Artificial Intelligence-Assisted Multiparameter Size Discrimination of Silver Nanoparticles through Electrochemical Collision.

Single particle collision is an important tool for size analysis at the individual particle level; however, due to complex dynamic behaviors of nanoparticles on the surface of an electrode, the accuracy of size discrimination is limited. A silver (Ag) nanoparticle (NP) was chosen as the research target, and the dynamic behavior of Ag NPs was simplified by enhancing adsorption between Ag NP and Au ultramicroelectrode (UME) in alkaline media. Immediately after, accurate dynamic and thermodynamic information on single Ag NP was accurately extracted from collision events, including current intensity, transferred charge, and duration time. On the basis that there were differences between parameters of different-sized Ag NPs, multiparameter size discrimination was proposed, which improved the accuracy compared to single-parameter discrimination. More intriguingly, multiparameter analysis was combined with artificial intelligence, a tool adept at processing multidimensional data, for the first time. Finally, artificial intelligence-assisted multiparameter size discrimination was successfully used to intelligently distinguish mixed Ag NPs, with an optimal accuracy of more than 95%. To sum up, the artificial intelligence-assisted multiparameter method showed an excellent ability to quickly achieve the most accurate size discrimination of nanoparticles at the level of individual particle and provide an effective guidance for the application of nanoparticles.

The B-box transcription factor IbBBX29 regulates leaf development and flavonoid biosynthesis in sweet potato.

Plant flavonoids are valuable natural antioxidants. Sweet potato (Ipomoea batatas) leaves are rich in flavonoids, regenerate rapidly, and can adapt to harsh environments, making them an ideal material for flavonoid biofortification. Here, we demonstrate that the B-box (BBX) family transcription factor IbBBX29 regulates the flavonoid contents and development of sweet potato leaves. IbBBX29 was highly expressed in sweet potato leaves and significantly induced by auxin (IAA). Overexpression of IbBBX29 contributed to a 21.37%-70.94% increase in leaf biomass, a 12.08%-21.85% increase in IAA levels, and a 31.33%-63.03% increase in flavonoid accumulation in sweet potato, whereas silencing this gene produced opposite effects. Heterologous expression of IbBBX29 in Arabidopsis (Arabidopsis thaliana) led to a dwarfed phenotype, along with enhanced IAA and flavonoid accumulation. RNA-seq analysis revealed that IbBBX29 modulates the expression of genes involved in the IAA signaling and flavonoid biosynthesis pathways. Chromatin immunoprecipitation-quantitative polymerase chain reaction and electrophoretic mobility shift assay indicated that IbBBX29 targets key genes of IAA signaling and flavonoid biosynthesis to activate their expression by binding to specific T/G-boxes in their promoters, especially those adjacent to the transcription start site. Moreover, IbBBX29 physically interacted with developmental and phenylpropanoid biosynthesis-related proteins, such as AGAMOUS-LIKE 21 protein IbAGL21 and MYB308-like protein IbMYB308L. Finally, overexpressing IbBBX29 also increased flavonoid contents in sweet potato storage roots. These findings indicate that IbBBX29 plays a pivotal role in regulating IAA-mediated leaf development and flavonoid biosynthesis in sweet potato and Arabidopsis, providing a candidate gene for flavonoid biofortification in plants.

ESCO2's oncogenic role in human tumors: a pan-cancer analysis and experimental validation.

PURPOSE: Establishment of sister chromatid cohesion N-acetyltransferase 2 (ESCO2) is involved in the mitotic S-phase adhesins acetylation and is responsible for bridging two sister chromatids. However, present ESCO2 cancer research is limited to a few cancers. No systematic pan-cancer analysis has been conducted to investigate its role in diagnosis, prognosis, and effector function. METHODS: We thoroughly examined the ESCO2 carcinogenesis in pan-cancer by combining public databases such as The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), UALCAN and Tumor Immune Single-cell Hub (TISCH). The analysis includes differential expression analysis, survival analysis, cellular effector function, gene mutation, single cell analysis, and tumor immune cell infiltration. Furthermore, we confirmed ESCO2's impacts on clear cell renal cell carcinoma (ccRCC) cells' proliferative and invasive capacities in vitro. RESULTS: In our study, 30 of 33 cancer types exhibited considerably greater levels of ESCO2 expression in tumor tissue using TCGA and GTEx databases, whereas acute myeloid leukemia (LAML) exhibited significantly lower levels. Kaplan-Meier survival analyses in adrenocortical carcinoma (ACC), kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), brain lower grade glioma (LGG), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), mesothelioma (MESO), and pancreatic adenocarcinoma (PAAD) demonstrated that tumor patients with high ESCO2 expression have short survival periods. However, in thymoma (THYM), colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ), ESCO2 was a favorable prognostic factor. Moreover, ESCO2 expression positively correlates with tumor stage and tumor size in several cancers, including LIHC, KIRC, KIRP and LUAD. Function analysis revealed that ESCO2 participates in mitosis, cell cycle, DNA damage repair, and other processes. CDK1 was identified as a downstream gene regulated by ESCO2. Furthermore, ESCO2 might also be implicated in immune cell infiltration. Finally, ESCO2'S knockdown significantly inhibited the A498 and T24 cells' proliferation, invasion, and migration. CONCLUSIONS: In conclusion, ESCO2 is a possible pan-cancer biomarker and oncogene that can reliably predict the prognosis of cancer patients. ESCO2 was also implicated in the cell cycle and proliferation regulation. In a nutshell, ESCO2 is a therapeutically viable and dependable target.

Molecular strategies of the pygmy grasshopper Eucriotettix oculatus adapting to long-term heavy metal pollution.

To study the heavy metal accumulation and its impact on insect exterior and chromosome morphology, and reveal the molecular mechanism of insects adapting to long-term heavy metal compound pollution habitats, this study, in the Diaojiang river basin, which has been polluted by heavy metals(HMs) for nearly a thousand years, two Eucriotettix oculatus populations was collected from mining and non-mining areas. It was found that the contents of 7 heavy metals (As, Cd, Pb, Zn, Cu, Sn, Sb) in E. oculatus of the mining area were higher than that in the non-mining 1-11 times. The analysis of morphology shows that the external morphology, the hind wing type and the chromosomal morphology of E. oculatus are significant differences between the two populations. Based on the heavy metal accumulation，morphological change, and stable population density, it is inferred that the mining area population has been affected by heavy metals and has adapted to the environment of heavy metals pollution. Then, by analyzing the transcriptome of the two populations, it was found that the digestion, immunity, excretion, endocrine, nerve, circulation, reproductive and other systems and lysosomes, endoplasmic reticulum and other cell structure-related gene expression were suppressed. This shows that the functions of the above-mentioned related systems of E. oculatus are inhibited by heavy metal stress. However, it has also been found that through the significant up-regulation of genes related to the above system, such as ATP2B, pepsin A, ubiquitin, AQP1, ACOX, ATPeV0A, SEC61A, CANX, ALDH7A1, DLD, aceE, Hsp40, and catalase, etc., and the down-regulation of MAPK signalling pathway genes, can enhanced nutrient absorption, improve energy metabolism, repair damaged cells and degrade abnormal proteins, maintain the stability of cells and systems, and resist heavy metal damage so that E. oculatus can adapt to the environment of heavy metal pollution for a long time.

Current Lifetime of Single-Nanoparticle Electrochemical Collision for In Situ Monitoring Nanoparticles Agglomeration and Aggregation.

In situ monitoring of the agglomeration/aggregation process of nanoparticles (NPs) is crucial because it seriously affects cell entry, biosafety, catalytic performance of NPs, and so on. Nevertheless, it remains hard to monitor the solution phase agglomeration/aggregation of NPs via conventional techniques such as electron microscopy, which requires sample pretreatment and cannot represent native state NPs in solution. Considering that single-nanoparticle electrochemical collision (SNEC) is powerful to detect NPs in solution at the single-particle level, and the current lifetime, which refers to the time that current intensity decays to 1/e of the original value, is skilled in distinguishing different sized NPs, herein, a current lifetime-based SNEC has been developed to distinguish a single Au NP (d = 18 nm) from its agglomeration/aggregation. Based on this, the agglomeration/aggregation process of small-sized NPs and the discrimination of agglomeration vs aggregation have been carefully investigated at the single-particle level. Results showed that the agglomeration/aggregation of Au NPs (d = 18 nm) in 0.8 mM HClO4 climbed from 19% to 69% over two hours, whereas there was no visible granular sediment, and Au NPs tended to agglomerate rather than aggregate irreversibly under normal conditions. Hence, the proposed current lifetime-based SNEC could serve as a complementary method to in situ monitor the agglomeration/aggregation of small-sized NPs in solution at the single-particle level and provide effective guidance for the practical application of NPs.

Transcriptional landscape of cholangiocarcinoma revealed by weighted gene coexpression network analysis.

Cholangiocarcinoma (CCA) is a type of cancer with limited treatment options and a poor prognosis. Although some important genes and pathways associated with CCA have been identified, the relationship between coexpression and phenotype in CCA at the systems level remains unclear. In this study, the relationships underlying the molecular and clinical characteristics of CCA were investigated by employing weighted gene coexpression network analysis (WGCNA). The gene expression profiles and clinical features of 36 patients with CCA were analyzed to identify differentially expressed genes (DEGs). Subsequently, the coexpression of DEGs was determined by using the WGCNA method to investigate the correlations between pairs of genes. Network modules that were significantly correlated with clinical traits were identified. In total, 1478 mRNAs were found to be aberrantly expressed in CCA. Seven coexpression modules that significantly correlated with clinical characteristics were identified and assigned representative colors. Among the 7 modules, the green and blue modules were significantly related to tumor differentiation. Seventy-eight hub genes that were correlated with tumor differentiation were found in the green and blue modules. Survival analysis showed that 17 hub genes were prognostic biomarkers for CCA patients. In addition, we found five new targets (ISM1, SULT1B1, KIFC1, AURKB and CCNB1) that have not been studied in the context of CCA and verified their differential expression in CCA through experiments. Our results not only promote our understanding of the relationship between the transcriptome and clinical data in CCA but will also guide the development of targeted molecular therapy for CCA.

Ptip is essential for tooth development via regulating Wnt pathway.

OBJECTIVE: Epigenetic regulation plays important role in stem cell maintenance. Ptip was identified as epigenetic regulator, but the role in dental progenitor cells remains unclear. SUBJECTS AND METHODS: Dental mesenchymal progenitor cells were targeted by Sp7-icre and visualized in mTmG; Sp7-icre mice. The Ptipf/f ; Sp7-icre mice were generated and the phenotype of incisors and molars were shown by micro-computerized tomography, scanning electron microscope, hematoxylin & eosin staining, and immunofluorescence. Dental mesenchymal progenitor cells were sorted by fluorescence-activated cell sorting from lower incisors and RNA sequencing was performed. RESULTS: The Sp7-icre targets dental mesenchymal progenitor cells in incisors and molars. The Ptipf/f ; Sp7-icre mice showed spontaneous fractures in the cusp of upper incisors and lower incisors at 3 weeks (w), compensative overgrowth of lower incisors at 1 month (M), and overgrowth extended to the outside at 2 M. The molars showed shortened roots. The functions of odontoblasts and dental mesenchymal progenitor cells were impaired. Mechanically, loss of Ptip activates the Wnt pathway and upregulates the expression of Wls in dental mesenchymal progenitor cells. Also, the regenerative ability of lower incisors was significantly impaired. CONCLUSION: We first demonstrated that Ptip was crucial for tooth development via regulating Wnt signaling.

ISRIB inhibits the senescence of type II pulmonary epithelial cells to alleviate pulmonary fibrosis induced by silica in mice.

The role and mechanisms of integrated stress response inhibitor (ISRIB) on silicosis are still not well defined. In the present study, the effects of ISRIB on cellular senescence and pulmonary fibrosis in silicosis were evaluated by RNA sequencing, micro-computed tomography, pulmonary function assessment, histological examination, and Western blot analysis. The results showed that ISRIB significantly reduced the degree of pulmonary fibrosis in mice with silicosis and reduced the expression of type I collagen, fibronectin, α-smooth muscle actin, and transforming growth factor-ß1. Both in vivo and in vitro results showed that ISRIB reversed the expression of senescence-related factors ß-galactosidase, phosphor-ataxia telangiectasia mutated, phosphor-ataxia telangiectasia and Rad3-related protein, p-p53, p21, p16, and plasminogen activator inhibitor type 1. The aforementioned results were consistent with the sequencing results. These findings implied that ISRIB might reduce the degree of pulmonary fibrosis in mice with silicosis by inhibiting the cellular senescence of alveolar epithelial cell type II.

FLPP: A Federated-Learning-Based Scheme for Privacy Protection in Mobile Edge Computing.

Data sharing and analyzing among different devices in mobile edge computing is valuable for social innovation and development. The limitation to the achievement of this goal is the data privacy risk. Therefore, existing studies mainly focus on enhancing the data privacy-protection capability. On the one hand, direct data leakage is avoided through federated learning by converting raw data into model parameters for transmission. On the other hand, the security of federated learning is further strengthened by privacy-protection techniques to defend against inference attack. However, privacy-protection techniques may reduce the training accuracy of the data while improving the security. Particularly, trading off data security and accuracy is a major challenge in dynamic mobile edge computing scenarios. To address this issue, we propose a federated-learning-based privacy-protection scheme, FLPP. Then, we build a layered adaptive differential privacy model to dynamically adjust the privacy-protection level in different situations. Finally, we design a differential evolutionary algorithm to derive the most suitable privacy-protection policy for achieving the optimal overall performance. The simulation results show that FLPP has an advantage of 8∼34% in overall performance. This demonstrates that our scheme can enable data to be shared securely and accurately.

Application of Microhaplotypes in Sibling Kinship Testing.

OBJECTIVES: To investigate the efficacy of different numbers of microhaplotype (MH) loci and the introduction of different reference samples on the identification of full sibling, half sibling and differentiation between full sibling and half sibling kinships, and to explore the effect of changing mutation rate on sibling testing. METHODS: First, a family map involving three generations was established, and four full sibling identification models, five half sibling identification models and five models distinguishing full and half siblings were constructed for different reference samples introduced. Based on the results of the previous study, two sets of nonbinary SNP-MH containing 34 and 54 loci were selected. Based on the above MH loci, 100 000 pairs of full sibling vs. unrelated individuals, 100 000 pairs of half sibling vs. unrelated individuals and 100 000 pairs of full sibling vs. half sibling were simulated based on the corresponding sibling kinship testing models, and the efficacy of each sibling kinship testing model was analyzed by the likelihood ratio algorithm under different thresholds. The mutant rate of 54 MH loci was changed to analyze the effect of mutation rate on sibling identification. RESULTS: In the same relationship testing model, the systematic efficacy of sibling testing was positively correlated with the number of MH loci detected. With the same number of MH loci, the efficacy of full sibling testing was better than that of uncle or grandfather when the reference sample introduced was a full sibling of A, but there was no significant difference in the identification efficacy of the four reference samples introduced for full sibling and half sibling differentiation testing. In addition, the mutation rate had a slight effect on the efficacy of sibling kinship testing. CONCLUSIONS: Increasing the number of MH loci and introducing reference samples of known relatives can increase the efficacy of full sibling testing, half sibling testing, and differentiation between full and half sibling kinships. The level of mutation rate in sibling testing by likelihood ratio method has a slight but insignificant effect on the efficacy.

Current Lifetime of Single-Nanoparticle Collision for Sizing Nanoparticles.

Accurate size analysis of nanoparticles (NPs) is vital for nanotechnology. However, this cannot be realized based on conventional single-nanoparticle collision (SNC) because the current intensity, a thermodynamic parameter of SNC for sizing NPs, is always smaller than the theoretical value due to the effect of NP movements on the electrode surface. Herein, a size-dependent dynamic parameter of SNC, current lifetime, which refers to the time that the current intensity decays to 1/e of the original value, was originally utilized to distinguish differently sized NPs. Results showed that the current lifetime increased with NP size. After taking the current lifetime into account rather than the current intensity, the overlap rates for the peak-type current transients of differently sized Pt NPs (10 and 15 nm) and Au NPs (18 and 35 nm) reduced from 73 and 7% to 45 and 0%, respectively, which were closer to the theoretical values (29 and 0%). Hence, the proposed SNC dynamics-based method holds great potential for developing reliable electrochemical approaches to evaluate NP sizes accurately.

Single-Nanoparticle Collision Electrochemistry Biosensor Based on an Electrocatalytic Strategy for Highly Sensitive and Specific Detection of H7N9 Avian Influenza Virus.

Single-nanoparticle collision electrochemistry (SNCE) has gradually become an attractive analytical method due to its advantages in analytical detection, such as a fast response, low cost, low sample consumption, and in situ real-time detection of analytes. However, the biological analyte's direct detection based on the SNCE blocking mode has the problems of low sensitivity and specificity. In this work, an SNCE biosensor based on SNCE electrocatalytic strategy was used for the detection of H7N9 AIV. Nucleic acid aptamers were introduced to recognize the target virus (H7N9 AIV). After the recognition event, ssDNA1 was released and hybridized with another ssDNA2. Owing to the nicking endonuclease Nt.AlwI-mediated target nucleic acid cyclic amplification, one virus particle can indirectly induce the release of 4.2 × 106 Au NPs that can be counted by the SNCE electrocatalytic strategy. The high conversion efficiency greatly improved the detection sensitivity, and the detection limit was as low as 24.3 fg/mL. Therefore, the constructed biosensor can achieve a highly sensitive and specific detection of H7N9 AIV and show a great potential in bioanalytical application.

Estimating leaf area index using unmanned aerial vehicle data: shallow vs. deep machine learning algorithms.

Measuring leaf area index (LAI) is essential for evaluating crop growth and estimating yield, thereby facilitating high-throughput phenotyping of maize (Zea mays). LAI estimation models use multi-source data from unmanned aerial vehicles (UAVs), but using multimodal data to estimate maize LAI, and the effect of tassels and soil background, remain understudied. Our research aims to (1) determine how multimodal data contribute to LAI and propose a framework for estimating LAI based on remote-sensing data, (2) evaluate the robustness and adaptability of an LAI estimation model that uses multimodal data fusion and deep neural networks (DNNs) in single- and whole growth stages, and (3) explore how soil background and maize tasseling affect LAI estimation. To construct multimodal datasets, our UAV collected red-green-blue, multispectral, and thermal infrared images. We then developed partial least square regression (PLSR), support vector regression, and random forest regression models to estimate LAI. We also developed a deep learning model with three hidden layers. This multimodal data structure accurately estimated maize LAI. The DNN model provided the best estimate (coefficient of determination [R2] = 0.89, relative root mean square error [rRMSE] = 12.92%) for a single growth period, and the PLSR model provided the best estimate (R2 = 0.70, rRMSE = 12.78%) for a whole growth period. Tassels reduced the accuracy of LAI estimation, but the soil background provided additional image feature information, improving accuracy. These results indicate that multimodal data fusion using low-cost UAVs and DNNs can accurately and reliably estimate LAI for crops, which is valuable for high-throughput phenotyping and high-spatial precision farmland management.

Rhodohalobacter sulfatireducens sp. nov., isolated from a marine solar saltern.

A novel Gram-stain-negative, oxidase-positive, catalase-positive, non-motile, facultatively anaerobic, rod-shaped bacterium, designated WB101T, was isolated from a marine solar saltern located in Wendeng, PR China. Strain WB101T shared a high level of 16S rRNA gene sequence similarity with Rhodohalobacter barkolensis 15182T (93.5%), R. halophilus JZ3C29T (93.2%), and 'R. mucosus' 8A47T (92.1%). Strain WB101T formed a species-level branch within the genus Rhodohalobacter in both phylogenetic and phylogenomic topologies. The DNA G + C content was 42.0%. Strain WB101T was found to have menaquinone-7 as the only respiratory quinone. The dominant cellular fatty acid (≥ 10%) was iso-C15:0. The major polar lipids were diphosphatidylglycerol, phosphatidylglycerol, and phosphatidylcholine. Characterisation based on phylogenetic, physiological, and biochemical properties indicated that strain WB101T represents a novel species of the genus Rhodohalobacter, and the name Rhodohalobacter sulfatireducens sp. nov. is proposed. The type strain is WB101T (= KCTC 92204T = MCCC 1H00518T).

Litter nitrogen concentration changes mediate effects of drought and plant species richness on litter decomposition.

Biodiversity loss, exotic plant invasion and climatic change are three important global changes that can affect litter decomposition. These effects may be interactive and these global changes thus need to be considered simultaneously. Here, we assembled herbaceous plant communities with five species richness levels (1, 2, 4, 8 or 16) and subjected them to a drought treatment (no, moderate or intensive drought) that was factorially combined with an invasion treatment (presence or absence of the non-native Symphyotrichum subulatum). We collected litter of these plant communities and let it decompose for 9 months in the plant communities from which it originated. Drought decreased litter decomposition, while invasion by S. subulatum had little impact. Increasing species richness decreased litter decomposition except under intensive drought. A structural equation model showed that drought and species richness affected litter decomposition indirectly through changes in litter nitrogen concentration rather than by altering quantity and diversity of soil meso-fauna or soil physico-chemical properties. The slowed litter decomposition under high species diversity originated from a sampling effect, specifically from low litter nitrogen concentrations in the two dominant species. We conclude that effects on litter decomposition rates that are mediated by changing concentrations of the limiting nutrient in litter need to be considered when predicting effects of global changes such as plant diversity loss.

Association between ambient air pollution and blood sex hormones levels in men.

Concerns are growing over time on the adverse health effects of air pollution. However, the association between ambient air pollution and blood sex hormones in men is poorly understood. We included 72,917 men aged 20-55 years from February 2014 to December 2019 in Beijing, China in this study. Blood testosterone, follicle stimulating hormone, luteinizing hormone, estradiol, and prolactin levels of each participant were measured. We collected exposure data of daily ambient levels of particulate matter ≤10 µm (PM10) and ≤2.5 µm (PM2.5), nitrogen dioxide, sulfur dioxide (SO2), carbon monoxide, and ozone. Generalized linear mixed models were used to analyze the potential association between ambient air pollution exposure and blood sex hormone levels. The results showed that both immediate and short-term cumulative PM2.5, PM10, and SO2 exposure was related to altered serum sex hormone levels in men, especially testosterone. An increase of 10 µg/m3 in PM2.5 and PM10 in the current day was related to a 1.6% (95% confidence interval [CI]: 0.9%-2.3%) and 1.1% (95% CI: 0.5%-1.6%) decrease in testosterone, respectively, and a decreasing tendency of accumulated effects persisted within lag 0-30 days. The present study demonstrated that it is important to control ambient air pollution exposure to reduce effects on the reproductive health of men.

A new sub-pathway of long-patch base excision repair involving 5' gap formation.

Base excision repair (BER) is one of the most frequently used cellular DNA repair mechanisms and modulates many human pathophysiological conditions related to DNA damage. Through live cell and in vitro reconstitution experiments, we have discovered a major sub-pathway of conventional long-patch BER that involves formation of a 9-nucleotide gap 5' to the lesion. This new sub-pathway is mediated by RECQ1 DNA helicase and ERCC1-XPF endonuclease in cooperation with PARP1 poly(ADP-ribose) polymerase and RPA The novel gap formation step is employed during repair of a variety of DNA lesions, including oxidative and alkylation damage. Moreover, RECQ1 regulates PARP1 auto-(ADP-ribosyl)ation and the choice between long-patch and single-nucleotide BER, thereby modulating cellular sensitivity to DNA damage. Based on these results, we propose a revised model of long-patch BER and a new key regulation point for pathway choice in BER.

Ultrasensitive Electrochemiluminescence Biosensor Based on Closed Bipolar Electrode for Alkaline Phosphatase Detection in Single Liver Cancer Cell.

An ultrasensitive electrochemiluminescence (ECL) biosensor was proposed based on a closed bipolar electrode (BPE) for the detection of alkaline phosphatase (ALP). For most of the BPE-ECL biosensors, an effective signal amplification strategy was the key to enhance the sensitivity of the system. Herein, the signal amplification strategy of the enzyme catalysis was utilized in the BPE-ECL system. Au nanoparticles (NPs) were electrodeposited on the cathode surface of the ITO electrode to improve the stability and sensitivity of the signal. Compared with the previous BPE-ECL biosensors, the sensitivity was increased by at least 3 orders of magnitude. The biosensor showed high sensitivity and specificity of ALP detection with a detection limit of as low as 3.7 aM. Besides, it was further applied to the detection of ALP in different types of cells and successfully realized ALP detection in single Hep G2 cell, which had a huge application prospect in single biomolecule detection or single cell analysis.

A novel prognostic model based on epithelial-mesenchymal transition-related genes predicts patient survival in gastric cancer.

BACKGROUND: Gastric cancer (GC) represents a major malignancy and is the third deathliest cancer globally. Several lines of evidence indicate that the epithelial-mesenchymal transition (EMT) has a critical function in the development of gastric cancer. Although plentiful molecular biomarkers have been identified, a precise risk model is still necessary to help doctors determine patient prognosis in GC. METHODS: Gene expression data and clinical information for GC were acquired from The Cancer Genome Atlas (TCGA) database and 200 EMT-related genes (ERGs) from the Molecular Signatures Database (MSigDB). Then, ERGs correlated with patient prognosis in GC were assessed by univariable and multivariable Cox regression analyses. Next, a risk score formula was established for evaluating patient outcome in GC and validated by survival and ROC curves. In addition, Kaplan-Meier curves were generated to assess the associations of the clinicopathological data with prognosis. And a cohort from the Gene Expression Omnibus (GEO) database was used for validation. RESULTS: Six EMT-related genes, including CDH6, COL5A2, ITGAV, MATN3, PLOD2, and POSTN, were identified. Based on the risk model, GC patients were assigned to the high- and low-risk groups. The results revealed that the model had good performance in predicting patient prognosis in GC. CONCLUSIONS: We constructed a prognosis risk model for GC. Then, we verified the performance of the model, which may help doctors predict patient prognosis.

Gene networks and toxicity/detoxification pathways in juvenile largemouth bass (Micropterus salmoides) liver induced by acute lead stress.

Lead (Pb) is a nonessential heavy metal that can be bioconcentrated to highly toxic levels in the environment. To understand the genes and toxicity/detoxification pathways of juvenile largemouth bass, liver transcriptomes were investigated in this fish after acute 96 h Pb exposure (Pb nitrate 0, 17.8, or 100 mg/L). Acute Pb exposure induced an immune response and apoptosis pathway activation in the liver. A number of transcripts related to complement and coagulation cascades were significantly increased. Up- and downregulated genes were significantly enriched in numerous pathways, including the natural killer cell-mediated cytotoxicity pathway, the Jak-STAT and P53 signaling pathways, cancer and apoptosis. These genes included Bid，Bcl-2, JNK, and PI3K (17.8 mg/L) and PI3K, AKT, PPARδ, RAS, MMPs, c-Jun p53, and PD-L1 (100 mg/L). Comprehensive analysis of liver transcriptomic data revealed numerous pathways associated with the immune system and carcinogenesis, especially pathways related to apoptosis and systemic lupus erythematosus.