Intratumoral injection of norcantharidin liposome emulsion hybrid delivery system amplifies the cancer-fighting effects of oral sorafenib against hepatocellular carcinoma.

Interventional therapies are increasingly used in clinical trials for hepatocellular carcinoma (HCC). Sorafenib is the front-line remedy for HCC, however, chemoresistance occurs immutably and affects the effectiveness of treatment. In a previous study, a norcantharidin liposome emulsion hybrid (NLEH) delivery system for HCC was developed. This study aims to examine the therapeutic effects of the combination of intratumoral injection of NLEH and sorafenib in treating HCC. Sorafenib combined with NLEH activated the apoptosis pathway by synergistically upregulating caspase-9, promoting cytotoxicity, apoptosis (64.57%), and G2/M cell cycle arrest (48.96%). Norcantharidin could alleviate sorafenib resistance by counteracting sorafenib-induced phosphorylation of Akt. Additionally, intratumoral injection of NLEH exhibited a sustained accumulation in the tumor within 24 h and didn't distribute to other major organs. Intratumoral injection of NLEH in combination with oral sorafenib displayed the most potent tumor growth inhibitory effect (77.91%) in vivo. H&E staining results and the indicators of the renal and liver function tests demonstrated the safety of this combination therapy. Overall, these results showed that intratumoral injection of NLEH in combination with oral sorafenib treatment represented a rational potential therapeutic option for HCC.

Discrimination of Deoxynivalenol Levels of Barley Kernels Using Hyperspectral Imaging in Tandem with Optimized Convolutional Neural Network.

Deoxynivalenol (DON) in raw and processed grain poses significant risks to human and animal health. In this study, the feasibility of classifying DON levels in different genetic lines of barley kernels was evaluated using hyperspectral imaging (HSI) (382-1030 nm) in tandem with an optimized convolutional neural network (CNN). Machine learning methods including logistic regression, support vector machine, stochastic gradient descent, K nearest neighbors, random forest, and CNN were respectively used to develop the classification models. Spectral preprocessing methods including wavelet transform and max-min normalization helped to enhance the performance of different models. A simplified CNN model showed better performance than other machine learning models. Competitive adaptive reweighted sampling (CARS) in combination with successive projections algorithm (SPA) was applied to select the best set of characteristic wavelengths. Based on seven wavelengths selected, the optimized CARS-SPA-CNN model distinguished barley grains with low levels of DON (<5 mg/kg) from those with higher levels (5 mg/kg < DON ≤ 14 mg/kg) with an accuracy of 89.41%. The lower levels of DON class I (0.19 mg/kg ≤ DON ≤ 1.25 mg/kg) and class II (1.25 mg/kg < DON ≤ 5 mg/kg) were successfully distinguished based on the optimized CNN model, yielding a precision of 89.81%. The results suggest that HSI in tandem with CNN has great potential for discrimination of DON levels of barley kernels.

PD-L1 blockade liberates intrinsic antitumourigenic properties of glycolytic macrophages in hepatocellular carcinoma.

OBJECTIVE: Patients with increased PD-L1+ host cells in tumours are more potent to benefit from antiprogrammed death-1/programmed death ligand-1 (PD-L1) treatment, but the underlying mechanism is still unclear. We aim to elucidate the nature, regulation and functional relevance of PD-L1+ host cells in hepatocellular carcinoma (HCC). DESIGN: A total of untreated 184 HCC patients was enrolled randomly. C57BL/6 mice are given injection of Hepa1-6 cells to form autologous hepatoma. ELISpot, flow cytometry and real-time PCR are applied to analyse the phenotypic characteristics of PD-L1+ cells isolated directly from HCC specimens paired with blood samples or generated from ex vivo and in vitro culture systems. Immunofluorescence and immunohistochemistry are performed to detect the presence of immune cells on paraffin-embedded and formalin-fixed samples. The underlying regulatory mechanisms of metabolic switching are assessed by both in vitro and in vivo studies. RESULTS: We demonstrate that PD-L1+ host macrophages, which constructively represent the major cellular source of PD-L1 in HCC tumours, display an HLA-DRhighCD86high glycolytic phenotype, significantly produce antitumourigenic IL-12p70 and are polarised by intrinsic glycolytic metabolism. Mechanistically, a key glycolytic enzyme PKM2 triggered by hepatoma cell derived fibronectin 1, via a HIF-1α-dependent manner, concurrently controls the antitumourigenic properties and inflammation-mediated PD-L1 expression in glycolytic macrophages. Importantly, although increased PKM2+ glycolytic macrophages predict poor prognosis of patients, blocking PD-L1 on these cells eliminates PD-L1-dominant immunosuppression and liberates intrinsic antitumourigenic properties. CONCLUSIONS: Selectively modulating the 'context' of glycolytic macrophages in HCC tumours might restore their antitumourigenic properties and provide a precise strategy for anticancer therapy.