Exercise-Induced Reduction of IGF1R Sumoylation Attenuates Neuroinflammation in APP/PS1 Transgenic Mice.

INTRODUCTION: Alzheimer's Disease (AD), a progressive neurodegenerative disorder, is marked by cognitive deterioration and heightened neuroinflammation. The influence of Insulin-like Growth Factor 1 Receptor (IGF1R) and its post-translational modifications, especially sumoylation, is crucial in understanding the progression of AD and exploring novel therapeutic avenues. OBJECTIVES: This study investigates the impact of exercise on the sumoylation of IGF1R and its role in ameliorating AD symptoms in APP/PS1 mice, with a specific focus on neuroinflammation and innovative therapeutic strategies. METHODS: APP/PS1 mice were subjected to a regimen of moderate-intensity exercise. The investigation encompassed assessments of cognitive functions, alterations in hippocampal protein expressions, neuroinflammatory markers, and the effects of exercise on IGF1R and SUMO1 nuclear translocation. Additionally, the study evaluated the efficacy of KPT-330, a nuclear export inhibitor, as an alternative to exercise. RESULTS: Exercise notably enhanced cognitive functions in AD mice, possibly through modulations in hippocampal proteins, including Bcl-2 and BACE1. A decrease in neuroinflammatory markers such as IL-1ß, IL-6, and TNF-α was observed, indicative of reduced neuroinflammation. Exercise modulated the nuclear translocation of SUMO1 and IGF1R in the hippocampus, thereby facilitating neuronal regeneration. Mutant IGF1R (MT IGF1R), lacking SUMO1 modification sites, showed reduced SUMOylation, leading to diminished expression of pro-inflammatory cytokines and apoptosis. KPT-330 impeded the formation of the IGF1R/RanBP2/SUMO1 complex, thereby limiting IGF1R nuclear translocation, inflammation, and neuronal apoptosis, while enhancing cognitive functions and neuron proliferation. CONCLUSION: Moderate-intensity exercise effectively mitigates AD symptoms in mice, primarily by diminishing neuroinflammation, through the reduction of IGF1R Sumoylation. KPT-330, as a potential alternative to physical exercise, enhances the neuroprotective role of IGF1R by inhibiting SUMOylation through targeting XPO1, presenting a promising therapeutic strategy for AD.

Potential mechanism of the Shunaoxin pill for preventing cognitive impairment in type 2 diabetes mellitus.

Objective: This study aims to analyze the efficacy and mechanism of action of the Shunaoxin pill in preventing cognitive impairment in diabetic patients using network pharmacology. Methods: The main active compounds of the Shunaoxin pills and their action targets were identified via the TCMSP and Batman-TCM databases. The GEO database was used to identify the genes in type 2 diabetic individuals associated with cognitive impairment. Subsequently, a common target protein-protein interaction (PPI) network was constructed using the STRING database, and targets associated with diabetes and cognitive impairment were screened by performing a topological analysis of the PPI network. The AutoDock Vina software was used for molecular docking to evaluate the reliability of the bioinformatic analysis predictions and validate the interactions between the active ingredients of the Shunaoxin pill and proteins associated with diabetes and cognitive impairment. Results: Based on the TCMSP and Batman-Tcm platform, 48 active ingredients of the Shunaoxin pill were identified, corresponding to 222 potential action targets. Further analysis revealed that 18 active components of the Shunaoxin pill might contribute to cognitive impairment in type 2 diabetic patients. Molecular docking simulations demonstrated that the active ingredients of the Shunaoxin pill (hexadecanoic acid, stigmasterol, beta-sitosterol, and angelicin) targeted four core proteins: OPRK1, GABRA5, GABRP, and SCN3B. Conclusion: Active ingredients of the Shunaoxin pill may alleviate cognitive impairment in diabetic patients by targeting the proteins OPRK1, GABRA5, GABRP, and SCN3B.

Development of a prognostic prediction model based on a combined multi-omics analysis of head and neck squamous cell carcinoma cell pyroptosis-related genes.

This study aimed to understand the prognosis of patients with head and neck squamous cell carcinoma (HNSCC) and to develop and validate a prognostic model for HNSCC based on pyroptosis-associated genes (PAGs) in nasopharyngeal carcinoma. The Cancer Genome Atlas database was used to identify differentially expressed PAGs. These genes were analyzed using the Kyoto Encyclopedia of Genes and Genomes functional annotation analyses and Gene Ontology analyses. The NLR family pyrin domain containing 1 (NLRP1) gene, charged multivesicular body protein 7 (CHMP7) gene, and cytochrome C (CYCS) gene were used to create a prognostic model for HNSCC. The results of the Kaplan-Meier (K-M) and Cox regression analyses indicated that the developed model served as an independent risk factor for HNSCC. According to the K-M analysis, the overall survival of high-risk patients was lower than that of low-risk patients. The hazard ratios corresponding to the risk scores determined using the multivariate and univariate Cox regression analyses were 1.646 (95% confidence interval (CI): 1.189-2.278) and 1.724 (95% CI: 1.294-2.298), respectively, and the area under the receiver operator characteristic curve was 0.621. The potential mechanisms associated with the functions of the identified genes were then identified, and the tumor microenvironment and levels of immune cell infiltration achieved were analyzed. The immune infiltration analysis revealed differences in the distribution of Th cells, tumor-infiltrating lymphocytes, regulatory T cells, follicular helper T cells, adipose-derived cells, interdigitating dendritic cells, CD8+ T cells, and B cells. However, validating bioinformatics analyses through biological experiments is still recommended. This study developed a prognostic model for HNSCC that included NLRP1, CHMP7, and CYCS.

Exercise improves choroid plexus epithelial cells metabolism to prevent glial cell-associated neurodegeneration.

Recent studies have shown that physical activities can prevent aging-related neurodegeneration. Exercise improves the metabolic landscape of the body. However, the role of these differential metabolites in preventing neurovascular unit degeneration (NVU) is still unclear. Here, we performed single-cell analysis of brain tissue from young and old mice. Normalized mutual information (NMI) was used to measure heterogeneity between each pair of cells using the non-negative Matrix Factorization (NMF) method. Astrocytes and choroid plexus epithelial cells (CPC), two types of CNS glial cells, differed significantly in heterogeneity depending on their aging status and intercellular interactions. The MetaboAnalyst 5.0 database and the scMetabolism package were used to analyze and calculate the differential metabolic pathways associated with aging in the CPC. These mRNAs and corresponding proteins were involved in the metabolites (R)-3-Hydroxybutyric acid, 2-Hydroxyglutarate, 2-Ketobutyric acid, 3-Hydroxyanthranilic acid, Fumaric acid, L-Leucine, and Oxidized glutathione pathways in CPC. Our results showed that CPC age heterogeneity-associated proteins (ECHS1, GSTT1, HSD17B10, LDHA, and LDHB) might be directly targeted by the metabolite of oxidized glutathione (GSSG). Further molecular dynamics and free-energy simulations confirmed the insight into GSSG's targeting function and free-energy barrier on these CPC age heterogeneity-associated proteins. By inhibiting these proteins in CPC, GSSG inhibits brain energy metabolism, whereas exercise improves the metabolic pathway activity of CPC in NVU by regulating GSSG homeostasis. In order to develop drugs targeting neurodegenerative diseases, further studies are needed to understand how physical exercise enhances NVU function and metabolism by modulating CPC-glial cell interactions.

The effect of denture-wearing on physical activity is associated with cognitive impairment in the elderly: A cross-sectional study based on the CHARLS database.

Background: Currently, only a few studies have examined the link between dental health, cognitive impairment, and physical activity. The current study examined the relationship between denture use and physical activity in elderly patients with different cognitive abilities. Methods: The study data was sourced from the 2018 China Health and Retirement Longitudinal Study (CHARLS) database, which included information on denture use and amount of daily physical activity undertaken by older persons. Physical activity was categorized into three levels using the International Physical Activity General Questionnaire and the International Physical Activity Scale (IPAQ) rubric. The relationship between denture use and physical activity in middle-aged and older persons with varying degrees of cognitive functioning was studied using logistic regression models. Results: A total of 5,892 older people with varying cognitive abilities were included. Denture use was linked to physical activity in the cognitively healthy 60 + age group (p = 0.004). Denture use was positively related with moderate physical activity in the population (odds ratio, OR: 1.336, 95% confidence interval: 1.173-1.520, p < 0.001), according to a multivariate logistic regression analysis, a finding that was supported by the calibration curve. Furthermore, the moderate physical activity group was more likely to wear dentures than the mild physical activity group among age-adjusted cognitively unimpaired middle-aged and older persons (OR: 1.213, 95% CI: 1.053-1.397, p < 0.01). In a fully adjusted logistic regression model, moderate physical activity population had increased ORs of 1.163 (95% CI: 1.008-1.341, p < 0.05) of dentures and vigorous physical activity population had not increased ORs of 1.016 (95% CI: 0.853-1.210, p > 0.05), compared with mild physical activity population. Conclusion: This findings revealed that wearing dentures affects physical activity differently in older persons with different cognitive conditions. In cognitively unimpaired older adults, wearing dentures was associated with an active and appropriate physical activity status.

Quercetin targets VCAM1 to prevent diabetic cerebrovascular endothelial cell injury.

Introduction: Endothelial cells play important roles in neurodegenerative diseases caused by diabetes, therefore, we aimed at investigating the mechanisms through which endothelial cells are involved in diabetes development. Methods: Single cell analysis was performed to identify the major endothelial cell subtypes in cardiovascular tissues that are involved in diabetes development. A cell-cell communication approach was then used to identify ligand-receptor interaction pairs between these cell types. Differential expression analysis between the two experimental groups [standard chow diet group and diabetogenic diet with cholesterol (DDC) group] was used to identify diabetes-related differentially expressed genes (DEGs). The upregulated genes were used to identify candidate ligands or receptors, as well as the corresponding cell types. Cell trajectory inference was performed to identify the stage of cell development and changes in expression of candidate ligands or receptors during cell development. Gene set enrichment analysis (GSEA) was conducted to investigate the biological functions of genes of purpose. Finally, molecular dynamics simulations (MDSs) were used to predict potential drugs with the ability to target the proteins of purpose. Results: Seven cell types, including five endothelial cell subtypes (EC_1, EC_2, EC_3, EC_4, and EC_EndMT), were identified from endothelial cell-enriched single cell samples from the heart and aorta of mice. Cell-cell communication analysis revealed the potential ligand-receptor interactions between these cell types while five important ligand-receptor-associated genes, including Fn1, Vcam1, Fbn1, Col4a1, and Col4a2, were established by differential expression analysis. Among them, Vcam1 is mainly expressed in EC_EndMT and is involved in interactions between EC_EndMT and other cells. Cell trajectory extrapolation analysis revealed a shift from EC_2/EC_4 to EC_EndMT and a shift from EC_EndMT to EC_3/EC_1 during the progression of diabetes. GSEA analysis revealed that upregulation of VCAM1 may have inhibitory effects on cell growth and energy metabolism. Conclusion: EC_EndMT subtypes have a complex role in neurodegenerative diseases caused by diabetes. Through mechanisms involved in cell-cell communication, Vcam1 may play an important role in dysregulation of biological functions of EC_ EndMT. Molecular docking results of the quercetin-VCAM1 complex suggest that quercetin may be an effective drug for targeting this protein.

Exploring the Potential Mechanisms of Melilotus officinalis (L.) Pall. in Chronic Muscle Repair Patterns Using Single Cell Receptor-Ligand Marker Analysis and Molecular Dynamics Simulations.

Information regarding the function of Melilotus officinalis (L.) Pall. in skeletal muscles is still unknown. In this study, we explored the possible regulatory targets of M. (L.) Pall. that affects the repair patterns in chronic muscle injury. We analyzed the potential target genes and chemical composition of M. (L.) Pall. and constructed a "drug-component-disease target genes" network analysis. Five active ingredients and 87 corresponding targets were obtained. Muscle-tendon junction (MTJ) cells were used to perform receptor-ligand marker analysis using the CellphoneDB algorithm. Targets of M. (L.) Pall. were screened further for the cellular ligand-receptor protein action on MTJs. Enrichment analysis suggests that those protein-associated ligand receptors may be associated with a range of intercellular signaling pathways. Molecular docking validation was then performed. Five proteins (CCL2, VEGFA, MMP2, MET, and EGFR) may be regulated by the active ingredient luteolin and scoparone. Finally, molecular dynamics simulations revealed that luteolin can stably target binding to MMP2. M. (L.) Pall. influences skeletal muscle repair patterns by affecting the fibroblast interactions in the muscle-tendon junctions through the active ingredients luteolin and scoparone.

Based on Network Pharmacology and Molecular Dynamics Simulations, Baicalein, an Active Ingredient of Yiqi Qingre Ziyin Method, Potentially Protects Patients With Atrophic Rhinitis From Cognitive Impairment.

Cognition may be improved by the active ingredients of the Yiqi Qingre Ziyin method in patients with atrophic rhinitis (AR). This study aimed to identify potential targets of the Yiqi Qingre Ziyin method for the treatment of patients with cognitive impairment. Nasal mucosal tissue samples from patients with AR were subjected to proteomic assays, and differentially expressed proteins were obtained. To explore the mechanism of AR leading to mild cognitive impairment (MCI), a differential analysis of AR related differential proteins in the MCI related GSE140831 dataset was performed. Most AR-related differential proteins are also differentially expressed in peripheral blood tissues of MCI, have similar biological functions and are enriched in similar pathways. These co-expressed differential factors in AR and MCI are known as common differential proteins of AR and MCI (CDPAM). Based on the analysis and validation of the random forest, support vector machine and neural network models, CDPAM acted as a diagnostic marker for MCI risk. Cytochrome C (CYCS) was significantly upregulated in the peripheral blood of patients with MCI. The active ingredients in the Yiqi Qingre Ziqin method were obtained and targeted 137 proteins. Among these targeted proteins, CYCS belong to the CDPAM set. Molecular docking and molecular dynamics analysis revealed that baicalein, an active ingredient in the Yiqi Qingre Ziyin method, stably targeted the CYCS protein. Results of the enrichment analysis revealed that the up-regulation of CYCS expression may have a defensive effect on the cells to resist foreign stimuli. Therefore, baicalein, an active ingredient in the Yiqi Qingre Ziyin method, may prevent the development and progression of MCI by targeting the CYCS protein.

Potential Mechanism Underlying Exercise Upregulated Circulating Blood Exosome miR-215-5p to Prevent Necroptosis of Neuronal Cells and a Model for Early Diagnosis of Alzheimer's Disease.

Exercise is crucial for preventing Alzheimer's disease (AD), although the exact underlying mechanism remains unclear. The construction of an accurate AD risk prediction model is beneficial as it can provide a theoretical basis for preventive exercise prescription. In recent years, necroptosis has been confirmed as an important manifestation of AD, and exercise is known to inhibit necroptosis of neuronal cells. In this study, we extracted 67 necroptosis-related genes and 32 necroptosis-related lncRNAs and screened for key predictive AD risk genes through a random forest analysis. Based on the neural network Prediction model, we constructed a new logistic regression-based AD risk prediction model in order to provide a visual basis for the formulation of exercise prescription. The prediction model had an area under the curve (AUC) value of 0.979, indicative of strong predictive power and a robust clinical application prospect. In the exercise group, the expression of exosomal miR-215-5p was found to be upregulated; miR-215-5p could potentially inhibit the expressions of IDH1, BCL2L11, and SIRT1. The single-cell SCENIC assay was used to identify key transcriptional regulators in skeletal muscle. Among them, CEBPB and GATA6 were identified as putative transcriptional regulators of miR-215. After "skeletal muscle removal of load," the expressions of CEBPB and GATA6 increased substantially, which in turn led to the elevation of miR-215 expression, thereby suggesting a putative mechanism for negative feedback regulation of exosomal homeostasis.

Prognostic and Functional Analysis of NPY6R in Uveal Melanoma Using Bioinformatics.

Neuropeptides can mediate tumor cell proliferation and differentiation through autocrine, paracrine, neurosecretory, and endocrine mechanisms. This study investigated the expression and prognostic significance of neuropeptide Y receptor Y6 (NPY6R) in uveal melanoma (UVM) and preliminarily investigated the biological function of NPY6R in UVM. NPY6R was poorly expressed in most tumors and was associated with better prognosis in UVM. Among the clinicopathological features of UVM, NPY6R expression was lower in male patients. The area under the curve (AUC) value of NPY6R for the diagnosis of UVM was 0.676 (95% CI: 0.556-0.795). A nomogram including four clinical predictors was constructed. NPY6R expression was significantly associated with features of the UVM immune microenvironment. ESTIMATE and CIBERSORT algorithms were used to calculate the fraction of immune cells and the percentage of infiltration in each patient, respectively. NPY6R expression-related gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analyses were performed. GO and KEGG enrichment analyses revealed that NPY6R-related genes are mainly enriched in pathways and functions related to visual light perception. Gene set enrichment analysis suggested that NPY6R is associated with tumor progression in UVM. NPY6R is involved in the tumor progression of UVM and has a good predictive value as a prognostic marker of UVM.

Exploring the Mechanism of Yiqi Qingre Ziyin Method in Regulating Neuropeptide Expression for the Treatment of Atrophic Rhinitis.

Atrophic rhinitis (AR) is a chronic disease that causes severe structural changes to the nasal mucosa leading to squamous epithelial metaplasia. However, treatment regarding AR remains a major challenge. We used network pharmacology and molecular docking methods to explore the potential mechanisms of the Yiqi Qingre Ziyin method to modulate neuropeptides in the treatment of AR. The active ingredients of the Yiqi Qingre Ziyin method and their targets of action were obtained from the Traditional Chinese Medicine Systematic Pharmacology Database Analysis Platform (TCMSP). Disease targets for AR were obtained from four databases: GeneCards, PharmGKB, DrugBank, and Online Mendelian Inheritance in Man (OMIM). A total of 59 active ingredients, 39 potential targets, and 76 relevant neuropeptides were obtained after deduplication. We constructed target interaction networks with the STRING database. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the 14 potential target proteins. We used Cytoscape software to construct the "drug-active ingredient-potential target" and "ingredient-target-pathway" networks of the Yiqi Qingre Ziyin method for treating AR. Molecular docking results suggest that dipeptidyl peptidase 4 (DPP4), opioid receptor gene d1 (OPRD1), and opioid receptor m1 (OPRM1) are key targets for the Yiqi Qingre Ziyin method. Therefore, this study proposed a potential mechanism for the treatment of AR by affecting the expression of neuropeptide-related genes (including DPP4, OPRD1, and OPRM1), which may potentially improve the immune microenvironment of the nasal mucosa.

Untargeted Metabolomic Profiling of Cuprizone-Induced Demyelination in Mouse Corpus Callosum by UPLC-Orbitrap/MS Reveals Potential Metabolic Biomarkers of CNS Demyelination Disorders.

Multiple sclerosis (MS) is a neurodegenerative disorder characterized by periodic neuronal demyelination, which leads to a range of symptoms and eventually to disability. The goal of this research was to use UPLC-Orbitrap/MS to identify validated biomarkers and explore the metabolic mechanisms of MS in mice. Thirty-two C57BL/6 male mice were randomized into two groups that were fed either normal food or 0.2% CPZ for 11 weeks. The mouse demyelination model was assessed by LFB and the expression of MBP by immunofluorescence and immunohistochemistry. The metabolites of the corpus callosum were quantified using UPLC-Orbitrap/MS. The mouse pole climbing experiment was used to assess coordination ability. Multivariate statistical analysis was adopted for screening differential metabolites, and the ingenuity pathway analysis (IPA) was used to reveal the metabolite interaction network. We successfully established the demyelination model. The CPZ group slowly lost weight and showed an increased pole climbing time during feeding compared to the CON group. A total of 81 metabolites (VIP > 1 and P < 0.05) were determined to be enriched in 24 metabolic pathways; 41 metabolites were markedly increased, while 40 metabolites were markedly decreased in the CPZ group. The IPA results revealed that these 81 biomarker metabolites were associated with neuregulin signaling, PI3K-AKT signaling, mTOR signaling, and ERK/MAPK signaling. KEGG pathway analysis showed that two significantly different metabolic pathways were enriched, namely, the glycerophospholipid and sphingolipid metabolic pathways, comprising a total of nine biomarkers. Receiver operating characteristic analysis showed that the metabolites (e.g., PE (16 : 0/22 : 6(4Z, 7Z, 10Z, 13Z, 16Z, 19Z)), PC (18 : 0/22 : 4(7Z, 10Z, 13Z, 16Z)), cytidine 5'-diphosphocholine, PS (18 : 0/22 : 6(4Z, 7Z, 10Z, 13Z, 16Z, 19Z)), glycerol 3-phosphate, SM (d18 : 0/16 : 1(9Z)), Cer (d18:1/18 : 0), galabiosylceramide (d18:1/18 : 0), and GlcCer (d18:1/18 : 0)) have good discrimination ability for the CPZ group. In conclusion, the differential metabolites have great potential to serve as biomarkers of demyelinating diseases. In addition, we identified metabolic pathways associated with CPZ-induced demyelination pathogenesis, which provided a new perspective for understanding the relationship between metabolites and CNS demyelination pathogenesis.

An integrative microenvironment approach for laryngeal carcinoma: the role of immune/methylation/autophagy signatures on disease clinical prognosis and single-cell genotypes.

The effects of methylation/autophagy-related genes (MARGs) and immune infiltration in the tumor microenvironment on the prognosis of laryngeal cancer were comprehensively explored in this study. Survival analysis screened out 126 MARGs and 10 immune cells potentially associated with the prognosis of laryngeal carcinoma. Cox and lasso regression analyses were then used to select 8 MARGs (CAPN10, DAPK2, MBTPS2, ST13, CFLAR, FADD, PEX14 and TSC2) and 2 immune cells (Eosinophil and Mast cell) to obtain the prognostic risk scoring system (pRS). The pRS was used to establish a risk prediction model for the prognosis of laryngeal cancer. The predictive ability of the prediction model was evaluated by GEO datasets and our clinical samples. Further analysis revealed that pRS is highly associated with single nucleotide polymorphism (SNP), copy number variation (CNV), immune checkpoint blockade (ICB) therapy and tumor microenvironment. Moreover, the screened pRS-related ceRNA network and circ_0002951/miR-548k/HAS2 pathway provide potential therapeutic targets and biomarkers of laryngocarcinoma. Based on the clustering results of pRS-related genes, single cells were then genotyped and revealed by integrated scRNA-seq in laryngeal cancer samples. Fibroblasts were found enriched in high risk cell clusters at the scRNA-seq level. Fibroblast-related ligand-receptor interactions were then exposed and a neural network-based deep learning model based on these pRS-related hub gene signatures was also established with a high accuracy in cell type prediction. In conclusion, the combination of single-cell and transcriptome laryngeal carcinoma landscape analyses can investigate the link between the tumor microenvironmental and prognostic characteristics.

lncRNA DLEU2 acts as a miR-181a sponge to regulate SEPP1 and inhibit skeletal muscle differentiation and regeneration.

Sarcopenia is a serious public health problem associated with the loss of muscle mass and function. The purpose of this study was to identify molecular markers and construct a ceRNA pathway as a significant predictor of sarcopenia. We designed a prediction model to select important differentially expressed mRNAs (DEMs), and constructed a sarcopenia associated ceRNA network. After correlation analysis of each element in the ceRNA network based on clinical samples and GTEX database, C2C12 mouse myoblasts were used as a model to verify the identified ceRNA pathways. A new model for predicting sarcopenia based on four molecular markers SEPP1, SV2A, GOT1, and GFOD1 was developed. The model was used to construct a ceRNA network and showed high accuracy. Correlation analysis showed that the expression levels of lncDLEU2, SEPP1, and miR-181a were closely associated with a high risk of sarcopenia. lncDLEU2 inhibits muscle differentiation and regeneration by acting as a miR-181a sponge regulating SEPP1 expression. In this study, a highly accurate prediction tool was developed to improve the prediction outcomes of sarcopenia. These findings suggest that the lncDLEU2-miR-181a-SEPP1 pathway inhibits muscle differentiation and regeneration. This pathway may be a new therapeutic target for the treatment of sarcopenia.

A prediction modeling based on SNOT-22 score for endoscopic nasal septoplasty: a retrospective study.

BACKGROUND: To create a nomogram prediction model for the efficacy of endoscopic nasal septoplasty, and the likelihood of patient benefiting from the operation. METHODS: A retrospective analysis of 155 patients with nasal septum deviation (NSD) was performed to develop a predictive model for the efficacy of endoscopic nasal septoplasty. Quality of life (QoL) data was collected before and after surgery using Sinonasal Outcome Test-22 (SNOT-22) scores to evaluate the surgical outcome. An effective surgical outcome was defined as a SNOT-22 score change ≥ 9 points after surgery. Multivariate logistic regression analysis was then used to establish a predictive model for the NSD treatment. The predictive quality and clinical utility of the predictive model were assessed by C-index, calibration plots, and decision curve analysis. RESULTS: The identified risk factors for inclusion in the predictive model were included. The model had a good predictive power, with a AUC of 0.920 in the training group and a C index of 0.911 in the overall sample. Decision curve analysis revealed that the prediction model had a good clinical applicability. CONCLUSIONS: Our prediction model is efficient in predicting the efficacy of endoscopic surgery for NSD through evaluation of factors including: history of nasal surgery, preoperative SNOT-22 score, sinusitis, middle turbinate plasty, BMI, smoking, follow-up time, seasonal allergies, and advanced age. Therefore, it can be cost-effective for individualized preoperative assessment.

MiR-1908/EXO1 and MiR-203a/FOS, regulated by scd1, are associated with fracture risk and bone health in postmenopausal diabetic women.

BACKGROUND: Stearoyl-coenzyme A desaturase-1 (SCD1) can inhibit the development of diabetic bone disease by promoting osteogenesis. In this study, we examined whether this regulation by SCD1 is achieved by regulating the expression of related miRNAs. METHODS: SCD1 expression levels were observed in human bone-marrow mesenchymal stem cells (BM-MSCs) of patients with type 2 diabetes mellitus (T2DM), and the effect of SCD1 on osteogenesis was observed in human adipose-derived MSCs transfected with the SCD1 lentiviral system. We designed a bioinformatics prediction model to select important differentially expressed miRNAs, and established protein-protein interaction and miRNA-mRNA networks. miRNAs and mRNAs were extracted and their differential expression was detected. The SCD1-miRNA-mRNA network was validated. FINDINGS: SCD1 expression in bone marrow was downregulated in patients with T2DM and low-energy fracture, and SCD1 expression promotes BM-MSC osteogenic differentiation. The predictors in the nomogram were seven microRNAs, including hsa-miR-1908 and hsa-miR-203a. SCD1 inhibited the expression of CDKN1A and FOS, but promoted the expression of EXO1 and PLS1. miR-1908 was a regulator of EXO1 expression, and miR-203a was a regulator of FOS expression. INTERPRETATION: The regulation of BM-MSCs by SCD1 is a necessary condition for osteogenesis through the miR-203a/FOS and miR-1908/EXO1 regulatory pathways.

Predicting the risk of sarcopenia in elderly patients with patellar fracture: development and assessment of a new predictive nomogram.

PURPOSE: To develop a risk prediction model for postoperative sarcopenia in elderly patients with patellar fractures in China. PATIENTS AND METHODS: We conducted a community survey of patients aged ≥55 years who underwent surgery for patellar fractures between January 2013 and October 2018, through telephone interviews, community visits, and outpatient follow-up. We established a predictive model for assessing the risk of sarcopenia after patellar fractures. We developed the prediction model by combining multivariate logistic regression analysis with the least absolute shrinkage model and selection operator regression (lasso analysis) as well as the Support Vector Machine (SVM) algorithm. The predictive quality and clinical utility of the predictive model were determined using C-index, calibration plots, and decision curve analysis. We also conducted internal sampling methods for qualitative assessment. RESULT: We recruited 137 participants (53 male; mean age, 65.7 years). Various risk factors were assessed, and low body mass index and advanced age were identified as the most important risk factor (P < 0.05). The prediction rate of the model was good (C-index: 0.88; 95% CI [0.80552-0.95448]), with a satisfactory correction effect. The C index is 0.97 in the validation queue and 0.894 in the entire cohort. Decision curve analysis suggested good clinical practicability. CONCLUSION: Our prediction model shows promise as a cost-effective tool for predicting the risk of postoperative sarcopenia in elderly patients based on the following: advanced age, low body mass index, diabetes, less outdoor exercise, no postoperative rehabilitation, different surgical methods, diabetes, open fracture, and removal of internal fixation.

Reliability of synovial fluid alpha-defensin and leukocyte esterase in diagnosing periprosthetic joint infection (PJI): a systematic review and meta-analysis.

BACKGROUND: Synovial fluid proteins had been applied as diagnostic biomarkers for periprosthetic joint infection (PJI) in recent research papers. Thus, this meta-analysis aimed to estimate the diagnostic efficiency of synovial fluid α-defensin and leukocyte esterase (LE) for PJI. METHODS: We conducted our systematic review by searching the keywords in online databases such as PubMed, Embase, Cochrane, Elsevier, Springer, and Web of Science from the time of database inception to October 2018. Inclusion criteria were as follows: patients who have undergone knee, hip, or shoulder joint replacements; α-defensin or leukocyte esterase (LE strip) of synovial fluid was detected as the biomarker for PJI diagnosis; and Musculoskeletal Infection Society (MSIS) or utilizing a combination of clinical data was considered as the gold standard. Diagnostic parameters including sensitivity, specificity, diagnostic odds ratio (DOR), and area under the summary of receiver operating characteristics curve (AUSROC) were calculated for the included studies to evaluate the synovial fluid α-defensin and LE for PJI diagnosis. RESULTS: After full-text review, 28 studies were qualified for this systematic review, 16 studies used α-defensin and the other 12 were conducted using LE strip. The pooled sensitivity, specificity, and DOR of LE strip were 87% (95% CI 84-90%), 96% (95% CI 95-97%), and 170.09 (95% CI 97.63-296.32), respectively, while the pooled sensitivity, specificity, and DOR of α-defensin were 87% (95% CI 83-90%), 97% (95% CI 96-98%), and 158.18 (95% CI 74.26-336.91), respectively. The AUSROC for LE strip and α-defensin were 0.9818 and 0.9685, respectively. CONCLUSION: Both LE strip and α-defensin of synovial fluid provide rapid and convenient diagnosis for PJI. Sensitivity of α-defensin and LE strip are the same, while both these two methods have high specificity in clinical practice.