Smartphone-Based Free-to-Total Prostate Specific Antigen Ratio Detection System Using a Colorimetric Reaction Integrated with Proximity-Induced Bio-Barcode and CRISPR/Cas12a Assay.

The free-to-total prostate-specific antigen (f/t-PSA) ratio is of great significance in the accurate diagnosis of prostate cancer. Herein, a smartphone-based detection system is reported using a colorimetric reaction integrated with proximity-induced bio-barcode and the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas12a assay for f/t-PSA ratio detection. DNA/antibody recognition probes are designed to bind f-PSA or t-PSA and induce the release of the DNA bio-barcode. The CRISPR/Cas12a system is activated by the DNA bio-barcode to release Ag+ from the C-Ag+-C structure of the hairpin DNA. The released Ag+ is used to affect the tetramethylbenzidine (TMB)-H2O2-based colorimetric reaction catalyzed by Pt nanoparticles (NPs), as the peroxidase-like activity of the Pt NPs can be efficiently inhibited by Ag+. A smartphone with a self-developed app is used as an image reader and analyzer to analyze the colorimetric reaction and provide the results. A limit of detection of 0.06 and 0.04 ng mL-1 is achieved for t-PSA and f-PSA, respectively. The smartphone-based method showed a linear response between 0.1 and 100 ng mL-1 of t-PSA or f-PSA. In tests with clinical samples, the smartphone-based method successfully diagnosed prostate cancer patients from benign prostatic hyperplasia patients and healthy cases with high sensitivity and specificity.

Cas13a-based multiplex RNA targeting for potato virus Y.

MAIN CONCLUSION: The Cas13a-based multiplex RNA targeting system can be engineered to confer resistance to RNA viruses, whereas the number and expression levels of gRNAs have no significant effect on viral interference. The CRISPR-Cas systems provide adaptive immunity to bacterial and archaeal species against invading phages and foreign plasmids. The class 2 type VI CRISPR/Cas effector Cas13a has been harnessed to confer the protection against RNA viruses in diverse eukaryotic species. However, whether the number and expression levels of guide RNAs (gRNAs) have effects on the efficiency of RNA virus inhibition is unknown. Here, we repurpose CRISPR/Cas13a in combination with an endogenous tRNA-processing system (polycistronic tRNA-gRNA) to target four genes of potato virus Y (PVY) with varying expression levels. We expressed Cas13a and four different gRNAs in potato lines, and the transgenic plants expressing multiple gRNAs displayed similar suppression of PVY accumulation and reduced disease symptoms as those expressing a single gRNA. Moreover, PTG/Cas13a-transformed plants with different expression levels of multiple gRNAs displayed similar resistance to PVY strains. Collectively, this study suggests that the Cas13a-based multiplex RNA targeting system can be utilized to engineer resistance to RNA viruses in plants, whereas the number and expression levels of gRNAs have no significant effect on CRISPR/Cas13a-mediated viral interference in plants.

TPQCI: A topology potential-based method to quantify functional influence of copy number variations.

Copy number variation (CNV) is a major type of chromosomal structural variation that play important roles in many diseases including cancers. Due to genome instability, a large number of CNV events can be detected in diseases such as cancer. Therefore, it is important to identify the functionally important CNVs in diseases, which currently still poses a challenge in genomics. One of the critical steps to solve the problem is to define the influence of CNV. In this paper, we provide a topology potential based method, TPQCI, to quantify this kind of influence by integrating statistics, gene regulatory associations, and biological function information. We used this metric to detect functionally enriched genes on genomic segments with CNV in breast cancer and multiple myeloma and discovered biological functions influenced by CNV. Our results demonstrate that, by using our proposed TPQCI metric, we can detect disease-specific genes that are influenced by CNVs. Source codes of TPQCI are provided in Github (https://github.com/usos/TPQCI).

Tetrahedral DNA nanostructures for effective treatment of cancer: advances and prospects.

Recently, DNA nanostructures with vast application potential in the field of biomedicine, especially in drug delivery. Among these, tetrahedral DNA nanostructures (TDN) have attracted interest worldwide due to their high stability, excellent biocompatibility, and simplicity of modification. TDN could be synthesized easily and reproducibly to serve as carriers for, chemotherapeutic drugs, nucleic acid drugs and imaging probes. Therefore, their applications include, but are not restricted to, drug delivery, molecular diagnostics, and biological imaging. In this review, we summarize the methods of functional modification and application of TDN in cancer treatment. Also, we discuss the pressing questions that should be targeted to increase the applicability of TDN in the future.

Correlation Analysis of Histopathology and Proteogenomics Data for Breast Cancer.

Tumors are heterogeneous tissues with different types of cells such as cancer cells, fibroblasts, and lymphocytes. Although the morphological features of tumors are critical for cancer diagnosis and prognosis, the underlying molecular events and genes for tumor morphology are far from being clear. With the advancement in computational pathology and accumulation of large amount of cancer samples with matched molecular and histopathology data, researchers can carry out integrative analysis to investigate this issue. In this study, we systematically examine the relationships between morphological features and various molecular data in breast cancers. Specifically, we identified 73 breast cancer patients from the TCGA and CPTAC projects matched whole slide images, RNA-seq, and proteomic data. By calculating 100 different morphological features and correlating them with the transcriptomic and proteomic data, we inferred four major biological processes associated with various interpretable morphological features. These processes include metabolism, cell cycle, immune response, and extracellular matrix development, which are all hallmarks of cancers and the associated morphological features are related to area, density, and shapes of epithelial cells, fibroblasts, and lymphocytes. In addition, protein specific biological processes were inferred solely from proteomic data, suggesting the importance of proteomic data in obtaining a holistic understanding of the molecular basis for tumor tissue morphology. Furthermore, survival analysis yielded specific morphological features related to patient prognosis, which have a strong association with important molecular events based on our analysis. Overall, our study demonstrated the power for integrating multiple types of biological data for cancer samples in generating new hypothesis as well as identifying potential biomarkers predicting patient outcome. Future work includes causal analysis to identify key regulators for cancer tissue development and validating the findings using more independent data sets.

Dual-Functionalized Ionic Liquid Biphasic Solvent for Carbon Dioxide Capture: High-Efficiency and Energy Saving.

To address the problems of high viscosity and difficult regeneration of the rich phase solution, a dual-functionalized ionic liquid ([DETAH][Tz]) was dissolved into a 1-propanol-water solvent to form a novel biphasic solvent for CO2 capture. The rich phase kept 96% of the total CO2 loading (1.713 mol mol-1) but only 44% of the total volume, and its viscosity was only 2.57 mPa s. As a regeneration promoter, 1-propanol helped the rich phase to maintain 90% of its initial loading after fifth regeneration. The high number of amine functional groups into [DETAH]+ and the equimolar reaction of [Tz]- provided the high CO2 loading, while [Tz]-H and 1-propanol ensured the high regeneration efficiency of the rich solution by enhancing the hydrolysis of RNCOO- to form HCO3-/CO32- and propyl carbonate. Due to a stronger polar and an aggregation of the CO2 absorption products in water, the CO2 products were enriched into the lower water phase while most of the 1-propanol was in the upper phase. The heat duty of [DETAH][Tz]-1-propanol-water was approximately 29.93% lower than [DETAH][Tz]-water (2.84 GJ ton-1 CO2) and 47.63% lower than MEA (3.80 GJ ton-1 CO2), which would be a promising candidate for CO2 capture.

Generation of virus-resistant potato plants by RNA genome targeting.

CRISPR/Cas systems provide bacteria and archaea with molecular immunity against invading phages and foreign plasmids. The class 2 type VI CRISPR/Cas effector Cas13a is an RNA-targeting CRISPR effector that provides protection against RNA phages. Here we report the repurposing of CRISPR/Cas13a to protect potato plants from a eukaryotic virus, Potato virus Y (PVY). Transgenic potato lines expressing Cas13a/sgRNA (small guide RNA) constructs showed suppressed PVY accumulation and disease symptoms. The levels of viral resistance correlated with the expression levels of the Cas13a/sgRNA construct in the plants. Our data further demonstrate that appropriately designed sgRNAs can specifically interfere with multiple PVY strains, while having no effect on unrelated viruses such as PVA or Potato virus S. Our findings provide a novel and highly efficient strategy for engineering crops with resistances to viral diseases.

Polyethylene Glycol-Functionalized Magnetic Fe3O4/P(MMA-AA) Composite Nanoparticles Enhancing Efficient Capture of Circulating Tumor Cells.

Circulating tumor cells (CTCs) played a significant role in early diagnosis and prognosis of carcinomas, and efficient capture of CTCs was highly desired to provide important and reliable evidence for clinical diagnosis. In present work, we successfully synthesized functional magnetic Fe3O4/P(MMA-AA) composite nanoparticles (FCNPs) inspired by a counterbalance concept for recognition and capture of CTCs. This counterbalance, composed of polyethylene glycol (PEG) suppressing cell adhesion and anti-epithelial-cell-adhesion-molecule (anti-EpCAM) antibody targeting tumor cells, could both enhance the specific capture of tumor cells and reduce unspecific adhesion of normal cells. The study showed that the PEG density on the surface of the FCNPs affected the specificity of the materials, and a density of ca. 15% was efficient for reducing the unspecific adhesion. After incubation with the mixture of HepG2 cells and Jurkat T cells, the FCNPs reached a capture efficiency as high as about 86.5% of the cancer cells, suggesting great potential on detection of CTCs in the diagnoses and prognoses of cancer metastasis.

Improving model-data mismatch for photon-counting detector model using global and local model parameters.

BACKGROUND: An energy-discriminating capability of a photon counting detector (PCD) can provide many clinical advantages, but several factors, such as charge sharing (CS) and pulse pileup (PP), degrade the capability by distorting the measured x-ray spectrum. To fully exploit the merits of PCDs, it is important to characterize the output of PCDs. Previously proposed PCD output models showed decent agreement with physical PCDs; however, there were still scopes to be improved: a global model-data mismatch and pixel-to-pixel variations. PURPOSES: In this study, we improve a PCD model by using count-rate-dependent model parameters to address the issues and evaluate agreement against physical PCDs. METHODS: The proposed model is based on the cascaded model, and we made model parameters condition-dependent and pixel-specific to deal with the global model-data mismatch and the pixel-to-pixel variation. The parameters are determined by a procedure for model parameter estimation with data acquired from different thicknesses of water or aluminum at different x-ray tube currents. To analyze the effects of having proposed model parameters, we compared three setups of our model: a model with default parameters, a model with global parameters, and a model with global-and-local parameters. For experimental validation, we used CdZnTe-based PCDs, and assessed the performance of the models by calculating the mean absolute percentage errors (MAPEs) between the model outputs and the actual measurements from low count-rates to high count-rates, which have deadtime losses of up to 24%. RESULTS: The outputs of the proposed model visually matched well with the PCD measurements for all test data. For the test data, the MAPEs averaged over all the bins were 49.2-51.1% for a model with default parameters, 8.0-9.8% for a model with the global parameters, and 1.2-2.7% for a model with the global-and-local parameters. CONCLUSION: The proposed model can estimate the outputs of physical PCDs with high accuracy from low to high count-rates. We expect that our model will be actively utilized in applications where the pixel-by-pixel accuracy of a PCD model is important.

Visual and colorimetric detection of microRNA in clinical samples based on strand displacement amplification and nanozyme-mediated CRISPR-Cas12a system.

The sensitive and accurate detection of target microRNA is especially important for the diagnosis, staging, and treatment of hepatocellular carcinoma (HCC). Herein, we report a simple strand displacement and CRISPR-Cas12a amplification strategy with nanozymes as a signal reporter for the binary visual and colorimetric detection of the HCC related microRNA. Pt@Au nanozymes with excellent peroxidase enzyme activity were prepared and linked to magnetic beads via a single-stranded DNA (ssDNA) linker. The target microRNA was designed to trigger strand displacement amplification and release a DNA promoter to activate the CRISPR-Cas12a system. The activated CRISPR-Cas12a system efficiently cleaved the linker ssDNA and released Pt@Au nanozymes from magnetic beads to induce the colorimetric reaction of 3,3',5,5'-tetramethylbenzidine. The strand displacement amplification converted the single microRNA input into abundant DNA promoter output, which improved the detection sensitivity by over two orders of magnitude. Through integration of strand displacement amplification and the nanozyme-mediated CRISPR-Cas12a system, limits of detection of 0.5 pM and 10 pM for miRNA-21 were achieved with colorimetric and visual readouts, respectively. The proposed strategy can achieve accurate quantitative detection of miRNA-21 in the range from 1 pM to 500 pM. The detection results for miRNA-21 using both colorimetric and visual readouts were validated in 40 clinical serum samples. Significantly, the proposed strategy achieved visual HCC diagnosis with the naked eye and could distinguish distinct Barcelona clinical HCC stages by colorimetric detection, showing good application prospects for sensitive and facile point-of-care testing for HCC.

Multidimensional Interactive Cascading Nanochips for Detection of Multiple Liver Diseases via Precise Metabolite Profiling.

It is challenging to detect and differentiate multiple diseases with high complexity/similarity from the same organ. Metabolic analysis based on nanomatrix-assisted laser desorption/ionization mass spectrometry (NMALDI-MS) is a promising platform for disease diagnosis, while the enhanced property of its core nanomatrix materials has plenty of room for improvement. Herein, a multidimensional interactive cascade nanochip composed of iron oxide nanoparticles (FeNPs)/MXene/gold nanoparticles (AuNPs), IMG, is reported for serum metabolic profiling to achieve high-throughput detection of multiple liver diseases. MXene serves as a multi-binding site and an electron-hole source for ionization during NMALDI-MS analysis. Introduction of AuNPs with surface plasmon resonance (SPR) properties facilitates surface charge accumulation and rapid energy conversion. FeNPs are integrated into the MXene/Au nanocomposite to sharply reduce the thermal conductivity of the nanochip with negligible heat loss for strong thermally-driven desorption, and construct a multi-interaction proton transport pathway with MXene and AuNPs for strong ionization. Analysis of these enhanced serum fingerprint signals detected from the IMG nanochip through a neural network model results in differentiation of multiple liver diseases via a single pass and revelation of potential metabolic biomarkers. The promising method can rapidly and accurately screen various liver diseases, thus allowing timely treatment of liver diseases.

Cas13d-mediated multiplex RNA targeting confers a broad-spectrum resistance against RNA viruses in potato.

CRISPR-Cas systems endow the bacterial and archaeal species with adaptive immune mechanisms to fend off invading phages and foreign plasmids. The class 2 type VI CRISPR/Cas effector Cas13d has been harnessed to confer the protection against RNA viruses in diverse eukaryotic species. However a vast number of different viruses can potentially infect the same host plant resulting in mixed infection, thus necessitating the generation of crops with broad-spectrum resistance to multiple viruses. Here we report the repurposing of CRISPR/Cas13d coupled with an endogenous tRNA-processing system (polycistronic tRNA-gRNA, PTG) to target the multiple potato RNA viruses. Expression of Cas13d and four different gRNAs were observed in transgenic potato lines expressing the Cas13d/PTG construct. We show that the Cas13d/PTG transgenic plants exhibit resistance to either PVY, PVS, PVX or PLRV alone or two/three viruses simultaneously by reducing viral accumulation in plant cells. In sum, our findings provide an efficient strategy for engineering crops that can simultaneously resist infection by multiple RNA viruses.

MnOx@N-doped carbon nanosheets derived from Mn-MOFs and g-C3N4 for peroxymonosulfate activation: Electron-rich Mn center induced by N doping.

The fabrication of metal-carbon hybrids with heteroatom doping from manganese-metal organic frameworks (MOFs) has rarely been reported for peroxymonosulfate (PMS) activation. In this work, novel MnOx@N-doped carbon (MnOx@NC) nanosheets were prepared using 2D manganese-1,4 benzenedicarboxylic acid-based MOFs (Mn-MOFs) and different proportions of graphitic carbon nitride (g-C3N4, additional N source and carbon source) to activate PMS for sulfamethoxazole (SMX) removal. The polarization difference induced by Mn-N coordination during the carbonization process made C an electron-poor center and Mn an electron-rich center, thus providing more Mn(II) for PMS activation. Benefiting from the highest Mn(II) content, the most uniform and exposed MnOx active sites, abundant N active species and rich defective sites, MnOx@NC-20 showed excellent degradation (72.9% within 5 min) and mineralization performance (47.40% within 60 min) for SMX. Nonradical and radical processes worked together in MnOx@NC-20/PMS/SMX system, where singlet oxygen (1O2) dominated the degradation of SMX. N-doped carbon not only exhibited dragging and protection effects on MnOx, but also provided adsorption sites for PMS and pollutants, thus reducing their migration distance. Moreover, the electrons of organic substrates could be captured by the electron-poor carbon layer and then transported to the electron-rich Mn center, thus improving the utilization efficiency of PMS and the redox of Mn. This study provides a facile optimization method to prepare MOFs-derived carbon catalysts with improved stability and catalytic performance.

Causal Associations Between Tobacco, Alcohol Use and Risk of Infectious Diseases: A Mendelian Randomization Study.

INTRODUCTION: The causal effects of smoking and alcohol use on the risk of infectious diseases are unclear, and it is hard investigate them in an observational study due to the potential confounding factors. The aim of this study was to use Mendelian randomization (MR) techniques to assess the causalities between smoking, alcohol use and risk of infectious diseases. METHODS: Univariable and multivariable MR analyses were performed using genome-wide association data for the age of initiation of regular smoking (AgeSmk, N = 341,427), smoking initiation (SmkInit, N = 1,232,091), cigarettes per day (CigDay, N = 337,334), lifetime smoking (LifSmk, N = 462,690), drinks per week (DrnkWk, N = 941,280), sepsis (N = 486,484), pneumonia (N = 486,484), upper respiratory tract infection (URTI, N = 486,484) and urinary tract infection (UTI, N = 486,214) among individuals of European ancestry. Independent genetic variants that were significantly (P < 5 × 10-8) associated with each exposure were considered as instruments. The inverse-variance-weighted method was used in the primary analysis, which was followed by a series of sensitivity analyses. RESULTS: Genetically predicted SmkInit was associated with an increased risk of sepsis (OR 1.353, 95% CI 1.079-1.696, P = 0.009), pneumonia (OR 1.770, 95% CI 1.464-2.141, P = 3.8 × 10-9) and UTI (OR 1.445, 95% CI 1.184-1.764, P = 3 × 10-4). Moreover, genetically predicted CigDay was associated with a higher risk of sepsis (OR 1.403, 95% CI 1.037-1.898, P = 0.028) and pneumonia (OR 1.501, 95% CI 1.167-1.930, P = 0.00156). Furthermore, genetically predicted LifSmk was associated with an increased risk of sepsis (OR 2.200, 95% CI 1.583-3.057, P = 2.63 × 10-6), pneumonia (OR 3.462, 95% CI 2.798-4.285, P = 3.28 × 10-30), URTI (OR 2.523, 95% CI 1.315-4.841, P = 0.005) and UTI (OR 2.036, 95% CI 1.585-2.616, P = 3.0 × 10-8). However, there was no significant causal evidence for genetically predicted DrnkWk in sepsis, pneumonia, URTI or UTI. Multivariable MR analyses and sensitivity analyses showed that the above results for causal association estimations were robust. CONCLUSION: In this MR study, we demonstrated the causal association between tobacco smoking and risk of infectious diseases. However, no evidence was found to support causality between alcohol use and the risk of infectious diseases.

DNA tetrahedron-based CRISPR bioassay for treble-self-amplified and multiplex HPV-DNA detection with elemental tagging.

Sensitive quantification of multiple analytes of interest is of great significance for clinical diagnosis. CRISPR Cas platforms offer a strategy for improving the specificity, sensitivity, and speed of nucleic acid-based diagnostics, while their multiplex analysis capability is still limited and challenging. Herein, we develop a novel DNA Tetrahedron (DTN)-supported biosensor based on the spatially separated CRISPR Cas self-amplification strategy and multiple-metal-nanoparticle tagging coupled with inductively coupled plasma mass spectrometry (ICP-MS) detection to improve the sensitivity and feasibility of the platform for multiplex detection of HPV-DNA (HPV-16, HPV-18 and HPV-52). Given target DNA induces robust trans-cleavage activity of the Cas12a/crRNA duplex, and the surrounding corresponding single-stranded DNA (ssDNA) linker are cleaved into short fragments that are unable to bond metal-nanoparticle probes (197Au, 107Ag, 195Pt) onto DTN modified magnetic beads probe (MBs-DTN), resulting in obvious ICP-MS signal change. Of note, compared with ssDNA functionalized MBs, a higher Signal-to-Noise Ratio was obtained by using MBs-DTN in our system, further amplifying the signal by regulating probes on the surface of MBs. As expected, the HPV-DNA could be detected with detection limits as low as 218 fM and be multiplexed assayed at one test with high accuracy and specificity by this proposed strategy. Furthermore, we demonstrated that the HPV-DNA in cervical swab samples could be detected, showing high consistency with DNA sequencing results. We believe that this work provides a promising option in designing CRISPR based multiplex detection system for high sensitivity, good specificity, and clinical molecular diagnostics.

Prediction of Prognosis, Immunotherapy and Chemotherapy with an Immune-Related Risk Score Model for Endometrial Cancer.

Endometrial cancer (EC) is the most common gynecologic cancer. The overall survival remains unsatisfying due to the lack of effective treatment screening approaches. Immunotherapy as a promising therapy has been applied for EC treatment, but still fails in many cases. Therefore, there is a strong need to optimize the screening approach for clinical treatment. In this study, we employed co-expression network (GCN) analysis to mine immune-related GCN modules and key genes and further constructed an immune-related risk score model (IRSM). The IRSM was proved effective as an independent predictor of poor prognosis. The roles of IRSM-related genes in EC were confirmed by IHC. The molecular basis, tumor immune microenvironment and clinical characteristics of the IRSM were revealed. Moreover, the IRSM effectiveness was associated with immunotherapy and chemotherapy. Patients in the low-risk group were more sensitive to immunotherapy and chemotherapy than those in the high-risk group. Interestingly, the patients responding to immunotherapy were also more sensitive to chemotherapy. Overall, we developed an IRSM which could be used to predict the prognosis, immunotherapy response and chemotherapy sensitivity of EC patients. Our analysis not only improves the treatment of EC but also offers targets for personalized therapeutic interventions.

Identify potential driver genes for PAX-FOXO1 fusion-negative rhabdomyosarcoma through frequent gene co-expression network mining.

Background: Rhabdomyosarcoma (RMS) is a soft tissue sarcoma usually originated from skeletal muscle. Currently, RMS classification based on PAX-FOXO1 fusion is widely adopted. However, compared to relatively clear understanding of the tumorigenesis in the fusion-positive RMS, little is known for that in fusion-negative RMS (FN-RMS). Methods: We explored the molecular mechanisms and the driver genes of FN-RMS through frequent gene co-expression network mining (fGCN), differential copy number (CN) and differential expression analyses on multiple RMS transcriptomic datasets. Results: We obtained 50 fGCN modules, among which five are differentially expressed between different fusion status. A closer look showed 23% of Module 2 genes are concentrated on several cytobands of chromosome 8. Upstream regulators such as MYC, YAP1, TWIST1 were identified for the fGCN modules. Using in a separate dataset we confirmed that, comparing to FP-RMS, 59 Module 2 genes show consistent CN amplification and mRNA overexpression, among which 28 are on the identified chr8 cytobands. Such CN amplification and nearby MYC (also resides on one of the above cytobands) and other upstream regulators (YAP1, TWIST1) may work together to drive FN-RMS tumorigenesis and progression. Up to 43.1% downstream targets of Yap1 and 45.8% of the targets of Myc are differentially expressed in FN-RMS vs. normal comparisons, which also confirmed the driving force of these regulators. Discussion: We discovered that copy number amplification of specific cytobands on chr8 and the upstream regulators MYC, YAP1 and TWIST1 work together to affect the downstream gene co-expression and promote FN-RMS tumorigenesis and progression. Our findings provide new insights for FN-RMS tumorigenesis and offer promising targets for precision therapy. Experimental investigation about the functions of identified potential drivers in FN-RMS are in progress.

Comprehensive evaluations of a prototype full field-of-view photon counting CT system through phantom studies.

Objective. Photon counting CT (PCCT) has been a research focus in the last two decades. Recent studies and advancements have demonstrated that systems using semiconductor-based photon counting detectors (PCDs) have the potential to provide better contrast, noise and spatial resolution performance compared to conventional scintillator-based systems. With multi-energy threshold detection, PCD can simultaneously provide the photon energy measurement and enable material decomposition for spectral imaging. In this work, we report a performance evaluation of our first CdZnTe-based prototype full-size PCCT system through various phantom imaging studies.Approach.This prototype system supports a 500 mm scan field-of-view and 10 mmz-coverage at isocenter. Phantom scans were acquired using 120 kVp from 50 to 400 mAs to assess the imaging performance on: CT number accuracy, uniformity, noise, spatial resolution, material differentiation and quantification.Main results.Both qualitative and quantitative evaluations show that PCCT, under the tested conditions, has superior imaging performance with lower noise and improved spatial resolution compared to conventional energy integrating detector (EID)-CT. Using projection domain material decomposition approach with multiple energy bin measurements, PCCT virtual monoenergetic images have lower noise, and good accuracy in quantifying iodine and calcium concentrations. These results lead to increased contrast-to-noise ratio (CNR) for both high and low contrast study objects compared to EID-CT at matched dose and spatial resolution. PCCT can also generate super-high resolution images using much smaller detector pixel size than EID-CT and greatly improve image spatial resolution.Significance.Improved spatial resolution and quantification accuracy with reduced image noise of the PCCT images can potentially lead to better diagnosis at reduced radiation dose compared to conventional EID-CT. Increased CNR achieved by PCCT suggests potential reduction in iodine contrast media load, resulting in better patient safety and reduced cost.

Removal of Sb(V) from wastewater via siliceous ferrihydrite: Interactions among ferrihydrite, coprecipitated Si, and adsorbed Sb(V).

Although ferrihydrite (Fh) exhibits good Sb(V) adsorption behavior, the instability of its amorphous structure limits its engineering applications. In this study, siliceous ferrihydrite (SiFh) was prepared via coprecipitation to resolve these limitations. X-ray diffraction (XRD), Fourier-transform infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS), and SiFh aging tests revealed that the growth of Fh particles covered with Fe-O-Si links was inhibited while maintaining their amorphous structure. Meanwhile, the XRD patterns indicated that SiFh maintained excellent stability after five adsorption-desorption cycles. During the aging process, the added Si decreased the electrostatic interaction between SiFh and Sb(V), which weakened the affinity between Sb(V) and Fh; however, most of the Sb(V) still entered the Fe lattice after seven days of aging, which was favorable for Sb(V) recovery during reutilization. Furthermore, Sb(V) adsorbed from the simulated textile wastewater onto SiFh had the highest adsorption energy (Eads), which meant its unstable inner-sphere complexation on the surface of SiFh. Meanwhile, the presence of SO42-, NO3-, Ca2+, and Mg2+ contributed to Sb(V) outer-sphere adsorption. Both of these factors were conducive to Sb(V) desorption. Hence, SiFh is a promising adsorbent owing to its facile preparation process, stability, and optimal regeneration properties.

In silico Methods for Identification of Potential Therapeutic Targets.

At the initial stage of drug discovery, identifying novel targets with maximal efficacy and minimal side effects can improve the success rate and portfolio value of drug discovery projects while simultaneously reducing cycle time and cost. However, harnessing the full potential of big data to narrow the range of plausible targets through existing computational methods remains a key issue in this field. This paper reviews two categories of in silico methods-comparative genomics and network-based methods-for finding potential therapeutic targets among cellular functions based on understanding their related biological processes. In addition to describing the principles, databases, software, and applications, we discuss some recent studies and prospects of the methods. While comparative genomics is mostly applied to infectious diseases, network-based methods can be applied to infectious and non-infectious diseases. Nonetheless, the methods often complement each other in their advantages and disadvantages. The information reported here guides toward improving the application of big data-driven computational methods for therapeutic target discovery.