Oil-recovery performance of a superhydrophobic sponge-covered disc skimmer.

Frequent oil spill accidents caused by transportation, storage and usage may lead to severe damage on aquatic and ecological environments. Effective methods for rapid oil recovery are urgently in demand. Polyvinyl chloride, hydrophobic nano-SiO2, expanded graphite were separately applied to polyurethane and melamine sponge to fabricate superhydrophobic sponge material. The selected superhydrophobic sponge was introduced to establish sponge - covered disc skimmer. Oil recovery tests of the device were conducted to determine the optimum parameters. The examined operating conditions encompassed sponge thickness, immersion depth, rotational speed, oil slick thickness, operation time. The results showed that the melamine sponge modified by both polyvinyl chloride and hydrophobic nano-SiO2 exhibits super-hydrophobicity with a water contact angle of 150.3°. The absorption capacity for diesel oil can reach 53.89 g/g. The absorption capacity can still achieve 90 % of its initial capacity even after 500 extrusion-absorption separation tests. The results indicate the superiority of the superhydrophobic sponge covered surface in oil recovery over the standard steel surface regardless of the operating conditions. The recovery rate of the device can still achieve 96.4 % of its initial capacity with 95 % efficiency even after 85 h operation. The results suggest the superhydrophobic sponge - covered disc skimmer may have great application perspectives in oil spill recovery.

In-depth metaproteomics analysis of tongue coating for gastric cancer: a multicenter diagnostic research study.

BACKGROUND: Our previous study revealed marked differences in tongue images between individuals with gastric cancer and those without gastric cancer. However, the biological mechanism of tongue images as a disease indicator remains unclear. Tongue coating, a major factor in tongue appearance, is the visible layer on the tongue dorsum that provides a vital environment for oral microorganisms. While oral microorganisms are associated with gastric and intestinal diseases, the comprehensive function profiles of oral microbiota remain incompletely understood. Metaproteomics has unique strength in revealing functional profiles of microbiota that aid in comprehending the mechanism behind specific tongue coating formation and its role as an indicator of gastric cancer. METHODS: We employed pressure cycling technology and data-independent acquisition (PCT-DIA) mass spectrometry to extract and identify tongue-coating proteins from 180 gastric cancer patients and 185 non-gastric cancer patients across 5 independent research centers in China. Additionally, we investigated the temporal stability of tongue-coating proteins based on a time-series cohort. Finally, we constructed a machine learning model using the stochastic gradient boosting algorithm to identify individuals at high risk of gastric cancer based on tongue-coating microbial proteins. RESULTS: We measured 1432 human-derived proteins and 13,780 microbial proteins from 345 tongue-coating samples. The abundance of tongue-coating proteins exhibited high temporal stability within an individual. Notably, we observed the downregulation of human keratins KRT2 and KRT9 on the tongue surface, as well as the downregulation of ABC transporter COG1136 in microbiota, in gastric cancer patients. This suggests a decline in the defense capacity of the lingual mucosa. Finally, we established a machine learning model that employs 50 microbial proteins of tongue coating to identify individuals at a high risk of gastric cancer, achieving an area under the curve (AUC) of 0.91 in the independent validation cohort. CONCLUSIONS: We characterized the alterations in tongue-coating proteins among gastric cancer patients and constructed a gastric cancer screening model based on microbial-derived tongue-coating proteins. Tongue-coating proteins are shown as a promising indicator for identifying high-risk groups for gastric cancer. Video Abstract.

Highly Transparent, Temperature-Resistant, and Flexible Polyimide Aerogels for Solar Energy Collection.

Advanced aerogel materials with low thermal conductivity and high transparency have shown great application prospects in the solar thermal energy conversion field. However, most aerogels do not meet these requirements due to their low optical transparency and poor mechanical properties. To tackle this problem, we have created versatile polyimide (PI) aerogel materials by adjusting the monomers to alter their molecular structure. These materials exhibit exceptional thermal insulation properties and high transparency, making them ideal for use in the construction of efficient solar collector devices. Incorporating 1,3,5-benzenetricarbonyl trichloride into PI aerogel results in high strength (>3 MPa) and excellent transmittance (>90%) over a broad range of wavelengths (500-2650 nm). The as-prepared PI aerogel solar collector (PIASC) also exhibits a low thermal conductivity (0.032 W/mK), a low density (0.1 g/cm3), and high porosity (90%). By changing the shape of the collector from a flat plate to a cylindrical ring, the heat collection efficiency and capacity are significantly improved, resulting in efficient heat collection. The circular ring collector has a maximum heat collection temperature of 236.8 °C. The PIASC, which is both flexible and highly transparent, is an ideal candidate for advanced optical elements and solar collectors.

Deep learning radio-clinical signatures for predicting neoadjuvant chemotherapy response and prognosis from pretreatment CT images of locally advanced gastric cancer patients.

BACKGROUND: Early noninvasive screening of patients who would benefit from neoadjuvant chemotherapy (NCT) is essential for personalized treatment of locally advanced gastric cancer (LAGC). The aim of this study was to identify radio-clinical signatures from pretreatment oversampled computed tomography (CT) images to predict the response to NCT and prognosis of LAGC patients. METHODS: LAGC patients were retrospectively recruited from six hospitals from January 2008 to December 2021. An SE-ResNet50-based chemotherapy response prediction system was developed from pretreatment CT images preprocessed with an imaging oversampling method (i.e. DeepSMOTE). Then, the deep learning (DL) signature and clinic-based features were fed into the deep learning radio-clinical signature (DLCS). The predictive performance of the model was evaluated based on discrimination, calibration, and clinical usefulness. An additional model was built to predict overall survival (OS) and explore the survival benefit of the proposed DL signature and clinicopathological characteristics. RESULTS: A total of 1060 LAGC patients were recruited from six hospitals; the training cohort (TC) and internal validation cohort (IVC) patients were randomly selected from center I. An external validation cohort (EVC) of 265 patients from five other centers was also included. The DLCS exhibited excellent performance in predicting the response to NCT in the IVC [area under the curve (AUC), 0.86] and EVC (AUC, 0.82), with good calibration in all cohorts ( P >0.05). Moreover, the DLCS model outperformed the clinical model ( P <0.05). Additionally, we found that the DL signature could serve as an independent factor for prognosis [hazard ratio (HR), 0.828, P =0.004]. The concordance index (C-index), integrated area under the time-dependent ROC curve (iAUC), and integrated Brier score (IBS) for the OS model were 0.64, 1.24, and 0.71 in the test set. CONCLUSION: The authors proposed a DLCS model that combined imaging features with clinical risk factors to accurately predict tumor response and identify the risk of OS in LAGC patients prior to NCT, which can then be used to guide personalized treatment plans with the help of computerized tumor-level characterization.

Development of a tongue image-based machine learning tool for the diagnosis of gastric cancer: a prospective multicentre clinical cohort study.

Background: Tongue images (the colour, size and shape of the tongue and the colour, thickness and moisture content of the tongue coating), reflecting the health state of the whole body according to the theory of traditional Chinese medicine (TCM), have been widely used in China for thousands of years. Herein, we investigated the value of tongue images and the tongue coating microbiome in the diagnosis of gastric cancer (GC). Methods: From May 2020 to January 2021, we simultaneously collected tongue images and tongue coating samples from 328 patients with GC (all newly diagnosed with GC) and 304 non-gastric cancer (NGC) participants in China, and 16 S rDNA was used to characterize the microbiome of the tongue coating samples. Then, artificial intelligence (AI) deep learning models were established to evaluate the value of tongue images and the tongue coating microbiome in the diagnosis of GC. Considering that tongue imaging is more convenient and economical as a diagnostic tool, we further conducted a prospective multicentre clinical study from May 2020 to March 2022 in China and recruited 937 patients with GC and 1911 participants with NGC from 10 centres across China to further evaluate the role of tongue images in the diagnosis of GC. Moreover, we verified this approach in another independent external validation cohort that included 294 patients with GC and 521 participants with NGC from 7 centres. This study is registered at ClinicalTrials.gov, NCT01090362. Findings: For the first time, we found that both tongue images and the tongue coating microbiome can be used as tools for the diagnosis of GC, and the area under the curve (AUC) value of the tongue image-based diagnostic model was 0.89. The AUC values of the tongue coating microbiome-based model reached 0.94 using genus data and 0.95 using species data. The results of the prospective multicentre clinical study showed that the AUC values of the three tongue image-based models for GCs reached 0.88-0.92 in the internal verification and 0.83-0.88 in the independent external verification, which were significantly superior to the combination of eight blood biomarkers. Interpretation: Our results suggest that tongue images can be used as a stable method for GC diagnosis and are significantly superior to conventional blood biomarkers. The three kinds of tongue image-based AI deep learning diagnostic models that we developed can be used to adequately distinguish patients with GC from participants with NGC, even early GC and precancerous lesions, such as atrophic gastritis (AG). Funding: The National Key R&D Program of China (2021YFA0910100), Program of Zhejiang Provincial TCM Sci-tech Plan (2018ZY006), Medical Science and Technology Project of Zhejiang Province (2022KY114, WKJ-ZJ-2104), Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer (JBZX-202006), Natural Science Foundation of Zhejiang Province (HDMY22H160008), Science and Technology Projects of Zhejiang Province (2019C03049), National Natural Science Foundation of China (82074245, 81973634, 82204828), and Chinese Postdoctoral Science Foundation (2022M713203).

Identification and subcellular colocalization of protein transport protein Sec61α and Sec61γ in Nosema bombycis.

The main function of Sec61 complex is participating in the transport of polypeptide chains across the endoplasmic reticulum. The Sec61α subunit is the largest subunit of the Sec61 complex and shows high degree of conservation. In this study, we identified the NbSec61α and NbSec61γ genes in the microsporidian Nosema bombycis for the first time. Multiple sequence alignment showed that the sequence similarity between NbSec61α and homologous proteins of other microsporidia was greater than 48 %. NbSec61α contains a "plug" domain (amino acids 40-74) unique to the Sec61/SecY complex. Phylogenetic analysis based on NbSec61α and NbSec61γ indicated that the N. bombycis was closely related to Nosema granulosis, Nosema ceranae and Nosema apis. Indirect immunfluorescence assay showed that NbSec61α and NbSec61γ were mainly distributed in the perinuclear region of N. bombycis in different developmental phases. qRT-PCR results revealed that the expression level of NbSec61α gene increased in the early stage and reached the highest at 48 h, then decreased in the late stages. After knockdown of NbSec61α, the expression of NbSec61α, NbSec61γ and NbssrRNA genes were all significantly down-regulated. These results suggest that the NbSec61α and NbSec61γ may play an important role in the intracellular development of N. bombycis.

Interpretation for Individual Brain Age Prediction Based on Gray Matter Volume.

The relationship between age and the central nervous system (CNS) in humans has been a classical issue that has aroused extensive attention. Especially for individuals, it is of far greater importance to clarify the mechanisms between CNS and age. The primary goal of existing methods is to use MR images to derive high-accuracy predictions for age or degenerative diseases. However, the associated mechanisms between the images and the age have rarely been investigated. In this paper, we address the correlation between gray matter volume (GMV) and age, both in terms of gray matter themselves and their interaction network, using interpretable machine learning models for individuals. Our goal is not only to predict age accurately but more importantly, to explore the relationship between GMV and age. In addition to targeting each individual, we also investigate the dynamic properties of gray matter and their interaction network with individual age. The results show that the mean absolute error (MAE) of age prediction is 7.95 years. More notably, specific locations of gray matter and their interactions play different roles in age, and these roles change dynamically with age. The proposed method is a data-driven approach, which provides a new way to study aging mechanisms and even to diagnose degenerative brain diseases.

The correlation between infiltration of FoxP3+ Tregs, CD66b+ TANs and CD163+ TAMs in colorectal cancer.

Introduction: The infiltration of immune cells in tumor tissue is affected by the tumor microenvironment. However, the relationship between the infiltration of regulatory T cells (Tregs), tumor-associated neutrophils (TANs) and tumor-associated macrophages (TAMs) in colorectal cancer (CRC) remains unclear. Material and methods: Tissue microarray and immunohistochemistry were used to detect the infiltration of FoxP3+ Tregs, CD66b+ TANs and CD163+ TAMs in 249 CRC samples (training cohort) and 243 CRC samples (validation cohort). The relationship between two cells was evaluated by Spearman's rank correlation coefficient and comparison between two groups was analyzed by Mann-Whitney U test. Results: The continuous variable positive cell numbers were non-normally distributed. Spearman correlation analysis showed that CD66b+ TAN level in cancer tissues was negatively related to FoxP3+ Treg level (correlation coefficient: -0.495, p < 0.05) and CD163+ TAM level (correlation coefficient: -0.266, p < 0.05), and FoxP3+ Treg level was positively related to CD163+ TAM level (correlation coefficient: 0.467, p < 0.05) in the training cohort. The numbers of FoxP3+ Tregs were significantly different between low and high CD66b+ TAN level groups (p < 0.001), as well as that of CD66b+ TANs in low and high CD163+ TAM level groups and CD163+ TAMs in different FoxP3+ Treg level groups. The results of the validation cohort were similar to those of the training cohort. Conclusions: There is a negative correlation between infiltration of CD66b+ TANs and that of FoxP3+ Tregs or CD163+ TAMs, and a positive correlation between infiltration of FoxP3+ Tregs and CD163+ TAMs in CRC tissues.

Use of DNA nanosensors based on upconverting nanoparticles for detection of Nosema bombycis by fluorescence resonance energy transfer.

In this study, NaYF4:20%Yb, 2%Er upconverting nanoparticles (UCNPs) were synthesized by solvothermal method and characterized by transmission electron microscopy and upconversion fluorescence spectrometry. The results showed that the UCNP particles present good dispersion and uniform spherical shape with a size of 29 ~ 42 nm. Hydroxyl UCNPs were converted to hydrophilic carboxylic acid-functionalized ones by ligand exchange, and the streptavidin was attached on the surface of carboxylic acid-functionalized UCNPs via amide bond. The DNA nanosensors based on UCNPs with DNA probes have been successfully developed. Only the genomic DNA of Nosema bombycis can be specifically detected by the DNA nanosensors when the DNA of Bombyx mori and its pathogens was used as target DNA. When the DNA nanosensors were used to detect the DNA of N. bombycis, a broad emission peak signal appeared at 580 nm. There is linear relationship between the signal intensity and DNA concentration of N. bombycis, I580/I545 (R2 = 0.820) and I545/I654 (R2 = 0.901). The detectable minimum concentration of genomic DNA of N. bombycis was 100 ng/µL while the tested concentrations of N. bombycis genomic DNA were 3000 ng/µL, 1500 ng/µL, 1000 ng/µL, 500 ng/µL, 250 ng/µL, and 100 ng/µL, respectively. The whole detection process for target DNA takes less than 60 min.

Latent Network Construction for Univariate Time Series Based on Variational Auto-Encode.

Time series analysis has been an important branch of information processing, and the conversion of time series into complex networks provides a new means to understand and analyze time series. In this work, using Variational Auto-Encode (VAE), we explored the construction of latent networks for univariate time series. We first trained the VAE to obtain the space of latent probability distributions of the time series and then decomposed the multivariate Gaussian distribution into multiple univariate Gaussian distributions. By measuring the distance between univariate Gaussian distributions on a statistical manifold, the latent network construction was finally achieved. The experimental results show that the latent network can effectively retain the original information of the time series and provide a new data structure for the downstream tasks.

Prognostic significance of CD163+ tumor-associated macrophages in colorectal cancer.

BACKGROUND: This study aimed to explore the prognostic significance of tumor-associated macrophage (TAM) infiltration in colorectal cancer (CRC) patients. METHODS: Tissue microarray and immunohistochemistry were used to detect the infiltration of CD163+ TAMs in 209 CRC samples, and the Kaplan-Meier method was used for survival analysis. Cox proportional hazards analysis was used for univariate analysis and multivariate analysis of clinically relevant confounders. RESULTS: The samples were divided into low-level (n = 105) and high-level infiltration groups (n = 104) by the median number of CD163+ TAMs detected. The overall survival (OS) and disease-free survival (DFS) of CRC patients in the low-level CD163+ TAM infiltration group were longer than those in the high-level CD163+ TAM infiltration group (P < 0.001). Infiltration of CD163+ TAMs in CRC tissues was a negative prognostic factor for CRC patients. Risks of death and disease recurrence for CRC patients in the low-level CD163+ TAM infiltration group were lower than those in the high-level CD163+ TAM infiltration group (HROS = 0.183, 95% CI 0.052-0.647, P = 0.008; HRDFS = 0.191, 95% CI 0.078-0.470, P = 0.000). CONCLUSIONS: The infiltration of CD163+ TAMs in CRC tissue is an independent adverse factor for the prognosis of CRC patients. High-level infiltration of CD163+ TAMs is associated with shorter OS and DFS.

Complex Network Construction of Univariate Chaotic Time Series Based on Maximum Mean Discrepancy.

The analysis of chaotic time series is usually a challenging task due to its complexity. In this communication, a method of complex network construction is proposed for univariate chaotic time series, which provides a novel way to analyze time series. In the process of complex network construction, how to measure the similarity between the time series is a key problem to be solved. Due to the complexity of chaotic systems, the common metrics is hard to measure the similarity. Consequently, the proposed method first transforms univariate time series into high-dimensional phase space to increase its information, then uses Gaussian mixture model (GMM) to represent time series, and finally introduces maximum mean discrepancy (MMD) to measure the similarity between GMMs. The Lorenz system is used to validate the correctness and effectiveness of the proposed method for measuring the similarity.

Identification and subcellular localisation of hexokinase-2 in Nosema bombycis.

Hexokinase (HXK) is the first key enzyme in the glycolytic pathway and plays an extremely important role in energy metabolism. By searching the microsporidian database, we found a sequence (NBO_27g0008) of Nosema bombycis Nägali, 1857 with high similarity to hexokinase-2, and named it as NbHXK2. The NbHXK2 gene has 894 bp and encodes 297 amino acids with 34.241 kD molecular weight and 5.26 isoelectric point. NbHXK2 contains 31 phosphorylation sites and 4 potential N-glycosylation sites with signal peptides and no transmembrane domain. Multiple sequence alignment showed that NbHXK2 shares more than 40% amino acid identity with that of other microsporidia, and the homology with hexokinase-2 of Nosema tyriae Canning, Curry, Cheney, Lafranchi-Tristem, Kawakami, Hatakeyama, Iwano et Ishihara, 1999, Nosema pyrausta (Paillot, 1927) and Nosema ceranae Fries, Feng, da Silva, Slemenda et Pieniazek, 1996 was 89.17%, 87.82% and 69.86%, respectively. Phylogenetic analysis based on the amino acid sequence of hexokinase showed that all microsporidia cluster together in the same clade, and are far away from animals, plants and fungi, and that N. bombycis is closely related to N. tyriae; N. pyrausta; N. ceranae and Nosema apis Zander, 1909. Immunolocalisation with the prepared polyclonal antibody showed that NbHXK2 was mainly distributed in the cytoplasm and plasmalemma in proliferative, sporulation stage and mature spore of N. bombycis. qRT-PCR assay showed that the NbHXK2 expressed at higher level during spore germination and at early stage of proliferation. These results indicate that N. bombycis may use its own glycolytic pathways to supply energy for infection and development, especially germination and in the early stage of proliferation, and acquire energy from the host through certain ways as well.

Isolation and identification of two Serratia marcescens strains from silkworm, Bombyx mori.

Bacterial septicemia commonly occurs and usually cause huge losses in sericulture industry. Here, two pathogenic bacterial strains were isolated from dead silkworm and named as ZJ-1 and ZJ-2. Phenotypic and genotypic analysis results revealed that both of these two strains are closely related to Serratia marcescens (S. marcescens). The morphological as well as physiological and biochemical characteristics of ZJ-1 were accordant with S. marcescens mentioned in Bergey's manual of determinative bacteriology, whereas ZJ-2 showed some discrepancies such as the utilization of malonate and starch, fermentation of maltose and sucrose, and tests of urease, etc. Surprisingly, ZJ-2 could produce red pigment at high temperature (37°) but ZJ-1 could not. Besides, by analyzing the lethal concentration 50 (LC50) of ZJ-1 and ZJ-2, it was found that the virulence of ZJ-2 was lower than that of ZJ-1. These results revealed that ZJ-1 and ZJ-2 were two different strains of S. marcescens and that ZJ-2 was expected to be a safe (low-toxicity) and efficient strain for the production of red pigment. Nonetheless, further research in molecular level is needed to understand the regulation mechanism of pigment production and infection of ZJ-2.

Cisplatin resistance in gastric cancer cells is involved with GPR30-mediated epithelial-mesenchymal transition.

Cisplatin is the major chemotherapeutic drug in gastric cancer, particularly in treating advanced gastric cancer. Tumour cells often develop resistance to chemotherapeutic drugs, which seriously affects the efficacy of chemotherapy. GPR30 is a novel oestrogen receptor that is involved in the invasion, metastasis and drug resistance of many tumours. Targeting GPR30 has been shown to increase the drug sensitivity of breast cancer cells. However, few studies have investigated the role of GPR30 in gastric cancer. Epithelial-mesenchymal transition (EMT) has been shown to be associated with the development of chemotherapeutic drug resistance. In this study, we demonstrated that GPR30 is involved in cisplatin resistance by promoting EMT in gastric cancer. GPR30 knockdown resulted in increased sensitivity of different gastric cancer (GC) cells to cisplatin and alterations in the epithelial/mesenchymal markers. Furthermore, G15 significantly enhanced the cisplatin sensitivity of GC cells while G1 inhibited this phenomenon. In addition, EMT occurred when AGS and BGC-823 were treated with cisplatin. Down-regulation of GPR30 with G15 inhibited this transformation, while G1 promoted it. Taken together, these results revealed the role of GPR30 in the formation of cisplatin resistance, suggesting that targeting GPR30 signalling may be a potential strategy for improving the efficacy of chemotherapy in gastric cancer.

Recombinant cucurmosin-based immunotoxin targeting HER-2 with potent in vitro anti-cancer cytotoxicity.

Trastuzumab is a humanized monoclonal antibody against HER2 approved by FDA for breast and gastric cancer therapy. However, only a quarter of patients have the potential to benefit from it, and most of them develop resistance within therapy. The main purpose of this study is to broaden trastuzumab's therapeutic window by conjugating trastuzumab with recombinant cucurmosin to form an immunotoxin called T-CUS245C. T-CUS245C was chemically conjugated and the purification of T-CUS245C was evaluated by SDS-PAGE. SRB tests showed a remarkable cytotoxicity of T-CUS245C with IC50 values in picomolar range on HER2 positive cancer cells without significantly proliferation inhibition on HER2 negative cells (P < 0.01). Confocal microscopy verified the time-dependent internalization effects of T-CUS245C and revealed that the lethal efficacy can be increased by provoking the internalization. These results indicate the therapeutic potential of T-CUS245C for the HER-2 targeted therapy.

Huaier n-butanol extract suppresses proliferation and metastasis of gastric cancer via c-Myc-Bmi1 axis.

Gastric cancer (GC) ranks as the third leading cause of cancer-related mortality worldwide, and approximately 42% of all cases diagnosed each year worldwide are diagnosed in China. A large number of clinical applications have revealed that Trametes robiniophila Μurr. (Huaier) exhibits an anti-tumour effect. However, loss of the bioactive components of Huaier during the extraction procedure with water is unavoidable, and the underlying mechanism of the anti-cancer effect of Huaier remains poorly understood. In this study, we investigated the anti-cancer effect of Huaier n-butanol extract, which contained 51.4% total flavonoids, on HGC27, MGC803, and AGS human GC cell lines in vitro. At a low concentration, Huaier n-butanol extract inhibited the growth of these GC cell types, induced cell cycle arrest and reduced cell metastasis. Moreover, Huaier n-butanol extract suppressed the c-Myc-Bmi1 signalling pathway, and overexpression of Bmi1 reversed the effects of Huaier n-butanol extract on GC cells. Thus, our findings indicate that Huaier n-butanol extract suppresses the proliferation and metastasis of GC cells via a c-Myc-Bmi1-mediated approach, providing a new perspective for our understanding of the anti-tumour effects of Huaier. These results suggest that Huaier n-butanol extract could be an attractive therapeutic adjuvant for the treatment of human GC.

Does the use of targeted agents in advanced gastroesophageal cancer increase complete response? A meta-analysis of 18 randomized controlled trials.

PURPOSE: We aimed to investigate whether the use of targeted agents (TAs) in advanced gastroesophageal cancer (GEC) increased the complete response (CR) and to assess the surrogate endpoints for survival in the targeted treatment of GEC by using a meta-analysis of randomized controlled trials (RCTs). METHODS: Eligible studies were identified using Medline, PubMed, and meeting abstracts. Searches were last updated on April 30, 2018. We calculated the incidence and Peto odds ratio (Peto OR) of CR events in patients assigned to TAs compared with controls. Simple linear regression models were fitted for median overall survival (OS) and each surrogate [median progression-free survival (PFS), CRs, objective response rate (ORR), and disease control rate (DCR), respectively]. RESULTS: A total of 7,892 GEC patients from 18 RCTs were included for analysis. The incidence of CR in GEC patients treated with TAs was 2.0% (95% CI, 1.3%-3.0%) compared with 1.7% (95% CI, 1.0%-2.7%) in the control arms. The use of TAs in advanced GEC had a tendency to improve the possibility of archiving CR (Peto OR 1.42; 95% CI, 0.98-2.04; P=0.064) compared with controls. Subgroup analysis according to treatment TAs showed that the addition of antiepidermal growth factor receptor (EGFR) agents to chemotherapy in GEC significantly improved the CR rate in comparison with control (Peto OR 1.77; 95% CI, 1.02-3.09; P=0.044), but not for other molecular TAs (P=0.49 for angiogenesis inhibitors, P=0.66 for mesenchymal-epithelial transition inhibitors). We also found that the addition of TAs to first-line therapy (Peto OR 1.41; 95% CI, 0.94-2.11; P=0.098) had a tendency to increase the chance of obtaining a CR, but not for second-line therapy (Peto OR 1.47; 95% CI, 0.60-3.55; P=0.40). In addition, correlation analysis indicates that PFS, ORR, and DCR were strongly correlated with OS for GEC patients receiving TAs (r=0.85 for PFS; r=0.86 for ORR; r=0.81 for DCR). No marked correlation was found between OS and CRs (r=0.43; P=0.18). CONCLUSION: Although the CR is a rate event in advanced GEC patients, adding the TAs to therapies, especially for anti-EGFR agents, increases the chance of archiving CR in comparison with the controls. PFS, ORR, and DCR are significantly correlated with OS and could be used as surrogate endpoints in patients with GEC who have received TA therapy, but not for CR.

eIF5A2 regulates the resistance of gastric cancer cells to cisplatin via induction of EMT.

Cisplatin is the first-line chemotherapy drug for gastric cancer (GC), but treatment failure often occurs due to development of resistance. The mechanism of cisplatin resistance remains a mystery. Eukaryotic translation initiation factor 5A2 (eIF5A2) is an important tumor-promoting factor and has been rarely studied in GC. This study aimed to investigate the role of eIF5A2 in cisplatin resistance of GC cells and its relationship with epithelial-mesenchymal transition (EMT). We found that it is negative correlation between cisplatin resistance and eIF5A2's expression in GC cells. Silencing of eIF5A2 enhanced the sensitivity of GC cells to cisplatin, while overexpression of eIF5A2 decreased sensitivity. Cisplatin treatment induced gene expression changes consistent with EMT. EMT was blocked and the sensitivity of GC cells to cisplatin was increased by inhibiting the expression of Twist, indicating that EMT regulates the sensitivity of GC cells to cisplatin. Knockdown of eIF5A2 was associated with upregulation of the epithelial markers E-cadherin and ß-catenin, while the expression of mesenchymal markers vimentin and N-cadherin decreased, indicating that eIF5A2 can reverse the EMT process and block the effect of cisplatin on EMT-related markers. Knockdown or overexpression of eIF5A2 did not affect the sensitivity of gastric cancer cells to cisplatin by Twist siRNA. Altogether, these data suggest that eIF5A2 regulates the resistance of gastric cancer cells to cisplatin by mediating EMT, and support the conclusion that eIF5A2 may be a molecular target for anti-tumor therapy.

Denoised P300 and machine learning-based concealed information test method.

In this paper, a novel P300-based concealed information test (CIT) method was proposed to improve the efficiency of differentiating deception and truth-telling. Thirty subjects including the guilty and innocent performed the paradigm based on three types of stimuli. In order to reduce the influence from the occasional variability of cognitive states on the CIT, several single-trials from Pz in probe stimuli within each subject were first averaged. Then the three groups of features were extracted from these averaged single-trials. Finally, two classes of feature samples were used to train a support vector machine (SVM) classifier. Meanwhile, the optimal number of averaged Pz waveforms and some other parameter values in the classifiers were determined by the cross validation procedures. Results show that if choosing accuracy of 90% as a detecting standard of P3 component to classify a subject's status (guilty or innocent), our method can achieve individual diagnostic rate of 100%. The individual diagnostic rate of our method was higher than the results of the other related reports. The presented method improves efficiency of CIT, and is more practical, lower fatigue and less countermeasure behavior in comparison with previous report methods, which could extend the laboratory study to the practical application.