Single-cell RNA sequencing reveals the MIF/ACKR3 receptor-ligand interaction between neutrophils and nucleus pulposus cells in intervertebral disc degeneration.

OBJECTIVES: To unravel the heterogeneity and function of microenvironmental neutrophils during intervertebral disc degeneration (IDD). METHODS: Single-cell RNA sequencing (scRNA-seq) was utilized to dissect the cellular landscape of neutrophils in intervertebral disc (IVD) tissues and their crosstalk with nucleus pulposus cells (NPCs). The expression levels of macrophage migration inhibitory factor (MIF) and ACKR3 in IVD tissues were detected. The MIF/ACKR3 axis was identified and its effects on IDD were investigated in vitro and in vivo. RESULTS: We sequenced here 71520 single cells from 5 control and 9 degenerated IVD samples using scRNA-seq. We identified a unique cluster of neutrophils abundant in degenerated IVD tissues that highly expressed MIF and was functionally enriched in extracellular matrix organization (ECMO). Cell-to-cell communication analyses showed that this ECMO-neutrophil subpopulation was closely interacted with an effector NPCs subtype, which displayed high expression of ACKR3. Further analyses revealed that MIF was positively correlated with ACKR3 and functioned via directly binding to ACKR3 on effector NPCs. MIF inhibition attenuated degenerative changes of NPCs and extracellular matrix, which could be partially reversed by ACKR3 overexpression. Clinically, a significant correlation of high MIF/ACKR3 expression with advanced IDD grade was observed. Furthermore, we also found a positive association between MIF+ ECMO-neutrophil counts and ACKR3+ effector NPCs density as well as higher expression of the MIF/ACKR3 signaling in areas where these two cell types were neighbors. CONCLUSIONS: These data suggest that ECMO-neutrophil promotes IDD progression by their communication with NPCs via the MIF/ACKR3 axis, which may shed light on therapeutic strategies.

Apoptosis signal-regulated kinase-1 promotes nucleus pulposus cell senescence and apoptosis to regulate intervertebral disc degeneration.

This study investigated the role of apoptosis signal-regulated kinase-1 (ASK1) in intervertebral disc degeneration (IDD). The nucleus pulposus (NP) tissues of non-IDD and IDD patients were subjected to H&E, Safranin-O-fast green, and IHC staining. qRT-PCR was used to assess ASK1 mRNA level within NP tissue samples and cells. CCK-8 assay, SA-ß-gal staining, and then flow cytometry were conducted, respectively, to assess the viability, senescence, and apoptosis of NP cells. The extracellular matrix (ECM)-related factors were detected using Western blot analysis. Furthermore, the effect of ASK1 upon the IDD rat model was evaluated through nuclear magnetic resonance imaging (MRI) analysis, HE, Safranin-O-fast green staining, and IHC staining. Finally, JNK inhibitors were utilized to verify the effect of the JNK/p38 signaling on IDD. ASK1 mRNA and protein were upregulated within NP tissue samples from the IDD group, IL-1ß-stimulated NP cells, and IDD rats. ASK1 inhibition promoted cell viability and repressed the senescence and apoptosis of NP cells; promoted Collagen II and Aggrecan; inhibited MMP3, MMP9, ADAMTS4, and ADAMTS5 protein levels; and increased NP cells in rat IVD tissues. ASK1 overexpression exerted the opposite effects of ASK1 inhibition upon NP cells. Additionally, JNK/p38 signaling suppression could reverse the ASK1 upregulation-induced dysfunction. In conclusion, ASK1 facilitated the senescence and apoptosis of NP cells in promoting IDD progression, which may be mediated by the JNK/p38 pathway.

A three miRNAs panel in paraffin tissue serves as tool for predicting prognosis of renal cell carcinoma.

Background: Renal cell carcinoma (RCC) stands as the most prevalent form of urogenital cancer. However, there is currently no universally accepted method for predicting the prognosis of RCC. MiRNA holds great potential as a prognostic biomarker for RCC. Methods: A total of 100 cases with complete paraffin specimens and over 5-year follow-up data meeting the requirements were collected. Utilizing the clinical information and follow-up data of the specimens, an information model was developed. The expression levels of eight microRNAs were identified using RT-qPCR. Finally, determine and analyze the clinical application value of these microRNAs as prognostic markers for RCC. Results: Significant differences were observed in the expression of two types of miRNAs (miR-378a-5p, miR-23a-5p) in RCC tissue, and three types of miRNAs (miR-378a-5p, miR-642a-5p, miR-23a-5p) were found to be linked to the prognosis of RCC. Establish biomarker combinations of miR-378a-5p, miR-642a-5p, and miR-23a-5p to evaluate RCC prognosis. Conclusion: The combination of three microRNA groups (miR-378a-5p, miR-642a-5p, and miR-23a-5p) identified in paraffin section specimens of RCC in this study holds significant potential as biomarkers for assessing RCC prognosis.

Causal relationship between intervertebral disc degeneration and osteoporosis: a bidirectional two-sample Mendelian randomization study.

Introduction: The relationship between intervertebral disc degeneration (IVDD) and osteoporosis (OP), diagnosed primarily using bone mineral density (BMD), remains unclear so far. The present study, therefore, aimed to investigate the potential relationship between osteoporosis and intervertebral disc degeneration using Mendelian randomization and genome-wide association analyses. Specifically, the impact of bone mineral density on the development of intervertebral disc degeneration was evaluated. Materials and methods: The genome-wide association studies (GWAS) summary data of OP/BMDs and IVDD were collected from the FinnGen consortium, the GEFOS consortium, and MRC-IEU. The relationship between IVDD and OP was then explored using TSMR. The inverse-variance weighted (IVW) method was adopted as the primary effect estimate, and the reliability and stability of the results were validated using various methods, including MR-Egger, weighted median, simple mode, weighted mode, and MR-PRESSO. Results: No significant causal relationship was observed between OP and IVDD (IVW, P > 0.05) or between femoral neck BMD (FA-BMD) and IVDD when OP and FA-BMD were used as exposures. However, increased levels of total body BMD (TB-BMD) and lumbar spine BMD (LS-BMD) were revealed as significant risk factors for IVDD (TB-BMD: IVW, OR = 1.201, 95% CI: 1.123-1.284, P = 8.72 × 10-8; LS-BMD: IVW, OR = 1.179, 95% CI: 1.083-1.284, P = 1.43 × 10-4). Interestingly, both heel BMD (eBMD) and femur neck BMD (FN-BMD) exhibited potential causal relationships (eBMD: IVW, OR = 1.068, 95% CI: 1.008-1.131, P = 0.0248; FN-BMD, IVW, OR = 1.161, 95% CI: 1.041-1.295, P = 0.0074) with the risk of IVDD. The reverse MR analysis revealed no statistically causal impact of IVDD on OP and the level of BMD (P > 0.05). Conclusion: OP and the level of FA-BMD were revealed to have no causal relationship with IVDD. The increased levels of TB-BMD and LS-BMD could promote the occurrence of IVDD. Both eBMD and FN-BMD have potential causal relationships with the risk of IVDD. No significant relationship exists between IVDD and the risk of OP. Further research is warranted to comprehensively comprehend the molecular mechanisms underlying the impact of OP and BMD on IVDD and vice versa.

A panel based on three-miRNAs as diagnostic biomarker for prostate cancer.

Background: Prostate cancer (PCa) is one of the most prevalent malignancies affecting the male life cycle. The incidence and mortality of prostate cancer are also increasing every year. Detection of MicroRNA expression in serum to diagnose prostate cancer and determine prognosis is a very promising non-invasive modality. Materials and method: A total of 224 study participants were included in our study, including 112 prostate cancer patients and 112 healthy adults. The experiment consisted of three main phases, namely, the screening phase, the testing phase, and the validation phase. The expression levels of serum miRNAs in patients and healthy adults were detected using quantitative reverse transcription-polymerase chain reaction. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were used to evaluate the diagnostic ability, specificity, and sensitivity of the candidate miRNAs. Result: Eventually, three miRNAs most relevant to prostate cancer diagnosis were selected, namely, miR-106b-5p, miR-129-1-3p and miR-381-3p. We used these three miRNAs to construct a diagnostic panel with very high diagnostic potential for prostate cancer, which had an AUC of 0.912 [95% confidence interval (CI): 0.858 to 0.950; p < 0.001; sensitivity = 91.67%; specificity = 79.76%]. In addition, the three target genes (DTNA, GJB1, and TRPC4) we searched for are also expected to be used for prostate cancer diagnosis and treatment in the future.

Testing the accuracy of a four serum microRNA panel for the detection of primary bladder cancer: a discovery and validation study.

BACKGROUND: Bladder cancer (BC) is one of the ten most common cancers worldwide with late detection and early age of diagnosis. There is abundant evidence that early detection and timely intervention can lead to a better prognosis of BC. Substantial evidence has indicated that microRNAs (miRNAs) are specific to different tumour types and are remarkably stable, indicating that serum miRNAs may serve as potential cancer diagnostic markers. This study aimed to identify suitable serum miRNAs to create a panel that can be used to diagnose primary BC. METHODS: In this study, 18 miRNAs that were differentially expressed in BC were obtained from the PubMed or Gene Expression Omnibus database. Then, 18 BC-related-miRNAs were verified in screening and validation sets created using 56 (28 primary BC vs. 28 NCs) and 168 (84 primary BC vs. 84 NCs) serum samples, respectively. Quantitative reverse transcription-PCR (qRT-PCR) was performed to verify the identity of the differential miRNAs. A multi-miRNA panel with superior diagnostic performance was constructed. TCGA and KEGG databases were used to conduct the survival analysis and bioinformatics analysis, respectively. RESULTS: Six serum miRNAs (miR-221-5p, miR-181a-5p, miR-98-5p, miR-15a-5p, miR-222-3p, and miR-197-3p) were significantly aberrantly expressed in the BC patients, while four miRNAs from among them (miR-221-5p, miR-181a-5p, miR-15a-5p, miR-222-3p) were assembled into a panel that showed high diagnostic value (AUC = 0.875, 95% CI: 0.815 - 0.921; sensitivity: 82.14%; and specificity: 85.71%) based on the logistic regression analysis. The survival analysis showed that miR-181a-5p was closely associated with BC prognosis (Log-rank p-value < 0.05). CONCLUSION: The combination of the four miRNAs (miR-221-5p, miR-181a-5p, miR-15a-5p and miR-222-3p) may be a novel non-invasive serological biomarker for BC screening.

Early detection and timely intervention can lead to a better prognosis of bladder cancer.This study aimed to identify suitable serum miRNAs to create a panel that can be used to diagnose primary bladder cancer.

The value of a panel of circulating microRNAs in screening prostate cancer.

Background: Prostate cancer (PCa) remains a worldwide public health problem that poses a serious threat to the health of men worldwide. Many studies have found that microRNA (miRNA) in serum has the potential to be a biomarker for cancer screening. Our study was conducted to investigate the value of serum miRNAs in PCa screening. Methods: We selected 12 miRNAs from past studies for its association with PCa. We checked the expression levels of these miRNAs in the serum of 112 PCa patients and 112 healthy controls in a two-stage experiment. We plotted the receiver operating characteristic curve of miRNAs in the validation stage and constructed a four-miRNA panel with the highest diagnostic value using stepwise logistic regression. We also predicted the target genes with these four miRNAs through online databases and performed Gene Ontology functional annotation and pathway analysis. Results: The results showed that six miRNAs (miR-429, miR-10a-5p, miR-183-5p, miR-181a-5p, miR-1231, miR-129-5p) were abnormally expressed in the serum of PCa patients. We used four of these miRNAs including miR-1231, miR-10a-5p, miR-429 and miR-129-5p to construct a combination of miRNAs with high specificity and sensitivity in screening PCa (area under the curve =0.878). Bioinformatics analysis showed that the genes targeted by these miRNAs can be linked to the development of PCa. Conclusions: Our study detected and identified a set of miRNAs that serves as screening marker for PCa, which may assist in early diagnosis and treatment of PCa.

Constructions of quorum sensing signaling network for activated sludge microbial community.

In wastewater treatment systems, the interactions among various microbes based on chemical signals, namely quorum sensing (QS), play critical roles in influencing microbial structure and function. However, it is challenging to understand the QS-controlled behaviors and the underlying mechanisms in complex microbial communities. In this study, we constructed a QS signaling network, providing insights into the intra- and interspecies interactions of activated sludge microbial communities based on diverse QS signal molecules. Our research underscores the role of diffusible signal factors in both intra- and interspecies communication among activated sludge microorganisms, and signal molecules commonly considered to mediate intraspecies communication may also participate in interspecies communication. QS signaling molecules play an important role as communal resources among the entire microbial group. The communication network within the microbial community is highly redundant, significantly contributing to the stability of natural microbial systems. This work contributes to the establishment of QS signaling network for activated sludge microbial communities, which may complement metabolic exchanges in explaining activated sludge microbial community structure and may help with a variety of future applications, such as making the dynamics and resilience of highly complex ecosystems more predictable.

A serum panel of three microRNAs may serve as possible biomarkers for kidney renal clear cell carcinoma.

BACKGROUND: Although non-invasive radiological techniques are widely applied in kidney renal clear cell carcinoma (KIRC) diagnosis, more than 50% of KIRCs are detected incidentally during the diagnostic procedures to identify renal cell carcinoma (RCC). Thus, sensitive and accurate KIRC diagnostic methods are required. Therefore, in this study, we aimed to identify KIRC-associated microRNAs (miRNAs). METHODS: This three-phase study included 224 participants (112 each of patients with KIRC and healthy controls (NCs)). RT-qPCR was used to evaluate miRNA expression in KIRC and NC samples. Receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were used to predict the usefulness of serum miRNAs in KIRC diagnosis. In addition, we performed survival and bioinformatics analyses. RESULTS: We found that miR-1-3p, miR-129-5p, miR-146b-5p, miR-187-3p, and miR-200a-3p were significantly differentially expressed in patients with KIRC. A panel consisting of three miRNAs (miR-1-3p, miR-129-5p, and miR-146b-5p) had an AUC of 0.895, ranging from 0.848 to 0.942. In addition, using the GEPIA database, we found that the miRNAs were associated with CREB5. According to the survival analysis, miR-146b-5p overexpression was indicative of a poorer prognosis in patients with KIRC. CONCLUSIONS: The identified three-miRNA panel could serve as a non-invasive indicator for KIRC and CREB5 as a potential target gene for KIRC treatment.

The value of a three-microRNA panel in serum for prostate cancer screening.

BACKGROUND: Globally, prostate cancer is the second most common malignancy in males. Serum microRNAs (miRNAs) may function as non-invasive and innovative biomarkers for various cancers. Our study aimed to determine potential miRNAs for prostate cancer screening. METHODS: A three-stage study was accomplished to ascertain crucial miRNAs as markers. In the screening stage, we searched PubMed for aberrantly expressed miRNAs relevant to prostate cancer and selected them as candidate miRNAs. In training and validation stages, with serum specimens from 112 prostate cancer patients and 112 healthy controls, expressions of candidate miRNAs were identified through quantitative reverse transcription-polymerase chain reaction. The diagnostic capabilities of miRNAs were determined by receiver operating characteristic curves. Bioinformatic analysis was utilized to explore the function of the critical miRNAs. RESULTS: Expression of six serum miRNAs (miR-34b-3p, miR-556-5p, miR-200c-3p, miR-361-5p, miR-369-3p, miR-485-3p) were significantly altered in prostate cancer patients contrasted with healthy controls. The optimal combination of critical miRNAs is a three-miRNA panel (miR-34b-3p, miR-200c-3p, and miR-361-5p) with good diagnostic capability. FLRT2, KIAA1755, LDB3, and NTRK3 were identified as the potential genes targeted by the three-miRNA panel. CONCLUSIONS: The three-miRNA panel may perform as an innovative and promising serum marker for prostate cancer screening.

Profiling of Serum miRNAs Constructs a Diagnostic 3-miRNA Panel for Clear-Cell Renal Cell Carcinoma.

BACKGROUND: Renal cell carcinoma (RCC) carries significant morbidity and mortality globally with an increasing incidence per year predominantly represented by clear-cell renal cell carcinoma (ccRCC) which accounts for 70-80% of all RCC cases. MicroRNAs(miRNAs) implicate tumor development and progression in epigenetic mechanisms and available profiling of serum miRNAs potentiate them as diagnostic markers for various cancers. MATERIALS AND METHODS: A total of 108 ccRCC patients and 112 normal controls were enrolled. A 3-stage experiment was conducted to identify differentially expressed serum miRNAs in ccRCC and establish a diagnostic miRNAs panel. Additionally, bioinformatic analysis was employed to predict selected miRNAs' target genes, preform functional annotation and explore the roles in ccRCC. RESULTS: MiR-429, miR-10a-5p, miR-154-5p were found to be up-regulated miRNAs. Inversely, miR-27a-3p and miR-221-3p were found to be down-regulated miRNAs. These 5 miRNAs were selected to construct diagnostic panel by backward stepwise logistic regression analysis and ultimately a 3-miRNA panel (miR-429, miR-10a-5p and miR-27a-3p) was established [area under the curve (AUC) = 0.897, sensitivity = 85.0%, specificity = 83.3%]. CONCLUSION: The panel of 3-miRNA holds promise as a novel, convenient, and noninvasive diagnostic method for early detection of ccRCC.

COL3A1 is a potential diagnostic biomarker for synovial chondromatosis and affects the cell cycle and migration of chondrocytes.

BACKGROUND: Synovial chondromatosis (SC) primarily affects the major joints and is characterized by the formation of benign cartilaginous nodules. In the present study, we evaluated the differences in the histology and gene expression of SC and normal cartilages and further elucidated the function of hub genes in SC. METHODS: Histological staining and biochemical analysis were performed to measure collagen and glycosaminoglycan (GAG) contents in SC and normal cartilage samples. Then, microarray analysis was performed using knee joint samples (three normal and three SC samples) to identify the differentially expressed genes (DEGs). Subsequently, bioinformatics analysis was performed to identify the hub genes and explore the mechanisms underlying SC. The intersection of the top 10 upregulated DEGs, top 10 downregulated DEGs, and hub genes was validated in SC tissues. Lastly, in vitro experiments and our clinical cohort were used to determine the potential biological functions and diagnostic value, respectively, of the most significant gene. RESULTS: The GAG and collagen contents were comparable to or higher in SC tissues than in normal tissues. Microarray analysis revealed 143 upregulated and 107 downregulated DEGs in SC. Furthermore, functional enrichment analysis revealed an association between immunity and metabolism-related pathways and SC development. Among 20 hub genes, two intersection genes, namely, collagen type III alpha 1 chain (COL3A1) and HSPA8, were notably expressed in SC tissues, with COL3A1 exhibiting a more significant difference in mRNA expression. Furthermore, COL3A1 can promote chondrocyte migration and cell cycle progression. Additionally, clinical data revealed COL3A1 can be a diagnostic marker for primary SC (AUC = 0.82) and be a positive correlation with neutrophil-to-lymphocyte ratio. CONCLUSIONS: These results suggest that SC tissues contained the abundant GAG and collagen. COL3A1 can affect the function of chondrocytes and be a diagnostic marker of primary SC patients. These findings provide a novel approach and a fundamental contribution for diagnosis and treatment in SC.

Artificial intelligence in wastewater treatment: A data-driven analysis of status and trends.

Wastewater treatment is a complex process that involves many uncertainties, leading to fluctuations in effluent quality and costs, and environmental risks. Artificial intelligence (AI) can handle complex nonlinear problems and has become a powerful tool for exploring and managing wastewater treatment systems. This study provides a summary of the current status and trends in AI research as applied to wastewater treatment, based on published papers and patents. Our results indicate that, at present, AI is primarily used to evaluate removal of pollutants (conventional, typical, and emerging contaminants), optimize models and process parameters, and control membrane fouling. Future research will likely continue to focus on removal of phosphorus, organic pollutants, and emerging contaminants. Moreover, analyzing microbial community dynamics and achieving multi-objective optimization are promising directions of research. The knowledge map shows that there may be future technological innovation related to predicting water quality under specific conditions, integrating AI with other information technologies and utilizing image-based AI and other algorithms in wastewater treatment. In addition, we briefly review development of artificial neural networks (ANNs) and explore the evolutionary path of AI in wastewater treatment. Our findings provide valuable insights into potential opportunities and challenges for researchers applying AI to wastewater treatment.

Vascular endothelium is the basic way for stem cells to treat erectile dysfunction: a bibliometric study.

Vascular endothelial is considered to be a key factor in the pathogenesis of erectile dysfunction (ED). The purpose is to reveal the research trend of the field of ED and vascular endothelium. In addition, the goal is to discover the role and mechanism of vascular endothelium in ED. Bibliometrics and visualization methods based on CiteSpace were selected. We conducted the co-authorship analysis of countries, institutions and authors, co-occurrence analysis of keywords, and co-citation analysis of literature and authors through CiteSpace 6.1.R3. 1431 articles from Web of Science Core Collection (WOSCC) were included in the analysis from 1991 to 2022. We found some influential and cutting-edge nodes in each map, including countries, institutions, authors, articles, etc. Stem cell, therapy, oxidative stress, cavernous nerve injury, radical prostatectomy, fibrosis, erectile function, mesenchymal stem cell, and apoptosis may be hot keywords. In conclusion, the efficacy and mechanisms of stem cells and their derivatives in the treatment of diabetes (DM) ED and cavernous nerve injury (CNI) ED are the future research trends. Stem cells therapy for ED is a hot spot in this field, which side notes that stem cells may work mainly through improving endothelial function. Vascular endothelial cells and VEGF may repair nerve and cavernous smooth muscle directly or indirectly, and finally polish up erectile function.

MMP9 and STAT1 are biomarkers of the change in immune infiltration after anti-tuberculosis therapy, and the immune status can identify patients with spinal tuberculosis.

BACKGROUND: Due to a lack of studies on immune-related pathogenesis and a clinical diagnostic model, the diagnosis of Spinal Tuberculosis (STB) remains uncertain. Our study aimed to investigate the possible pathogenesis of STB and to develop a clinical diagnostic model for STB based on immune cell infiltration. METHODS: Label-free quantification protein analysis of five pairs of specimens was used to determine the protein expression of the intervertebral disc in STB and non-STB. GO enrichment analysis, and KEGG pathway analysis were used to investigate the pathogenesis of STB. The Hub proteins were then eliminated. Four datasets were downloaded from the GEO database to analyze immune cell infiltration, and the results were validated using blood routine test data from 8535TB and 7337 non-TB patients. Following that, clinical data from 164 STB and 162 non-STB patients were collected. The Random-Forest algorithm was used to screen out clinical predictors of STB and build a diagnostic model. The differential expression of MMP9 and STAT1 in STB and controls was confirmed using immunohistochemistry. RESULTS: MMP9 and STAT1 were STB Hub proteins that were linked to disc destruction in STB. MMP9 and STAT1 were found to be associated with Monocytes, Neutrophils, and Lymphocytes in immune cell infiltration studies. Data from 15,872 blood routine tests revealed that the Monocytes ratio and Neutrophils ratio was significantly higher in TB patients than in non-TB patients (p < 0.001), while the Lymphocytes ratio was significantly lower in TB patients than in non-TB patients (p < 0.001). MMP9 and STAT1 expression were downregulated following the anti-TB therapy. For STB, a clinical diagnostic model was built using six clinical predictors: MR, NR, LR, ESR, BMI, and PLT. The model was evaluated using a ROC curve, which yielded an AUC of 0.816. CONCLUSIONS: MMP9 and STAT1, immune-related hub proteins, were correlated with immune cell infiltration in STB patients. MR, NR, LR ESR, BMI, and PLT were clinical predictors of STB. Thus, the immune cell Infiltration-related clinical diagnostic model can predict STB effectively.

CircRNA AFF4 induced by KDM1A promotes osteogenic differentiation through FNDC5/Irisin pathway.

BACKGROUND: Circular RNA (circ) AFF4 was documented to regulate osteogenesis but the underlying mechanism remains to be elucidated. The preliminary study showed that circ_AFF4 may promote osteogenesis via FNDC5/Irisin. Furthermore, the online prediction tool indicated the interaction of circ_AFF4, insulin-like growth factor-2 mRNA-binding protein 3 (IGF2BP3), FNDC5 and lysine (K)-specific demethylase 1 A (KDM1A). Therefore, this study aims to elucidate the relationships of KDM1A, circ_AFF4, IGF2BP3 and FNDC5/Irisin during osteogenesis. METHODS: The alkaline phosphatase (ALP) activities and osteogenic-related factors were determined using ALP and alizarin red S (ARS) staining, real-time quantitative PCR(RT-qPCR) and western blot. Immunoprecipitation (RIP), pull-down assay and fluorescence in situ hybridization (FISH) were used to examine the interactions among circ_AFF4/IGF2BP3/FNDC5. A mouse in vivo model was utilized to further confirm the regulatory effect on bone formation. RESULTS: Circ_AFF4 and KDM1A expression levels were increased during osteoinduction of BM-MSCs. Knockdown of circ_AFF4 and KDM1A significantly suppressed BM-MSC osteogenesis. We also proved that KDM1A directly bound to circ_AFF4 and FNDC5 promoter and induced circ_AFF4 and FNDC5 expression. Furthermore, circ_AFF4 enhanced the stability of FNDC5 by generating a circ_AFF4, IGF2BP3 and FNDC5 RNA-protein complex, and thereby induced Irisin and osteogenesis. The in vitro data was confirmed with in vivo model. CONCLUSION: These findings elucidate that KDM1A induces circ_AFF4, which promotes promote osteogenesis via IGF2BP3. This study indicates that circ_AFF4 may potentially represent a critical therapeutic target for the diseases.

Bladder cancer diagnosis with a four-miRNA panel in serum.

Background: Bladder cancer is one of the most prevalent malignancies. Due to the disadvantage of existing bladder cancer diagnostic tools, miRNAs hold promise as new diagnostic markers. Materials & methods: A total of 224 participants were involved in this three-cohort trial. A total of 15 candidate miRNAs were selected, and miRNAs with diagnostic ability were screened out with quantitative reverse transcription PCR. Diagnostic capability was ascertained by the receiver operating characteristic curve and area under the curve. Bioinformatics analysis was constructed for target gene prediction and functional annotation. Results: Six candidate miRNAs showed significantly different expression between bladder cancer patients and normal controls, and the final diagnostic panel comprised miR-181b-5p, miR-183-5p, miR-199-5p and miR-221-3p. Conclusion: This four-miRNA panel could represent a stable biomarker for bladder cancer diagnosis.

Bladder cancer is one of the most prevalent malignancies. Due to the disadvantage of existing bladder cancer diagnostic tools, miRNAs hold promise as new diagnostic markers. After an experiment composed of 224 participants, the authors screened out six candidate miRNAs that may contribute to diagnosing bladder cancer. The authors also repeatedly verified the reliability of candidate miRNAs. Finally, a combination of multiple miRNAs, consisting of miR-181b-5p, miR-183-5p, miR-199-5p, and miR-221-3p, was better and more reliable in predicting bladder cancer occurrence.

Machine learning-based clustering in cervical spondylotic myelopathy patients to identify heterogeneous clinical characteristics.

Background: Anterior cervical decompression and fusion can effectively treat cervical spondylotic myelopathy (CSM). Accurately classifying patients with CSM who have undergone anterior cervical decompression and fusion is the premise of precision medicine. In this study, we used machine learning algorithms to classify patients and compare the postoperative efficacy of each classification. Methods: A total of 616 patients with cervical spondylotic myelopathy who underwent anterior cervical decompression and fusion were enrolled. Unsupervised machine learning algorithms (UMLAs) were used to cluster subjects according to similar clinical characteristics. Then, the results of clustering were visualized. The surgical outcomes were used to verify the accuracy of machine learning clustering. Results: We identified two clusters in these patients who had significantly different baseline clinical characteristics, preoperative complications, the severity of neurological symptoms, and the range of decompression required for surgery. UMLA divided the CSM patients into two clusters according to the severity of their illness. The repose to surgical treatment between the clusters was significantly different. Conclusions: Our results showed that UMLA could be used to rationally classify a heterogeneous cohort of CSM patients effectively, and thus, it might be used as the basis for a data-driven platform for identifying the cluster of patients who can respond to a particular treatment method.

Development and Validation of a Machine Learning-Based Nomogram for Prediction of Ankylosing Spondylitis.

INTRODUCTION: Ankylosing spondylitis (AS) is a chronic progressive inflammatory disease of the spine and its affiliated tissues. AS mainly affects the axial bone, sacroiliac joint, hip joint, spinal facet, and adjacent ligaments. We used machine learning (ML) methods to construct diagnostic models based on blood routine examination, liver function test, and kidney function test of patients with AS. This method will help clinicians enhance diagnostic efficiency and allow patients to receive systematic treatment as soon as possible. METHODS: We consecutively screened 348 patients with AS through complete blood routine examination, liver function test, and kidney function test at the First Affiliated Hospital of Guangxi Medical University according to the modified New York criteria (diagnostic criteria for AS). By using random sampling, the patients were randomly divided into training and validation cohorts. The training cohort included 258 patients with AS and 247 patients without AS, and the validation cohort included 90 patients with AS and 113 patients without AS. We used three ML methods (LASSO, random forest, and support vector machine recursive feature elimination) to screen feature variables and then took the intersection to obtain the prediction model. In addition, we used the prediction model on the validation cohort. RESULTS: Seven factors-erythrocyte sedimentation rate (ESR), red blood cell count (RBC), mean platelet volume (MPV), albumin (ALB), aspartate aminotransferase (AST), and creatinine (Cr)-were selected to construct a nomogram diagnostic model through ML. In the training cohort, the C value and area under the curve (AUC) value of this nomogram was 0.878 and 0.8779462, respectively. The C value and AUC value of the nomogram in the validation cohort was 0.823 and 0.8232055, respectively. Calibration curves in the training and validation cohorts showed satisfactory agreement between nomogram predictions and actual probabilities. The decision curve analysis showed that the nonadherence nomogram was clinically useful when intervention was decided at the nonadherence possibility threshold of 1%. CONCLUSION: Our ML model can satisfactorily predict patients with AS. This nomogram can help orthopedic surgeons devise more personalized and rational clinical strategies.

AS is a chronic progressive inflammatory disease of the spine and its affiliated tissues. AS starts gradually, and its early symptoms are mild. Some hospitals lack HLA-B27 and related imaging instruments to assist in the diagnosis of AS. There are relatively few studies on liver function and kidney function of patients with AS. We used ML methods to construct diagnostic models. Our model can satisfactorily predict patients with AS. This diagnostic model can help orthopedic surgeons devise more personalized and rational clinical strategies.