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The mass and volume of Rosa roxburghii fruits are essential for fruit grading and consumer selection. Physical characteristics such as dimension, projected area, mass, and volume are interrelated. Image-based mass and volume estimation facilitates the automation of fruit grading, which can replace time-consuming and laborious manual grading. In this study, image processing techniques were used to extract fruit dimensions and projected areas, and univariate (linear, quadratic, exponential, and power) and multivariate regression models were used to estimate the mass and volume of Rosa roxburghii fruits. The results showed that the quadratic model based on the criterion projected area (CPA) estimated the best mass (R2 = 0.981) with an accuracy of 99.27%, and the equation is M = 0.280 + 0.940CPA + 0.071CPA2. The multivariate regression model based on three projected areas (PA1, PA2, and PA3) estimated the best volume (R2 = 0.898) with an accuracy of 98.24%, and the equation is V = − 8.467 + 0.657PA1 + 1.294PA2 + 0.628PA3. In practical applications, cost savings can be realized by having only one camera position. Therefore, when the required accuracy is low, estimating mass and volume simultaneously from only the dimensional information of the side view or the projected area information of the top view is recommended. [ABSTRACT FROM AUTHOR]

Background: p53, the most frequently mutated gene in cancer, lacks effective targeted drugs. Methods: We developed monoclonal antibodies (mAbs) that target a p53 hotspot mutation E285K without cross-reactivity with wild-type p53. They were delivered using lipid nanoparticles (LNPs) that encapsulate DNA plasmids. Western blot, BLI, flow cytometry, single-cell sequencing (scRNA-seq), and other methods were employed to assess the function of mAbs in vitro and in vivo. Results: These LNP-pE285K-mAbs in the IgG1 format exhibited a robust anti-tumor effect, facilitating the infiltration of immune cells, including CD8+ T, B, and NK cells. scRNA-seq revealed that IgG1 reduces immune inhibitory signaling, increases MHC signaling from B cells to CD8+ T cells, and enriches anti-tumor T cell and B cell receptor profiles. The E285K-mAbs were also produced in the dimeric IgA (dIgA) format, whose anti-tumor activity depended on the polymeric immunoglobulin receptor (PIGR), a membrane Ig receptor, whereas that of IgG1 relied on TRIM21, an intracellular IgG receptor. Conclusions: Targeting specific mutant epitopes using DNA-encoded and LNP-delivered mAbs represents a potential precision medicine strategy against p53 mutants in TRIM21- or PIGR-positive cancers. [ABSTRACT FROM AUTHOR]

The composite photocatalyst FeOOH/g-C 3 N 4 was prepared through thermal polycondensation and co-precipitation methods, followed by XRD, SEM and UV-vis characterization. The stability of FeOOH/g-C 3 N 4 was explored by the recycling test. The active species in the reaction system were investigated by the capture experiment. The results indicated that the optimal preparation condition for g-C 3 N 4 involved calcination at 600 °C for 4 h. XRD analysis revealed that g-C 3 N 4 exhibits a high-purity phase, and Fe in FeOOH/g-C 3 N 4 exists in a highly dispersed amorphous state. SEM analysis showed that FeOOH/g-C 3 N 4 has a rough surface with an irregular layered structure. Element composition analysis confirmed that the content of elements in the prepared catalyst is consistent with the theoretical calculation. FeOOH/g-C 3 N 4 possesses the largest specific surface area of 143.2 m 2 /g and a suitable pore distribution. UV-vis DRS analysis showed that the absorption intensity of FeOOH/g-C 3 N 4 is stronger than that of g-C 3 N 4 . When the catalyst dosage was 1.0 g/L, the H 2 O 2 dosage was 4 mmol/L, the PNP initial concentration was 10 mg/L and the initial pH value was 5, the PNP removal could reach 92% in 120 min. Even after 5 cycles, the efficiency of PNP removal by FeOOH/g-C 3 N 4 remains nearly 80%. The capture experiment indicated that both •OH and •O 2 - play roles in the photocatalytic degradation of PNP, with •OH being more significant. These findings affirm that FeOOH has been successfully incorporated into g-C 3 N 4 , resulting in a conspicuous catalytic effect on the degradation of PNP in the visible light-assisted Fenton-like reaction.

Background: Differentiation of glioma and solitary brain metastasis (SBM), which requires biopsy or multi-disciplinary diagnosis, remains sophisticated clinically. Histogram analysis of MR diffusion or molecular imaging hasn't been fully investigated for the differentiation and may have the potential to improve it., Methods: A total of 65 patients with newly diagnosed glioma or metastases were enrolled. All patients underwent DWI, IVIM, and APTW, as well as the T1W, T2W, T2FLAIR, and contrast-enhanced T1W imaging. The histogram features of apparent diffusion coefficient (ADC) from DWI, slow diffusion coefficient (Dslow), perfusion fraction (frac), fast diffusion coefficient (Dfast) from IVIM, and MTRasym@3.5ppm from APTWI were extracted from the tumor parenchyma and compared between glioma and SBM. Parameters with significant differences were analyzed with the logistics regression and receiver operator curves to explore the optimal model and compare the differentiation performance., Results: Higher ADC kurtosis (P = 0.022), frac kurtosis (P<0.001),and frac skewness (P<0.001) were found for glioma, while higher (MTRasym@3.5ppm) 10 (P = 0.045), frac 10 (P<0.001),frac 90 (P = 0.001), frac mean (P<0.001), and frac entropy (P<0.001) were observed for SBM. frac kurtosis (OR = 0.431, 95%CI 0.256-0.723, P = 0.002) was independent factor for SBM differentiation. The model combining (MTRasym@3.5ppm) 10 , frac 10 , and frac kurtosis showed an AUC of 0.857 (sensitivity: 0.857, specificity: 0.750), while the model combined with frac 10 and frac kurtosis had an AUC of 0.824 (sensitivity: 0.952, specificity: 0.591). There was no statistically significant difference between AUCs from the two models. (Z = -1.14, P = 0.25)., Conclusions: The frac 10 and frac kurtosis in enhanced tumor region could be used to differentiate glioma and SBM and (MTRasym@3.5ppm) 10 helps improving the differentiation specificity., (© 2024. The Author(s).)