Machine learning adjusted sequential CUSUM-analyses are superior to cross-sectional analysis of excess mortality after surgery DOI Creative Commons

Florian Bösch,

Stina Schild-Suhren,

Elif Yılmaz

et al.

International Journal of Medical Informatics, Journal Year: 2024, Volume and Issue: 193, P. 105684 - 105684

Published: Nov. 9, 2024

The assessment of clinical outcome quality, particularly in surgery, is crucial for healthcare improvement. Traditional cross-sectional analyses often fall short timely and systematic identification quality issues. This study explores the efficacy machine learning adjusted sequential CUSUM (Cumulative Sum) monitoring post-surgical mortality. Utilizing Global Open Source Severity Illness Score (GOSSIS) dataset involving 91,714 patient records from 147 hospitals, this involved development a model mortality using modified LightGBM algorithm. With this, cross sectional was simulated compared. demonstrated superior predictive accuracy (ROC AUC 0.88). Simulations revealed that AI risk-adjusted required fewer alterations to detect atypical trends compared standard methods. analysis represents significant advancement healthcare, especially surgery. Its ability minor discrepancies rates with greater sensitivity specificity positions it as valuable tool providers. approach could lead earlier interventions improved care.

Language: Английский

Proteome‐wide profiling reveals dysregulated molecular features and accelerated aging in osteoporosis: A 9.8‐year prospective study DOI Creative Commons
Jinjian Xu, Xue Cai,

Zelei Miao

et al.

Aging Cell, Journal Year: 2023, Volume and Issue: 23(2)

Published: Nov. 16, 2023

Abstract The role of circulatory proteomics in osteoporosis is unclear. Proteome‐wide profiling holds the potential to offer mechanistic insights into osteoporosis. Serum proteome with 413 proteins was profiled by liquid chromatography–tandem mass spectrometry (LC–MS/MS) at baseline, and 2nd, 3rd follow‐ups (7704 person‐tests) prospective Chinese cohorts 9.8 follow‐up years: discovery cohort ( n = 1785) internal validation 1630). Bone mineral density (BMD) measured using dual‐energy X‐ray absorptiometry (DXA) 1 through 3 lumbar spine (LS) femoral neck (FN). We used Light Gradient Boosting Machine (LightGBM) identify (OP)‐related proteomic features. relationships between serum BMD two were estimated linear mixed‐effects model (LMM). Meta‐analysis then performed explore combined associations. identified 53 associated LightGBM, a meta‐analysis showed that 22 these illuminated significant correlation p < 0.05). most common among them PHLD, SAMP, PEDF, HPTR, APOA1, SHBG, CO6, A2MG, CBPN, RAIN APOD, THBG. generate biological age (BA) bone. Each SD‐year increase KDM‐Proage higher risk LS‐OP (hazard ratio [HR], 1.25; 95% CI, 1.14–1.36, 4.96 × 10 −06 ), FN‐OP (HR, 1.13; 1.02–1.23, 9.71 −03 ). findings uncovered apolipoproteins, zymoproteins, complements, binding presented new could be crucial indicator for evaluating bone aging.

Language: Английский

Citations

15
Bioinformatic analysis of related immune cell infiltration and key genes in the progression of osteonecrosis of the femoral head DOI Creative Commons

Xudong Duan,

Fangze Xing,

Jiewen Zhang

et al.

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 14

Published: Jan. 11, 2024

Objective Osteonecrosis of the femoral head (ONFH) is a common orthopedic condition that will prompt joint dysfunction, significantly impacting patients’ quality life. However, specific pathogenic mechanisms underlying this disease remain elusive. The objective study to examine differentially expressed messenger RNAs (DE mRNAs) and key genes linked ONFH, concurrently investigating immune cell infiltration features in ONFH patients through application CIBERSORT algorithm. Methods Microarray was applied scrutinize mRNA expression profiles both healthy controls, with data integration sourced from GEO database. DE mRNAs were screened using Limma method. biological functions explored Kyoto Encyclopedia Genes Genomes (KEGG) pathway enrichment analysis, Gene Ontology (GO) functional Set Enrichment Analysis (GSEA). Additionally, support vector machine–recursive feature elimination (SVM-RFE) least absolute shrinkage selection operator (LASSO) employed discern diagnostic biomarkers associated disease. Receiver operating characteristic (ROC) analysis utilized assess statistical performance genes. validation performed qRT-PCR bone tissues obtained controls. Osteogenic differentiation BMSC then detected by alkaline phosphatase staining (ALP) verify correlation between osteogenic differentiation. Finally, executed evaluate dysregulation exploring cells Results After consolidating datasets, method revealed 107 DEGs, comprising 76 downregulated 31 upregulated close associations these such as migration, osteoblast differentiation, cartilage development extracellular region. Machine learning algorithms further identified APOD, FBXO43 LRP12 ROC curves demonstrated high efficacy results showed levels consistent those microarray analysis. In addition, vitro experiments APOD closely related BMSC. Immune suggested imbalances Neutrophils, Monocytes, Macrophages M2, Dendritic activated resting. Conclusion BMSCs can be used marker ONFH. differs controls patients.

Language: Английский

Citations

6
From Genomics to Metabolomics: Molecular Insights into Osteoporosis for Enhanced Diagnostic and Therapeutic Approaches DOI Creative Commons
Qingmei Li, Jihan Wang,

Congzhe Zhao

et al.

Biomedicines, Journal Year: 2024, Volume and Issue: 12(10), P. 2389 - 2389

Published: Oct. 18, 2024

Osteoporosis (OP) is a prevalent skeletal disorder characterized by decreased bone mineral density (BMD) and increased fracture risk. The advancements in omics technologies—genomics, transcriptomics, proteomics, metabolomics—have provided significant insights into the molecular mechanisms driving OP. These technologies offer critical perspectives on genetic predispositions, gene expression regulation, protein signatures, metabolic alterations, enabling identification of novel biomarkers for diagnosis therapeutic targets. This review underscores potential these multi-omics approaches to bridge gap between basic research clinical applications, paving way precision medicine OP management. By integrating technologies, researchers can contribute improved diagnostics, preventative strategies, treatments patients suffering from related conditions.

Language: Английский

Citations

4
Iron overload-induced ferroptosis of osteoblasts as a potential therapeutic target for osteoporosis DOI
Shuangqing Li, Shan Wan,

Yanting He

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 19, 2025

Abstract Osteoporosis is a systemic skeletal disorder marked by reduced bone mass, compromised microarchitecture, heightened fragility, and an increased risk of fractures. Fractures resulting from osteoporosis are leading cause mortality disability among the elderly. Ferroptosis emerging form programmed cell death that occurs due to unregulated iron-dependent lipid peroxidation. Our study reveals high-iron exposure triggers ferroptosis in osteoblasts through FTH1/FTL pathway, as demonstrated both in vivo vitro experiments. Ferroptotic initiate co-stimulatory pathway fosters osteoclast differentiation, culminating osteoporotic phenotype mice. We propose intervention mice could be utilized novel model for replicating clinical osteoporosis, inhibiting may represent promising therapeutic strategy treatment osteoporosis. Overall, our findings offer fresh perspectives on pathogenesis OP identify potential new targets management this condition.

Language: Английский

Citations

0
Proteomic Insights into Osteoporosis: Unraveling Diagnostic Markers and Therapeutic Targets for the Metabolic Bone Disease DOI Open Access

Jihan Wang,

Mengju Xue,

Ya Hu

et al.

Published: April 1, 2024

Osteoporosis (OP), a prevalent skeletal disorder characterized by compromised bone strength and increased susceptibility to fractures, poses significant public health concern. This review aims provide comprehensive analysis of the current state research in field, focusing on application proteomic techniques elucidate diagnostic markers therapeutic targets for OP. The integration cutting-edge technologies has enabled identification quantification proteins associated with metabolism, leading deeper understanding molecular mechanisms underlying In this review, we systematically examine recent advancements studies related OP, emphasizing potential biomarkers OP diagnosis discovery novel targets. Additionally, discuss challenges future directions highlighting impact transforming landscape treatment.

Language: Английский

Citations

3
Proteomic Insights into Osteoporosis: Unraveling Diagnostic Markers of and Therapeutic Targets for the Metabolic Bone Disease DOI Creative Commons
Jihan Wang,

Mengju Xue,

Ya Hu

et al.

Biomolecules, Journal Year: 2024, Volume and Issue: 14(5), P. 554 - 554

Published: May 4, 2024

Osteoporosis (OP), a prevalent skeletal disorder characterized by compromised bone strength and increased susceptibility to fractures, poses significant public health concern. This review aims provide comprehensive analysis of the current state research in field, focusing on application proteomic techniques elucidate diagnostic markers therapeutic targets for OP. The integration cutting-edge technologies has enabled identification quantification proteins associated with metabolism, leading deeper understanding molecular mechanisms underlying In this review, we systematically examine recent advancements studies related OP, emphasizing potential biomarkers OP diagnosis discovery novel targets. Additionally, discuss challenges future directions highlighting impact transforming landscape treatment.

Language: Английский

Citations

3
Proteomics in orthopedic research: Recent studies and their translational implications DOI
George Li, Argyrios Stampas, Yoshihiro Komatsu

et al.

Journal of Orthopaedic Research®, Journal Year: 2024, Volume and Issue: 42(8), P. 1631 - 1640

Published: June 19, 2024

Abstract Proteomics is a growing field that offers insights into various aspects of disease processes and therapy responses. Within the orthopedics, there are variety diseases have poor prognosis due to lack targeted curative or modifying therapy. Other been difficult manage in part clinical biomarkers offer meaningful insight progression severity. As an emerging technology, proteomics has increasingly applied studying bone biology assortment orthopedics related diseases, such as osteoarthritis, osteosarcoma tumors, osteoporosis, traumatic injury, spinal cord hip knee arthroplasty, fragile healing. These efforts range from mechanistic studies for elucidating novel tissue activity metabolism identification candidate diagnosis, prognosis, treatment. The knowledge gained these proteomic functional provided unique perspectives orthopedic diseases. In this review, we seek report on current state study overview advances clinically applicable discoveries, discuss opportunities may guide us future research.

Language: Английский

Citations

3
Nonlinear relationship between cardiometabolic index and bone mineral density in U.S. adults: the mediating role of percent body fat DOI Creative Commons

Heng Liu,

Huqiang Dong,

Yu Zhou

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Sept. 28, 2024

Language: Английский

Citations

2
An updated overview of the search for biomarkers of osteoporosis based on human proteomics DOI Creative Commons

Xiong‐Yi Wang,

Ruizhi Zhang,

Yi‐Ke Wang

et al.

Journal of Orthopaedic Translation, Journal Year: 2024, Volume and Issue: 49, P. 37 - 48

Published: Oct. 3, 2024

Language: Английский

Citations

2
Proteomic Biomarkers Associated with Low Bone Mineral Density: A Systematic Review DOI Open Access

Adriana Becerra‐Cervera,

Anna D. Argoty-Pantoja, Diana I. Aparicio‐Bautista

et al.

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(14), P. 7526 - 7526

Published: July 9, 2024

Osteoporosis is a globally relevant public health issue. Our study aimed to summarize the knowledge on proteomic biomarkers for low bone mineral density over last years. We conducted systematic review following PRISMA guidelines; scoured databases were PubMed, Web of Sciences, Scopus, and EBSCO, from inception 2 June 2023. A total 610 studies identified 33 assessed eligibility. Finally, 29 met criteria this review. The risk bias was evaluated using Joanna Briggs Institute Critical Appraisal Checklist tool. From selected, 154 proteins associated with changes density, which only 10 reported in at least two articles. protein-protein network analysis indicated potential involved skeletal system, immune system process, regulation protein metabolic signaling, transport, cellular component assembly, cell differentiation, hemostasis, extracellular matrix organization. Mass spectrometry-based profiling has allowed discovery new diagnostic potential. However, it necessary compare validate different populations determine their association metabolism evaluate translation clinical management osteoporosis.

Language: Английский

Citations

1