Efficacy of radial incision combined with tunnel floating line drainage in the treatment of high posterior horseshoe anal fistula and perianal flora: Randomized control trial.

Background: Due to the high prevalence of posterior horseshoe anal fistula and causing numerous complications, this study aimed to investigate the clinical effect of radial incision combined with tunnel floating line drainage (RCTD) and arc incision internal drainage in the treatment of the disease and the influence on perianal flora.

Methods: Ninety-six subjects treated with high posterior horseshoe anal fistula were stochastically assigned to a joint group (RCTD), and control group (arc incision internal drainage). The operation-related conditions, complication rate, anal function, and recurrence rate of 6 months after operation were compared, and perianal secretions were collected before operation and 1 day after operation to detect the changes of microbial flora.

Early prediction of acute kidney injury in patients with gastrointestinal bleeding admitted to the intensive care unit based on extreme gradient boosting.

Background: Acute kidney injury (AKI) is a common and important complication in patients with gastrointestinal bleeding who are admitted to the intensive care unit. The present study proposes an artificial intelligence solution for acute kidney injury prediction in patients with gastrointestinal bleeding admitted to the intensive care unit.

Methods: Data were collected from the eICU Collaborative Research Database (eICU-CRD) and Medical Information Mart for Intensive Care-IV (MIMIC-IV) database.

[Preparation and properties of silica/hydroxyapatite whiskers porous ceramics scaffold].

Objective: To investigate the preparation and properties of the novel silica (SiO )/hydroxyapatite (HAP) whiskers porous ceramics scaffold.

Methods: The HAP whiskers were modified by the SiO microspheres using the Stöber method. Three types of SiO /HAP whiskers were fabricated under different factors (for the No.

Prognostic Value of Systemic Inflammatory Response Index for the Prognosis of Diabetic Maintenance Hemodialysis Patients: A Retrospective Observational Study.

Background: The systemic inflammatory response index (SIRI) had been identified as an inflammatory marker and has been linked to determining clinical outcomes in several diseases. We advocated the relationship between the initial SIRI and the prognosis of diabetic maintenance hemodialysis (MHD) patients.

Methods: A total of 153 diabetic MHD patients who accepted regular HD treatment at our hospital were enrolled in this study.

Relationship between Abdominal Obesity and Insulin Resistance, Growth Hormone, and Insulin-like Growth Factor-1 in Individuals with Type 2 Diabetes.

This experiment was designed to investigate the correlation between abdominal obesity and insulin resistance (IR), growth hormone (GH) and insulin-like growth factor-1 (IGF-1) in patients with type 2 diabetes mellitus (T2DM). To do this experiment, 200 patients with T2DM were enrolled in this cross-sectional study. They were divided into the control group (T2DM without abdominal obesity) and the observation group (T2DM combined with abdominal obesity) according to the diagnostic criteria of abdominal obesity.

Effects of Full Inhalation of Sevoflurane and Total Intravenous Anesthesia on Hemodynamics, Serum Myocardial Enzymes, and Myocardial Markers in Elderly Patients Undergoing Hysterectomy.

Objective: To compare the effects of sevoflurane inhalation and intravenous anesthesia on hemodynamics, serum myocardial enzymes, and myocardial markers in elderly patients undergoing hysterectomy.

Methods: Group A and group B were established randomly regarding a total of 126 elderly patients who underwent an elective hysterectomy. Patients in group A were given full anesthesia with sevoflurane, and patients in group B were given anesthesia with intravenous anesthesia.

Gene selection for microarray data classification via adaptive hypergraph embedded dictionary learning.

Due to the rapid development of DNA microarray technology, a large number of microarray data come into being and classifying these data has been verified useful for cancer diagnosis, treatment and prevention. However, microarray data classification is still a challenging task since there are often a huge number of genes but a small number of samples in gene expression data. As a result, a computational method for reducing the dimension of microarray data is necessary.

Dual Laplacian regularized matrix completion for microRNA-disease associations prediction.

Since lots of miRNA-disease associations have been verified, it is meaningful to discover more miRNA-disease associations for serving disease diagnosis and prevention of human complex diseases. However, it is not practical to identify potential associations using traditional biological experimental methods since the process is expensive and time consuming. Therefore, it is necessary to develop efficient computational methods to accomplish this task.