Prediction and causal inference of cardiovascular and cerebrovascular diseases based on lifestyle questionnaires.

Cardiovascular and cerebrovascular diseases (CCVD) are prominent mortality causes in Japan, necessitating effective preventative measures, early diagnosis, and treatment to mitigate their impact. A diagnostic model was developed to identify patients with ischemic heart disease (IHD), stroke, or both, using specific health examination data. Lifestyle habits affecting CCVD development were analyzed using five causal inference methods. This study included 473,734 patients aged ≥ 40 years who underwent specific health examinations in Kanazawa, Japan between 2009 and 2018 to collect data on basic physical information, lifestyle habits, and laboratory parameters such as diabetes, lipid metabolism, renal function, and liver function. Four machine learning algorithms were used: Random Forest, Logistic regression, Light Gradient Boosting Machine, and eXtreme-Gradient-Boosting (XGBoost). The XGBoost model exhibited superior area under the curve (AUC), with mean values of 0.770 (± 0.003), 0.758 (± 0.003), and 0.845 (± 0.005) for stroke, IHD, and CCVD, respectively. The results of the five causal inference analyses were summarized, and lifestyle behavior changes were observed after the onset of CCVD. A causal relationship from 'reduced mastication' to 'weight gain' was found for all causal species theory methods. This prediction algorithm can screen for asymptomatic myocardial ischemia and stroke. By selecting high-risk patients suspected of having CCVD, resources can be used more efficiently for secondary testing.

Comparing region of interest selection and whole-field analysis for measurement of ciliary beat frequency in high-speed video analysis.

BACKGROUND: Ciliary beat frequency (CBF) is crucial in mucociliary clearance. High-speed video analysis (HSVA) is commonly used to measure CBF but lacks standardization. We compared visual observation and computer-assisted calculation using fast Fourier transformation (FFT) in freshly collected bronchial ciliary epithelial cells and cultured cells. METHODS: Bronchial epithelial cells were obtained from 12 patients who required bronchoscopic examination. Eighty-five videos of ciliary movement of freshly collected and cultured cells were recorded and used to calculate CBF using manual observation, region of interest (ROI) selection, and whole-field analysis. RESULTS: CBF measured by the ROI selection method strongly correlated with that measured using manual observation, especially in freshly collected cells. However, 27.8% of the manual observation method values were doubled in the ROI selection method, probably because a round trip of cilia was calculated as two cycles and needed to be corrected to 1/2 value. Upon increasing the number of ROIs, the results of the ROI selection method came closer to that of WFA. CONCLUSIONS: Computer-assisted calculation using FFT can aid in measuring CBF; however, current methods require visual confirmation. Further automated evaluation techniques are needed to establish more standardized and generalized CBF measurement methods using HSVA.

Quantitative analysis of the roles of IRM cell adhesion molecules in column formation in the fly brain.

The Drosophila visual center shows columnar structures, basic structural and functional units of the brain, that are shared with the mammalian cerebral cortex. Visual information received in the ommatidia in the compound eye is transmitted to the columns in the brain. However, the developmental mechanisms of column formation are largely unknown. The Irre Cell Recognition Module (IRM) proteins are a family of immunoglobulin cell adhesion molecules. The four Drosophila IRM proteins are localized to the developing columns, the structure of which is affected in IRM mutants, suggesting that IRM proteins are essential for column formation. Since IRM proteins are cell adhesion molecules, they may regulate cell adhesion between columnar neurons. To test this possibility, we specifically knocked down IRM genes in columnar neurons and examined the defects in column formation. We developed a system that automatically extracts the individual column images and quantifies the column shape. Using this system, we demonstrated that IRM genes play critical roles in regulating column shape in a core columnar neuron, Mi1. We also show that their expression in the other columnar neurons, Mi4 and T4/5, is essential, suggesting that the interactions between IRM proteins and multiple neurons shape the columns in the fly brain.

DWnt4 and DWnt10 Regulate Morphogenesis and Arrangement of Columnar Units via Fz2/PCP Signaling in the Drosophila Brain.

Columns are structural and functional units of the brain. However, the mechanism of column formation remains unclear. The medulla of the fly visual center shares features with the mammalian cerebral cortex, such as columnar and layered structures, and provides a good opportunity to study the mechanisms of column formation. Column formation is initiated by three core neurons in the medulla, namely, Mi1, R8, and R7. The proper orientation of neurons is required for the orientation and arrangement of multiple columns. Their orientations may be under the control of planar cell polarity (PCP) signaling, because it is known to regulate the orientation of cells in two-dimensional tissue structures. In this study, we demonstrate that the ligands DWnt4 and DWnt10 expressed specifically in the ventral medulla and dorsal medulla, respectively, globally regulate the columnar arrangement and orientation of Mi1 and R8 terminals through Fz2/PCP signaling in a three-dimensional space.