Tailoring chelating sites in two-dimensional covalent organic framework nanosheets for enhanced uranium capture.

In this study, we intricately designed and synthesized two isoreticular two-dimensional covalent organic framework nanosheets, namely TAPA-COF-1 and TAPA-COF-2, distinguished by their unique spatial arrangement of hydroxyl groups. These precisely engineered nanosheets were employed as a tailored platform for the selective capture of uranium, due to their tunable chelating sites and characteristic sheet-like morphology. Notably, TAPA-COF-1, featuring ortho-hydroxyl groups, demonstrated a significantly enhanced adsorption capacity for uranium capture originating from the additional oriented adjacent phenolic hydroxyl chelating sites in comparison to TAPA-COF-2 with para-hydroxyl groups, which was proved by theoretical calculation. The impressive features of TAPA-COF-1, including its notable selectivity, rapid adsorption kinetics, and high uptake capacity (657.2 mg g-1), endow it as a highly promising candidate for uranium capture.

Evaluating the Spatiotemporal Characteristics of Agricultural Eco-Efficiency Alongside China's Carbon Neutrality Targets.

Agriculture has the dual effect of contributing to both carbon emissions and sequestration, and thus plays a critical role in mitigating global climate change and achieving carbon neutrality. Agricultural eco-efficiency (AEE) is an important measurement through which we can assess the efforts toward reduced emissions and increased sequestration. The purpose of this study was to understand the relationship between China's target of carbon neutrality and AEE through an evaluative model, so as to improve AEE and ultimately achieve sustainable agricultural development. The Super-SBM model scientifically measures the AEE based on provincial panel data collected between 2000 and 2020. We selected kernel density function and spatial distribution to explore the spatial and temporal evolutionary trends, and used a Tobit model to identify the drivers of AEE. The research shows that (1) China's agricultural system functions as a net carbon sink, with all provinces' agricultural carbon sequestration levels recorded as higher than their carbon emissions from 2000 to 2020. (2) Despite sequestration levels, the level of AEE in China is not high enough, and the average efficiency level from 2000 to 2020 is 0.7726, showing an overall trend where AEE decreased at first and then increased. (3) The AEE of each province is clearly polarized; there are obvious core-periphery characteristics and spatial distribution of clustered contiguous areas. Central provinces generally have lower efficiency, eastern and northeastern provinces have higher efficiency, and northeastern provinces always remain in the high-efficiency group. (4) Influencing factors show that urbanization, upgrading of industrial structure, financial support for agriculture, and mechanization have a significant positive impact on AEE. These findings have important implications for the promotion of the low-carbon green development of Chinese agriculture.

Near-Infrared Photothermally Enhanced Photo-Oxygenation for Inhibition of Amyloid-ß Aggregation Based on RVG-Conjugated Porphyrinic Metal-Organic Framework and Indocyanine Green Nanoplatform.

Amyloid aggregation is associated with many neurodegenerative diseases such as Alzheimer's disease (AD). The current technologies using phototherapy for amyloid inhibition are usually photodynamic approaches based on evidence that reactive oxygen species can inhibit Aß aggregation. Herein, we report a novel combinational photothermally assisted photo-oxygenation treatment based on a nano-platform of the brain-targeting peptide RVG conjugated with the 2D porphyrinic PCN-222 metal-organic framework and indocyanine green (PCN-222@ICG@RVG) with enhanced photo-inhibition in Alzheimer's Aß aggregation. A photothermally assisted photo-oxygenation treatment based on PCN@ICG could largely enhance the photo-inhibition effect on Aß42 aggregation and lead to much lower neurotoxicity upon near-infrared (NIR) irradiation at 808 nm compared with a single modality of photo-treatment in both cell-free and in vitro experiments. Generally, local photothermal heat increases the instability of Aß aggregates and keeps Aß in the status of monomers, which facilitates the photo-oxygenation process of generating oxidized Aß monomers with low aggregation capability. In addition, combined with the brain-targeting peptide RVG, the PCN-222@ICG@RVG nanoprobe shows high permeability of the human blood-brain barrier (BBB) on a human brain-on-a-chip platform. The ex vivo study also demonstrates that NIR-activated PCN-222@ICG@RVG could efficiently dissemble Aß plaques. Our work suggests that the combination of photothermal treatment with photo-oxygenation can synergistically enhance the inhibition of Aß aggregation, which may boost NIR-based combinational phototherapy of AD in the future.

Identification of Sparse Volterra Systems: An Almost Orthogonal Matching Pursuit Approach.

This paper considers identification of sparse Volterra systems. A method based on the almost orthogonal matching pursuit (AOMP) is proposed. The AOMP algorithm allows one to estimate one non-zero coefficient at a time until all non-zero coefficients are found without losing the optimality and the sparsity, thus avoiding the curse of dimensionality often encountered in Volterra system identification.

Persistence of Excitation for Identifying Switched Linear Systems.

This paper investigates the uniqueness of parameters via persistence of excitation for switched linear systems. The main contribution is a much weaker sufficient condition on the regressors to be persistently exciting that guarantees the uniqueness of the parameter sets and also provides new insights in understanding the relation among different subsystems. It is found that for uniquely determining the parameters of switched linear systems, the needed minimum number of samples derived from our sufficient condition is much smaller than that reported in the literature.

Immune-related gene expression signatures in colorectal cancer.

The immune system is crucial in regulating colorectal cancer (CRC) tumorigenesis. Identification of immune-related transcriptomic signatures derived from the peripheral blood of patients with CRC would provide insights into CRC pathogenesis, and suggest novel clues to potential immunotherapy strategies for the disease. The present study collected blood samples from 59 patients with CRC and 62 healthy control patients and performed whole blood gene expression profiling using microarray hybridization. Immune-related gene expression signatures for CRC were identified from immune gene datasets, and an algorithmic predictive model was constructed for distinguishing CRC from controls. Model performance was characterized using an area under the receiver operating characteristic curve (ROC AUC). Functional categories for CRC-specific gene expression signatures were determined using gene set enrichment analyses. A Kaplan-Meier plotter survival analysis was also performed for CRC-specific immune genes in order to characterize the association between gene expression and CRC prognosis. The present study identified five CRC-specific immune genes [protein phosphatase 3 regulatory subunit Bα (PPP3R1), amyloid ß precursor protein, cathepsin H, proteasome activator subunit 4 and DEAD-Box Helicase 3 X-Linked]. A predictive model based on this five-gene panel showed good discriminatory power (independent test set sensitivity, 83.3%; specificity, 94.7%, accuracy, 89.2%; ROC AUC, 0.96). The candidate genes were involved in pathways associated with 'adaptive immune responses', 'innate immune responses' and 'cytokine signaling'. The survival analysis found that a high level of PPP3R1 expression was associated with a poor CRC prognosis. The present study identified five CRC-specific immune genes that were potential diagnostic biomarkers for CRC. The biological function analysis indicated a close association between CRC pathogenesis and the immune system, and may reveal more information about the immunogenic and pathogenic mechanisms driving CRC in the future. Overall, the association between PPP3R1 expression and survival of patients with CRC revealed potential new targets for CRC immunotherapy.

Prediction and Verification of the Major Ingredients and Molecular Targets of Tripterygii Radix Against Rheumatoid Arthritis.

Tripterygii Radix exhibits good clinical efficacy and safety in rheumatoid arthritis (RA) patients, but its effective components and mechanism of action are still unclear. The purpose of this study was to explore and verify the major ingredients and molecular targets of Tripterygii Radix in RA using drug-compounds-biotargets-diseases network and protein-protein interaction (PPI) network analyses. The processes and pathways were derived from Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The most important compounds and biotargets were determined based on the degree values. RA fibroblast-like synoviocytes (RA-FLS) were separated from RA patients and identified by hematoxylin and eosin (HE) staining and immunohistochemistry. The purity of RA-FLS was acquired by flow cytometry marked with CD90 or VCAM-1. RA-FLS were subjected to control, dimethyl sulfoxide (control), kaempferol, or lenalidomide treatment. Cell migration was evaluated by the transwell assay. The relative expression of biotarget proteins and cytokines was analyzed by western blotting and flow cytometry. In total, 144 chemical components were identified from Tripterygii Radix; kaempferol was the most active ingredient among 33 other components. Fourteen proteins were found to be affected in RA from 285 common biotargets. The tumor necrosis factor (TNF) signaling pathway was predicted to be one of the most latent treatment pathways. Migration of RA-FLS was inhibited and the expression of protein kinase B (AKT1), JUN, caspase 3 (CASP3), TNF receptor 1 and 2 (TNFR1 and TNFR2), interleukin-6 (IL-6), and TNF-α was significantly affected by kaempferol. Thus, this study confirmed kaempferol as the effective component of Tripterygii Radix against RA-FLS and TNF signaling pathway and its involvement in the regulation of AKT1, JUN, CASP3, TNFR1, TNFR2, IL-6, and TNF-α expression.

Use of peripheral blood transcriptomic biomarkers to distinguish high-grade cervical squamous intraepithelial lesions from low-grade lesions.

It is crucial to classify cervical lesions into high-grade squamous intraepithelial lesions (HSILs) and low-grade SILs (LSILs), as LSILs are conservatively treated by observation, based on an expectation of natural regression, whereas HSILs usually require electrosurgical excision. In the present study, peripheral blood gene expression profiles were analyzed to identify transcriptomic biomarkers distinguishing HSILs from LSILs. A total of 102 blood samples were collected from women with cervical SILs (66 HSIL and 36 LSIL) for microarray hybridization. Candidate gene signatures were identified using AdaBoost algorithms, and a predictive model was constructed using logistic regression to differentiate HSILs from LSILs. To correct for possible bias as a result of the limited sample size and to verify the stability of the predictive model, a two-fold cross validation and null set analysis was conducted over 1,000 iterations. The functions of the transcriptomic biomarkers were then analyzed to elucidate the pathogenesis of cervical SIL. A total of 10 transcriptomic genes (STMN3, TRPC4AP, DYRK2, AGK, KIAA0319L, GRPEL1, ZFC3H1, LYL1, ITGB1 and ARHGAP18) were identified. The predictive model based on the 10-gene panel exhibited well-discriminated power. A cross validation process using known disease status exhibited almost the same performance as that of the predictive model, whereas null-set analysis with randomly reassigned disease status exhibited much lower predictive performance for distinguishing HSILs from LSILs. These biomarkers were involved in the 'Rho GTPase cycle', 'mitochondrial protein import', 'oncogenic MAPK signaling', 'integrin cell surface interaction' and 'signaling by BRAF and RAF fusions'. In conclusion, peripheral blood gene expression analysis is a promising method for distinguishing HSILs from LSILs. The present study proposes 10 candidate genes that could be used in the future as diagnostic biomarkers and potential therapeutic targets for cervical SILs. A simple, non-invasive blood test would be clinically useful in the diagnosis and classification of patients with cervical SILs.

Peripheral blood transcriptome identifies high-risk benign and malignant breast lesions.

BACKGROUND: Peripheral blood transcriptome profiling is a potentially important tool for disease detection. We utilize this technique in a case-control study to identify candidate transcriptomic biomarkers able to differentiate women with breast lesions from normal controls. METHODS: Whole blood samples were collected from 50 women with high-risk breast lesions, 57 with breast cancers and 44 controls (151 samples). Blood gene expression profiling was carried out using microarray hybridization. We identified blood gene expression signatures using AdaBoost, and constructed a predictive model differentiating breast lesions from controls. Model performance was then characterized by AUC sensitivity, specificity and accuracy. Biomarker biological processes and functions were analyzed for clues to the pathogenesis of breast lesions. RESULTS: Ten gene biomarkers were identified (YWHAQ, BCLAF1, WSB1, PBX2, DDIT4, LUC7L3, FKBP1A, APP, HERC2P2, FAM126B). A ten-gene panel predictive model showed discriminatory power in the test set (sensitivity: 100%, specificity: 84.2%, accuracy: 93.5%, AUC: 0.99). These biomarkers were involved in apoptosis, TGF-beta signaling, adaptive immune system regulation, gene transcription and post-transcriptional protein modification. CONCLUSION: A promising method for the detection of breast lesions is reported. This study also sheds light on breast cancer/immune system interactions, providing clues to new targets for breast cancer immune therapy.

Porphyrinic Metal-Organic Framework Nanorod-Based Dual-Modal Nanoprobe for Sensing and Bioimaging of Phosphate.

Herein, a dual-modal fluorescent/colorimetric "Signal-On" nanoprobe based on PCN-222 nanorods (NRs) toward phosphate was proposed for the first time. Due to the high affinity of the zirconium node in PCN-222 NRs for phosphate, the structure collapse of PCN-222 NRs was triggered by phosphate, resulting in the release of the tetrakis(4-carboxyphenyl)porphyrin (TCPP) ligand from PCN-222 NRs as well as the enhancement of fluorescence and absorbance signals. The PCN-222 NR-based nanoprobe could be employed for phosphate detection over a wide concentration range with a detection limit down to 23 nM. The practical application of the PCN-222 NR-based nanoprobe in real samples was evaluated. Moreover, benefitting from the good biocompatibility and water dispersibility of PCN-222 NRs, this nanoprobe was successfully employed in the intracellular imaging of phosphate, revealing its promising application in the biological science. The present work would greatly extend the potential of nanostructured MOFs in the sensing and biological fields.

An ultrasensitive and selective fluorescent nanosensor based on porphyrinic metal-organic framework nanoparticles for Cu2+ detection.

Detecting trace amounts of copper ions (Cu2+) is of high importance since copper is an essential element in the environment and the human body. Despite the recent advances in Cu2+ detection, the current approaches still suffer from insensitivity and lack of in situ detection in living cells. In the present work, a fluorescent nanosensor based on porphyrinic metal-organic framework nanoparticles (MOF-525 NPs) is proposed for sensitive and selective monitoring of Cu2+ in aqueous solution and living cells. The MOF-525 NPs with attractive properties, including ultrasmall size, good water dispersity and intense red fluorescence, are prepared via a facile and environment-friendly hydrothermal route. The fluorescence signal of MOF-525 NPs could be quenched statically by Cu2+ with high selectivity due to the strong affinity of Cu2+ to the porphyrin ligand in MOF-525. The proposed fluorescent nanosensor has a linear response in the range of 1.0-250 nM with a low detection limit of 220 pM. Furthermore, it is successfully employed for the detection of Cu2+ in water samples and the intracellular imaging of Cu2+ in living cells, demonstrating its great potential in the sensing and biological fields.

Blood-based dynamic genomic signature for obsessive-compulsive disorder.

No biologically based diagnostic criteria are in clinical use today for obsessive-compulsive disorder (OCD), schizophrenia, and major depressive disorder (MDD), which are defined with reference to Diagnostic and Statistical Manual clinical symptoms alone. However, these disorders cannot always be well distinguished on clinical grounds and may also be comorbid. A biological blood-based dynamic genomic signature that can differentiate among OCD, MDD, and schizophrenia would therefore be of great utility. This study enrolled 77 patients with OCD, 67 controls with no psychiatric illness, 39 patients with MDD, and 40 with schizophrenia. An OCD-specific gene signature was identified using blood gene expression analysis to construct a predictive model of OCD that can differentiate this disorder from healthy controls, MDD, and schizophrenia using a logistic regression algorithm. To verify that the genes selected were not derived as a result of chance, the algorithm was tested twice. First, the algorithm was used to predict the cohort with true disease/control status and second, the algorithm predicted the cohort with disease/control status randomly reassigned (null set). A six-gene panel (COPS7A, FKBP1A, FIBP, TP73-AS1, SDF4, and GOLGA8A) discriminated patients with OCD from healthy controls, MDD, and schizophrenia in the training set (with an area under the receiver-operating-characteristic curve of 0.938; accuracy, 86%; sensitivity, 88%; and specificity, 85%). Our findings indicate that a blood transcriptomic signature can distinguish OCD from healthy controls, MDD, and schizophrenia. This finding further confirms the feasibility of using dynamic blood-based genomic signatures in psychiatric disorders and may provide a useful tool for clinical staff engaged in OCD diagnosis and decision making.

Porphyrinic Metal-Organic Framework PCN-224 Nanoparticles for Near-Infrared-Induced Attenuation of Aggregation and Neurotoxicity of Alzheimer's Amyloid-ß Peptide.

The aberrant aggregation of amyloid-ß peptide (Aß) in the brain has been considered as the major pathological hallmark of Alzheimer's diseases (AD). Inhibition of Aß aggregation is considered as an attractive therapeutic intervention for alleviating amyloid-associated neurotoxicity. Here, we report the near-infrared light (NIR)-induced suppression of Aß aggregation and reduction of Aß-induced cytotoxicity via porphyrinic metal-organic framework (MOF) PCN-224 nanoparticles. PCN-224 nanoparticles are hydrothermally synthesized by coordinating tetra-kis(4-carboxyphenyl)porphyrin (TCPP) ligands with zirconium. The PCN-224 nanoparticles show high photo-oxygenation efficiency, good biocompatibility, and high stability. The study reveals that the porphyrinic MOF-based nanoprobe activated by NIR light could successfully inhibit self-assembly of monomeric Aß into a ß-sheet-rich structure. Furthermore, photoexcited PCN-224 nanoparticles also significantly reduce Aß-induced cytotoxicity under NIR irradiation.

Gene expression signature for detection of gastric cancer in peripheral blood.

Gastric cancer (stomach cancer) is the fifth most common malignancy and the third leading cause of cancer-associated mortality worldwide. Identifying gastric cancer patients at an early and curable stage of the disease is essential if mortality rates for this disease are to decrease. A non-invasive blood-based test that is an indicator of gastric cancer risk would likely be of benefit in identifying gastric cancer patients at an early stage, and such a test may enhance clinical decision making. This study identified a four-gene expression signature in peripheral blood samples associated with gastric cancer. A total of 216 blood samples were collected, including those from 36 gastric cancer patients, 55 healthy controls and 125 patients with other carcinomas, and gene expression profiles were examined using an Affymetrix Gene Profiling microarray. Blood gene expression profiles were compared between patients with stomach cancer, healthy controls and patients affected with other malignancies. A four-gene panel was identified comprising purine-rich element binding protein B, structural maintenance of chromosomes 1A, DENN/MADD domain containing 1B and programmed cell death 4. The four-gene panel discriminated gastric cancer with an area under the receiver-operating-characteristic curve of 0.99, an accuracy of 95%, sensitivity of 92% and specificity of 96%. The non-invasive nature of the blood test, together with the relatively high accuracy of the four-gene panel may assist physicians in gastric cancer screening decision making.

A graphene quantum dot@Fe3O4@SiO2 based nanoprobe for drug delivery sensing and dual-modal fluorescence and MRI imaging in cancer cells.

A novel graphene quantum dot (GQD)@Fe3O4@SiO2 based nanoprobe was reported for targeted drug delivery, sensing, dual-modal imaging and therapy. Carboxyl-terminated GQD (C-GQD) was firstly conjugated with Fe3O4@SiO2 and then functionalized with cancer targeting molecule folic acid (FA). DOX drug molecules were then loaded on GQD surface of Fe3O4@SiO2@GQD-FA nanoprobe via pi-pi stacking, which resulted in Fe3O4@SiO2@GQD-FA/DOX conjugates based on a FRET mechanism with GQD as donor molecules and DOX as acceptor molecules. Meanwhile, we successfully performed in vitro MRI and fluorescence imaging of living Hela cells and monitored intracellular drug release process using this Fe3O4@SiO2@GQD-FA/DOX nanoprobe. Cell viability study demonstrated the low cytotoxicity of Fe3O4@SiO2@GQD-FA nanocarrier and the enhanced therapeutic efficacy of Fe3O4@SiO2@GQD-FA/DOX nanoprobe for cancer cells. This luminomagnetic nanoprobe will be a potential platform for cancer accurate diagnosis and therapy.

Capillary electrophoresis coupled with in-column fiber-optic laser-induced fluorescence detection for the rapid separation of neodymium.

In this study, in-column fiber-optic (ICFO) laser-induced fluorescence (LIF) detection technique is coupled with capillary electrophoresis (CE) for the rapid separation of neodymium for the first time. The effects of buffer concentration, buffer pH, and separation voltage on the CE behaviors, including electrophoretic efficiency and detection sensitivity, are investigated in detail. Under the optimal condition determined in this study (15 mM borate buffer, pH 10.50, separation voltage 24 kV), neodymium could be separated effectively from the neighboring lanthanides (praseodymium and samarium) within several minutes, and the limit of detection for neodymium is estimated to be at the ppt level. The ICFO-LIF-CE system assembled in this study exhibits unique performance characteristics such as low cost and flexibility. Meanwhile, the separation efficiency and detection sensitivity of the assembled CE system are comparable to or somewhat better than those obtained in the previous traditional CE systems, indicating the potential of the assembled CE system for practical applications in the fields of spent nuclear fuel analysis, nuclear waste disposal/treatment, and nuclear forensics.

Facile Fabrication of Mn2O3 Nanoparticle-Assembled Hierarchical Hollow Spheres and Their Sensing for Hydrogen Peroxide.

In the present work, we described the facile hydrothermal fabrication of Mn2O3 nanoparticle-assembled hierarchical hollow spheres and their application for the electrochemical determination of hydrogen peroxide (H2O2). The composition and morphology of the as-prepared samples were well characterized by powder X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS). Because of the electrochemical responses toward H2O2, a novel nonenzymatic electrochemical sensor for the H2O2 determination based on Mn2O3 hollow spheres modified glassy carbon electrode was proposed. The electrochemical properties of the modified electrode were investigated by cyclic voltammetry, electrochemical impedance spectroscopy and chronoamperometry. The modified electrode displayed distinct amperometric response to H2O2 in a wide concentration range 0.10-1276.5 µM, with a linear range of 0.10-126.5 µM and a detection limit of 0.07 µM (S/N = 3). It exhibited excellent analytical performance in terms of long-time stability, good reproducibility and acceptable anti-interference ability. In addition, it was applied for the H2O2 determination in real samples directly with acceptable accuracy and recovery, demonstrating its potential application in routine H2O2 analysis.

Blood-based biomarkers used to predict disease activity in Crohn's disease and ulcerative colitis.

BACKGROUND: Identifying specific genes that are differentially expressed during inflammatory bowel disease flares may help stratify disease activity. The aim of this study was to identify panels of genes to be able to distinguish disease activity in Crohn's disease (CD) and ulcerative colitis (UC). METHODS: Patients were grouped into categories based on disease and severity determined by histological grading. Whole blood was collected by PAXgene Blood RNA collection tubes, (PreAnalytiX) and gene expression analysis using messenger RNA was conducted. Logistic regression was performed on multiple combinations of common probe sets, and data were evaluated in terms of discrimination by computing the area under the receiving operator characteristic curve (ROC-AUC). RESULTS: Nine inactive CD, 8 mild CD, 10 moderate-to-severe CD, 9 inactive UC, 8 mild UC, 10 moderate-to-severe UC, and 120 controls were hybridized to Affymetrix U133 Plus 2 microarrays. Panels of 6 individual genes discriminated the stages of disease activity: CD with mild severity {ROC-AUC, 0.89 (95% confidence interval [CI], 0.84%-0.95%)}, CD with moderate-to-severe severity (ROC-AUC 0.98 [95% CI, 0.97-1.0]), UC with mild severity (ROC-AUC 0.92 [95% CI, 0.87-0.96]), and UC with moderate-to-severe severity (ROC-AUC 0.99 [95% CI, 0.97-1.0]). Validation by real-time reverse transcription-PCR confirmed the Affymetrix microarray data. CONCLUSIONS: The specific whole blood gene panels reliably distinguished CD and UC and determined the activity of disease, with high sensitivity and specificity in our cohorts of patients. This simple serological test has the potential to become a biomarker to determine the activity of disease.

Mining the Dynamic Genome: A Method for Identifying Multiple Disease Signatures Using Quantitative RNA Expression Analysis of a Single Blood Sample.

BACKGROUND: Blood has advantages over tissue samples as a diagnostic tool, and blood mRNA transcriptomics is an exciting research field. To realize the full potential of blood transcriptomic investigations requires improved methods for gene expression measurement and data interpretation able to detect biological signatures within the "noisy" variability of whole blood. METHODS: We demonstrate collection tube bias compensation during the process of identifying a liver cancer-specific gene signature. The candidate probe set list of liver cancer was filtered, based on previous repeatability performance obtained from technical replicates. We built a prediction model using differential pairs to reduce the impact of confounding factors. We compared prediction performance on an independent test set against prediction on an alternative model derived by Weka. The method was applied to an independent set of 157 blood samples collected in PAXgene tubes. RESULTS: The model discriminated liver cancer equally well in both EDTA and PAXgene collected samples, whereas the Weka-derived model (using default settings) was not able to compensate for collection tube bias. Cross-validation results show our procedure predicted membership of each sample within the disease groups and healthy controls. CONCLUSION: Our versatile method for blood transcriptomic investigation overcomes several limitations hampering research in blood-based gene tests.

Detection of rare point mutation via allele-specific amplification in emulsion PCR.

It is essential to analyze rare mutations in many fields of biomedical research. However, the detection of rare mutations is usually failed due to the interference of predominant wild-type DNA surrounded. Herein we describe a sensitive and facile method of detecting rare point mutation on the basis of allele-specific amplification in emulsion PCR. The identification and selective amplification of rare mutation are accomplished in one-pot reaction. The allele-specific primers coupled on magnetic beads allow the exclusive amplification and enrichment of the mutant amplicons. The productive beads bearing mutant amplicons are subsequently stained with the fluorescent dyes. Thus, the rare point mutations with a percentage as low as 0.1%, can be detected by fluorescent analysis. The relative percentages of mutation among different samples can be roughly accessed by counting the fraction of fluorescent positive beads through flow cytometry.