1.Predicting Clinically Significant Prostate Cancer Using Urine Metabolomics via Liquid Chromatography Mass Spectrometry
Chung-Hsin CHEN ; Hsiang-Po HUANG ; Kai-Hsiung CHANG ; Ming-Shyue LEE ; Cheng-Fan LEE ; Chih-Yu LIN ; Yuan Chi LIN ; William J. HUANG ; Chun-Hou LIAO ; Chih-Chin YU ; Shiu-Dong CHUNG ; Yao-Chou TSAI ; Chia-Chang WU ; Chen-Hsun HO ; Pei-Wen HSIAO ; Yeong-Shiau PU ;
The World Journal of Men's Health 2025;43(2):376-386
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.
2.Predicting Clinically Significant Prostate Cancer Using Urine Metabolomics via Liquid Chromatography Mass Spectrometry
Chung-Hsin CHEN ; Hsiang-Po HUANG ; Kai-Hsiung CHANG ; Ming-Shyue LEE ; Cheng-Fan LEE ; Chih-Yu LIN ; Yuan Chi LIN ; William J. HUANG ; Chun-Hou LIAO ; Chih-Chin YU ; Shiu-Dong CHUNG ; Yao-Chou TSAI ; Chia-Chang WU ; Chen-Hsun HO ; Pei-Wen HSIAO ; Yeong-Shiau PU ;
The World Journal of Men's Health 2025;43(2):376-386
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.
3.Predicting Clinically Significant Prostate Cancer Using Urine Metabolomics via Liquid Chromatography Mass Spectrometry
Chung-Hsin CHEN ; Hsiang-Po HUANG ; Kai-Hsiung CHANG ; Ming-Shyue LEE ; Cheng-Fan LEE ; Chih-Yu LIN ; Yuan Chi LIN ; William J. HUANG ; Chun-Hou LIAO ; Chih-Chin YU ; Shiu-Dong CHUNG ; Yao-Chou TSAI ; Chia-Chang WU ; Chen-Hsun HO ; Pei-Wen HSIAO ; Yeong-Shiau PU ;
The World Journal of Men's Health 2025;43(2):376-386
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.
4.Predicting Clinically Significant Prostate Cancer Using Urine Metabolomics via Liquid Chromatography Mass Spectrometry
Chung-Hsin CHEN ; Hsiang-Po HUANG ; Kai-Hsiung CHANG ; Ming-Shyue LEE ; Cheng-Fan LEE ; Chih-Yu LIN ; Yuan Chi LIN ; William J. HUANG ; Chun-Hou LIAO ; Chih-Chin YU ; Shiu-Dong CHUNG ; Yao-Chou TSAI ; Chia-Chang WU ; Chen-Hsun HO ; Pei-Wen HSIAO ; Yeong-Shiau PU ;
The World Journal of Men's Health 2025;43(2):376-386
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.
5.Predicting Clinically Significant Prostate Cancer Using Urine Metabolomics via Liquid Chromatography Mass Spectrometry
Chung-Hsin CHEN ; Hsiang-Po HUANG ; Kai-Hsiung CHANG ; Ming-Shyue LEE ; Cheng-Fan LEE ; Chih-Yu LIN ; Yuan Chi LIN ; William J. HUANG ; Chun-Hou LIAO ; Chih-Chin YU ; Shiu-Dong CHUNG ; Yao-Chou TSAI ; Chia-Chang WU ; Chen-Hsun HO ; Pei-Wen HSIAO ; Yeong-Shiau PU ;
The World Journal of Men's Health 2025;43(2):376-386
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.
6.Comparison of short-term clinical efficacy between CO external fixation and internal fixation with steel plate in the treatment of unstable distal radius fractures.
Min-Rui FU ; Chang-Long SHI ; Yong-Zhong CHENG ; Ming-Ming MA ; Zheng-Lin NIU ; Hai-Xiang SUN ; Jing-Hua GAO ; Zhong-Kai WU ; Yi-Ming XU
China Journal of Orthopaedics and Traumatology 2025;38(1):10-17
OBJECTIVE:
To evaluate the short-term clinical efficacy of external fixation and internal fixation with steel plate in the treatment of unstable distal radius fractures (AO-23C type), based on the principles of Chinese osteosynthesis (CO).
METHODS:
Forty-eight patients with unstable distal radius fractures between January 2022 and February 2023 were retrospectively analyzed and divided into the CO external fixation group and internal fixation group. CO external fixation group consisted of 25 patients, including 7 males and 18 females, aged from 37 to 56 years old with an average of ( 52.6±11.3) years old. Among them, there were 7 patients of traffic accidents and 18 patients of falls, resulting in a total of 25 patients of closed fractures and no open fractures, the treatment was conducted using closed reduction and CO external fixation. The internal fixation group consisted of 23 patients, comprising 8 males and 15 females, age ranged from 41 to 59 years old, with an average age of(53.3±13.7) years old. Among them, 8 patients resulted from car accidents while the remaining 15 patients were caused by falls. All 23 patients were closed fractures without any open fractures observed. The technique of open reduction and internal fixation with steel plate was employed. The perioperative data, including injury-operation time, operation duration, blood loss, and length of hospital stay, were assessed in both groups. Additionally, the QuickDASH score and visual analogue scale (VAS) were evaluated. Range of motion and grip strength assessment, imaging findings such as palmar inclination angle, ulnar declination angle, radius length, articular surface step, intra-articular space measurements were also examined along with any complications.
RESULTS:
The follow-up duration ranged from 0 to 24 months, with an average duration of (16.0±3.8) months. The CO external fixation exhibited significantly shorter time from injury to operation (2.4±3.3) d vs (7.4±3.7) d, shorter operation duration (56.27±15.23) min vs (74.10±5.26) min, lower blood loss (14.52±6.54) ml vs (32.32±10.03) ml, and reduced hospitalization days (14.04±3.24 )d vs (16.45±3.05) d compared to the internal fixation group (P<0.05). The QuickDASH score at 12 months post-operation was (8.21±1.64) in the CO external fixation group, while no significant difference was observed in the internal fixation group (7.04±3.64), P>0.05. There were no statistically significant differences in VAS between two groups at 6 weeks, as well as 1 and 3 months post-surgery (P>0.05). Additionally, there were no significant disparities observed in terms of range of motion and grip strength between two groups at the 2-year follow-up after the operation (P>0.05). After 12 months of surgery, the CO external fixation group exhibited a significantly smaller palmar inclination angle (17.90±2.18) ° vs (19.87±3.21) °, reduced articular surface step (0.11±0.03) mm vs (0.17±0.02) mm, and shorter radius length (8.16±1.11) mm compared to the internal fixation group (9.59±1.02) mm, P<0.05. The ulnar deviation angle and intra-articular space did not show any significant difference between two groups (P>0.05). The reduced fell within the allowable range between the CO external fixation group (23 out of 25 cases) and the internal fixation group (21 out of 23 cases) was not statistically significant (P=0.29). There was no significant difference in complications between the two groups(P>0.05).
CONCLUSION
Both the CO external fixation and open reduction with plate internal fixation demonstrate clinical efficacy in managing unstable distal radius fractures. The CO external fixation offers advantages in shorter injury-to-operation times, reduced intraoperative blood loss, and decreased surgical durations, while radial shortening is more effectively controlled by internal fixation.
Humans
;
Male
;
Female
;
Middle Aged
;
Radius Fractures/physiopathology*
;
Adult
;
Bone Plates
;
Fracture Fixation, Internal/methods*
;
External Fixators
;
Retrospective Studies
;
Fracture Fixation/methods*
;
Wrist Fractures
7.Single-position O-arm X-ray navigation assisted oblique lateral interbody fusion combined with minimally invasive percutaneous pedicle nail internal fixation for lumbar spondylolisthesis.
Kai-Kai TU ; Hui FEI ; Yu-Liang LOU ; Can-Feng WANG ; Chang-Ming LI ; Li-Shen ZHOU ; Feng HONG
China Journal of Orthopaedics and Traumatology 2025;38(5):447-453
OBJECTIVE:
To investigate the early clinical efficacy of single-position O-arm navigation-assisted oblique lateral interbody fusion(OLIF) combined with minimally invasive percutaneous pedicle screw fixation(PPS) in the treatment of lumbar spondylolisthesis.
METHODS:
A retrospective analysis was conducted on 22 patients with lumbar spondylolisthesis who underwent OLIF-PPS surgery including 11 males and 11 females with a mean age of (64.6±1.5) years old ranging from 49 to 80 years old between April 2021 and June 2023. All patients presented with lumbosacral pain, lower limb radiating pain, numbness, and had poor responses to conservative treatment. Surgical time, intraoperative blood loss, hospital stay, and postoperative complications were recorded. Clinical outcomes were evaluated using the visual analogue scale(VAS) and Oswestry disability index(ODI) preoperatively at 3 days after operation and the final follow-up. Standing lumbar anteroposterior and lateral X-rays were performed to measure disc height(DH), slippage degree, vertebral reduction rate, pedicle screw accuracy, and cage subsidence.
RESULTS:
All surgeries were successfully completed with a mean follow-up of (27.1±2.2) months (range 18 to 36 months). The mean surgical time was (76.1±12.2) min (range 60 to 93 min), intraoperative blood loss was (86.3±32.2) ml (range 40 to 113 ml), and hospital stay was (7.1±1.2) days. Postoperative VAS significantly improved from (7.2±0.7) preoperatively to (2.3±0.5) at 3 days after operation and (1.7±0.2) at the final follow-up (P<0.05). ODI decreased from (68.5±7.2)% preoperatively to (30.3±3.1)% at 3 days after operation and (16.6±1.6)% at the final follow-up (P<0.05). DH increased from (8.5±1.7) mm preoperatively to (18.1±1.4) mm at 3 days after operation and (17.2±1.1) mm at the final follow-up (P<0.05). Slippage degree improved from (24.1±4.6)% preoperatively to (10.3±4.2)% at 3 days after operation and (10.1±3.2)% at the final follow-up (P<0.05). A total of 88 pedicle screws were implanted with an excellent rate of 98% (86/88). Complications included transient left hip flexion weakness (2 cases) and left anteromedial thigh pain (1 case), all resolved during follow-up. No incision hematoma, infection, screw loosening, or cage subsidence occurred.
CONCLUSION
Single-position O-arm navigation-assisted OLIF combined with PPS demonstrates satisfactory early clinical efficacy for lumbar spondylolisthesis, with advantages including minimal invasiveness, significant pain relief, effective vertebral reduction, and low complication rates.
Humans
;
Male
;
Female
;
Spondylolisthesis/diagnostic imaging*
;
Middle Aged
;
Aged
;
Spinal Fusion/methods*
;
Lumbar Vertebrae/diagnostic imaging*
;
Minimally Invasive Surgical Procedures/methods*
;
Pedicle Screws
;
Aged, 80 and over
;
Retrospective Studies
8.Research progress on exosomes and their non-coding RNAs in the diagnosis of neurodegenerative diseases
Binpan WANG ; Yan PI ; Ming CHEN ; Kai CHANG
Chinese Journal of Preventive Medicine 2024;58(9):1415-1422
Neurodegenerative diseases, originating from irreversible progressive loss of neuronal structure or function, are difficult to diagnose and treat. They vary widely in scope and have poor prevention and prognosis. Therefore, research on their early diagnosis is particularly important. Exosomes are small vesicles of cellular origin that contain various bioactive small molecules, such as proteins, RNAs, and DNAs, and play important roles in intercellular communication. Recent studies have shown that exosomes and their non-coding RNAs are key factors in the pathogenesis of various neurodegenerative diseases. Therefore, exosomes and their non-coding RNAs may provide a breakthrough for the early diagnosis of neurodegenerative diseases. This review summarizes the biology of exosomes and the current research progress of exosomes and their non-coding RNAs in diagnosing neurodegenerative diseases and further explores the challenges and prospects they face.
9.Application of catalytic hairpin self-assembly combining with CRISPR-Cas12a sensing technology in exosomal microRNA-21
Binpan WANG ; Xiaoqi TANG ; Shuang ZHAO ; Ming CHEN ; Kai CHANG
Chinese Journal of Laboratory Medicine 2024;47(2):152-158
Objective:To establish a sensing technology of catalytic hairpin self-assembly (CHA) combining with clustered interspaced short palindromic repeats with associated protein 12a (CRISPR-Cas12a) for the detection of exosomal microRNA-21 (miR-21), and to analyze the performance.Methods:Eight patients diagnosed as breast cancer in the First Affiliated Hospital of the Army Military Medical University from September to October 2023 were selected as the breast cancer group; 8 healthy individuals who underwent physical examinations during the same period were selected as the healthy control group. Plasma exosomes and their miR-21 were extracted using the kit. DNA hairpins and CRISPR RNA sequences were designed for miR-21 sequences. The feasibility of detection technology was validated using polyacrylamide gel electrophoresis and fluorescence spectrophotometer. Hairpins concentration, CHA reaction time, Cas12a protein concentration and Cas12a protein reaction time were further optimized. On this basis, miR-21 was detected at different concentrations (0, 0.1, 0.5, 1.0, 2.5, 5.0, 7.5, 10.0 nmol/L), and fluorescence intensity was collected for unary linear regression analysis to evaluate methodological sensitivity; meanwhile, different types of miRNAs (miR-31, miR-26a, miR-192, miR-25-3p) and blank controls were detected to evaluate methodological specificity. A case-control study was conducted to detect the relative expression level of plasma exosomal miR-21 in breast cancer group and healthy control group using this detection technology and reverse transcription PCR (RT-PCR) to evaluate the detection ability of clinical samples.Results:A detection method for exosomal miR-21 was established using CHA combining with CRISPR-Cas12a. The concentration of miR-21 detected by this method showed a good linear relationship with fluorescence intensity (the linear correlation coefficient 0.966 7), and the linear detection range was 0.1-10.0 nmol/L, and the detection limit was 87.81 pmol/L. The fluorescence intensity of miR-21 was 450.27±23.96 which was higher than that of miR-31, miR-26a, miR-192, miR-25-3p, and the blank group (98.89±7.35, 98.12±2.07, 98.93±2.45, 96.66±2.45, 82.93±3.54, respectively), with statistical significance ( P<0.001). The results of RT-PCR showed that the relative expression levels of plasma exosomal miR-21 in the breast cancer group were higher than that in healthy control group (1.83±0.27 vs 0.93±0.12, P<0.001); CHA combining with CRISPR-Cas12a detection technology showed that the relative expression levels of plasma exosomal miR-21 in breast cancer group were higher than that in healthy control group (1.94±0.21 vs 0.98±0.08, P<0.001); There was no significant difference in the relative expression levels of plasma exosomal miR-21 between CHA combining with CRISPR-Cas12a detection technology and reverse transcription PCR in breast cancer group and healthy control group ( P>0.05). Conclusion:In this study, a highly sensitive and specific sensing technology of CHA combining with CRISPR-Cas12a for exosomal miR-21 was established. The results of detecting plasma exosomal miR-21 were consistent with the results of reverse transcription PCR, which can be used for screening of breast cancer patients.
10.Therapeutic effects of the NLRP3 inflammasome inhibitor N14 in the treatment of gouty arthritis in mice
Xiao-lin JIANG ; Kai GUO ; Yu-wei HE ; Yi-ming CHEN ; Shan-shan DU ; Yu-qi JIANG ; Zhuo-yue LI ; Chang-gui LI ; Chong QIN
Acta Pharmaceutica Sinica 2024;59(5):1229-1237
Monosodium urate (MSU)-induced the gouty arthritis (GA) model was used to investigate the effect of Nod-like receptor protein 3 (NLRP3) inhibitor N14 in alleviating GA. Firstly, the effect of NLRP3 inhibitor N14 on the viability of mouse monocyte macrophage J774A.1 was examined by the cell counting kit-8 (CCK-8) assay. The expression of mature interleukin 1

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