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This portable and self-contained lightweight microprocessor based Ergonomic Dosimeter is designed to collect continuously postural angles of the torso and the upper arm in the sagittal plane and the number of kneeling activities. Up to 4 h of task performance data can be stored in a non-volatile memory of the dosimeter, which can then be downloaded to a lap-top computer. The portable dosimeter was tested for test-retest reliability, compared with posture data obtained with a computer-based video analysis system and evaluated at a carpenter's apprentices school and at a construction site. The dosimeter was shown to be suitable for collecting posture and kneeling data for a prolonged period at construction sites. Keywords: Carpentry task; Posture Analysis; Kneeling activity; Egonomic dosimeter

Abstract Background Differential co-expression analysis is an emerging strategy for characterizing disease related dysregulation of gene expression regulatory networks. Given pre-defined sets of biological samples, such analysis aims at identifying genes that are co-expressed in one, but not in the other set of samples. Results We developed a novel probabilistic framework for jointly uncovering contexts (i.e. groups of samples) with specific co-expression patterns, and groups of genes with different co-expression patterns across such contexts. In contrast to current clustering and bi-clustering procedures, the implicit similarity measure in this model used for grouping biological samples is based on the clustering structure of genes within each sample and not on traditional measures of gene expression level similarities. Within this framework, biological samples with widely discordant expression patterns can be placed in the same context as long as the co-clustering structure of genes is concordant within these samples. To the best of our knowledge, this is the first method to date for unsupervised differential co-expression analysis in this generality. When applied to the problem of identifying molecular subtypes of breast cancer, our method identified reproducible patterns of differential co-expression across several independent expression datasets. Sample groupings induced by these patterns were highly informative of the disease outcome. Expression patterns of differentially co-expressed genes provided new insights into the complex nature of the ERα regulatory network. Conclusions We demonstrated that the use of the co-clustering structure as the similarity measure in the unsupervised analysis of sample gene expression profiles provides valuable information about expression regulatory networks.

Abstract Background A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Results Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. Conclusion The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org.

Abstract Background Integration of biological knowledge encoded in various lists of functionally related genes has become one of the most important aspects of analyzing genome-wide functional genomics data. In the context of cluster analysis, functional coherence of clusters established through such analyses have been used to identify biologically meaningful clusters, compare clustering algorithms and identify biological pathways associated with the biological process under investigation. Results We developed a computational framework for analytically and visually integrating knowledge-based functional categories with the cluster analysis of genomics data. The framework is based on the simple, conceptually appealing, and biologically interpretable gene-specific functional coherence score (CLEAN score). The score is derived by correlating the clustering structure as a whole with functional categories of interest. We directly demonstrate that integrating biological knowledge in this way improves the reproducibility of conclusions derived from cluster analysis. The CLEAN score differentiates between the levels of functional coherence for genes within the same cluster based on their membership in enriched functional categories. We show that this aspect results in higher reproducibility across independent datasets and produces more informative genes for distinguishing different sample types than the scores based on the traditional cluster-wide analysis. We also demonstrate the utility of the CLEAN framework in comparing clusterings produced by different algorithms. CLEAN was implemented as an add-on R package and can be downloaded at http://Clusteranalysis.org. The package integrates routines for calculating gene specific functional coherence scores and the open source interactive Java-based viewer Functional TreeView (FTreeView). Conclusion Our results indicate that using the gene-specific functional coherence score improves the reproducibility of the conclusions made about clusters of co-expressed genes over using the traditional cluster-wide scores. Using gene-specific coherence scores also simplifies the comparisons of clusterings produced by different clustering algorithms and provides a simple tool for selecting genes with a "functionally coherent" expression profile.

Abstract Background Transcriptional modules (TM) consist of groups of co-regulated genes and transcription factors (TF) regulating their expression. Two high-throughput (HT) experimental technologies, gene expression microarrays and Chromatin Immuno-Precipitation on Chip (ChIP-chip), are capable of producing data informative about expression regulatory mechanism on a genome scale. The optimal approach to joint modeling of data generated by these two complementary biological assays, with the goal of identifying and characterizing TMs, is an important open problem in computational biomedicine. Results We developed and validated a novel probabilistic model and related computational procedure for identifying TMs by jointly modeling gene expression and ChIP-chip binding data. We demonstrate an improved functional coherence of the TMs produced by the new method when compared to either analyzing expression or ChIP-chip data separately or to alternative approaches for joint analysis. We also demonstrate the ability of the new algorithm to identify novel regulatory relationships not revealed by ChIP-chip data alone. The new computational procedure can be used in more or less the same way as one would use simple hierarchical clustering without performing any special transformation of data prior to the analysis. The R and C-source code for implementing our algorithm is incorporated within the R package gimmR which is freely available at http://eh3.uc.edu/gimm. Conclusion Our results indicate that, whenever available, ChIP-chip and expression data should be analyzed within the unified probabilistic modeling framework, which will likely result in improved clusters of co-regulated genes and improved ability to detect meaningful regulatory relationships. Given the good statistical properties and the ease of use, the new computational procedure offers a worthy new tool for reconstructing transcriptional regulatory networks.

Abstract Background The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating variability of gene expression measurements in microarray experiments is essential for correctly identifying differentially expressed genes. Several recently developed methods for testing differential expression of genes utilize hierarchical Bayesian models to "pool" information from multiple genes. We have developed a statistical testing procedure that further improves upon current methods by incorporating the well-documented relationship between the absolute gene expression level and the variance of gene expression measurements into the general empirical Bayes framework. Results We present a novel Bayesian moderated-T, which we show to perform favorably in simulations, with two real, dual-channel microarray experiments and in two controlled single-channel experiments. In simulations, the new method achieved greater power while correctly estimating the true proportion of false positives, and in the analysis of two publicly-available "spike-in" experiments, the new method performed favorably compared to all tested alternatives. We also applied our method to two experimental datasets and discuss the additional biological insights as revealed by our method in contrast to the others. The R-source code for implementing our algorithm is freely available at http://eh3.uc.edu/ibmt. Conclusion We use a Bayesian hierarchical normal model to define a novel Intensity-Based Moderated T-statistic (IBMT). The method is completely data-dependent using empirical Bayes philosophy to estimate hyperparameters, and thus does not require specification of any free parameters. IBMT has the strength of balancing two important factors in the analysis of microarray data: the degree of independence of variances relative to the degree of identity (i.e. t-tests vs. equal variance assumption), and the relationship between variance and signal intensity. When this variance-intensity relationship is weak or does not exist, IBMT reduces to a previously described moderated t-statistic. Furthermore, our method may be directly applied to any array platform and experimental design. Together, these properties show IBMT to be a valuable option in the analysis of virtually any microarray experiment.

In non-small cell lung cancer (NSCLC) treatment, radiotherapy responses are not durable and toxicity limits therapy. We find that AM-101, a synthetic benzodiazepine activator of GABA(A) receptor, impairs the viability and clonogenicity of both primary and brain-metastatic NSCLC cells. Employing a human-relevant ex vivo 'chip', AM-101 is as efficacious as docetaxel, a chemotherapeutic used with radiotherapy for advanced-stage NSCLC. In vivo, AM-101 potentiates radiation, including conferring a significant survival benefit to mice bearing NSCLC intracranial tumors generated using a patient-derived metastatic line. GABA(A) receptor activation stimulates a selective-autophagic response via the multimerization of GABA(A) receptor-associated protein, GABARAP, the stabilization of mitochondrial receptor Nix, and the utilization of ubiquitin-binding protein p62. A high-affinity peptide disrupting Nix binding to GABARAP inhibits AM-101 cytotoxicity. This supports a model of GABA(A) receptor activation driving a GABARAP-Nix multimerization axis that triggers autophagy. In patients receiving radiotherapy, GABA(A) receptor activation may improve tumor control while allowing radiation dose de-intensification to reduce toxicity.

We present an in silico approach for drug discovery, dubbed connectivity enhanced structure activity relationship (ceSAR). Building on the landmark LINCS library of transcriptional signatures of drug-like molecules and gene knockdowns, ceSAR combines cheminformatic techniques with signature concordance analysis to connect small molecules and their targets and further assess their biophysical compatibility using molecular docking. Candidate compounds are first ranked in a target structure-independent manner, using chemical similarity to LINCS analogs that exhibit transcriptomic concordance with a target gene knockdown. Top candidates are subsequently rescored using docking simulations and machine learning-based consensus of the two approaches. Using extensive benchmarking, we show that ceSAR greatly reduces false-positive rates, while cutting run times by multiple orders of magnitude and further democratizing drug discovery pipelines. We further demonstrate the utility of ceSAR by identifying and experimentally validating inhibitors of BCL2A1, an important antiapoptotic target in melanoma and preterm birth-associated inflammation.

Intrinsic resistance to targeted therapeutics in PTEN-deficient glioblastoma (GBM) is mediated by redundant signaling networks that sustain critical metabolic functions. Here, we demonstrate that coordinated inhibition of the ribosomal protein S6 kinase 1 (S6K1) and the receptor tyrosine kinase AXL using LY-2584702 and BMS-777607 can overcome network redundancy to reduce GBM tumor growth. This combination of S6K1 and AXL inhibition suppressed glucose flux to pyrimidine biosynthesis. Genetic inactivation studies to map the signaling network indicated that both S6K1 and S6K2 transmit growth signals in PTEN-deficient GBM. Kinome-wide ATP binding analysis in inhibitor-treated cells revealed that LY-2584702 directly inhibited S6K1, and substrate phosphorylation studies showed that BMS-777607 inactivation of upstream AXL collaborated to reduce S6K2-mediated signal transduction. Thus, combination targeting of S6K1 and AXL provides a kinase-directed therapeutic approach that circumvents signal transduction redundancy to interrupt metabolic function and reduce growth of PTEN-deficient GBM., Significance: Therapy for glioblastoma would be advanced by incorporating molecularly targeted kinase-directed agents, similar to standard of care strategies in other tumor types. Here, we identify a kinase targeting approach to inhibit the metabolism and growth of glioblastoma., (©2024 The Authors; Published by the American Association for Cancer Research.)

Background: Cardiac complications in patients with hypereosinophilia cause significant morbidity and mortality. However, mechanisms of how eosinophilic inflammation causes heart damage are poorly understood., Methods: We developed a model of hypereosinophilia-associated heart disease by challenging hypereosinophilic mice with peptide from the cardiac myosin heavy chain. Disease outcomes were measured by histology, immunohistochemistry, flow cytometry, and measurement of cells and biomarkers in peripheral blood. Eosinophil dependence was determined by using eosinophil-deficient mice (ΔdblGATA). Single cells from heart were subjected to single cell RNA sequencing to assess cell composition, subtypes and expression profiles., Results: Mice challenged with myocarditic and control peptide had peripheral blood leukocytosis, but only those challenged with myocarditic peptide had heart inflammation. Heart tissue was infiltrated by eosinophil-rich inflammatory infiltrates associated with cardiomyocyte damage. Disease penetrance and severity were dependent on the presence of eosinophils. Single cell RNA sequencing showed enrichment of myeloid cells, T-cells and granulocytes (neutrophils and eosinophils) in the myocarditic mice. Macrophages were M2 skewed, and eosinophils had an activated phenotype. Gene enrichment analysis identified several pathways potentially involved in pathophysiology of disease., Conclusion: Eosinophils are required for heart damage in hypereosinophilia-associated heart disease. Additionally, myeloid cells, granulocytes and T-cell cooperatively or independently participate in the pathogenesis of hypereosinophilia-associated heart disease.

Aberrant regulation of signal transduction pathways can adversely derail biological processes for tissue development. One such process is the embryonic eyelid closure that is dependent on the mitogen-activated protein kinase kinase kinase 1 (MAP3K1). Map3k1 KO in mice results in defective eyelid closure and an autosomal recessive eye-open at birth phenotype. We have shown that in utero exposure to dioxin, a persistent environmental toxicant, induces the same eye defect in Map3k1 +/- heterozygous but not WT pups. Here, we explore the mechanisms of the Map3k1 (gene) and dioxin (environment) interactions (GxE) underlying defective eyelid closure. We show that, acting through the aryl hydrocarbon receptor, dioxin activates epidermal growth factor receptor signaling, which in turn depresses MAP3K1-dependent Jun N-terminal kinase (JNK) activity. The dioxin-mediated JNK repression is moderate but is exacerbated by Map3k1 heterozygosity. Therefore, dioxin exposed Map3k1 +/- embryonic eyelids have a marked reduction of JNK activity, accelerated differentiation and impeded polarization in the epithelial cells. Knocking out Ahr or Egfr in eyelid epithelium attenuates the open-eye defects in dioxin-treated Map3k1 +/- pups, whereas knockout of Jnk1 and S1pr that encodes the sphigosin-1-phosphate (S1P) receptors upstream of the MAP3K1-JNK pathway potentiates the dioxin toxicity. Our novel findings show that the crosstalk of aryl hydrocarbon receptor, epidermal growth factor receptor, and S1P-MAP3K1-JNK pathways determines the outcome of dioxin exposure. Thus, gene mutations targeting these pathways are potential risk factors for the toxicity of environmental chemicals., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: High-grade gliomas (HGG) carry a poor prognosis, with glioblastoma accounting for almost 50% of primary brain malignancies in the elderly. Unfortunately, despite the use of multiple treatment modalities, the prognosis remains poor in this population. Our preclinical studies suggest that the presence of aromatase expression, encoded by CYP19A1, is significantly upregulated in HGGs. Remarkably, we find that letrozole (LTZ), an FDA-approved aromatase inhibitor, has marked activity against HGGs., Patients and Methods: We conducted a phase 0/I single-center clinical trial (NCT03122197) to assess the tumoral availability, pharmacokinetics (PK), safety, and tolerability of LTZ in recurrent patients with HGG. Planned dose cohorts included 2.5, 5, 10, 12.5, 15, 17.5, and 20 mg of LTZ administered daily pre- and postsurgery or biopsy. Tumor samples were assayed for LTZ content and relevant biomarkers. The recommended phase 2 dose (R2PD) was determined as the dose that resulted in predicted steady-state tumoral extracellular fluid (ECF; Css,ecf) >2 μmol/L and did not result in ≥33% dose-limiting adverse events (AE) assessed using CTCAE v5.0., Results: Twenty-one patients were enrolled. Common LTZ-related AEs included fatigue, nausea, musculoskeletal, anxiety, and dysphoric mood. No DLTs were observed. The 15 mg dose achieved a Css,ecf of 3.6 ± 0.59 μmol/L. LTZ caused dose-dependent inhibition of estradiol synthesis and modulated DNA damage pathways in tumor tissues as evident using RNA-sequencing analysis., Conclusions: On the basis of safety, brain tumoral PK, and mechanistic data, 15 mg daily is identified as the RP2D for future trials., (©2024 American Association for Cancer Research.)

Mitogen-activated protein 3 kinase 1 (MAP3K1) has a plethora of cell type-specific functions not yet fully understood. Herein, we describe a role for MAP3K1 in female reproductive tract (FRT) development. MAP3K1 kinase domain-deficient female mice exhibited an imperforate vagina, labor failure and infertility. These defects corresponded with shunted Müllerian ducts (MDs), the embryonic precursors of FRT, that manifested as a contorted caudal vagina and abrogated vaginal-urogenital sinus fusion in neonates. The MAP3K1 kinase domain is required for optimal activation of the Jun-N-terminal kinase (JNK) and cell polarity in the MD epithelium, and for upregulation of WNT signaling in the mesenchyme surrounding the caudal MD. The MAP3K1-deficient epithelial cells and MD epithelium had reduced expression of WNT7B ligands. Correspondingly, conditioned media derived from MAP3K1-competent, but not -deficient, epithelial cells activated a TCF/Lef-luciferase reporter in fibroblasts. These observations indicate that MAP3K1 regulates MD caudal elongation and FRT development, in part through the induction of paracrine factors in the epithelium that trans-activate WNT signaling in the mesenchyme., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2024. Published by The Company of Biologists Ltd.)

Key regulatory decisions during cleavage divisions in mammalian embryogenesis determine the fate of preimplantation embryonic cells. Single-cell RNA sequencing of early-stage-2-cell, 4-cell, and 8-cell-blastomeres show that the aryl hydrocarbon receptor (AHR), traditionally considered as an environmental sensor, directs blastomere differentiation. Disruption of AHR functions in Ahr knockout embryos or in embryos from dams exposed to dioxin, the prototypic xenobiotic AHR agonist, significantly impairs blastocyst formation, causing repression and loss of transcriptional heterogeneity of OCT4 and CDX2 and incidence of nonspecific downregulation of pluripotency. Trajectory-the path of differentiation-and gene variability analyses further confirm that deregulation of OCT4 functions and changes of transcriptional heterogeneity resulting from disruption of AHR functions restrict the emergence of differentiating blastomeres in 4-cell embryos. It appears that AHR directs the differentiation of progenitor blastomeres and that disruption of preimplantation AHR functions may significantly perturb embryogenesis leading to long-lasting conditions at the heart of disease in offspring's adulthood., (© 2022. The Author(s).)

Microtubule-associated protein 1 light chain 3 gamma (MAP1LC3C or LC3C) is a member of the microtubule-associated family of proteins that are essential in the formation of autophagosomes and lysosomal degradation of cargo. LC3C has tumor-suppressing activity, and its expression is dependent on kidney cancer tumor suppressors, such as von Hippel-Lindau protein and folliculin. Recently, we demonstrated that LC3C autophagy is regulated by noncanonical upstream regulatory complexes and targets for degradation postdivision midbody rings associated with cancer cell stemness. Here, we show that loss of LC3C leads to peripheral positioning of the lysosomes and lysosomal exocytosis (LE). This process is independent of the autophagic activity of LC3C. Analysis of isogenic cells with low and high LE shows substantial transcriptomic reprogramming with altered expression of zinc (Zn)-related genes and activity of polycomb repressor complex 2, accompanied by a robust decrease in intracellular Zn. In addition, metabolomic analysis revealed alterations in amino acid steady-state levels. Cells with augmented LE show increased tumor initiation properties and form aggressive tumors in xenograft models. Immunocytochemistry identified high levels of lysosomal-associated membrane protein 1 on the plasma membrane of cancer cells in human clear cell renal cell carcinoma and reduced levels of Zn, suggesting that LE occurs in clear cell renal cell carcinoma, potentially contributing to the loss of Zn. These data indicate that the reprogramming of lysosomal localization and Zn metabolism with implication for epigenetic remodeling in a subpopulation of tumor-propagating cancer cells is an important aspect of tumor-suppressing activity of LC3C., Competing Interests: Conflict of interest The authors declare that they do not have conflicts of interests with the content of this article., (Published by Elsevier Inc.)

Background: In the United States, the illicit use of synthetic opioids such as fentanyl has led to a serious public health crisis. Synthetic opioids are known to enhance viral replication and to suppress immunologic responses, but their effects on HIV pathogenesis remain unclear. Thus, we examined the impact of fentanyl on HIV-susceptible and HIV-infected cell types., Methods: TZM-bl and HIV-infected lymphocyte cells were incubated with fentanyl at varying concentrations. Expression levels of the CXCR4 and CCR5 chemokine receptors and HIV p24 antigen were quantified with ELISA. HIV proviral DNA was quantified using SYBR RT-PCR. Cell viability was detected with the MTT assay. RNAseq was performed to characterize cellular gene regulation in the presence of fentanyl., Results: Fentanyl enhanced expression of both chemokine receptor levels in a dose-dependent manner in HIV-susceptible and infected cell lines. Similarly, fentanyl induced viral expression in HIV-exposed TZM-bl cells and in HIV-infected lymphocyte cell lines. Multiple genes associated with apoptosis, antiviral/interferon response, chemokine signaling, and NFκB signaling were differentially regulated., Conclusions: Synthetic opioid fentanyl impacts HIV replication and chemokine co-receptor expression. Increased virus levels suggest that opioid use may increase the likelihood of transmission and accelerate disease progression.

Background: The objective was to assess secretion of small extracellular vesicular microRNA (exo-miRNA) in head and neck squamous cell carcinoma (HNSCC) according to human papillomavirus (HPV) status, and determine the translational potential as a liquid biopsy for early detection., Methods: This study employed a combination of cell culture and case-control study design using archival pretreatment serum. Small extracellular vesicles (sEV) were isolated from conditioned culture media and human serum samples via differential ultracentrifugation. miRNA-sequencing was performed on each sEV isolate., Results: There were clear exo-miRNA profiles that distinguished HNSCC cell lines from nonpathologic oral epithelial control cells. While there was some overlap among profiles across all samples, there were apparent differences in exo-miRNA profiles according to HPV-status. Importantly, differential exo-miRNA profiles were also apparent in serum from early-stage HNSCC cases relative to cancer-free controls., Conclusions: Our findings indicate that exo-miRNA are highly dysregulated in HNSCC and support the potential of exo-miRNA as biomarkers for HNSCC., (© 2022 The Authors. Head & Neck published by Wiley Periodicals LLC.)

Background: Lupus nephritis (LN) is the most common and serious complication of systemic lupus erythematosus (SLE). LN pathogenesis is not fully understood. Axl receptor tyrosine kinase is upregulated and contributes to the pathogenic progress in LN. We have reported that Axl disruption attenuates nephritis development in mice., Methods: In this study, we analyzed the gene expression profiles with RNA-seq using renal cortical samples from nephritic mice. Axl-KO mice were bred onto a B6.lpr spontaneous lupus background, and renal disease development was followed and compared to the Axl-sufficient B6.lpr mice. Finally, anti-glomerular basement membrane (anti-GBM) Ab-induced nephritic mice were treated with Axl small molecule inhibitor, R428, at different stages of nephritis development. Blood urine nitrogen levels and renal pathologies were evaluated., Results: Transcriptome analysis revealed that renal Axl activation contributed to cell proliferation, survival, and motility through regulation of the Akt, c-Jun, and actin pathways. Spontaneous lupus-prone B6.lpr mice with Axl deficiency showed significantly reduced kidney damages and decreased T cell infiltration compared to the renal damage and T cell infiltration in Axl-sufficient B6.lpr mice. The improved kidney function was independent of autoAb production. Moreover, R428 significantly reduced anti-GBM glomerulonephritis at different stages of GN development compared to the untreated nephritic control mice. R428 administration reduced inflammatory cytokine (IL-6) production, T cell infiltration, and nephritis disease activity., Conclusions: Results from this study emphasize the important role of Axl signaling in LN and highlight Axl as an attractive target in LN., (© 2022. The Author(s).)

Background: Metformin slows tumor growth and progression in vitro, and in combination with chemoradiotherapy, resulted in high overall survival in patients with head and neck cancer squamous cell carcinoma (HNSCC) in our phase 1 clinical trial (NCT02325401). Metformin is also postulated to activate an antitumor immune response. Here, we investigate immunologic effects of metformin on natural killer (NK) and natural killer T cells, including results from two phase I open-label studies in patients with HNSCC treated with metformin (NCT02325401, NCT02083692)., Methods: Peripheral blood was collected before and after metformin treatment or from newly diagnosed patients with HNSCC. Peripheral immune cell phenotypes were evaluated using flow cytometry, cytokine expression by ELISA and/or IsoLight, and NK cell-mediated cytotoxicity was determined with a flow-based NK cell cytotoxicity assay (NKCA). Patient tumor immune infiltration before and after metformin treatment was analyzed with immunofluorescence. NK cells were treated with either vehicle or metformin and analyzed by RNA sequencing (RNA-seq). NK cells were then treated with inhibitors of significant pathways determined by RNA-seq and analyzed by NKCA, ELISA, and western blot analyses., Results: Increased peripheral NK cell activated populations were observed in patients treated with metformin. NK cell tumor infiltration was enhanced in patients with HNSCC treated with metformin preoperatively. Metformin increased antitumorigenic cytokines ex vivo, including significant increases in perforin. Metformin increased HNSCC NK cell cytotoxicity and inhibited the CXCL1 pathway while stimulating the STAT1 pathway within HNSCC NK cells. Exogenous CXCL1 prevented metformin-enhanced NK cell-mediated cytotoxicity. Metformin-mediated NK cell cytotoxicity was found to be AMP-activated protein kinase independent, but dependent on both mechanistic target of rapamycin and pSTAT1., Conclusions: Our data identifies a new role for metformin-mediated immune antitumorigenic function through NK cell-mediated cytotoxicity and downregulation of CXCL1 in HNSCC. These findings will inform future immunomodulating therapies in HNSCC., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

MicroRNAs (miRNAs) are small non-coding RNA that are powerful regulators of gene expression and can affect the expression of hundreds of genes. miRNAs can be packed in small extracellular vesicles (SEV) and released into the extracellular space by neurons and microglia to act locally as well as pass through the blood-brain barrier and act systemically. We sought to understand the differences in neuronal SEV miRNA expression between frontotemporal dementia (FTD), Alzheimer's disease (AD), and healthy aging. Plasma was obtained from FTD, AD, and healthy aging participants that were matched based on age, sex, and race/ethnicity. Additionally, a subset of participants also provided paired cerebrospinal fluid samples to compare neuronal SEV miRNAs in plasma and cerebrospinal fluid. Neuronal SEV were isolated using differential ultracentrifugation and antibody conjugated Dynabeads® for the neuronal surface marker, L1CAM. RNA sequencing was performed. 12 FTD, 11 with AD, and 10 healthy aging participants were enrolled in the study. In FTD, SEV miRNA-181c was downregulated compared to healthy controls. In AD, miRNA-122 and miRNA-3591 were downregulated compared to those in healthy controls and FTD. Using an FDR <0.2, only miRNA-21-5p was found to have increased expression in the cerebrospinal fluid compared to plasma in a group of AD and FTD participants. SEV miRNA-181c is significantly downregulated in FTD compared to healthy controls and may mediate its effects through microglial-directed neuroinflammation and interaction with TAR DNA-binding protein 43 (TDP-43) based on pathway analysis. Additionally, the FOXO and Hippo pathways may be important mediators of FTD, based on pathway analysis. Lastly, because only one SEV miRNA was differentially expressed between the plasma and cerebrospinal fluid in paired samples, plasma represents an appropriate biofluid for studying neuronal SEV miRNA., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc.)

There are only a few platforms that integrate multiple omics data types, bioinformatics tools, and interfaces for integrative analyses and visualization that do not require programming skills. Here we present iLINCS ( http://ilincs.org ), an integrative web-based platform for analysis of omics data and signatures of cellular perturbations. The platform facilitates mining and re-analysis of the large collection of omics datasets (>34,000), pre-computed signatures (>200,000), and their connections, as well as the analysis of user-submitted omics signatures of diseases and cellular perturbations. iLINCS analysis workflows integrate vast omics data resources and a range of analytics and interactive visualization tools into a comprehensive platform for analysis of omics signatures. iLINCS user-friendly interfaces enable execution of sophisticated analyses of omics signatures, mechanism of action analysis, and signature-driven drug repositioning. We illustrate the utility of iLINCS with three use cases involving analysis of cancer proteogenomic signatures, COVID 19 transcriptomic signatures and mTOR signaling., (© 2022. The Author(s).)

Millions of transcriptome samples were generated by the Library of Integrated Network-based Cellular Signatures (LINCS) program. When these data are processed into searchable signatures along with signatures extracted from Genotype-Tissue Expression (GTEx) and Gene Expression Omnibus (GEO), connections between drugs, genes, pathways and diseases can be illuminated. SigCom LINCS is a webserver that serves over a million gene expression signatures processed, analyzed, and visualized from LINCS, GTEx, and GEO. SigCom LINCS is built with Signature Commons, a cloud-agnostic skeleton Data Commons with a focus on serving searchable signatures. SigCom LINCS provides a rapid signature similarity search for mimickers and reversers given sets of up and down genes, a gene set, a single gene, or any search term. Additionally, users of SigCom LINCS can perform a metadata search to find and analyze subsets of signatures and find information about genes and drugs. SigCom LINCS is findable, accessible, interoperable, and reusable (FAIR) with metadata linked to standard ontologies and vocabularies. In addition, all the data and signatures within SigCom LINCS are available via a well-documented API. In summary, SigCom LINCS, available at https://maayanlab.cloud/sigcom-lincs, is a rich webserver resource for accelerating drug and target discovery in systems pharmacology., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)