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 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

ObjectiveTo explore the scientific connotation of fried charcoal survivability of Lonicerae Japonicae Flos（LJF） by analyzing the correlation between the color change and the intrinsic components during the processing of LJF Carbonisata（LJFC）， and taking pH， charcoal adsorption and microscopic characteristics as indexes. MethodLJFC samples with different degrees of processing were prepared according to the stir-frying time of 0.0， 1.5， 3.0， 4.5， 6.0， 7.5， 9.0， 10.5 min（numbered S1-S8）， and the contents of gallic acid， chlorogenic acid， cryptochlorogenic acid， rutin， luteoloside， isochlorogenic acid A and isochlorogenic acid C were determined by high performance liquid chromatography（HPLC）， and the L^*（brightness）， a^*（red-greenness） and b^*（yellow-blueness） of LJFC samples with different degrees of processing were determined by spectrophotometer， and the correlation analysis and principal component analysis（PCA） between the contents of seven representative components and the color of the samples were carried out by SPSS 26. 0 and SIMCA-P 14.1. Then pH， adsorption force and characteristic structure of different samples of LJFC were detected and the processing pattern of LJFC was analyzed. ResultThe results of quantitative analysis revealed that the contents of luteoloside， rutin， chlorogenic acid and isochlorogenic acid A gradually decreased， and the contents of cryptochlorogenic acid， isochlorogenic acid C and gallic acid firstly increased and then decreased. The L^* and b^* of the sample powders decreased， and a^* showed a trend of increasing and then decreasing. The L^* and b^* were positively correlated with the contents of chlorogenic acid， rutin， luteoloside， isochlorogenic acid A， b^* was positively correlated with the content of gallic acid， and a^* was positively correlated with the contents of cryptochlorogenic acid and isochlorogenic acid C. PCA revealed that samples could be clearly divided into 3 groups， S1-S2 as one group， S3-S5 as one group， and S6-S8 as one group， with S3 having the highest score. The results of regression analysis showed that only isochlorogenic acid C could be used to predict the contents of components by colorimetric values combined with regression equations. Physicochemical analysis showed that pH of LJFC increased with the increase of degree of charcoal stir-frying， while adsorption force showed a tendency of increasing and then decreasing， with the highest adsorption force in the S5 sample， and the non-glandular hairs， calcium oxalate clusters and pollen grains had a varying degree of decreasing with the deepening of processing degree， and the microstructures of S6-S8 samples were obviously charred with pollen grains almost invisible. ConclusionThe changes in chemical composition and color characteristics of LJFC during the processing have certain correlations， combined with the changes in physicochemical properties， S5 sample is found to be the optimal processed products， which can provide a reference for the processing standardization and quality evaluation of LJFC， and enrich the scientific connotation of fried charcoal survivability of LJF.

Objective:To explore the repairing effect and mechanism of tangeretin in rats with spinal cord injury.Methods:The rats were divided into sham-operation group, model group and tangeretin group according to random number table, with 8 rats in each group. Except for the sham-operation group, Allen hit method was used to make rat models in the other groups. After the model was successfully established, the tangeretin group was intragastrically administered with tangeretin 50 mg/kg, and the sham-operation group and the model group were intragastrically administered with an equal volume of normal saline once a day for 14 days. On days 0, 3, 7, and 14 after modeling, the motor function recovery of rats was assessed using the Basso-Beattie-Bresnahan (BBB) score; the morphological changes of the spinal cord tissues were observed using HE staining and Nissl staining; the SOD and GSH activities and MDA, IL-1β, TNF-α, and IL-10 levels in the spinal cord tissues of rats in each group were measured using ELISA kit detection; the GFAP and Neun expressions in the spinal cord tissues were detected by immunofluorescence; the IL-1β, TNF-α, IL-10, nuclear factor E2-related factor 2 (Nrf-2), and NAD (P) H-quinone oxidoreductase 1 (NQO-1) expressions in the spinal cord tissues were detected by Western blot.Results:Compared with the model group, the BBB score increased in the tangeretin group ( P<0.05), HE staining score decreased ( P<0.05), and the number of Nissl bodies increased ( P<0.05); the level of IL-10, SOD and GSH activities increased ( P<0.05), and IL-1β, TNF-α and MDA levels decreased in the spinal cord tissue ( P<0.05); GFAP fluorescence intensity decreased ( P<0.05) and NeuN fluorescence intensity increased ( P<0.05); the relative expression of IL-1β and TNF-α decreased ( P<0.05), and the relative expressions of IL-10, Nrf-2 and NQO-1 protein increased ( P<0.05). Conclusions:Tangeretin can exert anti-inflammatory and anti-oxidative stress effects through the Nrf2/NQO1 signaling pathway and alleviate early spinal cord injury in rats. On the other hand, it may promote the recovery of spinal cord injury by reducing glial scar generation and promoting neural cellogenesis.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

This study was aimed at creating an engineered strain of Bacillus subtilis for efficient expression of biologically active type 2 toxin B(TcdB2)derived from a highly virulent strain of Clostridium difficile.The TcdB2 gene was cloned from ST1/RT027 strain genome DNA,incorporated into the PHT01 vector,and then transformed into B.subtilis strain WB800N for prokaryotic expression.Cell toxicity assays revealed that the recombinant TcdB2 exhibited cytotoxic effects in various cells.The engineered B.subtilis strain effectively expressed biologically active TcdB2,thus providing a basis for further exploration of the pathogenic mechanisms of highly virulent strains of C.difficile and establishing a foundation for potential vaccine can-didate targets.