An Empirical Study on Personal Health Records System based on Individual and Environmental Features

To promote the adoption of PHR system, understanding the factors that affect patients’ adoption of PHR system is of necessity. Based on previous research, this paper tries to develop a model to explore those elements that influence the behavior intentions of patients from the perspective of consumers. It is assumed that individual features and environmental features affect individuals’ attitudes to PHR. Data from 265 participants’ response to questionnaire was collected. The SPSS and partial least squares (PLS) technique was adopted to examine the casual relationships this paper hypothesized. The results show that affordability and coercive pressure have the significant effect on individuals’ attitude towards PHR. Therefore, suggestion regarding what developers, institutions and government should do to improve the adoption rate of PHR was raised

Evaluating Summary Statistics with Mutual Information for Cosmological Inference

The ability to compress observational data and accurately estimate physical parameters relies heavily on informative summary statistics. In this paper, we introduce the use of mutual information (MI) as a means of evaluating the quality of summary statistics in inference tasks. MI can assess the sufficiency of summaries, and provide a quantitative basis for comparison. We propose to estimate MI using the Barber-Agakov lower bound and normalizing flow based variational distributions. To demonstrate the effectiveness of our method, we compare three different summary statistics (namely the power spectrum, bispectrum, and scattering transform) in the context of inferring reionization parameters from mock images of 21~cm observations with Square Kilometre Array. We find that this approach is able to correctly assess the informativeness of different summary statistics and allows us to select the optimal set of statistics for inference tasks.Comment: Accepted at the ICML 2023 Workshop on Machine Learning for Astrophysics, comments welcom

{μ-6,6′-Dimeth­oxy-2,2′-[ethane-1,2-diylbis(nitrilo­methyl­idyne)]diphenolato}-μ-nitrato-dinitratoterbium(III)zinc(II)

In the title heteronuclear ZnII—TbIII complex (systematic name: {6,6′-dimeth­oxy-2,2′-[ethane-1,2-diylbis(nitrilo­methyl­id­yne)]diphenolato-1κ4 O 6,O 1,O 1′,O 6′}:2κ4 O 1,N,N′,O 1′-μ-nitrato-1:2κ2 O:O′-dinitrato-1κ4 O,O′-terbium(III)zinc(II)), [TbZn(C18H18N2O4)(NO3)3], with the hexa­dentate Schiff base compartmental ligand N,N′-bis­(3-methoxy­salicyl­idene)ethyl­enediamine (H2 L), the Tb and Zn atoms are triply bridged by two phenolate O atoms of the Schiff base ligand and one nitrate ion. The five-coordinate Zn atom is in a square-pyramidal geometry with the donor centers of two imine N atoms, two phenolate O atoms and one of the bridging nitrate O atoms. The TbIII center has a ninefold coordination environment of O atoms, involving the phenolate O atoms, two meth­oxy O atoms, two O atoms from two nitrate ions and one from the bridging nitrate ion. Weak inter­molecular C—H⋯O inter­actions generate a two-dimensional layer structure

Identifying functional network changing patterns in individuals at clinical high-risk for psychosis and patients with early illness schizophrenia: A group ICA study.

Although individuals at clinical high risk (CHR) for psychosis exhibit a psychosis-risk syndrome involving attenuated forms of the positive symptoms typical of schizophrenia (SZ), it remains unclear whether their resting-state brain intrinsic functional networks (INs) show attenuated or qualitatively distinct patterns of functional dysconnectivity relative to SZ patients. Based on resting-state functional magnetic imaging data from 70 healthy controls (HCs), 53 CHR individuals (among which 41 subjects were antipsychotic medication-naive), and 58 early illness SZ (ESZ) patients (among which 53 patients took antipsychotic medication) within five years of illness onset, we estimated subject-specific INs using a novel group information guided independent component analysis (GIG-ICA) and investigated group differences in INs. We found that when compared to HCs, both CHR and ESZ groups showed significant differences, primarily in default mode, salience, auditory-related, visuospatial, sensory-motor, and parietal INs. Our findings suggest that widespread INs were diversely impacted. More than 25% of voxels in the identified significant discriminative regions (obtained using all 19 possible changing patterns excepting the no-difference pattern) from six of the 15 interrogated INs exhibited monotonically decreasing Z-scores (in INs) from the HC to CHR to ESZ, and the related regions included the left lingual gyrus of two vision-related networks, the right postcentral cortex of the visuospatial network, the left thalamus region of the salience network, the left calcarine region of the fronto-occipital network and fronto-parieto-occipital network. Compared to HCs and CHR individuals, ESZ patients showed both increasing and decreasing connectivity, mainly hypo-connectivity involving 15% of the altered voxels from four INs. The left supplementary motor area from the sensory-motor network and the right inferior occipital gyrus in the vision-related network showed a common abnormality in CHR and ESZ groups. Some brain regions also showed a CHR-unique alteration (primarily the CHR-increasing connectivity). In summary, CHR individuals generally showed intermediate connectivity between HCs and ESZ patients across multiple INs, suggesting that some dysconnectivity patterns evident in ESZ predate psychosis in attenuated form during the psychosis risk stage. Hence, these connectivity measures may serve as possible biomarkers to predict schizophrenia progression

Interaction of autophagy with microRNAs and their potential therapeutic implications in human cancers

AbstractAutophagy is a tightly regulated intracellular self-digestive process involving the lysosomal degradation of cytoplasmic organelles and proteins. A number of studies have shown that autophagy is dysregulated in cancer initiation and progression, or cancer cells under various stress conditions. As a catabolic pathway conserved among eukaryotes, autophagy is regulated by the autophagy related genes and pathways. MicroRNAs (miRNAs) are small, non-coding endogenous RNAs that may regulate almost every cellular process including autophagy. And autophagy is also involved in the regulation of miRNAs expression and homeostasis. Here we reviewed some literatures on the interaction of miRNAs with autophagy and the application of miRNAs-mediated autophagic networks as a promising target in pre-clinical cancer models. Furthermore, strategies of miRNAs delivery for miRNAs-based anti-cancer therapy will also be summarized and discussed