Estimating Variation in Surface Emissivities of Intertidal Macroalgae using an Infrared Thermometer and the Effects on Temperature Measurements

Accurate measurements of surface temperatures with an infrared (IR) thermometer require input of the emissivities of the surfaces being measured; however, few determinations of the emissivities of intertidal organisms’ surfaces have been made. Emissivities of intertidal macroalgae were measured to determine whether algal species, measurement angle, hydration, and layering affected them. Emissivities were similar and averaged 0.94 among 11 of 13 species. The species with lower and more variable emissivities (Chondracanthus exasperatus and Desmarestia viridis) differed in morphology from the other species, which were relatively flat thin blades with little surface texture. Measurement angle caused emissivities to decrease significantly in Mazzaella splendens but not in three other species. Hydration and layering of Ulva lactuca also had no effect. At 22 °C, measured temperatures were within 1 °C of actual temperatures when thermometer emissivity settings ranged from 0.75 to 1.00. When emissivities were set lower than actual values, measured temperatures were lower than actual temperatures at 15 °C and higher than actual temperatures at 60 °C. When the IR thermometer was used to measure surface temperatures of nine species of intertidal algae immediately before they were inundated by the incoming tide, temperatures were higher in mid intertidal than low intertidal individuals and higher on a sunnier day than an overcast day. Temperatures of U. lactucaincreased with increasing height on the shore, but temperatures of Ulvaria obscura did not. Temperatures were also higher in Fucus distichus blades than receptacles, and lower in U. lactucaand M. splendens occurring in the lower layers of stacks of algae

Covalent targeting of remote cysteine residues to develop CDK12 and CDK13 inhibitors

Cyclin-dependent kinases 12 and 13 (CDK12 and CDK13) play critical roles in the regulation of gene transcription. However, the absence of CDK12 and CDK13 inhibitors has hindered the ability to investigate the consequences of their inhibition in healthy cells and cancer cells. Here we describe the rational design of a first-in-class CDK12 and CDK13 covalent inhibitor, THZ531. Co-crystallization of THZ531 with CDK12–cyclin K indicates that THZ531 irreversibly targets a cysteine located outside the kinase domain. THZ531 causes a loss of gene expression with concurrent loss of elongating and hyperphosphorylated RNA polymerase II. In particular, THZ531 substantially decreases the expression of DNA damage response genes and key super-enhancer-associated transcription factor genes. Coincident with transcriptional perturbation, THZ531 dramatically induced apoptotic cell death. Small molecules capable of specifically targeting CDK12 and CDK13 may thus help identify cancer subtypes that are particularly dependent on their kinase activities.United States. National Institutes of Health (HG002668)United States. National Institutes of Health (CA109901

Covalent targeting of remote cysteine residues to develop CDK12 and CDK13 inhibitors

Cyclin-dependent kinases 12 and 13 (CDK12 and CDK13) play critical roles in the regulation of gene transcription. However, the absence of CDK12 and CDK13 inhibitors has hindered the ability to investigate the consequences of their inhibition in healthy cells and cancer cells. Here we describe the rational design of a first-in-class CDK12 and CDK13 covalent inhibitor, THZ531. Co-crystallization of THZ531 with CDK12–cyclin K indicates that THZ531 irreversibly targets a cysteine located outside the kinase domain. THZ531 causes a loss of gene expression with concurrent loss of elongating and hyperphosphorylated RNA polymerase II. In particular, THZ531 substantially decreases the expression of DNA damage response genes and key super-enhancer-associated transcription factor genes. Coincident with transcriptional perturbation, THZ531 dramatically induced apoptotic cell death. Small molecules capable of specifically targeting CDK12 and CDK13 may thus help identify cancer subtypes that are particularly dependent on their kinase activities.United States. National Institutes of Health (HG002668)United States. National Institutes of Health (CA109901

Optimizing huddle engagement through leadership and problem-solving within primary care: A study protocol for a cluster randomized trial

Abstract Background Team-based care has been identified as a key component in transforming primary care. An important factor in implementing team-based care is the requirement for teams to have daily huddles. During huddles, the care team, comprising physicians, nurses, and administrative staff, come together to discuss their daily schedules, track problems, and develop countermeasures to fix these problems. However, the impact of these huddles on staff burnout over time and patient outcomes are not clear. Further, there are challenges to implementing huddles in fast-paced primary care clinics. We will test whether the impact of a behavioral intervention of leadership training and problem-solving during the daily huddling process will result in higher consistent huddling in the intervention arm and result in higher team morale, reduced burnout, and improved patient outcomes. Methods/design We will conduct a care-team-level cluster randomized trial within primary care practices in two Midwestern states. The intervention will comprise a 1-day training retreat for leaders of primary care teams, biweekly sessions between huddle optimization coaches and members of the primary care teams, as well as coaching site visits at 30 and 100 days post intervention. This behavioral intervention will be compared to standard care, in which care teams have huddles without any support or training. Surveys of primary care team members will be administered at baseline (prior to training), 100 days (for the intervention arm only), and 180 days to assess team dynamics. The primary outcome of this trial will be team morale. Secondary outcomes will assess the impact of this intervention on clinician burnout, patient satisfaction, and quality of care. Discussion This trial will provide evidence on the impact of a behavioral intervention to implement huddles as a key component of team-based care models. Knowledge gained from this trial will be critical to broader deployment and successful implementation of team-based care models. Trial registration Clinicaltrials.gov , NCT03062670 . Registered on 23 February 2017

High Levels of DEK Autoantibodies in Sera of Patients With Polyarticular Juvenile Idiopathic Arthritis and With Early Disease Flares Following Cessation of Antiâ Tumor Necrosis Factor Therapy

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142962/1/art40404_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142962/2/art40404-sup-0001-Supinfo.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142962/3/art40404.pd

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Distinguishing Binders from False Positives by Free Energy Calculations: Fragment Screening Against the Flap Site of HIV Protease

Molecular docking is a powerful tool used in drug discovery and structural biology for predicting the structures of ligand–receptor complexes. However, the accuracy of docking calculations can be limited by factors such as the neglect of protein reorganization in the scoring function; as a result, ligand screening can produce a high rate of false positive hits. Although absolute binding free energy methods still have difficulty in accurately rank-ordering binders, we believe that they can be fruitfully employed to distinguish binders from nonbinders and reduce the false positive rate. Here we study a set of ligands that dock favorably to a newly discovered, potentially allosteric site on the flap of HIV-1 protease. Fragment binding to this site stabilizes a closed form of protease, which could be exploited for the design of allosteric inhibitors. Twenty-three top-ranked protein–ligand complexes from AutoDock were subject to the free energy screening using two methods, the recently developed binding energy analysis method (BEDAM) and the standard double decoupling method (DDM). Free energy calculations correctly identified most of the false positives (≥83%) and recovered all the confirmed binders. The results show a gap averaging ≥3.7 kcal/mol, separating the binders and the false positives. We present a formula that decomposes the binding free energy into contributions from the receptor conformational macrostates, which provides insights into the roles of different binding modes. Our binding free energy component analysis further suggests that improving the treatment for the desolvation penalty associated with the unfulfilled polar groups could reduce the rate of false positive hits in docking. The current study demonstrates that the combination of docking with free energy methods can be very useful for more accurate ligand screening against valuable drug targets