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.

ObjectiveTo analyze the expression level of triggering receptor expressed on myeloid cells-1 （TREM-1） in serum and ascites of patients with cirrhotic ascites， and to investigate its correlation with clinical features and inflammatory markers and its role in the diagnosis of infection and prognostic evaluation. MethodsA total of 110 patients with cirrhotic ascites who were hospitalized in The Fifth Hospital of Shijiazhuang from January 2019 to December 2020 were enrolled， and according to the presence or absence of intra-abdominal infection， they were divided into infection group with 72 patients and non-infection group with 38 patients. The patients with infection were further divided into improvement group with 38 patients and non-improvement group with 34 patients. Clinical data and laboratory markers were collected from all patients. Serum and ascites samples were collected， and ELISA was used to measure the level of TREM-1. The independent-samples t test was used for comparison of normally distributed continuous data between two groups； the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups， and the Kruskal-Wallis H test was used for comparison between multiple groups； the chi-square test was used for comparison of categorical data between two groups. A Spearman correlation analysis was used to investigate the correlation between indicators. A multivariate Logistic regression analysis was used to identify the influencing factors for the prognosis of patients with cirrhotic ascites and infection. The receiver operating characteristic （ROC） curve was used to evaluate the diagnostic and prognostic efficacy of each indicator， and the Delong test was used for comparison of the area under the ROC curve （AUC）. ResultsThe level of TREM-1 in ascites was significantly positively correlated with that in serum （r=0.50， P<0.001）. Compared with the improvement group， the non-improvement group had a significantly higher level of TREM-1 in ascites （Z=-2.391， P=0.017） and serum （Z=-2.544， P=0.011）， and compared with the non-infection group， the infection group had a significantly higher level of TREM-1 in ascites （Z=-3.420， P<0.001）， while there was no significant difference in the level of TREM-1 in serum between the two groups （P>0.05）. The level of TREM-1 in serum and ascites were significantly positively correlated with C-reactive protein （CRP）， procalcitonin （PCT）， white blood cell count， and neutrophil-lymphocyte ratio （r=0.288， 0.344， 0.530， 0.510， 0.534， 0.454， 0.330， and 0.404， all P<0.05）. The ROC curve analysis showed that when PCT， CRP， and serum or ascitic TREM-1 were used in combination for the diagnosis of cirrhotic ascites with infection， the AUCs were 0.715 and 0.740， respectively. The multivariate Logistic regression analysis showed that CRP （odds ratio ［OR］=1.019， 95% confidence interval ［CI］： 1.001‍ ‍—‍ ‍1.038， P=0.043） and serum TREM-1 （OR=1.002， 95%CI： 1.000‍ ‍—‍ ‍1.003， P=0.016） were independent risk factors for the prognosis of patients with cirrhotic ascites and infection， and the combination of these two indicators had an AUC of 0.728 in predicting poor prognosis. ConclusionThe level of TREM-1 is closely associated with the severity of infection and prognosis in patients with cirrhotic ascites， and combined measurement of TREM-1 and CRP/PCT can improve the diagnostic accuracy of infection and provide support for prognostic evaluation.

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.

Ischemic stroke(IS)is a devastating neurological disease commonly around the world.Although modern medicine has recognized the confined mechanisms in the pathological process of cerebral ischemia,it has never been enough for the treatment of IS.Recent studies have confirmed the vital role of mitochondrial dysfunction in neuronal injury after cerebral ische-mia,thereby exerting a potential target for prevention and treat-ment of IS.Herein,we review the main molecular mechanisms of neuronal injury and death by mitochondrial dyshomeostasis under the condition of ischemia/hypoxia,especially mitochon-drial permeability transition pore opening,oxidative stress and apoptotic signaling.Given remodeling of mitochondrial function as a new idea for the management of IS,some emerging strate-gies containing mitochondrial antioxidant,mitophagy regulation and mitochondrial transfer also raise concern in this paper.

Objective CT scans combined with Mimics software were used to measure femoral offset(FO),rotation center height(RCH)and lower leg length discrepancy(LLD)following total hip arthroplasty(THA),and the relationship between FO,RCH and LLD after THA is discussed.Methods Retrospective analysis was performed on 40 patients with unilateral THA who met standard cases from October 2020 to June 2022.There were 21 males and 19 females,18 patients on the left side and 22 patients on the right side,aged range from 30 to 81 years old,with an average age of(58.90±14.13)years old,BMI ranged from 17.3 to 31.5 kg·m-2withan average of(25.3±3.4)kg·m-2.There were 30 cases of femoral head necrosis(Ficattype Ⅳ),2 cases of hip osteoarthritis(Tonnis type Ⅲ),2 cases of developmental hip dislocation combined with end-stage osteoarthritis(Crowe type Ⅲ),and 6 cases of femoral neck fracture(Garden type Ⅳ).Three-dimensional CT reconstruction of pelvis was taken preoperative and postoperative,and three-dimensional reconstruction model was established after processing by Mimics software.FO,RCH and LLD were measured on the model.The criteria for FO reconstruction were as follows:postoperative bi-lateral FO difference less than 5 mm;the standard for equal length of both lower limbs was as follows:postoperative LLD differ-ence less than 5 mm.Results Bilateral FO difference was positively correlated with LLD(r=0.744,P＜0.00l).Chi-square test was performed between the FO reconstructed group and the non-reconstructed eccentricity group:The results showed that the i-sometric ratio of lower limbs in the FO reconstructed group was significantly higher than that in the FO reconstructed group(x2=6.320,P=0.012).The bilateral RCH difference was significantly negatively correlated with LLD(r=-0.877,P＜0.001).There is a linear relationship between bilateral FO difference and bilateral RCH difference and postoperative LLD,and the lin-ear regression equation is satisfied:postoperative LLD=0.038x-0.099y+0.257(x:postoperative bilateral FO difference,y:post-operative bilateral RCH difference;Unit:cm),F=77.993,R2=0.808,P=0.009.Conclusion After THA,LLD increased with the increase of FO and decreased with the increase of RCH.The effect of lower limb isometric length can be obtained more easily by reconstruction of FO.There is a linear relationship between the bilateral FO difference and the bilateral RCH difference after THA and LLD,and the regression equation can provide a theoretical reference forjudging LLD.

Objective To explore clinical effect of vancomycin calcium sulfate combined with internal fixation on cal-caneal beak-like fracture secondary to calcaneal osteomyelitis caused by diabetic foot.Methods From April 2018 to October 2021,a retrospective analysis was performed on 5 patients with calcaneal bone osteomyelitis secondary to diabetic foot,includ-ing 2 males and 3 females,aged from 48 to 60 years old;diabetes course ranged from 5 to 13 years;the courses of diabetic foot disease ranged from 18 to 52 days;5 patients were grade Ⅲ according to Wagner classification.All patients were treated with debridement,vancomycin bone cement implantation,negative pressure aspiration at stage Ⅰ,vancomycin calcium sulfate and internal fixation at stage Ⅱ for calcaneal beak-like fracture.Surgical incision and fracture healing time were recorded,and the recurrence of osteomyelitis was observed.American Orthopedic Foot Andankle Society(AOFAS)score and exudation at 12 months after operation were evaluated.Results Five patients were successfully completed operation without lower extremity vascular occlusion,and were followed up for 16 to 36 months.The wound healing time after internal fixation ranged from 16 to 26 days,and healing time of fractures ranged from 16 to 27 weeks.AOFAS score ranged from 65 to 91 at 12 months after oper-ation,and 2 patients got excellent result,2 good and 1 fair.Among them,1 patient with skin ulcer on the back of foot caused by scalding at 5 months after operation(non-complication),was recovered after treatment;the wound leakage complication oc-curred in 2 patients,and were recovered after dressing change.No osteomyelitis or fracture occurred in all patients.Conclusion Vancomycin calcium sulfate with internal fixation in treating calcaneal osteomyelitis secondary to calcaneal osteomyelitis caused by diabetic foot could not only control infection,but also promote fracture healing,and obtain good clinical results.

Objective To compare clinical efficacy of robot-assisted(RA)and remote sensing navigation alignment(RSNA)system-assisted total knee arthroplasty(TKA).Methods From March 2023 to June 2023,60 patients who underwent the first unilateral TKA due to severe knee osteoarthritis(KOA)were admitted and divided into RSNA group and RA group according to different treatment methods,with 30 patients in each group.There were 5 males and 25 females in RSNA group,aged from 56 to 81 years old with an average of(66.33±7.16)years old;body mass index(BM1)ranged from 19.87 to 38.54 kg·m-2 with an average of(28.40±6.18)kg·m-2;the courses of disease ranged from 5 to 36 months with an average of(18.20±8.98)months;RSNA system was used to assist the positioning of osteotomy.There were 7 males and 23 females in RA group,aged from 55 to 82 years old with an average of(67.83±8.61)years old;BMI ranged from 19.67 to 37.25 kg·m-2 with an aver-age of(28.01±4.89)kg·m-2;the courses of disease ranged from 3 to 33 months with an average of(17.93±9.20)months;RA was performed.Operation time,incision length,latent blood loss at 2 weeks after operation and incidence of lower extremity thrombosis were compared between two groups.Hip-knee ankle angle(HKAA),HKAA deviation,lateral distal femoral angle(LDFA),medial proximal tibial angle(MPTA)and posterior tibial slope(PTS)were compared between two groups;Western Ontario McMaster Universities Osteoarthritis Index(WOMAC)and Knee Society score(KSS)were used to evaluate functional recovery before operation,3 and 6 months after operation.Results The operation was performed successfully in both groups,and there were no serious complications such as vascular and nerve injury during operation.The wound healed well at stage Ⅰafter operation,and the follow-up time was 6 months.The operation time,latent blood loss at 2 weeks after operation and inci-sion length in RSNA group were(94.35±5.75)min,(130.54±17.53)mland(14.73±2.14)cm,respectively;while(102.57±6.88)min,(146.33±19.47)ml and(16.78±2.32)cm in RA group,respectively.RSNA group was better than RA group(P＜0.05).No deep vein thrombosis occurred in both groups at 2 weeks after operation,5 patients occurred intermuscular vein throm-bosisin in RSNA group and 8 patients in RA group,the difference was not statistically significant(P＞0.05).In RSNA group,HKAA,LDFA and MPTA were(173.00±5.54)°,(86.96±3.45)°,(82.79±3.35)° before operation,and(178.34±1.85)°,(89.92±0.42)°,(89.84±0.73)° at 1 week after operation,respectively.In RA group,HKAA,LDFA and MPTA were(173.31±6.48)°,(87.15±3.40)° and(82.99±3.05)° before operation,and(178.52±1.79)°,(90.03±0.39)° and(90.15±0.47)° at 1 week after operation,respectively.HKAA,LDFA and MPTA were significantly improved in both groups at 1 week after oper-ation(P＜0.05).There were no significant difference in HKAA,LDFA,MPTA and PTS between two groups before operation and 1 week after operation(P＞0.05).There was no significant difference in deviation distribution of HKAA at 1 week after op-eration(x2=2.61 1,P=0.456).There were no significant difference in WOMAC and KSS between two groups before operation,3 and 6 months after operation(P＞0.05),and postoperative WOMAC and KSS at 3 and 6 months between two groups were im-proved compared with those before operation(P＜0.05).Conclusion Both RA and RSNA system assisted TKA could obtain ac-curate osteotomy,RA has higher surgical accuracy,RSNA system assisted operation has less trauma,and operation is simpler.