Relative Orientation and Position Detections Based on an RGB-D Sensor and Dynamic Cooperation Strategies for Jumping Sensor Nodes Recycling.

This paper presents relative orientation and position detection methods for jumping sensor nodes (JSNs) recycling. The methods are based on motion captures of the JSNs by an RGB-D sensor mounted on a carrier robot and the dynamic cooperation between the carrier and the JSNs. A disc-like label with two different colored sides is mounted on the top of the JSNs. The RGB-D sensor can detect the motion of the label to calculate the orientations and positions of the JSNs and the carrier relative to each other. After the orientations and positions have been detected, the JSNs jump into a cabin mounted on the carrier in dynamic cooperation with the carrier for recycling. The performances of the proposed methods are tested with a prototype system. The results show that the carrier can detect a JSN from up to 2 m away and sense its relative orientation and position successfully. The errors of the JSN's orientation and position detections relative to the carrier could be reduced to the values smaller than 1° and 1 cm, respectively, by using the dynamic cooperation strategies. The proposed methods in this paper could also be used for other kinds of mobile sensor nodes and multi-robot systems.

Out-of-set association analysis of lung cancer drugs and symptoms based on clinical case data mining.

BACKGROUND: There are 1.8 million lung cancer deaths worldwide, accounting for 18% of global cancer deaths, including 710,000 in China, accounting for 23.8% of all cancer deaths in China. OBJECTIVE: To explore the out-of-set association rules of lung cancer symptoms and drugs through text mining of traditional Chinese medicine (TCM) treatment of lung cancer, and form medical case analysis to analyze the experience of TCM syndrome differentiation in its treatment. METHODS: The medical records of all patients diagnosed with lung cancer in Nanjing Chest Hospital from January to December 2018 were collected, and the out-of-set association analysis was performed using the MedCase v5.2 TCM clinical scientific research auxiliary platform based on the frequent pattern growth enhanced association analysis algorithm. RESULTS: In terms of TCM treatment of lung cancer, the clinical symptoms with high correlation included cough, expectoration, chest distress, and white phlegm; and the drugs with high correlation included Pinellia ternata, licorice root, white Atractylodes rhizome, and Radix Ophiopogonis; with the prescriptions based on Erchen and Maimendong decoctions. CONCLUSION: This analytical study of the medical cases of TCM treatment for lung cancer was performed using data mining techniques, and the out-of-set association rules between clinical symptoms and drugs were analyzed, including the understanding of lung cancer in TCM. Moreover, the essence of experience in drug use was gathered, providing significant scientific guidance for the clinical treatment of lung cancer.

GJA4 expressed on cancer associated fibroblasts (CAFs)-A 'promoter' of the mesenchymal phenotype.

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer worldwide. Connexin is a transmembrane protein involved in gap junctions (GJs) formation. Our previous study found that connexin 37 (Cx37), encoded by gap junction protein alpha 4 (GJA4), expressed on fibroblasts acts as a promoter of CRC and is closely related to epithelial-mesenchymal transition (EMT) and tumor immune microenvironment. However, to date, the mechanism concerning the malignancy of GJA4 in tumor stroma has not been studied. METHODS: Hematoxylin-eosin (HE) and immunohistochemical (IHC) staining were used to validate the expression and localization of GJA4. Using single-cell analysis, enrichment analysis, spatial transcriptomics, immunofluorescence staining (IF), Sirius red staining, wound healing and transwell assays, western blotting (WB), Cell Counting Kit-8 (CCK8) assay and in vivo experiments, we investigated the possible mechanisms of GJA4 in promoting CRC. RESULTS: We discovered that in CRC, GJA4 on fibroblasts is involved in promoting fibroblast activation and promoting EMT through a fibroblast-dependent pathway. Furthermore, GJA4 may act synergistically with M2 macrophages to limit T cell infiltration by stimulating the formation of an immune-excluded desmoplasic barrier. Finally, we found a significantly correlation between GJA4 and pathological staging (P < 0.0001) or D2 dimer (R = 0.03, P < 0.05). CONCLUSION: We have identified GJA4 expressed on fibroblasts is actually a promoter of the tumor mesenchymal phenotype. Our findings suggest that the interaction between GJA4+ fibroblasts and M2 macrophages may be an effective target for enhancing tumor immunotherapy.

Analysis of the cluster efficacy and prescription characteristics of traditional Chinese medicine intervention for non-small cell lung cancer based on a clustering algorithm.

BACKGROUND: In recent years, malignant tumors have gradually become one of the main causes of death for Chinese residents, of which lung cancer ranks first in both the incidence and mortality in China. OBJECTIVE: To mine the text of traditional Chinese medicine (TCM) clinical medical cases after data cleaning, analyze it, and study the experience of TCM doctors in treating non-small cell lung cancer (NSCLC). METHODS: The applied approach was based on the data mining methods of decentralized and hierarchical system clustering of data from a drug and prescription database. This study involved 215 patients, 287 cases, and 147 types of clinical drugs. RESULTS: The data analysis of the clinical treatment of NSCLC in TCM showed that Erchen Decoction was the main method for the treatment of non-small cell lung cancer in clinical treatment of non-small cell lung cancer. Junjian recipes were close to each other, with Banzhilian, Lobelia, Shanci Mushroom, Hedyotis diffusa to anticancer and detoxify. CONCLUSION: This study analyzed the core TCM prescription for NSCLC by collecting the empirical essence and characteristics of specific medications. It has some guiding scientific significance for the clinical treatment of lung cancer.

Microalgal mediated antibiotic co-metabolism: Kinetics, transformation products and pathways.

The mutual interaction of a microalga Chlorella vulgaris with four antibiotics viz. sulfamethoxazole (SMX), trimethoprim (TMP), azithromycin (AZI), and levofloxacin (LEV) individually and in mixture was studied in batch culture. SMX, TMP, and LEV stimulated algal growth, while AZI inhibited its growth. The Combination Index (CI)-isobologram indicated antagonism of the antibiotic mixture on the growth of C. vulgaris. Higher removal efficiency was observed in the mixed antibiotic than in the single antibiotic batch cultures. Biodegradation was the main antibiotic removal mechanism with a similar antibiotic biosorption pattern in single and mix antibiotic cultures. Scanning electron microscopy and Fourier transform infrared spectrophotometry showed minor biochemical alterations on algal cells surface and a stable algal population. Monod kinetics model was successfully applied to understand the growth with respect to the removal efficiency of C. vulgaris in single and mix antibiotic batch cultures. Results indicated relatively higher specific growth rate in the mix antibiotic batch culture with removal efficiency in the order of SMX > LEV > TMP > AZI. In total, 46 metabolites with 18 novel ones of the four antibiotics were identified by using high-resolution mass spectrometry based on the suspect screening approach to propose the potential transformation pathways. Most of the transformation products demonstrated lower toxicity than their respective parents. These findings implied that C. vulgaris could be an outstanding candidate for advanced treatment of antibiotic removal in wastewater.