Short-term outcomes of distal gastrectomy versus total gastrectomy for gastric cancer under enhanced recovery after surgery: a propensity score-matched analysis.

Enhanced recovery after surgery (ERAS) has been used safely and effectively in patients with gastric cancer. Our aim was to evaluate the short-term outcomes of total gastrectomy (TG) versus distal gastrectomy (DG) for gastric cancer under ERAS. A prospectively collected database of 1349 patients with gastric cancer who underwent TG or DG between January 2016 and September 2022 was retrospectively analyzed.

Automatic summarization of endoscopic skull base surgical videos through object detection and hidden Markov modeling.

Endoscopic endonasal surgery is a medical procedure that utilizes an endoscopic video camera to view and manipulate a surgical site accessed through the nose. Despite these surgeries being video recorded, these videos are seldom reviewed or even saved in patient files due to the size and length of the video file. Editing to a manageable size may necessitate viewing 3 h or more of surgical video and manually splicing together the desired segments.

Melatonin inhibited the progression of gastric cancer induced by Bisphenol S via regulating the estrogen receptor 1.

In recent years, Bisphenol S (BPS) has increasingly been used as an alternative to Bisphenol A (BPA) in food, paper, and personal care products. It is imperative to clarify the relationship between BPS and tumors in order to treat and prevent diseases. This study discovered a new method for predicting tumor correlations between BPS interactive genes.

Deep causal learning for robotic intelligence.

This invited Review discusses causal learning in the context of robotic intelligence. The Review introduces the psychological findings on causal learning in human cognition, as well as the traditional statistical solutions for causal discovery and causal inference. Additionally, we examine recent deep causal learning algorithms, with a focus on their architectures and the benefits of using deep nets, and discuss the gap between deep causal learning and the needs of robotic intelligence.

Nomogram for prediction of prolonged postoperative ileus after colorectal resection.

Background: Prolonged postoperative ileus (PPOI) is a major complication in patients undergoing colorectal resection. The aim of this study was to analyze the risk factors contributing to PPOI, and to develop an effective nomogram to determine the risks of this population.

Methods: A total of 1,254 patients with colorectal cancer who underwent radical colorectal resection at Fujian Cancer Hospital from March 2016 to August 2021 were enrolled as a training cohort in this study.

Dense Depth Estimation from Stereo Endoscopy Videos Using Unsupervised Optical Flow Methods.

In the context of Minimally Invasive Surgery, estimating depth from stereo endoscopy plays a crucial role in three-dimensional (3D) reconstruction, surgical navigation, and augmentation reality (AR) visualization. However, the challenges associated with this task are three-fold: 1) feature-less surface representations, often polluted by artifacts, pose difficulty in identifying correspondence; 2) ground truth depth is difficult to estimate; and 3) an endoscopy image acquisition accompanied by accurately calibrated camera parameters is rare, as the camera is often adjusted during an intervention. To address these difficulties, we propose an unsupervised depth estimation framework (END-flow) based on an unsupervised optical flow network trained on un-rectified binocular videos without calibrated camera parameters.

iGRLCDA: identifying circRNA-disease association based on graph representation learning.

While the technologies of ribonucleic acid-sequence (RNA-seq) and transcript assembly analysis have continued to improve, a novel topology of RNA transcript was uncovered in the last decade and is called circular RNA (circRNA). Recently, researchers have revealed that they compete with messenger RNA (mRNA) and long noncoding for combining with microRNA in gene regulation. Therefore, circRNA was assumed to be associated with complex disease and discovering the relationship between them would contribute to medical research.

Under-reporting of COVID-19 in the Northern Health Authority region of British Columbia.

Asymptomatic and pauci-symptomatic presentations of COVID-19 along with restrictive testing protocols result in undetected COVID-19 cases. Estimating undetected cases is crucial to understanding the true severity of the outbreak. We introduce a new hierarchical disease dynamics model based on the -mixtures hidden population framework.

Real-time virtual intraoperative CT in endoscopic sinus surgery.

Purpose: Endoscopic sinus surgery (ESS) is typically guided under preoperative computed tomography (CT), which increasingly diverges from actual patient anatomy as the surgery progresses. Studies have reported that the revision surgery rate in ESS ranges between 28 and 47%. This paper presents a method that can update the preoperative CT in real time to improve surgical completeness in ESS.

Interdigitating dendritic cell sarcoma located in the adrenal gland: a case report and literature review.

We report a case of interdigitating dendritic cell sarcoma (IDCS) originating from the adrenal gland. A 57-year-old middle-aged woman with no previous history of malignancy came to our hospital after color Doppler ultrasound revealed a right adrenal mass. An abdominal computed tomography scan also showed an adrenal mass.

Application of Primary/Secondary Circulating Tumor Cells for the Prediction of Biochemical Recurrence in Nonmetastatic Prostate Cancer Patients following Radical Prostatectomy or Radiotherapy: A Meta-Analysis.

Background: Circulating tumor cells (CTCs) have been regarded as an independent prognostic marker for metastatic castration-resistant prostate cancer (mCRPC). Its prognostic value, however, in nonmetastatic prostate cancer (NMPC) is still unclear.

Purpose: To elucidate whether CTCs can predict the biochemical recurrence (BCR) in NMPC patients following radical prostatectomy (RP) or radiotherapy (RT).

Total Synthesis of Dysifragilones A and B and Dysidavarone C.

The concise synthesis of dysifragilones A and B and dysidavarones has been accomplished for the first time in a divergent way from a common intermediate. The synthetic route features an intramolecular reductive Heck reaction to construct the 6/5/6/6/-tetracycle of dysifragilones A and B and an intramolecular palladium-catalyzed α-arylation of a sterically hindered ketone to forge the tetracyclo[7.7.

γ-Synuclein is Closely Involved in Autophagy that Protects Colon Cancer Cell from Endoplasmic Reticulum Stress.

Background: In previous studies, we provided evidence suggesting the involvement of γ-synuclein in growth, invasion, and metastasis of colon cancer cells in vitro and in vivo. Among γ-synuclein downstream genes, the microtubule-associated protein 1 Light Chain 3 (LC3), an autophagy gene, was screened by gene expression profile chip analysis.

Objective: We planned to investigate the functional effects of γ-synuclein on autophagy induced by ER stress in colon cancer cells.

CILP2 overexpression correlates with tumor progression and poor prognosis in patients with colorectal cancer in The Cancer Genome Atlas (TCGA) study.

Background: Genetic alterations play an important role in the progression of colorectal cancer (CRC). Identifying new biomarkers to assess the prognosis of patients with CRC is critical. Cartilage intermediate layer protein 2 (CILP2) gene, screened from TCGA database by bioinformatics, may be closely related to the progression of CRC.

SPRY4-IT1 promotes survival of colorectal cancer cells through regulating PDK1-mediated glycolysis.

Colorectal cancer (CRC) becomes the third leading cause of cancer-related deaths worldwide recently. The prognosis of CRC is still poor in decades, and targeted therapy is still a potential effective treatment. Long non-coding RNAs (lncRNAs) could regulate series of cellular functions and developmental processes.

Learning Representations to Predict Intermolecular Interactions on Large-Scale Heterogeneous Molecular Association Network.

Molecular components that are functionally interdependent in human cells constitute molecular association networks. Disease can be caused by disturbance of multiple molecular interactions. New biomolecular regulatory mechanisms can be revealed by discovering new biomolecular interactions.

GCNCDA: A new method for predicting circRNA-disease associations based on Graph Convolutional Network Algorithm.

Numerous evidences indicate that Circular RNAs (circRNAs) are widely involved in the occurrence and development of diseases. Identifying the association between circRNAs and diseases plays a crucial role in exploring the pathogenesis of complex diseases and improving the diagnosis and treatment of diseases. However, due to the complex mechanisms between circRNAs and diseases, it is expensive and time-consuming to discover the new circRNA-disease associations by biological experiment.

A Model-Based Recurrent Neural Network With Randomness for Efficient Control With Applications.

Recently, Recurrent Neural Network (RNN) control schemes for redundant manipulators have been extensively studied. These control schemes demonstrate superior computational efficiency, control precision, and control robustness. However, they lack planning completeness.

LMTRDA: Using logistic model tree to predict MiRNA-disease associations by fusing multi-source information of sequences and similarities.

Emerging evidence has shown microRNAs (miRNAs) play an important role in human disease research. Identifying potential association among them is significant for the development of pathology, diagnose and therapy. However, only a tiny portion of all miRNA-disease pairs in the current datasets are experimentally validated.

An Improved Deep Forest Model for Predicting Self-Interacting Proteins From Protein Sequence Using Wavelet Transformation.

Self-interacting proteins (SIPs), whose more than two identities can interact with each other, play significant roles in the understanding of cellular process and cell functions. Although a number of experimental methods have been designed to detect the SIPs, they remain to be extremely time-consuming, expensive, and challenging even nowadays. Therefore, there is an urgent need to develop the computational methods for predicting SIPs.

Comparison of Micro-Computed Tomography and Clinical Computed Tomography Protocols for Visualization of Nasal Cartilage Before Surgical Planning for Rhinoplasty.

Importance: There is no imaging standard to model nasal cartilage for the planning of rhinoplasty procedures. Preoperative visualization of cartilage may improve objective evaluation of nasal deformities, surgical planning, and surgical reconstruction.

Objectives: To evaluate the feasibility of visualizing nasal cartilage using high resolution micro-computed tomography (CT) compared with the criterion standard of pathologic findings in a cadaveric specimen and to evaluate its accuracy compared with various clinical CT protocols.

Syntheses of 12H-benzo[a]xanthen-12-ones and benzo[a]acridin-12(7H)-ones through Au(i)-catalyzed Michael addition/6-endo-trig cyclization/aromatization cascade annulation.

A multifaceted gold(i)-catalyzed aromaticity-driven double 6-endo cascade cyclization strategy to synthesize both 12H-benzo[a]xanthen-12-ones and benzo[a]acridin-12(7H)-ones, whose core motifs xanthone and acridone both exist as important scaffolds in an immense number of bioactive compounds, was developed. The scopes of this strategy were examined by using a batch of synthetic 1,3-diphenylprop-2-yn-1-one substrates. To probe the mechanism of this cyclization a control experiment for synthesizing intermediates was performed.

A Novel Recurrent Neural Network for Improving Redundant Manipulator Motion Planning Completeness.

Recurrent Neural Networks (RNNs) demonstrated advantages on control precision, system robustness and computational efficiency, and have been widely applied to redundant manipulator control optimization. Existing RNN control schemes locally optimize trajectories and are efficient and reliable on obstacle avoidance. However, for motion planning, they suffer from local minimum and do not have planning completeness.

Anatomical Region Segmentation for Objective Surgical Skill Assessment with Operating Room Motion Data.

 Most existing objective surgical motion analysis schemes are limited to structured surgical tasks or recognition of motion patterns for certain categories of surgeries. Analyzing instrument motion data with respect to anatomical structures can break the limit, and an anatomical region segmentation algorithm is required for the analysis.  An atlas was generated by manually segmenting the skull base into nine regions, including left/right anterior/posterior ethmoid sinuses, frontal sinus, left and right maxillary sinuses, nasal airway, and sphenoid sinus.