Metabolic reprogramming is one of the hallmarks of cancer. Nrf2 pathway is one of the critical signaling cascades involved in cell defense and survival against oxidative stress. The significance of Nrf2 in cancer metabolism begins to be recognized. In this minireview, we focus on the Nrf2‐mediated cancer metabolic reprogramming and intend to highlight the role of Nrf2 in the regulation of malignant transformation, cancer proliferation, and the development of treatment resistance via metabolic adaptations. We hope for the development of noninvasive biomarkers and novel therapeutic approaches for cancer based on Nrf2‐directed cancer metabolic reprogramming in the near future.

The development of chemoresistance to cisplatin regimens causes a poor prognosis in patients with advanced NSCLC. The role of noncanonical Wnt signaling in the regulation of properties of lung cancer stem cells and chemoresistance was interrogated, by accessing capacities of cell proliferation, migration, invasion, and clonogenicity as well as the apoptosis in A549 cell lines and cisplatin‐resistant A549 cells treated with Wnt5a conditional medium or protein kinase C (PKC) inhibitor GF109203X. Results showed that the noncanonical Wnt signaling ligand, Wnt5a, could promote the proliferation, migration, invasion, and colony formation in A549 lung adenocarcinoma cells and cisplatin‐resistant A549/DDP cells and increase the fraction of ALDH‐positive cell in A549/DDP cells. An exposure of cells to Wnt5a led to a significant reduction of A549/DDP cell apoptosis but not A549 cells. An addition of GF109203X could both strikingly increase the baseline apoptosis and resensitize the Wnt5a‐inhibited cell apoptosis. Interestingly, an inhibition of Wnt/PKC signaling pathway could reduce properties of lung cancer stem cells, promote cell apoptosis, and resensitize cisplatin‐resistant cells to cisplatin via a caspase/AIF‐dependent pathway. These data thus suggested that the Wnt5a could promote lung cancer cell mobility and cisplatin‐resistance through a Wnt/PKC signaling pathway and a blockage of this signaling may be an alternative therapeutic strategy for NSCLC patients with resistance to chemotherapies.

Background: Health education emerged as an important intervention for improving the awareness and self-management abilities of chronic disease patients. The development of information technologies has changed the form of patient educational materials from traditional paper materials to electronic materials. To date, the amount of patient educational materials on the internet is tremendous, with variable quality, which makes it hard to identify the most valuable materials by individuals lacking medical backgrounds. Objective: The aim of this study was to develop a health recommender system to provide appropriate educational materials for chronic disease patients in China and evaluate the effect of this system. Methods: A knowledge-based recommender system was implemented using ontology and several natural language processing (NLP) techniques. The development process was divided into 3 stages. In stage 1, an ontology was constructed to describe patient characteristics contained in the data. In stage 2, an algorithm was designed and implemented to generate recommendations based on the ontology. Patient data and educational materials were mapped to the ontology and converted into vectors of the same length, and then recommendations were generated according to similarity between these vectors. In stage 3, the ontology and algorithm were incorporated into an mHealth system for practical use. Keyword extraction algorithms and pretrained word embeddings were used to preprocess educational materials. Three strategies were proposed to improve the performance of keyword extraction. System evaluation was based on a manually assembled test collection for 50 patients and 100 educational documents. Recommendation performance was assessed using the macro precision of top-ranked documents and the overall mean average precision (MAP). Results: The constructed ontology contained 40 classes, 31 object properties, 67 data properties, and 32 individuals. A total of 80 SWRL rules were defined to implement the semantic logic of mapping patient original data to the ontology vector space. The recommender system was implemented as a separate Web service connected with patients' smartphones. According to the evaluation results, our system can achieve a macro precision up to 0.970 for the top 1 recommendation and an overall MAP score up to 0.628. Conclusions: This study demonstrated that a knowledge-based health recommender system has the potential to accurately recommend educational materials to chronic disease patients. Traditional NLP techniques combined with improvement strategies for specific language and domain proved to be effective for improving system performance. One direction for future work is to explore the effect of such systems from the perspective of patients in a practical setting.

Background: Mobile health (mHealth) technology is an increasingly recognized and effective method for disease management and has the potential to intervene in pulmonary function, exacerbation risk, and psychological status of patients with chronic obstructive pulmonary disease (COPD). Objective: This study aimed to investigate the feasibility of an mHealth-based COPD management system designed for Chinese remote areas with many potential COPD patients but limited medical resources. Methods: The system was implemented based on a tailored closed-loop care pathway that breaks the heavy management tasks into detailed pieces to be quantified and executed by computers. Low-cost COPD evaluation and questionnaire-based psychological intervention are the 2 main characteristics of the pathway. A 6-month prospective observational study at the community level was performed to evaluate the effect of the system. Primary outcomes included changes in peak expiratory flow values, quality of life measured using the COPD assessment test scale, and psychological condition. Acute exacerbations, compliance, and adverse events were also measured during the study. Compliance was defined as the ratio of the actual frequency of self-monitoring records to the prescribed number. Results: A total of 56 patients was enrolled; 39 patients completed the 6-month study. There was no significant difference in the mean peak expiratory flow value before and after the 6-month period (366.1, SD 106.7 versus 313.1, SD 116.6; P=.11). Psychological condition significantly improved after 6 months, especially for depression, as measured using the Patient Health Questionnaire-9 scale (median 6.0, IQR 3.0-9.0 versus median 4.0, IQR 0.0-6.0; P=.001). The COPD assessment test score after 6 months of intervention was also lower than that at the baseline, and the difference was significant (median 4.0, IQR 1.0-6.0 versus median 3.0, IQR 0.0-6.0; P=.003). The median overall compliance was 91.1% (IQR 67%-100%). In terms of acute exacerbation, 110 exacerbations were detected and confirmed by health care providers (per 6 months, median 2.0, IQR 1.0-5.0). Moreover, 72 adverse events occurred during the study, including 1 death, 19 hospitalizations, and 52 clinic visits due to persistent respiratory symptoms. Conclusions: We designed and validated a feasible mHealth-based method to manage COPD in remote Chinese areas with limited medical resources. The proposed closed-loop care pathway was effective at the community level. Proper education and frequent communication with health care providers may encourage patients’ acceptance and use of smartphones to support COPD self-management. In addition, WeChat might play an important role in improving patient compliance and psychological distress. Further research might explore the effect of such systems on a larger scale and at a higher evidence level.

Objective: Interstitial lung disease (ILD) is a common extramuscular manifestation of the anti-synthetase syndrome (ASS). Patients with ASS-ILD are at risk in developing a progressive fibrosing phenotype despite appropriate treatments. This study investigated the risk factors and the predictive value of multiple risk factors for progressive pulmonary fibrosis (PPF) in patients with ASS-ILD. Methods: Ninety patients with a diagnosis of ASS and evidence of ILD on high-resolution computed tomography (HRCT) were recruited. Among them, 72 participants completed follow-up for more than 12 months. These patients were further divided into a PPF-ASS group (n = 18) and a non-PPF-ASS group (n = 54). Logistic regression analysis was performed to investigate the risk factors for PPF. The predictive value of the combined risk factors for predicting PPF were analyzed by a ROC curve. Results: The PPF-ASS group had a higher rate of positive non-Jo-1 antibodies, a significantly higher neutrophil-to-lymphocyte ratio (NLR) and serum lactate dehydrogenase (LDH), and a significantly lower PaO₂/FiO₂ ratio and diffusing capacity for carbon monoxide (DLCO%pred) than the non-PPF-ASS group. In addition, elevated serum Krebs von den Lungen-6 (KL-6) level and reticular opacities were significantly more common, and corticosteroid monotherapy at onset was administered more frequently in the PPF-ASS group. The median duration of follow-up was 37.4 months, survival was poorer in the PPF-ASS group, and the overall survival was 88.9%. Multivariate regression analysis further revealed that positive non-Jo-1 antibodies, NLR, and KL-6 were independent risk factors for PPF. These combined indexes had good accuracy (area under the curve = 0.874) in predicting PPF in patients with ASS-ILD. Conclusion: Positive non-Jo-1 antibodies, NLR, and serum KL-6 are independent risk factors for PPF in patients with ASS-ILD. Monitoring these markers can potentially predict PPF in this group of patients. Key Points • Positive non-Jo-1 antibodies, NLR, and serum KL-6 are independent risk factors associated with PPF in patients with ASS-ILD. • Monitoring non-Jo-1 antibodies, NLR, and serum KL-6 can potentially predict PPF in patients with ASS-ILD.