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.

This study aims to explore the effects and mechanisms of the traditional Chinese medicine Cordyceps sinensis(CS) in ameliorating heart aging and injury in mice based on animal experiments and network pharmacology. A mouse model of heart aging was established by continuously subcutaneous injection of D-galactose(D-gal). Thirty mice were randomly assigned into a normal group, a model group, a low-dose CS(CS-L) group, a high-dose CS(CS-H) group, and a vitamin E(VE) group. Mice in these groups were administrated with normal saline, different doses of CS suspension, or VE suspension via gavage daily. After 60 days of treatment with D-gal and various drugs, all mice were euthanized, and blood and heart tissue samples were collected for determination of the indicators related to heart aging and injury in mice. Experimental results showed that both high and low doses of CS and VE ameliorated the aging phenotype, improved the heart index and myocardial enzyme spectrum, restored the expression levels of proteins associated with cell cycle arrest and senescence-associated secretory phenotypes(SASP), and alleviated the fibrosis and histopathological changes of the heart tissue in model mice. From the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP),259 active ingredients of CS were retrieved. From Gene Cards and OMIM, 2 568 targets related to heart aging were identified, and 133common targets shared by CS and heart aging were obtained. The Gene Ontology(GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes( KEGG) pathway enrichment revealed that the pathways related to heart aging involved oxidative stress,apoptosis, inflammation-related signaling pathways, etc. The animal experiment results showed that both high and low doses of CS and VE ameliorated oxidative stress and apoptosis in the heart tissue to varying degrees in model mice. Additionally, CS-H and VE activated the nuclear factor E2-related factor 2(Nrf2)/heme oxygenase-1(HO-1) pathway and inhibited the expression of key proteins in the nuclear factor-κB(NF-κB) pathway in the heart tissue of model mice. In conclusion, this study demonstrated based on network pharmacology and animal experiments that CS may alleviate heart aging and injury in aging mice by reducing oxidative stress,apoptosis, and inflammation in the heart via the Nrf2/HO-1/NF-κB pathway.
Animals ; Cordyceps/chemistry* ; Mice ; NF-E2-Related Factor 2/genetics* ; NF-kappa B/genetics* ; Aging/genetics* ; Male ; Signal Transduction/drug effects* ; Network Pharmacology ; Drugs, Chinese Herbal/pharmacology* ; Heme Oxygenase-1/genetics* ; Heart/drug effects* ; Humans ; Myocardium/metabolism* ; Membrane Proteins/genetics*

OBJECTIVE: A new three-dimensional(3D) classification of posterior cruciate ligament (PCL) tibial avulsion fracture based on computed tomography(CT) features was established and the significance in clinical treatment was explored in this study. METHODS: From May 2013 to November 2023, 43 cases of PCL tibial avulsion fracture in the Second Hospital of Jilin University were analyzed retrospectively, including 29 males and 14 females, aged (34.3±8.5) years. According to traditional Meyers and McKeever classification, 3 cases were typeⅠ;2 cases of typeⅡ;38 cases were type Ⅲ. Based on the characteristics of CT images, 43 patients were given specific treatment strategies and followed up to evaluate the curative effect. According to the degree of fracture displacement, involved range and the integrity of fracture block demonstrated by CT images, the new three-dimensional classification of PCL avulsion fracture was established. Kappa coefficient was used for consistency test. RESULTS: A new 3D classification of PCL tibial avulsion fracture was established. TypeⅠwas the non-displaced fracture (displacement degree ≤3 mm), in which typeⅠa was the avulsion range limited in the posterior intercondylar fossa, and Ib was the avulsion range beyond the posterior intercondylar fossa. TypeⅡrepresented the displaced fracture in the posterior intercondylar fossa (avulsion limited to the posterior intercondylar fossa and fracture displacement>3 mm), in which typeⅡa represented a slight displacement with a intact broken block and the posterior elevation of the avulsion (hinge mechanism), typeⅡb represented the complete separation of fracture ends with a intact fracture block, and typeⅡc was the comminuted fracture. Type Ⅲ was the displaced fracture beyond the posterior intercondylar fossa (avulsion involving the articular surface of the tibial plateau or the intercondylar ridge and the degree of displacement > 3 mm), among which type Ⅲa was the simple fracture with intact broken block, type Ⅲb represented the comminuted fracture, and type Ⅲc was the complex fracture with tibial plateau fracture. According to this new 3D classification, 43 patients were classified as type Ia in 2 cases and typeⅠb in 1 case;typeⅡa in 2 cases, typeⅡb in 15 cases and typeⅡc in 7 cases;type Ⅲa in 2 cases, type Ⅲb in 5 cases and type Ⅲc in 9 cases. All the 43 cases in this study achieved bone union. At the last follow-up, according to the hospital for special surgery knee score(HSS)evaluation system for the knee joint function, 27 cases were excellent, 11 cases were good, 5 cases were fair. The average Kappa value of inter-observer reliability in the first stage was 0.793, and the second stage was 0.855. The average Kappa value of the whole stage was 0.839, indicating high level of consistency. The average Kappa value of intra-observer reliability was 0.893, indicating high level of consistency. CONCLUSION The 3D classification of PCL tibial avulsion fracture is intuitive, demonstrating a high level of reliability. It has a certain guiding significance for the selection of clinical treatment methods, and it is suggested to be promoted and applied as a new classification system in clinical practice.
Humans ; Male ; Female ; Posterior Cruciate Ligament/surgery* ; Adult ; Tibial Fractures/classification* ; Tomography, X-Ray Computed ; Middle Aged ; Retrospective Studies ; Fractures, Avulsion/classification* ; Imaging, Three-Dimensional ; Young Adult

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

OBJECTIVE: To establish venetoclax-resistant acute myeloid leukemia (AML) cell lines, assess the sensitivity of venetoclax-resistant cell lines to the BCL-2 protein family, and investigate their resistance mechanisms. METHODS: CCK-8 method was used to screen AML cell lines (MV4-11, MOLM13, OCI-AML2) that were relatively sensitive to venetoclax. Low concentrations of venetoclax continuously induced drug-resistance development in the cell lines. Changes in cell viability and apoptosis rate before and after resistance development were measured using the CCK-8 method and flow cytometry. BH3 profiling assay was performed to anayze the transform of mitochondrion-dependent apoptosis pathway as well as the sensitivity of resistant cell lines to BCL-2 family proteins and small molecule inhibitors. Real-time fluorescence quantitative PCR (RT-qPCR) was utilized to examine changes in the expression levels of BCL-2 protein family members in both venetoclax-resistant cell lines and multidrug-resistant patients. RESULTS: Venetoclax-resistant cell lines of MV4-11, MOLM13, and OCI-AML2 were successfully established, with IC₅₀ values exceeding 10-fold. Under the same concentration of venetoclax, the apoptosis rate of resistant cells decreased significantly (P < 0.05). BH3 profiling assay revealed that the drug-resistant cell lines showed increased sensitivity to many pro-apoptotic proteins (such as BIM,BID and NOXA). RT-qPCR showed significantly upregulated MCL1 and downregulated NOXA1 were detected in drug-resistant cell lines. Expression changes in MCL1 and NOXA1 in venetoclax-resistant patients were consistent with our established drug-resistant cell line results. CONCLUSION The venetoclax-resistant AML cell lines were successfully established through continuous induction with low concentrations of venetoclax. The venetoclax resistance resulted in alterations in the mitochondrial apoptosis pathway of the cells and an increased sensitivity of cells to pro-apoptotic proteins BIM, BID, and NOXA, which may be associated with the upregulation of MCL1 expression and downregulation of NOXA1 expression in the drug-resistant cells.
Humans ; Sulfonamides/pharmacology* ; Drug Resistance, Neoplasm ; Bridged Bicyclo Compounds, Heterocyclic/pharmacology* ; Leukemia, Myeloid, Acute/pathology* ; Proto-Oncogene Proteins c-bcl-2/metabolism* ; Cell Line, Tumor ; Apoptosis ; Antineoplastic Agents/pharmacology*

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*