Immunotherapy and targeted therapy for cholangiocarcinoma: Artificial intelligence research in imaging.

Cholangiocarcinoma (CCA) is a highly aggressive hepatobiliary malignancy, second only to hepatocellular carcinoma in prevalence. Despite surgical treatment being the recommended method to achieve a cure, it is not viable for patients with advanced CCA. Gene sequencing and artificial intelligence (AI) have recently opened up new possibilities in CCA diagnosis, treatment, and prognosis assessment. Basic research has furthered our understanding of the tumor-immunity microenvironment and revealed targeted molecular mechanisms, resulting in immunotherapy and targeted therapy being increasingly employed in the clinic. Yet, the application of these remedies in CCA is a challenging endeavor due to the varying pathological mechanisms of different CCA types and the lack of expressed immune proteins and molecular targets in some patients. AI in medical imaging has emerged as a powerful tool in this situation, as machine learning and deep learning are able to extract intricate data from CCA lesion images while assisting clinical decision making, and ultimately improving patient prognosis. This review summarized and discussed the current immunotherapy and targeted therapy related to CCA, and the research progress of AI in this field.

The value of an MRI-based radiomics model in predicting the survival and prognosis of patients with extrahepatic cholangiocarcinoma.

OBJECTIVES: The study aimed to establish radiomics models based on magnetic resonance imaging (MRI) multiparameter images to predict the survival and prognosis of patients with extrahepatic cholangiocarcinoma (ECC). METHODS: Seventy-eight patients with ECC confirmed by pathology were collected retrospectively. The radiomics model_a/b/c were constructed based on the 1/2/3-year survival of patients with ECC. The best texture features were selected according to postoperative survival time and ECC patient status to calculate the radiomics score (Rad-score). A cutoff value was selected, and patients were divided into high-risk and low-risk groups. RESULTS: Model_a, model_b, and model_c were used to predict 1-, 2-, and 3-year postoperative survival rates, respectively. The area under the curve values in the training and test groups were 1.000 and 0.933 for model_a, 0.909 and 0.907 for model_b, 1.000 and 0.975 for model_c, respectively. The survival prediction model based on the Rad-score showed that the postoperative mortality risk differed significantly between risk groups (p < 0.0001). CONCLUSIONS: The MRI radiomics model could be used to predict the survival and prognosis of patients with ECC.

Association of methylation risk score with incident type 2 diabetes mellitus: A nested case-control study.

AIMS: To investigate the association of methylation risk score (MRS) and its interactions with environmental factors with type 2 diabetes mellitus (T2DM) risk. METHODS: We conducted a nested case-control study with 241 onset cases and 241 matched controls. Conditional logistic regression models were employed to identify risk CpG sites. Simple and weighted MRSs were constructed based on the methylation levels of ATP-binding cassette G1 gene, fat mass and obesity associated gene, potassium voltage-gated channel member 1 gene, and thioredoxin-interacting protein gene previously associated with T2DM to estimate the association of MRS with T2DM risk. Stratified analyses were used to investigate interactions between MRS and environmental factors. RESULTS: A total of 10 CpG loci were identified from the aforementioned genes to calculate MRS. After controlling for potential confounding factors, taking tertile 1 as reference, the odds ratios (ORs) and 95% confidence intervals (CIs) for T2DM of tertile 3 was 2.39 (1.36-4.20) for simple MRS and 2.59 (1.45-4.63) for weighted MRS. With per SD score increment in MRS, the OR (95% CI) was 1.66 (1.29-2.14) and 1.60 (1.24-2.08) for simple and weighted MRSs, respectively. J-curved associations were observed between both simple and weighted MRSs and T2DM risks. Additionally, multiplication interactions for smoking and hypertension with simple MRS on the risk of T2DM were found, similarly for smoking and obesity with weighted MRS on the risk of T2DM (all Pinteraction < .05). CONCLUSION: Elevated simple and weighted MRSs were associated with increased risk of T2DM. Environmental risk factors may influence the association between MRS and T2DM.

MRI-based automatic identification and segmentation of extrahepatic cholangiocarcinoma using deep learning network.

BACKGROUND: Accurate identification of extrahepatic cholangiocarcinoma (ECC) from an image is challenging because of the small size and complex background structure. Therefore, considering the limitation of manual delineation, it's necessary to develop automated identification and segmentation methods for ECC. The aim of this study was to develop a deep learning approach for automatic identification and segmentation of ECC using MRI. METHODS: We recruited 137 ECC patients from our hospital as the main dataset (C1) and an additional 40 patients from other hospitals as the external validation set (C2). All patients underwent axial T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and diffusion-weighted imaging (DWI). Manual delineations were performed and served as the ground truth. Next, we used 3D VB-Net to establish single-mode automatic identification and segmentation models based on T1WI (model 1), T2WI (model 2), and DWI (model 3) in the training cohort (80% of C1), and compared them with the combined model (model 4). Subsequently, the generalization capability of the best models was evaluated using the testing set (20% of C1) and the external validation set (C2). Finally, the performance of the developed models was further evaluated. RESULTS: Model 3 showed the best identification performance in the training, testing, and external validation cohorts with success rates of 0.980, 0.786, and 0.725, respectively. Furthermore, model 3 yielded an average Dice similarity coefficient (DSC) of 0.922, 0.495, and 0.466 to segment ECC automatically in the training, testing, and external validation cohorts, respectively. CONCLUSION: The DWI-based model performed better in automatically identifying and segmenting ECC compared to T1WI and T2WI, which may guide clinical decisions and help determine prognosis.

Prediction of angiogenesis in extrahepatic cholangiocarcinoma using MRI-based machine learning.

Purpose: Reliable noninvasive method to preoperative prediction of extrahepatic cholangiocarcinoma (eCCA) angiogenesis are needed. This study aims to develop and validate machine learning models based on magnetic resonance imaging (MRI) for predicting vascular endothelial growth factor (VEGF) expression and the microvessel density (MVD) of eCCA. Materials and methods: In this retrospective study from August 2011 to May 2020, eCCA patients with pathological confirmation were selected. Features were extracted from T1-weighted, T2-weighted, and diffusion-weighted images using the MaZda software. After reliability testing and feature screening, retained features were used to establish classification models for predicting VEGF expression and regression models for predicting MVD. The performance of both models was evaluated respectively using area under the curve (AUC) and Adjusted R-Squared (Adjusted R2). Results: The machine learning models were developed in 100 patients. A total of 900 features were extracted and 77 features with intraclass correlation coefficient (ICC) < 0.75 were eliminated. Among all the combinations of data preprocessing methods and classification algorithms, Z-score standardization + logistic regression exhibited excellent ability both in the training cohort (average AUC = 0.912) and the testing cohort (average AUC = 0.884). For regression model, Z-score standardization + stochastic gradient descent-based linear regression performed well in the training cohort (average Adjusted R2 = 0.975), and was also better than the mean model in the test cohort (average Adjusted R2 = 0.781). Conclusion: Two machine learning models based on MRI can accurately predict VEGF expression and the MVD of eCCA respectively.

High-throughput single nucleus total RNA sequencing of formalin-fixed paraffin-embedded tissues by snRandom-seq.

Formalin-fixed paraffin-embedded (FFPE) tissues constitute a vast and valuable patient material bank for clinical history and follow-up data. It is still challenging to achieve single cell/nucleus RNA (sc/snRNA) profile in FFPE tissues. Here, we develop a droplet-based snRNA sequencing technology (snRandom-seq) for FFPE tissues by capturing full-length total RNAs with random primers. snRandom-seq shows a minor doublet rate (0.3%), a much higher RNA coverage, and detects more non-coding RNAs and nascent RNAs, compared with state-of-art high-throughput scRNA-seq technologies. snRandom-seq detects a median of >3000 genes per nucleus and identifies 25 typical cell types. Moreover, we apply snRandom-seq on a clinical FFPE human liver cancer specimen and reveal an interesting subpopulation of nuclei with high proliferative activity. Our method provides a powerful snRNA-seq platform for clinical FFPE specimens and promises enormous applications in biomedical research.

All-cause mortality risk with different metabolic abdominal obesity phenotypes: the Rural Chinese Cohort Study.

We aimed to investigate the association of metabolic obesity phenotypes with all-cause mortality risk in a rural Chinese population. This prospective cohort study enrolled 15 704 Chinese adults (38·86 % men) with a median age of 51·00 (interquartile range: 41·00-60·00) at baseline (2007-2008) and followed up during 2013-2014. Obesity was defined by waist circumference (WC: ≥ 90 cm for men and ≥ 80 cm for women) or waist-to-height ratio (WHtR: ≥ 0·5). The hazard ratio (HR) and 95 % CI for the risk of all-cause mortality related to metabolic obesity phenotypes were calculated using the Cox hazards regression model. During a median follow-up of 6·01 years, 864 deaths were identified. When obesity was defined by WC, the prevalence of participants with metabolically healthy non-obesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO) and metabolically unhealthy obesity (MUO) at baseline was 12·12 %, 2·80 %, 41·93 % and 43·15 %, respectively. After adjusting for age, sex, alcohol drinking, smoking, physical activity and education, the risk of all-cause mortality was higher with both MUNO (HR = 1·20, 95 % CI 1·14, 1·26) and MUO (HR = 1·20, 95 % CI 1·13, 1·27) v. MHNO, but the risk was not statistically significant with MHO (HR = 0·99, 95 % CI 0·89, 1·10). This result remained consistent when stratified by sex. Defining obesity by WHtR gave similar results. MHO does not suggest a greater risk of all-cause mortality compared to MHNO, but participants with metabolic abnormality, with or without obesity, have a higher risk of all-cause mortality. These results should be cautiously interpreted as the representation of MHO is small.

LRFNet: A deep learning model for the assessment of liver reserve function based on Child-Pugh score and CT image.

BACKGROUND AND OBJECTIVE: Liver reserve function should be accurately evaluated in patients with hepatic cellular cancer before surgery to evaluate the degree of liver tolerance to surgical methods. Meanwhile, liver reserve function is also an important indicator for disease analysis and prognosis of patients. Child-Pugh score is the most widely used liver reserve function evaluation and scoring system. However, this method also has many shortcomings such as poor accuracy and subjective factors. To achieve comprehensive evaluation of liver reserve function, we developed a deep learning model to fuse bimodal features of Child-Pugh score and computed tomography (CT) image. METHODS: 1022 enhanced abdomen CT images of 121 patients with hepatocellular carcinoma and impaired liver reserve function were retrospectively collected. Firstly, CT images were pre-processed by de-noising, data amplification and normalization. Then, new branches were added between the dense blocks of the DenseNet structure, and the center clipping operation was introduced to obtain a lightweight deep learning model liver reserve function network (LRFNet) with rich liver scale features. LRFNet extracted depth features related to liver reserve function from CT images. Finally, the extracted features are input into a deep learning classifier composed of fully connected layers to classify CT images into Child-Pugh A, B and C. Precision, Specificity, Sensitivity, and Area Under Curve are used to evaluate the performance of the model. RESULTS: The AUC by our LRFNet model based on CT image for Child-Pugh A, B and C classification of liver reserve function was 0.834, 0.649 and 0.876, respectively, and with an average AUC of 0.774, which was better than the traditional clinical subjective Child-Pugh classification method. CONCLUSION: Deep learning model based on CT images can accurately classify Child-Pugh grade of liver reserve function in hepatocellular carcinoma patients, provide a comprehensive method for clinicians to assess liver reserve function before surgery.

Complex dynamics in a Hopfield neural network under electromagnetic induction and electromagnetic radiation.

Due to the potential difference between two neurons and that between the inner and outer membranes of an individual neuron, the neural network is always exposed to complex electromagnetic environments. In this paper, we utilize a hyperbolic-type memristor and a quadratic nonlinear memristor to emulate the effects of electromagnetic induction and electromagnetic radiation on a simple Hopfield neural network (HNN), respectively. The investigations show that the system possesses an origin equilibrium point, which is always unstable. Numerical results uncover that the HNN can present complex dynamic behaviors, evolving from regular motions to chaotic motions and finally to regular motions, as the memristors' coupling strength changes. In particular, coexisting bifurcations will appear with respect to synaptic weights, which means bi-stable patterns. In addition, some physical results obtained from breadboard experiments confirm Matlab analyses and Multisim simulations.

Acute appendicitis after colorectal endoscopic mucosal resection: a case report.

Endoscopic mucosal resection (EMR) was originally described in 1973 and is currently a popular practice used in treating polyps, small adenomas, and early cancers. Although the safety of EMR has been proven in numerous studies, complications occur occasionally. We report a case in which the patient complained of severe upper abdominal pain and who was diagnosed with acute appendicitis after colorectal EMR. The patient recovered well after surgery. Cautious observation is necessary when resuming oral intake in patients who undergo colorectal EMR and who complain of postoperative abdominal pain. Observation is especially important for patients with a fecalith that may have originally existed in the appendix or in the colon near the appendix.

Multimodal molecular imaging evaluation for early diagnosis and prognosis of cholangiocarcinoma.

Cholangiocarcinoma (CCA) is an aggressive and lethal malignancy with limited therapeutic options. Despite recent advances in diagnostic imaging for CCA, the early diagnosis of CCA and evaluation of tumor invasion into the bile duct and its surrounding tissues remain challenging. Most patients with CCA are diagnosed at an advanced stage, at which treatment options are limited. Molecular imaging is a promising diagnostic method for noninvasive imaging of biological events at the cellular and molecular level in vivo. Molecular imaging plays a key role in the early diagnosis, staging, and treatment-related evaluation and management of cancer. This review will describe different methods for molecular imaging of CCA, including nuclear medicine, magnetic resonance imaging, optical imaging, and multimodal imaging. The main challenges and future directions in this field are also discussed.

Protective Effect of Topiroxostat on Myocardial Injury Induced by Lipopolysaccharide.

BACKGROUND: Myocardial injury induced by sepsis is the most common cause of death. Topiroxostat has been found to have organ protective effects, but its role in septic shock-related cardiomyocyte damage is still unclear and needs further study. MATERIAL AND METHODS: An endotoxemic shock model in rats was constructed. After topiroxostat treatment, hemodynamic parameters, myocardial injury marker enzymes, oxidative stress, myocardial injury, and apoptosis were measured by polyphysiograph, enzyme-linked immunosorbent assay, hematoxylin and eosin staining, TUNEL staining, and western blot. During in vitro experiments, the effect of topiroxostat on cell vitality, oxidative stress, inflammatory factors, apoptosis-related markers, phosphorylated-p65 (p-p65) and p65 expressions were measured by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), flow cytometry, enzyme-linked immunosorbent assay, quantitative real-time polymerase chain reaction, and western blot. RESULTS: Topiroxostat improved myocardial dysfunction and superoxide dismutase activity while suppressing levels of creatine kinase, lactate dehydrogenase and malondialdehyde in serum of endotoxemic shock rats. Additionally, topiroxostat augmented dry-wet weight ratios of the hearts in rats. Meanwhile, topiroxostat was proved to alleviate interstitial edema and apoptosis in myocardial tissues of endotoxemic shock rats. During in vitro experiments, topiroxostat pretreatment elevated lipopolysaccharide (LPS)-induced H9c2 cell vitality, and alleviated oxidative stress and inflammation. Moreover, topiroxostat pretreatment downregulated apoptosis-related markers, p-p65, and p-p65/p65 levels in LPS-induced H9c2 cells. CONCLUSIONS: Topiroxostat attenuated LPS-induced myocardial injury via repressing apoptosis and oxidative stress.

Global knowledge mapping and emerging trends in research between spasmolytic polypeptide-expressing metaplasia and gastric carcinogenesis: A bibliometric analysis from 2002 to 2022.

Background: Spasmolytic polypeptide expression metaplasia (SPEM) occurs in the corpus of the stomach and is closely related to inflammations caused by H. pylori infection. Recently, SPEM was suggested as one of the dubious precancerous lesions of gastric cancer (GC). Thus, further research on SPEM cell transdifferentiation and its underlying mechanisms could facilitate the development of new molecular targets improving the therapeutics of GC. Using bibliometrics, we analyzed publications, summarized the research hotspots and provided references for scientific researchers engaged in related research fields. Methods: We searched the Web of Science Core Collection (WoSCC) for publications related to SPEM-GC from 2002 to 2022. The VOSviewer, SCImago, CiteSpace and R software were used to visualize and analyze the data. Gene targets identified in the keyword list were analyzed for functional enrichment using the KEGG and GO databases. Results: Of the 292 articles identified in the initial search, we observed a stable trend in SPEM-GC research but rapid growth in the number of citations. The United States was the leader in terms of quality publications and international cooperation among them. The total number of articles published by Chinese scholars was second to the United States. Additionally, despite its low centrality and average citation frequency, China has become one of the world's most dynamic countries in academics. In terms of productivity, Vanderbilt University was identified as the most productive institution. Further, we also observed that Gastroenterology was the highest co-cited journal, and Goldenring Jr. was the most prolific author with the largest centrality. Conclusion: SPEM could serve as an initial step in diagnosing gastric precancerous lesions. Current hotspots and frontiers of research include SPEM cell lineage differentiation, interaction with H. pylori, disturbances of the mucosal microenvironment, biomarkers, clinical diagnosis and outcomes of SPEM, as well as the development of proliferative SPEM animal models. However, further research and collaboration are still required. The findings presented in this study can be used as reference for the research status of SPEM-GC and determine new directions for future studies.

NORAD lentivirus shRNA mitigates fibrosis and inflammatory responses in diabetic cardiomyopathy via the ceRNA network of NORAD/miR-125a-3p/Fyn.

OBJECTIVE: Diabetic cardiomyopathy (DCM) is a serious complication of diabetes, but its pathogenesis is still unclear. This study investigated the mechanism of long noncoding RNA (lncRNA) NORAD in DCM. METHODS: Male leptin receptor-deficient (db/db) mice and leptin control mice (db/ +) were procured. DCM model was established by subcutaneous injection of angiotensin II (ATII) in db/db mice. NORAD lentivirus shRNA or Adv-miR-125a-3p was administered to analyze cardiac function, fibrosis, serum biochemical indexes, inflammation and fibrosis. Primary cardiomyocytes were extracted and transfected with miR-125a-3p mimic. The competing endogenous RNA (ceRNA) network of NORAD/miR-125a-3p/Fyn was verified. The levels of fibrosis- and inflammation-related factors were measured. RESULTS: In db/db mice treated with ATII, the body weight and serum biochemical indexes were increased, while the cardiac function was decreased, and inflammatory cell infiltration and fibrosis were induced. NORAD was upregulated in diabetic and DCM mice. The 4-week intravenous injection of NORAD lentivirus shRNA reduced body weight and serum biochemical indexes, improved cardiac function, and attenuated inflammation and fibrosis in DCM mice. NORAD acted as a sponge to adsorb miR-125a-3p, and miR-125a-3p targeted Fyn. Intravenous injection of miR-125a-3p adenovirus improved cardiac function and fibrosis and reduced inflammatory responses in DCM mice. Co-overexpression of miR-125-3p and Fyn partly reversed the improving effect of miR-125-3p overexpression on cardiac fibrosis in DCM mice. CONCLUSION: NORAD lentivirus shRNA improved cardiac function and fibrosis and reduced inflammatory responses in DCM mice via the ceRNA network of NORAD/miR-125a-3p/Fyn. These findings provide a valuable and promising therapeutic target for the treatment of DCM.

Effects of non-pharmacological interventions on anxiety, depression, and sleep quality in patients with postoperative glaucoma: A protocol for systematic review and network meta-analysis.

BACKGROUND: Glaucoma is the second most-common blinding ophthalmic disease in the world, and its incidence has been rising year by year in recent years. Currently, the main treatment of glaucoma still relies on surgery. Glaucoma patients often suffer from various psychological problems like anxiety and depression not only because of the lack of understanding of the surgical treatment of glaucoma, but also the long-term stress and the poor prognosis. As alternative therapies, non-pharmacological interventions can greatly alleviate psychological burdens and improve sleep quality in surgically treated glaucoma patients. Randomized controlled trials of non-pharmacologic interventions for glaucoma have been reported, although the results remain conflicting. Evidences for determining the efficacy of non-pharmacologic interventions for glaucoma are scant. This study aims to assess the effects of non-pharmacological interventions on anxiety, depression, and sleep quality in patients with postoperative glaucoma through a network meta-analysis. METHODS: A systematic search of relevant literatures published before August 2021 about the effects of non-pharmacological interventions on anxiety, depression, and sleep quality in patients with postoperative glaucoma will be performed in Wanfang, VP Information Chinese Journal Service Platform, China National Knowledge Infrastructure, Chinese BioMedicine Literature Database, Pubmed, Embase, Cochrane, and Web of science. Two reviewers will be independently responsible for literature screening and selection, quality assessment, and data extraction. WinBUGS 1.4 will be used for the network meta-analysis. RESULTS: This meta-analysis will provide additional and stronger evidences for non-pharmacological interventions on anxiety, depression, and sleep quality in patients with postoperative glaucoma, which will help clinicians and decision makers to make an optimal therapeutic strategy. CONCLUSION: This study will provide a reliable evidence-based basis for the clinical application of non-pharmacological interventions on anxiety, depression, and sleep quality in patients with postoperative glaucoma. ETHICS AND DISSEMINATION: Ethical approval was not required for this study. The systematic review will be published in a peer-reviewed journal, presented at conferences, and shared on social media platforms. This review would be disseminated in a peer-reviewed journal or conference presentations. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/TYJPK.

Consensus on eradication of Helicobacter pylori and prevention and control of gastric cancer in China (2019, Shanghai).

BACKGROUND AND AIM: China is a country with high prevalence of Helicobacter pylori (H. pylori) infection, which in turn is closely related to the occurrence of gastric cancer. Therefore, the risks of H. pylori infection and gastric cancer are highly overlapping, and the prevention and treatment of H. pylori infection are necessary to prevent gastric cancer. METHODS: Based on evidence-based medicine and the Delphi method, the National Clinical Medical Research Center for Digestive Disease along with the National Early Gastrointestinal Cancer Prevention and Treatment Center Alliance organized dozens of experts in the fields of digestive diseases, H. pylori research, gastric cancer surgery, epidemiology, health economics, and health management to discuss the relationship between H. pylori eradication and prevention and the treatment of gastric cancer. RESULTS: A preliminary consensus on the relationship between H. pylori infection and gastric cancer, H. pylori eradication and gastric cancer prevention, and H. pylori screening and eradication strategy was reached. The consensus further clarified the relationship between H. pylori and gastric cancer and how to formulate future prevention and control strategies for gastric cancer. CONCLUSIONS: This consensus could provide guidance on early detection, diagnosis, and treatment of H. pylori to reduce the occurrence of gastric cancer in China.

Clinical Features and Prognosis of Crohn's Disease with Upper Gastrointestinal Tract Phenotype in Chinese Patients.

BACKGROUND: The epidemiology of upper gastrointestinal (L4) Crohn's disease in China remains poorly characterized. AIMS: We aimed to identify the clinical characteristics of L4 disease and clarify the relationship between disease characteristics at diagnosis and early outcomes. METHODS: We retrospectively enrolled 246 patients diagnosed between 2013 and 2017 and followed up for > 1 year post-diagnosis. Primary outcomes included the 1-year rates of hospitalization and abdominal surgery according to disease location and behavior. RESULTS: Of 80 patients with L4 disease (61, 25, and 18 with esophagogastroduodenal, jejunal, and proximal ileal involvement, respectively), none had granuloma, whereas 66.7%, 50%, 46.9%, 75%, and 70% had disease-specific endoscopic lesions in the esophagus, stomach, duodenum, jejunum, and proximal ileum, respectively. Compared to non-L4 disease, L4 disease was associated with higher rates of abdominal surgery (41.3% vs. 11.4%, P < 0.001) but similar rates of hospitalization within 1 year post-diagnosis. In L4 disease, jejunal and proximal ileal involvement was associated with stricturing behavior (P = 0.034, P < 0.001) and higher abdominal surgery rate (both: P < 0.001). Risk factors for abdominal surgery within 1 year post-diagnosis included age ≥ 40 years (OR 1.920; 95% CI 1.095-3.367), L4 phenotype (OR 6.335; 95% CI 3.862-10.390), stricturing disease (OR 3.162; 95% CI 1.103-9.866), and penetrating disease (OR 11.504; 95% CI 3.409-38.825), whereas the protective factor was female sex (OR 0.214; 95% CI 0.123-0.373). CONCLUSIONS: Early outcomes are worse for L4 than for non-L4 disease. Jejunoileum involvement predicts stricturing disease and early surgery. More aggressive initial therapy is needed to improve L4-disease prognosis.

Comparison of the short-term and long-term outcomes of surgical treatment versus endoscopic treatment for early esophageal squamous cell neoplasia larger than 2 cm: a retrospective study.

BACKGROUND: NCCN Guidelines of esophageal cancer recommend that endoscopic therapy is considered "preferred" for patients with limited early-stage disease less than or equal to 2 cm. However, there is currently no definite evidence to support either endoscopic therapy or esophagectomy for early esophageal cancer larger than 2 cm. We aimed to explore the optimal treatment for this condition. METHODS: From January 2010 to June 2016, 116 patients with early esophageal neoplasia [high-grade dysplasia (HGD), lamina propria and muscularis mucosae (T1a) cancer, selected superficial submucosa (T1b) cancer without lymph node metastases] larger than 2 cm and treated either surgically or endoscopically were included. RESULTS: Endoscopic therapy was performed in 69 patients and esophagectomy in 47 patients, respectively. The median follow-up time was 43.8 months in the endoscopic cohort and 49.4 months in the surgical cohort. The overall survival was similar between the two cohorts (97.1% vs. 91.5%, P = 0.18). Survival without readmission for treatment-related complicates was also similar. Minor and severe procedure-related complications occurred more often in the surgical cohort than in the endoscopic cohort (63.8% vs. 43.5% and 8.5% vs. 0 respectively, P < 0.05 for both). Four patients in the endoscopic cohort had to undergo additional esophagectomy and were alive during follow-up. There were no procedure-related deaths in the endoscopic cohort, whereas two deaths occurred in the surgical cohort. Recurrence occurred in nine patients in the endoscopic group (13%): six with local recurrence, one with residual neoplasia and two with metachronous neoplasia. None of them died after repeated endoscopic treatments. CONCLUSIONS: Efficacy was similar between endoscopic therapy and esophagectomy in the treatment of early esophageal squamous cell neoplasia larger than 2 cm and endoscopic therapy was associated with fewer and manageable complications. We recommend endoscopic treatment should be preferred selected for early esophageal neoplasia larger than 2 cm.

An attempt to treat Hoffa fractures under arthroscopy: A case report.

We treated a 15-year-old female patient with fracture of the post-lateral femoral condyle and the bone shifted in front of the knee. Considering that the traditional surgical approach has the shortcomings of significant trauma and poor prognosis, we designed an arthroscopic procedure, which achieved satisfactory short-term efficacy, effectively reduced and fixed the fractures, avoided damage to vascular nerves, and maximally reduced the trauma caused by surgery itself.