BACKGROUND:Multiple observational studies have suggested a potential association between telomere length and musculoskeletal diseases.However,the underlying mechanisms remain unclear. OBJECTIVE:To investigate the genetic causal relationship between telomere length and musculoskeletal diseases using two-sample Mendelian randomization analysis. METHODS:Genome-wide association study summary data of telomere length were obtained from the UK Biobank.Genome-wide association study summary data of 10 common musculoskeletal diseases(osteonecrosis,osteomyelitis,osteoporosis,rheumatoid arthritis,low back pain,spinal stenosis,gout,scapulohumeral periarthritis,ankylosing spondylitis and deep venous thrombosis of lower limbs)were obtained from the FinnGen consortium.Inverse variance weighting,Mendelian randomization-Egger and weighted median methods were used to evaluate the causal relationship between telomere length and 10 musculoskeletal diseases.Inverse variance weighting was the primary Mendelian randomization analysis method,and sensitivity analysis was performed to explore the robustness of the results. RESULTS AND CONCLUSION:(1)Inverse variance-weighted results indicated a negative causal relationship between genetically predicted telomere length and rheumatoid arthritis(odds ratio=0.78,95%confidence interval:0.64-0.95,P=0.015)and osteonecrosis(odds ratio=0.56,95%confidence interval:0.36-0.90,P=0.016).No causal relationship was found between telomere length and the other eight musculoskeletal diseases(all P>0.05).(2)Sensitivity analysis affirmed the robustness of these causal relationships,and Mendelian randomization-Egger intercept analysis found no evidence of potential horizontal pleiotropy(all P>0.05).(3)This Mendelian randomized study supports that telomere length has protective effects against rheumatoid arthritis and osteonecrosis.However,more basic and clinical research will be needed to support our findings in the future.

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 effectiveness of Ilizarov technique combined with steel needle internal fixation in treating Charcot neuroarthropathy (CN) of the foot and ankle. METHODS: Between June 2020 and December 2023, 12 patients with Eichenholtz stage Ⅲ CN of the foot and ankle were treated with Ilizarov technique and steel needle internal fixation. There were 9 males and 3 females with an average age of 48.6 years (range, 19-66 years). The disease duration ranged from 1 to 16 months (mean, 6.8 months). Ankle joint involvement predominated in 7 cases, while midfoot involvement occurred in 5 cases; 3 cases presented with skin ulceration and soft tissue infection. Preoperative American Orthopedic Foot and Ankle Society (AOFAS) score was 31.2±9.0, 36-Item Short-Form Health Survey (SF-36)-Physical Component Summary (PCS) score was 32.6±6.8, and Mental Component Summary (MCS) score was 47.8±8.4. Postoperative assessments included wound healing, regular X-ray film/CT evaluations of fusion status, and effectiveness via AOFAS and SF-36-PCS, MCS scores. RESULTS: All operations were successfully completed without neurovascular complication. Two patients experienced delayed wound healing requiring intervention, and the others achieved primary healing. All patients were followed up 15-43 months (mean, 23.3 months). Imaging confirmed successful joint fusion within 13-21 weeks (mean, 16.8 weeks). At last follow-up, the AOFAS score was 72.5±6.4, and the SF-36-PCS and MCS scores were 63.2±8.4 and 76.7±5.3, respectively, all of which improved compared to preoperative levels, with significant differences ( P<0.05). CONCLUSION Ilizarov technique combined with steel needle internal fixation effectively restores walking function and achieves satisfactory short-term effectiveness in CN of the foot and ankle.
Humans ; Middle Aged ; Male ; Female ; Adult ; Ilizarov Technique ; Arthropathy, Neurogenic/surgery* ; Aged ; Ankle Joint/surgery* ; Treatment Outcome ; Needles ; Fracture Fixation, Internal/instrumentation* ; Steel ; Young Adult ; Foot Joints/surgery*

The persistent high prevalence and poor survival outcomes of lung cancer underscore the urgent need for innovative therapeutic modalities. Here, we present a novel multifunctional delivery platform for the synergistic treatment of lung malignancies, combining in situ-triggerable photodynamic therapy (PDT) with radiotherapy. The new platform CLL was developed by loading a new reactive oxygen species (ROS)-triggerable photosensitizer, luminol-conjugated chlorin e6 (Ce6), into liposomes. CLL can be activated through the bioluminescence resonance energy transfer effect under oxidative stress, thereby producing singlet oxygen for targeted tumor treatment without external irradiation. In vitro studies showed significant cytotoxic effects of CLL in both 4T1 and A549 tumor cells. Furthermore, a PDT-radiopharmaceutical combination nanotherapy CLL-¹⁷⁷Lu was engineered by incorporating the radionuclide ¹⁷⁷Lu into CLL. CLL-¹⁷⁷Lu demonstrated synergistic antitumor effects in 4T1 and A549 tumor cells, as well as in mouse models of 4T1 breast cancer lung metastasis or A549 tumor xenografts. Mechanistically, CLL-¹⁷⁷Lu can induce singlet oxygen/ROS generation, enhance tumor cell apoptosis, and promote M1 macrophage-mediated immunotherapy. Preliminary assessments showed a favorable profile for CLL-¹⁷⁷Lu, highlighting its potential as a promising nanotherapy for cancer treatment. Additionally, CLL can serve as a versatile platform for delivering a range of therapies to achieve synergistic antitumor effects.

Simultaneous management of intestinal mucosal barrier dysfunction and gut microbiota dysregulation represents a significant challenge in the treatment of inflammatory bowel disease (IBD). Herein, we report a novel system that integrates multi-enzyme mimicking cerium single-atom nanocatalysts (CeSACs) with Lactobacillus reuteri probiotics (LR@CeSACs) for multipronged management of IBD. In this system, CeSACs demonstrate robust multi-enzyme activities across a broad pH range, effectively scavenging elevated reactive oxygen species, downregulating pro-inflammatory cytokines, and suppressing the expression of fibrosis-related genes. Moreover, probiotics promote the targeting and retention of the CeSACs for sustained catalytic antioxidant therapy. In turn, the inflammation relief enabled by CeSACs promotes bacterial viability, allowing for the rapid reshaping of intestinal barrier function and the restoration of gut microbiota. Therefore, LR@CeSACs exhibit excellent catalytic anti-inflammatory and anti-fibrotic therapeutic effects, as well as a certain prophylactic effect, as demonstrated in several murine models.

OBJECTIVE: To elucidate the role and mechanism of microRNA-145-5p (miR-145-5p) in hypoxia-induced pyroptosis of human alveolar epithelial cells. METHODS: In vitro, human alveolar epithelial cell line BEAS-2B was cultured. Cells in the logarithmic growth phase were cultured to 80% confluence and then used for the experiment. (1) BEAS-2B cells were cultured under 1% O₂ hypoxic condition, with a normoxic control group. Western blotting was employed to detect the expressions of pyroptosis marker proteins [NOD-like receptor protein 3 (NLRP3), Gasdermin D N-terminal domain (GSDMD-N), and caspase-1] in cells cultured for 24 hours. Real-time fluorescent quantitative reverse transcription-polymerase chain reaction (RT-PCR) was used to detect the expression of miR-145-5p in cells cultured for 6 hours and 12 hours. (2) Cells were transfected with 30 nmol/L miR-145-5p mimic to overexpress miR-145-5p expression under normoxic condition or 30 nmol/L miR-145-5p inhibitor to suppress miR-145-5p expression under hypoxic condition. Control group and negative control group were respectively set up. After 24 hours of cell culture, Western blotting was used to detect the expressions of pyroptosis marker proteins and nuclear factor-E2-related factor 2 (Nrf2) in cells. Flow cytometry was applied to detect the level of reactive oxygen species (ROS) in cells. The target genes of miR-145-5p were predicted by miR target gene prediction software miRWalk and verified by Western blotting. (3) Under hypoxic condition, cells were transfected with 6.94 ng/μL silent information regulator 5 (Sirt5) overexpression plasmid or pretreated with 12.5 mmol/L N-acetyl-L-cysteine (NAC) as an ROS inhibitor. The empty plasmid group and control group were set up. After 24 hours of cell culture, Western blotting was used to detect the expressions of Sirt5, Nrf2, and pyroptosis marker proteins in cells. Flow cytometry was used to detect the level of ROS in cells. RESULTS: (1) Compared with the normoxic control group, the expression levels of pyroptosis marker proteins in the 24-hour hypoxia group was significantly increased, indicating that hypoxia could induce pyroptosis in BEAS-2B cells. The expression level of miR-145-5p in cells gradually increased with the extension of hypoxia induction time, indicating that hypoxia could cause the increase of miR-145-5p expression level. (2) The expression levels of pyroptosis marker proteins in cells of miR-145-5p mimic group significantly increased under normoxic condition as compared with the control and negative control groups [NLRP3 protein (NLRP3/β-actin): 1.58±0.07 vs. 1.00±0.01, 0.98±0.07, GSDMD-N protein (GSDMD-N/β-actin): 1.71±0.03 vs. 1.01±0.01, 0.85±0.03, caspase-1 protein (caspase-1/β-actin): 2.33±0.04 vs. 1.01±0.01, 1.05±0.04, all P < 0.05], Nrf2 protein expression level was significantly decreased (Nrf2/β-actin: 0.79±0.03 vs. 1.00±0.01, 1.03±0.04, both P < 0.05), ROS level was significantly up-regulated (fluorescence intensity: 1.74±0.03 vs. 1.00±0.01, 0.92±0.03, both P < 0.05). Under hypoxia condition, compared with control group and negative control group, the expression levels of pyroptosis marker proteins in miR-145-5p inhibitor group were significantly decreased [NLRP3 protein (NLRP3/β-actin): 0.21±0.04 vs. 1.70±0.02, 1.63±0.04; GSDMD-N protein (GSDMD-N/β-actin): 1.32±0.02 vs. 2.51±0.02, 2.72±0.03; caspase-1 protein (caspase-1/β-actin): 0.56±0.01 vs. 2.77±0.02, 3.12±0.03; all P < 0.05], Nrf2 protein expression level was significantly increased (Nrf2/β-actin: 1.57±0.04 vs. 1.22±0.01, 1.28±0.04, both P < 0.05), ROS level was significantly down-regulated (fluorescence intensity: 0.64±0.05 vs. 1.87±0.04, 1.70±0.07, both P < 0.05). The results indicated that miR-145-5p could promote cell pyrodeath. The predictive result of miRWalk showed that the 3' untranslated region (3'UTR) of Sirt5 had complementary base binding sites with miR-145-5p. The expression level of Sirt5 protein in cells of miR-145-5p mimic group was significantly lower than that of control group and negative control group under normoxic condition (Sirt5/β-actin: 0.59±0.03 vs. 1.00±0.01, 1.01±0.03, both P < 0.05), which verified that Sirt5 was the target gene of miR-145-5p. (3) The occurrence of pyrodeath could be partially reversed by transfection with Sirt5 overexpression plasmid or adding ROS inhibitor NAC into cells, and Sirt5 overexpression could also up-regulate Nrf2 expression and eliminate intracellular ROS. CONCLUSION In human alveolar epithelial cells, miR-145-5p can down-regulate Nrf2 by targeting Sirt5, thereby increasing ROS expression and inducing pyrodeath.
Humans ; MicroRNAs ; Pyroptosis ; Cell Hypoxia ; Alveolar Epithelial Cells/cytology* ; Cell Line ; NLR Family, Pyrin Domain-Containing 3 Protein ; Caspase 1/metabolism* ; Epithelial Cells/metabolism* ; Gasdermins ; Phosphate-Binding Proteins