cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57992/nmrxiv.p112.s1158.d5024
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ6_Anhydrocyanobacterin F[5]

description: 5
DOI: 10.57992/nmrxiv.p112.s1158.d5025
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ6_Anhydrocyanobacterin F[6]

description: 6
DOI: 10.57992/nmrxiv.p112.s1158.d5026
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ6_Anhydrocyanobacterin F[7]

description: 7
DOI: 10.57992/nmrxiv.p112.s1158.d5027
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ6_Anhydrocyanobacterin F[8]

description: 8
DOI: 10.57992/nmrxiv.p112.s1158
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ6_Anhydrocyanobacterin F
DOI: 10.57992/nmrxiv.p112.s1158.d5028
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ6_Anhydrocyanobacterin F[9]

description: 9
DOI: 10.57992/nmrxiv.p112.s1155.d4982
title: PCC9009_Schanbacher_ACBderivatives_cmp_4_CB[1]

description: 1
DOI: 10.57992/nmrxiv.p112.s1155.d4983
title: PCC9009_Schanbacher_ACBderivatives_cmp_4_CB[10]

description: 10
DOI: 10.57992/nmrxiv.p112.s1155.d4984
title: PCC9009_Schanbacher_ACBderivatives_cmp_4_CB[2]

description: 2
DOI: 10.57992/nmrxiv.p112.s1155.d4985
title: PCC9009_Schanbacher_ACBderivatives_cmp_4_CB[3]

description: 3
DOI: 10.57992/nmrxiv.p112.s1155.d4986
title: PCC9009_Schanbacher_ACBderivatives_cmp_4_CB[4]

description: 4
DOI: 10.57992/nmrxiv.p112.s1155.d4987
title: PCC9009_Schanbacher_ACBderivatives_cmp_4_CB[5]

description: 5
DOI: 10.57992/nmrxiv.p112.s1155.d4988
title: PCC9009_Schanbacher_ACBderivatives_cmp_4_CB[6]

description: 6
DOI: 10.57992/nmrxiv.p112.s1155.d4989
title: PCC9009_Schanbacher_ACBderivatives_cmp_4_CB[7]

description: 7
DOI: 10.57992/nmrxiv.p112.s1155.d4990
title: PCC9009_Schanbacher_ACBderivatives_cmp_4_CB[8]

description: 8
DOI: 10.57992/nmrxiv.p112.s1155.d4991
title: PCC9009_Schanbacher_ACBderivatives_cmp_4_CB[9]

description: 9
DOI: 10.57992/nmrxiv.p112.s1160.d5036
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B[1]

description: 1
DOI: 10.57992/nmrxiv.p112.s1160.d5037
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B[10]

description: 10
DOI: 10.57992/nmrxiv.p112.s1160.d5038
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B[11]

description: 11
DOI: 10.57992/nmrxiv.p112.s1160.d5039
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B[12]

description: 12
DOI: 10.57992/nmrxiv.p112.s1160.d5040
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B[13]

description: 13
DOI: 10.57992/nmrxiv.p112.s1160.d5041
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B[14]

description: 14
DOI: 10.57992/nmrxiv.p112.s1160.d5042
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B[2]

description: 2
DOI: 10.57992/nmrxiv.p112.s1160.d5043
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B[3]

description: 3
DOI: 10.57992/nmrxiv.p112.s1160.d5044
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B[4]

description: 4
DOI: 10.57992/nmrxiv.p112.s1160.d5045
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B[5]

description: 5
DOI: 10.57992/nmrxiv.p112.s1160.d5046
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B[6]

description: 6
DOI: 10.57992/nmrxiv.p112.s1160.d5047
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B[7]

description: 7
DOI: 10.57992/nmrxiv.p112.s1160
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B
DOI: 10.57992/nmrxiv.p112.s1160.d5048
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B[8]

description: 8
DOI: 10.57992/nmrxiv.p112.s1160.d5049
title: PCC9009_Schanbacher_ACBderivatives_cmp_Z8_Anhydrocyanobacterin B[9]

description: 9
DOI: 10.57992/nmrxiv.p112.s1163.d5073
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ3Anhydrocyanobacterin E[1]

description: 1
DOI: 10.57992/nmrxiv.p112.s1163.d5074
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ3Anhydrocyanobacterin E[10]

description: 10
DOI: 10.57992/nmrxiv.p112.s1163.d5075
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ3Anhydrocyanobacterin E[11]

description: 11
DOI: 10.57992/nmrxiv.p112.s1163.d5076
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ3Anhydrocyanobacterin E[12]

description: 12
DOI: 10.57992/nmrxiv.p112.s1163.d5077
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ3Anhydrocyanobacterin E[13]

description: 13
DOI: 10.57992/nmrxiv.p112.s1163.d5078
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ3Anhydrocyanobacterin E[14]

description: 14
DOI: 10.57992/nmrxiv.p112.s1163.d5079
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ3Anhydrocyanobacterin E[15]

description: 15
DOI: 10.57992/nmrxiv.p112.s1163
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ3Anhydrocyanobacterin E
DOI: 10.57992/nmrxiv.p112.s1163.d5080
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ3Anhydrocyanobacterin E[16]

description: 16
DOI: 10.57992/nmrxiv.p112.s1163.d5081
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ3Anhydrocyanobacterin E[17]

description: 17
DOI: 10.57992/nmrxiv.p112.s1161.d5050
title: PCC9009_Schanbacher_ACBderivatives_cmp_5_ACB[1]

description: 1
DOI: 10.57992/nmrxiv.p112.s1163.d5082
title: PCC9009_Schanbacher_ACBderivatives_cmp_EZ3Anhydrocyanobacterin E[18]

description: 18
DOI: 10.57992/nmrxiv.p112.s1161.d5051
title: PCC9009_Schanbacher_ACBderivatives_cmp_5_ACB[10]

description: 10
DOI: 10.57992/nmrxiv.p112.s1161.d5052
title: PCC9009_Schanbacher_ACBderivatives_cmp_5_ACB[11]

description: 11
DOI: 10.57992/nmrxiv.p112.s1161.d5053
title: PCC9009_Schanbacher_ACBderivatives_cmp_5_ACB[2]

description: 2
DOI: 10.57992/nmrxiv.p112.s1161.d5054
title: PCC9009_Schanbacher_ACBderivatives_cmp_5_ACB[3]

description: 3
DOI: 10.57992/nmrxiv.p112.s1161.d5055
title: PCC9009_Schanbacher_ACBderivatives_cmp_5_ACB[4]

description: 4
DOI: 10.57992/nmrxiv.p112.s1161.d5056
title: PCC9009_Schanbacher_ACBderivatives_cmp_5_ACB[5]

description: 5
DOI: 10.57992/nmrxiv.p112.s1161.d5057
title: PCC9009_Schanbacher_ACBderivatives_cmp_5_ACB[6]

description: 6
DOI: 10.57992/nmrxiv.p112.s1161.d5058
title: PCC9009_Schanbacher_ACBderivatives_cmp_5_ACB[7]

description: 7
DOI: 10.57992/nmrxiv.p112.s1161.d5059
title: PCC9009_Schanbacher_ACBderivatives_cmp_5_ACB[8]

description: 8
DOI: 10.57992/nmrxiv.p112.s1162.d5060
title: PCC9009_Schanbacher_ACBderivatives_cmp_E1_Anhydrocyanobacterin C[1]

description: 1
DOI: 10.57992/nmrxiv.p112.s1162.d5061
title: PCC9009_Schanbacher_ACBderivatives_cmp_E1_Anhydrocyanobacterin C[10]

description: 10
DOI: 10.57992/nmrxiv.p112.s1162.d5062
title: PCC9009_Schanbacher_ACBderivatives_cmp_E1_Anhydrocyanobacterin C[11]

description: 11
DOI: 10.57992/nmrxiv.p112.s1162.d5063
title: PCC9009_Schanbacher_ACBderivatives_cmp_E1_Anhydrocyanobacterin C[12]

description: 12
DOI: 10.57992/nmrxiv.p112.s1162.d5064
title: PCC9009_Schanbacher_ACBderivatives_cmp_E1_Anhydrocyanobacterin C[13]

description: 13
DOI: 10.57992/nmrxiv.p112.s1162.d5065
title: PCC9009_Schanbacher_ACBderivatives_cmp_E1_Anhydrocyanobacterin C[2]

description: 2
DOI: 10.57992/nmrxiv.p112.s1162.d5066
title: PCC9009_Schanbacher_ACBderivatives_cmp_E1_Anhydrocyanobacterin C[3]

description: 3
DOI: 10.57992/nmrxiv.p112.s1162.d5067
title: PCC9009_Schanbacher_ACBderivatives_cmp_E1_Anhydrocyanobacterin C[4]

description: 4
DOI: 10.57992/nmrxiv.p112.s1162.d5068
title: PCC9009_Schanbacher_ACBderivatives_cmp_E1_Anhydrocyanobacterin C[5]

description: 5
DOI: 10.57992/nmrxiv.p112.s1162.d5069
title: PCC9009_Schanbacher_ACBderivatives_cmp_E1_Anhydrocyanobacterin C[6]

description: 6
DOI: 10.57992/nmrxiv.p112
title: Halogenation-Guided Chemical Screening uncovers Cyanobacterin Derivatives from the Cyanobacterium Scytonema hofmanni PCC9009

description: Isolation, Characterization, and NMR-Based Structure Elucidation of Halogenated Natural Products from the Cyanobacterium Scytonema hofmanni PCC9009
DOI: 10.57992/nmrxiv.p112.s1162
title: PCC9009_Schanbacher_ACBderivatives_cmp_E1_Anhydrocyanobacterin C
DOI: 10.57992/nmrxiv.p112.s1162.d5070
title: PCC9009_Schanbacher_ACBderivatives_cmp_E1_Anhydrocyanobacterin C[7]

description: 7
DOI: 10.57992/nmrxiv.p112.s1162.d5071
title: PCC9009_Schanbacher_ACBderivatives_cmp_E1_Anhydrocyanobacterin C[8]

description: 8
DOI: 10.57992/nmrxiv.p112.s1162.d5072
title: PCC9009_Schanbacher_ACBderivatives_cmp_E1_Anhydrocyanobacterin C[9]

description: 9
DOI: 10.6084/m9.figshare.29046386
title: Integrating genomic additive relationship matrices improves the efficiency in diploid banana breeding

description: This study investigated if integrating molecular information into the clonal model could improve the partitioning of the variance components and yield more accurate estimates of genetic parameters and prediction accuracy of breeding values of 14 key traits in diploid banana. A set of 2,792 informative single nucleotide polymorphism markers were used to construct the genomic-based relationship matrices. We compared the partitioning of genetic variance into additive and non-additive components using the pedigree-based best linear unbiased prediction (P-BLUP) model, the genomic best linear unbiased prediction (G-BLUP) method, which integrates the genetic relationship established through molecular marker information and a combination of the P-BLUP and G-BLUP information, which sources to create a hybrid matrix that estimates hybrid best linear unbiased prediction (H-BLUP).
DOI: 10.6084/m9.figshare.29046386.v1
title: Integrating genomic additive relationship matrices improves the efficiency in diploid banana breeding

description: This study investigated if integrating molecular information into the clonal model could improve the partitioning of the variance components and yield more accurate estimates of genetic parameters and prediction accuracy of breeding values of 14 key traits in diploid banana. A set of 2,792 informative single nucleotide polymorphism markers were used to construct the genomic-based relationship matrices. We compared the partitioning of genetic variance into additive and non-additive components using the pedigree-based best linear unbiased prediction (P-BLUP) model, the genomic best linear unbiased prediction (G-BLUP) method, which integrates the genetic relationship established through molecular marker information and a combination of the P-BLUP and G-BLUP information, which sources to create a hybrid matrix that estimates hybrid best linear unbiased prediction (H-BLUP).
DOI: 10.15468/dl.v2uwxs
title: Occurrence Download

description: A dataset containing 5690 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Coccocarpia palmicola (Spreng.) Arv. & D.J.Galloway"
 ]
}

 The dataset includes 5690 records from 170 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028088-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vymq24
title: Occurrence Download

description: A dataset containing 63 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ellisomyces anomalus (Hesselt. & P.Anderson) Benny & R.K.Benj."
 ]
}

 The dataset includes 63 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028089-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.afubxf
title: Occurrence Download

description: A dataset containing 55985 species occurrences available in GBIF matching the query:
{
 "and" : [
 "License is one of (CC0 1.0, CC-BY 4.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Plebejus idas (Linnaeus, 1761)"
 ]
}

 The dataset includes 55985 records from 372 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028070-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16917886
title: First field evidence for the spatial heterogeneity of HONO exchange fluxes in wheat fields of the Huai River Basin

description: Raw data for Han et al. submitted to journal.
DOI: 10.6084/m9.figshare.29957618
title: Supplementary Material for: Low hepsin expression associates with a better response to gemcitabine-based neoadjuvant therapy in pancreatic ductal adenocarcinoma

description: Background: Hepsin is a type 2 transmembrane serine protease (TTSP), primarily located on the cell membrane, which can degrade the extracellular matrix and modify connections between cells and the extracellular matrix. Given these features, hepsin is thought to play a role in cancer invasion and metastasis. While studied in various other cancers, hepsin’s role in pancreatic cancer remains unexamined.

Methods: Our study included 223 patients diagnosed with pancreatic ductal adenocarcinoma. Among these, 66 received neoadjuvant therapy and these were analyzed separately. Tissue microarrays and immunohistochemistry were used to assess the expression of hepsin in pancreatic ductal adenocarcinoma tissue. Hepsin expression intensity, ranging from negative to strong, was evaluated against clinicopathological parameters, including age at surgery, sex, T-stage, N-stage, tumor grade, perivascular and perineural invasion, CA19-9 levels, ASA class, stage, and, in the neoadjuvant-treated group, response to neoadjuvant therapy. 

Results: A strong hepsin expression was observed in 105 (67%) patients who did not receive neoadjuvant therapy, while 27 (42%) neoadjuvant-treated patients exhibited a strong expression. Hepsin expression did not associate with survival in either group. In the neoadjuvant-treated group, a strong positivity was, however associated with a lower T-stage (p = 0.005) and higher N-stage (p = 0.048). Among those receiving gemcitabine-based chemotherapy, a weaker hepsin expression associated with a better treatment response (p = 0.011).

Conclusions: A low hepsin expression following neoadjuvant therapy associated with a better treatment response among those receiving gemcitabine-based treatment. Thus, hepsin does not appear to influence prognosis in pancreatic cancer patients, regardless of whether they received neoadjuvant therapy or not.
DOI: 10.6084/m9.figshare.29957618.v1
title: Supplementary Material for: Low hepsin expression associates with a better response to gemcitabine-based neoadjuvant therapy in pancreatic ductal adenocarcinoma

description: Background: Hepsin is a type 2 transmembrane serine protease (TTSP), primarily located on the cell membrane, which can degrade the extracellular matrix and modify connections between cells and the extracellular matrix. Given these features, hepsin is thought to play a role in cancer invasion and metastasis. While studied in various other cancers, hepsin’s role in pancreatic cancer remains unexamined.

Methods: Our study included 223 patients diagnosed with pancreatic ductal adenocarcinoma. Among these, 66 received neoadjuvant therapy and these were analyzed separately. Tissue microarrays and immunohistochemistry were used to assess the expression of hepsin in pancreatic ductal adenocarcinoma tissue. Hepsin expression intensity, ranging from negative to strong, was evaluated against clinicopathological parameters, including age at surgery, sex, T-stage, N-stage, tumor grade, perivascular and perineural invasion, CA19-9 levels, ASA class, stage, and, in the neoadjuvant-treated group, response to neoadjuvant therapy. 

Results: A strong hepsin expression was observed in 105 (67%) patients who did not receive neoadjuvant therapy, while 27 (42%) neoadjuvant-treated patients exhibited a strong expression. Hepsin expression did not associate with survival in either group. In the neoadjuvant-treated group, a strong positivity was, however associated with a lower T-stage (p = 0.005) and higher N-stage (p = 0.048). Among those receiving gemcitabine-based chemotherapy, a weaker hepsin expression associated with a better treatment response (p = 0.011).

Conclusions: A low hepsin expression following neoadjuvant therapy associated with a better treatment response among those receiving gemcitabine-based treatment. Thus, hepsin does not appear to influence prognosis in pancreatic cancer patients, regardless of whether they received neoadjuvant therapy or not.
DOI: 10.6084/m9.figshare.29957624
title: Supplementary Material for: Retrospective Analysis of Allergen Characteristics in Patients with Allergic Diseases in Sanmen, Zhejiang Province

description: Objective: Allergic diseases represent a growing global health challenge, necessitating region-specific allergen characterization for targeted prevention and treatment. This study aimed to analyze the characteristics of allergens in patients with allergic diseases in Sanmen, Zhejiang Province.
Methods: A retrospective analysis was performed on allergen test results obtained from patients with allergic diseases who attended the People's Hospital of Sanmen County, Zhejiang Province, from July 2019 to June 2023. The serum total IgE levels and allergen-specific IgE (sIgE) positivity rates were assessed, and intergroup differences were statistically analyzed using hypothesis testing methodologies.
Results: A comprehensive analysis of 19,598 patients with allergic diseases was conducted, evaluating serum total IgE levels and allergen-specific IgE (sIgE) positivity rates. The positivity rate for serum total IgE was 25.67%, significantly higher than the IgE prevalence of inhalant allergens (24.84%) and food allergens (12.48%), significantly higher than the positivity rate for food allergen sIgE at 12.48% (P&lt;0.001). Dermatophagoides spp. allergens was identified as the primary source of inhalant allergens with a positivity rate of 16.31%, whereas crustacean allergens (tropomyosin) was the most prevalent food allergen with a positivity rate of 5.17%. The positivity rates for serum total IgE and sIgE were significantly higher in males compared to females (P&lt;0.001). Although females exhibited a higher positivity rate for dog hair allergy, the difference was insignificant (P=0.306). The serum total IgE positivity rate was highest in the ≤12 age group and declined with age, with a resurgence observed in individuals over 60. Similarly, the positivity rates for Dermatophagoides spp. allergens and cow's milk also decreased with age. The highest incidence of allergic diseases occurred between August and November, peaking in November at 30.63%. Among patients with allergic diseases, 23.20% tested positive for at least one sIgE, while 3.17% demonstrated positivity for three or more allergens.
Conclusion: In Sanmen, Zhejiang, Dermatophagoides spp. allergens was identified as the principal inhalant allergen among patients with allergic diseases, whereas crustacean allergens (tropomyosin) was the predominant food allergen. Male patients demonstrated a higher allergen positivity rate compared to females. These findings derived from allergen screening establish a solid foundation for laboratory diagnostics, thereby aiding in the prevention, diagnosis, and treatment of allergic diseases.
DOI: 10.6084/m9.figshare.29957624.v1
title: Supplementary Material for: Retrospective Analysis of Allergen Characteristics in Patients with Allergic Diseases in Sanmen, Zhejiang Province

description: Objective: Allergic diseases represent a growing global health challenge, necessitating region-specific allergen characterization for targeted prevention and treatment. This study aimed to analyze the characteristics of allergens in patients with allergic diseases in Sanmen, Zhejiang Province.
Methods: A retrospective analysis was performed on allergen test results obtained from patients with allergic diseases who attended the People's Hospital of Sanmen County, Zhejiang Province, from July 2019 to June 2023. The serum total IgE levels and allergen-specific IgE (sIgE) positivity rates were assessed, and intergroup differences were statistically analyzed using hypothesis testing methodologies.
Results: A comprehensive analysis of 19,598 patients with allergic diseases was conducted, evaluating serum total IgE levels and allergen-specific IgE (sIgE) positivity rates. The positivity rate for serum total IgE was 25.67%, significantly higher than the IgE prevalence of inhalant allergens (24.84%) and food allergens (12.48%), significantly higher than the positivity rate for food allergen sIgE at 12.48% (P&lt;0.001). Dermatophagoides spp. allergens was identified as the primary source of inhalant allergens with a positivity rate of 16.31%, whereas crustacean allergens (tropomyosin) was the most prevalent food allergen with a positivity rate of 5.17%. The positivity rates for serum total IgE and sIgE were significantly higher in males compared to females (P&lt;0.001). Although females exhibited a higher positivity rate for dog hair allergy, the difference was insignificant (P=0.306). The serum total IgE positivity rate was highest in the ≤12 age group and declined with age, with a resurgence observed in individuals over 60. Similarly, the positivity rates for Dermatophagoides spp. allergens and cow's milk also decreased with age. The highest incidence of allergic diseases occurred between August and November, peaking in November at 30.63%. Among patients with allergic diseases, 23.20% tested positive for at least one sIgE, while 3.17% demonstrated positivity for three or more allergens.
Conclusion: In Sanmen, Zhejiang, Dermatophagoides spp. allergens was identified as the principal inhalant allergen among patients with allergic diseases, whereas crustacean allergens (tropomyosin) was the predominant food allergen. Male patients demonstrated a higher allergen positivity rate compared to females. These findings derived from allergen screening establish a solid foundation for laboratory diagnostics, thereby aiding in the prevention, diagnosis, and treatment of allergic diseases.
DOI: 10.6084/m9.figshare.29957627
title: Supplementary Material for: FBXW7 Protects Against Diabetic Nephropathy by Targeting Metadherin For Ubiquitin Degradation

description: Objective: Diabetic nephropathy (DN), a critical complication of diabetes, is characterized by progressive renal function impairment and fibrosis development. F-box and WD repeat domain-containing 7 (FBXW7), an E3 ubiquitin ligase, is recognized for its role in metabolic disorders, however, its specific functions and mechanisms in DN remain incompletely understood. This study aimed to clarify the role of FBXW7 in the pathogenesis of DN.
Methods: Mouse tubular epithelial cells (mTECs) cultured under hyperglycemic conditions were used. FBXW7 overexpression was induced in the kidneys of db/db mice and in mTECs to evaluate its effects on renal fibrosis and related molecular pathways. The interaction between FBXW7 and metadherin (Mtdh) was examined by using co-immunoprecipitation (Co-IP) and western blotting techniques.
Results: FBXW7 expression was found to be significant reduced in in the kidneys of DN patients and db/db mice. Overexpression of FBXW7 markedly improved albuminuria, blood urea nitrogen, uric acid levels, and renal fibrosis in db/db mice. Additionally, FBXW7 was shown to inhibit high glucose-induced fibrosis in mTECs through a mechanism involving the ubiquitin-mediated degradation of Mtdh, a protein known to promote fibrosis. Suppression of Mtdh via FBXW7 overexpression was also linked to inactivation of TGF-β/Smad3 signaling in DN.
Conclusion: These findings highlight the protective role of FBXW7 in DN by downregulating Mtdh and indicate that FBXW7 represents a promising therapeutic target for DN.
Key words: Diabetic nephropathy, FBXW7, metadherin, ubiquitin