Abstract: An electronic device and a method for predicting a blockage of a coronary artery are provided. The method includes: obtaining multiple pieces of electrocardiogram (ECG) data respectively corresponding to a coronary artery set; generating multiple first probabilities corresponding to the multiple pieces of electrocardiogram data respectively according to the multiple pieces of electrocardiogram data and a first phase model, generating a first determined result according to the multiple first probabilities, and selecting a first data subset corresponding to a first probability subset from the multiple pieces of electrocardiogram data in response to each one in the first data subset of the multiple first probabilities being greater than a first threshold; generating multiple second probabilities corresponding to the first data subset according to the first data subset and a second phase model, and generating a second determined result according to the multiple second probabilities.

Abstract: An electronic device and a method for selecting a feature of an electrocardiogram (ECG) are provided. The method includes: obtaining the ECG; performing a first pre-processing on the ECG to generate a first ECG; marking multiple extreme points corresponding to at least one type of wave on the first ECG; calculating a first feature value corresponding to a first feature according to the multiple extreme points of the at least one type of wave, generating a first performance index corresponding to a machine learning model according to the first feature value, and determining whether to select the first feature according to the first performance index; and outputting the first feature in response to selecting the first feature.

Abstract: A method for establishing a disease prediction model is provided. The method includes the steps of extracting feature values for multiple microbiota features from microbiota data of each of a plurality of samples, selecting a portion of the extracted microbiota features as selected features, and training a disease prediction model. Each piece of training data used in training the disease prediction model includes (i) disease data for each of the samples and (ii) the feature values of the selected features for the sample. The microbiota features include species-level features, microbiota interaction features, and community-level features.

Abstract: An electronic device and a method for diagnosing heart state based on electrocardiogram (ECG) are provided. An ECG file is obtained, and the ECG file is in a first file format and includes a plurality of potential traces of a plurality of leads. The ECG file is converted to a second file format to obtain electrocardiogram data corresponding to multiple leads. Each potential trace relative to time in the ECG file is converted to the ECG data of each lead. Integrated ECG data associated with the leads is generated based on the ECG data of the plurality of leads through the zero-padding operation and the stacking operation. A diagnostic result of heart status is generated based on the integrated ECG data and a deep learning model.

Abstract: Isoindoline compounds and their pharmaceutical compositions. Also provided are methods of treating a Cisd2-insufficiency associated disorder and protecting against doxorubicin-induced cardiotoxicity.

Abstract: Provided is a method for preventing or treating a metabolic disorder, including administering to a subject a therapeutically effective amount of TRABID protein or a functionally related variant thereof, or a nucleic acid encoding TRABID protein or a functionally related variant thereof. Also provided is a method for reducing fat accumulation through TRABID-induced deubiquitination to promote autophagy activity and lipid metabolism.

Abstract: A feature selection method is provided, including: inputting a plurality of pieces of training data into a plurality of training models to perform selection in a plurality of features through each training model for obtaining multiple feature pools; sorting the features based on the number of times each feature is selected by the feature pools to obtain a feature ranking; and extracting a plurality of designated features from the features based on the feature ranking.

Abstract: A method of treating a Cisd2 insufficiency-associated disorder. The method includes administering to a subject in need a compound of formula (I). Also disclosed is a method of increasing Cisd2 gene expression.

Abstract: Isoindoline compounds and their pharmaceutical compositions. Also provided are methods of treating a Cisd2-insufficiency associated disorder and protecting against doxorubicin-induced cardiotoxicity.

Abstract: A method and an electronic device for selecting influence indicators by using an automatic mechanism are provided. The method includes following steps. Raw data is obtained, where the raw data includes a body-related variable and a plurality of to-be-measured indicators corresponding to the body-related variable. The body-related variable is set as a target parameter. The body-related variable and the to-be-measured indicators are input into a plurality of validation models, and the to-be-measured indicators are sorted according an output result of the validation models to obtain ranking data. Importance of the to-be-measured indicators is calculated by using a screening condition according to the ranking data, so as to select a candidate indicator from the to-be-measured indicators. An influence indicator is determined by calculating a correlation between the candidate indicator and the body-related variable.

Abstract: An electronic device and a method for screening features for predicting a physiological state are provided. The method includes: obtaining multiple physiological data corresponding to multiple features; generating multiple first subsets of the multiple features according to the multiple physiological data based on a first model, wherein the multiple first subsets respectively correspond to the multiple physiological data; selecting a first feature from the multiple features according to the multiple first subsets, calculating a first relation index of the first feature and a second feature corresponding to the multiple features, and selecting the second feature as an accompanied feature of the first feature according to the first relation index; and outputting the first feature and the accompanied feature.

Abstract: An electronic device and a method for predicting a blockage of a coronary artery are provided. The method includes: obtaining multiple pieces of electrocardiogram (ECG) data respectively corresponding to a coronary artery set; generating multiple first probabilities corresponding to the multiple pieces of electrocardiogram data respectively according to the multiple pieces of electrocardiogram data and a first phase model, generating a first determined result according to the multiple first probabilities, and selecting a first data subset corresponding to a first probability subset from the multiple pieces of electrocardiogram data in response to each one in the first data subset of the multiple first probabilities being greater than a first threshold; generating multiple second probabilities corresponding to the first data subset according to the first data subset and a second phase model, and generating a second determined result according to the multiple second probabilities.

Abstract: An electronic device and a method for selecting a feature of an electrocardiogram (ECG) are provided. The method includes: obtaining the ECG; performing a first pre-processing on the ECG to generate a first ECG; marking multiple extreme points corresponding to at least one type of wave on the first ECG; calculating a first feature value corresponding to a first feature according to the multiple extreme points of the at least one type of wave, generating a first performance index corresponding to a machine learning model according to the first feature value, and determining whether to select the first feature according to the first performance index; and outputting the first feature in response to selecting the first feature.

Abstract: Provided is a method for preventing or treating a metabolic disorder, including administering to a subject a therapeutically effective amount of TRABID protein or a functionally related variant thereof, or a nucleic acid encoding TRABID protein or a functionally related variant thereof. Also provided is a method for reducing fat accumulation through TRABID-induced deubiquitination to promote autophagy activity and lipid metabolism.

Abstract: A method and an electronic device for selecting influence indicators by using an automatic mechanism are provided. The method includes following steps. Raw data is obtained, where the raw data includes a body-related variable and a plurality of to-be-measured indicators corresponding to the body-related variable. The body-related variable is set as a target parameter. The body-related variable and the to-be-measured indicators are input into a plurality of validation models, and the to-be-measured indicators are sorted according an output result of the validation models to obtain ranking data. Importance of the to-be-measured indicators is calculated by using a screening condition according to the ranking data, so as to select a candidate indicator from the to-be-measured indicators. An influence indicator is determined by calculating a correlation between the candidate indicator and the body-related variable.

Abstract: The present invention is related to a Cisd2 knockout mouse with phenotype comprising mitochondrial breakdown and dysfunction, wherein Cisd2 is defined as SEQ ID NO. 1. The present invention is also related to a mouse model of Wolfram Syndrome 2 (WFS2) disease consisting of a Cisd2 knockout mouse. The present invention is further related to a method for screening a candidate agent for preventing or treating WFS2 disease.

Abstract: The present invention is related to a Cisd2 knockout mouse with phenotype comprising mitochondrial breakdown and dysfunction, wherein Cisd2 is defined as SEQ ID NO. 1. The present invention is also related to a mouse model of Wolfram Syndrome 2 (WFS2) disease consisting of a Cisd2 knockout mouse. The present invention is further related to a method for screening a candidate agent for preventing or treating WFS2 disease.

Abstract: An aging animal model and a method for screening an agent for treating or preventing aging associated phenotypes or delaying onset of aging.

Abstract: A method of identifying a genotype of a transgenic mouse and reducing the variability of a transagene expression in the transgenic mouse comprises the step of introducing into a mouse (a) a transgene expression cassette, (b) a coat color expression cassette and (c) an insulator positioned at 5? or 3? end of the transgene expression cassette.

Abstract: A method of identifying a genotype of a transgenic mouse and reducing the variability of a transagene expression in the transgenic mouse comprises the step of introducing into a mouse (a) a transgene expression cassette, (b) a coat color expression cassette and (c) an insulator positioned at 5′ or 3′ end of the transgene expression cassette.