{"document":"journal-rps/record","document_version":"1.2","document_notes":{"1.1":"Added the canonical source the journal holds and the execution evidence another application produced. The sections that were already here say what they said in 1.0.","1.2":"Added the scope of a re-execution verdict: what the run re-executed, what it did not, and how much of the registered work answered. A verdict on a check of the paper's printed figures and a verdict on a re-run protocol are now stated apart. No earlier section changed."},"generated_at":"2026-11-09T19:40:28+00:00","publisher":"Journal of Open Source Science","what_this_is":"The journal's record for one paper, as one file. It holds the paper as it was read, the readings made of it, the registered plan, the runs, the result and the ledger behind it. A reading is a reading, a run is a run, and a verdict is not an editorial decision. The runs section records Journal executions. The execution_evidence section holds analyses performed by Automated Assays, with their source versions and results.","record":{"id":"09656134-57e5-49dc-b62a-b2810a9e319a","title":"Differentially Expressed Genes Reveal the Biomarkers and Molecular Mechanism of Osteonecrosis.","state":"submitted","article_type":"original_research","relationship_kind":"original","revision":0,"version":1,"synthetic":false,"doi":"10.1155/2022/8684137","authors":["Huanzhi Ma","Wei Zhang","Jun Shi"],"abstract":"Osteonecrosis is one of the most refractory orthopedic diseases, which seriously threatens the health of old patients. High-throughput sequencing (HTS) and microarray analysis have confirmed as an effective way for investigating the pathological mechanism of disease. In this study, GSE7716, GSE74089, and GSE123568 were obtained from Gene Expression Omnibus (GEO) database and used to identify differentially expressed genes (DEGs) by R language. Subsequently, the DEGs were analyzed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Moreover, the protein-protein interaction (PPI) network of DEGs was analyzed by STRING database and Cytoscape. The results showed that 318 downregulated genes and 58 upregulated genes were observed in GSE7116; 690 downregulated genes and 1148 upregulated genes were screened from 34183 genes in GSE74089. The DEGs involved in progression of osteonecrosis involved inflammation, immunological rejection, and bacterial infection-related pathways. The GO enrichment showed that osteonecrosis was related with extracellular matrix, external encapsulating structure organization, skeletal system development, immune response activity, cell apoptosis, mononuclear cell differentiation, and serine/threonine kinase activity. Moreover, PPI network showed that the progression of osteonecrosis of the femoral head was related with CCND1, CDH1, ESR1, SPP1, LOX, JUN, ITGA, ABL1, and VEGF, and osteonecrosis of the jaw is related with ACTB, CXCR4, PTPRC, IL1B, CXCL8, TNF, JUN, PTGS2, FOS, and RHOA. In conclusion, this study identified the hub factors and pathways which might play important roles in progression of osteonecrosis and could be used as potential biomarkers for diagnosis and treatment of osteonecrosis.","package_hash":"6e4fb3f55c37680dff018daf68bcfa954bf68abb0a1b6a203c275ef14a535282","plan_hash":null,"plan_version":null,"first_receipt_at":"2026-11-04T07:03:23+00:00","decided_at":null,"days_open":5,"intake":{"method":"sci_import","source_name":"Journal of healthcare engineering","source_identifier":"pmid:35035862","source_url":null,"corpus_record_id":"pmid:35035862","recorded_by":"Journal Editor","ingested_at":"2026-11-04T07:03:23+00:00"},"lineage":{"relationship":"original","parent":null,"descendants":[]}},"source_text":{"held":false,"kind":"abstract","what_the_kind_means":"only the abstract was read","characters":null,"sha256":null,"intact":null,"note":"The hash is of the text as it arrived. 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High-throughput sequencing (HTS) and microarray analysis have confirmed as an effective way for investigating the pathological mechanism of disease. In this study, GSE7716, GSE74089, and GSE123568 were obtained from Gene Expression Omnibus (GEO) database and used to identify differentially expressed genes (DEGs) by R language. Subsequently, the DEGs were analyzed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Moreover, the protein-protein interaction (PPI) network of DEGs was analyzed by STRING database and Cytoscape. The results showed that 318 downregulated genes and 58 upregulated genes were observed in GSE7116; 690 downregulated genes and 1148 upregulated genes were screened from 34183 genes in GSE74089. The DEGs involved in progression of osteonecrosis involved inflammation, immunological rejection, and bacterial infection-related pathways. The GO enrichment showed that osteonecrosis was related with extracellular matrix, external encapsulating structure organization, skeletal system development, immune response activity, cell apoptosis, mononuclear cell differentiation, and serine/threonine kinase activity. Moreover, PPI network showed that the progression of osteonecrosis of the femoral head was related with CCND1, CDH1, ESR1, SPP1, LOX, JUN, ITGA, ABL1, and VEGF, and osteonecrosis of the jaw is related with ACTB, CXCR4, PTPRC, IL1B, CXCL8, TNF, JUN, PTGS2, FOS, and RHOA. In conclusion, this study identified the hub factors and pathways which might play important roles in progression of osteonecrosis and could be used as potential biomarkers for diagnosis and treatment of osteonecrosis.\",\n  \"claims\": [\n   {\n    \"id\": \"claim-method\",\n    \"statement\": \"After that, the difference in mRNA level of the dataset was obtained by the lmFit and eBayes function in limma package. 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High-throughput sequencing (HTS) and microarray analysis have confirmed as an effective way\"\n   ],\n   \"order_basis\": \"paper_text_order:206\",\n   \"id\": \"assay:1\"\n  },\n  {\n   \"role\": \"data_generation\",\n   \"definition_id\": \"apoptosis_assay\",\n   \"definition_version\": \"99e1195c7d6f\",\n   \"definition_digest\": null,\n   \"required_operations\": [],\n   \"support_state\": \"partial\",\n   \"source_hashes\": {\n    \"assay_lexicon\": \"99e1195c7d6f\"\n   },\n   \"confidence\": 0.69,\n   \"evidence\": [\n    \"development, immune response activity, cell apoptosis, mononuclear cell differentiation, and serin\"\n   ],\n   \"order_basis\": \"paper_text_order:1258\",\n   \"id\": \"assay:2\"\n  },\n  {\n   \"role\": \"analysis\",\n   \"definition_id\": \"differential_expression\",\n   \"definition_version\": \"f2132e96ae6c7a4e\",\n   \"definition_digest\": null,\n   \"required_operations\": [\n    \"normalise_counts\",\n    \"differential_expression_fit\",\n    \"fdr_bh\"\n   ],\n   \"support_state\": \"supported\",\n   \"source_hashes\": {\n    \"dsl_catalogue\": \"f2132e96ae6c7a4e\"\n   },\n   \"confidence\": 1.0,\n   \"evidence\": [\n    \"After that, the difference in mRNA level of the dataset was obtained by the lmFit and eBayes function in limma package. Finally, the genes with significantly different expression (P < 0.05) were obtained. The corresponding P value of gene symbols following a t-test was defined as the adjusted p value; log2 fold change >2 and P < 0.05 were considered to be the cut-off criteria for differentially expressed genes (DEGs).\"\n   ],\n   \"order_basis\": \"consumes_earlier_output\",\n   \"id\": \"assay:3\"\n  }\n ]\n}\n","document":{"sci_version":"1.2","schema":"https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json","id":"pmid:35035862","kind":"science-record","revision":5,"content_hash":"sha256:b44849eeb7550066e0b4fa757265197b72209628678e02a248f9979c4eb8b427","created_at":"2026-11-01T17:36:45Z","updated_at":"2026-11-01T22:48:14Z","generator":{"name":"corpus-assay-engine","run_id":"reading-sci-2026-11-01"},"paper":{"state":"complete","title":"Differentially Expressed Genes Reveal the Biomarkers and Molecular Mechanism of Osteonecrosis.","doi":"10.1155/2022/8684137","pmid":"35035862","authors":["Huanzhi Ma","Wei Zhang","Jun Shi"],"journal":"Journal of healthcare engineering","year":2022,"abstract":"Osteonecrosis is one of the most refractory orthopedic diseases, which seriously threatens the health of old patients. High-throughput sequencing (HTS) and microarray analysis have confirmed as an effective way for investigating the pathological mechanism of disease. In this study, GSE7716, GSE74089, and GSE123568 were obtained from Gene Expression Omnibus (GEO) database and used to identify differentially expressed genes (DEGs) by R language. Subsequently, the DEGs were analyzed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Moreover, the protein-protein interaction (PPI) network of DEGs was analyzed by STRING database and Cytoscape. The results showed that 318 downregulated genes and 58 upregulated genes were observed in GSE7116; 690 downregulated genes and 1148 upregulated genes were screened from 34183 genes in GSE74089. The DEGs involved in progression of osteonecrosis involved inflammation, immunological rejection, and bacterial infection-related pathways. The GO enrichment showed that osteonecrosis was related with extracellular matrix, external encapsulating structure organization, skeletal system development, immune response activity, cell apoptosis, mononuclear cell differentiation, and serine/threonine kinase activity. Moreover, PPI network showed that the progression of osteonecrosis of the femoral head was related with CCND1, CDH1, ESR1, SPP1, LOX, JUN, ITGA, ABL1, and VEGF, and osteonecrosis of the jaw is related with ACTB, CXCR4, PTPRC, IL1B, CXCL8, TNF, JUN, PTGS2, FOS, and RHOA. In conclusion, this study identified the hub factors and pathways which might play important roles in progression of osteonecrosis and could be used as potential biomarkers for diagnosis and treatment of osteonecrosis.","claims":[{"id":"claim-method","statement":"After that, the difference in mRNA level of the dataset was obtained by the lmFit and eBayes function in limma package. Finally, the genes with significantly different expression (P < 0.05) were obtained. The corresponding P value of gene symbols following a t-test was defined as the adjusted p value; log2 fold change >2 and P < 0.05 were considered to be the cut-off criteria for differentially expressed genes (DEGs).","kind":"methodological","target":null,"evidence":[{"asset":"source:pmid:35035862","locator":"sections[4] \"2.2. Differential Genes Analysis\" paragraph 2","quote":"After that, the difference in mRNA level of the dataset was obtained by the lmFit and eBayes function in limma package. Finally, the genes with significantly different expression (P < 0.05) were obtained. The corresponding P value of gene symbols following a t-test was defined as the adjusted p value; log2 fold change >2 and P < 0.05 were considered to be the cut-off criteria for differentially expressed genes (DEGs)."}],"state":"complete"},{"id":"claim-data-access","statement":"The data used to support the findings of this study are available on reasonable request from the corresponding author.","kind":"methodological","target":null,"evidence":[{"asset":"source:pmid:35035862","locator":"sections[14] \"Data Availability\" paragraph 2","quote":"The data used to support the findings of this study are available on reasonable request from the corresponding author."}],"state":"complete"},{"id":"claim-target-result","statement":"Differential-expression analysis identified 318 downregulated and 58 upregulated genes in GSE7116, and 690 downregulated and 1,148 upregulated genes in GSE74089.","kind":"qualitative","target":null,"evidence":[{"asset":"source:pmid:35035862","locator":"sections[0] \"Abstract\" paragraph 1","quote":"The results showed that 318 downregulated genes and 58 upregulated genes were observed in GSE7116; 690 downregulated genes and 1148 upregulated genes were screened from 34183 genes in GSE74089."}],"state":"complete"}],"gaps":[]},"experiment":{"state":"complete","objective":"Differential-expression analysis identified 318 downregulated and 58 upregulated genes in GSE7116, and 690 downregulated and 1,148 upregulated genes in GSE74089.","steps":[{"id":"read_published_estimate","order":1,"name":"Read the published estimate from the source","kind":"other","state":"complete","blocked_on":null,"description":"The claim, method and evidence span published with the source article.","duration_hours":null,"parameters":[],"inputs":["source:pmid:35035862"],"outputs":["the published estimate and its evidence"],"instruments":[],"reagents":[]},{"id":"obtain_source_data","order":2,"name":"Obtain the source data from the named repository","kind":"data-preparation","state":"complete","blocked_on":null,"description":"The GEO series accession resolves and its sample accessions are listed. 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