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Lung cancer is the leading cause of cancer-related deaths worldwide. Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) showed great therapeutic efficacy for non-small cell lung cancer (NSCLC) patients. However, acquired resistance severely limits the clinical application and efficacy of EGFR-TKIs. In the current study, we found that solamargine (SM), a natural alkaloid derived from the fruit of Lycium tomato lobelia, has been found to inhibit the progression of NSCLC and enhance the anti-cancer effect of EGFR-TKIs. In brief, SM significantly inhibited the cell viability of NSCLC cells and enhanced the anti-cancer effect of gefitinib (GFTN) and erlotinib (ERL). Mechanistically, SM decreased the expression of MALAT1 and induced miR-141-3p, whereas reduced SP1 protein levels. Interestingly, both MALAT1 and Sp1 have classical and conservative binding sites of miR-141-3p in their 3′-UTR regions. Silence of MALAT1 and overexpression of miR-141-3p both decreased the protein expression of Sp1. Subsequently, promoter activity and protein expression of IGFBP1 were up-regulated by SM, which was not observed in cells with SP1 overexpression. Moreover, the inhibitory effect of SM on cell growth was significantly blocked by knockdown of IGFBP1 expression. More importantly, the combination of SM and GFTN synergistically inhibited the progression of lung cancer. Similar results were observed in experiments in vivo. Finally, the clinical relevance of MALAT1, Sp1, and IGFBP1 was further validated using bioinformatics analysis. Taken together, we confirmed that SM significantly enhanced the anti-cancer effect of EGFR-TKIs by regulating the MALAT1/miR-141-3p/Sp1/IGFBP1 signaling pathway. This study unravels a novel mechanism and suggests a new potential NSCLC associated therapy.

Hepatocellular carcinoma (HCC) is one of the most common primary malignancies. Drug resistance has significantly prevented the clinical application of sorafenib (SF), a first-line targeted medicine for the treatment of HCC. Solamargine (SM), a natural alkaloid, has shown potential antitumor activity, but studies about antitumor effect of SM are obviously insufficient in HCC. In the present study, we found that SM significantly inhibited the growth of HCC and enhanced the anticancer effect of SF. In brief, SM significantly inhibited the growth of HepG2 and Huh-7 cells. The combination of SM and SF showed a synergistic antitumor effect. Mechanistically, SM downregulated the expression of long noncoding RNA HOTTIP and TUG1, followed by increasing the expression of miR-4726-5p. Moreover, miR-4726-5p directly bound to the 3'-UTR region of MUC1 and decreased the expression of MUC1 protein. Overexpression of MUC1 partially reversed the inhibitory effect of SM on HepG2 and Huh-7 cells viability, which suggested that MUC1 may be the key target in SM-induced growth inhibition of HCC. More importantly, the combination of SM and SF synergistically restrained the expression of MUC1 protein. Taken together, our study revealed that SM inhibited the growth of HCC and enhanced the anticancer effect of SF through HOTTIP-TUG1/miR-4726-5p/MUC1 signaling pathway. These findings will provide potential therapeutic targets and strategies for the treatment of HCC.

In the past decade, human activity recognition (HAR) has grown in popularity due to its applications in security and entertainment. As recent years have witnessed the emergence of health care and exoskeleton robotics which make use of wearable suits, human–machine interaction based on action recognition performs an important role in multimedia applications. Considering the limitations of the application scenario, the surface electromyography (sEMG) signal stands out in many wearable data collection devices for HAR. That is because: (1) timely feedback; (2) no damage to the human body; and (3) the wide range of recognizable actions. However, existing public datasets of sEMG contained relatively few activities, and several large-scale datasets only collected the action of the hand. In addition, the processing of sEMG signals is a new field with no effective evaluation system for it. To tackle these problems, we establish a novel dataset for HAR on lower-limb sEMG named “HAR-sEMG,” using 6 sEMG signal sensors attached to the left leg. A benchmark summarizing experiments with many combinations of existing high-dimensional signal processing algorithms-based manifold learning on our dataset is also provided for a performance analysis.

Robotic arms are expected to perform increasingly complex and intelligent tasks in industrial applications. These functions depend, to a large extent, on successful image classification. However, conventional image classification methods perform less well on randomly placed parts where there is uneven illumination in the industrial environment. Through detailed analysis of images taken in an industrial grasping environment, here, we propose a weighted ensemble neural network that can effectively overcome the impact of uneven placement and illumination over an entire image. For an image with overlapping parts, we combine ensemble learning with random cropping and develop the random cropping ensemble neural network (RCE-NN). RCE-NN has two main components: 1) random cropping helps to select different subimages in the image and 2) the weighted ensemble handles the results of each subimage classification to reduce subimage noise. In this article, the uncertainty of the class probability is considered, and therefore, the entropy of the subimage is used to predict the weight. We conduct experiments on our new FIST-Parts10 data set to verify the effectiveness of RCE-NN for image classification.

In China, Brucea javanica oil emulsion injection (BJOEI) has been used as adjuvant therapy to treat cancer for many years. Many systematic reviews (SRs) or meta-analyses (MAs) were published to evaluate its efficacy and safety. Nevertheless, uneven quality made it difficult to reach a consensus and there has been no specific review to integrate the evidence of BJOEI for cancer at present. Therefore, a comprehensive evidence map is needed to guide clinicians.We, for the first time, conducted an overview to assess the SRs/MAs of BJOEI, and provided a comprehensive evidence map to guide clinicians. Besides, this study provided a promising direction for future research to promote the generation of advanced evidence.An overview of SRs or MAs.The pre-defined search strategies were applied to 8 databases. Suitable SRs/MAs were included according to the inclusion and exclusion criteria. Methodological quality, reporting quality, and risk of bias were assessed. An evidence map was conducted to show the situation of clinical evidence.27 SRs/MAs in 7 cancer types were included in this overview. The main problems of SRs/MAs were concentrated on the following aspects: without registration or protocol, lacking gray literature retrieval and a list of excluded studies, incomplete description in the literature retrieval strategy or the methods of merging results, the bias of each synthetic result, less exploration in heterogeneity or publication bias, deficiencies in assessing evidence quality and less description in conflict, funding or access to relevant information. Based on the rules of GRADE, the evidence quality of 154 items in 27 SRs/MAs was defined as moderate quality (103 items), low-quality (44 items), and very low-quality (7 items). Especially, risk of bias (154 items), imprecision (27 items), inconsistency (20 items), and publication bias (9 items) were the main downgrading factors.BJOEI may be a promising adjuvant therapy for treating cancer, especially in the digestive system. However, high-quality SRs/MAs are expected to be carried out to improve the reliability of the above conclusion in the future.

17α-ethinylestradiol (17α-EE

Complementary and alternative medicine (CAM) plays a critical role in treating cancer patients. Traditional Chinese Medicine (TCM) is the main component of CAM. TCM, especially Chinese Herbal Medicine (CHM), has been increasingly used in China, some other Asian countries and European countries. It has been proven to enhance the efficacy of chemotherapy, radiotherapy, targeted-therapy, and immunotherapy. It lessens the damage caused by these therapies. CHM functions on cancer by inhibiting tumor progression and improving an organism’s immune system. Increasing evidence has shown that many CHM exert favorable effects on the immune regulation. We will summarize the role of CHM on patient’s immune system when treating cancer patients. Our evidence reveals that single herbs, including their extracts, compound formulations, and preparations, will provide current advances on CHM study, especially from the perspective of immune regulation and novel insights for CHM application in clinic. The main herbs used to treat cancer patients are health-strengthening (Fu-Zheng) herbs and pathogen eliminating (Qu-Xie) herbs. The key mechanism is regulating the immune system of cancer patients. Firstly, health-strengthening herbs are mainly functioned as immune regulatory effectors on cancer. Secondly, some of the compound formulations mainly strengthen the health of patients by regulating the immune system of cancer patients. Lastly, some Chinese medicine preparations are widely used to treat cancer for their properties of spiriting vital energy and anti-cancer effects, mainly by improving immunity. CHM plays a positive role in regulating patients’ immune system, which helps cancer patients to fight against cancer itself and finally improves patients’ life quality.

Nasopharyngeal carcinoma (NPC) is a common head and neck malignancy with higher incidence in Southern China and Southeast Asia. Solamargine (SM), a steroidal alkaloid glycoside, has been shown to have anticancer properties. However, the underlying mechanism involved remains undetermined. In this study, we showed that SM inhibited the growth of NPC cells. Mechanistically, we found that solamargine decreased lncRNA colon cancer-associated transcript-1 (CCAT1) and increased miR7-5p expression. There was a reciprocal interaction of CCAT1 and miR7-5p. In addition, SM inhibited the expression of SP1 protein and promoter activity, which was strengthened by miR7-5p mimics and inhibited by overexpressed CCAT1. MiR7-5p could bind to 3'-UTR of SP1 and attenuated SP1 gene expression. Exogenously expressed SP1 feedback resisted SM-increased miR7-5p expression and more importantly reversed SM-inhibited growth of NPC cells. Finally, SM inhibited NPC tumor growth in vivo. Collectively, our results show that SM inhibits the growth of NPC cells through reciprocal regulation of CCAT1 and miR7-5p, followed by inhibition of SP1 gene expression in vitro and in vivo. The interregulation and correlation among CCAT1, miR7-5p and SP1, and the feedback regulatory loop unveil the novel molecular mechanism underlying the overall responses of SM in anti-NPC.

Background Lung cancer is a leading cause of cancer-related death worldwide. Previously we demonstrated that polyphyllin I (PPI), a bioactive component extracted from Paris polyphylla, inhibited the growth of non-small cell lung cancer (NSCLC) cells through the SAPK/JNK-mediated suppressing p65, DNMT1 and EZH2 expressions. However, the molecular mechanism underlying anti-lung cancer effect by PPI still remain elusive. Purpose In this current study, we further explored the molecular mechanism underlying the anti-lung cancer effect of PPI. Methods MTT, Cell-LightTM EdU DNA cell proliferation and colony formation assays were used to measure cell growth. Western blot were used to examine protein levels of c-Jun and p21. The expression level of long non-codingth RNA HOX transcript antisense RNA (HOTAIR) was measured by qRT-PCR. The p21 promoter activity was measured by Dual-Luciferase Reporter Assay System. The transient transfection experiments were used to silence and overexpression of c-Jun, p21 and HOTAIR. Tumor xenograft and bioluminescent imaging experiments were carried out to confirm the in vitro findings. Results We showed that PPI suppressed growth of NSCLC cells. Mechanistically, we observed that PPI reduced expression of HOTAIR, while increased transcription factor c-Jun protein levels. Additionally, PPI also induced protein expression and promoter activity of p21, a cyclin-dependent kinase inhibitor. While exogenously expressed HOTAIR showed no effect on c-Jun levels, silencing of c-Jun significantly reversed the PPI-inhibited HOTAIR expression. Moreover, excessive expressed c-Jun further enhanced PPI-inhibited HOTAIR expression and PPI-induced p21 protein levels. Intriguingly, overexpression of HOTAIR and silencing of c-Jun overcame the PPI-induced p21 protein and promoter activity. Finally, silencing of p21 neutralized the PPI-inhibited cell proliferation. Similar results were also found in one xenograft mouse model. Conclusion Our results demonstrate that PPI inhibits growth of NSCLC cells through regulation of HOTAIR and c-Jun expressions, which lead to induction of p21 gene. The interactions among HOTAIR, c-Jun and p21 regulatory axis converge in the overall anti-lung cancer effect of PPI. This study unveils an additional new mechanism for the anti-lung cancer role of PPI.

microRNA-21 (miRNA-21) is a well-characterized oncogenic miRNA in human cancers. In the present study, we found that miRNA-21 was upregulated, while long noncoding RNA Mortal Obligate RNA Transcript (lncRNA MORT), which has been reported to be silenced in 16 types of cancers, was downregulated in tumor tissues than in adjacent healthy tissues of patients with ovarian carcinoma. Expression of lncRNA MORT in tumor tissues was found to be significantly affected by tumor size but not by tumor metastasis. Expression levels of lncRNA MORT and miRNA-21 were significantly and inversely correlated in both tumor tissues and adjacent healthy tissues. Overexpression of lncRNA MORT inhibited miRNA-21, while miRNA-21 overexpression failed to significantly affect lncRNA MORT expression. Overexpression of lncRNA MORT inhibited, while miRNA-21 overexpression promoted the proliferation of cells of ovarian cancer cell lines. In addition, miRNA-21 overexpression partially reversed the inhibitory effects of lncRNA MORT overexpression on cancer cell proliferation. However, overexpression of lncRNA MORT showed no significant effects on cancer cell migration and invasion. Therefore, lncRNA MORT was downregulated in ovarian carcinoma and lncRNA MORT overexpression inhibited cancer cell proliferation, possibly by downregulating miRNA-21.

To assess the effectiveness and safety of traditional Chinese medical therapy for cancer-related fatigue.We systematically searched eight electronic databases up to June 2017 for randomized clinical trials of traditional Chinese medical therapy for cancer-related fatigue. Two authors independently extracted data and assessed the risk bias of the included trials using the Cochrane Handbook. Data were analyzed by RevMan 5.2 software.A total of 23 trials involving 1832 participants identified with cancer-related fatigue were included. Twenty trials reported a beneficial effect of traditional Chinese medical therapy on cancer-related fatigue. On pooling the data from Chinese herbal medicine therapy and acupuncture or moxibustion therapy, respectively, significant differences were found between experimental groups and control groups. Fatigue improvement rates showed significant differences between traditional Chinese medical therapy and control groups [odds ratio (OR), 7.62; 95% confidence interval (CI), 3.75-15.49; P0.000 01; and OR, 3.78; 95% CI, 2.29-6.23; P0.000 01). Fatigue change scores also showed significant differences between the two groups (mean difference, -0.91; 95% CI, -0.16 to -0.65; P0.000 01). Eleven trials demonstrated that traditional Chinese medical therapy improved the quality of life of cancer patients. No severe adverse effects occurred in traditional Chinese medical therapy groups.Meta-analysis showed that Chinese medical therapy seems to be effective and safe in the treatment of cancer-related fatigue.

Background: To explore novel related genes and potential biomarkers that predict progression from smokers to lung adenocarcinoma (LA). Methods: Three datasets from GEO (Gene Expression Omnibus) database were used to identify differentially expressed genes (DEGs) between LA tissue (LAT) and normal tumor adjacent tissue (TAT). The overlap of DEGs could be found and enriched in gene oncology (GO) and pathways to discover the potential biological mechanisms. Protein-protein interaction (PPI) network was applied to find the relationship among proteins. Survival analysis contributed to the definiteness of key genes. The expression of key genes in LA patients who smoke was verified. Furthermore, genetic alterations, co-expression and pathways of key genes were explored. To obtain more information, key genes were further analyzed in immune infiltration, drug target and the distribution of single cell in LA. Results: 245 DEGs were revealed in 3 datasets from GEO. In Kaplan Meier plotter, we found that high expression of COL1A1, COL1A2 and COL3A1 was associated with poorer survival while low expression of DCN was contributed to poorer survival in LAs who smoke. Thus, three up-regulated genes (COL1A1, COL1A2, COL3A1) and one down-regulated gene (DCN) were defined as key genes. Their genetic alterations were more common in female LA smokers and co-expression genes/proteins of them mainly functioned at extracellular matrix. Furthermore, COL1A1, COL1A2, COL3A1 genes had a common targeted drug called Collagenase clostridium histolyticum (DB00048) and DCN gene had a targeted drug called Tromethamine (DB03754). In the Single Cell Expression Atlas of EMBL-EBL, COL3A1 gene was specifically highly expressed in female LA patients with brain metastasis. Conclusions: COL1A1, COL1A2, COL3A1 and DCN could be regarded as novel potential biomarkers that predict progression from smokers to lung adenocarcinoma.

Background Cancer-related fatigue (CRF) is the most common symptom in patients with advanced non-small cell lung cancer (NSCLC) undergoing treatment with chemotherapy. However, evidence upon which to base management strategies is scarce. Traditional Chinese Medicine (TCM) has been shown to be beneficial to patients with CRF. Chinese herbal injections should be administered under an evidence-based approach. This trial aims to assess the efficacy and safety of the addition of the Shenmai injection (SMI) to conventional therapy for CRF in NSCLC patients undergoing chemotherapy. Methods/design The study is a two-group, prospective, randomized controlled trial (RCT) designed to evaluate the efficacy and safety of SMI for CRF NSCLC patients undergoing chemotherapy. Eligible participants will be randomized to either a treatment group receiving a 5-day Shenmai injection regimen plus conventional therapy or a control group receiving only conventional therapy. The primary outcome is fatigue, assessed using severity scores from the Functional Assessment for Chronic Illness Therapy-Fatigue (FACIT-F) measurement system. Secondary outcomes include symptom distress scores, depression, sleep disorders, quality of life, and levels of immunologic indicators. Assessments will be carried out at baseline and on day 5 (the end of the intervention). Discussion This study can provide evidence to support clinical decision-making in the management of CRF in NSCLC patients undergoing chemotherapy in a way that can be scaled up and used throughout China. Trial registration Chinese Clinical Trial Registry (chictr.org.cn), ChiCTR-INR-17013737. Registered on 6 December 2017. Electronic supplementary material The online version of this article (10.1186/s13063-018-2845-7) contains supplementary material, which is available to authorized users.

Berberine (BBR), one of active alkaloid found in the rhizome, exhibited anti‐cancer properties. We have showed that BBR inhibited growth of non‐small cell lung cancer (NSCLC) cells through mitogen‐activated protein kinase (MAPK)‐mediated increase in forkhead box O3a (FOXO3a). However, the in‐depth mechanism underlying the anti‐tumor effects still remained to be elucidated. Herein, we further confirmed that BBR not only induced cell cycle arrest, but also reduced migration and invasion of NSCLC cells. Mechanistically, we observed that BBR reduced 3‐phosphoinositide‐dependent protein kinase‐1 (PDPK1) and transcription factor SP1 protein expressions. Exogenously expressed SP1 overcame BBR‐inhibited PDPK1 expression. Moreover, BBR inhibited DNA methyltransferase 1 (DNMT1) gene expression and overexpressed DNMT1 resisted BBR‐inhibited cell growth. Intriguingly, overexpressed PDPK1 antagonized BBR‐inhibited SP1 and DNMT1 expressions. Finally, metformin enhanced the effects of BBR both in vitro and in vivo. Collectively, we observe that BBR inhibits proliferation of NSCLC cells through inhibition of SP1 and PDPK1; this results in a reduction of DNMT1 expression. The interplay of PDPK1 and SP1 contributes to the inhibition of DNMT1 in response to BBR. In addition, there is a synergy of BBR and metformin. This study uncovers a new mechanism of BBR in combination with metformin for NSCLC‐associated therapy.

Lung cancer is a leading cause of cancer‑associated mortality worldwide, including in developing countries such as China. Traditional Chinese medicine may provide a novel insight for the treatment of patients with lung cancer. The present study aimed to uncover the mechanism by which the Chinese herbal medicine, Fuzheng Kang‑Ai (FZKA), functions on lung cancer cell metastasis. The results demonstrated that treatment with FZKA markedly inhibited cell viability, migration and invasion of lung cancer cells, as determined by cell viability and Transwell assays. Notably, the activity and expression of matrix metalloproteinase 9 (MMP9) was significantly inhibited by FZKA treatment on lung cancer cells, as determined by an MMP9 activity assay and western blot analysis. Furthermore, FZKA markedly inhibited epithelial‑mesenchymal transition (EMT) of lung cancer cells by inhibiting the expression of the mesenchymal markers N‑cadherin and vimentin. In addition, activation of the oncoprotein signal transducer and activator of transcription 3 (STAT3) was suppressed following treatment with FZKA. Conversely, overexpression of STAT3 was able to rescue MMP9 activity following FZKA treatment. The present study indicated that FZKA may inhibit lung cancer metastasis via the STAT3/MMP9 pathway and EMT, suggesting that FZKA may serve as a novel promising therapeutic strategy for the treatment of patients with late stage lung cancer.

Additional file 1: Table S1. Sequences of all primers (qRT-PCR) and siRNAs. Figure S1. HPLC chromatograms in different drinks of FZKA decoction have similar patterns. Figure S2. STAT3 was inhibited both at protein and mRNA levels by treating with siSTAT3 in PC9 cells. Figure S3. Flow cytometry analysis of cell apoptosis data showing the gating strategy.

Person re-identification, as a branch of image retrieval, has an extremely important application in public safety. In the past few decades, researchers have improved its accuracy through a variety of methods, including increasing data volumes and developing feature extraction or metric learning schemes. As the data volumes increased, researchers began to turn handcrafted feature algorithms to deep learning. Now, with the emergence of deep learning and large-scale data, we need to discuss which kind of metric learning performances on the re-identification problem is better. In this paper, to address the data shortage problem and learn invariant property from different cameras, we choose a camera adaptation method to increase the data volumes. We conduct comprehensive experiments on two datasets with camera adaptation and combine recent advances on feature extraction and metric learning. To ensure fairness, all methods use a unified code library that includes 4 deep feature extraction networks and 8 metric learning. The experimental results show that, under the premise of continuous improvement in deep learning, the traditional metric method based on Euclidean distance also achieved commendable results.

Ethnopharmacological relevance The Chinese herbal medicine Fuzheng Kang-Ai (FZKA) decoction obtained from Guangdong Kangmei Pharmaceutical Company, which contains 12 components with different types of constituents, has been used as part of the adjuvant treatment of lung cancer for decades. We previously showed that FZKA decoction enhances the growth inhibition of epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI)-resistant non-small cell lung cancer (NSCLC) cells by suppressing glycoprotein mucin 1 (MUC1) expression. However, the molecular mechanism underlying the therapeutic potential, particularly in sensitizing or/and enhancing the anti-lung cancer effect of EGFR-TKIs, remains unclear. Materials and methods Cell viability was measured using 3-(4, 5-diMEThylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) and 5-ethynyl -2′-deoxyuridine (EdU) assays. Western blot analysis was performed to examine the protein expressions of DNA methyltransferase 1 (DNMT1), specificity protein 1 (SP1), and MET, an oncogene encoding for a trans-membrane tyrosine kinase receptor activated by the hepatocyte growth factor (HGF). The expression of MET mRNA was measured by quantitative real-time PCR (qRT-PCR). Exogenous expression of DNMT1 and SP1, and MET were carried out by transient transfection assays. The promoter activity of MET was tested using Dual-luciferase reporter assays. A nude mouse xenografted tumor model further evaluated the effect of the combination of FZKA decoction and erlotinib in vivo. Results The combination of FZKA and erlotinib produced an even greater inhibition of NSCLC cell growth. FZKA decreased the expressions of DNMT1, SP1, and MET (c-MET) proteins, and the combination of FZKA and erlotinib demonstrated enhanced responses. Interestingly, there was a mutual regulation of DNMT1 and SP1. In addition, exogenously expressed DNMT1 and SP1 blocked the FZKA-inhibited c-MET expression. Moreover, excessive expressed MET neutralized FZKA-inhibited growth of NSCLC cells. FZKA decreased the mRNA and promoter activity of c-MET, which was not observed in cells with ectopic expressed DNMT1 gene. Similar findings were observed in vivo. Conclusion FZKA decreases MET gene expression through the repression and mutual regulation of DNMT1 and SP1 in vitro and in vivo. This leads to inhibit the growth of human lung cancer cells. The combination of FZKA and EGFR-TKI erlotinib exhibits synergy in this process. The regulatory loops among the DNMT1, SP1 and MET converge in the overall effects of FZKA and EGFR-TKI erlotinib. This in vitro and in vivo study clarifies an additional novel molecular mechanism underlying the anti-lung cancer effects in response to the combination of FZKA and erlotinib in gefitinib-resistant NSCLC cells.

Person re-identification, a branch of image retrieval, is an increasingly important public safety application. When monitoring larger areas, it is crucial to correctly match the same person in different camera views. With the emergence of deep learning and large-scale data, metric learning has significantly improved person re-identification performance, but the extent to which deep features affect metric learning performance is unknown. However, given the large number of approaches, datasets, evaluation indices, and experimental environments, comparing metric learning methods directly is difficult. To obtain a more comprehensive empirical evaluation of the person re-identification, here we summarize the different types of features and metric learning approaches from a label attributes perspective. Then, by combining advanced approaches to data enhancement and feature extraction, we conduct comprehensive experiments on metric learning methods with two datasets. For fairness, all methods use a unified code library that includes two data enhancement schemes, eight feature extraction algorithms, and eight metric learning methods. Our results show that, the relations of loss function with deep feature space and metric learning.

Rice grading is an important topic in the research of food security, which targets at assessing the quality of rice. However, there is seldom attention from researchers. In this paper, we propose a novel rice grading system, named as Deep-Rice, which is built upon a deep learning framework. Specifically, Deep-Rice employs a multi-view CNN architecture to extract the discriminative features from different views of rice images, and tries to optimize the CNN parameters by using a modified softmax loss function. In accompany with this deep model, we also build a large-scaled rice dataset, which is denoted as FIST-Rice, to provide a baseline database for the research of food security. FIST-Rice is the first publicly available multi-sensor rice dataset, which contains sound and unsound kernel samples with the total number of 30,000. Each sample is captured under three different illumination conditions. We evaluate the proposed Deep-Rice model on the FIST-Rice dataset by comparing with the AdaBoost and SVM methods. The experimental results indicate the Deep-Rice model achieves improved performance in different conditions of light intensity. The FIST-Rice dataset and baseline codes will be released for further public research.

Although lots of great achievements have been gained in the battle against cancer during the past decades, cancer is still the leading cause of death in the world including in developing countries such as China. Traditional Chinese medicine (TCM) is popular in Chinese and East Asian societies as well as some other Western countries and plays an active role in the modern healthcare system including patients with cancer, which may act as a potential effective strategy in treating human cancers. In this review, we aimed to introduce the mechanisms of TCM compound, as an option of individualized therapy, in treating cancer patients from the perspective of both Chinese and Western medicine. In the view of traditional Chinese medicine theory, individualized treatment for human cancers based on syndrome type benefits the cancer patients with personalized conditions. Balancing Qi, Xue, Yin and Yang, eliminating phlegm and removing dampness is how TCM compound functions on cancer patients. While in the view of Western medicine, inhibiting cancer cell growth and metastasis as well as improving immune status is how herbal compounds act on cancer patients. We also summarized the applications of TCM compound in human cancers, which will shed light on the clinical application of TCM compound on patients with cancer. TCM compound could be used as a complementary and alternative medicine (CAM) in human cancers. It could be applied in cancer patients with cancer-related fatigue (CRF). In addition, it is a good method for alleviating the side effects of both radiotherapy and chemotherapy. Therefore, TCM compound plays a critical role in treating patients with cancer, which has a promising strategy in the field of cancer management.

DNA methylation is one of the main epigenetic modifications. It controls gene expression through altering chromosomal structure, DNA conformation, DNA stability and the function way between DNA and protein. In this chapter, we first provided insights into the process of DNA methylation, and the methods measuring DNA methylation level. Then, we summarized the mechanisms by which DNA methylation functions in human cancers. Furthermore, we explored the functional roles/consequences of DNA methylation in the initiation, development, and metastasis of human cancers as well as related pathways. Last but not the least, we discussed the clinical applications of DNA methylation in tumor diagnosis and therapy, as well as the future direction and potential pitfalls of DNA methylation applied in clinic. Our main goal is to better understand the exact role of DNA methylation in human cancers from its mechanisms to its applications, which identifies novel epigenetic strategies for treating cancer patients.

SPIRIT checklist. (DOC 105 kb)

β-elemene, a compound derived from Rhizoma zedoariae, is a promising new plant-derived drug with broad-spectrum anticancer activity. However, the underlying mechanism by which this agent inhibits human lung cancer cell growth has not been well elucidated. In this study, we showed that β-elemene inhibits human non-small cell lung carcinoma (NSCLC) cell growth, and increased phosphorylation of ERK1/2, Akt and AMPKα. Moreover, β-elemene inhibited expression of DNA methyltransferase 1 (DNMT1), which was not observed in the presence of the specific inhibitors of ERK (PD98059) or AMPK (compound C). Overexpression of DNMT1 reversed the effect of β-elemene on cell growth. Interestingly, metformin not only reversed the effect of β-elemene on phosphorylation of Akt but also strengthened the β-elemene-reduced DNMT1. In addition, β-elemene suppressed Sp1 protein expression, which was eliminated by either ERK1/2 or AMPK inhibitor. Conversely, overexpression of Sp1 antagonized the effect of β-elemene on DNMT1 protein expression and cell growth. Taken together, our results show that β-elemene inhibits NSCLC cell growth via ERK1/2- and AMPKα-mediated inhibition of transcription factor Sp1, followed by reduction in DNMT1 protein expression. Metformin augments the effect of β-elemene by blockade of Akt signalling and additively inhibition of DNMT1 protein expression. The reciprocal ERK1/2 and AMPKα signalling pathways contribute to the overall responses of β-elemene. This study reveals a potential novel mechanism by which β-elemene inhibits growth of NSCLC cells.