1.Quality of life and related factors among family members of tuberculosis patients.
Wei FENG ; Furong LIU ; Chuanrui MA ; Shengjie JU ; Liang SUN ; Lizhang CHEN
Journal of Central South University(Medical Sciences) 2013;38(10):1075-1079
OBJECTIVE:
To understand the quality of life and related factors among family members of tuberculosis patients and provide a reference for the improvement of their quality of life.
METHODS:
A total of 222 family members of tuberculosis patients at 4 tuberculosis hospitals in Changsha and 327 healthy controls were surveyed with structured questionnaire, the short version of the WHO quality of life scale (WHOQOL-BREF).
RESULTS:
The mean score of the family members of tuberculosis patients in the psychological domain, physical domain and environmental domains was lower than that of the control group (P<0.01). Multiple linear regression showed that gender, age, monthly income, educational level, patient condition and knowledge of tuberculosis prevention and treatment were the factors affecting their quality of life.
CONCLUSION
The quality of life of the family members of tuberculosis patients is lower than that of the control group.
Family Health
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Humans
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Quality of Life
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Surveys and Questionnaires
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Tuberculosis
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psychology
2.MouseVenue3D: A Markerless Three-Dimension Behavioral Tracking System for Matching Two-Photon Brain Imaging in Free-Moving Mice.
Yaning HAN ; Kang HUANG ; Ke CHEN ; Hongli PAN ; Furong JU ; Yueyue LONG ; Gao GAO ; Runlong WU ; Aimin WANG ; Liping WANG ; Pengfei WEI
Neuroscience Bulletin 2022;38(3):303-317
Understanding the connection between brain and behavior in animals requires precise monitoring of their behaviors in three-dimensional (3-D) space. However, there is no available three-dimensional behavior capture system that focuses on rodents. Here, we present MouseVenue3D, an automated and low-cost system for the efficient capture of 3-D skeleton trajectories in markerless rodents. We improved the most time-consuming step in 3-D behavior capturing by developing an automatic calibration module. Then, we validated this process in behavior recognition tasks, and showed that 3-D behavioral data achieved higher accuracy than 2-D data. Subsequently, MouseVenue3D was combined with fast high-resolution miniature two-photon microscopy for synchronous neural recording and behavioral tracking in the freely-moving mouse. Finally, we successfully decoded spontaneous neuronal activity from the 3-D behavior of mice. Our findings reveal that subtle, spontaneous behavior modules are strongly correlated with spontaneous neuronal activity patterns.
Animals
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Behavior, Animal
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Brain/diagnostic imaging*
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Imaging, Three-Dimensional/methods*
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Mice
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Neuroimaging
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Rodentia