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Peer-Review Record

Kinin B1 Receptor Antagonism Prevents Acute Kidney Injury to Chronic Kidney Disease Transition in Renal Ischemia-Reperfusion by Increasing the M2 Macrophages Population in C57BL6J Mice

Biomedicines 2023, 11(8), 2194; https://doi.org/10.3390/biomedicines11082194
by Gabriel Rufino Estrela 1,2,*,†, Raisa Brito Santos 1,3,†, Alexandre Budu 1, Adriano Cleis de Arruda 1,3, Jonatan Barrera-Chimal 4 and Ronaldo Carvalho Araújo 1,*
Reviewer 1:
Reviewer 2: Anonymous
Biomedicines 2023, 11(8), 2194; https://doi.org/10.3390/biomedicines11082194
Submission received: 15 June 2023 / Revised: 19 July 2023 / Accepted: 28 July 2023 / Published: 4 August 2023
(This article belongs to the Section Immunology and Immunotherapy)

Round 1

Reviewer 1 Report

This paper is significant in that it explains the clinical parameters, cytokines and histopathological findings that suggest that a Kinin B1 receptor (B1R) antagonist is useful in the process from AKI to CKD. What should be pursued further is the transition of tubulointerstitial markers of tubulointerstitial damage. Mention of markers such as urinary beta2microglobulin urinary L-FABP urinary NAG urinary NGAL should be added. The description of the histopathological findings is also simplistic and a detailed description of the glomerular, vascular and tubulointerstitial changes should be added.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

This very interesting and original experimental work demonstrate the role of the kinin/kallicrein system as the trigger of inflammation and lately renal fibrosis in Acute Kidney Injury as the influence of this pathway on macrophage transition (from M2 to M1) and the ability of Kinin B1 receptor antagonist to strongly mitigate this detrimental pathway . My main concern relates to the statistical analysis : although not specified in the text, when analyzing the figures, I guess that each group of experiments contains 5 animals. Thus, its is highly improbable that values of each parameters analyzed are following a Gaussian distribution. Unless authors can prove it using valuable normality tests (Shapiro-Wilk testcoupled with D'agostino-Pearson test), they should give results as median and range and use non-parametric ANOVA (Kruskal-Wallis test) for statistical analyses.

Globally, English wording is good.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

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