LSTM-TrajGAN: A Deep Learning Approach to Trajectory Privacy Protection

The prevalence of location-based services contributes to the explosive growth of individual-level trajectory data and raises public concerns about privacy issues. In this research, we propose a novel LSTM-TrajGAN approach, which is an end-to-end deep learning model to generate privacy-preserving synthetic trajectory data for data sharing and publication. We design a loss metric function TrajLoss to measure the trajectory similarity losses for model training and optimization. The model is evaluated on the trajectory-user-linking task on a real-world semantic trajectory dataset. Compared with other common geomasking methods, our model can better prevent users from being re-identified, and it also preserves essential spatial, temporal, and thematic characteristics of the real trajectory data. The model better balances the effectiveness of trajectory privacy protection and the utility for spatial and temporal analyses, which offers new insights into the GeoAI-powered privacy protection

Exploring the effectiveness of geomasking techniques for protecting the geoprivacy of Twitter users

With the ubiquitous use of location-based services, large-scale individual-level location data has been widely collected through location-awareness devices. Geoprivacy concerns arise on the issues of user identity de-anonymization and location exposure. In this work, we investigate the effectiveness of geomasking techniques for protecting the geoprivacy of active Twitter users who frequently share geotagged tweets in their home and work locations. By analyzing over 38,000 geotagged tweets of 93 active Twitter users in three U.S. cities, the two-dimensional Gaussian masking technique with proper standard deviation settings is found to be more effective to protect user\u27s location privacy while sacrificing geospatial analytical resolution than the random perturbation masking method and the aggregation on traffic analysis zones. Furthermore, a three-dimensional theoretical framework considering privacy, analytics, and uncertainty factors simultaneously is proposed to assess geomasking techniques. Our research offers insights into geoprivacy concerns of social media users\u27 georeferenced data sharing for future development of location-based applications and services

Aflatoxin B1-DNA adducts modify the effects of post-operative adjuvant transarterial chemoembolization improving hepatocellular carcinoma prognosis

Aim: DNA damage involves in the carcinogenesis of some cancer and may act as a target for therapeutic intervention of cancers. However, it is unclear whether aflatoxin B1 (AFB1)-DNA adducts (ADAs), an important kind of DNA damage caused by AFB1, affect the efficiency of post-operative adjuvant transarterial chemoembolization (po-TACE) treatment improving hepatocellular carcinoma (HCC) survival. Methods: A hospital-based retrospective study, including 318 patients with Barcelona Clinic Liver Cancer (BCLC)-C stage HCC from high AFB1 exposure areas, to investigate the potential effects of ADAs in the tissues with HCC on po-TACE treatment. The amount of ADAs in the cancerous tissues was tested by competitive enzyme-linked immunosorbent assay (c-ELISA). Results: Among these patients with HCC, the average amount of ADAs was 3.00 µmol/mol ± 1.51 µmol/mol DNA in their tissues with cancer. For these patients, increasing amount of ADAs was significantly associated with poorer overall survival (OS) and tumor reoccurrence-free survival (RFS), with corresponding death risk (DR) of 3.69 (2.78–4.91) and tumor recurrence risk (TRR) of 2.95 (2.24–3.88). The po-TACE therapy can efficiently improve their prognosis [DR = 0.59 (0.46–0.76), TRR = 0.63 (0.49–0.82)]. Interestingly, this improving role was more noticeable among these patients with high ADAs [DR = 0.36 (0.24–0.53), TRR = 0.40 (0.28–0.59)], but not among those with low ADAs (P > 0.05). Conclusions: These results suggest that increasing ADAs in the cancerous tissues may be beneficial for po-TACE in ameliorating the survival of patients with HCC

Identification of genes related to the development of bamboo rhizome bud

Bamboo (Phyllostachys praecox) is one of the largest members of the grass family Poaceae, and is one of the most economically important crops in Asia. However, complete knowledge of bamboo development and its molecular mechanisms is still lacking. In the present study, the differences in anatomical structure among rhizome buds, rhizome shoots, and bamboo shoots were compared, and several genes related to the development of the bamboo rhizome bud were identified. The rice cross-species microarray hybridization showed a total of 318 up-regulated and 339 down-regulated genes, including those involved in regulation and signalling, metabolism, and stress, and also cell wall-related genes, in the bamboo rhizome buds versus the leaves. By referring to the functional dissection of the homologous genes from Arabidopsis and rice, the putative functions of the 52 up-regulated genes in the bamboo rhizome bud were described. Six genes related to the development of the bamboo rhizome bud were further cloned and sequenced. These show 66–90% nucleotide identity and 68–98% amino acid identity with the homologous rice genes. The expression patterns of these genes revealed significant differences in rhizome shoots, rhizome buds, bamboo shoots, leaves, and young florets. Furthermore, in situ hybridization showed that the PpRLK1 gene is expressed in the procambium and is closely related to meristem development of bamboo shoots. The PpHB1 gene is expressed at the tips of bamboo shoots and procambium, and is closely related to rhizome bud formation and procambial development. To our knowledge, this is the first report that uses rice cross-species hybridization to identify genes related to bamboo rhizome bud development, and thereby contributes to the further understanding of the molecular mechanism involved in bamboo rhizome bud development

The association of two single nucleotide polymorphisms (SNPs) in growth hormone (GH) gene with litter size and superovulation response in goat-breeds

Two active mutations (A 781 G and A 1575 G) in growth hormone (GH) gene, and their associations with litter size (LS), were investigated in both a high prolificacy (Matou, n = 182) and a low prolificacy breed (Boer, n = 352) by using the PCR-RFLP method. Superovulation experiments were designed in 57 dams, in order to evaluate the effect of different genotypes of the GH gene on superovulation response. Two genotypes (AA and AB, CC and CD) in each mutation were detected in these two goat breeds. Neither BB nor DD homozygous genotypes were observed. The genotypic frequencies of AB and CC were significantly higher than those of AA and CD. In the third parity, Matou dams with AB or CC genotypes had significantly larger litter sizes than those with AA and CD (p < 0.05). On combining the two loci, both Matou and Boer dams with ABCD genotype had the largest litter sizes when compared to the other genotypes (p < 0.05). When undergoing like superovulation treatments, a significantly higher number of corpora lutea and ova, with a lower incidence of ovarian cysts, were harvested in the AB and CC genotypes than in AA and CD. These results show that the two loci of GH gene are highly associated with abundant prolificacy and superovulation response in goat breeds