UCFNNet: Ulcerative colitis evaluation based on fine-grained lesion learner and noise suppression gating.

BACKGROUND AND OBJECTIVE: Ulcerative colitis (UC) is a chronic disease characterized by recurrent symptoms and significant morbidity. The exact cause of the disease remains unknown. The selection of current treatment options for ulcerative colitis depends on the severity and location of the disease in each patient. Therefore, developing a fully automated endoscopic images for evaluating UC is crucial for guiding treatment plans and facilitating early prevention efforts. METHODS: We propose a network called ulcerative colitis evaluation based on fine-grained lesion learner and noise suppression gating (UCFNNet). UCFNNet contains three novel modules. Firstly, a fine-grained lesion feature learner (FG-LF Learner) is proposed by integrating local features and a Softmax category prediction (SCP) module to improve the feature accuracy in small lesion areas. Subsequently, a graph convolutional feature combiner (GCFC) is developed to connect features across adjacent convolutional layers and to incorporate short connections between input and output, thereby mitigating feature loss during transmission. Thereafter, a noise suppression gating (NS gating) technique is designed by implementing a grid attention mechanism and a feature gating (FG) module to prioritize significant lesion features and suppress irrelevant and noisy regions in the input feature map. RESULTS: We evaluate the performance of the proposed network on both privately-collected and publicly-available datasets. The evaluation of UC achieves excellent results on privately-collected dataset, with an accuracy (ACC) of 89.57 %, Matthews correlation coefficient (MCC) of 85.52 %, precision of 89.26 %, recall of 89.48 %, and F1-score of 89.78 %. The results are also impressive on publicly-available dataset, with ACC of 85.47 %, MCC of 80.42 %, precision of 85.62 %, recall of 84.00 %, and F1-score of 84.53 %, surpassing the performance of state-of-the-art techniques. CONCLUSION: Our proposed model introduces three innovative algorithm modules, which outperform the current state-of-the-art methods and achieve high ACC and F1-score. This indicates that our method has superior performance compared to traditional machine learning and existing deep methods, which means that our method has good application prospects. Meanwhile, it has been verified that the proposed model demonstrates good interpretability. The source code is available at github.com/YinLeRenNB/UCFNNet.

Artificial intelligence-based diagnosis of standard endoscopic ultrasonography scanning sites in the biliopancreatic system: a multicenter retrospective study.

BACKGROUND: There are challenges for beginners to identify standard biliopancreatic system anatomical sites on endoscopic ultrasonography (EUS) images. Therefore, the authors aimed to develop a convolutional neural network (CNN)-based model to identify standard biliopancreatic system anatomical sites on EUS images. METHODS: The standard anatomical structures of the gastric and duodenal regions observed by EUS was divided into 14 sites. The authors used 6230 EUS images with standard anatomical sites selected from 1812 patients to train the CNN model, and then tested its diagnostic performance both in internal and external validations. Internal validation set tests were performed on 1569 EUS images of 47 patients from two centers. Externally validated datasets were retrospectively collected from 16 centers, and finally 131 patients with 85 322 EUS images were included. In the external validation, all EUS images were read by CNN model, beginners, and experts, respectively. The final decision made by the experts was considered as the gold standard, and the diagnostic performance between CNN model and beginners were compared. RESULTS: In the internal test cohort, the accuracy of CNN model was 92.1-100.0% for 14 standard anatomical sites. In the external test cohort, the sensitivity and specificity of CNN model were 89.45-99.92% and 93.35-99.79%, respectively. Compared with beginners, CNN model had higher sensitivity and specificity for 11 sites, and was in good agreement with the experts (Kappa values 0.84-0.98). CONCLUSIONS: The authors developed a CNN-based model to automatically identify standard anatomical sites on EUS images with excellent diagnostic performance, which may serve as a potentially powerful auxiliary tool in future clinical practice.

Application of deep learning in the diagnosis and evaluation of ulcerative colitis disease severity.

Background: Achieving endoscopic and histological remission is a critical treatment objective in ulcerative colitis (UC). Nevertheless, interobserver variability can significantly impact overall assessment performance. Objectives: We aimed to develop a deep learning algorithm for the real-time and objective evaluation of endoscopic disease activity and prediction of histological remission in UC. Design: This is a retrospective diagnostic study. Methods: Two convolutional neural network (CNN) models were constructed and trained using 12,257 endoscopic images and biopsy results sourced from 1124 UC patients who underwent colonoscopy at a single center from January 2018 to December 2022. Mayo Endoscopy Subscore (MES) and UC Endoscopic Index of Severity Score (UCEIS) assessments were conducted by two experienced and independent reviewers. Model performance was evaluated in terms of accuracy, sensitivity, and positive predictive value. The output of the CNN models was also compared with the corresponding histological results to assess histological remission prediction performance. Results: The MES-CNN model achieved 97.04% accuracy in diagnosing endoscopic remission of UC, while the MES-CNN and UCEIS-CNN models achieved 90.15% and 85.29% accuracy, respectively, in evaluating endoscopic severity of UC. For predicting histological remission, the CNN models achieved accuracy and kappa values of 91.28% and 0.826, respectively, attaining higher accuracy than human endoscopists (87.69%). Conclusion: The proposed artificial intelligence model, based on MES and UCEIS evaluations from expert gastroenterologists, offered precise assessment of inflammation in UC endoscopic images and reliably predicted histological remission.

Application of deep learning in the diagnosis and evaluation of ulcerative colitis disease severity Why was this study done? This study aimed to develop a real-time and objective diagnostic tool to reduce subjectivity when evaluating ulcerative colitis (UC) endoscopic disease activity and to predict histological remission without mucosal biopsy. What did the researchers do? We developed and validated a deep learning algorithm that uses UC endoscopic images to predict the Mayo Endoscopic Score (MES), US Endoscopic Index of Severity Score (UCEIS), and histological remission. What did the researchers find? The constructed MES- and UCEIS-based models both achieved high accuracy and performance in predicting histological remission, outperforming human endoscopists. What do the findings mean? The efficiency and performance of the deep learning algorithm rivaled that of expert assessments, which may assist endoscopists in making more objective evaluations of UC severity and in predicting histological remission.

MCE-Net: polyp segmentation with multiple branch series-parallel attention and channel interaction via edge distribution guidance.

Objective.Accurate polyp segmentation is vital for diagnosing colorectal cancer. However, it is still challenging for accurate polyp segmentation and several bottlenecks exist, such as incomplete boundary, localization bias and lack of micro blocks along with large fragmented boundaries in uncertain regions.Approach.To address the above issues, a novel polyp segmentation network with multiple branch series-parallel attention (MBSA) and channel interaction via edge distribution guidance is proposed. Initially, the edge distribution guidance strategy is proposed to generate the edge distribution following Cauchy distribution to capture complementary edges with sufficient details. Subsequently, a MBSA module is put forward to extract features from various receptive fields to pinpoint tiny polyps by a multiple kernel dilated convolution block, while combining semantics of different dimensions to filter out noise and refining the details of micro target. Ultimately, the channel interaction model is proposed to improve the segmentation accuracy of the polyps in uncertain area by splitting channels into groups and conducts group-wise interaction to excavate subtle clues contained in different channels.Main results.Extensive experimental results demonstrate that the proposed method is superior over the state-of-the-art methods with the mean dice of 0.8972, 0.9420, 0.8312, 0.8064 and 0.9214 on five public polyp datasets.Significance.The proposed method improves the integrity of the margins and internal details for polyp segmentation, which will provide a powerful aid for doctors to achieve accurate judgments, reducing the likelihood of colorectal cancer and improving the survival chances of patients.

Alterations in metabolome and microbiome signatures provide clues to the role of antimicrobial peptide KT2 in ulcerative colitis.

Introduction: Ulcerative colitis (UC) is an inflammatory disease of the intestinal tract with unknown etiology. Both genetic and environmental factors are involved in the occurrence and development of UC. Understanding changes in the microbiome and metabolome of the intestinal tract is crucial for the clinical management and treatment of UC. Methods: Here, we performed metabolomic and metagenomic profiling of fecal samples from healthy control mice (HC group), DSS (Dextran Sulfate Sodium Salt) -induced UC mice (DSS group), and KT2-treated UC mice (KT2 group). Results and Discussion: In total, 51 metabolites were identified after UC induction, enriched in phenylalanine metabolism, while 27 metabolites were identified after KT2 treatment, enriched in histidine metabolism and bile acid biosynthesis. Fecal microbiome analysis revealed significant differences in nine bacterial species associated with the course of UC, including Bacteroides, Odoribacter, and Burkholderiales, which were correlated with aggravated UC, and Anaerotruncus, Lachnospiraceae, which were correlated with alleviated UC. We also identified a disease-associated network connecting the above bacterial species with UC-associated metabolites, including palmitoyl sphingomyelin, deoxycholic acid, biliverdin, and palmitoleic acid. In conclusion, our results indicated that Anaerotruncus, Lachnospiraceae, and Mucispirillum were protective species against DSS-induced UC in mice. The fecal microbiomes and metabolomes differed significantly among the UC mice and KT2-treated and healthy-control mice, providing potential evidence for the discovery of biomarkers of UC.

KT2 alleviates ulcerative colitis by reducing Th17 cell differentiation through the miR-302c-5p/STAT3 axis.

BACKGROUND: The abnormal differentiation of Th17 cells aggravates ulcerative colitis (UC). Antimicrobial peptides (AMPs) exert pivotal protection functions against UC. KT2 is a cationic AMP that mediates colon cancer development. However, KT2's function in UC remains unclear. METHODS: The UC mouse model was induced by administering 2.5% dextran sulfate sodium, and the mice were given an enema of KT2. KT2's function in UC and Th17 cell differentiation in vivo was evaluated through various molecular experiments. The KT2's function in Th17 cell differentiation in vitro was evaluated by the proportion of CD4+ IL-17+ T cells, IL-17 levels, and RORγt expression levels. Meanwhile, the mechanism was assessed through quantitative real-time PCR, various loss-of-function assays, and dual-luciferase reporter gene assay. RESULTS: KT2 restrained Th17 cell differentiation in both in vivo and in vitro UC models and slowed the UC process. KT2 elevated miR-302c-5p expression, as well as restrained Th17 cell differentiation by increasing miR-302c-5p. Meanwhile, miR-302c-5p interacted with the signal transducer and activator of transcription 3 (STAT3) and negatively regulated its expression. Furthermore, our data revealed that KT2 restrained the activation of STAT3 by elevating miR-302c-5p, thereby inhibiting Th17 cell differentiation. CONCLUSION: KT2 alleviates UC by repressing Th17 cell differentiation through the miR-302c-5p/STAT3 axis.

Dietary inulin supplementation modulates the composition and activities of carbohydrate-metabolizing organisms in the cecal microbiota of broiler chickens.

Inulin is a highly effective prebiotic and an attractive alternative to antibiotic growth promoters for increasing production and maintaining health in chickens. However, how inulin elicits its effects on members of the intestinal microbiota is unknown, even though their importance for energy metabolism and the health of chickens is well documented. A combination of 16S rRNA Illumina sequencing and transcriptomic analysis was used to investigate the effects of supplementing a corn-based basal diet with 1, 2, or 4% inulin or 400 ppm bacitracin on the composition, diversity and activities of carbohydrate-metabolizing organisms (CMOs) in the cecal microbiota of broiler chickens. We found that members of Bacteroides were the most abundant non-starch degrading CMOs, contributing 43.6-52.1% of total glycoside hydrolase genes and 34.6-47.1% activity to the meta-transcriptomes of chickens in the different dietary groups, although members of Parabacteroides, Prevotella, Alistipes, Clostridium, Barnesiella, Blastocystis, Faecalibacterium and others were also actively involved. Inulin and bacitracin inclusion in the basal diet did not change significantly the composition or diversity of these CMOs. Inulin supplementation at three levels promoted the activities of Bacteroides, Prevotella and Bifidobacterium, and 2% level appears to be the most optimal dosage for bifidobacterial activity.

Mono-mercapto-functionalized pillar[5]arene: a host-guest complexation accelerated reversible redox dimerization.

A mono-mercapto-functionalized pillar[5]arene and its dimer, capable of being reversibly interconverted, were successfully synthesized. Fascinatingly, a faster reversible redox conversion involving a dynamic disulfide bond was observed between their host-guest complexes compared with the hosts themselves.

Optimal Colonoscopic Surveillance Interval After Normal Baseline Screening Colonoscopy.

The optimal colonoscopic surveillance interval in the Chinese population is unclear. The present study aimed to assess the optimal colonoscopic surveillance interval after normal baseline screening colonoscopy to avoid overuse or underuse of colonoscopy. This retrospective study included individuals with normal baseline colonoscopy who had undergone at least 2 follow-up colonoscopy examinations at the Digestive Endoscopy Center of our hospital between 2000 and 2013. The risk factors for adenoma and the optimal colonoscopic surveillance interval were assessed. A total of 1,005 individuals (419 men; mean age, 49.34 ± 13.29 years) were included in the study. Of these, 169 individuals had adenomas at colonoscopic surveillance (mean, 1.32 ± 0.79 procedures). The mean adenoma diameter was 0.54 ± 0.38 cm, and the mean number of adenomas was 1.76 ± 1.29. The mean adenoma surveillance interval was 4.76 ± 2.89 years. The risk factors for adenoma identification were age more than 50 years and male gender. The optimal colonoscopic surveillance interval was 4.76 years according to an adenoma detection rate of 5%. The optimal colonoscopic surveillance interval is around 5 years for individuals with normal baseline colonoscopy. Age more than 50 years and male gender are risk factors for adenoma identification.

Construction of a novel DNA-based comparator and its application in intelligent analysis.

In this work, a novel and general comparator was constructed based on cascaded strand displacement reactions and DNA hybridization and its potential in intelligently weighing the quantitative predominance of two targets was explored in a complex biological matrix, which not only enriches the information processing mode of DNA computation but also provides an instructive way to deal with quantitative analyzing tasks in further DNA-based logic sensors.

Optimal colonoscopy surveillance interval period for the adenoma patients who had an adequate polypectomy at baseline colonoscopy.

The role of surveillance colonoscopy has long been established: it reduces both the incidence and the mortality of colorectal cancer. We aimed to assess the optimal colonoscopy surveillance interval period for the adenoma patients who underwent an adequate polypectomy at baseline colonoscopy to avoid overuse or underuse of colonoscopy. A retrospective study was carried out on the baseline adenoma patients who had had at least two completed colonoscopy examinations during the years 2000-2013 in the Digestive Endoscopy Center of the First Affiliated Hospital of Kunming Medical University. All the patients had a complete polypectomy of adenomas at baseline. Data on the patients' demographics and colorectal findings were extracted from a specially designed colonoscopy database. The end point was the finding of adenoma during the subsequent surveillance colonoscopy; an analysis was carried out to identify recurrence factors and the optimal colonoscopy surveillance interval period. A total of 765 (463 men, 302 women, average age 56.51±11.95) eligible patients were included in the study. Three hundred and twelve patients had adenoma and 453 had no adenoma after surveillance colonoscopies (the frequency of repeat colonoscopy is 1-10, average 1.73±1.24). The diameter of adenomas found on the follow-up colonoscopy was 0.2-3.0 cm (average 0.54±0.30 cm). The number of adenomas was 1-11 (2.21±1.53) and the surveillance adenoma interval period was 0.5-13 years (2.64±2.36 years). A total of 576 patients had baseline nonadvanced adenomas. Male sex, age older than 50 years, and more than two different intestine segment adenomas were the risk factors for recurrence. The optimal colonoscopy surveillance interval period is 2.85 years (95% confidence interval: 2.53-3.17) according to the recurrence rate of 5% adenomas. One hundred and eighty-nine patients had baseline advanced adenomas. Male sex, diameter of adenomas less than 1.0 cm, and adenomas in the right colon or the whole colon were the risk factors for recurrence. The optimal colonoscopy surveillance interval period is 2.06 years (95% confidence interval: 1.71-2.45) according to the recurrence rate of 5% adenomas. The optimal colonoscopy surveillance interval period is 3 years or so for the adenoma patients who had an adequate polypectomy at baseline colonoscopy. Male sex, age older than 50 years, less than 1.0 cm adenomas diameter and the right colon, or multisegment intestine adenomas were the risk factors for recurrence. This has significance for guiding the follow-up colonoscopy interval time of the patients with intestine adenomas.

Population Density and Risk of Inflammatory Bowel Disease: A Prospective Population-Based Study in 13 Countries or Regions in Asia-Pacific.

INTRODUCTION: Living in an urban environment may increase the risk of developing inflammatory bowel disease (IBD). It is unclear if this observation is seen globally. We conducted a population-based study to assess the relationship between urbanization and incidence of IBD in the Asia-Pacific region. METHODS: Newly diagnosed IBD cases between 2011 and 2013 from 13 countries or regions in Asia-Pacific were included. Incidence was calculated with 95% confidence interval (CI) and pooled using random-effects model. Meta-regression analysis was used to assess incidence rates and their association with population density, latitude, and longitude. RESULTS: We identified 1175 ulcerative colitis (UC), 656 Crohn's disease (CD), and 37 IBD undetermined (IBD-U). Mean annual IBD incidence per 100 000 was 1.50 (95% CI: 1.43-1.57). India (9.31; 95% CI: 8.38-10.31) and China (3.64; 95% CI, 2.97-4.42) had the highest IBD incidence in Asia. Incidence of overall IBD (incidence rate ratio [IRR]: 2.19; 95% CI: 1.01-4.76]) and CD (IRR: 3.28; 95% CI: 1.83-9.12) was higher across 19 areas of Asia with a higher population density. In China, incidence of IBD (IRR: 2.37; 95% CI: 1.10-5.16) and UC (IRR: 2.63; 95% CI: 1.2-5.8) was positively associated with gross domestic product. A south-to-north disease gradient (IRR: 0.94; 95% CI: 0.91-0.98) was observed for IBD incidence and a west-to-east gradient (IRR: 1.14; 95% CI: 1.05-1.24) was observed for CD incidence in China. This study received IRB approval. CONCLUSIONS: Regions in Asia with a high population density had a higher CD and UC incidence. Coastal areas within China had higher IBD incidence. With increasing urbanization and a shift from rural areas to cities, disease incidence may continue to climb in Asia.

Differential expression of serum microRNAs in glucocorticoid-resistant patients with ulcerative colitis.

Inflammatory bowel disease (IBD) includes ulcerative colitis (UC) and Crohn's disease (CD). Glucocorticoids (GCs) are the most effective treatment for moderate to severe active UC. However, one-third of patients are not sensitive to GCs (i.e., they are GC resistant). The mechanism of GC resistance in IBD is unknown, and it remains unclear how to predict resistance in IBD patients. This study aimed to explore the possible correlation between miRNA expression and variability in GC-resistant and GC-sensitive patients with ulcerative colitis. A comparative serum microRNA analysis in GC-resistant and GC-sensitive patients with ulcerative colitis was conducted by microarray. Differential microRNA expression was further validated in serum samples by quantitative real-time PCR. We found that downregulated microRNAs had a significant correlation with several signal transduction pathways (the PI3K-Akt and MAPK signaling pathways) and target genes (HSP90B1, MAPK13, MAPK9, PIK3AP1 and TLR4) related to GC resistance. Eight downregulated microRNAs were chosen for further validation in 76 serum samples. The results showed that miR-16-2-3p, miR-30e-3p, miR-32-5p, miR-642a-5p, miR-150-5p, and miR-224-5p were significantly downregulated in the GC-resistant group. Receiver operating characteristic analysis showed that the area under the curves (AUCs) for those microRNAs were 0.94, 0.93, 0.85, 0.87, 0.92, and 0.99, with specificities of 97.30%, 89.20%, 59.50%, 73.00%, 97.30%, and 97.30% and sensitivities of 74.40%, 84.60%, 97.40%, 92.30%, 66.70%, and 89.70%, respectively. Our study provides preliminary evidence for the pathogenic mechanism of GC resistance and shows that serum microRNAs might serve as biomarkers for GC resistance in IBD.

A Novel Reconfigurable Logic Unit Based on the DNA-Templated Potassium-Concentration-Dependent Supramolecular Assembly.

Plenty of molecular circuits with specific functions have been developed; however, logic units with reconfigurability, which could simplify the circuits and speed up the information process, are rarely reported. In this work, we designed a novel reconfigurable logic unit based on a DNA-templated, potassium-concentration-dependent, supramolecular assembly, which could respond to the input stimuli of H+ and K+ . By inputting different concentrations of K+ , the logic unit could implement three significant functions, including a half adder, a half subtractor, and a 2-to-4 decoder. Considering its reconfigurable ability and good performance, the novel prototypes developed here may serve as a promising proof of principle in molecular computers.

Critical role of Keratin 1 in maintaining epithelial barrier and correlation of its down-regulation with the progression of inflammatory bowel disease.

Inflammatory bowel disease (IBD) is the result of a chronic intestinal inflammatory response which usually occurred in colon and small intestine. Keratins constitute the intermediate filament cytoskeleton in all epithelia. The present study was intended to explore the role of Keratin 1 (KRT1) in the progress of IBD. In normal intestinal tissue, the expression of KRT1 was detected by RT-PCR and Western blot. The levels of KRT1 protein significantly decreased in serum samples of IBD patients as compared with sera of healthy controls. Immunohistochemistry revealed that the expression of KRT1 decreased in various intestinal diseases, especially in Crohn's disease and ulcerative colitis. Furthermore, down-regulated KRT1 was correlated with the severity of IBD. The overexpression of KRT1 maintained epithelial barrier in Caco-2 cells after IL-1ß treatment. Furthermore, IL-1ß-induced disruption of tight junction became significantly attenuated in KRT1 over-expressing Caco-2 cells as compared with control cells. Thus, KRT1 played an important role of maintaining epithelial barrier and its down-regulation in intestinal tissue was correlated with the progression of IBD.

Identification of Environmental Factors Associated with Inflammatory Bowel Disease in a Southwestern Highland Region of China: A Nested Case-Control Study.

BACKGROUND: The aim of this study was to examine environmental factors associated with inflammatory bowel disease (IBD) in Yunnan Province, a southwestern highland region of China. METHODS: In this nested case-control study, newly diagnosed ulcerative colitis (UC) cases in 2 cities in Yunnan Province and Crohn's disease (CD) cases in 16 cities in Yunnan Province were recruited between 2008 and 2013. Controls were matched by geography, sex and age at a ratio of 1:4. Data were collected using the designed questionnaire. Conditional logistic regression models were used to estimate adjusted odds ratios (ORs). RESULTS: A total of 678 UC and 102 CD cases were recruited. For UC, various factors were associated with an increased risk of developing UC: dietary habits, including frequent irregular meal times; consumption of fried foods, salty foods and frozen dinners; childhood factors, including intestinal infectious diseases and frequent use of antibiotics; and other factors, such as mental labor, high work stress, use of non-aspirin non-steroidal anti-inflammatory drugs and allergies (OR > 1, p < 0.05). Other factors showed a protective effect: such as consumption of fruits, current smoking, physical activity, and drinking tea (OR < 1, p < 0.05). For CD, appendectomy and irregular meal times increased the disease risk (OR >1, p < 0.05), whereas physical activity may have reduced this risk (OR < 1, p < 0.05). CONCLUSIONS: This study is the first nested case-control study to analyze the association between environmental factors and IBD onset in a southwestern highland region of China. Certain dietary habits, lifestyles, allergies and childhood factors may play important roles in IBD, particularly UC.

Expression of guanylate cyclase-C, guanylin, and uroguanylin is downregulated proportionally to the ulcerative colitis disease activity index.

The transmembrane receptor guanylate cyclase-C (GC-C) signaling pathway has been implicated in several gastrointestinal disorders. Activation of GC-C via guanylin (Gn) and uroguanylin (Ugn) regulates intestinal fluid and electrolyte homeostasis. However, how it regulates the pathogenesis of inflammatory bowel disease (IBD) is still unclear. Here, we investigated the activation of GC-C signaling in ulcerative colitis (UC) of different clinical severities. A total of 60 UC patients and 20 normal controls were recruited. Evaluation of the UC disease activity index (DAI) was performed using a modified Mayo scoring system. The expression of GC-C, Gn and Ugn in the colonic mucosa was measured by quantitative real-time PCR and Western blot. We found that the UC patients had significantly lower expression of GC-C, Gn and Ugn than the controls. Furthermore, there were significant differences for GC-C, Gn and Ugn expression for the UC groups of Grade 1, 2 and 3, and their expression levels were reduced with increases in their DAI. Taken together, our results demonstrate that GC-C, Gn and Ugn are downregulated in UC, and this downregulation is more significant with aggravation of the clinical condition. Therefore, the GC-C signaling pathway may be implicated in the progression of UC.

Heat shock factor 2 levels are associated with the severity of ulcerative colitis.

BACKGROUND AND AIMS: The morbidity of ulcerative colitis (UC) is increasing in China every year. In addition, there is a lack of accurate diagnostic indices with which to evaluate the activity of the disease. The aim of this study was to identify UC-associated proteins as biomarkers for the diagnosis, and objective assessment of disease activity. METHODS: Differential expression of serum proteins from UC patients compared to normal controls was analyzed by two-dimensional electrophoresis (2-DE) and matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF-MS). The expression of heat shock factor 2(HSF2)in colonic mucosa in Crohn's disease, Behcet's disease, ulcerative colitis, intestinal tuberculosis, infective enteritis, intestinal lymphoma, and normal controls was investigated by immunohistochemistry (IHC). The expression of the HSF2 in colonic mucosa of UC subjects with varying severity of disease was measured by real time-PCR and Western Blots. The expression of HSF2 was inhibited by HSF2 small interfering RNA (siRNA) transfection in Caco-2 cells. The concentrations of HSF2, IL-1ß, and TNF-α in serum and IL-1ß, and TNF-α in the supernatants of transfected Caco-2 cells were determined by ELISA. RESULTS: HSF2 was differentially expressed in UC patients compared to normal controls. HSF2 expression was significantly higher in the intestinal mucosa of UC patients compared to other six groups. The results of immunohistochemistry, real time-PCR, Western Blots, and ELISA showed that the expression of HSF2 increased in parallel with the severity of UC. The serum concentration of HSF2 also positively correlated with levels of IL-1ß and TNF-α. After down-regulation expression of HSF2 in Caco-2 cells by RNA interference, the productions of IL-1ß and TNF-α stimulated by lipopolysaccharide (LPS) increased dramatically. CONCLUSIONS: HSF2 appears to be a potential novel molecular marker for UC activity, and may provide a basis for studies on the pathogenesis and novel therapeutic targets for UC.