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.

Thrombosis is a key factor that increases the mortality rate of COVID-19 patients and causes long COVID sequelae. Guanxinning Tablet (GXNT), which is composed of Salvia miltiorrhiza and Ligusticum Chuanxiong, has significant antithrombotic activity, but the similarities and differences between its anti-conventional thrombus and microthrombus induced by COVID-19 remain unclear. In this paper, the main active components, potential targets and mechanisms of GXNT in the treatment of thrombus and microthrombus caused by COVID-19 were preliminarily revealed by using anti-platelet experiments in vitro, network pharmacology analysis, molecular docking technology and molecular biology experiments. The results of platelet aggregation and adhesion experiments in vitro showed that GXNT had significant anti-platelet aggregation and adhesion activities in a dose-dependent manner. Using network pharmacology analysis, it was revealed that salvianolic acid B, tanshinone IIA, caffeic acid and ligustrazine in GXNT could resist thrombus and microthrombus caused by COVID-19 through key targets as the high mobility group box 1 protein (HMGB1), tumor necrosis factor (TNF), interleukin 6 (IL6) and AKT serine/threonine kinase 1 (AKT1). HMGB1 signaling pathway is one of its key common mechanisms. Western blot also indicated that GXNT significantly inhibited the expression of HMGB1 protein in platelets. In summary, this paper explores the similarities and differences between the mechanism of GXNT against conventional thrombus and microthrombus caused by COVID-19 and provides drug reference and theoretical basis for clinical prevention and treatment of long COVID sequelae. The animal experiment has been approved by the Experimental Animal Ethics Committee of Tianjin University of Traditional Chinese Medicine (No. TCM-LAEC2023187g1549).

Objective:To investigate the effect of selenium on cyclophosphamide(CTX)-induced spermatogenic impairment(SI)in mice and its underlying mechanism.Methods:We equally randomized 36 male KM mice into 3 SI model and 3 control groups,the first 3 treated by intraperitoneal injection of CTX at 100 mg/kg(the SI model control group),CTX plus SI model control group,selenium deficient model group(-Se SI),selenium supplemented model group(+Se SI),while latter 3 by intraperitoneal injection of normal saline(the normal control),selenium deficiency control group(-Se control),selenium addition control group(+Se control),respectively,all once a week for 6 successive weeks.Then we observed the histopathological changes in the testes of all the mice by HE staining,obtained the sperm count in the epididymides,determined the expressions of glutathione peroxidase 4(GPx4)and SLC7A11 proteins by Western blot and ferroptosis-related genes by RT-qPCR,and examined the changes in the expres-sions of ferroptosis-related proteins and genes in the GC2-spd cells treated with ferroptosis inhibitors and inducers in combination with different concentrations of inorganic sodium selenite(SeS)and organic selenomethionine(SeM).Results:Compared with the nor-mal controls,the SI model mice showed significantly decreased testicular and prostatic organ coefficients,reduced spermatogenic lay-ers,increased voids,decreased serum ferritin concentration(P<0.05),and elevated transferrin concentration(P<0.05).The or-gan coefficients were significantly higher in the+Se SI and+Se control than in the-Se SI and-Se control groups(P<0.05,P<0.01),with evident pathological improvement of the testis tissue in the+Se controls.The expressions of the GPx4 and solute carrier family 7 members 11(SLC7A11)genes in the testis were dramatically down-regulated in the SI model controls(P<0.01),but up-reg-ulated in the+Se SI and+Se control compared with those in the-Se SI and-Se control group(P<0.01 and P<0.05),but there were no statistically significant differences between their protein expressions.The results of in vitro GC2 spd cell experiments indicated that the GPx4 gene and GPx4 protein levels in the-Se group were significantly lower than those in the normal control group(P<0.05),while the SLC7A11 gene level decreased(P<0.01).Different doses of SeS and SeM significantly increased the GPx4 protein expression compared to the average Se group.Low doses of SeM promoted a significant increase in GPx4 gene levels,while high doses of SeS increased the expression levels of SLC7A11 gene and SLC7A11 protein(P<0.05,P<0.01).The Se group showed a signifi-cant decrease in the levels of acsl4 and ptgs2 genes compared to the normal control group.SeM promoted the expression of acsl4,while SeS promoted the expression of ptgs2 and fth1(P<0.01,P<0.05).The intervention results of GC2 spd showed that the Erastin group had a decrease in ptgs2 compared to the normal control group,while the SeS+Erastin and SeM+Erastin groups had an increase in ptgs2 gene expression compared to the Erastin group.However,the ptgs2 expression of Fer-1 was lower than that of the normal con-trol group,and the ptgs2 gene level of SeS+Fer-1 and SeM+Fer-1 groups was lower than that of Fer-1 group(P<0.05);The gene quantity of GPx4 in the SeM+Erastin and SeM+Fer-1 groups increased compared to the Erastin and Fer-1 groups(P<0.01,P<0.05);SeM+Erastin and SeS+Erastin showed a decrease in SLC7A11 compared to the Erastin group,as well as SeM+Fer-1 and SeS+Fer-1 groups compared to the Fer-1 group,accompanied by an increase in acsl4 and fth1(P<0.01).Conclusion:Selenium deficiency causes the reduction of the SLC7A11 and GPx4 gene levels,disorder of ferroptosis-related genes and down-regulation of the GPx4 protein expression in the mouse testis and spermatocytes.Selenium can promote the expression of GPx4,up-regulate the level of SLC7A11,and improve spermatogenesis in the testis of the mouse with SI.There are differences between organic SeM and inorganic SeS in regulating the ferroptosis pathway-related genes.

Objective To summarize the reasons and management strategies of reoperation after oblique lateral interbody fusion(OLIF),and put forward preventive measures.Methods From October 2015 to December 2019,23 patients who under-went reoperation after OLIF in four spine surgery centers were retrospectively analyzed.There were 9 males and 14 females with an average age of(61.89±8.80)years old ranging from 44 to 81 years old.The index diagnosis was degenerative lumbar intervertebral dics diseases in 3 cases,discogenie low back pain in 1 case,degenerative lumbar spondylolisthesis in 6 cases,lumbar spinal stenosis in 9 cases and degenerative lumbar spinal kyphoscoliosis in 4 cases.Sixteen patients were primarily treated with Stand-alone OLIF procedures and 7 cases were primarily treated with OLIF combined with posterior pedicle screw fixation.There were 17 cases of single fusion segment,2 of 2 fusion segments,4 of 3 fusion segments.All the cases underwent reoperation within 3 months after the initial surgery.The strategies of reoperation included supplementary posterior pedicle screw instrumentation in 16 cases;posterior laminectomy,cage adjustment and neurolysis in 2 cases,arthroplasty and neuroly-sis under endoscope in 1 case,posterior laminectomy and neurolysis in 1 case,pedicle screw adjustment in 1 case,exploration and decompression under percutaneous endoscopic in 1 case,interbody fusion cage and pedicle screw revision in 1 case.Visu-al analogue scale(VAS)and Oswestry disability index(ODI)index were used to evaluate and compare the recovery of low back pain and lumbar function before reoperation and at the last follow-up.During the follow-up process,the phenomenon of fusion cage settlement or re-displacement,as well as the condition of intervertebral fusion,were observed.The changes in in-tervertebral space height before the first operation,after the first operation,before the second operation,3 to 5 days after the second operation,6 months after the second operation,and at the latest follow-up were measured and compared.Results There was no skin necrosis and infection.All patients were followed up from 12 to 48 months with an average of(28.1±7.3)months.Nerve root injury symptoms were relieved within 3 to 6 months.No cage transverse shifting and no dislodgement,loosening or breakage of the instrumentation was observed in any patient during the follow-up period.Though the intervertebral disc height was obviously increased at the first postoperative,there was a rapid loss in the early stage,and still partially lost after reopera-tion.The VAS for back pain recovered from(6.20±1.69)points preoperatively to(1.60±0.71)points postoperatively(P＜0.05).The ODI recovered from(40.60±7.01)％preoperatively to(9.14±2.66)％postoperatively(P＜0.05).Conclusion There is a risk of reoperation due to failure after OLIF surgery.The reasons for reoperation include preoperative bone loss or osteoporosis the initial surgery was performed by Stand-alone,intraoperative endplate injury,significant subsidence of the fusion cage after surgery,postoperative fusion cage displacement,nerve damage,etc.As long as it is discovered in a timely manner and handled properly,further surgery after OLIF surgery can achieve better clinical results,but prevention still needs to be strengthened.

Tubulin beta 4A class IVa (TUBB4A) spectrum disorders include autosomal dominant dystonia type 4 or hypomyelination with atrophy of the basal ganglia and cerebellum (H-ABC syndrome). However, in rare cases, only mild hypomyelination in the cortex with no basal ganglia atrophy may be observed. We report a case of a family with TUBB4A mutation and complicated hereditary spasticity paraplegia (HSP). We performed quadro whole-exome sequencing (WES) on the family to identify the causative gene of progressive spastic paraparesis with isolated hypomyelination leukodystrophy. We identified a novel TUBB4A p.F341L mutation, which was present in all three affected patients but absent in the unaffected father. The affected patients presented with adult-onset TUBB4A disorder, predominant spastic paraparesis with/without ataxia, and brain hypomyelination with no cognitive impairment or extrapyramidal symptoms. In the literature, HSP is considered a TUBB4A spectrum disorder.

Mutations in the synaptic nuclear envelope protein 1 (SYNE1) gene are associated with substantial clinical heterogeneity. Here, we report the first case of SYNE1 ataxia in Taiwan due to two novel truncating mutations. Our patient, a 53-year-old female, exhibited pure cerebellar ataxia with c.1922del in exon 18 and c. C3883T mutations in exon 31. Previous studies have indicated that the prevalence of SYNE1 ataxia among East Asian populations is low. In this study, we identified 27 cases of SYNE1 ataxia from 22 families in East Asia. Of the 28 patients recruited in this study (including our patient), 10 exhibited pure cerebellar ataxia, and 18 exhibited ataxia plus syndromes. We could not find an exact correlation between genotypes and phenotypes. Additionally, we established a precise molecular diagnosis in our patient’s family and extended the findings on the ethnic, phenotypic, and genotypic diversity of the SYNE1 mutational spectrum.