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.

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.

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.

WRKY transcription factor is a type of transcription factor unique to plants and plays an important role in various physiological processes of plants. This study is based on the transcriptome data of Atractylodes lancea, the correlation between the FPKM values of the AlWRKY gene and the AlTPS gene of Atractylodes lancea was analyzed. Combined with the analysis results, the candidate gene AlWRKY65 with a significant positive correlation with the expression levels of AlTPS1 and AlTPS6 genes and a relatively high FPKM value was screened. The candidate gene was cloned to obtain the open reading frame ORF of the AlWRKY65 gene, and the related information of its encoded protein was analyzed and the gene expression was studied. The results showed that AlWRKY65 contains a 681 bp open reading frame and encoding 226 amino acids. Through amino acid sequence homology analysis, it was found that AlWRKY65 amino acid sequence had high homology with several plants such as HaWRKY65 and LsWRKY65; AlWRKY65 protein had a typical WRKYGQK domain, belonging to IIe subgroup of WRKY transcription factor family; phylogenetic analysis indicated that AlWRKY65 protein had the higher homology with CcWRKY65 protein; the expression of AlWRKY65 gene in different tissues of two producing areas of Atractylodes lancea were assayed via real-time fluorescence quantitative PCR, and the results showed that all of them were highly expressed in leaves and also has tissue differences. The expression level of AlWRKY65 gene was down-regulated within 48 h of methyl jasmonate (MeJA) induction; subcellular localization and transcriptional activation assay suggested that AlWRKY65 was located in the nucleus and had no transcriptional activation activity. This study provides a reference for further elucidating the biological function of AlWRKY65 in Atractylodes lancea.

Background: The initiation of sodium-glucose cotransporter-2 inhibitors (SGLT2i) typically leads to a reversible initial dip in estimated glomerular filtration rate (eGFR). The implications of this phenomenon on clinical outcomes are not well-defined. Methods: We searched MEDLINE, Embase, and Cochrane Library from inception to March 23, 2023 to identify randomized controlled trials and cohort studies comparing kidney and cardiovascular outcomes in patients with and without initial eGFR dip after initiating SGLT2i. Pooled estimates were calculated using random-effect meta-analysis. Results: We included seven studies in our analysis, which revealed that an initial eGFR dip following the initiation of SGLT2i was associated with less annual eGFR decline (mean difference, 0.64; 95% confidence interval [CI], 0.437 to 0.843) regardless of baseline eGFR. The risk of major adverse kidney events was similar between the non-dipping and dipping groups but reduced in patients with a ≤10% eGFR dip (hazard ratio [HR], 0.915; 95% CI, 0.865 to 0.967). No significant differences were observed in the composite of hospitalized heart failure and cardiovascular death (HR, 0.824; 95% CI, 0.633 to 1.074), hospitalized heart failure (HR, 1.059; 95% CI, 0.574 to 1.952), or all-cause mortality (HR, 0.83; 95% CI, 0.589 to 1.170). The risk of serious adverse events (AEs), discontinuation of SGLT2i due to AEs, kidney-related AEs, and volume depletion were similar between the two groups. Patients with >10% eGFR dip had increased risk of hyperkalemia compared to the non-dipping group. Conclusion Initial eGFR dip after initiating SGLT2i might be associated with less annual eGFR decline. There were no significant disparities in the risks of adverse cardiovascular outcomes between the dipping and non-dipping groups.

Purpose: Protective ileostomy and colostomy are performed in patients undergoing low anterior resection with a high leakage risk. We aimed to compare surgical, medical, and daily care complications between these 2 ostomies in order to make individual choice. Methods: Patients who underwent low anterior resection for rectal tumors with protective stomas between January 2011 and September 2018 were enrolled. Stoma-related complications were prospectively recorded by wound, ostomy, and continence nurses. The cancer stage and treatment data were obtained from the Taiwan Cancer Database of our Big Data Center. Other demographic data were collected retrospectively from medical notes. The complications after stoma creation and after the stoma reversal were compared. Results: There were 176 patients with protective colostomy and 234 with protective ileostomy. Protective ileostomy had higher proportions of high output from the stoma for 2 consecutive days than protective colostomy (11.1% vs. 0%, P<0.001). Protective colostomy resulted in more stoma retraction than protective ileostomy (21.6% vs. 9.4%, P=0.001). Female, open operation, ileostomy, and carrying stoma more than 4 months were also significantly associated with a higher risk of stoma-related complications during diversion. For stoma retraction, the multivariate analysis revealed that female (odds ratio [OR], 4.00; 95% confidence interval [CI], 2.13–7.69; P<0.001) and long diversion duration (≥4 months; OR, 2.33; 95% CI, 1.22–4.43; P=0.010) were independent risk factors, but ileostomy was an independent favorable factor (OR, 0.40; 95% CI, 0.22–0.72; P=0.003). The incidence of complication after stoma reversal did not differ between colostomy group and ileostomy group (24.3% vs. 20.9%, P=0.542). Conclusion We suggest avoiding colostomy in patients who are female and potential prolonged diversion when stoma retraction is a concern. Otherwise, ileostomy should be avoided for patients with impaired renal function. Wise selection and flexibility are more important than using one type of stoma routinely.

Purpose: Protective ileostomy and colostomy are performed in patients undergoing low anterior resection with a high leakage risk. We aimed to compare surgical, medical, and daily care complications between these 2 ostomies in order to make individual choice. Methods: Patients who underwent low anterior resection for rectal tumors with protective stomas between January 2011 and September 2018 were enrolled. Stoma-related complications were prospectively recorded by wound, ostomy, and continence nurses. The cancer stage and treatment data were obtained from the Taiwan Cancer Database of our Big Data Center. Other demographic data were collected retrospectively from medical notes. The complications after stoma creation and after the stoma reversal were compared. Results: There were 176 patients with protective colostomy and 234 with protective ileostomy. Protective ileostomy had higher proportions of high output from the stoma for 2 consecutive days than protective colostomy (11.1% vs. 0%, P<0.001). Protective colostomy resulted in more stoma retraction than protective ileostomy (21.6% vs. 9.4%, P=0.001). Female, open operation, ileostomy, and carrying stoma more than 4 months were also significantly associated with a higher risk of stoma-related complications during diversion. For stoma retraction, the multivariate analysis revealed that female (odds ratio [OR], 4.00; 95% confidence interval [CI], 2.13–7.69; P<0.001) and long diversion duration (≥4 months; OR, 2.33; 95% CI, 1.22–4.43; P=0.010) were independent risk factors, but ileostomy was an independent favorable factor (OR, 0.40; 95% CI, 0.22–0.72; P=0.003). The incidence of complication after stoma reversal did not differ between colostomy group and ileostomy group (24.3% vs. 20.9%, P=0.542). Conclusion We suggest avoiding colostomy in patients who are female and potential prolonged diversion when stoma retraction is a concern. Otherwise, ileostomy should be avoided for patients with impaired renal function. Wise selection and flexibility are more important than using one type of stoma routinely.

Purpose: Protective ileostomy and colostomy are performed in patients undergoing low anterior resection with a high leakage risk. We aimed to compare surgical, medical, and daily care complications between these 2 ostomies in order to make individual choice. Methods: Patients who underwent low anterior resection for rectal tumors with protective stomas between January 2011 and September 2018 were enrolled. Stoma-related complications were prospectively recorded by wound, ostomy, and continence nurses. The cancer stage and treatment data were obtained from the Taiwan Cancer Database of our Big Data Center. Other demographic data were collected retrospectively from medical notes. The complications after stoma creation and after the stoma reversal were compared. Results: There were 176 patients with protective colostomy and 234 with protective ileostomy. Protective ileostomy had higher proportions of high output from the stoma for 2 consecutive days than protective colostomy (11.1% vs. 0%, P<0.001). Protective colostomy resulted in more stoma retraction than protective ileostomy (21.6% vs. 9.4%, P=0.001). Female, open operation, ileostomy, and carrying stoma more than 4 months were also significantly associated with a higher risk of stoma-related complications during diversion. For stoma retraction, the multivariate analysis revealed that female (odds ratio [OR], 4.00; 95% confidence interval [CI], 2.13–7.69; P<0.001) and long diversion duration (≥4 months; OR, 2.33; 95% CI, 1.22–4.43; P=0.010) were independent risk factors, but ileostomy was an independent favorable factor (OR, 0.40; 95% CI, 0.22–0.72; P=0.003). The incidence of complication after stoma reversal did not differ between colostomy group and ileostomy group (24.3% vs. 20.9%, P=0.542). Conclusion We suggest avoiding colostomy in patients who are female and potential prolonged diversion when stoma retraction is a concern. Otherwise, ileostomy should be avoided for patients with impaired renal function. Wise selection and flexibility are more important than using one type of stoma routinely.