A survey of current practices in post-polypectomy surveillance in Korea.

BACKGROUND/AIMS: We investigated the clinical practice patterns of post-polypectomy colonoscopic surveillance among Korean endoscopists. METHODS: In a web-based survey conducted between September and November 2021, participants were asked about their preferred surveillance intervals and the patient age at which surveillance was discontinued. Adherence to the recent guidelines of the U.S. Multi-Society Task Force on Colorectal Cancer (USMSTF) was also analyzed. RESULTS: In total, 196 endoscopists completed the survey. The most preferred first surveillance intervals were: a 5-year interval after the removal of 1-2 tubular adenomas < 10 mm; a 3-year interval after the removal of 3-10 tubular adenomas < 10 mm, adenomas ≥ 10 mm, tubulovillous or villous adenomas, ≤ 20 hyperplastic polyps < 10 mm, 1-4 sessile serrated lesions (SSLs) < 10 mm, hyperplastic polyps or SSLs ≥ 10 mm, and traditional serrated adenomas; and a 1-year interval after the removal of adenomas with highgrade dysplasia, >10 adenomas, 5-10 SSLs, and SSLs with dysplasia. In piecemeal resections of large polyps ( > 20 mm), surveillance colonoscopy was mostly preferred after 1 year for adenomas and 6 months for SSLs. The mean USMSTF guideline adherence rate was 30.7%. The largest proportion of respondents (40.8%-55.1%) discontinued the surveillance at the patient age of 80-84 years. CONCLUSIONS: A significant discrepancy was observed between the preferred post-polypectomy surveillance intervals and recent international guidelines. Individualized measures are required to increase adherence to the guidelines.

Approaches and considerations in the endoscopic treatment of T1 colorectal cancer.

The detection of early colorectal cancer (CRC) is increasing through the implementation of screening programs. This increased detection enhances the likelihood of minimally invasive surgery and significantly lowers the risk of recurrence, thereby improving patient survival and reducing mortality rates. T1 CRC, the earliest stage, is treated endoscopically in cases with a low risk of lymph node metastasis (LNM). The advantages of endoscopic treatment compared with surgery include minimal invasiveness and limited tissue disruption, which reduce morbidity and mortality, preserve bowel function to avoid colectomy, accelerate recovery, and improve cost-effectiveness. However, T1 CRC has a risk of LNM. Thus, selection of the appropriate treatment between endoscopic treatment and surgery, while avoiding overtreatment, is challenging considering the potential for complete resection, LNM, and recurrence risk.

Application of clinical decision support tools for predicting outcomes with vedolizumab therapy in patients with inflammatory bowel disease: A KASID multicentre study.

BACKGROUND/AIM: We aimed to validate clinical decision support tools (CDSTs) to predict real-life effectiveness of vedolizumab (VDZ) in patients with inflammatory bowel disease. METHODS: We retrospectively enrolled patients with Crohn's disease (CD) or ulcerative colitis (UC) treated with VDZ at 10 tertiary referral centres in Korea between January 2017 and November 2021. We assessed clinical remission (CREM) and response (CRES), corticosteroid-free clinical remission (CSF-CREM) and response (CSF-CRES), biochemical response based on C-reactive protein (BioRES[CRP]) and faecal calprotectin (BioRES[FC]), endoscopic healing (EH), and the need to optimise or switch drugs based on CDST-defined response groups. Additionally, the area under the receiver operating characteristics curve (AUC) for the CDSTs was calculated. RESULTS: We included 143 patients with CD and 219 with UC. We observed incremental trends on CSF-CRES at week 14 (W14) (ptrend = 0.004) and decreasing trends for the need to optimise or switch drugs (ptrend = 0.016) in CD from the low to high probability groups. Except for CSF-CREM at W54, we noticed incremental trends for all clinical responses at W14, W26 and W54 (ptrend <0.001) in UC. W26 and W54 BioRES[CRP] and W14 EH also showed increasing trends (ptrend <0.05) in UC. With increasing probabilities of response, drug optimisation or switching was less frequently required in UC (ptrend = 0.013). With 26 points cut-off, CDSTs effectively identified W14 CSF-CRES, W26 BioRES[CRP], BioRES[FC] and W54 BioRES[CRP] in UC, all with AUCs >0.600, whereas CDSTs showed poor accuracy in CD. CONCLUSIONS: CDSTs for VDZ had acceptable accuracy in predicting effectiveness outcomes including clinical and biochemical outcomes in UC. However, their utility in CD was limited.

Design of Network-on-Chip-Based Restricted Coulomb Energy Neural Network Accelerator on FPGA Device.

Sensor applications in internet of things (IoT) systems, coupled with artificial intelligence (AI) technology, are becoming an increasingly significant part of modern life. For low-latency AI computation in IoT systems, there is a growing preference for edge-based computing over cloud-based alternatives. The restricted coulomb energy neural network (RCE-NN) is a machine learning algorithm well-suited for implementation on edge devices due to its simple learning and recognition scheme. In addition, because the RCE-NN generates neurons as needed, it is easy to adjust the network structure and learn additional data. Therefore, the RCE-NN can provide edge-based real-time processing for various sensor applications. However, previous RCE-NN accelerators have limited scalability when the number of neurons increases. In this paper, we propose a network-on-chip (NoC)-based RCE-NN accelerator and present the results of implementation on a field-programmable gate array (FPGA). NoC is an effective solution for managing massive interconnections. The proposed RCE-NN accelerator utilizes a hierarchical-star (H-star) topology, which efficiently handles a large number of neurons, along with routers specifically designed for the RCE-NN. These approaches result in only a slight decrease in the maximum operating frequency as the number of neurons increases. Consequently, the maximum operating frequency of the proposed RCE-NN accelerator with 512 neurons increased by 126.1% compared to a previous RCE-NN accelerator. This enhancement was verified with two datasets for gas and sign language recognition, achieving accelerations of up to 54.8% in learning time and up to 45.7% in recognition time. The NoC scheme of the proposed RCE-NN accelerator is an appropriate solution to ensure the scalability of the neural network while providing high-performance on-chip learning and recognition.

Efficacy, tolerability, and safety of oral sulfate tablet versus 2 L-polyethylene glycol/ascorbate for bowel preparation in older patients: prospective, multicenter, investigator single-blinded, randomized study.

BACKGROUND: We compared the efficacy, tolerability, and safety of oral sulfate tablets (OST, which contains simethicone) and 2 L-polyethylene glycol/ascorbate (2 L-PEG/Asc) with a split-dosing regimen in older individuals aged ≥ 70 years who underwent scheduled colonoscopy. METHODS: This prospective, randomized, investigator-blinded, multicenter study was conducted between June 2022 and October 2023. Participants aged ≥ 70 years were randomized at a ratio of 1:1 to the OST or 2 L-PEG/Asc groups. RESULTS: In total, 254 patients were evaluated using a modified full analysis set. Successful overall bowel preparation was excellent and similar between the OST and 2 L-PEG/Asc groups for the Boston Bowel Preparation Scale (BBPS) (96.5% vs. 96.6%) and Harefield Cleansing Scale (HCS) (96.5% vs. 97.4%). The overall high-quality preparation rate was higher in the OST group than in the 2 L-PEG/Asc group (BBPS: 55.7% vs. 28.4%, P < 0.001; HCS: 66.1% vs. 38.8%, P < 0.001). The overall adenoma detection rate (54.8% vs. 35.3, P = 0.003) was superior in the OST group compared to the 2 L-PEG/Asc group. Tolerability scores, including overall satisfaction, were generally higher in the OST group than in the 2 L-PEG/Asc group. The incidence of major solicited adverse events was comparable between the two groups (55.7% vs. 68.1, P = 0.051), and there were no clinically significant changes in the serum laboratory profiles on the day of or 7 days after colonoscopy. CONCLUSIONS: OST is an effective and safe low-volume agent for colonoscopy, with better tolerance than 2 L-PEG/Asc, in older individuals aged ≥ 70 years.

Hand Gesture Recognition Using FSK Radar Sensors.

Hand gesture recognition, which is one of the fields of human-computer interaction (HCI) research, extracts the user's pattern using sensors. Radio detection and ranging (RADAR) sensors are robust under severe environments and convenient to use for hand gestures. The existing studies mostly adopted continuous-wave (CW) radar, which only shows a good performance at a fixed distance, which is due to its limitation of not seeing the distance. This paper proposes a hand gesture recognition system that utilizes frequency-shift keying (FSK) radar, allowing for a recognition method that can work at the various distances between a radar sensor and a user. The proposed system adopts a convolutional neural network (CNN) model for the recognition. From the experimental results, the proposed recognition system covers the range from 30 cm to 180 cm and shows an accuracy of 93.67% over the entire range.

The Effect of Intervention for Improving Colonoscopy Quality Is Associated with the Personality Traits of Endoscopists.

Background/Aims: This study investigated whether the personality traits of endoscopists are associated with the effect of interventions for the improvement of colonoscopy quality. Methods: This prospective, multicenter, single-blind study was performed with 13 endoscopists in three health screening centers over a 12-month period. Quality indicators (QIs), including adenoma detection rate (ADR), polyp detection rate (PDR), and withdrawal time, were measured every 3 months. Consecutive interventions for the improvement of colonoscopy quality were conducted every 3 months, which included the personal notification of QIs, the in-group notification of QIs, and finally a targeted "quality education" session. The personality traits of each endoscopist were evaluated for perfectionism, fear of negative evaluation, and cognitive flexibility after the last QI assessment. Results: A total of 4,095 colonoscopies were evaluated to measure the QIs of the individual endoscopists for 12 months. The mean ADR, PDR, and withdrawal time of the 13 endoscopists were 32.3%, 47.7%, and 394 seconds at baseline and increased to 39.0%, 55.1%, and 430 seconds by the end of the study (p=0.003, p=0.006, and p=0.004, respectively). Among the three interventions, only quality education significantly improved QIs: ADR, 36.0% to 39.0% (odds ratio, 1.28; 95% confidence interval, 1.01 to 1.63). The improvement of ADR and PDR by education was significantly associated with perfectionism (r=0.617, p=0.033 and r=0.635, p=0.027, respectively) and fear of negative evaluation (r=0.704, p=0.011 and r=0.761, p=0.004, respectively). Conclusions: Education can improve colonoscopy quality, and its effect size is associated with an endoscopist's personal traits such as perfectionism and fear of negative evaluation (Clinical-Trials.gov Registry NCT03796169).

Is colorectal endoscopic submucosal dissection safe and effective for 15-19-mm tumors?

PURPOSE: The outcomes of colorectal endoscopic submucosal dissection (ESD) in 15-19-mm tumors are unclear. This study compared the effectiveness and safety of colorectal ESD for 15-19-mm tumors and tumors exceeding that size. METHODS: From August 2018 to December 2020, 213 cases of colorectal tumors removed by colorectal ESD at a tertiary hospital were enrolled in this study. The cases were divided into two groups according to the pathologically measured size of the resected lesion: an intermediate group (15-19 mm, n = 62) and a large group (≥ 20 mm, n = 151). The en bloc resection rate, complete resection rate, and complications were investigated retrospectively. RESULTS: The en bloc resection rate was significantly higher in the intermediate than large group (100% vs. 94%, p = 0.049), and the mean total procedure time was shorter in the intermediate than large group (29.2 [Formula: see text] 12.6 vs. 48.4 [Formula: see text] 28.8 min, p < 0.001). However, the mean procedure speed was significantly lower in the intermediate than large group (0.25 [Formula: see text] 0.10 vs. 0.28 [Formula: see text] 0.11 cm2/min, p = 0.031). The complete resection rate, post-procedural bleeding, and perforation rate were not significantly different between the two groups. In multivariate analyses, the total procedure time and mean procedure speed were significantly associated with lesion size. CONCLUSION: Colorectal ESD of 15-19-mm lesions is effective, and has a shorter procedure time and higher en bloc resection rate than the same procedure for larger lesions.

FPGA Implementation of Keyword Spotting System Using Depthwise Separable Binarized and Ternarized Neural Networks.

Keyword spotting (KWS) systems are used for human-machine communications in various applications. In many cases, KWS involves a combination of wake-up-word (WUW) recognition for device activation and voice command classification tasks. These tasks present a challenge for embedded systems due to the complexity of deep learning algorithms and the need for optimized networks for each application. In this paper, we propose a depthwise separable binarized/ternarized neural network (DS-BTNN) hardware accelerator capable of performing both WUW recognition and command classification on a single device. The design achieves significant area efficiency by redundantly utilizing bitwise operators in the computation of the binarized neural network (BNN) and ternary neural network (TNN). In a complementary metal-oxide semiconductor (CMOS) 40 nm process environment, the DS-BTNN accelerator demonstrated significant efficiency. Compared with a design approach where BNN and TNN were independently developed and subsequently integrated as two separate modules into the system, our method achieved a 49.3% area reduction while yielding an area of 0.558 mm2. The designed KWS system, which was implemented on a Xilinx UltraScale+ ZCU104 field-programmable gate array (FPGA) board, receives real-time data from the microphone, preprocesses them into a mel spectrogram, and uses this as input to the classifier. Depending on the order, the network operates as a BNN or a TNN for WUW recognition and command classification, respectively. Operating at 170 MHz, our system achieved 97.1% accuracy in BNN-based WUW recognition and 90.5% in TNN-based command classification.

sEMG-Based Hand Gesture Recognition Using Binarized Neural Network.

Recently, human-machine interfaces (HMI) that make life convenient have been studied in many fields. In particular, a hand gesture recognition (HGR) system, which can be implemented as a wearable system, has the advantage that users can easily and intuitively control the device. Among the various sensors used in the HGR system, the surface electromyography (sEMG) sensor is independent of the acquisition environment, easy to wear, and requires a small amount of data. Focusing on these advantages, previous sEMG-based HGR systems used several sensors or complex deep-learning algorithms to achieve high classification accuracy. However, systems that use multiple sensors are bulky, and embedded platforms with complex deep-learning algorithms are difficult to implement. To overcome these limitations, we propose an HGR system using a binarized neural network (BNN), a lightweight convolutional neural network (CNN), with one dry-type sEMG sensor, which is implemented on a field-programmable gate array (FPGA). The proposed HGR system classifies nine dynamic gestures that can be useful in real life rather than static gestures that can be classified relatively easily. Raw sEMG data collected from a dynamic gesture are converted into a spectrogram with information in the time-frequency domain and transferred to the classifier. As a result, the proposed HGR system achieved 95.4% classification accuracy, with a computation time of 14.1 ms and a power consumption of 91.81 mW.

Korean Guidelines for Postpolypectomy Colonoscopic Surveillance: 2022 revised edition.

Colonoscopic polypectomy is effective in decreasing the incidence and mortality of colorectal cancer (CRC). Premalignant polyps discovered during colonoscopy are associated with the risk of metachronous advanced neoplasia. Postpolypectomy surveillance is the most important method for managing advanced metachronous neoplasia. A more efficient and evidence-based guideline for postpolypectomy surveillance is required because of the limited medical resources and concerns regarding colonoscopy complications. In these consensus guidelines, an analytic approach was used to address all reliable evidence to interpret the predictors of CRC or advanced neoplasia during surveillance colonoscopy. The key recommendations state that the high-risk findings for metachronous CRC following polypectomy are as follows: adenoma ≥10 mm in size; 3 to 5 (or more) adenomas; tubulovillous or villous adenoma; adenoma containing high-grade dysplasia; traditional serrated adenoma; sessile serrated lesion containing any grade of dysplasia; serrated polyp of at least 10 mm in size; and 3 to 5 (or more) sessile serrated lesions. More studies are needed to fully comprehend the patients who are most likely to benefit from surveillance colonoscopy and the ideal surveillance interval to prevent metachronous CRC.

FPGA Implementation of Efficient CFAR Algorithm for Radar Systems.

The constant false-alarm rate (CFAR) algorithm is essential for detecting targets during radar signal processing. It has been improved to accurately detect targets, especially in nonhomogeneous environments, such as multitarget or clutter edge environments. For example, there are sort-based and variable index-based algorithms. However, these algorithms require large amounts of computation, making them difficult to apply in radar applications that require real-time target detection. We propose a new CFAR algorithm that determines the environment of a received signal through a new decision criterion and applies the optimal CFAR algorithms such as the modified variable index (MVI) and automatic censored cell averaging-based ordered data variability (ACCA-ODV). The Monte Carlo simulation results of the proposed CFAR algorithm showed a high detection probability of 93.8% in homogeneous and nonhomogeneous environments based on an SNR of 25 dB. In addition, this paper presents the hardware design, field-programmable gate array (FPGA)-based implementation, and verification results for the practical application of the proposed algorithm. We reduced the hardware complexity by time-sharing sum and square operations and by replacing division operations with multiplication operations when calculating decision parameters. We also developed a low-complexity and high-speed sorter architecture that performs sorting for the partial data in leading and lagging windows. As a result, the implementation used 8260 LUTs and 3823 registers and took 0.6 µs to operate. Compared with the previously proposed FPGA implementation results, it is confirmed that the complexity and operation speed of the proposed CFAR processor are very suitable for real-time implementation.

FPGA Implementation of the Chirp-Scaling Algorithm for Real-Time Synthetic Aperture Radar Imaging.

Synthetic aperture radar (SAR), which can generate images of regions or objects, is an important research area of radar. The chirp scaling algorithm (CSA) is a representative SAR imaging algorithm. The CSA has a simple structure comprising phase compensation and fast Fourier transform (FFT) operations by replacing interpolation for range cell migration correction (RCMC) with phase compensation. However, real-time processing still requires many computations and a long execution time. Therefore, it is necessary to develop a hardware accelerator to improve the speed of algorithm processing. In addition, the demand for a small SAR system that can be mounted on a small aircraft or drone and that satisfies the constraints of area and power consumption is increasing. In this study, we proposed a CSA-based SAR processor that supports FFT and phase compensation operations and presents field-programmable gate array (FPGA)-based implementation results. We also proposed a modified CSA flow that simplifies the traditional CSA flow by changing the order in which the transpose operation occurs. Therefore, the proposed CSA-based SAR processor was designed to be suitable for modified CSA flow. We designed the multiplier for FFT to be shared for phase compensation, thereby achieving area efficiency and simplifying the data flow. The proposed CSA-based SAR processor was implemented on a Xilinx UltraScale+ MPSoC FPGA device and designed using Verilog-HDL. After comparing the execution times of the proposed SAR processor and the ARM cortex-A53 microprocessor, we observed a 136.2-fold increase in speed for the 4096 × 4096-pixel image.

FMCW Radar Sensors with Improved Range Precision by Reusing the Neural Network.

This paper addresses the challenge of enhancing range precision in radar sensors through supervised learning. However, when the range precision surpasses the range resolution, it leads to a rapid increase in the number of labels, resulting in elevated learning costs. The removal of background noise in indoor environments is also crucial. In response, this study proposes a methodology aiming to increase range precision while mitigating the issue of a growing number of labels in supervised learning. Neural networks learned for a specific section are reused to minimize learning costs and maximize computational efficiency. Formulas and experiments confirmed that identical fractional multiple patterns in the frequency domain can be applied to analyze patterns in other FFT bin positions (representing different target positions). In conclusion, the results suggest that neural networks trained with the same data can be repurposed, enabling efficient hardware implementation.

Method for Improving Range Resolution of Indoor FMCW Radar Systems Using DNN.

Various studies on object detection are being conducted, and in this regard, research on frequency-modulated continuous wave (FMCW) RADAR is being actively conducted. FMCW RADAR requires high-distance resolution to accurately detect objects. However, if the distance resolution is high, a high-modulation bandwidth is required, which has a prohibitively high cost. To address this issue, we propose a two-step algorithm to detect the location of an object through DNN using many low-cost FMCW RADARs. The algorithm first infers the sector by measuring the distance to the object for each FMCW RADAR and then measures the position through the grid according to the inferred sector. This improves the distance resolution beyond the modulation bandwidth. Additionally, to detect multiple targets, we propose a Gaussian filter. Multiple targets are detected through an ordered-statistic constant false-alarm rate (OS-CFAR), and there is an 11% probability that multiple targets cannot be detected. In the lattice structure proposed in this paper, the performance of the proposed algorithm compared to those in existing works was confirmed with respect to the cost function. The difference in performance versus complexity was also confirmed when the proposed algorithm had the same complexity and the same performance, and it was confirmed that there was a performance improvement of up to five-fold compared to those in previous papers. In addition, multi-target detection was shown in this paper. Through MATLAB simulation and actual measurement on a single target, RMSEs were 0.3542 and 0.41002 m, respectively, and through MATLAB simulation and actual measurement on multiple targets, RMSEs were confirmed to be 0.548265 and 0.762542 m, respectively. Through this, it was confirmed that this algorithm works in real RADAR.

Korean guidelines for postpolypectomy colonoscopic surveillance: 2022 revised edition.

Colonoscopic polypectomy is effective in decreasing the incidence and mortality of colorectal cancer (CRC). Premalignant polyps discovered during colonoscopy are associated with the risk of metachronous advanced neoplasia. Postpolypectomy surveillance is the most important method for the management of advanced metachronous neoplasia. A more efficient and evidence-based guideline for postpolypectomy surveillance is required because of limited medical resources and concerns regarding colonoscopy complications. In these consensus guidelines, an analytic approach was used to address all reliable evidence to interpret the predictors of CRC or advanced neoplasia during surveillance colonoscopy. The key recommendations state that the high-risk findings for metachronous CRC following polypectomy are as follows: (1) adenoma ≥10 mm in size; (2) 3 to 5 (or more) adenomas; (3) tubulovillous or villous adenoma; (4) adenoma containing high-grade dysplasia; (5) traditional serrated adenoma; (6) sessile serrated lesion (SSL) containing any grade of dysplasia; (7) serrated polyp of at least 10 mm in size; and (8) 3 to 5 (or more) SSLs. More studies are needed to fully comprehend the patients most likely to benefit from surveillance colonoscopy and the ideal surveillance interval to prevent metachronous CRC.

[Korean Guidelines for Postpolypectomy Colonoscopic Surveillance: 2022 Revised Edition].

Colonoscopic polypectomy is effective in decreasing the incidence and mortality of colorectal cancer (CRC). Premalignant polyps discovered during colonoscopy are associated with the risk of metachronous advanced neoplasia. Postpolypectomy surveillance is the most important method for managing advanced metachronous neoplasia. A more efficient and evidence-based guideline for postpolypectomy surveillance is required because of the limited medical resources and concerns regarding colonoscopy complications. In these consensus guidelines, an analytic approach was used to address all reliable evidence to interpret the predictors of CRC or advanced neoplasia during surveillance colonoscopy. The key recommendations state that the high-risk findings for metachronous CRC following polypectomy are as follows: 1) adenoma ≥10 mm in size; 2) 3-5 (or more) adenomas; 3) tubulovillous or villous adenoma; 4) adenoma containing high-grade dysplasia; 5) traditional serrated adenoma; 6) sessile serrated lesion (SSL) containing any grade of dysplasia; 7) serrated polyp of at least 10 mm in size; and 8) 3-5 (or more) SSLs. More studies are needed to fully comprehend the patients who are most likely to benefit from surveillance colonoscopy and the ideal surveillance interval to prevent metachronous CRC.

Evaluation of the efficacy of 1 L polyethylene glycol plus ascorbic acid and an oral sodium sulfate solution: A multi-center, prospective randomized controlled trial.

INTRODUCTION: Low-volume bowel preparation has been developed to increase patient compliance. We compared 1 L of polyethylene glycol/ascorbic acid (PEG/Asc) and oral sodium sulfate (OSS) with respect to bowel preparation efficacy, compliance, and safety. METHODS: A multicenter, prospective, randomized, single-blinded, non-inferiority trial was conducted in 3 hospitals. Patients were randomized to receive a bowel-cleansing agent. Bowel-cleansing efficacy was evaluated using the Boston Bowel Preparation Scale (BBPS). Satisfaction, feeling, taste of the bowel cleanser, and adverse events after taking the bowel cleanser were investigated through a questionnaire. Additionally, blood samples were analyzed before and after bowel cleansing. RESULTS: In total, 172 patients were analyzed (85 with 1 L PEG/Asc and 87 with OSS), and the mean BBPS scores were comparable between agents. The 1L PEG/Asc group tended to have a higher BBPS score in the right colon (2.22 vs 2.02; P = .08). The compliance of 1 L of PEG/Asc was comparable to that of OSS. Patients taking 1 L PEG/Asc reported greater thirst and dizziness (P = .04 and P = .047, respectively) than the OSS cohort. On the other hand, gastrointestinal symptoms such as vomiting and abdominal distension were more common in the OSS group, without statistical significance. In terms of laboratory adverse events, elevation of serum creatinine was found in both groups after taking the bowel cleansing agent (P < .001 for the 1L PEG/Asc group; P = .04 for the OSS group). However, most of the increased values were within the normal ranges. DISCUSSION: The 1L PEG/Asc treatment was comparable to OSS in terms of bowel preparation efficacy, compliance, and safety.

The Common and Unique Pattern of Microbiome Profiles among Saliva, Tissue, and Stool Samples in Patients with Crohn's Disease.

This study aimed to elucidate common and unique microbiome patterns in saliva, intestinal tissue biopsy, and stool samples from patients with Crohn's disease (CD). Saliva, tissue, and stool samples from patients with CD were prospectively collected. Quantitative and phylogenetic analyses of 16s rRNA sequencing data were performed with bioinformatical pipelines. A total of 30 patients were enrolled in this study. The composition of major microbial taxa was similar between tissue and stool samples. A total of 11 of the 20 most abundant microbiota were found in both samples. The microbial community in saliva was significantly distinct from that in tissue and stool. The major species of microbiota and their composition also differed significantly from those of tissue and stool samples. However, Streptococcus and Prevotella are common genera in saliva, tissue, and stool microbiome. The abundance of Streptococcus, Pantoea, and Actinomyces from the saliva sample group were significantly different, varying with the location of the inflammation. Saliva has a distinct microbial community compared with tissues and stools in patients with CD. Prevotella and Streptococcus, which are commonly observed in saliva, stool, and tissue, can be considered a potential biomarker related to the diagnosis or prognosis of CD.