CoChat
Sign Up
Cited by 126

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Exosome-based bone-targeting drug delivery alleviates impaired osteoblastic bone formation and bone loss in inflammatory bowel diseases

Guo, Jiawei, Wang, Fuxiao, Hu, Yan, Luo, Ying, Wei, Yan, Xu, Ke, Zhang, Hao, Liu, Han, Bo, Lumin, Lv, Shunli, Sheng, Shihao, Zhuang, Xinchen, Zhang, Tao, Xu, Can, Chen, Xiao, Su, Jiacan·2023·Cell Reports Medicine
DOI 10.1016/j.xcrm.2022.100881PMC PMC9873828
Open this paper in CoChat — free account

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.xcrm.2022.100881

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Figures

Graphical abstract
Graphical abstract CC BY-NC-ND · PubMed Central
Figure 1 UC models showed reduced bone mass but increased bone marrow adipose (A) Representative μCT reconstruction images of the femurs. Overall view (left), trabecular bone (right, upper), cortical bone (right, lower). n = 5. (B) Quantitative analysis of the trabecular bone including BV/TV, Tb.Th, Tb.N, BS/BV, Tb.Sp, and SMI. n = 5. (C) Quantitative analysis of the cortical bone including cortical bone thickness (Cb.Th) and total porosity. n = 5. (D) Representative μCT reconstruction images of the bone marrow adipose tissue. Marrow adipose tissue/marrow volume as a quantitative measurement. n = 5. (E) Image of mechanical stress testing. (F) Maximum load and elasticity modulus of the femurs. n = 5. Data are represented as mean ± SD (error bars) from biological replicates. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001, by non-paired Student’s t test. See also Figures S1–S3.
Figure 1 UC models showed reduced bone mass but increased bone marrow adipose (A) Representative μCT reconstruction images of the femurs. Overall view (left), trabecular bone (right, upper), cortical bone (right, lower). n = 5. (B) Quantitative analysis of the trabecular bone including BV/TV, Tb.Th, Tb.N, BS/BV, Tb.Sp, and SMI. n = 5. (C) Quantitative analysis of the cortical bone including cortical bone thickness (Cb.Th) and total porosity. n = 5. (D) Representative μCT reconstruction images of the bone marrow adipose tissue. Marrow adipose tissue/marrow volume as a quantitative measurement. n = 5. (E) Image of mechanical stress testing. (F) Maximum load and elasticity modulus of the femurs. n = 5. Data are represented as mean ± SD (error bars) from biological replicates. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001, by non-paired Student’s t test. See also Figures S1–S3.CC BY-NC-ND · PubMed Central
Figure 2 UC models showed suppressed osteogenesis but promoted adipogenesis in vivo (A) Representative images of calcein double-labeling assay of periosteum bone (Pb), endosteal bone (Eb), and trabecular bone (Tb) of the femurs. n = 5. Scale bar, 50 μm. (B and C) Bone formation rate (BFR) per bone surface and mineral apposition rate (MAR) of the femurs. n = 5. (D) Immunofluorescence staining of OCN (green) of the femurs. n = 5. Scale bar, 50 μm. (E) Quantitative analysis of OCN+ osteoblast number per bone surface (No.OBs/BS). n = 5. (F) Immunohistochemistry staining of FABP4 (gray) of the femurs. n = 5. Scale bar, 50 μm. (G) Quantitative analysis of FABP4+ fat cell number. n = 5. (H) Ocn and Osterix mRNA expressions. n = 5. (I) Ocn and Osterix protein levels. n = 5. (J) Fabp4 and Adipoq mRNA expressions. n = 5. (K) Fabp4 and Adipoq protein levels. n = 5. Data are represented as mean ± SD (error bars) from biological replicates. ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001, by non-paired Student’s t test. See also Figures S2–S4.
Figure 2 UC models showed suppressed osteogenesis but promoted adipogenesis in vivo (A) Representative images of calcein double-labeling assay of periosteum bone (Pb), endosteal bone (Eb), and trabecular bone (Tb) of the femurs. n = 5. Scale bar, 50 μm. (B and C) Bone formation rate (BFR) per bone surface and mineral apposition rate (MAR) of the femurs. n = 5. (D) Immunofluorescence staining of OCN (green) of the femurs. n = 5. Scale bar, 50 μm. (E) Quantitative analysis of OCN+ osteoblast number per bone surface (No.OBs/BS). n = 5. (F) Immunohistochemistry staining of FABP4 (gray) of the femurs. n = 5. Scale bar, 50 μm. (G) Quantitative analysis of FABP4+ fat cell number. n = 5. (H) Ocn and Osterix mRNA expressions. n = 5. (I) Ocn and Osterix protein levels. n = 5. (J) Fabp4 and Adipoq mRNA expressions. n = 5. (K) Fabp4 and Adipoq protein levels. n = 5. Data are represented as mean ± SD (error bars) from biological replicates. ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001, by non-paired Student’s t test. See also Figures S2–S4.CC BY-NC-ND · PubMed Central
Figure 3 Inflammation in UC inhibited the proliferation of BMSC in vitro (A) IL-1α, IL-1β, and Tnf-α mRNA expressions. n = 5. (B) Representative images of colony-forming unit fibroblast (CFU-F) assay of BMSC. Colony number as quantitative measurements. n = 5. Scale bar, 500 μm. (C) Representative images of alizarin red S staining of BMSCs after 14 day osteogenic induction. Positive cells as quantitative measurements. n = 5. Scale bars, 500 μm (left) and 50 μm (right). (D) Representative images of oil red staining of BMSCs after 21 day adipogenic induction. Positive cells as quantitative measurements. n = 5. Scale bars, 500 μm (left) and 50 μm (right). (E) Ocn, Osterix, and Runx2 mRNA expressions of human BMSCs after 7 day osteogenic induction, with simultaneous treatment of the serum from health volunteers (control group) and patients with UC (UC group), respectively. n = 6. (F) Fabp4, Adipoq, and Pparγ mRNA expressions of human BMSCs after 7 day adipogenic induction, with simultaneous treatment of the serum from health volunteers (control group) and patients with UC (UC group), respectively. n = 6. Data are represented as mean ± SD (error bars) from biological replicates. ns, not significant, ∗p < 0.05, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001, by non-paired Student’s t test. See also Figure S5.
Figure 3 Inflammation in UC inhibited the proliferation of BMSC in vitro (A) IL-1α, IL-1β, and Tnf-α mRNA expressions. n = 5. (B) Representative images of colony-forming unit fibroblast (CFU-F) assay of BMSC. Colony number as quantitative measurements. n = 5. Scale bar, 500 μm. (C) Representative images of alizarin red S staining of BMSCs after 14 day osteogenic induction. Positive cells as quantitative measurements. n = 5. Scale bars, 500 μm (left) and 50 μm (right). (D) Representative images of oil red staining of BMSCs after 21 day adipogenic induction. Positive cells as quantitative measurements. n = 5. Scale bars, 500 μm (left) and 50 μm (right). (E) Ocn, Osterix, and Runx2 mRNA expressions of human BMSCs after 7 day osteogenic induction, with simultaneous treatment of the serum from health volunteers (control group) and patients with UC (UC group), respectively. n = 6. (F) Fabp4, Adipoq, and Pparγ mRNA expressions of human BMSCs after 7 day adipogenic induction, with simultaneous treatment of the serum from health volunteers (control group) and patients with UC (UC group), respectively. n = 6. Data are represented as mean ± SD (error bars) from biological replicates. ns, not significant, ∗p < 0.05, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001, by non-paired Student’s t test. See also Figure S5.CC BY-NC-ND · PubMed Central
Figure 4 Wnt signaling was inhibited in BMSCs from UC models (A) The sorting strategy of BMSCs by flow cytometry. The BMSC is described as the cluster whose expression pattern is Ly6A/E+CD29+CD45−CD11b−. (B and C) The RNA sequencing results of sorted BMSCs. GO and KEGG analysis of differently expressed genes between BMSCs from control and UC mice. n = 3. (D–G) GSEA revealing the enrichment of differently expressed genes in the Wnt (D), Pparγ (E), calcium (F), and NF-κB (G) signaling pathways, respectively. n = 3. (H) The heatmap based on the differently expressed genes between BMSCs from control and UC mice. Representative genes in the Wnt pathway (i), PPARγ (ii), MAPK (iii), TGF-β (iv), and NF-κB pathway are plotted. n = 3. Data were obtained from biological replicates.
Figure 4 Wnt signaling was inhibited in BMSCs from UC models (A) The sorting strategy of BMSCs by flow cytometry. The BMSC is described as the cluster whose expression pattern is Ly6A/E+CD29+CD45−CD11b−. (B and C) The RNA sequencing results of sorted BMSCs. GO and KEGG analysis of differently expressed genes between BMSCs from control and UC mice. n = 3. (D–G) GSEA revealing the enrichment of differently expressed genes in the Wnt (D), Pparγ (E), calcium (F), and NF-κB (G) signaling pathways, respectively. n = 3. (H) The heatmap based on the differently expressed genes between BMSCs from control and UC mice. Representative genes in the Wnt pathway (i), PPARγ (ii), MAPK (iii), TGF-β (iv), and NF-κB pathway are plotted. n = 3. Data were obtained from biological replicates.CC BY-NC-ND · PubMed Central
Figure 5 TNF-α promoted β-catenin degradation and inhibited osteogenic gene expression (A) Co-immunoprecipitation of BMSCs treated by vehicle or recombinant TNF-α. (B) Immunoblotting of downstream molecules of the Wnt and NF-κB signaling pathways in BMSCs after vehicle or recombinant TNF-α treatment. (C) Luciferase reporter assay. BMSC was transfected with β-catenin expression plasmid with TOPFlash reporter. Firefly luciferase activities were measured. (D) Immunoblotting of β-catenin and the presence of ubiquitin. (E) Cycloheximide chasing assay of β-catenin in BMSCs after being treated by vehicle or recombinant TNF-α for 24 h. (F) Immunoblotting of β-catenin in the cytoplasm and nucleus of BMSCs, which were treated by vehicle or recombinant TNF-α for 24 h. (G and H) Chromatin immunoprecipitation (ChIP) assays on the promoter regions of the Runx2 and Osterix genes were performed in BMSCs treated by vehicle or recombinant TNF-α for 24 h. n = 3. Data are represented as mean ± SD (error bars) from biological replicates. ns, not significant, ∗∗∗∗p < 0.0001, by paired Student’s t test.
Figure 5 TNF-α promoted β-catenin degradation and inhibited osteogenic gene expression (A) Co-immunoprecipitation of BMSCs treated by vehicle or recombinant TNF-α. (B) Immunoblotting of downstream molecules of the Wnt and NF-κB signaling pathways in BMSCs after vehicle or recombinant TNF-α treatment. (C) Luciferase reporter assay. BMSC was transfected with β-catenin expression plasmid with TOPFlash reporter. Firefly luciferase activities were measured. (D) Immunoblotting of β-catenin and the presence of ubiquitin. (E) Cycloheximide chasing assay of β-catenin in BMSCs after being treated by vehicle or recombinant TNF-α for 24 h. (F) Immunoblotting of β-catenin in the cytoplasm and nucleus of BMSCs, which were treated by vehicle or recombinant TNF-α for 24 h. (G and H) Chromatin immunoprecipitation (ChIP) assays on the promoter regions of the Runx2 and Osterix genes were performed in BMSCs treated by vehicle or recombinant TNF-α for 24 h. n = 3. Data are represented as mean ± SD (error bars) from biological replicates. ns, not significant, ∗∗∗∗p < 0.0001, by paired Student’s t test.CC BY-NC-ND · PubMed Central
Figure 6 Preparation of bone-targeted and drug-loaded nanoparticles (A) Schematic diagram of exosome isolation including cell culture, gradient centrifugation, and drug (Wnt agonist 1) loading. (B) Morphological image of the NP revealed by transmission electron microscope. (C) Diameter distribution of the NP revealed by nanoparticle tracking analysis (NTA). (D) The protein level of CD9, HSP70, TSG101, CD63, and GLG1 of GLG1-NP and CTRL-NP revealed by western blotting. (E) Organ distribution of Cy5-labeled NP at 4 and 8 h after tail vein injection revealed by biophotonic imaging analysis.
Figure 6 Preparation of bone-targeted and drug-loaded nanoparticles (A) Schematic diagram of exosome isolation including cell culture, gradient centrifugation, and drug (Wnt agonist 1) loading. (B) Morphological image of the NP revealed by transmission electron microscope. (C) Diameter distribution of the NP revealed by nanoparticle tracking analysis (NTA). (D) The protein level of CD9, HSP70, TSG101, CD63, and GLG1 of GLG1-NP and CTRL-NP revealed by western blotting. (E) Organ distribution of Cy5-labeled NP at 4 and 8 h after tail vein injection revealed by biophotonic imaging analysis.CC BY-NC-ND · PubMed Central
Figure 7 GLG1-NP rescued osteoblastic bone formation in UC models (A) Schematic diagram of UC mice treated by GLG1-NP. The femurs were finally collected on day 28. (B) Representative μCT reconstruction images of the femurs. Overall view (left), Tb (top right), and cortical bone (bottom right). n = 5. (C and D) Quantitative analysis of the trabecular and cortical bone revealed by μCT. n = 5. (E) Representative images of calcein double-labeling assay of Pb, Eb, and Tb of the femurs. n = 5. Scale bar, 50 μm. (F and G) BFR per bone surface and MAR of the femurs. n = 5. (H) Immunofluorescence staining of OCN (green) of the femurs. No.OBs/BS as a quantitative measurement. n = 5. Scale bar, 50 μm. (I) Immunohistochemistry staining of FABP4 (gray) of the femurs. FABP4+ fat cell number as a quantitative measurement. n = 5. Scale bar, 50 μm. Data are represented as mean ± SD (error bars) from biological replicates. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001, by two-way ANOVA and Turkey’s multiple comparison test for post hoc analysis. See also Figures S6 and S7.
Figure 7 GLG1-NP rescued osteoblastic bone formation in UC models (A) Schematic diagram of UC mice treated by GLG1-NP. The femurs were finally collected on day 28. (B) Representative μCT reconstruction images of the femurs. Overall view (left), Tb (top right), and cortical bone (bottom right). n = 5. (C and D) Quantitative analysis of the trabecular and cortical bone revealed by μCT. n = 5. (E) Representative images of calcein double-labeling assay of Pb, Eb, and Tb of the femurs. n = 5. Scale bar, 50 μm. (F and G) BFR per bone surface and MAR of the femurs. n = 5. (H) Immunofluorescence staining of OCN (green) of the femurs. No.OBs/BS as a quantitative measurement. n = 5. Scale bar, 50 μm. (I) Immunohistochemistry staining of FABP4 (gray) of the femurs. FABP4+ fat cell number as a quantitative measurement. n = 5. Scale bar, 50 μm. Data are represented as mean ± SD (error bars) from biological replicates. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001, by two-way ANOVA and Turkey’s multiple comparison test for post hoc analysis. See also Figures S6 and S7.CC BY-NC-ND · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 72

  1. Hardy, 2009, Bone loss in inflammatory disorders, J. Endocrinol., 201, 309, 10.1677/JOE-08-0568 · DOI
  2. Merlotti, 2022, Bone fragility in gastrointestinal disorders, Int. J. Mol. Sci., 23, 2713, 10.3390/ijms23052713 · DOI
  3. Liu, 2021, The microbiome in inflammatory bowel diseases: from pathogenesis to therapy, Nat. Nanotechnol., 16, 331, 10.1038/s41565-020-00818-8 · DOI
  4. Kaplan, 2015, The global burden of IBD: from 2015 to 2025, Nat. Rev. Gastroenterol. Hepatol., 12, 720, 10.1038/nrgastro.2015.150 · DOI · Paper page
  5. Ye, 2013, Review of inflammatory bowel disease in China, Sci. World J., 2013, 10.1155/2013/296470 · DOI · Paper page
  6. Rodríguez-Bores, 2007, Basic and clinical aspects of osteoporosis in inflammatory bowel disease, World J. Gastroenterol., 13, 6156, 10.3748/wjg.v13.i46.6156 · DOI
  7. Szafors, 2018, Risk of fracture and low bone mineral density in adults with inflammatory bowel diseases. A systematic literature review with meta-analysis, Osteoporos. Int., 29, 2389, 10.1007/s00198-018-4586-6 · DOI
  8. Lamb, 2019, British Society of Gastroenterology consensus guidelines on the management of inflammatory bowel disease in adults, Gut, 68, s1, 10.1136/gutjnl-2019-318484 · DOI · Paper page
  9. Oliveira, 2017, Diagnosis and management of inflammatory bowel disease in children, BMJ, 357, j2083, 10.1136/bmj.j2083 · DOI
  10. Chen, 2018, RANKL signaling in bone marrow mesenchymal stem cells negatively regulates osteoblastic bone formation, Bone Res., 6, 34, 10.1038/s41413-018-0035-6 · DOI · Paper page
  11. Hu, 2021, RANKL from bone marrow adipose lineage cells promotes osteoclast formation and bone loss, EMBO Rep., 22, 10.15252/embr.202152481 · DOI
  12. Hamdani, 2008, Dextran sodium sulfate-induced colitis causes rapid bone loss in mice, Bone, 43, 945, 10.1016/j.bone.2008.06.018 · DOI
  13. Metzger, 2017, Inflammatory bowel disease in a rodent model alters osteocyte protein levels controlling bone turnover, J. Bone Miner. Res., 32, 802, 10.1002/jbmr.3027 · DOI
  14. Dresner-Pollak, 2004, Interleukin 10-deficient mice develop osteopenia, decreased bone formation, and mechanical fragility of long bones, Gastroenterology, 127, 792, 10.1053/j.gastro.2004.06.013 · DOI
  15. Al Saedi, 2022, Characterization of skeletal phenotype and associated mechanisms with chronic intestinal inflammation in the winnie mouse model of spontaneous chronic colitis, Inflamm. Bowel Dis., 28, 259, 10.1093/ibd/izab174 · DOI
  16. Khosla, 2017, Osteoporosis treatment: recent developments and ongoing challenges, Lancet Diabetes Endocrinol., 5, 898, 10.1016/S2213-8587(17)30188-2 · DOI
  17. Estell, 2021, Emerging insights into the comparative effectiveness of anabolic therapies for osteoporosis, Nat. Rev. Endocrinol., 17, 31, 10.1038/s41574-020-00426-5 · DOI
  18. Bernstein, 2014, What is the role for bisphosphonates in IBD?, Gut, 63, 1369, 10.1136/gutjnl-2013-306141 · DOI
  19. Narayanan, 2018, Inflammation-induced lymphatic architecture and bone turnover changes are ameliorated by irisin treatment in chronic inflammatory bowel disease, Faseb. J., 32, 4848, 10.1096/fj.201800178R · DOI
  20. Chen, 2022, The horizon of bone organoid: a perspective on construction and application, Bioact. Mater., 18, 15
  21. Chen, 2020, Gli1(+) cells couple with type H vessels and are required for type H vessel formation, Stem Cell Rep., 15, 110, 10.1016/j.stemcr.2020.06.007 · DOI
  22. Salhotra, 2020, Mechanisms of bone development and repair, Nat. Rev. Mol. Cell Biol., 21, 696, 10.1038/s41580-020-00279-w · DOI
  23. Leppkes, 2020, Cytokines in inflammatory bowel diseases - update 2020, Pharmacol. Res., 158, 10.1016/j.phrs.2020.104835 · DOI
  24. Yang, 2013, Tumor necrosis factor alpha suppresses the mesenchymal stem cell osteogenesis promoter miR-21 in estrogen deficiency-induced osteoporosis, J. Bone Miner. Res., 28, 559, 10.1002/jbmr.1798 · DOI
  25. Du, 2018, TNF-alpha suppresses osteogenic differentiation of MSCs by accelerating P2Y2 receptor in estrogen-deficiency induced osteoporosis, Bone, 117, 161, 10.1016/j.bone.2018.09.012 · DOI
  26. Russell, 2021, IL-17A and TNF modulate normal human spinal entheseal bone and soft tissue mesenchymal stem cell osteogenesis, adipogenesis, and stromal function, Cells, 10, 341, 10.3390/cells10020341 · DOI
  27. Tevlin, 2017, Pharmacological rescue of diabetic skeletal stem cell niches, Sci. Transl. Med., 9, 10.1126/scitranslmed.aag2809 · DOI
  28. Xue, 2021, Recent advances in design of functional biocompatible hydrogels for bone tissue engineering, Adv. Funct. Mater., 31, 10.1002/adfm.202009432 · DOI
  29. Xue, 2022, Fabrication of physical and chemical crosslinked hydrogels for bone tissue engineering, Bioact. Mater., 12, 327
  30. Song, 2019, Reversal of osteoporotic activity by endothelial cell-secreted bone targeting and biocompatible exosomes, Nano Lett., 19, 3040, 10.1021/acs.nanolett.9b00287 · DOI
  31. Hu, 2021, Exosome-guided bone targeted delivery of Antagomir-188 as an anabolic therapy for bone loss, Bioact. Mater., 6, 2905
  32. Liu, 2022, Bacterial extracellular vesicles as bioactive nanocarriers for drug delivery: advances and perspectives, Bioact. Mater., 14, 169
  33. Esposito, 2019, Bone vascular niche E-selectin induces mesenchymal-epithelial transition and Wnt activation in cancer cells to promote bone metastasis, Nat. Cell Biol., 21, 627, 10.1038/s41556-019-0309-2 · DOI
  34. Wang, 2020, HucMSC-exosomes carrying miR-326 inhibit neddylation to relieve inflammatory bowel disease in mice, Clin. Transl. Med., 10, e113, 10.1002/ctm2.113 · DOI
  35. Holgersen, 2015, Piroxicam treatment augments bone abnormalities in interleukin-10 knockout mice, Inflamm. Bowel Dis., 21, 257, 10.1097/MIB.0000000000000269 · DOI
  36. Seul, 2011, Osteoblast-specific expression of MEF induces osteopenia through downregulation of osteoblastogenesis and upregulation of osteoclastogenesis, J. Bone Miner. Res., 26, 341, 10.1002/jbmr.208 · DOI
  37. Baek, 2012, Myeloid Elf-1-like factor stimulates adipogenic differentiation through the induction of peroxisome proliferator-activated receptor gamma expression in bone marrow, J. Cell. Physiol., 227, 3603, 10.1002/jcp.24064 · DOI
  38. Wang, 2022, Disruption of hematopoiesis attenuates the osteogenic differentiation capacity of bone marrow stromal cells, Stem Cell Res. Ther., 13, 27, 10.1186/s13287-022-02708-3 · DOI
  39. Chang, 2013, NF-kappaB inhibits osteogenic differentiation of mesenchymal stem cells by promoting beta-catenin degradation, Proc. Natl. Acad. Sci. USA, 110, 9469, 10.1073/pnas.1300532110 · DOI
  40. Compston, 2019, Lancet, 393, 364, 10.1016/S0140-6736(18)32112-3 · DOI · Paper page
  41. Liang, 2022, Osteoporosis pathogenesis and treatment: existing and emerging avenues, Cell. Mol. Biol. Lett., 27, 72, 10.1186/s11658-022-00371-3 · DOI
  42. Song, 2022, Advances in pathogenesis and therapeutic strategies for osteoporosis, Pharmacol. Ther., 237, 10.1016/j.pharmthera.2022.108168 · DOI · Paper page
  43. Komatsu, 2022, Mechanisms of joint destruction in rheumatoid arthritis - immune cell-fibroblast-bone interactions, Nat. Rev. Rheumatol., 18, 415, 10.1038/s41584-022-00793-5 · DOI
  44. de Oliveira, 2020, Obesity/metabolic syndrome and diabetes mellitus on peri-implantitis, Trends Endocrinol. Metabol., 31, 596, 10.1016/j.tem.2020.05.005 · DOI
  45. Ke, 2019, Mechanisms underlying bone loss associated with gut inflammation, Int. J. Mol. Sci., 20, 6323, 10.3390/ijms20246323 · DOI
  46. Zouali, 2021, B lymphocytes, the gastrointestinal tract and autoimmunity, Autoimmun. Rev., 20, 10.1016/j.autrev.2021.102777 · DOI
  47. Kaplan, 2017, Understanding and preventing the global increase of inflammatory bowel disease, Gastroenterology, 152, 313, 10.1053/j.gastro.2016.10.020 · DOI · Paper page
  48. Zhou, 2020, Bone mineral density is negatively correlated with ulcerative colitis: a systematic review and meta-analysis, Clin. Transl. Med., 9, 18, 10.1186/s40169-020-00270-0 · DOI
  49. Haschka, 2016, High-resolution quantitative computed tomography demonstrates structural defects in cortical and trabecular bone in IBD patients, J. Crohns Colitis, 10, 532, 10.1093/ecco-jcc/jjw012 · DOI
  50. van Staa, 2003, Inflammatory bowel disease and the risk of fracture, Gastroenterology, 125, 1591, 10.1053/j.gastro.2003.09.027 · DOI
  51. Agrawal, 2011, Bone, inflammation, and inflammatory bowel disease, Curr. Osteoporos. Rep., 9, 251, 10.1007/s11914-011-0077-9 · DOI
  52. Ciucci, 2015, Bone marrow Th17 TNFalpha cells induce osteoclast differentiation, and link bone destruction to IBD, Gut, 64, 1072, 10.1136/gutjnl-2014-306947 · DOI
  53. Chen, 2020, A selected small molecule prevents inflammatory osteolysis through restraining osteoclastogenesis by modulating PTEN activity, Clin. Transl. Med., 10, e240, 10.1002/ctm2.240 · DOI
  54. Meirow, 2022, Specific inflammatory osteoclast precursors induced during chronic inflammation give rise to highly active osteoclasts associated with inflammatory bone loss, Bone Res., 10, 36, 10.1038/s41413-022-00206-z · DOI
  55. Redlich, 2012, Inflammatory bone loss: pathogenesis and therapeutic intervention, Nat. Rev. Drug Discov., 11, 234, 10.1038/nrd3669 · DOI
  56. Bischoff, 1997, Altered bone metabolism in inflammatory bowel disease, Am. J. Gastroenterol., 92, 1157
  57. Silvennoinen, 1996, Increased degradation of type I collagen in patients with inflammatory bowel disease, Gut, 38, 223, 10.1136/gut.38.2.223 · DOI
  58. Ludvigsson, 2019, Fracture risk in patients with inflammatory bowel disease: a nationwide population-based cohort study from 1964 to 2014, Am. J. Gastroenterol., 114, 291, 10.14309/ajg.0000000000000062 · DOI
  59. Ahn, 2022, High risk of fractures within 7 Years of diagnosis in asian patients with inflammatory bowel diseases, Clin. Gastroenterol. Hepatol., 20, e1022, 10.1016/j.cgh.2021.06.026 · DOI
  60. Uluçkan, 2016, Chronic skin inflammation leads to bone loss by IL-17-mediated inhibition of Wnt signaling in osteoblasts, Sci. Transl. Med., 8, 330ra37, 10.1126/scitranslmed.aad8996 · DOI
  61. Munir, 2017, Adipogenic differentiation of mesenchymal stem cells alters their immunomodulatory properties in a tissue-specific manner, Stem Cell., 35, 1636, 10.1002/stem.2622 · DOI
  62. Osorio, 2022, Inflammatory stimuli alter bone marrow composition and compromise bone health in the malnourished host, Front. Immunol., 13, 10.3389/fimmu.2022.846246 · DOI
  63. da Silva, 2016, Obesity modifies bone marrow microenvironment and directs bone marrow mesenchymal cells to adipogenesis, Obesity, 24, 2522, 10.1002/oby.21660 · DOI
  64. Noack, 2015, Prostaglandin E2 impairs osteogenic and facilitates adipogenic differentiation of human bone marrow stromal cells, Prostaglandins Leukot. Essent. Fatty Acids, 94, 91, 10.1016/j.plefa.2014.11.008 · DOI
  65. Tian, 2022, Skeletal muscle mitoribosomal defects are linked to low bone mass caused by bone marrow inflammation in male mice, J. Cachexia Sarcopenia Muscle, 13, 1785, 10.1002/jcsm.12975 · DOI
  66. Li, 2018, PPAR-Gamma and Wnt regulate the differentiation of MSCs into adipocytes and osteoblasts respectively, Curr. Stem Cell Res. Ther., 13, 185, 10.2174/1574888X12666171012141908 · DOI
  67. Soós, 2022, Effects of targeted therapies on bone in rheumatic and musculoskeletal diseases, Nat. Rev. Rheumatol., 18, 249, 10.1038/s41584-022-00764-w · DOI
  68. Cui, 2022, A bone-targeted engineered exosome platform delivering siRNA to treat osteoporosis, Bioact. Mater., 10, 207
  69. Jiang, 2022, Engineered extracellular vesicles for bone therapy, Nano Today, 44, 10.1016/j.nantod.2022.101487 · DOI
  70. Kiesler, 2015, Experimental models of inflammatory bowel diseases, Cell. Mol. Gastroenterol. Hepatol., 1, 154, 10.1016/j.jcmgh.2015.01.006 · DOI
  71. Wirtz, 2017, Chemically induced mouse models of acute and chronic intestinal inflammation, Nat. Protoc., 12, 1295, 10.1038/nprot.2017.044 · DOI · Paper page
  72. Lee, 2014, TSG-6 as a biomarker to predict efficacy of human mesenchymal stem/progenitor cells (hMSCs) in modulating sterile inflammation in vivo, Proc. Natl. Acad. Sci. USA, 111, 16766, 10.1073/pnas.1416121111 · DOI

Cited by

Sorted by citations

See all 126

Metadata

Authors
Guo, J., Wang, F., Hu, Y., Luo, Y., Wei, Y., Xu, K., Zhang, H., Liu, H., Bo, L., Lv, S., Sheng, S., Zhuang, X., Zhang, T., Xu, C., Chen, X., & Su, J.
Venue
Cell Reports Medicine
Publisher
Elsevier BV
Published
2023-01
Volume
4
Issue
1
Pages
100881
ISSN
2666-3791
DOI
10.1016/j.xcrm.2022.100881
PMC
PMC9873828
Cited by
126
References
6
Language
en
Licence
Funders
  • National Natural Science Foundation of China (21QA1412000, 81871099, 82172098, 82230071)
  • Ministry of Science and Technology of the People&apos;s Republic of China (2018YFC2001500)
  • Shanghai Municipality Science and Technology Commission
  • National Key Research and Development Program of China
  • Shanghai Rising-Star Program

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review