Assessable and interpretable sensitivity analysis in the pattern graph framework for nonignorable missingness mechanisms.

The pattern graph framework solves a wide range of missing data problems with nonignorable mechanisms. However, it faces two challenges of assessability and interpretability, particularly important in safety-critical problems such as clinical diagnosis: (i) How can one assess the validity of the framework's a priori assumption and make necessary adjustments to accommodate known information about the problem? (ii) How can one interpret the process of exponential tilting used for sensitivity analysis in the pattern graph framework and choose the tilt perturbations based on meaningful real-world quantities? In this paper, we introduce Informed Sensitivity Analysis, an extension of the pattern graph framework that enables us to incorporate substantive knowledge about the missingness mechanism into the pattern graph framework. Our extension allows us to examine the validity of assumptions underlying pattern graphs and interpret sensitivity analysis results in terms of realistic problem characteristics. We apply our method to a prevalent nonignorable missing data scenario in clinical research. We validate and compare our method's results of our method with a number of widely-used missing data methods, including Unweighted CCA, KNN Imputer, MICE, and MissForest. The validation is done using both boot-strapped simulated experiments as well as real-world clinical observations in the MIMIC-III public dataset.

Analysis of Missingness Scenarios for Observational Health Data.

Despite the extensive literature on missing data theory and cautionary articles emphasizing the importance of realistic analysis for healthcare data, a critical gap persists in incorporating domain knowledge into the missing data methods. In this paper, we argue that the remedy is to identify the key scenarios that lead to data missingness and investigate their theoretical implications. Based on this proposal, we first introduce an analysis framework where we investigate how different observation agents, such as physicians, influence the data availability and then scrutinize each scenario with respect to the steps in the missing data analysis. We apply this framework to the case study of observational data in healthcare facilities. We identify ten fundamental missingness scenarios and show how they influence the identification step for missing data graphical models, inverse probability weighting estimation, and exponential tilting sensitivity analysis. To emphasize how domain-informed analysis can improve method reliability, we conduct simulation studies under the influence of various missingness scenarios. We compare the results of three common methods in medical data analysis: complete-case analysis, Missforest imputation, and inverse probability weighting estimation. The experiments are conducted for two objectives: variable mean estimation and classification accuracy. We advocate for our analysis approach as a reference for the observational health data analysis. Beyond that, we also posit that the proposed analysis framework is applicable to other medical domains.

Post-training intrahippocampal infusion of nicotine-bucladesine combination causes a synergistic enhancement effect on spatial memory retention in rats.

We previously had shown that bilateral intrahippocampal infusion of 1 microg nicotine (but not 0.5 microg dose) led to an improvement in spatial memory retention in the Morris water maze task in male rats. We also reported that a similar type of bilateral infusion of H89, a protein kinase AII (PKA II) inhibitor, caused a deficit in spatial memory retention. In the present study, we wished to test the hypothesis that intrahippocampal infusion of dibutyryl cyclic AMP (DB-cAMP also called bucladesine), a membrane permeable selective activator of PKA, into the CA1 region can cause an improvement in spatial memory in this maze task. Indeed, bilateral infusion of 10 and 100 microM bucladesine (but not 1 and 5 microM doses) led to a significant reduction in escape latency and travel distance (showing an improvement in spatial memory) compared to the control. Also, bilateral infusion of 0.5 microg nicotine or 1 microM bucladesine alone did not lead to an improvement in spatial memory. However, such bilateral infusion of bucladesine at 1 and 5 microM concentrations infused within minutes after 0.5 microg nicotine infusion improved spatial memory retention. Taken together, our data suggest that intrahippocampal bucladesine infusions improve spatial memory retention in male rats and that bucladesine can interact synergistically with nicotine to improve spatial memory.

Intra-hippocampal inhibition of protein kinase AII attenuates morphine-induced conditioned place preference.

Morphine and other drugs of abuse modulate protein kinase A (PKA) signaling within the mesolimbic reward pathway. Using a balanced conditioned place preference (CPP) paradigm, we studied the possible involvement of protein kinase AII (PKA II) on the acquisition, expression and consolidation of morphine place conditioning in male Wistar rats. Subcutaneous administration of various doses of morphine sulfate (1-9 mg/kg) induced CPP in a dose-dependent manner. H-89, a selective PKA II inhibitor, was administered into CA1 region of the hippocampus at 1, 2.5 and 5 microM/rat. Using a 3-day schedule of conditioning, it was found that the H-89 did not produce a significant place preference or place aversion. H-89 (1, 2.5 and 5 microM/rat) significantly reduced the time spent by rats in the morphine compartment when given immediately after each conditioning session (consolidation), whereas it had no effect when administered before morphine during the conditioning phase (acquisition) or before testing for place preference in the absence of morphine (expression). It is concluded that the PKA II may play an active role in the consolidation of reward-related memory of morphine in CA1 region of the hippocampus.

The Effect of Exposure to High Noise Levels on the Performance and Rate of Error in Manual Activities.

INTRODUCTION: Sound is among the significant environmental factors for people's health, and it has an important role in both physical and psychological injuries, and it also affects individuals' performance and productivity. The aim of this study was to determine the effect of exposure to high noise levels on the performance and rate of error in manual activities. METHODS: This was an interventional study conducted on 50 students at Shiraz University of Medical Sciences (25 males and 25 females) in which each person was considered as its own control to assess the effect of noise on her or his performance at the sound levels of 70, 90, and 110 dB by using two factors of physical features and the creation of different conditions of sound source as well as applying the Two-Arm coordination Test. The data were analyzed using SPSS version 16. Repeated measurements were used to compare the length of performance as well as the errors measured in the test. RESULTS: Based on the results, we found a direct and significant association between the levels of sound and the length of performance. Moreover, the participant's performance was significantly different for different sound levels (at 110 dB as opposed to 70 and 90 dB, p < 0.05 and p < 0.001, respectively). CONCLUSION: This study found that a sound level of 110 dB had an important effect on the individuals' performances, i.e., the performances were decreased.