Background/Aims: Nonalcoholic fatty liver disease (NAFLD) is a common disease with severe inflammatory processes associated with numerous gastrointestinal diseases, such as inflammatory bowel disease (IBD). Therefore, we investigated the relationship between NAFLD and IBD and the possible risk factors associated with the diagnosis of IBD. Methods: This longitudinal nationwide cohort study investigated the risk of IBD in patients with NAFLD alone. General characteristics, comorbidities, and incidence of IBD were also compared. Results: Patients diagnosed with NAFLD had a significant risk of developing IBD compared to control individuals, who were associated with a 2.245-fold risk of the diagnosis of IBD and a 2.260- and 2.231-fold of increased diagnosis of ulcerative colitis and Crohn’s disease, respectively (P< 0.001). The cumulative risk of IBD increased annually during the follow-up of patients with NAFLD (P< 0.001). Conclusions Our results emphasize that NAFLD significantly impacts its incidence in patients with NAFLD. If patients with NAFLD present with risk factors, such as diabetes mellitus and dyslipidemia, these conditions should be properly treated with regular follow-ups. Furthermore, we believe that these causes may be associated with the second peak of IBD.

Background/Aims: Nonalcoholic fatty liver disease (NAFLD) is a common disease with severe inflammatory processes associated with numerous gastrointestinal diseases, such as inflammatory bowel disease (IBD). Therefore, we investigated the relationship between NAFLD and IBD and the possible risk factors associated with the diagnosis of IBD. Methods: This longitudinal nationwide cohort study investigated the risk of IBD in patients with NAFLD alone. General characteristics, comorbidities, and incidence of IBD were also compared. Results: Patients diagnosed with NAFLD had a significant risk of developing IBD compared to control individuals, who were associated with a 2.245-fold risk of the diagnosis of IBD and a 2.260- and 2.231-fold of increased diagnosis of ulcerative colitis and Crohn’s disease, respectively (P< 0.001). The cumulative risk of IBD increased annually during the follow-up of patients with NAFLD (P< 0.001). Conclusions Our results emphasize that NAFLD significantly impacts its incidence in patients with NAFLD. If patients with NAFLD present with risk factors, such as diabetes mellitus and dyslipidemia, these conditions should be properly treated with regular follow-ups. Furthermore, we believe that these causes may be associated with the second peak of IBD.

Background/Aims: Nonalcoholic fatty liver disease (NAFLD) is a common disease with severe inflammatory processes associated with numerous gastrointestinal diseases, such as inflammatory bowel disease (IBD). Therefore, we investigated the relationship between NAFLD and IBD and the possible risk factors associated with the diagnosis of IBD. Methods: This longitudinal nationwide cohort study investigated the risk of IBD in patients with NAFLD alone. General characteristics, comorbidities, and incidence of IBD were also compared. Results: Patients diagnosed with NAFLD had a significant risk of developing IBD compared to control individuals, who were associated with a 2.245-fold risk of the diagnosis of IBD and a 2.260- and 2.231-fold of increased diagnosis of ulcerative colitis and Crohn’s disease, respectively (P< 0.001). The cumulative risk of IBD increased annually during the follow-up of patients with NAFLD (P< 0.001). Conclusions Our results emphasize that NAFLD significantly impacts its incidence in patients with NAFLD. If patients with NAFLD present with risk factors, such as diabetes mellitus and dyslipidemia, these conditions should be properly treated with regular follow-ups. Furthermore, we believe that these causes may be associated with the second peak of IBD.

OBJECTIVE: The objective was to identify risk factors that were associated with the progression from endometriosis to ovarian cancer based on medical insurance data. METHODS: The study was performed on a dataset obtained from the National Health Insurance Research Database, which covered all the inpatient claim data from 2000 to 2013 in Taiwan. The International Classification of Diseases (ICD) code 617 was used to screen the dataset for the patients who were admitted to hospital due to endometriosis. They were then tracked for subsequent diagnosis of ovarian cancer, and available biological, socioeconomic and clinical information was also collected. Univariate and multivariate analyses were then performed based on the Cox regression model to identify risk factors. C-index was calculated and cross validated. RESULTS: A total of 229,617 patients who were admitted to hospital due to endometriosis from 2000 to 2013 were included in the study, out of whom 1,473 developed ovarian cancer by the end of 2013. A variety of factors, including age, residence, hospital stratification, premium range, and various comorbidities had significant impact on the progression (p < 0.05). Among them, age, urbanization of residence, hospital stratification, premium range, post-endometriosis childbearing, pelvic inflammation, and depression all had independent, significant impact (p < 0.05). The validated C-index was 0.69. CONCLUSION: For a woman diagnosed with endometriosis, increased age, residing in a highly urbanized area, low or high income, depression, pelvic inflammation, and absence of childbearing post-endometriosis all put her at high-risk to develop ovarian cancer. The findings may be of help to gynecologists to identify high-risk patients.
Cohort Studies* ; Comorbidity ; Dataset ; Depression ; Diagnosis ; Endometriosis* ; Female ; Humans ; Inflammation ; Inpatients ; Insurance* ; International Classification of Diseases ; Multivariate Analysis ; National Health Programs ; Ovarian Neoplasms* ; Risk Factors* ; Taiwan ; Urbanization

Humans ; Male ; Middle Aged ; Radiography ; Rupture, Spontaneous ; diagnostic imaging ; etiology ; physiopathology ; Ureter ; injuries ; Urolithiasis ; complications ; diagnosis ; diagnostic imaging

PURPOSE: Urinary catheterization is a common technique in clinical practice. There is, however, no consensus on management prior to removal of the indwelling catheter for short-term patients. This systematic review examined the necessity of clamping before removal of an indwelling urinary catheter in short-term patients. METHODS: A systematic literature review was conducted using eight databases and predetermined keywords-guided searches. Some 2,515 studies were evaluated. Ten studies that met the inclusion criteria were selected. RESULTS: The quality of the studies was assessed using the Jadad scoring system. Only 40.0% of studies were rated as high quality. This review found that catheter clamping prior to removal was not necessary for the short-term patient. When made a comparison with the unclamping group, there was no significant difference in recatheterization risk, risk of urine retention, patients' subjective perceptions and rate of urinary tract infection. CONCLUSIONS: This review indicated that bladder training by clamping prior to removal of urinary catheters is not necessary in short-term catheter patients. In addition, clamping carries the risk of complications such as prolonging urinary catheter retention and urinary tract injury. Further investigation requires higher quality methodologies and more diverse study designs.
Attitude to Health ; Catheters, Indwelling ; Constriction ; Device Removal ; Humans ; Patient Education as Topic/methods ; Perception ; Randomized Controlled Trials as Topic ; Retreatment ; Urinary Catheterization/*methods ; Urinary Catheters ; Urinary Retention/psychology ; Urinary Tract Infections/therapy ; Urination/physiology

D-psicose 3-epimerase (DPEase) is demonstrated to be useful in the bioproduction of D-psicose, a rare hexose sugar, from D-fructose, found plenty in nature. Clostridium cellulolyticum H10 has recently been identified as a DPEase that can epimerize D-fructose to yield D-psicose with a much higher conversion rate when compared with the conventionally used DTEase. In this study, the crystal structure of the C. cellulolyticum DPEase was determined. The enzyme assembles into a tetramer and each subunit shows a (β/α)(8) TIM barrel fold with a Mn(2+) metal ion in the active site. Additional crystal structures of the enzyme in complex with substrates/products (D-psicose, D-fructose, D-tagatose and D-sorbose) were also determined. From the complex structures of C. cellulolyticum DPEase with D-psicose and D-fructose, the enzyme has much more interactions with D-psicose than D-fructose by forming more hydrogen bonds between the substrate and the active site residues. Accordingly, based on these ketohexose-bound complex structures, a C3-O3 proton-exchange mechanism for the conversion between D-psicose and D-fructose is proposed here. These results provide a clear idea for the deprotonation/protonation roles of E150 and E244 in catalysis.
Binding Sites ; Biocatalysis ; Catalytic Domain ; Clostridium cellulolyticum ; enzymology ; Hexoses ; chemistry ; Manganese ; chemistry ; Protein Structure, Quaternary ; Racemases and Epimerases ; chemistry ; metabolism ; Substrate Specificity

Background: Therapeutic interventions for diabetes are most effective when administered in the newly onset phase, yet determining the exact onset moment can be elusive in practice. Spontaneous autoimmune diabetes among NOD mice appears randomly between 12 and 32 weeks of age with an incidence range from 60 to 90%. Furthermore, the disease often progresses rapidly to severe diabetes within days, resulting in a very short window of newly onset phase, that poses significant challenge in early diagnosis. Conventionally, extensive blood glucose (BG) testing is typically required on large cohorts throughout several months to conduct prospective survey. We incorporated ultrasensitive urine glucose (UG) testing into an ordinary BG survey process, initially aiming to elucidate the lag period required for excessive glucose leaking from blood to urine during diabetes progression in the mouse model. Results: The observations unexpectedly revealed that small amounts of glucose detected in the urine often coincide with, sometimes even a couple days prior than elevated BG is diagnosed. Accordingly, we conducted the UG-based survey protocol in another cohort that was validated to accurately identified every individual near onset, who could then be confirmed by following few BG tests to fulfill the consecutive BG + criteria. This approach required fewer than 95 BG tests, compared to over 700 tests with traditional BG survey, to diagnose all the 37–38 diabetic mice out of total 60. The average BG level at diagnosis was slightly below 350 mg/dl, lower than the approximately 400 mg/dl observed with conventional BG monitoring. Conclusions We demonstrated a near perfect correlation between BG + and ultrasensitive UG + results in prospective survey with no lag period detected under twice weekly of testing frequency. This led to the refined protocol based on surveying with noninvasive UG testing, allowing for the early identification of newly onset diabetic mice with only a few BG tests required per mouse. This protocol significantly reduces the need for extensive blood sampling, lancet usage, labor, and animal distress, aligning with the 3Rs principle. It presents a convenient, accurate, and animal-friendly alternative for early diabetes diagnosis, facilitating research on diagnosis, pathogenesis, prevention, and treatment.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.