Blood-supplementing effect of low molecular weight peptides of E-Jiao on chemotherapy-induced myelosuppression: evaluation of pharmacological activity and identification of bioactive peptides released in vivo.

Background: Equus asinus L. [Equidae; Asini Corri Colla] (donkey-hide gelatin, E-Jiao) is a traditional Chinese medicine renowned for its exceptional blood-supplementing effect. However, the specific components that contribute to its efficacy remain elusive. This study aimed to demonstrate that peptides are responsible for E-Jiao's blood-supplementing effect and to explore the specific peptides contributing to its efficacy. Methods: The low molecular weight peptides of E-Jiao (LMEJ) were obtained using an in vitro digestion method. LMEJ and peptides in the rat bloodstream were characterized by peptidomics analysis. The blood-supplementing effect of LMEJ was assessed using blood-deficient zebrafish and mouse models. The effect of the peptides detected in rat blood was evaluated using the same zebrafish model, and network pharmacology analysis was performed to investigate the underlying mechanisms. Results: A total of 660 unique peptides were identified within LMEJ. Both E-Jiao and LMEJ significantly alleviated myelosuppression in mice but only LMEJ attenuated myelosuppression in zebrafish. After the administration of E-Jiao to rats, 67 E-Jiao-derived peptides were detected in the bloodstream, 41 of which were identical to those identified in LMEJ. Out of these 41 peptides, five were synthesized. Subsequent verification of their effects revealed that two of them were able to alleviate myelosuppression in zebrafish. Network pharmacology study suggested that E-Jiao may exert a blood-supplementing effect by regulating signaling pathways such as JAK-STAT, IL-17 and others. These results indicated that peptides are at least partially responsible for E-Jiao's efficacy. Conclusion: This study provides a crucial foundation for further exploration of the bioactive components of E-Jiao.

Radiomics Analysis of Quantitative Maps from Synthetic MRI for Predicting Grades and Molecular Subtypes of Diffuse Gliomas.

PURPOSE: To investigate the feasibility of using radiomics analysis of quantitative maps from synthetic MRI to preoperatively predict diffuse glioma grades, isocitrate dehydrogenase (IDH) subtypes, and 1p/19q codeletion status. METHODS: Data from 124 patients with diffuse glioma were used for analysis (n = 87 for training, n = 37 for testing). Quantitative T1, T2, and proton density (PD) maps were obtained using synthetic MRI. Enhancing tumour (ET), non-enhancing tumour and necrosis (NET), and peritumoral edema (PE) regions were segmented followed by manual fine-tuning. Features were extracted using PyRadiomics and then selected using Levene/T, BorutaShap and maximum relevance minimum redundancy algorithms. A support vector machine was adopted for classification. Receiver operating characteristic curve analysis and integrated discrimination improvement analysis were implemented to compare the performance of different radiomics models. RESULTS: Radiomics models constructed using features from multiple tumour subregions (ET + NET + PE) in the combined maps (T1 + T2 + PD) achieved the highest AUC in all three prediction tasks, among which the AUC for differentiating lower-grade and high-grade diffuse gliomas, predicting IDH mutation status and predicting 1p/19q codeletion status were 0.92, 0.95 and 0.86 respectively. Compared with those constructed on individual T1, T2, and PD maps, the discriminant ability of radiomics models constructed on the combined maps separately increased by 11, 17 and 10% in predicting glioma grades, 35, 52 and 19% in predicting IDH mutation status, and 16, 15 and 14% in predicting 1p/19q codeletion status (p < 0.05). CONCLUSION: Radiomics analysis of quantitative maps from synthetic MRI provides a new quantitative imaging tool for the preoperative prediction of grades and molecular subtypes in diffuse gliomas.

Analytical strategies to identify multicomponent quality markers for commercial Hua-ju-hong using multidimensional chemical analysis.

Hua-ju-hong (HJH) is a Chinese medicinal material obtained from Citrus grandis 'Tomentosa' (CGT) and Citrus grandis (L.) Osbeck (CG) with various commercial specifications. It is known for relieving cough and dispelling phlegm. To reveal the quality marker for distinguishing the various HJH, 215 batches of commercial HJH were studied systematically using multidimensional chemical analysis. Ten major components were identified by high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry and quantified via high-performance liquid chromatography coupled with diode array detection. In this study, a rapid, efficient, and low-cost chromatographic method was established. Total coumarin-hemiterpene and total coumarin-monoterpene were first classified and analyzed in HJH. The result indicated that the main component, naringin, was not the quality marker for differentiating CGT from CG. For reflecting the unique medicinal and food value of HJH, coumarins should be the more potential quality markers. Flavonoids were the possible quality markers for distinguishing two growth stages of fruit-exocarp and young fruit. For the first time, two chemotypes of HJH were identified in CG. This study provides a convenient yet reliant chromatographic method and novel yet systematic strategies for overall quality control of commercial HJH.

Multi-parametric Z-spectral MRI may have a good performance for glioma stratification in clinical patients.

OBJECTIVES: To comprehensively and noninvasively risk-stratify glioma grade, isocitrate dehydrogenase (IDH) genotype, and 1p/19q codeletion status using multi-contrast Z-spectral magnetic resonance imaging (MRI). METHODS: One hundred and thirteen patients with glioma were retrospectively included. Multiple contrasts contributing to Z-spectra, including direct saturation of water (DSW), semi-solid magnetization transfer contrast (MTC), amide proton transfer (APT) effect, aliphatic nuclear Overhauser effect, and the 2-ppm chemical exchange saturation transfer peak (CEST@2ppm), were fitted with five individual Lorentzian functions. Z-spectral contrasts were compared according to the three most important risk stratifications: tumor grade, IDH genotype, and 1p/19q codeletion status. We further investigated the differentiation of 1p/19q codeletion status within IDH mutant gliomas. The stratification performance of individual Z-spectral contrasts and their combination was quantified using receiver operating characteristic (ROC) analyses. RESULTS: DSW was significantly different within grade, IDH genotypes, and 1p/19q codeletion status. APT was significantly different with grade and IDH mutation, but not with 1p/19q subtypes. CEST@2ppm was only significantly different with 1p/19q codeletion subtypes. DSW and CEST@2ppm were the two Z-spectral contrasts able to differentiate 1p/19q codeletion subtypes within IDH mutant gliomas. For differentiating glioma grades using ROC analyses, DSW achieved the largest AUC. For differentiating IDH genotypes, DSW and APT achieved comparable AUCs. DSW was the best metric for differentiating 1p/19q codeletion status within all patients and within the IDH mutant patients. Combining all Z-spectral contrasts improved sensitivity and specificity for all risk stratifications. CONCLUSIONS: Multi-parametric Z-spectral MRI serves as a useful, comprehensive, and noninvasive imaging technique for glioma stratification in clinical patients. KEY POINTS: • Multiple contrasts contributing to Z-spectra were separately fitted with Lorentzian functions. • Z-spectral contrasts were compared within the three most important and common tumor risk stratifications for gliomas: tumor grade, IDH genotype, and 1p/19q codeletion status. • The stratification performance of individual Z-spectral contrasts and their combination was quantified using receiver operating characteristic analyses, which found Z-spectral MRI to be a useful and comprehensive imaging biomarker for glioma stratification.