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MET exon 14 (METex14) skipping is the most reported MET mutation in non-small cell lung cancer (NSCLC) and has been confirmed to respond to MET tyrosine kinase inhibitors (TKI) in clinical trials. While MET TKI tepotinib was recently approved for METex14 skipping NSCLC in China, real-world evidence is limited. We report our experience treating NSCLC patients referred from oncology sites across China with tepotinib in the Boao Lecheng Pilot Zone. Four patients have been prescribed the drug with a median age of 67 years (range, 61–71 years). One patient has concomitant BRAF V600E mutation, and another patient had savolitinib as first line of therapy but discontinued due to hepatotoxicity. Till the end of follow-up, four patients were all on tepotinib therapy, with a median duration of therapy of 19 months. One patient achieved partial response and three achieved stable disease. Three patients had peripheral edema, but all were mild. Our experience showed in real clinical setting, tepotinib had robust and durable clinical activity and a favorable toxicity profile in Chinese patients with METex14 skipping NSCLC. It is the first report on the effectiveness of tepotinib in a patient with both METex14 skipping and BRAF V600E mutations and successful MET inhibitor switch after MET inhibitor-induced liver injury.

The accurate modeling of multi-temporal correlation of photovoltaic stations output is important to achieve the precise power system reliability. However, the existing studies is mainly focused on the hourly temporal correlation between adjacent interval outputs of photovoltaic station. In this paper, a novel multi-temporal correlation modeling method for photovoltaic station output is proposed by using an improved nonparametric disaggregation (INPD) technique, and the multi-temporal characteristic representing the interactive correlation between the total daily output and hourly temporal outputs are deeply explored. Moreover, a three-stage sampling method for the INPD based power system reliability evaluation is further presented considering the multi-temporal correlation of photovoltaic stations output, which includes 1) the random sampling of daily photovoltaic station output; 2) the random disaggregation of daily output to the hourly temporal outputs and 3) the random sampling of power device. Finally, several numerical tests are conducted for a modified IEEE-RTS79 to validate the proposed method.

This paper describes the design of a bionic soft exoskeleton and demonstrates its feasibility for assisting the expectoration function rehabilitation of patients with spinal cord injury (SCI). Methods: A human–robot coupling respiratory mechanic model is established to mimic human cough, and a synergic inspire–expire assistance strategy is proposed to maximize the peak expiratory flow (PEF), the key metric for promoting cough intensity. The negative pressure module of the exoskeleton is a soft “iron lung” using layer-jamming actuation. It assists inspiration by increasing insufflation to mimic diaphragm and intercostal muscle contraction. The positive pressure module exploits soft origami actuators for assistive expiration; it pressures human abdomen and bionically “pushes” the diaphragm upward. Results: The maximum increase in PEF ratios for mannequins, healthy participants, and patients with SCI with robotic assistance were 57.67%, 278.10%, and 124.47%, respectively. The soft exoskeleton assisted one tetraplegic SCI patient to cough up phlegm successfully. Conclusion: The experimental results suggest that the proposed soft exoskeleton is promising for assisting the expectoration ability of SCI patients in everyday life scenarios. Significance: The proposed soft exoskeleton is promising for advancing the application field of rehabilitation exoskeletons from motor functions to respiratory functions.