Nanoscale Metal-Organic Layer Isolates Phthalocyanines for Efficient Mitochondria-Targeted Photodynamic Therapy.

Zinc-phthalocyanine (ZnPc) photosensitizers (PSs) have shown great potential in photodynamic therapy (PDT) owing to their strong absorption at long wavelengths (650-750 nm), high triplet quantum yields, and biocompatibility. However, the clinical utility of ZnPc PSs is limited by their poor solubility and tendency to aggregate in aqueous environments. Here we report the design of a new nanoscale metal-organic layer (nMOL) assembly, ZnOPPc@nMOL, with ZnOPPc [ZnOPPc = zinc(II)-2,3,9,10,16,17,23,24-octa(4-carboxyphenyl)phthalocyanine] PSs supported on the secondary building units (SBUs) of a Hf12 nMOL for PDT. Upon irradiation, SBU-bound ZnOPPc PSs absorb 700 nm light and efficiently sensitize the formation of singlet oxygen by preventing aggregation-induced self-quenching of ZnOPPc excited states. With intrinsic mitochondria-targeting capability, ZnOPPc@nMOL showed exceptional PDT efficacy with >99% tumor growth inhibition and 40-60% cure rates on two mouse models of colon cancer.

Nanoscale Metal-Organic Framework Co-delivers TLR-7 Agonists and Anti-CD47 Antibodies to Modulate Macrophages and Orchestrate Cancer Immunotherapy.

Nanoscale metal-organic frameworks (nMOFs) are excellent radiosensitizers for radiotherapy-radiodynamic therapy (RT-RDT). Herein, we report surface modification of a Hf-DBP nMOF for the co-delivery of a hydrophobic small-molecule toll-like receptor 7 agonist, imiquimod (IMD), and a hydrophilic macromolecule, anti-CD47 antibody (αCD47), for macrophage modulation and reversal of immunosuppression in tumors. IMD repolarizes immunosuppressive M2 macrophages to immunostimulatory M1 macrophages, while αCD47 blocks CD47 tumor cell surface marker to promote phagocytosis. Upon X-ray irradiation, IMD@Hf-DBP/αCD47 effectively modulates the immunosuppressive tumor microenvironment and activates innate immunity to orchestrate adaptive immunity when synergized with an anti-PD-L1 immune checkpoint inhibitor, leading to complete eradication of both primary and distant tumors on a bilateral colorectal tumor model. nMOFs thus provide a unique platform to co-deliver multiple immunoadjuvants for macrophage therapy to induce systematic immune responses and superb antitumor efficacy.

Nanoscale Metal-Organic Frameworks Stabilize Bacteriochlorins for Type I and Type II Photodynamic Therapy.

Herein we report the design of a bacteriochlorin-based nanoscale metal-organic framework, Zr-TBB, for highly effective photodynamic therapy via both type I and type II mechanisms. The framework of Zr-TBB stabilizes 5,10,15,20-tetra(p-benzoato)bacteriochlorin (TBB) ligands toward oxygen and light via geometrical constraint. Upon 740 nm light irradiation, Zr-TBB efficiently generates various reactive oxygen species, including singlet oxygen, superoxide anion, hydrogen peroxide, and hydroxyl radicals, to afford superb antitumor efficacy on mouse models of breast and colon cancers, with cure rates of 40% and 60%, respectively.

Titanium Hydroxide Secondary Building Units in Metal-Organic Frameworks Catalyze Hydrogen Evolution under Visible Light.

Herein we report the design of two new titanium metal-organic frameworks (MOFs), Ti3-BPDC-Ir and Ti3-BPDC-Ru, by doping [Ir(ppy)2(dcbpy)]Cl or [Ru(bpy)2(dcbpy)]Cl2 (bpy = 2,2'-bipyridine, ppy = 2-phenylpyridine, dcbpy = 2,2'-bipyridine-5,5'-dicarboxylate) into the Ti3-BPDC framework (BPDC = biphenyl-4,4'-dicarboxylate). Hierarchical assembly of photosensitizing ligands and Ti3(OH)2 secondary building units (SBUs) facilitates multielectron transfer to drive photocatalytic hydrogen evolution (HER) under visible light with turnover numbers of 6632 and 786 for Ti3-BPDC-Ir and Ti3-BPDC-Ru, respectively. Photophysical and electrochemical studies establish the photocatalytic HER via reductive quenching of the excited photosensitizers followed by electron transfer from the reduced photosensitizers to Ti3(OH)2 SBUs and explain the catalytic difference between the two MOFs. Density functional theory calculations reveal key steps of HER via protonation of TiIII-OH to generate the TiIII species with a vacant coordination site followed by proton-coupled electron transfer to afford the key TiIV-H intermediate.

Metal-Organic Framework Stabilizes a Low-Coordinate Iridium Complex for Catalytic Methane Borylation.

Catalytic borylation has recently been suggested as a potential strategy to convert abundant methane to fine chemicals. However, synthetic utility of methane borylation necessitates significant improvement of catalytic activities over original phenanthroline- and diphosphine-Ir complexes. Herein, we report the use of metal-organic frameworks (MOFs) to stabilize low-coordinate Ir complexes for highly active methane borylation to afford the monoborylated product. The mono(phosphine)-Ir based MOF, Zr-P1-Ir, significantly outperformed other Ir catalysts in methane borylation to afford CH3Bpin with a turnover number of 127 at 110 °C. Density functional theory calculations indicated a significant reduction of activation barrier for the rate limiting oxidative addition of methane to the four-coordinate (P1)IrIII(Bpin)3 catalyst to form the six-coordinate (P1)IrV(Bpin)3(CH3)(H) intermediate, thus avoiding the formation of sterically encumbered seven-coordinate IrV intermediates as found in other Ir catalysts based on chelating phenanthroline, bipyridine, and diphosphine ligands. MOF thus stabilizes the homogeneously inaccessible, low-coordinate (P1)Ir(boryl)3 catalyst to provide a unique strategy to significantly lower the activation barrier for methane borylation. This MOF-based catalyst design holds promise in addressing challenging catalytic reactions involving highly inert substrates.

Hypoglycemia Emergencies: Factors Associated with Prehospital Care, Transportation Status, Emergency Department Disposition, and Cost.

Objectives: The objectives of this study were to evaluate demographic/clinical characteristics and treatment/transportation decisions by emergency medical services (EMS) for patients with hypoglycemia and link EMS activations to patient disposition, outcomes, and costs to the emergency medical system. This evaluation was to identify potential areas where improvements in prehospital healthcare could be made. Methods: This was a retrospective analysis of the National Emergency Medical Services Information System (NEMSIS) registry and three national surveys: Nationwide Emergency Department Sample (NEDS), National Hospital Ambulatory Medical Care Survey (NHAMCS), and Medical Expenditure Panel Survey (MEPS) from 2013, to examine care of hypoglycemia from the prehospital and the emergency department (ED) perspectives. Results: The study estimated 270,945 hypoglycemia EMS incidents from the NEMSIS registry. Treatments were consistent with national guidelines (i.e., oral glucose, intravenous [IV] dextrose, or glucagon), and patients were more likely to be transported to the ED if the incident was in a rural setting or they had other chief concerns related to the pulmonary or cardiovascular system. Use of IV dextrose decreased the likelihood of transportation. Approximately 43% of patients were not transported from the scene. Data from the NEDS survey estimated 258,831 ED admissions for hypoglycemia, and 41% arrived by ambulance. The median ambulance expenditure was $664 ± 98. From the ED, 74% were released. The average ED charge that did not lead to hospital admission was $3106 ± 86. Increased odds of overnight admission included infection and acute renal failure. Conclusions: EMS activations for hypoglycemia are sizeable and yet a considerable proportion of patients are not transported to or are discharged from the ED. Seemingly, these events resolved and were not medically complex. It is possible that implementation and appropriate use of EMS treat-and-release protocols along with utilizing programs to educate patients on hypoglycemia risk factors and emergency preparedness could partially reduce the burden of hypoglycemia to the healthcare system.

Multi-omics enrichment analysis using the GeneTrail2 web service.

MOTIVATION: Gene set analysis has revolutionized the interpretation of high-throughput transcriptomic data. Nowadays, with comprehensive studies that measure multiple -omics from the same sample, powerful tools for the integrative analysis of multi-omics datasets are required. RESULTS: Here, we present GeneTrail2, a web service allowing the integrated analysis of transcriptomic, miRNomic, genomic and proteomic datasets. It offers multiple statistical tests, a large number of predefined reference sets, as well as a comprehensive collection of biological categories and enables direct comparisons between the computed results. We used GeneTrail2 to explore pathogenic mechanisms of Wilms tumors. We not only succeeded in revealing signaling cascades that may contribute to the malignancy of blastemal subtype tumors but also identified potential biomarkers for nephroblastoma with adverse prognosis. The presented use-case demonstrates that GeneTrail2 is well equipped for the integrative analysis of comprehensive -omics data and may help to shed light on complex pathogenic mechanisms in cancer and other diseases. AVAILABILITY AND IMPLEMENTATION: GeneTrail2 can be freely accessed under https://genetrail2.bioinf.uni-sb.de CONTACT: : dstoeckel@bioinf.uni-sb.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Impact of a Pharmacy-Cardiology Collaborative Practice on Dofetilide Safety Monitoring.

BACKGROUND: Limited studies have been published examining dofetilide's postmarketing use and its recommended monitoring. OBJECTIVE: To evaluate the impact of a collaborative pharmacy-cardiology antiarrhythmic drug (AAD) monitoring program on dofetilide monitoring. METHODS: This retrospective cohort study was performed to assess if a novel monitoring program improved compliance with dofetilide-specific monitoring parameters based on the Food and Drug Administration's Risk Evaluation and Mitigation Strategy. RESULTS: A total of 30 patients were included in the analysis. The monitoring parameters evaluated included electrocardiogram, serum potassium, serum magnesium, and kidney function. The primary outcome evaluated was the composite of these dofetilide monitoring parameters obtained in each cohort. In the standard cohort, 245 of 352 (69.6%) monitoring parameters were completed versus 134 of 136 (98.5%) in the intervention group ( P < 0.05). CONCLUSION: A collaborative pharmacy-cardiology AAD monitoring program was associated with a significant improvement in dofetilide monitoring. This improvement could potentially translate into enhanced patient safety outcomes, such as prevention of adverse drug reactions and decreased hospitalizations.

DrugTargetInspector: An assistance tool for patient treatment stratification.

Cancer is a large class of diseases that are characterized by a common set of features, known as the Hallmarks of cancer. One of these hallmarks is the acquisition of genome instability and mutations. This, combined with high proliferation rates and failure of repair mechanisms, leads to clonal evolution as well as a high genotypic and phenotypic diversity within the tumor. As a consequence, treatment and therapy of malignant tumors is still a grand challenge. Moreover, under selective pressure, e.g., caused by chemotherapy, resistant subpopulations can emerge that then may lead to relapse. In order to minimize the risk of developing multidrug-resistant tumor cell populations, optimal (combination) therapies have to be determined on the basis of an in-depth characterization of the tumor's genetic and phenotypic makeup, a process that is an important aspect of stratified medicine and precision medicine. We present DrugTargetInspector (DTI), an interactive assistance tool for treatment stratification. DTI analyzes genomic, transcriptomic, and proteomic datasets and provides information on deregulated drug targets, enriched biological pathways, and deregulated subnetworks, as well as mutations and their potential effects on putative drug targets and genes of interest. To demonstrate DTI's broad scope of applicability, we present case studies on several cancer types and different types of input -omics data. DTI's integrative approach allows users to characterize the tumor under investigation based on various -omics datasets and to elucidate putative treatment options based on clinical decision guidelines, but also proposing additional points of intervention that might be neglected otherwise. DTI can be freely accessed at http://dti.bioinf.uni-sb.de.

NetworkTrail--a web service for identifying and visualizing deregulated subnetworks.

UNLABELLED: The deregulation of biochemical pathways plays a central role in many diseases like cancer or Parkinsons's disease. In silico tools for calculating these deregulated pathways may help to gain new insights into pathogenic mechanisms and may open novel avenues for therapy stratification in the sense of personalized medicine. Here, we present NetworkTrail, a web service for the detection of deregulated pathways and subgraphs in biological networks. NetworkTrail uses a state-of-the-art integer linear programming-based approach for this task and offers interfaces to the Biological Network Analyzer (BiNA) and Cytoscape Web for visualizing the resulting subnetworks. By providing an accessible interface to otherwise hard-to-use command line tools, the new web service enables non-experts to quickly and reliably carry out this type of network analyses. AVAILABILITY AND IMPLEMENTATION: NetworkTrail is a JavaServer Pages-based web service. The algorithm for finding deregulated subnetworks has been implemented in C++. NetworkTrail is available at http://networktrail.bioinf.uni-sb.de/.

An integer linear programming approach for finding deregulated subgraphs in regulatory networks.

Deregulation of cell signaling pathways plays a crucial role in the development of tumors. The identification of such pathways requires effective analysis tools that facilitate the interpretation of expression differences. Here, we present a novel and highly efficient method for identifying deregulated subnetworks in a regulatory network. Given a score for each node that measures the degree of deregulation of the corresponding gene or protein, the algorithm computes the heaviest connected subnetwork of a specified size reachable from a designated root node. This root node can be interpreted as a molecular key player responsible for the observed deregulation. To demonstrate the potential of our approach, we analyzed three gene expression data sets. In one scenario, we compared expression profiles of non-malignant primary mammary epithelial cells derived from BRCA1 mutation carriers and of epithelial cells without BRCA1 mutation. Our results suggest that oxidative stress plays an important role in epithelial cells of BRCA1 mutation carriers and that the activation of stress proteins may result in avoidance of apoptosis leading to an increased overall survival of cells with genetic alterations. In summary, our approach opens new avenues for the elucidation of pathogenic mechanisms and for the detection of molecular key players.

Correction: Luedemann et al. Prostate Cancer-Associated miRNAs in Saliva: First Steps to an Easily Accessible and Reliable Screening Tool. Biomolecules 2022, 12, 1366.

The authors wish to make the following corrections to their paper [...].

Splitting Vertices in 2-Layer Graph Drawings.

Bipartite graphs model the relationships between two disjoint sets of entities in several applications and are naturally drawn as 2-layer graph drawings. In such drawings, the two sets of entities (vertices) are placed on two parallel lines (layers), and their relationships (edges) are represented by segments connecting vertices. Methods for constructing 2-layer drawings often try to minimize the number of edge crossings. We use vertex splitting to reduce the number of crossings, by replacing selected vertices on one layer by two (or more) copies and suitably distributing their incident edges among these copies. We study several optimization problems related to vertex splitting, either minimizing the number of crossings or removing all crossings with fewest splits. While we prove that some variants are ${\mathsf {NP}}$NP-complete, we obtain polynomial-time algorithms for others. We run our algorithms on a benchmark set of bipartite graphs representing the relationships between human anatomical structures and cell types.

ANCAC: amino acid, nucleotide, and codon analysis of COGs--a tool for sequence bias analysis in microbial orthologs.

BACKGROUND: The COG database is the most popular collection of orthologous proteins from many different completely sequenced microbial genomes. Per definition, a cluster of orthologous groups (COG) within this database exclusively contains proteins that most likely achieve the same cellular function. Recently, the COG database was extended by assigning to every protein both the corresponding amino acid and its encoding nucleotide sequence resulting in the NUCOCOG database. This extended version of the COG database is a valuable resource connecting sequence features with the functionality of the respective proteins. RESULTS: Here we present ANCAC, a web tool and MySQL database for the analysis of amino acid, nucleotide, and codon frequencies in COGs on the basis of freely definable phylogenetic patterns. We demonstrate the usefulness of ANCAC by analyzing amino acid frequencies, codon usage, and GC-content in a species- or function-specific context. With respect to amino acids we, at least in part, confirm the cognate bias hypothesis by using ANCAC's NUCOCOG dataset as the largest one available for that purpose thus far. CONCLUSIONS: Using the NUCOCOG datasets, ANCAC connects taxonomic, amino acid, and nucleotide sequence information with the functional classification via COGs and provides a GUI for flexible mining for sequence-bias. Thereby, to our knowledge, it is the only tool for the analysis of sequence composition in the light of physiological roles and phylogenetic context without requirement of substantial programming-skills.

miRTrail--a comprehensive webserver for analyzing gene and miRNA patterns to enhance the understanding of regulatory mechanisms in diseases.

BACKGROUND: Expression profiling provides new insights into regulatory and metabolic processes and in particular into pathogenic mechanisms associated with diseases. Besides genes, non-coding transcripts as microRNAs (miRNAs) gained increasing relevance in the last decade. To understand the regulatory processes of miRNAs on genes, integrative computer-aided approaches are essential, especially in the light of complex human diseases as cancer. RESULTS: Here, we present miRTrail, an integrative tool that allows for performing comprehensive analyses of interactions of genes and miRNAs based on expression profiles. The integrated analysis of mRNA and miRNA data should generate more robust and reliable results on deregulated pathogenic processes and may also offer novel insights into the regulatory interactions between miRNAs and genes. Our web-server excels in carrying out gene sets analysis, analysis of miRNA sets as well as the combination of both in a systems biology approach. To this end, miRTrail integrates information on 20.000 genes, almost 1.000 miRNAs, and roughly 280.000 putative interactions, for Homo sapiens and accordingly for Mus musculus and Danio rerio. The well-established, classical Chi-squared test is one of the central techniques of our tool for the joint consideration of miRNAs and their targets. For interactively visualizing obtained results, it relies on the network analyzers and viewers BiNA or Cytoscape-web, also enabling direct access to relevant literature. We demonstrated the potential of miRTrail by applying our tool to mRNA and miRNA data of malignant melanoma. MiRTrail identified several deregulated miRNAs that target deregulated mRNAs including miRNAs hsa-miR-23b and hsa-miR-223, which target the highest numbers of deregulated mRNAs and regulate the pathway "basal cell carcinoma". In addition, both miRNAs target genes like PTCH1 and RASA1 that are involved in many oncogenic processes. CONCLUSIONS: The application on melanoma samples demonstrates that the miRTrail platform may open avenues for investigating the regulatory interactions between genes and miRNAs for a wide range of human diseases. Moreover, miRTrail cannot only be applied to microarray based expression profiles, but also to NGS-based transcriptomic data. The program is freely available as web-server at mirtrail.bioinf.uni-sb.de.

Prostate Cancer-Associated miRNAs in Saliva: First Steps to an Easily Accessible and Reliable Screening Tool.

BACKGROUND: Common diagnostic tools for prostate cancer-prostate-specific antigen and transrectal biopsy-show only low predictive value and poor sensitivity. This study examines circulating miRNA in saliva to explore the possibility of a non-invasive and easy-to-execute diagnostic tool for prostate cancer screenings. METHODS: 16 miRNAs were extracted from salivary exosomes and analyzed via the delta-CT method. The presented method enables an application of the test in any health institution and even outpatient sector. Recruited participants were suspected to suffer from prostate cancer due to elevated PSA serum levels. Of these participants, 43 were diagnosed with prostate cancer, while 31 suffered from benign diseases and served as control group. RESULTS: hsa-mir-331-3p and hsa-mir-200b were significantly reduced in prostate cancer patients compared to the control group. ROC curve analysis revealed a reliable differentiation strength (AUC &gt; 0.6) for both miRNAs with positive predictive values of 71% indicating prostate cancer. Differentiation of both groups based on PSA serum measurements was insufficient. The other 14 examined miRNAs showed no significant group differences. CONCLUSIONS: The presented method and miRNA are promising non-invasive tools to augment the current prostate cancer screening, thereby improving screening sensitivity and reducing numbers of false positive cancer suspects admitted to further invasive diagnostic and therapeutic steps.

Small RNAs as biomarkers to differentiate benign and malign prostate diseases: An alternative for transrectal punch biopsy of the prostate?

Prostate cancer (PCa) is the most common cancer and the third most frequent cause of male cancer death in Germany. MicroRNAs (miRNA) appear to be involved in the development and progression of PCa. A diagnostic differentiation from benign prostate hyperplasia (BPH) is often only possible through transrectal punch biopsy. This procedure is described as painful and carries risks. It was investigated whether urinary miRNAs can be used as biomarkers to differentiate the prostate diseases above. Therefore urine samples from urological patients with BPH (25) or PCa (28) were analysed using Next-Generation Sequencing to detect the expression profile of total and exosomal miRNA/piRNA. 79 miRNAs and 5 piwi-interacting RNAs (piRNAs) were significantly differentially expressed (adjusted p-value < 0.05 and log2-Fc > 1 or < -1). Of these, 6 miRNAs and 2 piRNAs could be statistically validated (AUC on test cohort > = 0.7). In addition, machine-learning algorithms were used to identify a panel of 22 additional miRNAs, whose interaction makes it possible to differentiate the groups as well. There are promising individual candidates for potential use as biomarkers in prostate cancer. The innovative approach of applying machine learning methods to this kind of data could lead to further small RNAs coming into scientific focus, which have so far been neglected.

A novel algorithm for detecting differentially regulated paths based on gene set enrichment analysis.

MOTIVATION: Deregulated signaling cascades are known to play a crucial role in many pathogenic processes, among them are tumor initiation and progression. In the recent past, modern experimental techniques that allow for measuring the amount of mRNA transcripts of almost all known human genes in a tissue or even in a single cell have opened new avenues for studying the activity of the signaling cascades and for understanding the information flow in the networks. RESULTS: We present a novel dynamic programming algorithm for detecting deregulated signaling cascades. The so-called FiDePa (Finding Deregulated Paths) algorithm interprets differences in the expression profiles of tumor and normal tissues. It relies on the well-known gene set enrichment analysis (GSEA) and efficiently detects all paths in a given regulatory or signaling network that are significantly enriched with differentially expressed genes or proteins. Since our algorithm allows for comparing a single tumor expression profile with the control group, it facilitates the detection of specific regulatory features of a tumor that may help to optimize tumor therapy. To demonstrate the capabilities of our algorithm, we analyzed a glioma expression dataset with respect to a directed graph that combined the regulatory networks of the KEGG and TRANSPATH database. The resulting glioma consensus network that encompasses all detected deregulated paths contained many genes and pathways that are known to be key players in glioma or cancer-related pathogenic processes. Moreover, we were able to correlate clinically relevant features like necrosis or metastasis with the detected paths. AVAILABILITY: C++ source code is freely available, BiNA can be downloaded from http://www.bnplusplus.org/. CONTACT: ack@bioinf.uni-sb.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.