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Liver fibrosis is a major risk factor for hepatocellular carcinoma origin, and its progression not only correlates with oxidative stress and inflammation, but also is encouraged by autophagy hold‐up. Therefore, new solutions to effectively attenuate oxidative stress and inflammation and coincidently favor autophagy are highly demanded to reverse liver fibrosis, and even hamper its escalation into hepatocellular carcinoma. Herein, the porous manganese‐substituted Prussian blue (PMPB) analogs are harnessed to activate autophagy, scavenge reactive oxygen species (ROS), and suppress inflammation for liver fibrosis therapy. PMPB can effectively inhibit macrophage activation, facilitate macrophage autophagy, eradicate ROS, and blockade cellular cross‐talk, thus impeding further inflammation progression. Moreover, the favorable spontaneous capture of PMPB by Kupffer cells allows more PMPB accumulation in liver to significantly attenuate liver injury and collagen deposition, thereby inhibiting the progression of liver fibrosis. PMPB‐based nanomedicine shows great potentials in promoting autophagy activation, eliminating ROS, inhibiting inflammation, and protecting hepatocytes from oxidative stress‐arised damages, which eventually attenuate the extent of liver fibrosis, holding great promise in clinical translation for treating liver fibrosis. The porous manganese‐substituted Prussian blue (PMPB) analogs have been developed to achieve both ROS scavenging and inflammation inhibition from its essence, activate cellular autophagy, protect hepatocytes from damage, blockade cellular cross‐talk, and alter the plasticity of liver fibrosis for eventually attenuating or reversing liver fibrosis.

In recent years, speech emotion recognition technology is of great significance in widespread applications such as call centers, social robots and health care. Thus, the speech emotion recognition has been attracted much attention in both industry and academic. Since emotions existing in an entire utterance may have varied probabilities, speech emotion is likely to be ambiguous, which poses great challenges to recognition tasks. However, previous studies commonly assigned a single-label or multi-label to each utterance in certain. Therefore, their algorithms result in low accuracies because of the inappropriate representation. Inspired by the optimally interacting theory, we address the ambiguous speech emotions by proposing a novel multi-classifier interactive learning (MCIL) method. In MCIL, multiple different classifiers first mimic several individuals, who have inconsistent cognitions of ambiguous emotions, and construct new ambiguous labels (the emotion probability distribution). Then, they are retrained with the new labels to interact with their cognitions. This procedure enables each classifier to learn better representations of ambiguous data from others, and further improves the recognition ability. The experiments on three benchmark corpora (MAS, IEMOCAP, and FAU-AIBO) demonstrate that MCIL does not only improve each classifier’s performance, but also raises their recognition consistency from moderate to substantial.

Dysregulated crosstalk between different signaling pathways contributes to tumor development, including resistance to cancer therapy. In the present study, we found that the mitogen-activated extracellular signal-regulated kinase (MEK) inhibitor trametinib failed to suppress the proliferation of PANC-1 and MGC803 cells by activating the Janus kinase 2 (JAK2)/signal transducer and activator of transcription 3 (STAT3) signaling pathway, while the JAK2 inhibitor fedratinib failed to inhibit the growth of the PANC-1 cells upon stimulation of extracellular signal-regulated kinase (ERK) signaling. In particular, the most prominent enhancement of the anti-proliferative effect resulted from the concurrent blockage of the JAK2/STAT3 and ERK signaling pathways. Furthermore, the combination of the two inhibitors resulted in a reduced tumor burden in mice. Our evidence suggests novel crosstalk between JAK2/STAT3 and ERK signaling in gastric cancer (GC) and pancreatic ductal adenocarcinoma (PDAC) cells and provides a therapeutic strategy to overcome potential resistance in gastrointestinal cancer.