1 expression. Our findings suggest that miR-10b acts as an oncogene by targeting the tumor suppressor gene, CSMD1, in HCC.

Hepatocellular carcinoma metastasis to the gingival soft tissues: A case report and review of the literature.

Metastases to the gingival soft tissues are rare in hepatocellular carcinoma (HCC). To the best of our knowledge, only 13 cases have been reported in English literature to date. The present study described the case of a 43-year-old Chinese man who was admitted to Tangdu Hospital (Xi'an, China) due to the presence of a gingival tumor that was initially diagnosed as granulation tissue by a dental surgeon. Examination of the patient's medical history revealed that a solid mass, measuring 1.5 cm in diameter, was identified in the right lobe of the liver 2 years prior to presentation at the current hospital; however, no biopsy was performed. Thus, the tumor was resected and histological examination resulted in an initial diagnosis of atypical squamous cell carcinoma. However, the histopathological characteristics, immunohistochemical features and serum α-fetoprotein expression levels supported a diagnosis of metastatic HCC. In conclusion, the present case study highlights the difficulties in diagnosing metastatic HCC without a history of primary HCC, and the importance of excluding a diagnosis of metastatic tumor when a lesion is identified in the gingival. Furthermore, it was determined that a final diagnosis of gingival metastasis of HCC predominantly depends on pathological characteristics and immunohistochemical features.

The Human Homolog of Drosophila Headcase Acts as a Tumor Suppressor through Its Blocking Effect on the Cell Cycle in Hepatocellular Carcinoma.

The molecular pathogenesis of hepatocellular carcinoma (HCC) is heterogeneous and extremely complex. Thus, for individual molecular targeted therapy, novel molecular markers are needed. The abnormal expression of the human homolog of Drosophila headcase (HECA homo) has been found in pancreatic, colorectal, and oral squamous cell carcinoma. Studies of oral squamous cell carcinoma have also demonstrated that the HECA homo protein can be negatively controlled by the Wnt-pathway and transcription factor 4 (TCF4) and can slow cell division by interacting with cyclins and CDKs. However, the role of HECA in HCC has not been reported elsewhere. Here, immunohistochemical analysis revealed that the downregulation of HECA homo protein occurred in 71.0% (66/93) of HCC cases and was positively correlated with a poorly differentiated grade, high serum AFP level, liver cirrhosis and large tumor size. The expression of HECA homo was detected in five live cell lines. In vitro, the overexpression of HECA homo in HepG2, Huh-7 and MHCC-97H cells could inhibit cell proliferation and colony formation and induce G1 phase arrest. In contrast, the downregulation of HECA homo could promote cell proliferation, colony formation and the cell cycle process. However, neither the overexpression nor downregulation of HECA homo in the three cell lines could affect cell migration or invasion. Collectively, HECA homo is regularly expressed in normal live cells, and the HECA homo protein level is heterogeneously altered in HCC, but the downregulation of HECA homo is more common and positively correlated with several malignant phenotypes. The HECA homo protein can slow cell proliferation to some extent primarily through its blocking effect on the cell cycle. Hence, the HECA homo protein may act as a tumor suppressor in HCC and might be a potential molecular marker for diagnostic classification and targeted therapy in HCC.

Induction of apoptosis and autophagy in metastatic thyroid cancer cells by valproic acid (VPA).

The present study investigated the effect of valproic acid (VPA) on the inhibition of RET signaling and induction of apoptosis in human thyroid carcinoma cells. VPA inhibited the viability of ARO and WRO cells and also inhibited cyclin D1 and caused caspase-3 cleavage. VPA decreased the level of RET protein and blocked the activation of RET downstream targets including phosphorylated ERK, phosphorylated AKT, and p70S6K/pS6. VPA induced metabolic stress, activated AMP-activated protein kinase and increased autophagic flux. Pharmacological inhibition of autophagy (chloroquine) augmented VPA-inducible cytotoxicity, suggesting that autophagy was protective in VPA-treated cells. VPA has a wide spectrum of activity against human thyroid carcinoma cells, and its cytotoxicity can be augmented by inhibiting autophagy. Expression of VPA molecular targets in metastatic human thyroid carcinoma cells suggests that VPA has a potential to become a thyroid cancer therapeutic agent.

Obstructive sleep apnea syndrome caused by uncommon tumors of the upper aerodigestive tract.

Obstructive sleep apnea syndrome (OSAS) is always caused by anatomic abnormalities, including nasal cavity, pharynx, and neuromuscular dysfunctions, leading to airway narrowing. OSAS associated with a mass in the aerodigestive tract is rare. In the present study, we report OSAS caused by 9 cases of preoperative uncommon tumors in the aerodigestive tract. Two tumors in the parapharyngeal space were pleomorphic adenoma, one oropharyngeal tumor was mucoepidermoid carcinoma, one tumor in the right tonsil was schwannoma, and five tumors were non-Hodgkin's lymphoma (NHL). Of the five NHL cases, one in the nasopharynx was diffuse large B-cell lymphoma, two were mantle cell lymphoma, one was chronic lymphocytic leukemia/small lymphocytic lymphoma, and one was NHL. Tumors in the aerodigestive tract should be considered in the differential diagnosis of OSAS upon exacerbation of snoring or sudden gasping. Further examinations should be performed, including a routine workup (computed tomography (CT) and magnetic resonance imaging) and positron emission tomography/CT.

[Effect of Ginkgo biloba extract on the function of alveolar polymorphonuclear neutrophils in severe acute pancreatitis rats complicated with lung injury].

OBJECTIVE: To explore the effect of Ginkgo biloba extract (GBE) on the function of alveolar polymorphonuclear neutrophils (PMN) in severe acute pancreatitis (SAP) rats complicated with lung injury (LI). METHODS: Forty-eight adult SD rats were randomly divided into three groups, i.e., the sham-operation group, the SAP group, and the GBE treatment group, 16 in each group. The SAP model was successfully induced by retrograde injection of 5% sodium taurocholate solution into the biliopancreatic duct. Rats in the sham-operation group only received flipping of the duodenum. Those in the GBE treatment group received GBE intervention based on SAP model. Equal volume of normal saline was given to rats in the sham-operation group and the SAP group. Rats were sacrificed at 6 and 12 h after operation respectively. The lung tissue was sampled to evaluate the LI score. The wet/dry ratio (W/D) of lung tissues was detected. The activity of myeloperoxidase (MPO) was measured. Alveolar PMN was harvested by bronchoalveolar lavage. The content of neutrophil elastase (NE) in bronchoalveolar lavage fluid (BALF) was measured by enzyme-linked immunoabsorbent assay (ELISA). The percentage of CD11b/CD18 double positive PMN was detected using flow cytometry. The expression of intercellular adhesion molecule-1 (ICAM-1) and NE protein in the lung tissue was detected by Western blot. RESULTS: Compared with the sham-operation group, significant pathologic lesion occurred in the lung tissue of rats in the SAP group; the pathologic LI score, lung tissue W/D ratio, MPO, and NE content in BALF significantly increased, the expression of ICAM-1 and NE in the lung tissue was obviously up-regulated, and the percentage of CD11b/CD18 double positive PMN significantly increased (P < 0.01). Compared with the SAP group, pathological lesion of the lung tissue was obviously attenuated, and the above indices were all significantly declined in the GBE treatment group (P < 0.01). CONCLUSIONS: Expression of ICAM-1 in the lung tissue and the percentage of D11b/ CD18 double positive PMN were up-regulated in SAP rats complicated with LI, resulting in the adherence of PMN to pulmonary vascular endothelial cells, and then activating PMN to release NE and aggravate LI. GBE could alleviate LI through down-regulating the expression ICAM-1 and CD11b/CD18, and hindering the adherence and activation of PMN to pulmonary vascular endothelial cells.

Dysplastic nodules with glypican-3 positive immunostaining: a risk for early hepatocellular carcinoma.

Glypican-3 (GPC3) has been reported to be a novel serum and histochemical marker for HCC. The positivity or negativity for GPC3 in hepatic precancerous lesions, such as dysplastic nodules (DN), has also been described. Moreover, our previous studies have demonstrated that some DN in liver cirrhosis represent monoclonal hyperplasia, and confirmed their neoplastic nature. However, additional studies must be performed to investigate further the relationship between DN with GPC3 positivity and HCC. Thus, we first investigated the expression of GPC3 in 136 HCC and 103 small DN (less than 1 cm in diameter) by immunohistochemical staining and determined the clonality of 81 DN from female patients using X-chromosome inactivation mosaicism and polymorphism of androgen receptor (AR) gene. Then we examined these samples for chromosomal loss of heterozygosity (LOH) at 11 microsatellite polymorphism sites. The results demonstrated that GPC3 immunoreactivity was detected in 103 of 136 HCC (75.7%) and 19 of 103 DN (18.4%), and the positive ratio correlated with HBsAg positivity. Clonality assays showed that 15 GPC3-positive DN from female patients, including 12 high-grade DN (HGDN), and 28 (42.4%) of 66 GPC3-negative DN, were monoclonal. In addition, among 19 GPC3-positive DN, chromosomal LOH was found at loci D6S1008 (100%, 19/19), D8S262 (52.6%, 10/19) and D11S1301 (57.9%, 11/19). However, the LOH frequency in GPC3-negative DN was 5.95% (5/84), 23.8% (20/84), and 4.76% (4/84) in three loci, respectively. Thus, we concluded that GPC3-positive DN, especially GPC3-positive HGDN, was really a late premalignant lesion of HCC.

Stat3 inhibits PTPN13 expression in squamous cell lung carcinoma through recruitment of HDAC5.

Proteins of the protein tyrosine phosphatase (PTP) family are known to be signaling molecules that regulate a variety of cellular processes including cell growth, differentiation, and apoptosis. PTPN13 (also known as FAP1, PTPL1, PTPLE, PTPBAS, and PTP1E), a putative tumor suppressor, is frequently inactivated in lung carcinoma through the loss of either mRNA or protein expression. However, the molecular mechanisms underlying its dysregulation have not been fully explored. Interleukin-6 (IL-6) mediated Stat3 activation is viewed as crucial for multiple tumor growth and progression. Here, we demonstrate that PTPN13 is a direct transcriptional target of Stat3 in the squamous cell lung carcinoma. Our data show that IL-6 administration or transfection of a constitutively activated Stat3 in HCC-1588 and SK-MES-1 cells inhibits PTPN13 mRNA transcription. Using luciferase reporter and ChIP assays, we show that Stat3 binds to the promoter region of PTPN13 and promotes its activity through recruiting HDAC5. Thus, our results suggest a previously unknown Stat3-PTPN13 molecular network controlling squamous cell lung carcinoma development.