Advancing the application of the analytical renal pathology system in allograft IgA nephropathy patients.

BACKGROUND: The analytical renal pathology system (ARPS) based on convolutional neural networks has been used successfully in native IgA nephropathy (IgAN) patients. Considering the similarity of pathologic features, we aim to evaluate the performance of the ARPS in allograft IgAN patients and broaden its implementation. METHODS: Biopsy-proven allograft IgAN patients from two different centers were enrolled for internal and external validation. We implemented the ARPS to identify glomerular lesions and intrinsic glomerular cells, and then evaluated its performance. Consistency between the ARPS and pathologists was assessed using intraclass correlation coefficients. The association of digital pathological features with clinical and pathological data was measured. Kaplan-Meier survival curve and cox proportional hazards model were applied to investigate prognosis prediction. RESULTS: A total of 56 biopsy-proven allograft IgAN patients from the internal center and 17 biopsy-proven allograft IgAN patients from the external center were enrolled in this study. The ARPS was successfully applied to identify the glomerular lesions (F1-score, 0.696-0.959) and quantify intrinsic glomerular cells (F1-score, 0.888-0.968) in allograft IgAN patients rapidly and precisely. Furthermore, the mesangial hypercellularity score was positively correlated with all mesangial metrics provided by ARPS [Spearman's correlation coefficient (r), 0.439-0.472, and all p values < 0.001]. Besides, a higher allograft survival was noticed among patients in the high-level groups of the maximum and ratio of endothelial cells, as well as the maximum and density of podocytes. CONCLUSION: We propose that the ARPS could be implemented in future clinical practice with outstanding capability.

Intestinal microbiota: a new force in cancer immunotherapy.

Cancer displays high levels of heterogeneity and mutation potential, and curing cancer remains a challenge that clinicians and researchers are eager to overcome. In recent years, the emergence of cancer immunotherapy has brought hope to many patients with cancer. Cancer immunotherapy reactivates the immune function of immune cells by blocking immune checkpoints, thereby restoring the anti-tumor activity of immune cells. However, immune-related adverse events are a common complication of checkpoint blockade, which might be caused by the physiological role of checkpoint pathways in regulating adaptive immunity and preventing autoimmunity. In this context, the intestinal microbiota has shown great potential in the immunotherapy of cancer. The intestinal microbiota not only regulates the immune function of the body, but also optimizes the therapeutic effect of immune checkpoint inhibitors, thus reducing the occurrence of complications. Therefore, manipulating the intestinal microbiota is expected to enhance the effectiveness of immune checkpoint inhibitors and reduce adverse reactions, which will lead to new breakthroughs in immunotherapy and cancer management. Video abstract.

The role of microbiota in the development of colorectal cancer.

Colorectal cancer is the third largest cancer in worldwide and has been proven to be closely related to the intestinal microbiota. Many reports and clinical studies have shown that intestinal microbial behavior may lead to pathological changes in the host intestines. The changes can be divided into epigenetic changes and carcinogenic changes at the gene level, which ultimately promote the production and development of colorectal cancer. This article reviews the pathways of microbial signaling in the intestinal epithelial barrier, the role of microbiota in inflammatory colorectal tumors, and typical microbial carcinogenesis. Finally, by gaining a deeper understanding of the intestinal microbiota, we hope to achieve the goal of treating colorectal cancer using current microbiota technologies, such as fecal microbiological transplantation.

[Low carbon number fatty acid content prediction based on near-infrared spectroscopy].

The rapid prediction of the low-carbon fatty acids (C < or = 14) content in grease samples was achieved by a mathematical model established by near infrared spectroscopy combined with support vector machine regression (SVR). In the present project, near-infrared spectrometer SupNIR-5700 was used to collect near-infrared spectra of 58 samples; partial least square (PLS) was applied to remove the strange samples, and principal component analysis (PCA) was conducted on the measurements; radial basis function (RBF) kernel function was selected to establish a regression model supporting vector machine, and then detailed analysis and discussions were conducted concerning their spectral preprocessing and parameters optimization methods. Experimental results showed that by applying particle swarm optimization (PSO) the model demonstrated improved performance, stronger generalization ability, better prediction accuracy and robustness. In the second pretreatment method after PSO, when the optimization parameters are: C = 2.085, gamma = 22.20, the prediction set and calibration set correlation coefficient (gamma) reached 0.998 0 and 0.925 8, respectively; and root mean square errors (MSE) were 0.000 4 and 0.014 3, respectively. Research results proved that the method based on near infrared spectroscopy and PSO-SVR for accurate and fast prediction of the low-carbon fatty acid content in vegetable oil is feasible.

High-oleic rapeseed oil quality indicators and endogenous antioxidant substances under different processing methods.

This study exposed high-oleic rapeseed oil (HORO) to different pretreatment (microwave or roasting) and processing methods to investigate (cold pressing, hexane extraction, subcritical butane extraction, and aqueous enzymatic extraction) the effects of processing technologies on HORO parameters associated with its physicochemical properties, endogenous antioxidant substances, and antioxidant capacity. The oil yield of various processing technologies was between 35.4% and 59.7%, and the fatty acid composition did not significantly differ. Hierarchical clustering and principal component analyses were used for evaluation. The results revealed that the microwave pretreatment-hexane extraction (M-HE) method resulted in significantly higher levels of tocopherols (688.4 mg/kg), polyphenols (1007.76 mg/kg), and phytosterols (1810.6 mg/kg) in HORO, implying strong free radical scavenging capacity (DPPH-oil: 79.63, DPPH-nonpolar: 71.42, DPPH-polar: 6.65, FRAP: 55.4, ABTS: 3043.7 µmol TE/kg). Hence, M-HE is a promising method for producing HORO with a higher stability and nutritional value.

[Determination of sodium cyclamate in liquor by high performance liquid chromatography-tandem mass spectrometry with linear trap technology].

An accurate determination of quantitative and confirmative method for sodium cyclamate in liquor by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) with linear trap technology has been established. Without pretreatment, the sample was directly injected after filtering through a 0.2 microm micro filter. The HPLC separation was performed on an Atlantis dC18 column (150 mm x 2.1 mm, 3 microm) by gradient elution with methanol and water containing 0.1% (v/v) formic acid. The eluent was determined and confirmed in multiple reaction monitoring-enhanced product ion (MRM-EPI) scan mode. The acquired data from MRM for the quantitative determination, and the product ion spectra were used for library search for qualitative confirmatory analysis. External standard was used for the quantitative determination of sodium cyclamate in liquor, and good linearity (r = 0.9991) was obtained over the range of 1.320 - 132.0 microg/L. The limit of detection (LOD, S/N = 3) for sodium cyclamate was 0.1 microg/L. The average recoveries ranged from 96.38% to 107.2% at the spiked levels of 2.640, 26.40 and 100.0 microg/L with the relative standard deviations (RSDs) less than 9%. The matching degrees of the spectra for all positive samples were higher than 92%. The method is simple, accurate and efficient for the determination of sodium cyclamate in liquor and particularly suitable for confirmatory analysis of positive samples.