PheMIME: An Interactive Web App and Knowledge Base for Phenome-Wide, Multi-Institutional Multimorbidity Analysis.

Motivation: Multimorbidity, characterized by the simultaneous occurrence of multiple diseases in an individual, is an increasing global health concern, posing substantial challenges to healthcare systems. Comprehensive understanding of disease-disease interactions and intrinsic mechanisms behind multimorbidity can offer opportunities for innovative prevention strategies, targeted interventions, and personalized treatments. Yet, there exist limited tools and datasets that characterize multimorbidity patterns across different populations. To bridge this gap, we used large-scale electronic health record (EHR) systems to develop the Phenome-wide Multi-Institutional Multimorbidity Explorer (PheMIME), which facilitates research in exploring and comparing multimorbidity patterns among multiple institutions, potentially leading to the discovery of novel and robust disease associations and patterns that are interoperable across different systems and organizations. Results: PheMIME integrates summary statistics from phenome-wide analyses of disease multimorbidities. These are currently derived from three major institutions: Vanderbilt University Medical Center, Mass General Brigham, and the UK Biobank. PheMIME offers interactive exploration of multimorbidity through multi-faceted visualization. Incorporating an enhanced version of associationSubgraphs, PheMIME enables dynamic analysis and inference of disease clusters, promoting the discovery of multimorbidity patterns. Once a disease of interest is selected, the tool generates interactive visualizations and tables that users can delve into multimorbidities or multimorbidity networks within a single system or compare across multiple systems. The utility of PheMIME is demonstrated through a case study on schizophrenia. Availability and implementation: The PheMIME knowledge base and web application are accessible at https://prod.tbilab.org/PheMIME/. A comprehensive tutorial, including a use-case example, is available at https://prod.tbilab.org/PheMIME_supplementary_materials/. Furthermore, the source code for PheMIME can be freely downloaded from https://github.com/tbilab/PheMIME. Data availability statement: The data underlying this article are available in the article and in its online web application or supplementary material.

Introduction of medical genomics and clinical informatics integration for p-Health care.

Achieving predictive, precise, participatory, preventive, and personalized health (abbreviated as p-Health) requires comprehensive evaluations of an individual's conditions captured by various measurement technologies. Since the 1950s, analysis of care providers' and physicians' notes and measurement data by computers to improve healthcare delivery has been termed clinical informatics. Since the 2010s, wide adoptions of Electronic Health Records (EHRs) have greatly improved clinical informatics development with fast growing pervasive wearable technologies that continuously capture the human physiological profile in-clinic (EHRs) and out-of-clinic (PHRs or Personal Health Records) to bolster mobile health (mHealth). In addition, after the Human Genome Project in the 1990s, medical genomics has emerged to capture the high-throughput molecular profile of a person. As a result, integrated data analytics is becoming one of the fast-growing areas under Biomedical Big Data to improve human healthcare outcomes. In this chapter, we first introduce the scope of data integration and review applications, data sources, and tools for clinical informatics and medical genomics. We then describe the data integration analytics at the raw data level, feature level, and decision level with case studies, and the opportunity for research and translation using advanced artificial intelligence (AI), such as deep learning. Lastly, we summarize the opportunities in biomedical big data integration that can reshape healthcare toward p-health.

Gadolinium-Encapsulated Graphene Carbon Nanotheranostics for Imaging-Guided Photodynamic Therapy.

Photosensitizers (PS) are an essential component of photodynamic therapy (PDT). Conventional PSs are often porphyrin derivatives, which are associated with high hydrophobicity, low quantum yield in aqueous solutions, and suboptimal tumor-to-normal-tissue (T/N) selectivity. There have been extensive efforts to load PSs into nanoparticle carriers to improve pharmacokinetics. The approach, however, is often limited by PS self-quenching, pre-mature release, and nanoparticle accumulation in the reticuloendothelial system organs. Herein, a novel, nanoparticle-based PS made of gadolinium-encapsulated graphene carbon nanoparticles (Gd@GCNs), which feature a high 1 O2 quantum yield, is reported. Meanwhile, Gd@GCNs afford strong fluorescence and high T1 relaxivity (16.0 × 10-3 m-1 s-1 , 7 T), making them an intrinsically dual-modal imaging probe. Having a size of approximately 5 nm, Gd@GCNs can accumulate in tumors through the enhanced permeability and retention effect. The unbound Gd@GCNs cause little toxicity because Gd is safely encapsulated within an inert carbon shell and because the particles are efficiently excreted from the host through renal clearance. Studies with rodent tumor models demonstrate the potential of the Gd@GCNs to mediate image-guided PDT for cancer treatment. Overall, the present study shows that Gd@GCNs possess unique physical, pharmaceutical, and toxicological properties and are an all-in-one nanotheranostic tool with substantial clinical translation potential.

LiGa5O8:Cr-based theranostic nanoparticles for imaging-guided X-ray induced photodynamic therapy of deep-seated tumors.

Using X-ray as the irradiation source, a photodynamic therapy process can be initiated from under deep tissues. This technology, referred to as X-ray induced PDT, or X-PDT, holds great potential to treat tumors at internal organs. To this end, one question is how to navigate the treatment to tumors with accuracy with external irradiation. Herein we address the issue with a novel, LiGa5O8: Cr (LGO:Cr)-based nanoscintillator, which emits persistent, near-infrared X-ray luminescence. This permits deep-tissue optical imaging that can be employed to guide irradiation. Specifically, we encapsulated LGO:Cr nanoparticles and a photosensitizer, 2,3-naphthalocyanine, into mesoporous silica nanoparticles. The nanoparticles were conjugated with cetuximab and systemically injected into H1299 orthotopic non-small cell lung cancer tumor models. The nanoconjugates can efficiently home to tumors in the lung, confirmed by monitoring X-ray luminescence from LGO:Cr. Guided by the imaging, external irradiation was applied, leading to efficient tumor suppression while minimally affecting normal tissues. To the best of our knowledge, the present study is the first to demonstrate, with systematically injected nanoparticles, that X-PDT can suppress growth of deep-seated tumors. The imaging guidance is also new to X-PDT, and is significant to the further transformation of the technology.

X-Ray Induced Photodynamic Therapy: A Combination of Radiotherapy and Photodynamic Therapy.

Conventional photodynamic therapy (PDT)'s clinical application is limited by depth of penetration by light. To address the issue, we have recently developed X-ray induced photodynamic therapy (X-PDT) which utilizes X-ray as an energy source to activate a PDT process. In addition to breaking the shallow tissue penetration dogma, our studies found more efficient tumor cell killing with X-PDT than with radiotherapy (RT) alone. The mechanisms behind the cytotoxicity, however, have not been elucidated. In the present study, we investigate the mechanisms of action of X-PDT on cancer cells. Our results demonstrate that X-PDT is more than just a PDT derivative but is essentially a PDT and RT combination. The two modalities target different cellular components (cell membrane and DNA, respectively), leading to enhanced therapy effects. As a result, X-PDT not only reduces short-term viability of cancer cells but also their clonogenecity in the long-run. From this perspective, X-PDT can also be viewed as a unique radiosensitizing method, and as such it affords clear advantages over RT in tumor therapy, especially for radioresistant cells. This is demonstrated not only in vitro but also in vivo with H1299 tumors that were either subcutaneously inoculated or implanted into the lung of mice. These findings and advances are of great importance to the developments of X-PDT as a novel treatment modality against cancer.

Gd and Eu Co-Doped Nanoscale Metal-Organic Framework as a T1-T2 Dual-Modal Contrast Agent for Magnetic Resonance Imaging.

Recently, a growing interest has been seen in the development of T1-T2 dual-mode probes that can simultaneously enhance contrast on T1- and T2-weighted images. A common strategy is to integrate T1 and T2 components in a decoupled manner into a nanoscale particle. This approach, however, often requires a multi-step synthesis and delicate nanoengineering, which may potentially affect the production and wide application of the probes. We herein report the facile synthesis of a 50-nm nanoscale metal-organic framework (NMOF) comprising gadolinium (Gd3+) and europium (Eu3+) as metallic nodes. These nanoparticles can be prepared in large quantities and can be easily coated with a layer of silica. The yielded Eu,Gd-NMOF@SiO2 nanoparticles are less toxic, highly fluorescent, and afford high longitudinal (38 mM-1s-1) and transversal (222 mM-1s-1) relaxivities on a 7 T magnet. The nanoparticles were conjugated with c(RGDyK), a tumor-targeting peptide sequence, which has a high binding affinity toward integrin αvß3. Eu,Gd-NMOF@SiO2 nanoparticles, when intratumorally or intravenously injected, induce simultaneous signal enhancement and signal attenuation on T1-and T2-weighted images, respectively. These results suggest great potential of the NMOFs as a novel T1-T2 dual-mode contrast agent.

Red Blood Cell-Facilitated Photodynamic Therapy for Cancer Treatment.

Photodynamic therapy (PDT) is a promising treatment modality for cancer management. So far, most PDT studies have focused on delivery of photosensitizers to tumors. O2, another essential component of PDT, is not artificially delivered but taken from the biological milieu. However, cancer cells demand a large amount of O2 to sustain their growth and that often leads to low O2 levels in tumors. The PDT process may further potentiate the oxygen deficiency, and in turn, adversely affect the PDT efficiency. In the present study, a new technology called red blood cell (RBC)-facilitated PDT, or RBC-PDT, is introduced that can potentially solve the issue. As the name tells, RBC-PDT harnesses erythrocytes, an O2 transporter, as a carrier for photosensitizers. Because photosensitizers are adjacent to a carry-on O2 source, RBC-PDT can efficiently produce 1O2 even under low oxygen conditions. The treatment also benefits from the long circulation of RBCs, which ensures a high intraluminal concentration of photosensitizers during PDT and hence maximizes damage to tumor blood vessels. When tested in U87MG subcutaneous tumor models, RBC-PDT shows impressive tumor suppression (76.7%) that is attributable to the codelivery of O2 and photosensitizers. Overall, RBC-PDT is expected to find wide applications in modern oncology.

Casein-Coated Fe5C2 Nanoparticles with Superior r2 Relaxivity for Liver-Specific Magnetic Resonance Imaging.

Iron oxide nanoparticles have been extensively used as T2 contrast agents for liver-specific magnetic resonance imaging (MRI). The applications, however, have been limited by their mediocre magnetism and r2 relaxivity. Recent studies show that Fe5C2 nanoparticles can be prepared by high temperature thermal decomposition. The resulting nanoparticles possess strong and air stable magnetism, suggesting their potential as a novel type of T2 contrast agent. To this end, we improve the synthetic and surface modification methods of Fe5C2 nanoparticles, and investigated the impact of size and coating on their performances for liver MRI. Specifically, we prepared 5, 14, and 22 nm Fe5C2 nanoparticles and engineered their surface by: 1) ligand addition with phospholipids, 2) ligand exchange with zwitterion-dopamine-sulfonate (ZDS), and 3) protein adsorption with casein. It was found that the size and surface coating have varied levels of impact on the particles' hydrodynamic size, viability, uptake by macrophages, and r2 relaxivity. Interestingly, while phospholipid- and ZDS-coated Fe5C2 nanoparticles showed comparable r2, the casein coating led to an r2 enhancement by more than 2 fold. In particular, casein coated 22 nm Fe5C2 nanoparticle show a striking r2 of 973 mM(-1)s(-1), which is one of the highest among all of the T2 contrast agents reported to date. Small animal studies confirmed the advantage of Fe5C2 nanoparticles over iron oxide nanoparticles in inducing hypointensities on T2-weighted MR images, and the particles caused little toxicity to the host. The improvements are important for transforming Fe5C2 nanoparticles into a new class of MRI contrast agents. The observations also shed light on protein-based surface modification as a means to modulate contrast ability of magnetic nanoparticles.

Nanoscintillator-mediated X-ray inducible photodynamic therapy for in vivo cancer treatment.

Photodynamic therapy is a promising treatment method, but its applications are limited by the shallow penetration of visible light. Here, we report a novel X-ray inducible photodynamic therapy (X-PDT) approach that allows PDT to be regulated by X-rays. Upon X-ray irradiation, the integrated nanosystem, comprised of a core of a nanoscintillator and a mesoporous silica coating loaded with photosensitizers, converts X-ray photons to visible photons to activate the photosensitizers and cause efficient tumor shrinkage.

Gd-encapsulated carbonaceous dots with efficient renal clearance for magnetic resonance imaging.

Nanoprobes for MRI and optical imaging are demonstrated. Gd@C-dots possess strong fluorescence and can effectively enhance signals on T1 -weighted MR images. The nanoprobes have low toxicity, and, despite a relatively large size, can be efficiently excreted by renal clearance from the host after systemic injection.

Iron oxide nanoparticle encapsulated diatoms for magnetic delivery of small molecules to tumors.

Small molecules can be co-loaded with iron oxide nanoparticles onto diatoms. With an external magnetic field, the diatoms, after systemic administration, can be attracted to tumors. This study suggests a great potential of diatoms as a novel and powerful therapeutic vehicle.

RGD-modified apoferritin nanoparticles for efficient drug delivery to tumors.

Ferritin (FRT) is a major iron storage protein found in humans and most living organisms. Each ferritin is composed of 24 subunits, which self-assemble to form a cage-like nanostructure. FRT nanocages can be genetically modified to present a peptide sequence on the surface. Recently, we demonstrated that Cys-Asp-Cys-Arg-Gly-Asp-Cys-Phe-Cys (RGD4C)-modified ferritin can efficiently home to tumors through RGD-integrin αvß3 interaction. Though promising, studies on evaluating surface modified ferritin nanocages as drug delivery vehicles have seldom been reported. Herein, we showed that after being precomplexed with Cu(II), doxorubicin can be loaded onto RGD modified apoferritin nanocages with high efficiency (up to 73.49 wt %). When studied on U87MG subcutaneous tumor models, these doxorubicin-loaded ferritin nanocages showed a longer circulation half-life, higher tumor uptake, better tumor growth inhibition, and less cardiotoxicity than free doxorubicin. Such a technology might be extended to load a broad range of therapeutics and holds great potential in clinical translation.

In vivo high-frequency, contrast-enhanced ultrasonography of uveal melanoma in mice: imaging features and histopathologic correlations.

PURPOSE: To evaluate the usefulness of in vivo imaging of uveal melanoma in mice using high-frequency contrast-enhanced ultrasound (HF-CE-US) with 2D or 3D modes and to correlate the sonographic findings with histopathologic characteristics. METHODS: Fourteen 12-week-old C57BL6 mice were inoculated into their right eyes with aliquots of 5 × 10(5)/2.5 µL B16LS9 melanoma cells and were randomly assigned to either of two groups. At 7 days after inoculation, tumor-bearing eyes in group 1 (n = 8) were imaged using HF-CE-US to determine the 2D tumor size and relative blood volume; eyes in group 2 (n = 6) were imaged by 3D microbubble contrast-enhanced ultrasound, and the tumor volume was determined. Histologic tumor burden was quantified in enucleated eyes by image processing software, and microvascular density was determined by counting von Willebrand factor-positive vascular channels. Ultrasound images were evaluated and compared with histopathologic findings. RESULTS: Using HF-CE-US, melanomas were visualized as relatively hyperechoic regions. The intraobserver variability of sonographic measurements was 9.65% ± 7.89%, and the coefficient of variation for multiple measurements was 7.33% ± 5.71%. The correlation coefficient of sonographic volume or size and histologic area was 0.71 (P = 0.11) and 0.79 (P = 0.32). The relative blood volume within the tumor demonstrated sonographically correlated significantly with histologic tumor vascularity (r = 0.83; P < 0.001). CONCLUSIONS: There was a positive linear correlation between sonographic tumor measurements and histologic tumor burden in the mouse ocular melanoma model. Contrast-enhanced intensity corresponded with microvascular density and blood volume. HF-CE-US is a real-time, noninvasive, reliable method for in vivo evaluation of experimental intraocular melanoma tumor area and relative blood volume.

Functional surfaces for high-resolution analysis of cancer cell interactions on exogenous hyaluronic acid.

Hyaluronic acid, a nonsulfated, linear glycosaminoglycan, is ubiquitously distributed in the extracellular matrix and is known to facilitate tumor progression by enhancing invasion, growth, and angiogenesis. Native HA has been attached to substrates to create patterned surfaces resistant to cell adhesion, and has been utilized in a variety of cell adhesion studies using either non covalently bound layers patterned by soft lithography or related methods. We use a new approach to study cell interactions with HA-presenting regions, by covalently linking HA adjacent to PEG-ylated regions, which resist cell adhesion. Colon and breast cancer cells seeded on the patterned HA surfaces adhere preferentially on HA-presenting regions and proliferate there. Furthermore, we demonstrate that cell adhesion is inhibited with the blocking of HA receptor, CD44, and that cellular adhesive processes, through protrusions spreading onto the HA surface, enhance spreading and movement outside the HA-presenting regions. Overall, this approach allows high-resolution analysis of cancer cell attachment, growth, and migration on exogenous native HA.

Nanometer-scale mapping and single-molecule detection with color-coded nanoparticle probes.

We report a method for single-molecule detection and biomolecular structural mapping based on dual-color imaging and automated colocalization of bioconjugated nanoparticle probes at nanometer precision. In comparison with organic dyes and fluorescent proteins, nanoparticle probes such as fluorescence energy-transfer nanobeads and quantum dots provide significant advantages in signal brightness, photostability, and multicolor-light emission. As a result, we have achieved routine two-color superresolution imaging and single-molecule detection with standard fluorescence microscopes and inexpensive digital color cameras. By using green and red nanoparticles to simultaneously recognize two binding sites on a single target, individual biomolecules such as nucleic acids are detected and identified without target amplification or probe/target separation. We also demonstrate that a powerful astrophysical method (originally developed to analyze crowded stellar fields) can be used for automated and rapid statistical analysis of nanoparticle colocalization signals. The ability to rapidly localize bright nanoparticle probes at nanometer precision has implications not only for ultrasensitive medical detection but also for structural mapping of molecular complexes in which individual components are tagged with color-coded nanoparticles.

Optically encoded nanoparticles for detecting single biomolecules and viruses: rapid analysis of two-color colocalization data by high-speed computing.

Nanometer-sized particles such as luminescent quantum dots (QDs) and energy-transfer nanoparticles have unique optical, electronic, and structural properties (e.g., signal brightness, photostability, and multicolor light emission) that are not available from traditional organic dyes and fluorescent proteins. Here we report the use of color-coded nanoparticles and dual-color fluorescence correlation for real-time detection of single native biomolecules and viruses in a microfluidic channel. Using green and red nanoparticles to simultaneously recognize two binding sites on a single target, we show that individual molecules of genes, proteins, and intact viruses can be detected and identified in complex mixtures without target amplification or probe/target separation. When combined with high-speed computing such as image segmentation and parallel computing, these nanoparticle probes raise new opportunities in molecular diagnostics, bioterrorism agent detection, and intracellular single-molecule imaging.

Segmentation of bionano images for understanding cell dynamics.

The use of quantum dots (QDs) and molecular beacons (MBs) is a recent advance in the field of nanotechnology. These techniques have enabled us to detect a single molecule in a cell, which helps in understanding the dynamics of a cell. The success of these techniques depends on the accurate and efficient analysis of the imaging data these techniques produce. The processing involves--segmentation of the particles, colocalisation and their tracking over multiple frames in 2D and 3D space. In this paper we have used the active contour models: snakes and their variation--GVF (gradient vector field) snakes for segmentation of nano(QD) and cell(MB) images. The results of segmentation have been used to measure the degree of colocalisation for quantum dot images and the gene expression values for molecular beacon images.

GoMiner: a resource for biological interpretation of genomic and proteomic data.

We have developed GoMiner, a program package that organizes lists of 'interesting' genes (for example, under- and overexpressed genes from a microarray experiment) for biological interpretation in the context of the Gene Ontology. GoMiner provides quantitative and statistical output files and two useful visualizations. The first is a tree-like structure analogous to that in the AmiGO browser and the second is a compact, dynamically interactive 'directed acyclic graph'. Genes displayed in GoMiner are linked to major public bioinformatics resources.

Development of gene ontology tool for biological interpretation of genomic and proteomic data.

We have designed and developed a Gene Ontology based navigation tool, GoMiner, which organizes lists of interesting genes from a microarray or a protein array experiment for biological interpretation. It provides quantitative and statistical output files and useful visualization (e.g., a tree-like structure) to map the list of genes to its biological functional categories. It also provides links to other resources such as pubmed, locuslink, and biological molecular interaction map and signaling pathway packages.

Development of a biomedical imaging informatics system for diagnosis and treatment planning.

The medical imaging technologies have been used for detecting tumors through the years. Tumors that can be viewed in imaging are usually big enough to contain billion tumor cells. Some patients may be cured if detected earlier and the surgery is performed well. Those lead to molecular imaging and image-guided surgery research activities, which post new challenges on large scale imaging data management and 3-D visualization. The goal of this project is to develop 3-D imaging informatics system that can interactively navigate large scale of organ and molecular levels imaging data for early diagnosis and treatment planning.