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Abstract Background Activation of pericytes leads to renal interstitial fibrosis, but the regulatory mechanism of pericytes in the progression from AKI to CKD remains poorly understood. CD36 activation plays a role in the progression of CKD. However, the significance of CD36 during AKI-CKD, especially in pericyte, remains to be fully defined. Methods GEO and DISCO database were used to analyze the expression of CD36 in pericyte during AKI-CKD; IRI to conduct AKI-CKD mouse model; Hypoxia/Reoxygenation (H/R) to induce the cell model; RT-qPCR and Western blotting to detect gene expression; IP and confocal-IF to determine the core fucosylation (CF) level of CD36. Flow cytometry (AV/PI staining) to detect the cell apoptosis and JC-1 staining to react to the change of mitochondrial membrane potential. Results During AKI to CKD progression, CD36 expression in pericytes is higher and may be influenced by CF. Moreover, we confirmed the positive association of CD36 expression with pericyte-myofibroblast transition and the progression of AKI-CKD in an IRI mouse model and hypoxia/reoxygenation (H/R) pericytes. Notably, we discovered that FUT8 upregulates both CD36 expression and its CF level, contributing to the activation of the mitochondrial-dependent apoptosis signaling pathway in pericytes, ultimately leading to the progression of AKI-CKD. Conclusion These results further identify FUT8 and CD36 as potential targets for the treatment in the progression of AKI-CKD.

Aims Finerenone has been approved for treating diabetic kidney disease (DKD) with reducing cardiorenal risk. Real-world data on finerenone treatment for the management of DKD are presently lacking. This study aimed to investigate the effect of finerenone on the renal parameters of the Chinese DKD population in the real-world medical setting for the first time, especially in combination with renin–angiotensin system inhibitors (RASi) and sodium-glucose cotransporter 2 inhibitors (SGLT2i).Methods Forty-two DKD patients were selected and completed a 6-month finerenone treatment. Renal parameters and adverse effects were collected at every visit.Results The median urine albumin-to-creatinine ratio (UACR) was 1426.11 (755.42, 3638.23) mg/g. Among them, the proportion of patients with a UACR of 300–5000 mg/g was 76.2%, and the proportion of patients with a UACR of >5000 mg/g was 14.3%. The median estimated glomerular filtration rate (eGFR) was 54.50 (34.16, 81.73) mL/min/1.73 m2. Finerenone decreased the UACR significantly throughout the study period (p .05). One patient each discontinued finerenone due to hyperkalemia (2.4%) and acute kidney injury (2.4%). No patient reported hypotension, breast pain, and gynecomastia.Conclusions This study from China first demonstrated finerenone decreased UACR with manageable safety in real-world DKD treatment. A triple regimen of RASi, SGLT2i, and finerenone may be a promising treatment strategy for lowering albuminuria and reducing hyperkalemia risk in advanced DKD patients.

Abstract Germline PALB2 pathogenic variants are associated with an increased lifetime risk for breast, pancreatic, and ovarian cancer. However, the interpretation of the pathogenicity of numerous PALB2 missense variants of uncertain significance (VUSs) identified in germline genetic testing remains a challenge. Here we selected ten potentially pathogenic PALB2 VUSs identified in 2279 Chinese patients with breast cancer and evaluated their impacts on PALB2 function by systematic functional assays. We showed that three PALB2 VUSs p.K16M [c.47 A > T], p.L24F [c.72 G > C], and p.L35F [c.103 C > T] in the coiled-coil domain impaired PALB2-mediated homologous recombination. The p.L24F and p.L35F variants partially disrupted BRCA1-PALB2 interactions, reduced RAD51 foci formation in response to DNA damage, abrogated ionizing radiation-induced G2/M checkpoint maintenance, and conferred increased sensitivity to olaparib and cisplatin. The p.K16M variant presented mild effects on BRCA1-PALB2 interactions and RAD51 foci formation. Altogether, we identify two novel PALB2 VUSs, p.L24F and p.L35F, that compromise PALB2 function and may increase cancer risk. These two variants display marked olaparib and cisplatin sensitivity and may help predict response to targeted therapy in the clinical treatment of patients with these variants.

Abstract Heavy metals contaminations in mining areas aroused wide concerns globally. Efficient evaluation of its pollution status is a basis for further soil reclamation. Visible and near–infrared reflectance (Vis–NIR) spectroscopy has been diffusely used for retrieving heavy metals concentrations. However, the reliability and feasibility of calibrated models were still doubtful. The present study estimated zinc (Zn) concentrations via the random forest (RF) and partial least squares regression (PLSR) using ground in-situ Zn concentrations as well as soil spectral reflectance at an Opencast Coal Mine of Ordos, China in February 2020. The coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), and the ratio of performance to deviation (RPD) were selected to assess the robustness of the methods in estimating Zn contents. Moreover, the characteristic bands were chosen by Pearson correlation analysis and Boruta Algorithm. Finally, the comparison between RF and PLSR combined with eight spectral reflectance transformation methods was conducted for four concentration groups to determine the optimal model. The results indicated that: (1) Zn contents represented a skewed distribution (coefficient of variation (CV) = 33%); (2) the spectral reflectance tended to decrease with the increase of Zn contents during 580–1850 nm based on Savitzky–Golay smoothing (SG); (3) the continuous wavelet transform (CWT) demonstrated higher effectiveness than other spectral reflectance transformation methods in enhancing spectral responses, the R2 between Zn contents and the soil spectral reflectance achieved the highest (R2 = 0.71) by using CWT; (4) the RF combined with CWT exhibited the best performance than other methods in the current study (R2 = 0.97, RPD = 3.39, RMSE = 1.05 mg kg−1, MAE = 0.79 mg kg−1). The current study supplied a scientific scheme and theoretical support for predicting heavy metals concentrations via the Vis–NIR spectral method in possible contaminated areas such as coal mines and metallic mineral deposit areas.

Toxic metals have attracted great concern worldwide due to their toxicity and slow decomposition. Although metal concentrations can be accurately obtained with chemical methods, it is difficult to map metal distributions on a large scale due to their inherently low efficiency and high cost. Moreover, chemical analysis methods easily lead to secondary contamination. To address these issues, 110 topsoil samples were collected using a soil sampler, and positions for each sample were surveyed using a global navigation satellite system (GNSS) receiver from a coal mine in northern China. Then, the metal contents were surveyed in a laboratory via a portable X-ray fluorescence spectroscopy (XRF) device, and GaoFen-5 (GF-5) satellite hyperspectral images were used to retrieve the spectra of the soil samples. Furthermore, a Savitzky–Golay (SG) filter and continuous wavelet transform (CWT) were selected to smooth and enhance the soil reflectance. Competitive adaptive reweighted sampling (CARS) and Boruta algorithms were utilized to identify the feature bands. The optimum two-stage method, consisting of the random forest (RF) and ordinary kriging (OK) methods, was used to infer the metal concentrations. The following outcomes were achieved. Firstly, both zinc (Zn) (68.07 mg/kg) and nickel (Ni) (26.61 mg/kg) surpassed the regional background value (Zn: 48.60 mg/kg, Ni: 19.5 mg/kg). Secondly, the optimum model of RF, combined with the OK (RFOK) method, with a relatively higher coefficient of determination (R2) (R2 = 0.60 for Zn, R2 = 0.30 for Ni), a lower root-mean-square error (RMSE) (RMSE = 12.45 mg/kg for Zn, RMSE = 3.97 mg/kg for Ni), and a lower mean absolute error (MAE) (MAE = 9.47 mg/kg for Zn, MAE = 3.31mg/kg for Ni), outperformed the other four models, including the RF, OK, inverse distance weighted (IDW) method, and the optimum model of RF combined with IDW (RFIDW) method in estimating soil Zn and Ni contents, respectively. Thirdly, the distribution of soil Zn and Ni concentrations obtained from the best-predicted method and the GF-5 satellite hyperspectral images was in line with the actual conditions. This scheme proves that satellite hyperspectral images can be used to directly estimate metal distributions, and the present study provides a scientific base for mapping heavy metal spatial distribution on a relatively large scale.

Familial idiopathic basal ganglia calcification (FIBGC) is a rare, autosomal dominant disorder involving bilateral calcification of the basal ganglia. To identify gene mutations related to a Chinese FIBGC lineage, we evaluated available individuals in the family using CT scans. DNA was extracted from the peripheral blood of available family members, and both exonic and flanking intronic sequences of the SLC20A2 gene were amplified by PCR and then sequenced. Non-denaturing polyacrylamide gel electrophoresis (PAGE) was used to confirm the presence of mutations. Allele imbalances of the SLC20A2 gene or relative quantity of SLC20A2 transcripts were evaluated using qRT-PCR. A novel heterozygous single base-pair deletion (c.510delA) within the SLC20A2 gene was identified. This deletion mutation was found to co-segregate with basal ganglia calcification in all of the affected family members but was not detected in unaffected individuals or in 167 unrelated Han Chinese controls. The mutation will cause a frameshift, producing a truncated SLC20A2 protein with a premature termination codon, most likely leading to the complete loss of function of the SLC20A2 protein. This mutation may also lead to a reduction in SLC20A2 mRNA expression by approximately 30% in cells from affected individuals. In conclusion, we identified a novel mutation in SLC20A2 that is linked to FIBGC. In addition to the loss of function at the protein level, decreasing the expression of SLC20A2 mRNA may be another mechanism that can regulate SLC20A2 function in IBGC individuals. We propose that the regional expression pattern of SLC20A1 and SLC20A2 might explain the unique calcification pattern observed in FIBGC patients.