Decoding the Popularity of TV Series: A Network Analysis Perspective

In this paper, we analyze the character networks extracted from three popular television series and explore the relationship between a TV show episode's character network metrics and its review from IMDB. Character networks are graphs created from the plot of a TV show that represents the interactions of characters in scenes, indicating the presence of a connection between them. We calculate various network metrics for each episode, such as node degree and graph density, and use these metrics to explore the potential relationship between network metrics and TV series reviews from IMDB. Our results show that certain network metrics of character interactions in episodes have a strong correlation with the review score of TV series. Our research aims to provide more quantitative information that can help TV producers understand how to adjust the character dynamics of future episodes to appeal to their audience. By understanding the impact of character interactions on audience engagement and enjoyment, producers can make informed decisions about the development of their shows

Interactions between the Nociceptin and Toll-like Receptor Systems.

Nociceptin and the nociceptin receptor (NOP) have been described as targets for treatment of pain and inflammation, whereas toll-like receptors (TLRs) play key roles in inflammation and impact opioid receptors and endogenous opioids expression. In this study, interactions between the nociceptin and TLR systems were investigated. Human THP-1 cells were cultured with or without phorbol myristate acetate (PMA 5 ng/mL), agonists specific for TLR2 (lipoteichoic acid, LTA 10 µg/mL), TLR4 (lipopolysaccharide, LPS 100 ng/mL), TLR7 (imiquimod, IMQ 10 µg/mL), TLR9 (oligonucleotide (ODN) 2216 1 µM), PMA+TLR agonists, or nociceptin (0.01-100 nM). Prepronociceptin (ppNOC), NOP, and TLR mRNAs were quantified by RT-qPCR. Proteins were measured using flow cytometry. PMA upregulated ppNOC mRNA, intracellular nociceptin, and cell membrane NOP proteins (all p < 0.05). LTA and LPS prevented PMA's upregulating effects on ppNOC mRNA and nociceptin protein (both p < 0.05). IMQ and ODN 2216 attenuated PMA's effects on ppNOC mRNA. PMA, LPS, IMQ, and ODN 2216 increased NOP protein levels (all p < 0.05). PMA+TLR agonists had no effects on NOP compared to PMA controls. Nociceptin dose-dependently suppressed TLR2, TLR4, TLR7, and TLR9 proteins (all p < 0.01). Antagonistic effects observed between the nociceptin and TLR systems suggest that the nociceptin system plays an anti-inflammatory role in monocytes under inflammatory conditions

Emerging roles of lymphatic endothelium in regulating adaptive immunity

Emerging research on the roles of stromal cells in modulating adaptive immune responses has included a new focus on lymphatic endothelial cells (LECs). LECs are presumably the first cells that come into direct contact with peripheral antigens, cytokines, danger signals, and immune cells travelling from peripheral tissues to lymph nodes. LECs can modulate dendritic cell function, present antigens to T cells on MHC class I and MHC class II molecules, and express immunomodulatory cytokines and receptors, which suggests that their roles in adaptive immunity are far more extensive than previously realized.. This Review summarizes the emergent evidence that LECs are important in maintaining peripheral tolerance, limiting and resolving effector T cell responses, and modulating leukocyte function

Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image Matching

This paper presents a robotic pick-and-place system that is capable of grasping and recognizing both known and novel objects in cluttered environments. The key new feature of the system is that it handles a wide range of object categories without needing any task-specific training data for novel objects. To achieve this, it first uses a category-agnostic affordance prediction algorithm to select and execute among four different grasping primitive behaviors. It then recognizes picked objects with a cross-domain image classification framework that matches observed images to product images. Since product images are readily available for a wide range of objects (e.g., from the web), the system works out-of-the-box for novel objects without requiring any additional training data. Exhaustive experimental results demonstrate that our multi-affordance grasping achieves high success rates for a wide variety of objects in clutter, and our recognition algorithm achieves high accuracy for both known and novel grasped objects. The approach was part of the MIT-Princeton Team system that took 1st place in the stowing task at the 2017 Amazon Robotics Challenge. All code, datasets, and pre-trained models are available online at http://arc.cs.princeton.eduComment: Project webpage: http://arc.cs.princeton.edu Summary video: https://youtu.be/6fG7zwGfIk

Physician Empathy in Public and Private Internal Medicine Residency Training Programs in Pasig City

Research Question: What are the levels of patient-perceived and self-assessed physician empathy among internal medicine (IM) residents in two tertiary hospitals in Pasig City? Is there a significant difference in patient-perceived and self-assessed physician empathy levels between public and private tertiary hospitals? Background: Empathy is important because it has been speculated to have a positive effect on patient outcomes; it is a skill that can be learned and developed. Objectives: This study obtained quantitative measurements of patient-perceived and self-assessed physician empathy. Empathy levels between public and private tertiary hospitals were compared. General Study Design: This study utilized a quantitative cross-sectional design, with surveys as the strategy for data collection. Participants: 162 out-patient department patients aged 19-75, and 69 IM residents were sampled from one private and one public tertiary hospital. Outcome Measures: The Jefferson Scale of Patient Perceptions of Physician Empathy (JSPPPE) and the Jefferson Scale of Physician Empathy (JSE) were used to measure the empathy levels. Analysis: Sample size calculation was done using OpenEpi. An alpha level of .05 was used for computing the independent samples t-test. Results: Internal medicine patients from the private hospital rated the physicians with higher empathy scores (mean=31.23) compared to their public hospital counterparts (mean=29.01), which is significant (p=.0134). Residents from the private hospital also scored a higher self-assessed empathy score (mean=110.46) compared to physicians from the public hospital (mean=102.13), which is significant (p=.0147). Conclusion: This study provided preliminary information on the empathy levels of physicians in the Philippine setting between private and public hospitals, showing that physician empathy levels are consistently higher in the private hospital facility. The results can help hospitals incorporate or improve training in empathy in internal medicine residency programs, as empathy is known to affect patient health outcome

Normalization and Statistical Analysis of Multiplexed Bead-Based Immunoassay Data Using Mixed-Effects Modeling

Multiplexed bead-based flow cytometric immunoassays are a powerful experimental tool for investigating cellular communication networks, yet their widespread adoption is limited in part by challenges in robust quantitative analysis of the measurements. Here we report our application of mixed-effects modeling for the normalization and statistical analysis of bead-based immunoassay data. Our data set consisted of bead-based immunoassay measurements of 16 phospho-proteins in lysates of HepG2 cells treated with ligands that regulate acute-phase protein secretion. Mixed-effects modeling provided estimates for the effects of both the technical and biological sources of variance, and normalization was achieved by subtracting the technical effects from the measured values. This approach allowed us to detect ligand effects on signaling with greater precision and sensitivity and to more accurately characterize the HepG2 cell signaling network using constrained fuzzy logic. Mixed-effects modeling analysis of our data was vital for ascertaining that IL-1α and TGF-α treatment increased the activities of more pathways than IL-6 and TNF-α and that TGF-α and TNF-α increased p38 MAPK and c-Jun N-terminal kinase (JNK) phospho-protein levels in a synergistic manner. Moreover, we used mixed-effects modeling-based technical effect estimates to reveal the substantial variance contributed by batch effects along with the absence of loading order and assay plate position effects. We conclude that mixed-effects modeling enabled additional insights to be gained from our data than would otherwise be possible and we discuss how this methodology can play an important role in enhancing the value of experiments employing multiplexed bead-based immunoassays.United States. Army Research Office (Contract W911NF-09-D-0001)National Institutes of Health (U.S.) (NIH P50-GM68762

A realist synthesis of pharmacist-conducted medication reviews in primary care after leaving hospital: what works for whom and why?

Background: Medication reviews for people transitioning from one healthcare setting to another potentially improve health outcomes, although evidence for outcome benefits varies. It is unclear when and why medication reviews performed by pharmacists in primary care for people who return from hospital to the community lead to beneficial outcomes. Objective: A realist synthesis was undertaken to develop a theory of what works, for whom, why and under which circumstances when pharmacists conduct medication reviews in primary care for people leaving hospital. Methods: The realist synthesis was performed in accordance with Realist And MEta-narrative Evidence Syntheses: Evolving Standards reporting standards. An initial programme theory informed a systematic literature search of databases (PubMed, Embase, Cumulative Index of Nursing and Allied Health Literature, International Pharmaceutical Abstracts, OpenGrey, Trove), augmented by agency and government sources of information. Documents were synthesised by exploring interactions between contexts, intervention, outcomes and causal mechanisms. Results: The synthesis identified 9 contexts in which 10 mechanisms can be activated to influence outcomes of pharmacist medication reviews conducted in primary care postdischarge. For a medication review to take place these include trust patients have in healthcare professionals, their healthcare priorities postdischarge, capacity to participate, perceptions of benefit and effort, and awareness required by all involved. For the medication review process, mechanisms which issue an invitation to collaborate between healthcare professionals, enable pharmacists employing clinical skills and taking responsibility for medication review outcomes were linked to more positive outcomes for patients. Conclusions: Medication reviews after hospital discharge seem to work successfully when conducted according to patient preferences, programmes promote coordination and collaboration between healthcare professionals and establish trust, and pharmacists take responsibility for outcomes. Findings of this realist synthesis can inform postdischarge medication review service models

Molecular Characterization of Branchial aquaporin 1aa and Effects of Seawater Acclimation, Emersion or Ammonia Exposure on Its mRNA Expression in the Gills, Gut, Kidney and Skin of the Freshwater Climbing Perch, Anabas testudineus

10.1371/journal.pone.0061163PLoS ONE84