Histological Risk Factors for Lymph Node Metastasis in pT1 Colorectal Cancer: Does Submucosal Invasion Depth Really Matter?

Objective: After endoscopic resection of colorectal cancer with submucosal invasion (pT1 CRC), additional surgical treatment is recommended if deep submucosal invasion (DSI) is present. This study aimed to further elucidate the risk factors for lymph node metastasis (LNM) in patients with pT1 CRC, especially the effect of DSI on LNM.

Methods: Patients with pT1 CRC who underwent lymph node dissection were selected.

Revealing the Dark Side of Non-Local Attention in Single Image Super-Resolution.

Single Image Super-Resolution (SISR) aims to reconstruct a high-resolution image from its corresponding low-resolution input. A common technique to enhance the reconstruction quality is Non-Local Attention (NLA), which leverages self-similar texture patterns in images. However, we have made a novel finding that challenges the prevailing wisdom.

IFKMHC: Implicit Fuzzy K-Means Model for High-Dimensional Data Clustering.

The graph-information-based fuzzy clustering has shown promising results in various datasets. However, its performance is hindered when dealing with high-dimensional data due to challenges related to redundant information and sensitivity to the similarity matrix design. To address these limitations, this article proposes an implicit fuzzy k-means (FKMs) model that enhances graph-based fuzzy clustering for high-dimensional data.

High-Similarity-Pass Attention for Single Image Super-Resolution.

Recent developments in the field of non-local attention (NLA) have led to a renewed interest in self-similarity-based single image super-resolution (SISR). Researchers usually use the NLA to explore non-local self-similarity (NSS) in SISR and achieve satisfactory reconstruction results. However, a surprising phenomenon that the reconstruction performance of the standard NLA is similar to that of the NLA with randomly selected regions prompted us to revisit NLA.

Coexisting Infantile Hepatic Hemangioma and Hepatoblastoma in a Neonate: A Case Report.

Infantile hepatic hemangioma and hepatoblastoma are the most common benign and malignant tumors of the liver in the neonatal and early childhood periods, respectively. However, the simultaneous occurrence of these 2 tumors in the same liver lesion is very rare. We report a case of a newborn infant diagnosed with a liver mass by ultrasound examination 4 days after birth.

Global Learnable Attention for Single Image Super-Resolution.

Self-similarity is valuable to the exploration of non-local textures in single image super-resolution (SISR). Researchers usually assume that the importance of non-local textures is positively related to their similarity scores. In this paper, we surprisingly found that when repairing severely damaged query textures, some non-local textures with low-similarity which are closer to the target can provide more accurate and richer details than the high-similarity ones.

Online Identification of Nonlinear Systems With Separable Structure.

Separable nonlinear models (SNLMs) are of great importance in system modeling, signal processing, and machine learning because of their flexible structure and excellent description of nonlinear behaviors. The online identification of such models is quite challenging, and previous related work usually ignores the special structure where the estimated parameters can be partitioned into a linear and a nonlinear part. In this brief, we propose an efficient first-order recursive algorithm for SNLMs by introducing the variable projection (VP) step.

Bladder paraganglioma after kidney transplantation: A case report.

Background: Kidney transplantation is associated with an increased risk of tumors in the urinary bladder. Among all the pathological types of tumors in the bladder, paraganglioma, which arises from extra-adrenal paraganglia and consists of chromaffin cells, is rare. Paragangliomas might cause severe clinical symptoms due to catecholamine hypersecretion or mass compression.

Coexistent Kaposi sarcoma and post-transplant lymphoproliferative disorder in the same lymph nodes after pediatric liver transplantation: A case report.

Background: Kaposi sarcoma and post-transplant lymphoproliferative disorder have been occasionally reported in post-liver transplant patients. However, the simultaneous occurrence of these two diseases in the same lymph nodes is very rare.

Case Summary: We report the case of a 19-mo-old boy, who presented with intermittent fever and enlarged cervical lymph nodes after liver transplantation.

Current indications for endoscopic submucosal dissection of early gastric cancer.

The development of endoscopic treatment technology has further promoted the minimally invasive treatment of early gastric cancer (EGC). Endoscopic treatment has achieved better therapeutic effects in terms of safety and prognosis and is the preferred treatment method for patients who meet the indications for endoscopic treatment. However, the consequent problem is that some patients receiving endoscopic treatment may undergo non-curative resection, and the principle of follow-up management for non-curative resection patients deserves further attention.

The Correlation Between Mutant p53 Protein Expression and Cell Atypia in Early Differentiated Gastric Adenocarcinoma.

Objective: This study aims to explore the correlation between the expression of mutant p53 protein and cellular atypia in early differentiated gastric adenocarcinoma (DGA).

Methods: A total of 107 cases of early DGA samples resected by endoscopic submucosal dissection (ESD) were collected from the Pathology Department of Beijing Friendship Hospital from January 2018 to December 2019. The EnVision two-step immunohistochemical method was used to detect the expression of mutant p53 protein in these cancer tissues, and the correlation with cell atypia was analyzed.

Insights Into Algorithms for Separable Nonlinear Least Squares Problems.

Separable nonlinear least squares (SNLLS) problems have attracted interest in a wide range of research fields such as machine learning, computer vision, and signal processing. During the past few decades, several algorithms, including the joint optimization algorithm, alternated least squares (ALS) algorithm, embedded point iterations (EPI) algorithm, and variable projection (VP) algorithms, have been employed for solving SNLLS problems in the literature. The VP approach has been proven to be quite valuable for SNLLS problems and the EPI method has been successful in solving many computer vision tasks.

Recursive Variable Projection Algorithm for a Class of Separable Nonlinear Models.

In this article, we study the recursive algorithms for a class of separable nonlinear models (SNLMs) in which the parameters can be partitioned into a linear part and a nonlinear part. Such models are very common in machine learning, system identification, and signal processing. Utilizing the special structure of the SNLMs, we propose a recursive variable projection (RVP) algorithm, in which at each recursion, the linear parameters of the model are eliminated, and the nonlinear parameters are updated by the recursive Levenberg-Marquart algorithm.

Malignant tumors associated with Peutz-Jeghers syndrome: Five cases from a single surgical unit.

Background: Peutz-Jeghers syndrome (PJS) is an autosomal dominant inherited disease easily causing secondary malignant changes without effective treatments.

Aim: To assess the clinical characteristics, diagnosis, and treatment of malignant changes secondary to PJS.

Methods: The clinical data of five patients with malignant changes secondary to PJS diagnosed and treated at Beijing Friendship Hospital from June 2014 to January 2017 were retrospectively analyzed; the follow-up ended in May 2018.

Term Selection for a Class of Separable Nonlinear Models.

In this paper, we consider the term selection problem for a class of separable nonlinear models. The strategy is a two-step process in which the nonlinear parameters of the model are first optimized by a variable projection method, and then the least absolute shrinkage and selection operator are adopted to obtain a sparse solution by picking out the critical terms automatically. This process may be repeated several times.

Basis Function Matrix-Based Flexible Coefficient Autoregressive Models: A Framework for Time Series and Nonlinear System Modeling.

We propose, in this paper, a framework for time series and nonlinear system modeling, called the basis function matrix-based flexible coefficient autoregressive (BFM-FCAR) model. It has very flexible nonlinear structure. We show that many famous nonlinear time series models can be derived under this framework by choosing the proper basis function matrices.

Modified Gram-Schmidt Method-Based Variable Projection Algorithm for Separable Nonlinear Models.

Separable nonlinear models are very common in various research fields, such as machine learning and system identification. The variable projection (VP) approach is efficient for the optimization of such models. In this paper, we study various VP algorithms based on different matrix decompositions.

Spontaneous cerebrospinal fluid rhinorrhea: A case report and analysis.

Introduction: Spontaneous cerebrospinal fluid leakage is usually caused by developmental abnormalities and is rare, accounting for approximately 5% of the cases of cerebrospinal fluid (CSF) leakage. To the best of our knowledge, clival dysplasia-caused CSF rhinorrhea has never been reported in the neurosurgical field.

Conclusion: Spontaneous cerebrospinal fluid rhinorrhea is often treated by surgery, and a transsphenoidal approach repair is the main surgical method used, offering the advantages of less trauma, fewer complications, rapid postoperative recovery, and low recurrence rate.

On Some Separated Algorithms for Separable Nonlinear Least Squares Problems.

For a class of nonlinear least squares problems, it is usually very beneficial to separate the variables into a linear and a nonlinear part and take full advantage of reliable linear least squares techniques. Consequently, the original problem is turned into a reduced problem which involves only nonlinear parameters. We consider in this paper four separated algorithms for such problems.

Efficacy and safety of using premedication with simethicone/Pronase during upper gastrointestinal endoscopy examination with sedation: A single center, prospective, single blinded, randomized controlled trial.

Background And Aim: To investigate the efficacy and safety of premedication with simethicone/Pronase during esophagogastroduodenoscopy (EGD) with sedation.

Methods: Six hundred and ten patients were randomly allocated to two groups based on type of premedication given. Premedication used in the control group was 10 mL lidocaine hydrochloride mucilage (LHM, N = 314) and premedication used in the intervention group was 80 mL simethicone/Pronase solution plus 10 mL lidocaine hydrochloride mucilage (SP/LHM, N = 296).

Evaluation and identification of factors related to and gene mutations in colorectal cancer: A meta-analysis.

Objective: The aim of this meta-analysis is to evaluate the distribution pattern of KRAS and BRAF mutations in colorectal cancer.

Materials And Methods: The database was searched without language restrictions. Meta-analyses were conducted using the STATA software.