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The synergistic effect and compatibility structure of active anti-inflammatory ingredients(iridoid glycosides: shanzhiside methylester and 8-O-acetylshanzhiside methyl ester, flavonoid glycoside: luteoloside, and phenylethanoid glycoside: forsythoside B) from Lamiophlomis rotata were explored based on network pharmacology and component structure theory. In network pharmacology, CTD, SwisseTargetPrediction, and PharmMapper databases were used to collect and screen the targets of all active ingredients. The inflammation-related targets were obtained from CTD and GeneCards databases. The core targets were obtained by Venny 2.1.0, STRING, and Cytoscape 3.9.1. Core targets were annotated by the GO function and enriched by the KEGG pathway based on the DAVID database. In terms of component structure, based on a uniform design method and xylene-induced ear swelling model in mice, tumor necrosis factor-α and interleukin-6 were taken as the dependent variables, and the compatibility relationship among anti-inflammatory ingredients from L. rotata was explored through the quadratic polynomial stepwise regression. In addition, in vivo pharmacological experiments were conducted to verify the results. A network pharmacology study showed that compared with a single ingredient, the combined action of the three ingredients can synergistically exert anti-inflammatory effects through more biological processes, pathways, and targets. Component structure study showed that the optimal structural ratio of shanzhiside methylester and 8-O-acetylshanzhiside methyl ester in the iridoid glycoside ingredient was 1.21∶1. The optimal structural ratio among the three types of ingredients(iridoid glycosides∶phenylethanol glycoside∶flavonoid glycoside) was 4.8∶1.6∶1. In conclusion, each anti-inflammatory ingredient from L. rotata can work synergistically, and there is an optimal compatibility ratio relationship among these ingredients. This work provides a new experimental basis for the intrinsic quality control of L. rotata.

Type I interferons (IFN-I) are cytokines with potent antiviral and inflammatory capacities. IFN-I signaling drives the expression of hundreds of IFN-I stimulated genes (ISGs), whose aggregate function results in the control of viral infection. A few of these ISGs are tasked with negatively regulating the IFN-I response to prevent overt inflammation. ISG15 is a negative regulator whose absence leads to persistent, low-grade elevation of ISG expression and concurrent, self-resolving mild autoinflammation. The limited breadth and low-grade persistence of ISGs expressed in ISG15 deficiency are sufficient to confer broad-spectrum antiviral resistance. Inspired by ISG15 deficiency, we have identified a nominal collection of 10 ISGs that recapitulate the broad antiviral potential of the IFN-I system. The expression of the 10 ISG collection in an IFN-I non-responsive cell line increased cellular resistance to Zika, Vesicular Stomatitis, Influenza A (IAV), and SARS-CoV-2 viruses. A deliverable prophylactic formulation of this syndicate of 10 ISGs significantly inhibited IAV PR8 replication in vivo in mice and protected hamsters against a lethal SARS-CoV-2 challenge, suggesting its potential as a broad-spectrum antiviral against many current and future emerging viral pathogens., One-Sentence Summary: Human inborn error of immunity-guided discovery and development of a broad-spectrum RNA antiviral therapy.

Estrogen receptors are essential pharmacological targets for treating hormonal disorders and estrogen-dependent malignancies. Selective activation of estrogen receptor (ER) β is hypothesized to provide therapeutic benefit with reduced risk of unwanted estrogenic side-effects associated with ERα activity. However, activating ERβ without activating α is challenging due to the high sequence and structural homology between the receptor subtypes. We assessed the impact of structural modifications to the parent compound OSU-ERβ-12 on receptor subtype binding selectivity using cell-free binding assays. Functional selectivity was evaluated by transactivation in HEK-293 cells overexpressing human or murine estrogen receptors. In vivo selectivity was examined through the uterotrophic effects of the analogs after oral administration in estrogen-naïve female mice. Furthermore, we evaluated the in vivo pharmacokinetics of the analogs following single dose IV and oral administration. Regarding selectivity, a single compound exhibited greater functional selectivity than OSU-ERβ-12 for human ERβ. However, like others in the meta -carborane series, its poor in vivo pharmacokinetics limit its suitability for further development. Surprisingly, and at odds with their pharmacokinetic and in vitro human activity data, most analogs potently induced uterotrophic effects in estrogen-naïve female mice. Further investigation of activity in HEK293 cells expressing murine estrogen receptors revealed species-specific differences in the ER-subtype selectivity of these analogs. Our findings highlight species-specific receptor pharmacology and the challenges it poses to characterizing developmental therapeutics in preclinical species. Significance Statement This study investigates para - and meta -substituted carborane analogs targeting estrogen receptors, revealing the greater selectivity of carborane analogs for human ERβ compared to the mouse homolog. These findings shed light on the intricacies of using preclinical species in drug development to predict human pharmacology. The report also provides insights for the refinement and optimization of carborane analogs as potential therapeutic agents for estrogen-related disease states., (© 2024 The Authors. This is an open access article under the terms of the Creative Commons Attribution CC BY License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited.)

Current treatment options for diabetic wounds face challenges due to low efficacy, as well as potential side effects and the necessity for repetitive treatments. To address these issues, we report a formulation utilizing trisulfide-derived lipid nanoparticle (TS LNP)-mRNA therapy to accelerate diabetic wound healing by repairing and reprogramming the microenvironment of the wounds. A library of reactive oxygen species (ROS)-responsive TS LNPs was designed and developed to encapsulate interleukin-4 (IL4) mRNA. TS2-IL4 LNP-mRNA effectively scavenges excess ROS at the wound site and induces the expression of IL4 in macrophages, promoting the polarization from the proinflammatory M1 to the anti-inflammatory M2 phenotype at the wound site. In a diabetic wound model of db/db mice, treatment with this formulation significantly accelerates wound healing by enhancing the formation of an intact epidermis, angiogenesis, and myofibroblasts. Overall, this TS LNP-mRNA platform not only provides a safe, effective, and convenient therapeutic strategy for diabetic wound healing but also holds great potential for clinical translation in both acute and chronic wound care., Competing Interests: Competing interests statement:Y.D. is a scientific advisory board member and holds equity in Arbor Biotechnologies and Sirnagen Therapeutics. Y.D. is a co-founder and holds equity in Immunanoengineering Therapeutics. Other authors declare no conflict of interest. A patent application related to this work was filed by The Ohio State University.

Since the approval of the lipid nanoparticles (LNP)-mRNA vaccines against the SARS-CoV-2 virus, there has been an increased interest in the delivery of mRNA through LNPs. However, current LNP formulations contain PEG lipids, which can stimulate the generation of anti-PEG antibodies. The presence of these antibodies can potentially cause adverse reactions and reduce therapeutic efficacy after administration. Given the widespread deployment of the COVID-19 vaccines, the increased exposure to PEG may necessitate the evaluation of alternative LNP formulations without PEG components. In this study, we investigated a series of polysarcosine (pSar) lipids as alternatives to the PEG lipids to determine whether pSar lipids could still provide the functionality of the PEG lipids in the ALC-0315 and SM-102 LNP systems. We found that complete replacement of the PEG lipid with a pSar lipid can increase or maintain mRNA delivery efficiency and exhibit similar safety profiles in vivo., Competing Interests: Y.D. is a scientific advisory board member and holds equity in Arbor Biotechnologies and Sirnagen Therapeutics. Y.D. is a co-founder and holds equity in Immunanoengineering Therapeutics. Other authors declare no conflict of interest., (© 2024 The Authors.)

Candida albicans (C. albicans) is one of the most common opportunistic fungi worldwide, which is associated with a high mortality rate. Despite treatment, C. albicans remains the leading cause of life-threatening invasive infections. Consequently, antimicrobial peptides (AMPs) are potential alternatives as antifungal agents with excellent antifungal activity. We previously reported that Css54, found in the venom of Centrurodies suffusus suffusus (C. s. suffusus) showed antibacterial activity against zoonotic bacteria. However, the antifungal activity of Css54 has not yet been elucidated. The objective of this study was to identify the antifungal activity of Css54 against C. albicans and analyze its mechanism. Css54 showed high antifungal activity against C. albicans. Css54 also inhibited biofilm formation in fluconazole-resistant fungi. The antifungal mechanism of action of Css54 was investigated using membrane-related assays, including the membrane depolarization assay and analysis of the membrane integrity of C. albicans after treatment with Css54. Css54 induced reactive oxygen species (ROS) production in C. albicans, which affected its antifungal activity. Our results indicate that Css54 causes membrane damage in C. albicans, highlighting its value as a potential therapeutic agent against C. albicans infection., (© 2024. The Author(s).)

Adipose stem cells (ASCs) have attracted considerable attention as potential therapeutic agents due to their ability to promote tissue regeneration. However, their limited tissue repair capability has posed a challenge in achieving optimal therapeutic outcomes. Herein, we conceive a series of lipid nanoparticles to reprogram ASCs with durable protein secretion capacity for enhanced tissue engineering and regeneration. In vitro studies identify that the isomannide-derived lipid nanoparticles (DIM1T LNP) efficiently deliver RNAs to ASCs. Co-delivery of self-amplifying RNA (saRNA) and E3 mRNA complex (the combination of saRNA and E3 mRNA is named SEC) using DIM1T LNP modulates host immune responses against saRNAs and facilitates the durable production of proteins of interest in ASCs. The DIM1T LNP-SEC engineered ASCs (DS-ASCs) prolong expression of hepatocyte growth factor (HGF) and C-X-C motif chemokine ligand 12 (CXCL12), which show superior wound healing efficacy over their wild-type and DIM1T LNP-mRNA counterparts in the diabetic cutaneous wound model. Overall, this work suggests LNPs as an effective platform to engineer ASCs with enhanced protein generation ability, expediting the development of ASCs-based cell therapies., (© 2024. The Author(s).)

Effective cancer immunotherapy is usually blocked by immunosuppressive factors in the tumour microenvironment, resulting in tumour promotion, metastasis and recurrence. Here we combine lipid nanoparticle-mRNA formulations and dendritic cell therapy (named CATCH) to boost the cancer-immunity cycle via progressive steps to overcome the immunosuppressive tumour microenvironment. Multiple types of sugar-alcohol-derived lipid nanoparticles are conceived to modulate the cancer-immunity cycle. First, one type of lipid nanoparticle containing CD40 ligand mRNA induces robust immunogenic cell death in tumoural tissues, leading to the release of tumour-associated antigens and the expression of CD40 ligand. Next, dendritic cells engineered by another type of lipid nanoparticle encapsulating CD40 mRNA are adoptively transferred, which are then activated by the CD40 ligand molecules in tumoural tissues. This promotes the secretion of multiple cytokines and chemokines, and the upregulation of co-stimulatory molecules on dendritic cells, which are crucial for reprogramming the tumour microenvironment and priming the T-cell responses. After dendritic cells present tumour-associated antigens to T cells, all the above stepwise events contribute to boosting a potent tumour-specific T-cell immunity that eradicates established tumours, suppresses distal lesions and prevents tumour rechallenge., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

A 59-year-old Asian woman with paroxysmal supraventricular tachycardia (PSVT), diabetes, and dyslipidemia was hospitalized with palpitations and chest discomfort. Her electrocardiogram showed short RP tachycardia with a heart rate of 167 bpm. She received intravenous adenosine with successful restoration of sinus rhythm and resolution of her symptoms.

The accelerated progress and approval of two mRNA-based vaccines to address the SARS-CoV-2 virus were unprecedented. This record-setting feat was made possible through the solid foundation of research on in vitro transcribed mRNA (IVT mRNA) which could be utilized as a therapeutic modality. Through decades of thorough research to overcome barriers to implementation, mRNA-based vaccines or therapeutics offer many advantages to rapidly address a broad range of applications including infectious diseases, cancers, and gene editing. Here, we describe the advances that have supported the adoption of IVT mRNA in the clinics, including optimization of the IVT mRNA structural components, synthesis, and lastly concluding with different classes of IVT RNA. Continuing interest in driving IVT mRNA technology will enable a safer and more efficacious therapeutic modality to address emerging and existing diseases., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Quantum defects in diamonds have been studied as a promising resource for quantum science. The subtractive fabrication process for improving photon collection efficiency often require excessive milling time that can adversely affect the fabrication accuracy. We designed and fabricated a Fresnel-type solid immersion lens using the focused ion beam. For a 5.8 µm-deep Nitrogen-vacancy (NV - ) center, the milling time was highly reduced (1/3 compared to a hemispherical structure), while retaining high photon collection efficiency (> 2.24 compared to a flat surface). In numerical simulation, this benefit of the proposed structure is expected for a wide range of milling depths.

Lipid nanoparticle (LNP)-mediated delivery of messenger RNA (mRNA) COVID-19 vaccines has provided large-scale immune protection to the public. To elicit a robust immune response against SARS-CoV-2 infections, antigens produced by mRNAs encoding SARS-CoV-2 Spike glycoprotein need to be efficiently delivered and presented to antigen-presenting cells such as dendritic cells (DCs). As concurrent innate immune stimulation can facilitate the antigen presentation process, a library of non-nucleotide STING agonist-derived amino lipids (SALs) was synthesized and formulated into LNPs for mRNA delivery. SAL12 lipid nanoparticles (SAL12-LNPs) were identified as most potent in delivering mRNAs encoding the Spike glycoprotein (S) of SARS-CoV-2 while activating the STING pathway in DCs. Two doses of SAL12 S-LNPs by intramuscular immunization elicited potent neutralizing antibodies against SARS-CoV-2 in mice.

Toll-like receptors (TLRs) and CD40-related signaling pathways represent critical bridges between innate and adaptive immune responses. Here, an immunotherapy regimen that enables co-stimulation of TLR7/8- and CD40-mediated pathways is developed. TLR7/8 agonist resiquimod (R848) derived amino lipids, RAL1 and RAL2, are synthesized and formulated into RAL-derived lipid nanoparticles (RAL-LNPs). The RAL2-LNPs show efficient CD40 mRNA delivery to DCs both in vitro (90.8 ± 2.7%) and in vivo (61.3 ± 16.4%). When combined with agonistic anti-CD40 antibody, this approach can produce effective antitumor activities in mouse melanoma tumor models, thereby suppressing tumor growth, prolonging mouse survival, and establishing antitumor memory immunity. Overall, RAL2-LNPs provide a novel platform toward cancer immunotherapy by integrating innate and adaptive immunity., (© 2022 Wiley-VCH GmbH.)

Antibiotic-resistant bacteria have become a public health problem. Thus, antimicrobial peptides (AMPs) have been evaluated as substitutes for antibiotics. Herein, we investigated PN5 derived from Pinus densiflora (pine needle). PN5 exhibited antimicrobial activity without causing cytotoxic effects. Based on these results, we examined the mode of action of PN5 against Gram-negative and -positive bacteria. PN5 exhibited membrane permeabilization ability, had antimicrobial stability in the presence of elastase, a proteolytic enzyme, and did not induce resistance in bacteria. Bacterial lipopolysaccharide (LPS) induces an inflammatory response in RAW 264.7 macrophages. PN5 suppressed proinflammatory cytokines mediated by NF-κB and mitogen-activated protein kinase signaling. In C57BL/6J mice treated with LPS and d-galactosamine, PN5 exhibited anti-inflammatory activity in inflamed mouse livers. Our results indicate that PN5 has antimicrobial and anti-inflammatory activities and thus may be useful as an antimicrobial agent to treat septic shock caused by multidrug-resistant (MDR) Escherichia coli without causing further resistance. IMPORTANCE Antibiotic-resistant bacteria are a global health concern. There is no effective treatment for antibiotic-resistant bacteria, and new alternatives are being suggested. The present study found antibacterial and anti-inflammatory activities of PN5 derived from Pinus densiflora (pine needle), and further investigated the therapeutic effect in a mouse septic model. As a mechanism of antibacterial activity, PN5 exhibited the membrane permeabilization ability of the toroidal model, and treated strains did not develop drug resistance during serial passages. PN5 showed immunomodulatory properties of neutralizing LPS in a mouse septic model. These results indicate that PN5 could be a new and promising therapeutic agent for bacterial infectious disease caused by antibiotic-resistant strains.

Cytokines are important immunotherapeutics with approved drugs for the treatment of human cancers. However, systemic administration of cytokines often fails to achieve adequate concentrations to immune cells in tumors due to dose-limiting toxicity. Thus, developing localized therapy that directly delivers immune-stimulatory cytokines to tumors may improve the therapeutic efficacy. In this study, we generated novel lipid nanoparticles (LNPs) encapsulated with mRNAs encoding cytokines including IL-12, IL-27 and GM-CSF, and tested their anti-tumor activity. We first synthesized ionizable lipid materials containing di-amino groups with various head groups (DALs). The novel DAL4-LNP effectively delivered different mRNAs in vitro to tumor cells and in vivo to tumors. Intratumoral injection of DAL4-LNP loaded with IL-12 mRNA was most potent in inhibiting B16F10 melanoma tumor growth compared to IL-27 or GM-CSF mRNAs in monotherapy. Furthermore, intratumoral injection of dual DAL4-LNP-IL-12 mRNA and IL-27 mRNA showed a synergistic effect in suppressing tumor growth without causing systematic toxicity. Most importantly, intratumoral delivery of IL-12 and IL-27 mRNAs induced robust infiltration of immune effector cells, including IFN-γ and TNF-α producing NK and CD8 + T cells into tumors. Thus, intratumoral administration of DAL-LNP loaded with IL-12 and IL-27 mRNA provides a new treatment strategy for cancer., (Copyright © 2022 Elsevier B.V. All rights reserved.)

RNA-binding proteins (RBPs) play an important role in RNA metabolism, regulating the stability, localization, and functional dynamics of RNAs. Alternation in the RBP-RNA network has profound implications in cellular physiology, and is related to the development and spread of cancer in certain cases. To regulate the expression of specific genes and their biological activities, various strategies have been applied to target RBPs for cancer treatments, including small-molecule inhibitors, small-interfering RNA, peptides, and aptamers. Recently, the deployment of the CRISPR-Cas9 technology has provided a new platform for RBP screening and regulation. This review summarizes the delivery systems of the CRISPR-Cas9 system and their role in RBP-based cancer therapeutics, including identification of novel RBPs and regulation of cancer-associated RBPs. The efficient delivery of the CRISPR-Cas9 system is important to the profound understanding and clinical transition of RBPs as cancer therapeutic targets., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Antibodies targeting costimulatory receptors of T cells have been developed for the activation of T cell immunity in cancer immunotherapy. However, costimulatory molecule expression is often lacking in tumor-infiltrating immune cells, which can impede antibody-mediated immunotherapy. Here, we hypothesize that delivery of costimulatory receptor mRNA to tumor-infiltrating T cells will enhance the antitumor effects of antibodies. We first design a library of biomimetic nanoparticles and find that phospholipid nanoparticles (PL1) effectively deliver costimulatory receptor mRNA (CD137 or OX40) to T cells. Then, we demonstrate that the combination of PL1-OX40 mRNA and anti-OX40 antibody exhibits significantly improved antitumor activity compared to anti-OX40 antibody alone in multiple tumor models. This treatment regimen results in a 60% complete response rate in the A20 tumor model, with these mice being resistant to rechallenge by A20 tumor cells. Additionally, the combination of PL1-OX40 mRNA and anti-OX40 antibody significantly boosts the antitumor immune response to anti-PD-1 + anti-CTLA-4 antibodies in the B16F10 tumor model. This study supports the concept of delivering mRNA encoding costimulatory receptors in combination with the corresponding agonistic antibody as a strategy to enhance cancer immunotherapy., (© 2021. The Author(s).)

Organelles are specialized compartments, where various proteins reside and play crucial roles to maintain essential cellular structures and functions in mammalian cells. A comprehensive understanding of protein expressions and subsequent localizations at each organelle is of great benefit to the development of organelle-based therapies. Herein, a set of single or dual organelle labeling messenger RNAs (SOLAR or DOLAR) is designed as novel imaging probes, which encode fluorescent proteins with various organelle localization signals. These mRNA probes enable to visualize the protein localizations at different organelles and investigate their trafficking from ribosomal machinery to specific organelles. According to the in vitro results, SOLAR probes show organelle targeting capabilities consistent with the design. Moreover, DOLAR probes with different linkers display distinct targeting properties depending on different organelle localization signals. Additionally, these mRNA probes also exhibit organelle labeling ability in vivo when delivered by lipid nanoparticles (LNPs). Therefore, these mRNA-based probes provide a unique tool to study cell organelles and may facilitate the design of organelle-based therapies., (© 2021 Wiley-VCH GmbH.)

The CRISPR-Cas system has revolutionized the biomedical research field with its simple and flexible genome editing method. In October 2020, Emmanuelle Charpentier and Jennifer A. Doudna were awarded the 2020 Nobel Prize in chemistry in recognition of their outstanding contributions to the discovery of CRISPR-Cas9 genetic scissors, which allow scientists to alter DNA sequences with high precision. Recently, the first phase I clinical trials in cancer patients affirmed the safety and feasibility of ex vivo CRISPR-edited T cells. However, specific and effective CRISPR delivery in vivo remains challenging due to the multiple extracellular and intracellular barriers. Here, we discuss the recent advances in novel lipid nanomaterials for CRISPR delivery and describe relevant examples of potential therapeutics in cancers, genetic disorders, and infectious diseases.

Within the pericentric regions of human chromosomes reside large arrays of tandemly repeated satellite sequences. Expression of the human pericentric satellite HSATII is prevented by extensive heterochromatin silencing in normal cells, yet in many cancer cells, HSATII RNA is aberrantly expressed and accumulates in large nuclear foci in cis. Expression and aggregation of HSATII RNA in cancer cells is concomitant with recruitment of key chromatin regulatory proteins including methyl-CpG binding protein 2 (MeCP2). While HSATII expression has been observed in a wide variety of cancer cell lines and tissues, the effect of its expression is unknown. We tested the effect of stable expression of HSATII RNA within cells that do not normally express HSATII. Ectopic HSATII expression in HeLa and primary fibroblast cells leads to focal accumulation of HSATII RNA in cis and triggers the accumulation of MeCP2 onto nuclear HSATII RNA bodies. Further, long-term expression of HSATII RNA leads to cell division defects including lagging chromosomes, chromatin bridges, and other chromatin defects. Thus, expression of HSATII RNA in normal cells phenocopies its nuclear accumulation in cancer cells and allows for the characterization of the cellular events triggered by aberrant expression of pericentric satellite RNA.

We previously reported on MetaBAT, an automated metagenome binning software tool to reconstruct single genomes from microbial communities for subsequent analyses of uncultivated microbial species. MetaBAT has become one of the most popular binning tools largely due to its computational efficiency and ease of use, especially in binning experiments with a large number of samples and a large assembly. MetaBAT requires users to choose parameters to fine-tune its sensitivity and specificity. If those parameters are not chosen properly, binning accuracy can suffer, especially on assemblies of poor quality. Here, we developed MetaBAT 2 to overcome this problem. MetaBAT 2 uses a new adaptive binning algorithm to eliminate manual parameter tuning. We also performed extensive software engineering optimization to increase both computational and memory efficiency. Comparing MetaBAT 2 to alternative software tools on over 100 real world metagenome assemblies shows superior accuracy and computing speed. Binning a typical metagenome assembly takes only a few minutes on a single commodity workstation. We therefore recommend the community adopts MetaBAT 2 for their metagenome binning experiments. MetaBAT 2 is open source software and available at https://bitbucket.org/berkeleylab/metabat., Competing Interests: The authors declare that they have no competing interests.

Thermal radiation transfer between two objects separated by a subwavelength gap (near-field thermal radiation transfer) can be orders of magnitude larger than that in free space, which is attracting increasing attention with respect to both fundamental nanoscience and its potential for high-power-density and high-efficiency conversion of heat to electricity in thermophotovoltaic (TPV) systems. However, the realization of near-field thermal radiation transfer in TPV systems involves significant challenges because it requires a subwavelength gap and large temperature difference between the emitter and the PV cell while minimizing the heat transfer that does not contribute to the photocurrent generation. To overcome these challenges, here we demonstrate a one-chip near-field TPV device consisting of a thin-film Si emitter and InGaAs PV cell with an intermediate Si substrate, which enables the suppression of the heat transfer due to sub-bandgap radiation by free carriers and surface modes. Through the one-chip integration and thermal isolation using Si process technologies, we realize a deep subwavelength gap (<150 nm) between the emitter and the intermediate substrate without using any external positioners while maintaining a large temperature difference (>700 K). Compared to the equivalent device operating in the far-field regime, we achieve 10-fold enhancement of the photocurrent in the PV cell without degrading the open-circuit voltage and fill factor, demonstrating the potential of our one-chip device for the future applications of near-field thermal radiation transfer.

In order to enhance second-harmonic generation (SHG) efficiency in a waveguide-coupled photonic nanocavity, we introduce a reflector at the edge of the waveguide and investigate its influence on input power and SHG efficiency. SHG efficiency and critical input power of the reflective waveguide-coupled cavity are controlled by the reflection amplitude and phase delay of the reflector. At input powers considerably lower than the critical power, SHG efficiency increases by up to three orders of magnitude higher than the case without reflector. Moreover, SHG efficiency of 100% at critical input power, which is twice that of the previous result, can be achieved over a wide phase range. These results prove the feasibility and controllability of highly efficient nonlinear optical devices.

The toxicity and accumulation of zinc oxide nanoparticles (ZnO-NPs), ZnO microparticles (ZnO-MPs) and Zn ions were evaluated after long-term feeding with zinc-replenished food (1600 mg zinc equivalent per kg food) for 270 consecutive days. It was difficult for ZnO-NPs, ZnO-MPs and Zn ions were difficult to pass through the intestine barrier, and most of them were excreted mainly through feces. The distribution results showed that there was no noticeable difference among the distribution profiles of ZnO-NPs, ZnO-MPs and Zn ions in mice. Zn accumulated only in the digestive tract organs after the exposure to all three samples. However, the biomedical parameters and pathological investigations showed liver lesions induced by ZnO-MPs, but fewer by ZnO-NPs or Zn ions. The reason for the remarkably low in vivo toxicity of ZnO-NPs is discussed. Our findings suggest that ZnO-NPs are relatively biocompatible as the nutritional additive at the commonly used dose.

Enhancers and promoters commonly occur in accessible chromatin characterized by depleted nucleosome contact; however, it is unclear how chromatin accessibility is governed. We show that log-additive cis-acting DNA sequence features can predict chromatin accessibility at high spatial resolution. We develop a new type of high-dimensional machine learning model, the Synergistic Chromatin Model (SCM), which when trained with DNase-seq data for a cell type is capable of predicting expected read counts of genome-wide chromatin accessibility at every base from DNA sequence alone, with the highest accuracy at hypersensitive sites shared across cell types. We confirm that a SCM accurately predicts chromatin accessibility for thousands of synthetic DNA sequences using a novel CRISPR-based method of highly efficient site-specific DNA library integration. SCMs are directly interpretable and reveal that a logic based on local, nonspecific synergistic effects, largely among pioneer TFs, is sufficient to predict a large fraction of cellular chromatin accessibility in a wide variety of cell types., (© 2016 Hashimoto et al.; Published by Cold Spring Harbor Laboratory Press.)

Motivation: The majority of disease-associated variants identified in genome-wide association studies reside in noncoding regions of the genome with regulatory roles. Thus being able to interpret the functional consequence of a variant is essential for identifying causal variants in the analysis of genome-wide association studies., Results: We present GERV (generative evaluation of regulatory variants), a novel computational method for predicting regulatory variants that affect transcription factor binding. GERV learns a k-mer-based generative model of transcription factor binding from ChIP-seq and DNase-seq data, and scores variants by computing the change of predicted ChIP-seq reads between the reference and alternate allele. The k-mers learned by GERV capture more sequence determinants of transcription factor binding than a motif-based approach alone, including both a transcription factor's canonical motif and associated co-factor motifs. We show that GERV outperforms existing methods in predicting single-nucleotide polymorphisms associated with allele-specific binding. GERV correctly predicts a validated causal variant among linked single-nucleotide polymorphisms and prioritizes the variants previously reported to modulate the binding of FOXA1 in breast cancer cell lines. Thus, GERV provides a powerful approach for functionally annotating and prioritizing causal variants for experimental follow-up analysis., Availability and Implementation: The implementation of GERV and related data are available at http://gerv.csail.mit.edu/., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

DNA methylation acts in concert with restriction enzymes to protect the integrity of prokaryotic genomes. Studies in a limited number of organisms suggest that methylation also contributes to prokaryotic genome regulation, but the prevalence and properties of such non-restriction-associated methylation systems remain poorly understood. Here, we used single molecule, real-time sequencing to map DNA modifications including m6A, m4C, and m5C across the genomes of 230 diverse bacterial and archaeal species. We observed DNA methylation in nearly all (93%) organisms examined, and identified a total of 834 distinct reproducibly methylated motifs. This data enabled annotation of the DNA binding specificities of 620 DNA Methyltransferases (MTases), doubling known specificities for previously hard to study Type I, IIG and III MTases, and revealing their extraordinary diversity. Strikingly, 48% of organisms harbor active Type II MTases with no apparent cognate restriction enzyme. These active 'orphan' MTases are present in diverse bacterial and archaeal phyla and show motif specificities and methylation patterns consistent with functions in gene regulation and DNA replication. Our results reveal the pervasive presence of DNA methylation throughout the prokaryotic kingdoms, as well as the diversity of sequence specificities and potential functions of DNA methylation systems.

Parasitic helminth worms, such as Schistosoma mansoni, are endemic in regions with a high prevalence of tuberculosis (TB) among the population. Human studies suggest that helminth coinfections contribute to increased TB susceptibility and increased rates of TB reactivation. Prevailing models suggest that T helper type 2 (Th2) responses induced by helminth infection impair Th1 immune responses and thereby limit Mycobacterium tuberculosis (Mtb) control. Using a pulmonary mouse model of Mtb infection, we demonstrated that S. mansoni coinfection or immunization with S. mansoni egg antigens can reversibly impair Mtb-specific T cell responses without affecting macrophage-mediated Mtb control. Instead, S. mansoni infection resulted in accumulation of high arginase-1-expressing macrophages in the lung, which formed type 2 granulomas and exacerbated inflammation in Mtb-infected mice. Treatment of coinfected animals with an antihelminthic improved Mtb-specific Th1 responses and reduced disease severity. In a genetically diverse mouse population infected with Mtb, enhanced arginase-1 activity was associated with increased lung inflammation. Moreover, in patients with pulmonary TB, lung damage correlated with increased serum activity of arginase-1, which was elevated in TB patients coinfected with helminths. Together, our data indicate that helminth coinfection induces arginase-1-expressing type 2 granulomas, thereby increasing inflammation and TB disease severity. These results also provide insight into the mechanisms by which helminth coinfections drive increased susceptibility, disease progression, and severity in TB.

Background: The increased multi-omics information on carefully phenotyped patients in studies of complex diseases requires novel methods for data integration. Unlike continuous intensity measurements from most omics data sets, phenome data contain clinical variables that are binary, ordinal and categorical., Results: In this paper we introduce an integrative phenotyping framework (iPF) for disease subtype discovery. A feature topology plot was developed for effective dimension reduction and visualization of multi-omics data. The approach is free of model assumption and robust to data noises or missingness. We developed a workflow to integrate homogeneous patient clustering from different omics data in an agglomerative manner and then visualized heterogeneous clustering of pairwise omics sources. We applied the framework to two batches of lung samples obtained from patients diagnosed with chronic obstructive lung disease (COPD) or interstitial lung disease (ILD) with well-characterized clinical (phenomic) data, mRNA and microRNA expression profiles. Application of iPF to the first training batch identified clusters of patients consisting of homogenous disease phenotypes as well as clusters with intermediate disease characteristics. Analysis of the second batch revealed a similar data structure, confirming the presence of intermediate clusters. Genes in the intermediate clusters were enriched with inflammatory and immune functional annotations, suggesting that they represent mechanistically distinct disease subphenotypes that may response to immunomodulatory therapies. The iPF software package and all source codes are publicly available., Conclusions: Identification of subclusters with distinct clinical and biomolecular characteristics suggests that integration of phenomic and other omics information could lead to identification of novel mechanism-based disease sub-phenotypes.

Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Because of the complex nature of these communities, existing metagenome binning methods often miss a large number of microbial species. In addition, most of the tools are not scalable to large datasets. Here we introduce automated software called MetaBAT that integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency for accurate metagenome binning. MetaBAT outperforms alternative methods in accuracy and computational efficiency on both synthetic and real metagenome datasets. It automatically forms hundreds of high quality genome bins on a very large assembly consisting millions of contigs in a matter of hours on a single node. MetaBAT is open source software and available at https://bitbucket.org/berkeleylab/metabat.

Background: In modern biomedical research of complex diseases, a large number of demographic and clinical variables, herein called phenomic data, are often collected and missing values (MVs) are inevitable in the data collection process. Since many downstream statistical and bioinformatics methods require complete data matrix, imputation is a common and practical solution. In high-throughput experiments such as microarray experiments, continuous intensities are measured and many mature missing value imputation methods have been developed and widely applied. Numerous methods for missing data imputation of microarray data have been developed. Large phenomic data, however, contain continuous, nominal, binary and ordinal data types, which void application of most methods. Though several methods have been developed in the past few years, not a single complete guideline is proposed with respect to phenomic missing data imputation., Results: In this paper, we investigated existing imputation methods for phenomic data, proposed a self-training selection (STS) scheme to select the best imputation method and provide a practical guideline for general applications. We introduced a novel concept of "imputability measure" (IM) to identify missing values that are fundamentally inadequate to impute. In addition, we also developed four variations of K-nearest-neighbor (KNN) methods and compared with two existing methods, multivariate imputation by chained equations (MICE) and missForest. The four variations are imputation by variables (KNN-V), by subjects (KNN-S), their weighted hybrid (KNN-H) and an adaptively weighted hybrid (KNN-A). We performed simulations and applied different imputation methods and the STS scheme to three lung disease phenomic datasets to evaluate the methods. An R package "phenomeImpute" is made publicly available., Conclusions: Simulations and applications to real datasets showed that MICE often did not perform well; KNN-A, KNN-H and random forest were among the top performers although no method universally performed the best. Imputation of missing values with low imputability measures increased imputation errors greatly and could potentially deteriorate downstream analyses. The STS scheme was accurate in selecting the optimal method by evaluating methods in a second layer of missingness simulation. All source files for the simulation and the real data analyses are available on the author's publication website.

Summary: With the rapid advances and prevalence of high-throughput genomic technologies, integrating information of multiple relevant genomic studies has brought new challenges. Microarray meta-analysis has become a frequently used tool in biomedical research. Little effort, however, has been made to develop a systematic pipeline and user-friendly software. In this article, we present MetaOmics, a suite of three R packages MetaQC, MetaDE and MetaPath, for quality control, differentially expressed gene identification and enriched pathway detection for microarray meta-analysis. MetaQC provides a quantitative and objective tool to assist study inclusion/exclusion criteria for meta-analysis. MetaDE and MetaPath were developed for candidate marker and pathway detection, which provide choices of marker detection, meta-analysis and pathway analysis methods. The system allows flexible input of experimental data, clinical outcome (case-control, multi-class, continuous or survival) and pathway databases. It allows missing values in experimental data and utilizes multi-core parallel computing for fast implementation. It generates informative summary output and visualization plots, operates on different operation systems and can be expanded to include new algorithms or combine different types of genomic data. This software suite provides a comprehensive tool to conveniently implement and compare various genomic meta-analysis pipelines., Availability: http://www.biostat.pitt.edu/bioinfo/software.htm, Contact: ctseng@pitt.edu, Supplementary Information: Supplementary data are available at Bioinformatics online.

Genomic meta-analysis to combine relevant and homogeneous studies has been widely applied, but the quality control (QC) and objective inclusion/exclusion criteria have been largely overlooked. Currently, the inclusion/exclusion criteria mostly depend on ad-hoc expert opinion or naïve threshold by sample size or platform. There are pressing needs to develop a systematic QC methodology as the decision of study inclusion greatly impacts the final meta-analysis outcome. In this article, we propose six quantitative quality control measures, covering internal homogeneity of coexpression structure among studies, external consistency of coexpression pattern with pathway database, and accuracy and consistency of differentially expressed gene detection or enriched pathway identification. Each quality control index is defined as the minus log transformed P values from formal hypothesis testing. Principal component analysis biplots and a standardized mean rank are applied to assist visualization and decision. We applied the proposed method to 4 large-scale examples, combining 7 brain cancer, 9 prostate cancer, 8 idiopathic pulmonary fibrosis and 17 major depressive disorder studies, respectively. The identified problematic studies were further scrutinized for potential technical or biological causes of their lower quality to determine their exclusion from meta-analysis. The application and simulation results concluded a systematic quality assessment framework for genomic meta-analysis.

Tuberculosis (TB) is caused by the intracellular bacteria Mycobacterium tuberculosis, and kills more than 1.5 million people every year worldwide. Immunity to TB is associated with the accumulation of IFNγ-producing T helper cell type 1 (Th1) in the lungs, activation of M.tuberculosis-infected macrophages and control of bacterial growth. However, very little is known regarding the early immune responses that mediate accumulation of activated Th1 cells in the M.tuberculosis-infected lungs. To define the induction of early immune mediators in the M.tuberculosis-infected lung, we performed mRNA profiling studies and characterized immune cells in M.tuberculosis-infected lungs at early stages of infection in the mouse model. Our data show that induction of mRNAs involved in the recognition of pathogens, expression of inflammatory cytokines, activation of APCs and generation of Th1 responses occurs between day 15 and day 21 post infection. The induction of these mRNAs coincides with cellular accumulation of Th1 cells and activation of myeloid cells in M.tuberculosis-infected lungs. Strikingly, we show the induction of mRNAs associated with Gr1+ cells, namely neutrophils and inflammatory monocytes, takes place on day 12 and coincides with cellular accumulation of Gr1+ cells in M.tuberculosis-infected lungs. Interestingly, in vivo depletion of Gr1+ neutrophils between days 10-15 results in decreased accumulation of Th1 cells on day 21 in M.tuberculosis-infected lungs without impacting overall protective outcomes. These data suggest that the recruitment of Gr1+ neutrophils is an early event that leads to production of chemokines that regulate the accumulation of Th1 cells in the M.tuberculosis-infected lungs.

Motivation: Microarray experiments frequently produce multiple missing values (MVs) due to flaws such as dust, scratches, insufficient resolution or hybridization errors on the chips. Unfortunately, many downstream algorithms require a complete data matrix. The motivation of this work is to determine the impact of MV imputation on downstream analysis, and whether ranking of imputation methods by imputation accuracy correlates well with the biological impact of the imputation., Methods: Using eight datasets for differential expression (DE) and classification analysis and eight datasets for gene clustering, we demonstrate the biological impact of missing-value imputation on statistical downstream analyses, including three commonly employed DE methods, four classifiers and three gene-clustering methods. Correlation between the rankings of imputation methods based on three root-mean squared error (RMSE) measures and the rankings based on the downstream analysis methods was used to investigate which RMSE measure was most consistent with the biological impact measures, and which downstream analysis methods were the most sensitive to the choice of imputation procedure., Results: DE was the most sensitive to the choice of imputation procedure, while classification was the least sensitive and clustering was intermediate between the two. The logged RMSE (LRMSE) measure had the highest correlation with the imputation rankings based on the DE results, indicating that the LRMSE is the best representative surrogate among the three RMSE-based measures. Bayesian principal component analysis and least squares adaptive appeared to be the best performing methods in the empirical downstream evaluation.