Towards Socially Intelligent Agents with Mental State Transition and Human Utility

Building a socially intelligent agent involves many challenges, one of which is to track the agent's mental state transition and teach the agent to make rational decisions guided by its utility like a human. Towards this end, we propose to incorporate a mental state parser and utility model into dialogue agents. The hybrid mental state parser extracts information from both the dialogue and event observations and maintains a graphical representation of the agent's mind; Meanwhile, the utility model is a ranking model that learns human preferences from a crowd-sourced social commonsense dataset, Social IQA. Empirical results show that the proposed model attains state-of-the-art performance on the dialogue/action/emotion prediction task in the fantasy text-adventure game dataset, LIGHT. We also show example cases to demonstrate: (\textit{i}) how the proposed mental state parser can assist agent's decision by grounding on the context like locations and objects, and (\textit{ii}) how the utility model can help the agent make reasonable decisions in a dilemma. To the best of our knowledge, we are the first work that builds a socially intelligent agent by incorporating a hybrid mental state parser for both discrete events and continuous dialogues parsing and human-like utility modeling

Structured Attention for Unsupervised Dialogue Structure Induction

Inducing a meaningful structural representation from one or a set of dialogues is a crucial but challenging task in computational linguistics. Advancement made in this area is critical for dialogue system design and discourse analysis. It can also be extended to solve grammatical inference. In this work, we propose to incorporate structured attention layers into a Variational Recurrent Neural Network (VRNN) model with discrete latent states to learn dialogue structure in an unsupervised fashion. Compared to a vanilla VRNN, structured attention enables a model to focus on different parts of the source sentence embeddings while enforcing a structural inductive bias. Experiments show that on two-party dialogue datasets, VRNN with structured attention learns semantic structures that are similar to templates used to generate this dialogue corpus. While on multi-party dialogue datasets, our model learns an interactive structure demonstrating its capability of distinguishing speakers or addresses, automatically disentangling dialogues without explicit human annotation.Comment: Long paper accepted by EMNLP 202

Protective effect of paeoniflorin against oxidative stress in human retinal pigment epithelium in vitro

Purpose: This study was conducted to determine whether paeoniflorin (PF) could prevent H(2)O(2)-induced oxidative stress in ARPE-19 cells and to elucidate the molecular pathways involved in this protection. Methods: Cultured ARPE-19 cells were subjected to oxidative stress with H(2)O(2) in the presence and absence of PF. The preventive effective of PF on reactive oxygen species (ROS) production and retinal pigment epithelium (RPE) cell death induced by H(2)O(2) was determined by 2', 7'-dichlorodihydrofluorescein diacetate (H(2)DCFDA) fluorescence and 3-(4, 5dimethylthiazol-2-yl)-2, 5 diphenyl tetrazolium bromide (MTT) assay. The ability of PF to protect RPE cells against ROS-mediated apoptosis was assessed by caspase-3 activity and 4', 6-diamidino-2-phenylindole (DAPI) staining. Furthermore, the protective effect of PF via the mitogen-activated protein kinase (MAPK) pathway was determined by western blot analysis. Results: PF protected ARPE-19 cells from H(2)O(2)-induced cell death with low toxicity. H(2)O(2)-induced oxidative stress increased ROS production and caspase-3 activity, which was significantly inhibited by PF in a dose-dependent manner. Pretreatment with PF attenuated H(2)O(2)-induced p38MAPK and extracellular signal regulated kinase (ERK) phosphorylation in human RPE cells, which contributed to cell viability in ARPE-19 cells. Conclusions: This is the first report to show that PF can protect ARPE-19 cells from the cellular apoptosis induced by oxidative stress. The results of this study open new avenues for the use of PF in treatment of ocular diseases, such as age-related macular degeneration (AMD), where oxidative stress plays a major role in disease pathogenesis.Biochemistry & Molecular BiologyOphthalmologySCI(E)PubMed1ARTICLE373-783512-35221

Performance evaluation of inpatient service in Beijing: a horizontal comparison with risk adjustment based on Diagnosis Related Groups

<p>Abstract</p> <p>Background</p> <p>The medical performance evaluation, which provides a basis for rational decision-making, is an important part of medical service research. Current progress with health services reform in China is far from satisfactory, without sufficient regulation. To achieve better progress, an effective tool for evaluating medical performance needs to be established. In view of this, this study attempted to develop such a tool appropriate for the Chinese context.</p> <p>Methods</p> <p>Data was collected from the front pages of medical records (FPMR) of all large general public hospitals (21 hospitals) in the third and fourth quarter of 2007. Locally developed Diagnosis Related Groups (DRGs) were introduced as a tool for risk adjustment and performance evaluation indicators were established: Charge Efficiency Index (CEI), Time Efficiency Index (TEI) and inpatient mortality of low-risk group cases (IMLRG), to reflect respectively work efficiency and medical service quality. Using these indicators, the inpatient services' performance was horizontally compared among hospitals. Case-mix Index (CMI) was used to adjust efficiency indices and then produce adjusted CEI (aCEI) and adjusted TEI (aTEI). Poisson distribution analysis was used to test the statistical significance of the IMLRG differences between different hospitals.</p> <p>Results</p> <p>Using the aCEI, aTEI and IMLRG scores for the 21 hospitals, Hospital A and C had relatively good overall performance because their medical charges were lower, LOS shorter and IMLRG smaller. The performance of Hospital P and Q was the worst due to their relatively high charge level, long LOS and high IMLRG. Various performance problems also existed in the other hospitals.</p> <p>Conclusion</p> <p>It is possible to develop an accurate and easy to run performance evaluation system using Case-Mix as the tool for risk adjustment, choosing indicators close to consumers and managers, and utilizing routine report forms as the basic information source. To keep such a system running effectively, it is necessary to improve the reliability of clinical information and the risk-adjustment ability of Case-Mix.</p

Exploring the mechanism of agarwood moxa smoke in treating sleep disorders based on GC–MS and network pharmacology

BackgroundAgarwood moxibustion is a folk therapy developed by individuals of the Li nationality in China. There is evidence that agarwood moxa smoke (AMS) generated during agarwood moxibustion therapy can treat sleep disorders via traditional Chinese medicines’ multiple target and pathway characteristics. However, the specific components and mechanisms involved have yet to be explored.ObjectiveGC–MS (Gas Chromatography–Mass Spectrometry) and network pharmacology were used to investigate AMS’s molecular basis and mechanism in treating sleep deprivation.MethodGC–MS was used to determine the chemical composition of AMS; component target information was collected from TCMSP (Traditional Chinese Medicine Systems Pharmacology), PubChem (Public Chemical Database), GeneCards (Human Gene Database), and DisGeNet (Database of Genes and Diseases) were used to identify disease targets, and JVenn (Joint Venn) was used to identify the common targets of AMS and sleep disorders. STRING was used to construct a protein interaction network, Cytoscape 3.9.1 was used to build a multilevel network diagram of the “core components-efficacy targets-action pathways,” the targets were imported into Metascape and DAVID for GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses and Autodock was used for molecular docking. This research used a network pharmacology methodology to investigate the therapeutic potential of Agarwood Moxa Smoke (AMS) in treating sleep problems. Examining the target genes and chemical constituents of AMS offers insights into the molecular processes and targets of the disease.ResultNine active ingredients comprising anti-inflammatory substances and antioxidants, such as caryophyllene and p-cymene, found seven sleep-regulating signaling pathways and eight targets linked to sleep disorders. GC–MS was used to identify the 94 active ingredients in AMS, and the active ingredients had strong binding with the key targets. Key findings included active components with known medicinal properties, such as p-cymene, eucalyptol, and caryophyllene. An investigation of network pharmacology revealed seven signaling pathways for sleep regulation and eight targets linked to sleep disorders, shedding light on AMS’s effectiveness in enhancing sleep quality.ConclusionAMS may alleviate sleep disorders by modulating cellular and synaptic signaling, controlling hormone and neurotransmitter pathways, etc. Understanding AMS’s material basis and mechanism of action provides a foundation for future research on treating sleep disorders with AMS. According to the study, Agarwood Moxa Smoke (AMS) may improve sleep quality by modifying cellular and synaptic signaling pathways for those who suffer from sleep problems. This might lead to the development of innovative therapies with fewer side effects

Somatic SF3B1 hotspot mutation in prolactinomas.

The genetic basis and corresponding clinical relevance of prolactinomas remain poorly understood. Here, we perform whole genome sequencing (WGS) on 21 patients with prolactinomas to detect somatic mutations and then validate the mutations with digital polymerase&nbsp;chain&nbsp;reaction (PCR) analysis of tissue samples from 227 prolactinomas. We identify the same hotspot somatic mutation in splicing factor 3 subunit B1 (SF3B1R625H) in 19.8% of&nbsp;prolactinomas. These patients with mutant prolactinomas display higher prolactin (PRL) levels (p = 0.02) and shorter progression-free survival (PFS) (p = 0.02) compared to patients without the mutation. Moreover, we identify that the SF3B1R625H mutation causes aberrant splicing of estrogen related receptor gamma (ESRRG), which results in stronger binding of pituitary-specific positive transcription factor 1 (Pit-1), leading to excessive PRL secretion. Thus our study validates an important mutation and elucidates a potential mechanism underlying the pathogenesis of prolactinomas that may lead to the development of targeted therapeutics