The Hybrid of Cu─TCPP@Mn3 O4 for Inflammation Relief by ROS Scavenging and O2 Production: An Efficient Strategy for Antiviral Therapy.

Seasonal influenza still greatly threatens public health worldwide, leading to significant morbidity and mortality. Antiviral medications for influenza treatment are limited and accompanied by increased drug resistance. In severe influenza virus infection, hyperinflammation and hypoxia may be the significant threats associated with mortality, so the development of effective therapeutic methods to alleviate excessive inflammation while reducing viral damage is highly pursued. Here, a multifunctional MOF-based nanohybrid of Cu─TCPP@Mn3 O4 as a novel drug against influenza A virus infection (MOF = metal-organic framework; TCPP = tetrakis (4-carboxyphenyl) porphyrin) is designed. Cu─TCPP@Mn3 O4 exhibits potent inhibitory capability against influenza A virus infection in vitro and in vivo. The mechanism study reveals that Cu─TCPP@Mn3 O4 inhibits the virus entry by binding to the HA2 subunit of influenza A virus hemagglutinin. In addition, the nanoparticles of Mn3 O4 in Cu─TCPP@Mn3 O4 can scavenge intracellular ROS with O2 generation to downregulate inflammatory factors and effectively inhibit cytokines production. By reconstructing the antioxidant microenvironment, Cu─TCPP@Mn3 O4 features as a promising nanomedicine with anti-inflammatory and anti-viral synergistic effects.

Nanoscale Two-Dimensional FeII- and CoII-Based Metal-Organic Frameworks of Porphyrin Ligand for the Photodynamic Therapy of Breast Cancer.

The delivery of biocompatible reagents into cancer cells can elicit an anticancer effect by taking advantage of the unique characteristics of the tumor microenvironment (TME). In this work, we report that nanoscale two-dimensional FeII- and CoII-based metal-organic frameworks (NMOFs) of porphyrin ligand meso-tetrakis (6-(hydroxymethyl) pyridin-3-yl) porphyrin (THPP) can catalyze the generation of hydroxyl radicals (•OH) and O2 in the presence of H2O2 that is overexpressed in the TME. Photodynamic therapy consumes the generated O2 to produce a singlet oxygen (1O2). Both •OH and 1O2 are reactive oxygen species (ROS) that inhibit cancer cell proliferation. The FeII- and CoII-based NMOFs were non-toxic in the dark but cytotoxic when irradiated with 660 nm light. This preliminary work points to the potential of porphyrin-based ligands of transition metals as anticancer drugs by synergizing different therapeutic modalities.

Synergistic photothermal-photodynamic-chemotherapy toward breast cancer based on a liposome-coated core-shell AuNS@NMOFs nanocomposite encapsulated with gambogic acid.

A multifunctional nanoplatform with core-shell structure was constructed in one-pot for the synergistic photothermal, photodynamic, and chemotherapy against breast cancer. In the presence of gambogic acid (GA) as the heat-shock protein 90 (HSP90) inhibitor and the gold nanostars (AuNS) as the photothermal reagent, the assembly of Zr4+ with tetrakis (4-carboxyphenyl) porphyrin (TCPP) gave rise to the nanocomposite AuNS@ZrTCPP-GA (AZG), which in turn, further coated with PEGylated liposome (LP) to enhance the stability and biocompatibility, and consequently the antitumor effect of the particle. Upon cellular uptake, the nanoscale metal - organic framework (NMOF) of ZrTCPP in the resulted AuNS@ZrTCPP-GA@LP (AZGL) could be slowly degraded in the weak acidic tumor microenvironment to release AuNS, Zr4+, TCPP, and GA to exert the synergistic treatment of tumors via the combination of AuNS-mediated mild photothermal therapy (PTT) and TCPP-mediated photodynamic therapy (PDT). The introduction of GA serves to reduce the thermal resistance of the cell to re-sensitize PTT and the constructed nanoplatform demonstrated remarkable anti-tumor activity in vitro and in vivo. Our work highlights a facile strategy to prepare a pH-dissociable nanoplatform for the effective synergistic treatment of breast cancer.

Reprogramming of the tumor microenvironment using a PCN-224@IrNCs/D-Arg nanoplatform for the synergistic PDT, NO, and radiosensitization therapy of breast cancer and improving anti-tumor immunity.

The low X-ray attenuation coefficient of tumor soft tissue and the hypoxic tumor microenvironment (TME) during radiation therapy (RT) of breast cancer result in RT resistance and thus reduced therapeutic efficacy. In addition, immunosuppression induced by the TME severely limits the antitumor immunity of radiation therapy. In this paper, we propose a PCN-224@IrNCs/D-Arg nanoplatform for the synergistic radiosensitization, photodynamic, and NO therapy of breast cancer that also boosts antitumor immunity (PCN = porous coordination network, IrNCs = iridium nanocrystals, D-Arg = D-arginine). The local tumors can be selectively ablated via reprogramming the tumor microenvironment (TME), photodynamic therapy (PDT) and NO therapy, and the presence of the high-Z element Ir that sensitizes radiotherapy. The synergistic execution of these treatment modalities also resulted in adapted antitumor immune response. The intrinsic immunomodulatory effects of the nanoplatform also repolarize macrophages toward the M1 phenotype and induce dendritic cell maturation, activating antitumor T cells to induce immunogenic cell death as demonstrated in vitro and in vivo. The nanocomposite design reported herein represents a new regimen for the treatment of breast cancer through TME reprogramming to exert a synergistic effect for effective cancer therapy and antitumor immunity.

NIR-PTT/ROS-Scavenging/Oxygen-Enriched Synergetic Therapy for Rheumatoid Arthritis by a pH-Responsive Hybrid CeO2-ZIF-8 Coated with Polydopamine.

Rheumatoid arthritis (RA) is an inflammatory type of arthritis that causes joint pain and damage. The inflammatory cell infiltration (e.g., M1 macrophages), the poor O2 supply at the joint, and the excess reactive oxygen species (ROS)-induced oxidative injury are the main causes of RA. We herein report a polydopamine (PDA)-coated CeO2-dopped zeolitic imidazolate framework-8 (ZIF-8) nanocomposite CeO2-ZIF-8@PDA (denoted as CZP) that can synergistically treat RA. Under near-infrared (NIR) light irradiation, PDA efficiently scavenges ROS and results in an increased temperature in the inflamed area because of its good light-to-heat conversion efficiency. The rise of temperature serves to obliterate hyper-proliferative inflammatory cells accumulated in the diseased area while vastly promoting the collapse of the acidic-responsive skeleton of ZIF-8 to release the encapsulated CeO2. The released CeO2 exerts its catalase-like activity to relieve hypoxia by generating oxygen via the decomposition of H2O2 highly expressed in the inflammatory sites. Thus, the constructed CZP composite can treat RA through NIR-photothermal/ROS-scavenging/oxygen-enriched combinative therapy and show good regression of pro-inflammatory cytokines and hypoxia-inducible factor-1α (HIF-1α) in vitro and promising therapeutic effect on RA in rat models. The multimodal nano-platform reported herein is expected to shed light on the design of synergistic therapeutic nanomedicine for effective RA therapy.

Modeling and analyzing complex biological networks incooperating experimental information on both network topology and stable states.

MOTIVATION: Linking the topology of a complex network to its long-term behavior is a basic problem in network theory, which has been on the focus of many recent research publications. To obtain a suitable Boolean model for a biological system, one must analyze the initial model and compare it with other experimental evidence, and if necessary, make adjustments by changing the topology of the wiring diagram. However, our knowledge on how to link the topology of a network to its long-term behavior is very limited due to the complexity of the problem. Since the need to consider complex biological networks has become ever greater, develop both theoretical foundation and algorithms for model selection and analysis has been brought to the forefront of biological network study. RESULTS: This article proposes a novel method to study intrinsically the relationship between experimental data and the possible Boolean networks, which can be used to model the underlying system. Simple and easy to use criteria for a Boolean network to have both a given network topology and a given set of stable states are derived. These criteria can be used to guide the selection of a Boolean network model for the system, as well as to gain information on the intrinsic properties, such as the robustness and the evolvability, of the system. A Boolean model for the fruit fly Drosophila melanogaster is used to explain the method.

Blood Gene Expression Profile Study Revealed the Activation of Apoptosis and p53 Signaling Pathway May Be the Potential Molecular Mechanisms of Ionizing Radiation Damage and Radiation-Induced Bystander Effects.

Radiotherapy is an effective treatment for local solid tumors, but the mechanism of damage to human body caused by radiation therapy needs further study. In this study, gene expression profiles of human peripheral blood samples exposed to different doses and rates of ionizing radiation (IR) were used for bioinformatics analysis to investigate the mechanism of IR damage and radiation-induced bystander effect (RIBE). Differentially expressed genes analysis, weighted gene correlation network analysis, functional enrichment analysis, hypergeometric test, gene set enrichment analysis, and gene set variation analysis were applied to analyze the data. Moreover, receiver operating characteristic curve analysis was performed to identify core genes of IR damage. Weighted gene correlation network analysis identified 3 modules associated with IR damage, 2 were positively correlated and 1 was negatively correlated. The analysis showed that the positively correlated modules were significantly involved in apoptosis and p53 signaling pathway, and ESR1, ATM, and MYC were potential transcription factors regulating these modules. Thus, the study suggested that apoptosis and p53 signaling pathway may be the potential molecular mechanisms of IR damage and RIBE, which could be driven by ESR1, ATM, and MYC.

Promoter DNA methylation analysis reveals a novel diagnostic CpG-based biomarker and RAB25 hypermethylation in clear cell renel cell carcinoma.

Clear-cell renal cell carcinoma (ccRCC) is a common aggressive urinary malignant tumor that cannot be easily diagnosed at an early stage. The DNA methylation occurs within promoter before precancerous lesion plays a pivotal role that could help us in diagnosing and understanding ccRCC. In this study, based on a whole-genome promoter DNA methylation profiling, we used shrunken centroids classifier method to identify a CpG-based biomarker that is capable of differentiating between ccRCC tumor and adjacent tissues. The biomarker was validated in 19 ccRCCs and three public datasets. We found that both CYP4B1 and RAB25 are downregulated with promoter hypermethylation and CA9 is upregulated with promoter hypomethylation, and we validated their mRNA differential expressions in 19 ccRCCs and 10 GEO datasets. We further confirmed that hypermethylated RAB25 is inversely correlated with its mRNA level. Log-rank test showed that ccRCC patients with low levels of CA9 promoter methylation had a higher survival rate. This reveals clinically a potential biomarker for use in early detection for ccRCC, and provides a better understanding of carcinogenesis.

Gaussian binomials and the number of sublattices.

The purpose of this short communication is to make some observations on the connections between various existing formulas of counting the number of sublattices of a fixed index in an n-dimensional lattice and their connection with the Gaussian binomials.

Indices of coincidence isometries of the hypercubic lattice Z n.

The problem of computing the index of a coincidence isometry of the hypercubic lattice Z{n} is considered. The normal form of a rational orthogonal matrix is analyzed in detail and explicit formulas for the indices of certain coincidence isometries of Z{n} are obtained. These formulas generalize the known results for n < or = 4.

Structures of coincidence symmetry groups.

The structure of the coincidence symmetry group of an arbitrary n-dimensional lattice in the n-dimensional Euclidean space is considered by describing a set of generators. Particular attention is given to the coincidence isometry subgroup (the subgroup formed by those coincidence symmetries that are elements of the orthogonal group). Conditions under which the coincidence isometry group can be generated by reflections defined by vectors of the lattice are discussed and an algorithm to decompose an arbitrary element of the coincidence isometry group in terms of reflections defined by vectors of the lattice is given.

Integrated network model provides new insights into castration-resistant prostate cancer.

Castration-resistant prostate cancer (CRPC) is the main challenge for prostate cancer treatment. Recent studies have indicated that extending the treatments to simultaneously targeting different pathways could provide better approaches. To better understand the regulatory functions of different pathways, a system-wide study of CRPC regulation is necessary. For this purpose, we constructed a comprehensive CRPC regulatory network by integrating multiple pathways such as the MEK/ERK and the PI3K/AKT pathways. We studied the feedback loops of this network and found that AKT was involved in all detected negative feedback loops. We translated the network into a predictive Boolean model and analyzed the stable states and the control effects of genes using novel methods. We found that the stable states naturally divide into two obvious groups characterizing PC3 and DU145 cells respectively. Stable state analysis further revealed that several critical genes, such as PTEN, AKT, RAF, and CDKN2A, had distinct expression behaviors in different clusters. Our model predicted the control effects of many genes. We used several public datasets as well as FHL2 overexpression to verify our finding. The results of this study can help in identifying potential therapeutic targets, especially simultaneous targets of multiple pathways, for CRPC.

Integrated Analysis Reveals together miR-182, miR-200c and miR-221 Can Help in the Diagnosis of Prostate Cancer.

Research has shown that microRNAs are promising biomarkers that can be used to promote a more accurate diagnosis of cancer. In this study, we developed an integrated multi-step selection process to analyze available high-throughput datasets to obtain information on microRNAs as cancer biomarkers. Applying this approach to the microRNA expression profiles of prostate cancer and the datasets in The Cancer Genome Atlas Data Portal, we identified miRNA-182, miRNA-200c and miRNA-221 as possible biomarkers for prostate cancer. The associations between the expressions of these three microRNAs with clinical parameters as well as their diagnostic capability were studied. Several online databases were used to predict the target genes of these three microRNAs, and the results were confirmed by significant statistical correlations. Comparing with the other 18 types of cancers listed in The Cancer Genome Atlas Data Portal, we found that the combination of both miRNA-182 and miRNA-200c being up-regulated and miRNA-221 being down-regulated only happens in prostate cancer. This provides a unique biological characteristic for prostate cancer that can potentially be used for diagnosis based on tissue testing. In addition, our study also revealed that these three microRNAs are associated with the pathological status of prostate cancer.

Boolean networks with multiexpressions and parameters.

To model biological systems using networks, it is desirable to allow more than two levels of expression for the nodes and to allow the introduction of parameters. Various modeling and simulation methods addressing these needs using Boolean models, both synchronous and asynchronous, have been proposed in the literature. However, analytical study of these more general Boolean networks models is lagging. This paper aims to develop a concise theory for these different Boolean logic-based modeling methods. Boolean models for networks where each node can have more than two levels of expression and Boolean models with parameters are defined algebraically with examples provided. Certain classes of random asynchronous Boolean networks and deterministic moduli asynchronous Boolean networks are investigated in detail using the setting introduced in this paper. The derived theorems provide a clear picture for the attractor structures of these asynchronous Boolean networks.

Determination of fiber orientation in MRI diffusion tensor imaging based on higher-order tensor decomposition.

High Angular Resolution Diffusion Imaging (HARDI) techniques have been used for resolving multiple fiber directions within a voxel. Using HARDI, a high-order tensor can be obtained through generalized diffusion tensor imaging (GDTI). In this paper, based on the decomposition of the high-order diffusion tensors, a mathematical technique is presented which permits accurate resolution of multiple, randomly-oriented fiber tracts within tissue. A sequence of pseudo-eigenvalues and pseudo-eigenvectors are derived from the diffusion tensor through successive application of a best least-square rank-1 tensor approximation. These pseudo-eigenvalues and pseudo-eigenvectors are used to identify the major fiber directions within an individual image voxel. Results of a numerical simulation are presented to demonstrate the technique.