STAIBT: Blockchain and CP-ABE Empowered Secure and Trusted Agricultural IoT Blockchain Terminal

The integration of agricultural Internet of Things (IoT) and blockchain has become the key technology of precision agriculture. How to protect data privacy and security from data source is one of the difficult issues in agricultural IoT research. This work integrates cryptography, blockchain and Interplanetary File System (IPFS) technologies, and proposes a general IoT blockchain terminal system architecture, which strongly supports the integration of the IoT and blockchain technology. This research innovatively designed a fine-grained and flexible terminal data access control scheme based on the ciphertext-policy attribute-based encryption (CP-ABE) algorithm. Based on CP-ABE and DES algorithms, a hybrid data encryption scheme is designed to realize 1-to-N encrypted data sharing. A "horizontal + vertical" IoT data segmentation scheme under blockchain technology is proposed to realize the classified release of different types of data on the blockchain. The experimental results show that the design scheme can ensure data access control security, privacy data confidentiality, and data high-availability security. This solution significantly reduces the complexity of key management, can realize efficient sharing of encrypted data, flexibly set access control strategies, and has the ability to store large data files in the agricultural IoT

Analysis of Differentially Expressed Proteins in Self-Paired Sera of Advanced Non-small Cell Lung Cancer Patients Responsive to Gefin

Background and objective All the advanced NSCLC patients that received EGFR-TKI therapy will eventually relapse after a period of efficacy. The aim of this study is to investigate the serum biomarkers as potential predictive factors for the efficacy of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) targeted therapy in advanced non-small cell lung cancer. Methods Twenty self-paired serum samples were collected from 9 advanced NSCLC patients that evaluated as disease control (SD or PR) after gefinitib therapy, at the time points of before and after gefinitib treatment but 2 weeks before being evaluated as disease progress. All samples were pre-separated by WCX microbeads, and then detected on the MALDI-TOF-MS platform of Bruker AutoflexTM. ClinProTools (Version: 2.1) was used to analyze the differentially expressed proteins. Results There were 7 protein peaks (m/z), 3242.09, 8 690.36, 2 952.64, 3 224.04, 1 450.51, 1 887.8 and 3 935.73 found statistically differentially expressed between the self-paired samples. Three proteins (3 242.09, 2 952.64 and 3 224.04) were down-regulated and four proteins (8 690.36, 1 450.51, 1 887.8 and 3 935.73) up-regulated in gefinitib treated sera. Conclusion The data here suggest that several specific protein peaks might indicate gefinitib resistance, yet the identities of these proteins and the mechanisms underlying the responsiveness to gefinitib treatment need further investigation

Effective noninvasive zygosity determination by maternal plasma target region sequencing

Background: Currently very few noninvasive molecular genetic approaches are available to determine zygosity for twin pregnancies in clinical laboratories. This study aimed to develop a novel method to determine zygosity by using maternal plasma target region sequencing. Methods: We constructed a statistic model to calculate the possibility of each zygosity type using likelihood ratios (Li) and empirical dynamic thresholds targeting at 4,524 single nucleotide polymorphisms (SNPs) loci on 22 autosomes. Then two dizygotic (DZ) twin pregnancies, two monozygotic (MZ) twin pregnancies and two singletons were recruited to evaluate the performance of our novel method. Finally we estimated the sensitivity and specificity of the model in silico under different cell-free fetal DNA (cff-DNA) concentration and sequence depth. Results/Conclusions: We obtained 8.90 Gbp sequencing data on average for six clinical samples. Two samples were classified as DZ with L values of 1.891 and 1.554, higher than the dynamic DZ cut-off values of 1.162 and 1.172, respectively. Another two samples were judged as MZ with 0.763 and 0.784 of L values, lower than the MZ cut-off values of 0.903 and 0.918. And the rest two singleton samples were regarded as MZ twins, with L values of 0.639 and 0.757, lower than the MZ cut-off values of 0.921 and 0.799. In silico, the estimated sensitivity of our noninvasive zygosity determination was 99.90% under 10% total cff-DNA concentration with 2 Gbp sequence data. As the cff-DNA concentration increased to 15%, the specificity was as high as 97% with 3.50 Gbp sequence data, much higher than 80% with 10% cff-DNA concentration. Significance: This study presents the feasibility to noninvasively determine zygosity of twin pregnancy using target region sequencing, and illustrates the sensitivity and specificity under various detecting condition. Our method can act as an alternative approach for zygosity determination of twin pregnancies in clinical practice.Multidisciplinary SciencesSCI(E)2ARTICLE6null

ACE-ADP: Adversarial Contextual Embeddings Based Named Entity Recognition for Agricultural Diseases and Pests

Entity recognition tasks, which aim to utilize the deep learning-based models to identify the agricultural diseases and pests-related nouns such as the names of diseases, pests, and drugs from the texts collected on the internet or input by users, are a fundamental component for agricultural knowledge graph construction and question-answering, which will be implemented as a web application and provide the general public with solutions for agricultural diseases and pest control. Nonetheless, there are still challenges: (1) the polysemous problem needs to be further solved, (2) the quality of the text representation needs to be further enhanced, (3) the performance for rare entities needs to be further improved. We proposed an adversarial contextual embeddings-based model named ACE-ADP for named entity recognition in Chinese agricultural diseases and pests domain (CNER-ADP). First, we enhanced the text representation and overcame the polysemy problem by using the fine-tuned BERT model to generate the contextual character-level embedded representation with the specific knowledge. Second, adversarial training was also introduced to enhance the generalization and robustness in terms of identifying the rare entities. The experimental results showed that our model achieved an F1 of 98.31% with 4.23% relative improvement compared to the baseline model (i.e., word2vec-based BiLSTM-CRF) on the self-annotated corpus named Chinese named entity recognition dataset for agricultural diseases and pests (AgCNER). Besides, the ablation study and discussion demonstrated that ACE-ADP could not only effectively extract rare entities but also maintain a powerful ability to predict new entities in new datasets with high accuracy. It could be used as a basis for further research on other domain-specific named entity recognition

Intratumoral heterogeneity of EGFR-activating mutations in advanced NSCLC patients at the single-cell level

Abstract Background Intratumoral epidermal growth factor receptor (EGFR) mutational heterogeneity is yet controversial in non-small cell lung cancer (NSCLC) patients. Single-cell analysis provides the genetic profile of single cancer cells and an in-depth understanding of the heterogeneity of a tumor. Methods Firstly, single H1975 cells harboring the EGFR L858R mutation were submitted to flow cytometry isolation, nested polymerase chain reaction (nested-PCR) amplification, and direct DNA sequencing to assess the feasibility of single-cell direct DNA sequencing. Then, the single cells of patients with lung adenocarcinoma receiving gefitinib were captured by laser capture microdissection and analyzed by the above methods to identify the intratumoral heterogeneity of the EGFR L858R mutant. Three patients with progression-free survival (PFS) > 14 months were categorized as the long PFS group, and 3 patients with PFS < 6 months as the short PFS group. The correlation between the abundance of EGFR L858R mutant and PFS was analyzed. Results 104 single H1975 cells were isolated. 100/104 were amplified by nested-PCR and confirmed by direct sequencing. We captured 135 tumor cells from the tissues of six patients. 120 single tumor cells were successfully amplified and sequenced. The rate of EGFR exon 21 mutation was only 77.5% (93/120). Furthermore, the rate of mutation in exon 21 of EGFR was significantly higher in the long PFS group than in the short PFS group (86.4 ± 4.9% vs. 68.9 ± 2.8%, P = 0.021). Conclusion Our study suggested the intratumoral heterogeneity of EGFR-activating mutations in lung adenocarcinoma confirmed on the single-cell level, which might be associated with EGFR-TKIs response in lung adenocarcinoma patients harboring the EGFR L858R mutation

High Resolution Melting Analysis for Detecting p53 Gene Mutations in Patients with Non-small Cell Lung Cancer

Background and objective It has been proven that p53 gene was related to many human cancers. The mutations in p53 gene play an important role in carcinogensis and mostly happened in exon 5-8. The aim of this study is to establish a high resolution melting (HRM) assay to detect p53 mutations from patients with non-small cell lung cancer (NSCLC), to investigate the characteristics of p53 gene mutations, and to analyze the relationship between p53 mutations and evolution regularity of pathogenesis. Methods p53 mutations in exon 5-8 were detected by HRM assay on DNA insolated from 264 NSCLC samples derived from tumor tissues and 54 control samples from pericancerous pulmonary tissues. The mutation samples by the HRM assay were confirmed by sequencing technique. Samples which were positive by HRM but wild type by sequencing were further confirmed by sub-clone and sequencing. Results No mutation was found in 54 pericancerous pulmonary samples by HRM assay. 104 of the 264 tumor tissues demonstrated mutation curves by HRM assay, 102 samples were confirmed by sequencing, including 95 point mutations and 7 frame shift mutations by insertion or deletion. The mutation rate of p53 gene was 39.4%. The mutation rate from exon 5-8 were 11.7%, 8%, 12.5% and 10.6%, respectively and there was no statistically significant difference between them (P=0.35). p53 mutations were significantly more frequent in males than that in females, but not related to the other clinicopathologic characteristics. Conclusion The results indicate that HRM is a sensitive in-tube methodology to detect for mutations in clinical samples. The results suggest that the arising p53 mutations in NSCLC may be due to spontaneous error in DNA synthesis and repair

Detection of UGT1A1*28 Polymorphism Using Fragment Analysis

Background and objective Uridine-diphosphoglucuronosyl transferase 1A1 (UGT1A1), UGT1A1*28 polymorphism can reduce UGT1A1 enzymatic activity, which may lead to severe toxicities in patients who receive irinotecan. This study tries to build a fragment analysis method to detect UGT1A1*28 polymorphism. Methods A total of 286 blood specimens from the lung cancer patients who were hospitalized in Guangdong General Hospital between April 2014 to May 2015 were detected UGT1A1*28 polymorphism by fragment analysis method. Results Comparing with Sanger sequencing, precision and accuracy of the fragment analysis method were 100%. Of the 286 patients, 236 (82.5% harbored TA6/6 genotype, 48 (16.8%) TA 6/7 genotype and 2 (0.7%) TA7/7 genotype. Conclusion Our data suggest hat the fragment analysis method is robust for detecting UGT1A1*28 polymorphism in clinical practice. It’s simple, time-saving, and easy-to-carry

Simple Is Best: A p-Phenylene Bridging Methoxydiphenylamine-Substituted Carbazole Hole Transporter for High-Performance Perovskite Solar Cells

Methoxydiphenylamine-substituted carbazole (MODPACz) is widely used to construct hole-transporting materials (HTMs) for perovskite solar cells (PSCs), whose performances rely highly on the linking way of the MODPACz units and the simplicity of the pi-bridge. In this paper, we report a new HTM, pPh-2MODPACz, using one of the simplest pi-bridges p-phenylene to link the MODPACz units. The structural feature endows pPh-2MODPACz with high hole mobility and conductivity, efficient hole extraction ability, and good film-forming property. MAPbI(3)-based PSCs using doped and undoped pPh-2MODPACz as the HTM offer efficiencies of similar to 20% and 16.07%, respectively; both are better than those of the devices with spiro-OMeTAD as the HTM. The device stability of pPh-2MODPACz-based PSCs is also greatly enhanced. This work demonstrates that the simplest p-phenylene bridge for linking MODPACz can derive a promising HTM with a high device performance, providing a distinctive pathway to develop new HTMs

Detection of Epidermal Growth Factor Receptor Mutations in Non-small Cell Lung Cancer Tumor Specimens from Various Ways by Denaturing High-performance Liquid Chromatography

Background and objective Epidermal growth factor receptor (EGFR) is the most important therapeutic target in non-small cell lung cancer (NSCLC). EGFR mutations may predict responsiveness to tyrosine kinase inhibitors (TKIs). These mutations are commonly identified using direct sequencing, which is considered the gold standard. But direct sequencing is time-consuming and hyposensitive. In addition, this method requires a lot of tumor specimens. Denaturing highperformance liquid chromatography (DHPLC) is a rapid automated sensitive and specific method in mutant gene detection. The aim of this study is to evaluate DHPLC as a rapid detection method for EGFR mutations in NSCLC tumor specimens. Methods DHPLC was used to evaluate the accuracy and sensitivity of detection the serial dilutions of mutant and wild type EGFR plasma DNA. Frozen tumor specimens of 83 NSCLC patients from various ways had been included, after DNA extraction and polymerase chain reaction (PCR) on EGFR exon 19 and 21, the results from the direct sequencing and DHPLC were compared. Results Mutant plasma DNA can be detected in the serial dilution of 1:100 by DHPLC and 1:10 by direct sequencing respectively. The results from DHPLC showed 22 EGFR mutations were detected in 83 NSCLC patients, and only 19 mutation samples had been conformed by direct sequencing. Moreover, the other 61 samples were deemed as wild type by DHPLC and direct sequencing. The sensitivity and specificity of DHPLC was 100% and 95.13% respectively. The detection of the tumor specimens from CT-guided transthoracic needle lung biopsy, lymph node biopsy and surgical resection all showed high sensitivity and specificity. EGFR mutation has strong correlation with gender and pathologic type, but irrelevant to age and smoking status. Conclusion DHPLC was a precise rapid preliminary screening method for detection of NSCLC EGFR genotype