The size of skeletal muscle cells is precisely regulated by intracellular signaling networks that determine the balance between overall rates of protein synthesis and degradation. Myofiber growth and protein synthesis are stimulated by the IGF-1/Akt/mammalian target of rapamycin (mTOR) pathway. In this study, we show that the transcription factor JunB is also a major determinant of whether adult muscles grow or atrophy. We found that in atrophying myotubes, JunB is excluded from the nucleus and that decreasing JunB expression by RNA interference in adult muscles causes atrophy. Furthermore, JunB overexpression induces hypertrophy without affecting satellite cell proliferation and stimulated protein synthesis independently of the Akt/mTOR pathway. When JunB is transfected into denervated muscles, fiber atrophy is prevented. JunB blocks FoxO3 binding to atrogin-1 and MuRF-1 promoters and thus reduces protein breakdown. Therefore, JunB is important not only in dividing populations but also in adult muscle, where it is required for the maintenance of muscle size and can induce rapid hypertrophy and block atrophy.

The regulation of energy homeostasis integrates diverse biological processes ranging from behavior to metabolism and is linked fundamentally to numerous disease states. To identify new molecules that can bypass homeostatic compensatory mechanisms of energy balance in intact animals, we screened for small-molecule modulators of Caenorhabditis elegans fat content. We report on several molecules that modulate fat storage without obvious deleterious effects on feeding, growth and reproduction. A subset of these compounds also altered fat storage in mammalian and insect cell culture. We found that one of the newly identified compounds exerts its effects in C. elegans through a pathway that requires previously undescribed functions of an AMP-activated kinase catalytic subunit and a transcription factor previously unassociated with fat regulation. Thus, our strategy identifies small molecules that are effective within the context of intact animals and reveals relationships between new pathways that operate across phyla to influence energy homeostasis.

Metabolic syndrome is a cluster of risk factors, such as obesity, insulin resistance, and hyperlipidemia that increases the individual's likelihood of developing cardiovascular diseases. Patients inflicted with metabolic disorders also suffer from tissue repair defect. Mitsugumin 53 (MG53) is a protein essential to cellular membrane repair. It facilitates the nucleation of intracellular vesicles to sites of membrane disruption to create repair patches, contributing to the regenerative capacity of skeletal and cardiac muscle tissues upon injury. Since individuals suffering from metabolic syndrome possess tissue regeneration deficiency and MG53 plays a crucial role in restoring membrane integrity, we studied MG53 activity in mice models exhibiting metabolic disorders induced by a 6 month high-fat diet (HFD) feeding. Western blotting showed that MG53 expression is not altered within the skeletal and cardiac muscles of mice with metabolic syndrome. Rather, we found that MG53 levels in blood circulation were actually reduced. This data directly contradicts findings presented by Song et. al that indict MG53 as a causative factor for metabolic syndrome (Nature 494, 375-379). The diminished MG53 serum level observed may contribute to the inadequate tissue repair aptitude exhibited by diabetic patients. Furthermore, immunohistochemical analyses reveal that skeletal muscle fibers of mice with metabolic disorders experience localization of subcellular MG53 around mitochondria. This clustering may represent an adaptive response to oxidative stress resulting from HFD feeding and may implicate MG53 as a guardian to protect damaged mitochondria. Therapeutic approaches that elevate MG53 expression in serum circulation may be a novel method to treat the degenerative tissue repair function of diabetic patients.

The goal of the current study is to examine the biological effects of epithelial-specific tumor suppressor maspin on tumor host immune response. Accumulated evidence demonstrates an anti-tumor effect of maspin on tumor growth, invasion and metastasis. The molecular mechanism underlying these biological functions of maspin is thought to be through histone deacetylase inhibition, key to the maintenance of differentiated epithelial phenotype. Since tumor-driven stromal reactivities co-evolve in tumor progression and metastasis, it is not surprising that maspin expression in tumor cells inhibits extracellular matrix degradation, increases fibrosis and blocks hypoxia-induced angiogenesis. Using the athymic nude mouse model capable of supporting the growth and progression of xenogeneic human prostate cancer cells, we further demonstrate that maspin expression in tumor cells elicits neutrophil- and B cells-dependent host tumor immunogenicity. Specifically, mice bearing maspin-expressing tumors exhibited increased systemic and intratumoral neutrophil maturation, activation and antibody-dependent cytotoxicity, and decreased peritumoral lymphangiogenesis. These results reveal a novel biological function of maspin in directing host immunity towards tumor elimination that helps explain the significant reduction of xenograft tumor incidence in vivo and the clinical correlation of maspin with better prognosis of several types of cancer. Taken together, our data raised the possibility for novel maspin-based cancer immunotherapies.

The preclinical models of pancreatic adenocarcinoma provide an alternative means for determining the mechanisms of malignancy and possibilities for treatments, thus representing a resource of immense potential for cancer treatment in medicine. To evaluate different tumor models, quantifiable magnetic resonance imaging (MRI) techniques can play a significant role in identifying valuable in vivo biomarkers of tumor characteristics. We characterized three models of pancreatic cancer with multiparametric MRI techniques. Tumor stromal density of each tumor was measured using diffusion-weighted imaging and magnetization transfer (MT-MRI). Histologic measurement showed a similar trend with tumor fibrosis levels. Results indicated that MRI measurements can serve as a valuable tool in identifying and evaluating tumor characteristics.

Vertebrate tissues exhibit mechanical homeostasis, showing stable stiffness and tension over time and recovery after changes in mechanical stress. However, the regulatory pathways that mediate these effects are unknown. A comprehensive identification of Argonaute 2-associated microRNAs and mRNAs in endothelial cells identified a network of 122 microRNA families that target 73 mRNAs encoding cytoskeletal, contractile, adhesive and extracellular matrix (CAM) proteins. The level of these microRNAs increased in cells plated on stiff versus soft substrates, consistent with homeostasis, and suppressed targets via microRNA recognition elements within the 3' untranslated regions of CAM mRNAs. Inhibition of DROSHA or Argonaute 2, or disruption of microRNA recognition elements within individual target mRNAs, such as connective tissue growth factor, induced hyper-adhesive, hyper-contractile phenotypes in endothelial and fibroblast cells in vitro, and increased tissue stiffness, contractility and extracellular matrix deposition in the zebrafish fin fold in vivo. Thus, a network of microRNAs buffers CAM expression to mediate tissue mechanical homeostasis.

Mitogen-activated protein kinase (MAPK) signaling consists of an array of successively acting kinases. The extracellular signal-regulated kinases 1/2 (ERK1/2) are major components of the greater MAPK cascade that transduce growth factor signaling at the cell membrane. Here we investigated ERK1/2 signaling in skeletal muscle homeostasis and disease. Using mouse genetics, we observed that the muscle-specific expression of a constitutively active MEK1 mutant promotes greater ERK1/2 signaling that mediates fiber-type switching to a slow, oxidative phenotype with type I myosin heavy chain expression. Using a conditional and temporally regulated Cre strategy as well as Mapk1 (ERK2) and Mapk3 (ERK1) genetically targeted mice, MEK1-ERK2 signaling was shown to underlie this fast-to-slow fiber type switching in adult skeletal muscle as well as during development. Physiologic assessment of these activated MEK1-ERK1/2 mice showed enhanced metabolic activity and oxygen consumption with greater muscle fatigue resistance. Moreover, induction of MEK1-ERK1/2 signaling increased dystrophin and utrophin protein expression in a mouse model of limb-girdle muscle dystrophy and protected myofibers from damage. In summary, sustained MEK1-ERK1/2 activity in skeletal muscle produces a fast-to-slow fiber-type switch that protects from muscular dystrophy, suggesting a therapeutic approach to enhance the metabolic effectiveness of muscle and protect from dystrophic disease.

Pancreatic ductal adenocarcinoma (PDA) is characterized by a pronounced fibroinflammatory stromal reaction consisting of inordinate levels of hyaluronan (HA), collagen, immune cells, and activated fibroblasts that work in concert to generate a robust physical barrier to the perfusion and diffusion of small molecule therapeutics. The targeted depletion of hyaluronan with a PEGylated recombinant human hyaluronidase (PEGPH20) lowers interstitial gel-fluid pressures and re-expands collapsed intratumoral vasculature, improving the delivery of concurrently administered agents. Here we report a non-invasive means of assessing biophysical responses to stromal intervention with quantitative multiparametric magnetic resonance imaging (MRI) at 14 Tesla (T). We found that spin-spin relaxation time T2 values and glycosaminoglycan chemical exchange saturation transfer (GagCEST) values decreased at 24 h, reflecting depletion of intratumoral HA content, and that these parameters recovered at 7 days concurrent with replenishment of intratumoral HA. This was also reflected in an increase in low-b apparent diffusion coefficient (ADC) at 24 h, consistent with improved tumor perfusion that again normalized at 7 days after treatment. Phantom imaging suggests that the GagCEST signal is driven by changes in HA versus other glycosaminoglycans. Thus, multiparametric magnetic resonance imaging (MRI) can be used as a non-invasive tool to assess therapeutic responses to targeted stromal therapy in PDA and likely other stroma-rich solid tumors that have high levels of hyaluronan and collagen.

There has been much effort to prioritize genomic variants with respect to their impact on "function". However, function is often not precisely defined: sometimes it is the disease association of a variant; on other occasions, it reflects a molecular effect on transcription or epigenetics. Here, we coupled multiple genomic predictors to build GRAM, a GeneRAlized Model, to predict a well-defined experimental target: the expression-modulating effect of a non-coding variant on its associated gene, in a transferable, cell-specific manner. Firstly, we performed feature engineering: using LASSO, a regularized linear model, we found transcription factor (TF) binding most predictive, especially for TFs that are hubs in the regulatory network; in contrast, evolutionary conservation, a popular feature in many other variant-impact predictors, has almost no contribution. Moreover, TF binding inferred from in vitro SELEX is as effective as that from in vivo ChIP-Seq. Second, we implemented GRAM integrating only SELEX features and expression profiles; thus, the program combines a universal regulatory score with an easily obtainable modifier reflecting the particular cell type. We benchmarked GRAM on large-scale MPRA datasets, achieving AUROC scores of 0.72 in GM12878 and 0.66 in a multi-cell line dataset. We then evaluated the performance of GRAM on targeted regions using luciferase assays in the MCF7 and K562 cell lines. We noted that changing the insertion position of the construct relative to the reporter gene gave very different results, highlighting the importance of carefully defining the exact prediction target of the model. Finally, we illustrated the utility of GRAM in fine-mapping causal variants and developed a practical software pipeline to carry this out. In particular, we demonstrated in specific examples how the pipeline could pinpoint variants that directly modulate gene expression within a larger linkage-disequilibrium block associated with a phenotype of interest (e.g., for an eQTL).

The robust fibroinflammatory stroma characteristic of pancreatic ductal adenocarcinoma (PDA) impedes effective drug delivery. Pulsed focused ultrasound (pFUS) can disrupt this stroma and has improved survival in an early clinical trial. Non-invasive methods to characterize pFUS treatment effects are desirable for advancement of this promising treatment modality in larger clinical trials.

Pancreatic ductal adenocarcinoma (PDA) is a fatal disease with very poor prognosis. Development of sensitive and noninvasive methods to monitor tumor progression in PDA is a critical and unmet need. Magnetic resonance imaging (MRI) can noninvasively provide information regarding underlying pathophysiological processes such as necrosis, inflammatory changes and fibrotic tissue deposition.

Management of breast cancer in limited-resource settings is hindered by a lack of low-cost, logistically sustainable approaches toward molecular and cellular diagnostic pathology services that are needed to guide therapy. To address these limitations, we have developed a multimodal cellphone-based platform-the EpiView-D4-that can evaluate both cellular morphology and molecular expression of clinically relevant biomarkers directly from fine-needle aspiration (FNA) of breast tissue specimens within 1 h. The EpiView-D4 is comprised of two components: (1) an immunodiagnostic chip built upon a "non-fouling" polymer brush-coating (the "D4") which quantifies expression of protein biomarkers directly from crude cell lysates, and (2) a custom cellphone-based optical microscope ("EpiView") designed for imaging cytology preparations and D4 assay readout. As a proof-of-concept, we used the EpiView-D4 for assessment of human epidermal growth factor receptor-2 (HER2) expression and validated the performance using cancer cell lines, animal models, and human tissue specimens. We found that FNA cytology specimens (prepared in less than 5 min with rapid staining kits) imaged by the EpiView-D4 were adequate for assessment of lesional cellularity and tumor content. We also found our device could reliably distinguish between HER2 expression levels across multiple different cell lines and animal xenografts. In a pilot study with human tissue (n = 19), we were able to accurately categorize HER2-negative and HER2-positve tumors from FNA specimens. Taken together, the EpiView-D4 offers a promising alternative to invasive-and often unavailable-pathology services and may enable the democratization of effective breast cancer management in limited-resource settings.

Highly sensitive, specific, and point-of-care (POC) serological assays are an essential tool to manage coronavirus disease 2019 (COVID-19). Here, we report on a microfluidic POC test that can profile the antibody response against multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigens-spike S1 (S1), nucleocapsid (N), and the receptor binding domain (RBD)-simultaneously from 60 μl of blood, plasma, or serum. We assessed the levels of antibodies in plasma samples from 31 individuals (with longitudinal sampling) with severe COVID-19, 41 healthy individuals, and 18 individuals with seasonal coronavirus infections. This POC assay achieved high sensitivity and specificity, tracked seroconversion, and showed good concordance with a live virus microneutralization assay. We can also detect a prognostic biomarker of severity, IP-10 (interferon-γ-induced protein 10), on the same chip. Because our test requires minimal user intervention and is read by a handheld detector, it can be globally deployed to combat COVID-19.

The earliest measurable changes to postinjury platelet biology may be in the platelet transcriptome, as platelets are known to carry messenger ribonucleic acids (RNAs), and there is evidence in other inflammatory and infectious disease states of differential and alternative platelet RNA splicing in response to changing physiology. Thus, the aim of this exploratory pilot study was to examine the platelet transcriptome and platelet RNA splicing signatures in trauma patients compared with healthy donors.

The prevalence of psoriasis differs by population, and it appears to be more common among Europeans than in East Asians. Recent genome-wide association studies (GWAS) have identified alleles that increase the risk of psoriasis, and these alleles may present different frequencies in different geographic regions.

Sample-wise deconvolution methods have been developed to estimate cell-type proportions and gene expressions in bulk-tissue samples. However, the performance of these methods and their biological applications has not been evaluated, particularly on human brain transcriptomic data. Here, nine deconvolution methods were evaluated with sample-matched data from bulk-tissue RNAseq, single-cell/nuclei (sc/sn) RNAseq, and immunohistochemistry. A total of 1,130,767 nuclei/cells from 149 adult postmortem brains and 72 organoid samples were used. The results showed the best performance of dtangle for estimating cell proportions and bMIND for estimating sample-wise cell-type gene expression. For eight brain cell types, 25,273 cell-type eQTLs were identified with deconvoluted expressions (decon-eQTLs). The results showed that decon-eQTLs explained more schizophrenia GWAS heritability than bulk-tissue or single-cell eQTLs alone. Differential gene expression associated with multiple phenotypes were also examined using the deconvoluted data. Our findings, which were replicated in bulk-tissue RNAseq and sc/snRNAseq data, provided new insights into the biological applications of deconvoluted data.

Pressure ulcers (PUs) are a prevalent skin disease affecting patients with impaired mobility and in high-risk groups. These ulcers increase patients' suffering, medical expenses, and burden on medical staff. This study introduces a clinical decision support system and verifies it for predicting real-time PU occurrences within the intensive care unit (ICU) by using MIMIC-IV and in-house ICU data. We develop various machine learning (ML) and deep learning (DL) models for predicting PU occurrences in real time using the MIMIC-IV and validate using the MIMIC-IV and Kangwon National University Hospital (KNUH) dataset. To address the challenge of missing values in time series, we propose a novel recurrent neural network model, GRU-D++. This model outperformed other experimental models by achieving the area under the receiver operating characteristic curve (AUROC) of 0.945 for the on-time prediction and AUROC of 0.912 for 48h in-advance prediction. Furthermore, in the external validation with the KNUH dataset, the fine-tuned GRU-D++ model demonstrated superior performances, achieving an AUROC of 0.898 for on-time prediction and an AUROC of 0.897 for 48h in-advance prediction. The proposed GRU-D++, designed to consider temporal information and missing values, stands out for its predictive accuracy. Our findings suggest that this model can significantly alleviate the workload of medical staff and prevent the worsening of patient conditions by enabling timely interventions for PUs in the ICU.

A key issue in drug design is how population variation affects drug efficacy by altering binding affinity (BA) in different individuals, an essential consideration for government regulators. Ideally, we would like to evaluate the BA perturbations of millions of single-nucleotide variants (SNVs). However, only hundreds of protein-drug complexes with SNVs have experimentally characterized BAs, constituting too small a gold standard for straightforward statistical model training. Thus, we take a hybrid approach: using physically based calculations to bootstrap the parameterization of a full model. In particular, we do 3D structure-based docking on ∼10,000 SNVs modifying known protein-drug complexes to construct a pseudo gold standard. Then we use this augmented set of BAs to train a statistical model combining structure, ligand and sequence features and illustrate how it can be applied to millions of SNVs. Finally, we show that our model has good cross-validated performance (97% AUROC) and can also be validated by orthogonal ligand-binding data.

Transcriptional activation domains (TADs) are difficult to predict and identify, since they are not conserved and have little consensus. Here, we describe a yeast-based screening method that is able to identify individual amino acid residues involved in transcriptional activation in a high throughput manner. A plant transcriptional activator, PIF3 (phytochrome interacting factor 3), was fused to the yeast GAL4-DNA-binding Domain (BD), driving expression of the URA3 (Orotidine 5'-phosphate decarboxylase) reporter, and used for negative selection on 5-fluroorotic acid (5FOA). Randomly mutagenized variants of PIF3 were then selected for a loss or reduction in transcriptional activation activity by survival on FOA. In the process, we developed a strategy to eliminate false positives from negative selection that can be used for both reverse-1- and 2-hybrid screens. With this method we were able to identify two distinct regions in PIF3 with transcriptional activation activity, both of which are functionally conserved in PIF1, PIF4, and PIF5. Both are collectively necessary for full PIF3 transcriptional activity, but neither is sufficient to induce transcription autonomously. We also found that the TAD appear to overlap physically with other PIF3 functions, such as phyB binding activity and consequent phosphorylation. Our protocol should provide a valuable tool for identifying, analyzing and characterizing novel TADs in eukaryotic transcription factors, and thus potentially contribute to the unraveling of the mechanism underlying transcriptional activation.

Measuring expression profiles of inflammatory biomarkers is important in monitoring the polarization of immune responses; therefore, results should be independent of quantitation methods if they are to be accepted as validated clinical pathology biomarkers. To evaluate effects of differing quantitation methods, the seven major circulating Th1/Th2/Th17 cytokines interleukin 2 (IL-2), interferon γ (IFN-γ), tumor necrosis factor α (TNF-α), IL-4, IL-6, IL-10 and IL-17A were quantified in plasma of lipopolysaccharide (LPS)-treated mice with two different multiplex platforms.