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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

A ZIF-8-derived copper-nitrogen co-hybrid carbon catalyst for peroxymonosulfate activation to degrade BPA.

A series of copper-nitrogen co-hybrid porous carbon catalysts were prepared by pyrolysis of copper-doped ZIF-8 in argon atmosphere. Both the precursors and the corresponding pyrolysis products retained the polyhedral morphology of ZIF-8. The catalytic performance of the catalysts obtained at different Cu doping levels and pyrolysis temperatures for PMS activation was compared by bisphenol A (BPA) degradation experiment. Among them 5%Cu-NC(8) catalyst obtained by pyrolysis of 5%Cu-ZIF-8 at 950 °C showed the best catalytic performance. The catalytic mechanism of PMS activation catalyzed by 5%Cu-NC(8) was analyzed by quenching experiment, ESR and XPS. The degradation pathways of BPA in 5%Cu-NC(8)/PMS system were proposed on the basis of LC-MS analyses. Pyridine N (including Cu-N), graphite N, CO group and the valence change of Cu were recognized as the catalytic active sites for 5%Cu-NC(8). Both free radical and non-free radical processes were involved in BPA degradation, and singlet oxygen (1O2) was identified to be the main active substance. The stable performance and low Cu leaching rate in recycling experiment indicated that 5%Cu-NC(8) had good reusability and stability. This study provided a new insight for the design of heterogeneous copper-nitrogen co-hybrid carbon catalysts.

Pyridazine doped g-C3N4 with nitrogen defects and spongy structure for efficient tetracycline photodegradation and photocatalytic H2 evolution.

In this study, with thiourea and 3-aminopyridazine as precursors, the graphite-phase carbon nitride (ACN-x) with nitrogen defects and sponge structure is prepared via the introduction of the benzene-like ring structure of pyridazine replacing a "melem" group through hydrothermal procedure combined with calcination. It is made possible by the attraction of three hydrogen bond receptors for 3-aminopyrazine to lone pair electrons on the "melem" molecule. The remarkable extensively photocatalytic activity can be attributed to three effects of the introduction of 3-aminopyridazine: (i)formation of nitrogen defects between adjacent tri-s-triazine groups; (ii)formation of effective charge transfer channels within the tri-s-triazine group; (iii)the spongy structure exposed abundant amino groups(-NH3) at edge sites, combining with the internal amino group and as hole stabilizer to prolong the excited state life of photocatalyst. The photogenerated carrier migration and separation efficiency improved effectively through the tuning synergy. As a result, ACN-x exhibits excellent photocatalytic activity, with hydrogen production efficiency of up to 11331.74 µmol g-1 h-1, which is approximately 94.5 times that of the pristine g-C3N4 (119.88 µmol g-1 h-1). The degradation constants of TC and RhB are 0.0498min-1 and 0.129min-1, which are 3.32 and 6.35 times of the pristine g-C3N4, respectively. The TC degradation in different initial concentrations, pH, dissolved organic matter concentrations, and water sources is conducted to prove the environmental adaptability of the ACN-x system. The mechanism of the system indicates that ·O2- plays an important role, and the ·OH and h+ play a minor role in the TC photocatalytic degradation. Finally, the TC degradation possible pathway is proposed.

Interaction of Nucleic Acids with Metal-Organic Framework Nanosheets by Fluorescence Spectroscopy and Molecular Dynamics Simulations.

The integration of nanomaterials and nucleic acids has attracted great attention in various research fields, especially biomedical applications. Designing two-dimensional nanomaterials and studying the mechanism of their interaction with nucleic acids are still attractive tasks. Herein, we designed and prepared a class of ultrathin two-dimensional metal-organic framework (MOF) nanosheets, named Zr-BTB MOF nanosheets, composed of Zr-O clusters and 1,3,5-benzenetribenzoate by a bottom-up synthesis strategy. The Zr-BTB MOF nanosheets possessed inherent excellent performance such as a high specific surface area, porosity, and biocompatibility. In addition, we clarified the interaction difference between the Zr-BTB MOF nanosheets and fluorophore-labeled double-stranded DNA and single-stranded DNA via molecular dynamics simulations and fluorescence measurement. Through molecular dynamics simulations, specific interactions between DNA and nanosheets such as forces, binding energies, and binding modes were deeply analyzed and clearly presented. Based on the affinity difference, the system showed the biosensing potential for target DNA detection with considerable specificity, sensitivity, and linearity. Our research results presented the Zr-BTB MOF nanosheet as a platform for nucleic acid detection, showing the potential for hybridization-based biosensing and related biological applications.

Oxygen-containing groups and P doped porous carbon nitride nanosheets towards enhanced photocatalytic activity.

Metal-free polymer graphite carbon nitride (CN) is a promising photocatalyst that has garnered significant research attention. However, unmodified CN possesses several shortcomings such as low specific surface area, poor dispersibility in water, and rapid photogenerated electron-hole recombination, which have severely impacted its mass adoption. Here, this study proposed a two-step heat treatment method to incorporate P dopant and the containing-oxygen groups successively into CN. The final product, denoted as PO-CN, possessed a porous ultrathin nanosheet-like morphology. The introduction of P dopant altered the intrinsic electronic structure of CN. Meanwhile, the presence of oxygen-containing groups improved the dispersibility of PO-CN in water. Also, it led to the formation of a porous ultrathin structure that could provide more active sites. Through the synergistic effects of these two methods, PO-CN demonstrated superior photocatalytic performance compared to the unmodified counterpart. Based on the collective results obtained experimentally and theoretically, PO-CN possessed a porous ultrathin structure, low resistance, and low carrier recombination. The results show an optimal hydrogen evolution rate of PO-CN (997.7 mol h-1 g-1), which was 11.2 times and 3.22 times that of the CN (88.89 mol h-1 g-1) and PCN (310.3 mol h-1 g-1). Moreover, PO-CN was then used in the degradation of Rhodamine B, and a degradation kinetic constant (k) of 0.15009 was calculated, which was 18.42 times and 8.22 times higher as compared to those of CN (0.00815) and PCN (0.01826). Hence, this work provides a new strategy for the alteration of the morphology and electronic structure of CN.

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.

NFAT as a Biomarker and Therapeutic Target in Non-Small Cell Lung Cancer-Related Brain Metastasis.

BACKGROUND: Brain metastases (BMs) are associated with poor prognosis and significant mortality, and approximately 25% of patients with non-small cell lung cancer (NSCLC) develop BMs. The present study was aimed to understand the relationships between BM and NSCLC and reveal potential biomarkers and therapeutic targets in NSCLC-related BM. METHODS: The differentially expressed genes (DEGs) expressed during NSCLC and BM development were predicted by bioinformatics analysis, and the expression of the upstream transcription factor nuclear factor of activated T cells (NFAT) was confirmed as a differential gene expressed in both NSCLC and BM. In addition, the expression of proteins encoded by these DEGs was verified by immunohistochemical experiments examining normal lung tissue, lung cancer tissue, and brain metastasis tissue from 30 patients with NSCLC related BM. RESULTS: The co-DEGs interleukin (IL)-11, cadherin 5 (CDH5) and C-C motif chemokine 2 (CCL2) link NSCLC and BM in the Gene Expression Omnibus (GEO) database, and NFAT may target the expression of these co-DEGs. In the GEO database, NFATc1 and NFATc3 were significantly downregulated in NSCLC tissues (P <.05), whereas NFATc1, NFATc2, NFATc3, and NFATc4 were significantly downregulated in BMs (P <.05). Consistent findings were observed in the immunohistochemical analysis. CONCLUSION: NFATc1 and NFATc3 may play important roles in the occurrence of NSCLC and BM by regulating IL-11, CDH5, and CCL2.

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.