TREC: APT Tactic / Technique Recognition via Few-Shot Provenance Subgraph Learning

APT (Advanced Persistent Threat) with the characteristics of persistence, stealth, and diversity is one of the greatest threats against cyber-infrastructure. As a countermeasure, existing studies leverage provenance graphs to capture the complex relations between system entities in a host for effective APT detection. In addition to detecting single attack events as most existing work does, understanding the tactics / techniques (e.g., Kill-Chain, ATT&CK) applied to organize and accomplish the APT attack campaign is more important for security operations. Existing studies try to manually design a set of rules to map low-level system events to high-level APT tactics / techniques. However, the rule based methods are coarse-grained and lack generalization ability, thus they can only recognize APT tactics and cannot identify fine-grained APT techniques and mutant APT attacks. In this paper, we propose TREC, the first attempt to recognize APT tactics / techniques from provenance graphs by exploiting deep learning techniques. To address the "needle in a haystack" problem, TREC segments small and compact subgraphs covering individual APT technique instances from a large provenance graph based on a malicious node detection model and a subgraph sampling algorithm. To address the "training sample scarcity" problem, TREC trains the APT tactic / technique recognition model in a few-shot learning manner by adopting a Siamese neural network. We evaluate TREC based on a customized dataset collected and made public by our team. The experiment results show that TREC significantly outperforms state-of-the-art systems in APT tactic recognition and TREC can also effectively identify APT techniques

Identification and validation of biomarkers for epithelial-mesenchymal transition-related cells to estimate the prognosis and immune microenvironment in primary gastric cancer by the integrated analysis of single-cell and bulk RNA sequencing data

Background: The epithelial-mesenchymal transition (EMT) is associated with gastric cancer (GC) progression and immune microenvironment. To better understand the heterogeneity underlying EMT, we integrated single-cell RNA-sequencing (scRNA-seq) data and bulk sequencing data from GC patients to evaluate the prognostic utility of biomarkers for EMT-related cells (ERCs), namely, cancer-associated fibroblasts (CAFs) and epithelial cells (ECs). Methods: scRNA-seq data from primary GC tumor samples were obtained from the Gene Expression Omnibus (GEO) database to identify ERC marker genes. Bulk GC datasets from the Cancer Genome Atlas (TCGA) and GEO were used as training and validation sets, respectively. Differentially expressed markers were identified from the TCGA database. Univariate Cox, least-absolute shrinkage, and selection operator regression analyses were performed to identify EMT-related cell-prognostic genes (ERCPGs). Kaplan-Meier, Cox regression, and receiver-operating characteristic (ROC) curve analyses were adopted to evaluate the prognostic utility of the ERCPG signature. An ERCPG-based nomogram was constructed by integrating independent prognostic factors. Finally, we evaluated the correlations between the ERCPG signature and immune-cell infiltration and verified the expression of ERCPG prognostic signature genes by in vitro cellular assays. Results: The ERCPG signature was comprised of seven genes (COL4A1, F2R, MMP11, CAV1, VCAN, FKBP10, and APOD). Patients were divided into high- and low-risk groups based on the ERCPG risk scores. Patients in the high-risk group showed a poor prognosis. ROC and calibration curves suggested that the ERCPG signature and nomogram had a good prognostic utility. An immune cell-infiltration analysis suggested that the abnormal expression of ERCPGs induced the formation of an unfavorable tumor immune microenvironment. In vitro cellular assays showed that ERCPGs were more abundantly expressed in GC cell lines compared to normal gastric tissue cell lines. Conclusions: We constructed and validated an ERCPG signature using scRNA-seq and bulk sequencing data from ERCs of GC patients. Our findings support the estimation of patient prognosis and tumor treatment in future clinical practice

Long-term exposure to PM\u3csub\u3e2.5\u3c/sub\u3e and incidence of disability in activities of daily living among oldest old

Currently the Chinese government has adopted World Health Organization interim target-1 values as the national ambient air quality standards values. However, the population-based evidence was insufficient, especially for the oldest old (aged 80+). We evaluated the association of fine particulate matters (PM2.5) exposure and incidence of disability in activities of daily living (ADL) in 15 453 oldest old in 886 counties/cities in China from 2002 to 2014 using Cox model with penalized splines and competing risk models to evaluate the linear or non-linear association. After adjusting for potential confounders, a J-shaped association existed between PM2.5 exposure with a threshold concentration of 33 μg/m3, and incident disability in ADL. Above this threshold, the risk magnitude significantly increased with increase of PM2.5 concentrations; compared to 33 μg/m3, the hazard ratio ranged from 1.03 (1.00–1.06) at 40 μg/m3 to 2.25 (1.54–3.29) at 110 μg/m3. The risk magnitude was not significantly changed below this threshold. Each 10 μg/m3 increase in PM2.5 exposure corresponded to a 7.7% increase in the risk of disability in ADL (hazard ratio 1.077, 95% CI 1.051–1.104). Men, smokers, and participants with cognitive impairment might be more vulnerable to PM2.5 exposure. The study provided limited population-based evidence for the oldest old and detected a threshold of 33 μg/m3, and supported that reduction to current World Health Organization interim target-1value (35 μg/m3) and Chinese national ambient air quality standards (35 μg/m3) or lower may be associated with lower risk of disability in ADL

Highly stable Zn anodes realized by 3D zincophilic and hydrophobic interphase buffer layer

Aqueous zinc-ion batteries (AZIBs) are promising contenders for energy storage systems owing to their low cost and high safety. However, their practical application is hindered by uncontrolled Zn dendrites and other side reactions. Here, the three-dimensional (3D) TiO2/Cu2Se/C heterostructure layer derived from MXene/Cu-MOF is constructed on the Zn anode to control the deposition/dissolution behavior, which has numerous active sites, better electrical conductivity and excellent structural stability. Based on DFT calculation, the built-in electric field (BIEF) formed of TiO2/Cu2Se/C can enhance charge transfer and ionic diffusion to inhibit the dendrites. Furthermore, hydrophobic coating has the ability to impede the corrosion and hydrogen evolution reaction (HER) of zinc anode. Thus, TiO2/Cu2Se/C@Zn enable the stable and reversible Zn plating/stripping process with the outstanding lifetime of 1100 h at 2 mA·cm–2 and even 650 h at 10 mA·cm–2. The batteries constructed with commercial MnO2 cathodes demonstrate the remarkable capacity (248.7 mAh·g−1 at 0.1 A·g−1) and impressive cycle stability (with 71.3% capacity retention after 300 cycles). As well as extending the life of AZIBs, this study is also motivating for other metal anode based secondary batteries

Long-term exposure to ambient fine particulate matter and fasting blood glucose level in a Chinese elderly cohort

Fasting blood glucose level is the primary indicator for the diagnosis of diabetes. We aim to conduct a longitudinal study on the association between long-term fine particulate matter (PM2.5) exposure and fasting blood glucose concentrations. We recruited and followed up 1449 participants older than 65 years of age in 2009, 2012, 2014, and 2017 in eight counties in China. Fasting blood glucose was repeatedly measured 3697 times in total among these participants. Data on annual ground-level PM2.5 concentrations with a 0.01° spatial resolution from 2005 to 2016 were used to assess exposures. An increase of 10 μg/m3 in 3-year average exposure to PM2.5 was associated with an increase of 0.146 mmol/L (95% confidence interval [CI]: 0.045, 0.248) in fasting blood glucose in all participants. The association was more pronounced among the subgroup with diabetes compared to the subgroup without diabetes (P < .05). In conclusion, Long-term PM2.5 exposure was associated with an increase in fasting blood glucose levels among elderly people. Elderly individuals with diabetes are particularly vulnerable to high level exposures of PM2.5. SUMMARY: Long-term PM2.5 exposure was associated with an increase in fasting blood glucose levels among elderly people. Elderly individuals with diabetes are particularly vulnerable to high level exposures of PM2.5. Keywords: elderly; fasting blood glucose; fine particulate matter; long-term exposur

Fibroblast Growth Factor 1 Promotes Rat Stem Leydig Cell Development

Fibroblast growth factor 1 (FGF1) is reported to be expressed in the testis. How FGF1 affects stem Leydig cell development remains unclear. Here, we report the effects of FGF1 on rat stem Leydig cell development in an ethane dimethane sulfonate (EDS)-treated model. FGF1 (100 ng/testis) significantly increased serum testosterone level, increased PCNA-positive Leydig cell percentage and Leydig cell number, but down-regulated the expression of Lhcgr, Star, Cyp11a1, Hsd3b1, Cyp17a1, and Hsd11b1 in Leydig cells per se, after its daily intratesticular injection from post-EDS day 14 for 14 days. Primary culture of the seminiferous tubules showed that FGF1 stimulated EdU incorporation to stem Leydig cells but blocked the differentiation into the Leydig cell lineage, possibly via FGFR1-mediated mechanism. In conclusion, FGF1 promotes stem Leydig cell proliferation but blocks its differentiation

A high-resolution study of particle export in the southern South China Sea based on Th-234 : U-238 disequilibrium

During a spring intermonsoon cruise in 2004, depth profiles of total and particulate Th-234 in the upper 100 m were collected at 36 stations in the southern South China Sea (SCS), covering a surface area of similar to 1.0 x 10(6) km(2). Thorium-234 was sampled by using a modified small-volume MnO2 co-precipitation technique, which allows mapping the Th-234 distribution with a high spatial resolution. A stratified structure of Th-234/U-238 disequilibria was generally observed in the upper 100 m water column, suggesting that the euphotic zone of the southern SCS in this season can be separated into two layers: an upper layer with low export production rates and a lower layer with high export production rates. At the same time, we observed extensive zones of Th-234 excess within the euphotic layer, which is possibly due to intense remineralization of particulate matter. Particulate organic carbon (POC) export was estimated from a three-dimensional steady state model of Th-234 fluxes combined with measurements of the POC/Th-234 ratio on suspended particles. The POC export for this region varied from a low of -10.7 +/- 1.5 mmolC m(-2) d(-1) to a high of 12.6 +/- 1.1 mmolC m(-2) d(-1), with an average of 3.8 +/- 4.0 mmolC m(-2) d(-1). A negative flux of POC export is interpreted as the result of lateral input of particulate matter from nearby waters. Regional patterns in POC export show enhanced fluxes along the western and southern boundaries of the study region, and a "tongue'' of low export extending northwestward from similar to 7 degrees N 116 degrees E to similar to 10 degrees N 111 degrees E. This geographic distribution is consistent with the overall surface circulation pattern of the southern SCS in this season