Machine Learning Algorithms for the Prediction of Locomotor Activity by an Infrared Motion Detector on the Sleep-wake States in Mice

Objective@#Even though studies using machine learning on sleep-wake states have been performed, studies in various conditions are still necessary. This study aimed to examine the performance of the prediction model of locomotor activities on sleep-wake states using machine learning algorithms. @*Methods@#The processed data using moving average of locomotor activities were used as predicting features. The sleep-wake states were used as true labels. The prediction models were established by machine learning classifiers such as support vector machine with radial basis function (SVM-RBF), linear discriminant analysis (LDA), naïve Bayes, and random forest (RF). The prediction model was evaluated by a six-fold cross validation. @*Results@#The SVM-RBF and RF showed acceptable performance within a window of moving average from 480 to 1,200 seconds. The highest accuracy (0.869) was shown by the RF at the interval of 480 seconds. Meanwhile, the highest area under the curve (0.939) was shown by LDA at the interval of 870 seconds. @*Conclusion@#This study suggested that the prediction model on sleep-wake state using machine learning could show an improvement of the model performance when using moving average with raw data. The prediction model using locomotor activity can be useful in research on sleep-wake state.

Cluster Analysis on the Mental Health States in a Community Sample of Young Women During Pre-Pregnancy, Pregnancy, or the Postpartum Period

Objective@#It is necessary to identify the mental health types of young women considering the importance of the mental health during the peripartum period. This study aimed to classify the mental health types in a community sample of young women with pre-pregnancy, pregnancy, or the postpartum period. @*Methods@#A total of 293 young women during pre-pregnancy, pregnancy, or the postpartum period were included in this study. The clinical characteristics of depression, anxiety, perceived stress, and quality of life were assessed. The clinical characteristics of the subject were classified by cluster analysis and compared by analysis of variance. @*Results@#From the cluster analysis, the subjects were classified into three groups. Cluster 1 showed significantly lower depression and anxiety and higher quality of life than those of cluster 2 and 3. Cluster 2 demonstrated significantly higher depression and anxiety and lower quality of life than those of cluster 3 and 1. Cluster 3 represented the intermediate levels between cluster 2 and 1. @*Conclusion@#This study suggested that young women during pre-pregnancy, pregnancy, or the postpartum period might be in a good mental health group, a high-risk group requiring active monitoring, or a group in need of treatment. By monitoring mental health, the groups with high risk or requiring treatment could be discovered and proper management for prevention or improvement of mental health and quality of life can be provided.

A Validation Study of Mental Health Monitoring Through a Mobile Application

Objective@#Face-to-face evaluation is the most important in psychiatric evaluation, but smart healthcare, including non-face-to-face evaluation, can be beneficial considering the situation in which face-to-face evaluation is limited or the preventive aspect of mental illness. In this paper, we aimed to check whether mental health screening tests have the same significance as paper-based tests even when collected through mobile applications. @*Methods@#A smart mental healthcare screening test was conducted on the 1,327 community subjects. We measured two indicators of depression (Patient Health Questionnaire 9-item scale, PHQ-9) and anxiety (Generalized Anxiety Disorder 7-item scale, GAD-7) to check mental health conditions. @*Results@#The average Cronbach’s alpha value of the PHQ-9 questionnaire was good at 0.870. As a result of PHQ-9’s principal component analysis, one component with an eigenvalue of 1 or more was identified, which is suitable to be described as a single factor. The average Cronbach’s alpha value of the GAD-7 was 0.919. The structural validity of the GAD-7 was confirmed through principal component analysis. @*Conclusion@#Our results show that PHQ-9 and GAD-7 scales performed through mobile applications can have the same meaning as paper-based tests. Surveys using a tablet PC, or smartphone application can monitor residents’ mental health and accumulate data. Based on these data, smart mental health management can check the mental health of residents and treat mental illness in connection with medical services.

Influences of Dopamine D2, D3 Agonist Quinpirole Dosage on Locomotor Activity Measured by Open-FieldTest / 우울ㆍ조울병

Background@#Dopamine D2 and D3 receptor agonist quinpirole have been tried as one of drug-induced bipolar animal models. An open-field test is used to assess locomotor activity related to anxiety. Not many studies have analyzed the effects of quinpirole dosages on locomotor activity. The purpose of this study was to look at the locomotor activity of quinpirole-injected mice in an open-field test. @*Methods@#The open-field test was used to observe the locomotor activities of 28 mice. Quinpirole was administrated at 0.05-5 mg/kg and normal saline were used as a control. The Mann-Whitney U-test was employed to compare the locomotor activities in the quinpirole and control groups. @*Results@#Quinpirole-induced locomotor activities reduced as time elapsed during the first 30 minutes following the injection in most mice, then increased or fluctuated in the later 30 minutes. As the dosage was increased, there was a stronger initial inhibition, followed by a rapid and further increase in the last 30 minutes. @*Conclusion@#This study showed the differential effects of quinpirole-induced locomotor activities depending on dosage, and initial suppression of locomotor activities by quinpirole was observed. Additionally, longitudinal observation of more than 1 hour would be required to look into the biphasic pattern of quinpirole in an animal model.

Analysis of ultradian rest-activity rhythms using locomotor activity in mice / 고신대학교의과대학학술지

Background@#Locomotor activity in mice may have an ultradian rest-activity rhythm. However, to date, no study has shown how locomotor activity can be explained statistically using fitted cosine curves. Therefore, this study explored whether the ultradian rhythm of locomotor activity in mice could be analyzed using cosine fitting analysis. @*Methods@#The locomotor activity of 20 male mice under a 12/12-hour dark/light cycle for 2 days was fitted to a cosine function to obtain the best fit. The mean absolute error (MAE) values were used to determine the explanatory power of the calculated cosine model for locomotor activity. The cosine fitting analysis was performed using R statistical software (version 4.1.1). @*Results@#The mean MAE was 0.2944, whereas the mean MAE for integrating the individual analyses in the two experimental groups was 0.3284. The periods of the estimated ultradian rest-activity rhythm ranged from 1.602 to 4.168 hours. @*Conclusions@#These results suggest that locomotor activity data reflect an ultradian rhythm better than a circadian rhythm. Locomotor activity can be statistically fitted to a cosine curve under well-controlled conditions. In the future, it will be necessary to explore whether this cosine-fitting analysis can be used to analyze ultradian rhythms under different experimental conditions.

Optimization of Analysis of Circadian Rest-Activity Rhythm Using Cosinor Analysis in Mice

Objective@#Data processing in analysis of circadian rhythm was performed in various ways. However, there was a lack of evidence for the optimal analysis of circadian rest-activity rhythm. Therefore, we aimed to perform mathematical simulations of data processing to investigate proper evidence for the optimal analysis of circadian rest-activity rhythm. @*Methods@#Locomotor activities of 20 ICR male mice were measured by infrared motion detectors. The data of locomotor activities was processed using data summation, data average, and data moving average methods for cosinor analysis. Circadian indices were estimated according to time block, respectively. Also, statistical F and p-values were calculated by zero-amplitude test. @*Results@#The data moving average result showed well-fitted cosine curves independent of data processing time. Meanwhile, the amplitude, MESOR, and acrophase were properly estimated within 800 seconds in data summation and data average methods. @*Conclusion@#These findings suggest that data moving average would be an optimal method for data processing in a cosinor analysis and data average within 800-second data processing time might be adaptable. The results of this study can be helpful to analyze circadian restactivity rhythms and integrate the results of the studies using different data processing methods.

Prediction of Locomotor Activity by Infrared Motion Detector on Sleep-wake State in Mice

Objective@#Behavioral assessments that effectively predict sleep-wake states were tried in animal research. This study aimed to examine the prediction power of an infrared locomotion detector on the sleep-wake states in ICR (Institute Cancer Research) mice. We also explored the influence of the durations and ways of data processing on the prediction power. @*Methods@#The locomotor activities of seven male mice in home cages were recorded by infrared detectors. Their sleep-wake states were assessed by video analysis. Using the receiver operating characteristic curve analysis, the cut-off score was determined, then the area under the curve (AUC) values of the infrared motion detector that predicted sleep-wake states were calculated. In order to improve the prediction power, the four ways of data processing on the prediction power were performed by Matlab 2013b. @*Results@#In the initial analysis of raw data, the AUC value was 0.785, but it gradually reached to 0.942 after data summation. The simple data averaging and summation among four different methods showed the maximal AUC value. The 10-minute data summation improved sensitivity (0.889) and specificity (0.901) significantly from the baseline value (sensitivity 0.615; specificity 0.936) (p ＜ 0.001). @*Conclusion@#This study suggests that the locomotor activity measured by an infrared motion detector might be useful to predict the sleep-wake states in ICR mice. It also revealed that only simple data summation may improve the predictive power. Using daily locomotor activities measured by an infrared motion detector is expected to facilitate animal research related to sleep-wake states.

Prediction of Locomotor Activity by Infrared Motion Detector on Sleep-wake State in Mice

Objective@#Behavioral assessments that effectively predict sleep-wake states were tried in animal research. This study aimed to examine the prediction power of an infrared locomotion detector on the sleep-wake states in ICR (Institute Cancer Research) mice. We also explored the influence of the durations and ways of data processing on the prediction power. @*Methods@#The locomotor activities of seven male mice in home cages were recorded by infrared detectors. Their sleep-wake states were assessed by video analysis. Using the receiver operating characteristic curve analysis, the cut-off score was determined, then the area under the curve (AUC) values of the infrared motion detector that predicted sleep-wake states were calculated. In order to improve the prediction power, the four ways of data processing on the prediction power were performed by Matlab 2013b. @*Results@#In the initial analysis of raw data, the AUC value was 0.785, but it gradually reached to 0.942 after data summation. The simple data averaging and summation among four different methods showed the maximal AUC value. The 10-minute data summation improved sensitivity (0.889) and specificity (0.901) significantly from the baseline value (sensitivity 0.615; specificity 0.936) (p ＜ 0.001). @*Conclusion@#This study suggests that the locomotor activity measured by an infrared motion detector might be useful to predict the sleep-wake states in ICR mice. It also revealed that only simple data summation may improve the predictive power. Using daily locomotor activities measured by an infrared motion detector is expected to facilitate animal research related to sleep-wake states.

Can Residual Symptoms During Inter-Episode Period after Partial Remission in Bipolar I Disorder Have Cyclic Patterns with Specific Frequencies?

This case report aimed to describe cyclic patterns of residual mood symptoms in partially remitted bipolar I patient. In a 24-year-old woman with bipolar I disorder, residual mood symptoms measured by self-rated daily mood chart for 18 months were analyzed using wavelet analysis. A 146-day periodicity was prominent for the first 100 days after discharge. Between 100–200 days, 146-day periodicity was progressively diminished and 21- and 8-day periodicity was prominent. Between 200–516 days, 21-day periodicity was diminished and 85-day periodicity became prominent. This case suggest that bipolar patients might have cyclic residual symptoms with specific frequencies.

Protein Kinase C Activity and Delayed Recovery of Sleep-Wake Cycle in Mouse Model of Bipolar Disorder

OBJECTIVE: Previous studies reported the delayed recovery group after circadian rhythm disruption in mice showed higher quinpiroleinduced locomotor activity. This study aimed to compare not only Protein Kinase C (PKC) activities in frontal, striatal, hippocampus and cerebellum, but also relative PKC activity ratios among brain regions according to recovery of circadian rhythm. METHODS: The circadian rhythm disruption protocol was applied to eight-week-old twenty male Institute Cancer Research mice. The circadian rhythm recovery patterns were collected through motor activities measured by Mlog system. Depressive and manic proneness were examined by forced swim test and quinpirole-induced open field test respectively. Enzyme-linked immunosorbent assay was employed to measure PKC activities. RESULTS: The delayed recovery group presented greater locomotor activities than the early recovery group (p=0.033). The delayed recovery group had significantly lower frontal PKC activity than the other (p=0.041). The former showed lower frontal/cerebellar PKC activity ratio (p=0.047) but higher striatal/frontal (p=0.038) and hippocampal/frontal (p=0.007) PKC activities ratios than the latter. CONCLUSION: These findings support potential mechanism of delayed recovery after circadian disruption in bipolar animal model could be an alteration of relative PKC activities among mood regulation related brain regions. It is required to investigate the PKC downstream signaling related to the delayed recovery pattern.

Post-Prandial Lipid Levels for Assessing Target Goal Achievement in Type 2 Diabetic Patients Taking Statin

It is inconvenient to perform serum lipid analysis in fasting state in diabetic patients with drug treatment. In patients with statin treatment and Asian diet, it has not been clearly known whether non-fasting values could be used for the clinical decision making in diabetic patients. In this study, fasting and post-prandial plasma lipid profiles of hospitalized type 2 diabetic patients taking statin, were measured in whom standard diabetic breakfast in traditional Korean style were provided. In repeated-measures ANOVA, there were no significant differences among fasting, post-prandial 2 and 4 hr low-density lipoprotein (LDL) and high density lipoprotein (HDL) cholesterol values. When compared to fasting levels, both post-prandial 2 hr and 4 hr LDL cholesterol levels were misclassified as not achieved target goal only in 4% of patients. Post-prandial HDL cholesterol matched with fasting values in women, without exception. In conclusion, the fasting and post-prandial LDL and HDL cholesterol levels are not significantly different each other and can be used in the assessment of achieving target goal in type 2 diabetes taking statin after Korean diet.

Study on the Differences between Anatomical Terminology and Terminology of High School Biology Textbook / 대한해부학회지

College students, who major in health science, feel troubles in learning anatomy due to the differences between anatomical terminology and biology terms used in high school course. Moreover, there can be errors in communication between patients and medical personnel. So we investigated and analyzed the terminologies used in 7 high school biology textbooks, and compared them with Korean anatomical terminology and official biological terminology. The concordance rate of high school biology terms with anatomical terminology was just 50.3 +/-2.7%, while that with official biological terminology was significantly higher (89.8+/-1.6%). Most notable differences between high school biology terms and anatomical terminology were found in descriptions of the reproductive system. In addition, several eponyms and unofficial word spacing were noted in high school biology textbooks. These results can be served as valuable basic resources for revision and standardization of terminologies used in biomedical fields. Collaboration among anatomists, biologists and high school teachers is thought be prerequisite.

Study on the Differences between High School Biology Textbook Terminologies and Official Terminologies of Histology or Embryology / 대한해부학회지

College students, who major in health science, feel troubles in learning histology or embryology due to the differences between medical terminology and biological terminologies used in high school course. Moreover, the differences can cause errors in communication between patients and medical personnel. So we investigated and analyzed the terminologies used in 7 high school biology textbooks, and compared them with official histological or embryological terminologies and official biological terminologies (Korean association of biological science). The concordance rates of high school biology terms with histological or embryological terminologies were just 42.3+/-4.0% or 55.8+/-18.1%, while those with official biological terminology were significantly higher (74.0+/-3.8% or 89.5+/- 8.0%). Most notable differences between high school biology textbook terminologies and histological terminologies were found in the chapter of the urinary system. In addition, several eponyms and unofficial word spacing were noted in high school textbooks. These results can be served as valuable basic resources for revision and standardization of terminologies used in the biomedical fields. Collaboration among anatomists, biologists and high school teachers is thought be prerequisite.

In situ hybridization Study on the Age-related Changes of Ghrelin mRNA Expression in Rat Stomach / 대한해부학회지

Ghrelin is a recently identified member of growth hormone secretagogue, which is synthesized as peptide of 28 amino acids in stomach, pituitary and intestines. Ghrelin controls food intake, and induces gastric acid secretion. It has been reported that synthesis and secretion of ghrelin changes according to age of animals. In this study, in situ hybridization technique with digoxigenin-labeled oligonucleotide probe is applied to elucidate the developmental change of ghrelin mRNA expression pattern in rat stomach. Ghrelin mRNA positive cells first appeared in stomach of 9 day rats, mainly in base of gastric glands. It showed the highest density and spread to neck area of the gastric gland in 6 week rats. Number of positive cells decreased significantly in 18 months. Most of ghrelin mRNA positive cells were found as closed-type endocrine cells in fundus area. These results suggest that ghrelin expression may be involved in development and ageing process.