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Preoperative determination of lymph node (LN) status is crucial in treatment planning for rectal cancer. This study prospectively evaluated the risk factors for lymph node metastasis (LNM) at staging and restaging based on a node-by-node pairing between MRI imaging findings and histopathology and constructed nomograms to evaluate its diagnostic value.From July 2021 to July 2022, patients with histopathologically verified rectal cancer who underwent MRI before surgery were prospectively enrolled. Histological examination of each LN status in the surgical specimens and anatomical matching with preoperative imaging. Taking histopathological results as the gold standard, federating clinical features from patients and LN imaging features on MRI-T2WI. Risk factors for LN metastasis were identified by multivariate logistic regression analysis and used to create a nomogram. The performance of the nomograms was assessed with calibration plots and bootstrapped-concordance index and validated using validation cohorts.A total of 500 target LNs in 120 patients were successfully matched with node-by-node comparisons. A total of 353 LNs did not receive neoadjuvant therapy and 147 LNs received neoadjuvant chemoradiotherapy (neoCRT). Characterization of LNs not receiving neoadjuvant therapy and multivariate regression showed that the short diameter, preoperative CEA level, mrT-stage, border contour, and signal intensity were associated with a high risk of LN metastasis (P 0.05). The nomogram predicted that the area under the curve was 0.855 (95% CI, 0.794-0.916) and 0.854 (95% CI, 0.727-0.980) in the training and validation cohorts, respectively. In the neoadjuvant therapy group, short diameter, ymrT-stage, internal signal, and MRI-EMVI were associated with LN positivity (P 0.05), and the area under the curves using the nomogram was 0.912 (95% CI, 0.856-0.968) and 0.915 (95% CI, 0.817-1.000) in two cohorts. The calibration curves demonstrate good agreement between the predicted and actual probabilities for both the training and validation cohorts.Our nomograms combined with preoperative clinical and imaging biomarkers have the potential to improve the prediction of nodal involvement, which can be used as an essential reference for preoperative N staging and restaging of rectal cancer.

Recently, serum exosomal circular RNAs (circRNAs) were applied to discriminate cancer patients from healthy individuals, indicating that exosomal circRNAs have the potential to be novel biomarkers for cancer diagnosis. This study aims to summarize the role of exosomal circRNAs in cancer diagnosis by a meta-analysis.A comprehensive literature search was conducted up to July 2021 in PubMed, Web of Science, EMBASE, and Cochrane Database. To evaluate the diagnostic value, the sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) were pooled. Threshold effect followed by subgroup analysis and meta-regression were performed to explore the source of heterogeneity. Sensitivity analysis was performed to assess the stability of this meta-analysis model. Fagan plots and likelihood ratio scattergrams were used to explore the potential clinical significance.Ten eligible studies with 514 controls and 557 patients were included in this diagnostic meta-analysis. The pooled sensitivity, specificity, PLR, NLR, and DOR were 0.75 (95% CI: 0.65-0.83), 0.84 (95% CI, 0.78-0.89), 5.87 (95% CI, 3.67-9.38), 0.28 (95% CI, 0.19-0.40), and 21.15 (95% CI, 10.25-43.68), respectively. The AUC was 0.89 (95% CI, 0.86-0.91). Sensitivity analysis showed that four studies had an impact on the pooled results and mainly contributed to the heterogeneity. Fagan's nomogram revealed that the prior probability of 20%, the post probability positive, the post probability negative were 59% and 6%, respectively.Our results suggested that exosomal circRNAs might serve as powerful biomarkers in detecting cancers with high sensitivity and specificity. However, more well-designed and multicenter diagnostic tests are needed to validate our results.

Background The effects of body mass index (BMI) in patients with rectal cancer have been poorly studied and are still controversial. In this study, we aimed to assess the effect of BMI on the long-term outcome in patients with rectal cancer after radical surgery. Materials and methods Between April 2012 and December 2020, patients who received total mesorectal excision (TME) surgery were enrolled in the study. Patients were divided into four groups according to BMI level. Kaplan–Meier survival curves with log-rank tests were used to analyze overall survival (OS), Disease-free survival (DFS), local recurrence-free survival and distant metastasis-free survival. Univariate and multivariate analyses were performed to identify the risk factors associated with the long-term outcome. Nomograms were developed to predict the OS and DFS based on independent prognostic factors. Results A total of 688 patients were included in this study. The median follow-up time was 69 months. The 5-year OS rates of the control, underweight, overweight and obese groups were 79.2%, 62.2%, 88.7% and 86.3%, respectively. The 5-year DFS rates were 74.8%, 58.2%, 80.5% and 81.4%, respectively. Overweight (HR 0.534; 95% CI 0.332–0.860, p = 0.010) was an independent protective factor for OS and DFS (HR 0.675; 95% CI 0.461–0.989, p = 0.044). Underweight was an independent risk factor for DFS (HR = 1.623; 95% CI 1.034–2.548; p = 0.035), and had a trend to be an independent risk factor for OS (HR 1.594; 95% 0.954–2.663; p = 0.075). Nomograms were established to predict the 2-year OS, 5-year OS, 2-year DFS and 5-year DFS with an area under curve (AUC) of 0.767, 0.712, 0.746 and 0.734, respectively. Conclusions For rectal cancer patients after radical surgery, overweight was an independent protective factor for OS and DFS. Underweight was an independent risk factor for DFS and had a trend to be an independent risk factor for OS. Nomograms incorporating BMI and other prognostic factors could be helpful to predict long-term outcome.

BACKGROUND This study aimed to evaluate the perioperative, pathological and oncological outcomes of open versus laparoscopic total mesorectal excision (TME) plus lateral lymph node dissection (LLND) for mid- and low- rectal cancer using propensity score matching. METHODS Between September 2009 and December 2018, consecutive patients who underwent open or laparoscopic TME plus LLND were collected. Based on the propensity score matching analysis, laparoscopic TME plus LLND was compared with open TME plus LLND for the perioperative, pathological, and oncological outcomes. RESULTS A total of 77 patients were collected. There were 13 patients who underwent open TME plus LLND (open group) and 64 patients who underwent laparoscopic TME plus LLND (laparoscopic group). After propensity score matching, 13 patients in the open group were matched to 39 patients in the laparoscopic group (1:3). The laparoscopic group had a significantly shorter length of incision (5 cm vs. 20 cm, p

Lymph node status is critical for staging rectal cancer and determining neoadjuvant therapy regimens. Establishing a matching between imaging and histopathological lymph nodes is fundamental for predicting lymph node status. This study reports a technique to achieve node-by-node pairing of mesorectal lymph nodes between imaging findings and histopathology.Fifty-two patients with histopathologically verified rectal cancer underwent magnetic resonance imaging before surgery. The status of each lymph node in the surgical specimens was analyzed histopathologically and matched with preoperative imaging after the operation.A total of 346 mesorectal lymph nodes were located on imaging evaluation, of which 313 were confirmed histopathologically, and 33 were unmatched. The total success rate of the technique was 90.5%. Node-by-node analysis revealed 280 benign and 33 malignant nodal structures.The technique to match mesorectal lymph node imaging findings to histopathology was feasible and effective. It simplified the technical method and had a reasonable success matching rate, which could provide a standardized approach for obtaining a prospective correlation between imaging and histological findings, supporting all subsequent related studies at the level of mesorectal lymph nodes.

Tremendous progress has been made in the field of lateral lymph nodes (LLNs) in rectal cancer, but no bibliometric analysis in this field has been carried out and published. To reveal the current status and trends in LLNs in rectal cancer, this bibliometric analysis was performed. Cooperation network, co-citation and keyword co-occurrence analyses were conducted. Annual publication, cooperation relationships among authors, institutions and countries, co-cited journal, co-cited author, co-cited reference and keywords were the main outcomes. A total of 345 studies were included in this bibliometric analysis. The number of articles published in this field has been increasing year by year. The authors, institutions and countries worked closely together in this field. Japan has the largest number of published articles, accounting for 51.59% of the total publications. International Journal of Colorectal Disease (30 papers, 8.70%) published the most papers in this field. The JCOG0212 trial was the most cited article. Preoperative chemoradiotherapy, multicenter, lateral lymph node dissection (LLND) and metastasis are recent hot keywords, and LLND had the highest burst strength. In conclusion, this bibliometric analysis found that Japanese institutions and authors dominated the field of LLNs in rectal cancer. The JCOG0212 trial was the most influential article, which had a significant impact on the development of guidelines. LLND is a hotspot in this field with the highest burst strength. Further prospective studies are needed in this field.

Colorectal cancer (CRC) is one of the most common malignant tumors in the world. CRC recurrence and metastasis cause poor prognosis. ANGPTLs (angiopoietin-like proteins) are a family of proteins that are widely involved in metabolic disease and tumorigenesis. The roles of ANGPTLs in CRC are still controversial and deserve further research. In this study, several databases were employed to explore the expression profiles, prognostic values, genetic alterations, potential biological function, and immune infiltration correlation of ANGPTLs in CRC. The expression of ANGPTL4 was significantly positively correlated with the stage of CRC. Therefore, cell and molecular experiments were further performed to explore the roles of ANGPTL4. Our results showed that the transcriptions of ANGPTLs in colon cancer and rectal cancer tissues were lower than those in normal tissues, but the protein expression varied among different ANGPTLs. In addition, the high expression of ANGPTLs led to a relatively poor oncological outcome. Specifically, the expression of ANGPTL4 is significantly positively correlated with the stage of CRC. Further investigation revealed that ANGPTLs are mainly involved in signal transduction and the regulation of transcription, while KEGG pathway analyses demonstrated pathways in cancer. Additionally, we also observed that ANGPTL4 could promote the proliferation and migration of CRC cells, and four specific small molecule compounds had potential ANGPTL4-binding capabilities, suggesting the clinical application of these small molecule compounds on CRC treatment. Our findings imply the prognostic values and potential therapeutic targets of ANGPTLs in CRC.

Localized inflammatory lesions in one area of the body may affect other distant organs through various modes of transmission thus initiating secondary inflammatory infections. Periodontal disease (PD) and inflammatory bowel disease (IBD) have been shown to coexist. Periodontitis is a multifactorial inflammatory disease, and dental plaque is considered to be the initial risk factor. Individuals with genetic susceptibility are more likely to develop periodontitis when exposed to external stimuli. IBD is affected by host genetics, immunoregulation, daily diet, and the gut microbiota, and its risk factors appear to be shared with those of PD. However, the key etiologies of both diseases remain unclear, thus hindering the exploration of possible links between IBD and PD. Recent studies and systematic reviews have focused on evidence-based statistics of the prevalence and clinical manifestations of both diseases, but discussions of the microbial etiological correlation between periodontitis and intestinal inflammation are scarce. Here, we summarize the potential common pathogenic microorganisms that may serve as bridges between the two diseases. Studies have shown that invasive microorganisms such asPorphyromonas gingivalis, Fusobacterium nucleatum, Klebsiellaspp. andCampylobacterspp. play key roles in the comorbidity of PD and IBD.

Antijoin cardinality estimation is among a handful of problems that has eluded accurate efficient solutions amenable to implementation in relational query optimizers. Given the widespread use of antijoin and subset-based queries in analytical workloads and the extensive research targeted at join cardinality estimation—a seemingly related problem—the lack of adequate solutions for antijoin cardinality estimation is intriguing. In this article, we introduce a novel sampling-based estimator for antijoin cardinality that (unlike existent estimators) provides sufficient accuracy and efficiency to be implemented in a query optimizer. The proposed estimator incorporates three novel ideas. First, we use prior workload information when learning a mixture superpopulation model of the data offline. Second, we design a Bayesian statistics framework that updates the superpopulation model according to the live queries, thus allowing the estimator to adapt dynamically to the online workload. Third, we develop an efficient algorithm for sampling from a hypergeometric distribution in order to generate Monte Carlo trials , without explicitly instantiating either the population or the sample. When put together, these ideas form the basis of an efficient antijoin cardinality estimator satisfying the strict requirements of a query optimizer, as shown by the extensive experimental results over synthetically-generated as well as massive TPC-H data.

Web crawlers work on the behalf of applications or services to find interesting and related information on the web. For example, search engines use web crawlers to index the Internet. Web crawlers have several challenges, such as complexity between links and highly intensive computation requirements when a web crawler wants to retrieve complex connected links. Another issue is the storage of a massive amount of indexed links or downloaded unstructured data, such as binary files, videos or images. As the volume of information on the Internet increases rapidly and requests may search data in a variety of formats including unstructured data, no cloud-based architecture exists in the literatures for web crawlers that could effectively address both highly intensive computing and storage issues. The cloud computing paradigm provides support for elastic resources and unstructured data, and provides pay-peruse features that allow individual businesses to run their own web crawlers for crawling the Internet or a limited web hosts. In this paper, we propose a cloud-based web crawler architecture that uses cloud computing features and the MapReduce programming technique. The proposed web crawler allows us to crawl the web by using distributed agents and each agent stores its own finding on a Cloud Azure Table (NoSQL database). The proposed web crawler also could store unstructured and massive amount of data on Azure Blob storage. We analyze the performance and scalability of the proposed web crawler and we describe the advantages of the proposed web crawler over traditional distributed web crawlers.