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Despite that convolutional neural networks (CNNs) have shown high-quality reconstruction for single image dehazing, recovering natural and realistic dehazed results remains a challenging problem due to semantic confusion in the hazy scene. In this article, we show that it is possible to recover textures faithfully by incorporating semantic prior into dehazing network since objects in haze-free images tend to show certain shapes, textures, and colors. We propose a semantic-aware dehazing network (SDNet) in which the semantic prior is taken as a color constraint for dehazing, benefiting the acquisition of a reasonable scene configuration. In addition, we design a densely connected block to capture global and local information for dehazing and semantic prior estimation. To eliminate the unnatural appearance of some objects, we propose to fuse the features from shallow and deep layers adaptively. Experimental results demonstrate that our proposed model performs favorably against the state-of-the-art single image dehazing approaches.

Aggregate nearest neighbor ( Ann ) query in both the euclidean space and road networks has been extensively studied, and the flexible aggregate nearest neighbor ( Fann ) problem further generalizes Ann by introducing an extra flexibility parameter $\phi$ ϕ that ranges in $(0, 1]$ ( 0 , 1 ] . In this article, we focus on Fann on road networks, denoted as Fann $_\mathcal {R}$ R , and its keyword-aware variant, denoted as KFann $_\mathcal {R}$ R . To solve these problems, we propose a series of universal (i.e., suitable for both max and sum ) algorithms, including a Dijkstra-based algorithm that enumerates $P$ P instead of $\phi |Q|$ ϕ | Q | -combinations of $Q$ Q , a queue-based approach that processes data points from-near-to-far, and a framework that combines incremental euclidean restriction (IER) and $k$ k NN. We also propose a specific exact solution to max - Fann $_\mathcal {R}$ R and a constant-factor ratio approximate solution to sum - Fann $_\mathcal {R}$ R . These specific algorithms are easy to implement and can achieve excellent performance in some scenarios. Besides, we further extend this problem to top- $k$ k and multiple Fann $_\mathcal {R}$ R (resp., KFann $_\mathcal {R}$ R ) queries. We conduct a comprehensive experimental evaluation for the proposed algorithms on real datasets to demonstrate their superior efficiency and high quality.

Serrated polyps have been recognized as the important premalignant lesions. In this study, we aimed to analyze the clinicopathological features of sessile serrated polyps and determine the association between sessile serrated polyps and synchronous advanced adenomas.Consecutive patients undergoing diagnostic or therapeutic colonoscopies (including 156 681 diagnostic colonoscopies) from 2011 to 2019 were included.A total of 958 patients, including 699 (73%) males, were detected with at least 1 sessile serrated polyp, and 65.9% (n = 658) of sessile serrated polyps were located in the distal colon. Advanced serrated lesions accounted for 9.1% (n = 91) of all the sessile serrated polyp (n = 999). The types of SSP included flat type (953/999, 95.4%) and sub-pedunculated or pedunculated type (46/999, 4.6%). Meanwhile, there was no obvious evidence supporting the association between advanced adenomas and characteristics of advanced serrated lesions or sessile serrated polyps.Sessile serrated polyps seem to be more frequently seen in the distal colon of men in this study. However, more evidence is required to confirm the actual distribution of sessile serrated polyp in colon among Chinese people. There is still much room for improvement of sessile serrated polyp detection rate, and more importance should be attached to sessile serrated polyp both for pathologists and endoscopists.

Effectively identifying compound-protein interactions (CPIs) is crucial for new drug design, which is an important step in silico drug discovery. Current machine learning methods for CPI prediction mainly use one-demensional (1D) compound/protein strings and/or the specific descriptors. However, they often ignore the fact that molecules are essentially modeled by the molecular graph. We observe that in real-world scenarios, the topological structure information of the molecular graph usually provides an overview of how the atoms are connected, and the local chemical context reveals the functionality of the protein sequence in CPI. These two types of information are complementary to each other and they are both significant for modeling compound-protein pairs. Motivated by this, we propose an end-to-end deep learning framework named GraphCPI, which captures the structural information of compounds and leverages the chemical context of protein sequences for solving the CPI prediction task. Our framework can integrate any popular graph neural networks for learning compounds, and it combines with a convolutional neural network for embedding sequences. To compare our method with classic and state-of-the-art deep learning methods, we conduct extensive experiments based on several widely-used CPI datasets. The experimental results show the feasibility and competitiveness of our proposed method.

The accurate identification of forest tree species is the basis for the utilization and protection of forest resources. In this study, we collected hyperspectral data on 3287 leaves from seven typi...

Evidence on the comparative diagnostic performance of endoscopic ultrasound (EUS)-based techniques for pancreatic cyst lesions (PCLs) is limited. This network meta-analysis comprehensively compared EUS-based techniques for PCLs diagnosis.A comprehensive literature search was performed for all comparative studies assessing the accuracy of 2 or more modalities for PCLs diagnosis. The primary outcome was the diagnostic efficacy for mucinous PCLs. Secondary outcomes were the diagnostic efficacy for malignant PCLs, diagnostic success rate, and adverse event rate. A network meta-analysis was conducted using the ANOVA model to assess the diagnostic accuracy of each index.Forty studies comprising 3641 patients were identified. The network ranking of the superiority index for EUS-guided needle-based confocal laser endomicroscopy (EUS-nCLE) and EUS-guided through-the-needle biopsy (EUS-TTNB) were significantly higher than other techniques for differentiating mucinous PCLs; besides, EUS-TTNB was also the optimal technique in identifying malignant PCLs. The evidence was inadequate for EUS-nCLE diagnosing malignant PCLs and CH-EUS for diagnosing both mucinous and malignant PCLs. Glucose showed a high sensitivity but low specificity, and molecular analysis (KRAS, GNAS and KRAS+GNAS mutations) showed a high specificity but low sensitivity for diagnosing mucinous PCLs. Satisfactory results were not obtained during the evaluation of the efficiency of pancreatic cyst fluid (PCF) biomarkers in detecting malignant PCLs.For centers with relevant expertise and facilities, EUS-TTNB and EUS-nCLE were better choices for the diagnosis of PCLs. Further studies are urgently required for further improving PCF biomarkers and validating diagnostic performance of the index techniques.

Li-rich high-Mn oxides, xLi2MnO3·(1 − x)LiMO2 (x ≥ 0.5, M = Co, Ni, Mn…), have attracted extensive research interest due to their high specific capacity and low cost. However, slow Li2MnO3 activation and poor cycling stability have affected their electrochemical performance. Herein, to solve these problems, morphology regulation and LiAlF4 coating strategies have been synergistically applied to a Li-rich high-Mn material Li1.7Mn0.8Co0.1Ni0.1O2.7 (HM-811). This dual-strategy successfully promotes the activation process of the Li2MnO3 phase and thus improves the electrochemical performance of HM-811. Theoretical computation indicates that the LiAlF4 layer has a lower Li+ migration barrier than the HM-811 matrix, so it could boost the diffusion of Li+ ions and promote the activation of the Li2MnO3 phase. Benefiting from the morphology regulation and LiAlF4 coating, the HM-811 cathode shows a high initial charge capacity of >300 mA h g−1. In addition, the modified HM-811 could deliver superior electrochemical performance even at a low temperature of −20 °C. This work provides a new approach for developing high performance cathode materials for next-generation Li-ion batteries.

Rain removal from a single image is a challenging problem and has attracted much attention in recent years. In this paper, we revisit the single image deraining problem, and present a novel solution. The central idea of our solution is to merge the merits of two-phase processing methods and the Fuzzy Broad Learning System (FBLS). Specifically, our solution first uses the dehazing algorithm to preprocess the input rainy image and separates it into the detail layer and the base layer. After that, it puts the Y-channel image of the detail layer into the FBLS to obtain the derained Y channel image, which is then combined with the Cb and Cr channel images to obtain the derained detail layer. Later, it fuses the derained detail layer and the base layer to get a preliminary derained image. Finally, it superimposes the details extracted from the dehazed image with some transparency on the preliminary result, obtaining the final result. Experimental results based on both real and synthetic rainy images demonstrate that our proposed solution can outperform several state-of-the-art algorithms, while it consumes much less running time and training time, compared against the competitors.

BACKGROUND Conventional clinical guidelines recommend that at least 12 lymph nodes should be removed during radical rectal cancer surgery to achieve accurate staging. The current application of neoadjuvant therapy has changed the number of lymph node dissection. AIM To investigate factors affecting the number of lymph nodes dissected after neoadjuvant chemoradiotherapy in locally advanced rectal cancer and to evaluate the relationship of the total number of retrieved lymph nodes (TLN) with disease-free survival (DFS) and overall survival (OS). METHODS A total of 231 patients with locally advanced rectal cancer from 2015 to 2017 were included in this study. According to the American Joint Committee on Cancer (AJCC)/Union for International Cancer Control (UICC) tumor-node-metastasis (TNM) classification system and the NCCN guidelines for rectal cancer, the patients were divided into two groups: group A (TLN ≥ 12, n = 177) and group B (TLN < 12, n = 54). Factors influencing lymph node retrieval were analyzed by univariate and binary logistic regression analysis. DFS and OS were evaluated by Kaplan-Meier curves and Cox regression models. RESULTS The median number of lymph nodes dissected was 18 (range, 12-45) in group A and 8 (range, 2-11) in group B. The lymph node ratio (number of positive lymph nodes/total number of lymph nodes) (P = 0.039) and the interval between neoadjuvant therapy and radical surgery (P = 0.002) were independent factors of the TLN. However,TLN was not associated with sex, age, ASA score, clinical T or N stage, pathological T stage, tumor response grade (Dworak), downstaging, pathological complete response, radiotherapy dose, preoperative concurrent chemotherapy regimen, tumor distance from anal verge, multivisceral resection, preoperative carcinoembryonic antigen level, perineural invasion, intravascular tumor embolus or degree of differentiation. The pathological T stage (P < 0.001) and TLN (P < 0.001) were independent factors of DFS, and pathological T stage (P = 0.011) and perineural invasion (P = 0.002) were independent factors of OS. In addition, the risk of distant recurrence was greater for TLN < 12 (P = 0.009). CONCLUSION A shorter interval to surgery after neoadjuvant chemoradiotherapy for rectal cancer under indications may cause increased number of lymph nodes harvested. Tumor shrinkage and more extensive lymph node retrieval may lead to a more favorable prognosis.

Saliency detection has been a hot topic in the field of computer vision. In this paper, we propose a novel approach that is based on multiscale segmentation and fuzzy broad learning. The core idea of our method is to segment the image into different scales, and then the extracted features are fed to the fuzzy broad learning system (FBLS) for training. More specifically, it first segments the image into superpixel blocks at different scales based on the simple linear iterative clustering algorithm. Then, it uses the local binary pattern algorithm to extract texture features and computes the average color information for each superpixel of these segmentation images. These extracted features are then fed to the FBLS to obtain multiscale saliency maps. After that, it fuses these saliency maps into an initial saliency map and uses the label propagation algorithm to further optimize it, obtaining the final saliency map. We have conducted experiments based on several benchmark datasets. The results show that our solution can outperform several existing algorithms. Particularly, our method is significantly faster than most of deep learning-based saliency detection algorithms, in terms of training and inferring time.

In recent years, spatial-keyword queries have attracted much attention with the fast development of location-based services. However, current spatial-keyword techniques are disk-based, which cannot fulfill the requirements of high throughput and low response time. With the surging data size, people tend to process data in distributed in-memory environments to achieve low latency. In this paper, we present the distributed solution, i.e., Skia (Spatial-Keyword In-memory Analytics), to provide a scalable backend for spatial-textual analytics. Skia introduces a two-level index framework for big spatial-textual data including: (1) efficient and scalable global index, which prunes the candidate partitions a lot while achieving small space budget; and (2) four novel local indexes, that further support low latency services for exact and approximate spatial-keyword queries. Skia can support common spatial-keyword queries via traditional SQL programming interfaces. The experiments conducted on large-scale real datasets have demonstrated the promising performance of the proposed indexes and our distributed solution.

BACKGROUND Colorectal cancer is a common digestive cancer worldwide. As a comprehensive treatment for locally advanced rectal cancer (LARC), neoadjuvant therapy (NT) has been increasingly used as the standard treatment for clinical stage II/III rectal cancer. However, few patients achieve a complete pathological response, and most patients require surgical resection and adjuvant therapy. Therefore, identifying risk factors and developing accurate models to predict the prognosis of LARC patients are of great clinical significance. AIM To establish effective prognostic nomograms and risk score prediction models to predict overall survival (OS) and disease-free survival (DFS) for LARC treated with NT. METHODS Nomograms and risk factor score prediction models were based on patients who received NT at the Cancer Hospital from 2015 to 2017. The least absolute shrinkage and selection operator regression model were utilized to screen for prognostic risk factors, which were validated by the Cox regression method. Assessment of the performance of the two prediction models was conducted using receiver operating characteristic curves, and that of the two nomograms was conducted by calculating the concordance index (C-index) and calibration curves. The results were validated in a cohort of 65 patients from 2015 to 2017. RESULTS Seven features were significantly associated with OS and were included in the OS prediction nomogram and prediction model: Vascular_tumors_bolt, cancer nodules, yN, body mass index, matchmouth distance from the edge, nerve aggression and postoperative carcinoembryonic antigen. The nomogram showed good predictive value for OS, with a C-index of 0.91 (95%CI: 0.85, 0.97) and good calibration. In the validation cohort, the C-index was 0.69 (95%CI: 0.53, 0.84). The risk factor prediction model showed good predictive value. The areas under the curve for 3- and 5-year survival were 0.811 and 0.782. The nomogram for predicting DFS included ypTNM and nerve aggression and showed good calibration and a C-index of 0.77 (95%CI: 0.69, 0.85). In the validation cohort, the C-index was 0.71 (95%CI: 0.61, 0.81). The prediction model for DFS also had good predictive value, with an AUC for 3-year survival of 0.784 and an AUC for 5-year survival of 0.754. CONCLUSION We established accurate nomograms and prediction models for predicting OS and DFS in patients with LARC after undergoing NT.

Background Epidemiologically, in China, locally advanced rectal cancer is a more common form of rectal cancer. Preoperative neoadjuvant concurrent chemoradiotherapy can effectively reduce the size of locally invasive tumors and improve disease-free survival (DFS) and pathologic response after surgery. At present, this modality has become the standard protocol for the treatment of locally advanced rectal cancer in many centers, but the optimal time for surgery after neoadjuvant therapy is still controversial. Aim To investigate the impact of time interval between neoadjuvant therapy and surgery on DFS and pathologic response in patients with locally advanced rectal cancer. Methods A total of 231 patients who were classified as having clinical stage II or III advanced rectal cancer and underwent neoadjuvant chemoradiation followed by surgery at the National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College from November 2014 to August 2017 were involved in this retrospective cohort study. The patients were divided into two groups based on the different time intervals between neoadjuvant therapy and surgery: 139 (60.2%) patients were in group A (≤ 9 wk), and 92 (39.2%) patients were in group B (> 9 wk). DFS and pathologic response were analyzed as the primary endpoints. The secondary endpoints were postoperative complications and sphincter preservation. Results For the 231 patients included, surgery was performed at ≤ 9 wk in 139 (60.2%) patients and at > 9 wk in 92 (39.8%). The patients' clinical characteristics, surgical results, and tumor outcomes were analyzed through univariate analysis combined with multivariate regression analysis. The overall pathologic complete response (pCR) rate was 27.2% (n = 25) in the longer time interval group (> 9 wk) and 10.8% (n = 15) in the shorter time interval group (≤ 9 wk, P = 0.001). The postoperative complications did not differ between the groups (group A, 5% vs group B, 5.4%; P = 0.894). Surgical procedures for sphincter preservation were performed in 113 (48.9%) patients, which were not significantly different between the groups (group A, 52.5% vs group B, 43.5%; P = 0.179). The pCR rate was an independent factor affected by time interval (P = 0.009; odds ratio [OR] = 2.668; 95%CI: 1.276-5.578). Kaplan-Meier analysis and Cox regression analysis showed that the longer time interval (> 9 wk) was a significant independent prognostic factor for DFS (P = 0.032; OR = 2.295; 95%CI: 1.074-4.905), but the time interval was not an independent prognostic factor for overall survival (P > 0.05). Conclusion A longer time interval to surgery after neoadjuvant therapy may improve the pCR rate and DFS but has little impact on postoperative complications and sphincter preservation.

Background For laparoscopic rectal cancer surgery, the inferior mesenteric artery (IMA) can be ligated at its origin from the aorta [high ligation (HL)] or distally to the origin of the left colic artery [low ligation (LL)]. Whether different ligation levels are related to different postoperative complications, operation time, and lymph node yield remains controversial. Therefore, we designed this study to determine the effects of different ligation levels in rectal cancer surgery. Aim To investigate the operative results following HL and LL of the IMA in rectal cancer patients. Methods From January 2017 to July 2019, this retrospective cohort study collected information from 462 consecutive rectal cancer patients. According to the ligation level, 235 patients were assigned to the HL group while 227 patients were assigned to the LL group. Data regarding the clinical characteristics, surgical characteristics and complications, pathological outcomes and postoperative recovery were obtained and compared between the two groups. A multivariate logistic regression analysis was performed to evaluate the possible risk factors for anastomotic leakage (AL). Results Compared to the HL group, the LL group had a significantly lower AL rate, with 6 (2.8%) cases in the LL group and 24 (11.0%) cases in the HL group (P = 0.001). The HL group also had a higher diverting stoma rate (16.5% vs 7.5%, P = 0.003). A multivariate logistic regression analysis was subsequently performed to adjust for the confounding factors and confirmed that HL (OR = 3.599; 95%CI: 1.374-9.425; P = 0.009), tumor located below the peritoneal reflection (OR = 2.751; 95%CI: 0.772-3.985; P = 0.031) and age (≥ 65 years) (OR = 2.494; 95%CI: 1.080-5.760; P = 0.032) were risk factors for AL. There were no differences in terms of patient demographics, pathological outcomes, lymph nodes harvested, blood loss, hospital stay and urinary function (P > 0.05). Conclusion In rectal cancer surgery, LL should be the preferred method, as it has a lower AL and diverting stoma rate.

Background Lateral lymph node metastasis is one of the leading causes of local recurrence in patients with advanced mid or low rectal cancer. Neoadjuvant chemoradiotherapy (NCRT) can effectively reduce the postoperative recurrence rate; thus, NCRT with total mesorectal excision (TME) is the most widely accepted standard of care for rectal cancer. The addition of lateral lymph node dissection (LLND) after NCRT remains a controversial topic. Aim To investigate the surgical outcomes of TME plus LLND, and the possible risk factors for lateral lymph node metastasis after NCRT. Methods This retrospective study reviewed 89 consecutive patients with clinical stage II-III mid or low rectal cancer who underwent TME and LLND from June 2016 to October 2018. In the NCRT group, TME plus LLND was performed in patients with short axis (SA) of the lateral lymph node greater than 5 mm. In the non-NCRT group, TME plus LLND was performed in patients with SA of the lateral lymph node greater than 10 mm. Data regarding patient demographics, clinical workup, surgical procedure, complications, and outcomes were collected. Multivariate logistic regression analysis was performed to evaluate the possible risk factors for lateral lymph node metastasis in NCRT patients. Results LLN metastasis was pathologically confirmed in 35 patients (39.3%): 26 (41.3%) in the NCRT group and 9 (34.6%) in the non-NCRT group. The most common site of metastasis was around the obturator nerve (21/35) followed by the internal iliac artery region (12/35). In the NCRT patients, 46% of patients with SA of LLN greater than 7 mm were positive. The postoperative 30-d mortality rate was 0%. Two (2.2%) patients suffered from lateral local recurrence in the 2-year follow up. Multivariate analysis showed that cT4 stage (odds ratio [OR] = 5.124, 95% confidence interval [CI]: 1.419-18.508; P = 0.013), poor differentiation type (OR = 4.014, 95%CI: 1.038-15.520; P = 0.044), and SA ≥ 7 mm (OR = 7.539, 95%CI: 1.487-38.214; P = 0.015) were statistically significant risk factors associated with LLN metastasis. Conclusion NCRT is not sufficient as a stand-alone therapy to eradicate LLN metastasis in lower rectal cancer patients and surgeons should consider performing selective LLND in patients with greater LLN SA diameter, poorer histological differentiation, or advanced T stage. Selective LLND for NCRT patients can have a favorable oncological outcome.

Power-aware task scheduling on processors has been a research hotspot in computing systems. Given an application $G$ G containing a set $N$ N of tasks $\lbrace n_1,\ldots, n_{|N|}\rbrace$ { n 1 , ... , n | N | } , and a system containing a set $U$ U of processors $\lbrace u_1,\ldots, u_{|U|}\rbrace$ { u 1 , ... , u | U | } , the power-aware task scheduling generally refers to finding the appropriate processor and frequency for each task $n_i$ n i , so as to make sure that all the tasks can be finished efficiently and the overall energy consumption is guaranteed. In this article, we study the problem of minimizing the schedule length for energy consumption constrained parallel applications on heterogeneous computing systems, where the schedule length refers to the time interval between starting the first task and finishing the last task. For this problem, existing work adopts a policy that preassigns the minimum energy consumption for each unassigned task. Nevertheless, our analysis reveals that, such a preassignment policy could be unfair for the low priority tasks, and it may not achieve an optimistic schedule length . Thereby, we propose a new task scheduling algorithm that suggests a weight-based mechanism to preassign energy consumption for unassigned tasks, and we provide the rigorous proof to show its feasibility. Further, we show that this idea can be extended to solve reliability maximization problems with energy consumption constraint or with both deadline and energy consumption constraints, where the reliability refers to the probability of executing application $G$ G without failures, and the deadline constraint refers to the “allowable” maximum schedule length. We have conducted extensive experiments based on real parallel applications. The experimental results consistently demonstrate that our proposed algorithms can achieve favourable performance, compared to state-of-the-art algorithms.

Background: Chemotherapy is the most important treatment method against cancer, in addition to surgery and radiotherapy. However, Multidrug Resistance (MDR) in cancer always results in the failure of chemotherapy. Effective chemotherapy agents need to be delivered efficiently, distributed mostly in the tumor tissue, and highly internalized by tumor cells to eventually inhibit proliferation or promote death of the tumor cells. A growing number of studies have indicated that any defects that emerge during these steps could contribute to the occurrence of MDR in tumors. Carbon Nanotubes (CNTs) are newly developed biocompatible materials that can be designed to deliver anticancer agents by functionalizing the CNTs with drugs. Enhanced drug delivery efficiency and improved treatment efficacy have been observed through CNT-based drug delivery systems. However, some reports have shown that the simple administration of CNTs can reverse MDR in cancer and enhance chemotherapy efficacy without anticancer agents attached to the surface of the CNTs. Objective: Through an extensive review of previous reports in regard to CNTs and chemotherapy, this paper aims to identify the various mechanisms of CNTs that inhibit MDR in cancer and enhance chemotherapy sensitivity. Results: CNTs can increase the antitumor effects of chemotherapy agents. CNTs can not only increase drug delivery accuracy and efficiency but also promote drug uptake, decrease drug efflux, improve tumor hypoxia conditions, and induce autophagy and apoptosis in tumor cells, which make the tumor more sensitive to antitumor agents.

A field experiment was conducted with 24 indica-japonica hybrid rice varieties (lines) of Yongyou series, from which three types (high yield and high AE (agronomic nitrogen use efficiency) [HH], high yield and medium AE [HM], medium yield and medium AE [MM]) were selected to explore the characteristics of varieties with high yield and high AE. The yield of HH type was 4.04%–4.38% and 13.37%–13.41% higher than that of HM type and MM type respectively, owing to the larger number of total spikelets, which was 5.87×108–6.20×108 hm–2. Compared with HM and MM type, HH type had a high percentage of tiller rate, which was 68.83%–70.05%. The LAI of HH type was maximum at heading stage and declined slowly after heading. As a result, the LAI of HH type was above 3.85 at maturity stage. The dry matter accumulation of HH type was 7.91–7.99 t hm–2 from heading to maturity, which was the highest in three types, and its dry matter accumulation was more than 21.15–21.46 t hm–2 in the whole growth period. The total nitrogen uptake of HH type showed 5.07%–5.14% and 4.50%–5.96% increase than that of HM type and MM type respectively at maturity stage. The nitrogen sbsorption rate from jointing to heading stage and from heading to maturity stage showed HH type > HM type > MM type, as well as NTSH (N transportation from stem after heading), NIPH (N increase in panicle after heading) and NHI (N harvest index). HH type had the highest NRE (nitrogen recovery use efficiency), AE, PE (physiological nitrogen use efficiency) and PFP (partial factor productivity of applied N). Expect for NRE and NRG (nitrogen requirement for 100 kg grain), all the other nitrogen utilization indexes of HM type were higher than that of MM type.

Colorectal cancer (CRC) is a common malignant tumor of the gastrointestinal tract. Lipid metabolism, as an important part of material and energy circulation, is well known to play a crucial role in CRC.To explore the relationship between serum lipids and CRC development and identify aberrantly expressed cholesterol metabolism genes in CRC.We retrospectively collected 843 patients who had confirmed CRC and received surgical resection from 2013 to 2015 at the Cancer Hospital of the Chinese Academy of Medical Sciences as our research subjects. The levels of serum total cholesterol (TC), triglycerides, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), LDL-C/HDL-C and clinical features were collected and statistically analyzed by SPSS. Then, we used the data from Oncomine to screen the differentially expressed genes (DEGs) of the cholesterol metabolism pathway in CRC and used Gene Expression Profiling Interactive Analysis to confirm the candidate DEGs. PrognoScan was used to analyze the prognostic value of the DEGs, and Search Tool for the Retrieval of Interacting Genes was used to construct the protein-protein interaction network of DEGs.The serum HDL-C level in CRC patients was significantly correlated with tumor size, and patients whose tumor size was more than 5 cm had a lower serum HDL-C level (1.18 ± 0.41 mmol/LSerum HDL-C levels are associated with tumor size and stage in CRC patients. LRP8, PCSK9, LDLR, MBTPS2 and FDXR are upregulated, while ABCA1 and OSBPL1A are downregulated in CRC. Among them, LDLR, ABCA1, OSBPL1A and FDXR were valuable prognostic factors of DFS and were involved in important cellular function pathways.

The absence of CD8+ T cells in the tumor center has become a major obstacle in the immunotherapy of colorectal cancer. Therefore, new therapeutic strategies are urgently needed to promote the accumulation of CD8+ T cells in the tumor center. Previous studies have shown that triterpenoid of

Introduction: Colorectal cancer has been ranked third among the most common cancers worldwide and raised to the second leading cause of cancer death with nearly one-tenth of cancer-related deaths globally, and nearly half of colorectal cancer patients present with or develop colorectal cancer liver metastasis (CRLM). Buzhong Tiaogan Formula (BTF) has been proven to treat CRLM in our team, but there are lacking of evidence on its effective in delaying colorectal liver metastasis (liver depression spleen deficiency type), so we will evaluate the efficacy and safety of BTF in preventing the occurrence of CRLM. Methods: This randomized controlled trial (RCT) will be carried out in 3 different hospitals in Shanxi Province planning to recruit 150 CRLM patients with the type of liver depression spleen deficiency. The control group will be treated by basic antitumor therapy and the treatment group will use BTF plus basic antitumor therapy. The primary outcomes will be quality of life of included patients, the time of occurrence of liver metastasis, the score of traditional Chinese medicine symptom for the type of liver depression spleen deficiency; and the secondary outcomes will include overall survival, progression-free survival, DFS, tumor microenvironment and immune state of the included patient. Safety evaluation will be recorded during the whole study. All data in this RCT will be analyzed by SPSS 23.0 software. This study has been approved by the Clinical Research Ethics Committee of Shanxi Province Hospital of Traditional Chinese medicine (2021Y-06016). Discussion: The results of this RCT will contribute to BTF for delaying colorectal liver metastasis (liver depression spleen deficient type). And the results from this RCT will be published in a relevant journal after finished. Trial registration: ChiMCTR2100005268 (September 4, 2021).

Disconnected pancreatic duct syndrome (DPDS) is an important and common complication of acute necrotizing pancreatitis. Endoscopic approach has been established as the first-line treatment for pancreatic fluid collections (PFCs) with less invasion and satisfactory outcome. However, the presence of DPDS significantly complicates the management of PFC; besides, there is no standardized treatment for DPDS. The diagnosis of DPDS presents the first step of management, which can be preliminarily established by imaging methods including contrast-enhanced computed tomography, ERCP, magnetic resonance cholangiopancreatography (MRCP), and EUS. Historically, ERCP is considered as the gold standard for the diagnosis of DPDS, and secretin-enhanced MRCP is recommended as an appropriate diagnostic method in existing guidelines. With the development of endoscopic techniques and accessories, the endoscopic approach, mainly including transpapillary and transmural drainage, has been developed as the preferred treatment over percutaneous drainage and surgery for the management of PFC with DPDS. Many studies concerning various endoscopic treatment strategies have been published, especially in the recent 5 years. Nonetheless, existing current literature has reported inconsistent and confusing results. In this article, the latest evidence is summarized to explore the optimal endoscopic management of PFC with DPDS.