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.

Objective To investigate the effect of varying ureteral wall thickness(UWT)at the site of ureteral stones on the clinical efficacy of ureteroscopic lithotripsy(URL).Methods The clinical data of 164 patients with ureteral stones in our hospital were retrospectively analyzed.According to different UWT,the patients were divided into the mild thickening group(84 cases,UWT<3.16 mm),the moderate thickening group(31 cases,UWT 3.16 to 3.49 mm),and the severe thickening group(49 cases,UWT>3.49 mm),and the differences of clinical related indicators among the three groups were compared.Results The incidence of postoperative renal colic and leukocyte disorder in the mild thickening group and the moderate thickening group were lower than those in the severe thickening group,and the differences were statistically significant(P<0.05).The postoperative catheterization time in the mild thickening group and the moderate thickening group were shorter than that in the severe thickening group,and the incidences of secondary lithotripsy,residual stones and stone return to kidney in the mild thickening group and the moderate thickening group were lower than those in the severe thickening group,with statistically significant differences(P<0.05).The length of hospital stay and hospitalization cost in the mild thickening group and the moderate thickening group were shorter/less than those in the severe thickening group,with statistically significant differences(P<0.05).Conclusion With the increase of UWT(especially when UWT>3.49 mm),the incidence of postoperative complications and hospitalization cost of URL increase to varying degrees,and the surgical efficacy decreases.In clinical work,UWT measurement holds potential value in predicting the surgical efficacy and complications of URL.

Objective:To comprehensively evaluate the clinical value of Elecsys serum abnormal prothrombin (PIVKA-Ⅱ) test reagent for auxiliary diagnosis of hepatocellular carcinoma (HCC) in the Chinese population.Methods:A multicenter case-control design was used in the study. Samples from patients with first-time confirmed, diagnosed, and untreated HCC, benign liver disease and interfering controls were collected continuously. Elecsys PIVKA-II and alpha-fetoprotein (AFP) were tested for analysis. Various clinical details of the subjects were collected and analyzed. The efficacy of PIVKA-II (21.29 ng/ml) and AFP (400 ng/ml) for HCC diagnosis was calculated at specific positive cut-off values. Statistical analysis was performed using the Kruskal-Wallis test or receiver operating characteristic curve.Results:A total of 448 subjects were eventually enrolled from five centers, including 185 HCC cases. PIVKA-II had a higher diagnostic sensitivity and accuracy than AFP (84.86% vs. 30.81% and 89.01% vs. 63.66%) when the benign liver disease group was used as the control group, while the specificity was slightly lower. A sensitive analysis showed that PIVKA-II had a sensitivity of >80% at this specific positive cut-off value in the subgroup of AFP-negative subjects, patients with different etiologies, and HCC patients with multiple Barcelona Clinic liver cancer stages (including early-stage HCC). At the same time, the PIVKA-II subject had a slightly higher area under the receiver operating characteristic curve than the AFP (0.920 0 vs. 0.880 9).Conclusion:The clinical efficacy of Elecsys PIVKA-Ⅱ is good and stable in the Chinese population. Additionally, it has the clinical potential to improve the current missed diagnosis status of AFP-negative HCC and HCC monitoring at an early stage, as well as the effectiveness of accuracy promotion for HCC auxiliary diagnosis in China.

Increased neuronal apoptosis is an important pathological feature of Alzheimer's disease (AD). The Bcl-2-interacting mediator of cell death (Bim) mediates amyloid-beta (Aβ)-induced neuronal apoptosis. Naturally-occurring antibodies against Bim (NAbs-Bim) exist in human blood, with their levels and functions unknown in AD. In this study, we found that circulating NAbs-Bim were decreased in AD patients. Plasma levels of NAbs-Bim were negatively associated with brain amyloid burden and positively associated with cognitive functions. Furthermore, NAbs-Bim purified from intravenous immunoglobulin rescued the behavioral deficits and ameliorated Aβ deposition, tau hyperphosphorylation, microgliosis, and neuronal apoptosis in APP/PS1 mice. In vitro investigations demonstrated that NAbs-Bim were neuroprotective against AD through neutralizing Bim-directed neuronal apoptosis and the amyloidogenic processing of amyloid precursor protein. These findings indicate that the decrease of NAbs-Bim might contribute to the pathogenesis of AD and immunotherapies targeting Bim hold promise for the treatment of AD.
Alzheimer Disease/pathology* ; Amyloid beta-Peptides/metabolism* ; Amyloid beta-Protein Precursor/metabolism* ; Animals ; Disease Models, Animal ; Humans ; Mice ; Mice, Transgenic

OBJECTIVE: To explore the efficacy and action mechanism of penetrating moxibustion at governor vessel for persistent allergic rhinitis of deficiency-cold syndrome. METHODS: Ninety patients with persistent allergic rhinitis of deficiency-cold syndrome were randomly divided into an observation group ( RESULTS: Compared before treatment, the TCM symptom scores, VAS scores, RQLQ scores, serum levels of IgE and complete blood count of EOS in the two groups were all reduced after treatment ( CONCLUSION Based on the momethasone furoate nasal spray, the adjuvant treatment of penetrating moxibustion at governor vessel could significantly improve the clinical symptoms in patients with persistent allergic rhinitis of deficiency-cold syndrome, and its mechanism may be related to the regulation of immune disorder.
Acupuncture Points ; Humans ; Moxibustion ; Quality of Life ; Rhinitis, Allergic/drug therapy* ; Syndrome ; Treatment Outcome

Objective:To summarize the experience of surgical treatment of primary liver cancer.Methods:The clinical data of 10 966 surgically managed cases with primary liver cancer, from January 1986 to December 2019 at Hepatobiliary Center, the First Affiliated Hospital of Nanjing Medical University, were retrospectively analyzed. The life table method was used to calculate the survival rate and postoperative recurrence rate. Log‐rank test was used to compare the survival process of different groups, and the Cox regression model was used for multivariate analysis. In addition, 2 884 cases of hepatocellular carcinoma(HCC) with more detailed follow‐up data from 2009 to 2019 were selected for survival analysis. Among 2 549 patients treated with hepatectomy, there were 2 107 males and 442 females, with an age of (56.6±11.1) years (range: 20 to 86 years). Among 335 patients treated with liver transplantation, there were 292 males and 43 females, with an age of (51.0±9.7) years (range: 21 to 73 years). The outcomes of hepatectomy versus liver transplantation, anatomic versus non-anatomic hepatectomy were compared, respectively.Results:Of the 10 966 patients with primary liver cancer, 10 331 patients underwent hepatectomy and 635 patients underwent liver transplantation. Patients with liver resection were categorized into three groups: 1986－1995(712 cases), 1996－2008(3 988 cases), 2009?2019(5 631 cases). The 5‐year overall survival rate was 32.9% in the first group(1986－1995). The 5‐year overall survival rate of resected primary liver cancer was 51.7% in the third group(2009‐2019), among which the 5‐year overal survival rates of hepatocellular carcinoma, intrahepatic cholangiocarcinoma and mixed liver cancer were 57.4%, 26.6% and 50.6%, respectively. Further analysis was performed on 2 549 HCC patients with primary hepatectomy. The 1‐, 3‐, 5‐, and 10‐year overall survival rates were 88.1%, 71.9%, 60.0%, and 41.0%, respectively, and the perioperative mortality rate was 1.0%. Two hundred and forty‐seven HCC patients underwent primary liver transplantation, with 1‐, 3‐, 5‐, and 10‐year overall survival rates of 84.0%, 64.8%, 61.9%, and 57.6%, respectively. Eighty‐eight HCC patients underwent salvage liver transplantation, with the 1‐, 3‐, 5‐, and 10‐year overall survival rates of 86.8%, 65.2%, 52.5%, and 52.5%, respectively. There was no significant difference in survival rates between the two groups with liver transplantation ( P>0.05). Comparing the overall survival rates and recurrence rates of primary hepatectomy (2 549 cases) with primary liver transplantation (247 cases), the 1‐, 3‐, 5‐, and 10‐year overall survival rates in patients within Milan criteria treated with hepatectomy and transplantation were 96.3%, 87.1%, 76.9%, 54.7%, and 95.4%, 79.4%, 77.4%, 71.7%, respectively ( P=0.754). The 1‐, 3‐, 5‐year recurrence rates were 16.3%, 35.9%, 47.6% and 8.1%, 11.7%, 13.9%, respectively( P<0.01). The 1‐, 3‐, 5‐, 10‐year overall survival rates in patients with no large vessels invasion beyond the Milan criteria treated with liver resection and transplantation were 87.2%, 65.9%, 53.0%, 33.0% and 87.6%, 71.8%, 71.8%, 69.3%, respectively( P=0.003); the 1‐, 3‐, 5‐year recurrence rate were 39.2%, 57.8%, 69.7% and 29.7%, 36.7%, 36.7%, respectively ( P<0.01). The 1‐, 3‐, 5‐, and 10‐year overall survival rates in patients with large vessels invasion treated with liver resection and transplantation were 62.1%, 36.1%, 22.2%, 15.0% and 62.9%, 31.8%,19.9%, 0, respectively ( P=0.387); the 1‐, 3‐, 5‐year recurrence rates were 61.5%, 74.7%, 80.8% and 59.7%, 82.9%, 87.2%, respectively( P=0.909). Independent prognostic factors for both overall survival and recurrence‐free survival rates of HCC patients treated with liver resection included gender, neoadjuvant therapy, symptoms, AST, intraoperative or postoperative blood transfusion, tumor number, tumor size, cirrhosis, macrovascular invasion, microvascular invasion, and pathological differentiation. Propensity score matching analysis of 443 pairs further showed that there was no significant difference in overall survival rate between anatomical liver resection and non‐anatomical liver resection( P=0.895), but the recurrence rate of non‐anatomical liver resection was higher than that of anatomical liver resection( P=0.035). Conclusions:In the past decade, the overall survival rate of HCC undergoing surgical treatment is significantly higher than before. For HCC patients with good liver function reservation, surgical resection can be performed first, and salvage liver transplantation can be performed after recurrence. The effect of salvage liver transplantation is comparable to that of primary liver transplantation. As for the choice of liver resection approaches, non‐anatomical resection can reserve more liver tissue and can be selected as long as the negative margin is guaranteed.