ABSTRACT
Objective:To evaluate EEG biofeedback therapy on clinical efficacy of children with different subtypes of attention deficit hyperactivity disorder (ADHD) using the integrated visual and auditory integration continuous performance test (IVA-CPT).Methods:Children with ADHD who completed more than 60 times of EEG biofeedback training in Hangzhou Seventh People's Hospital from July 2018 to September 2020 were selected as the research subjects. According to the results of IAV-CPT before treatment, all the children were divided into three subtypes: attention deficit type ( n=21), impulse hyperactivity type ( n=11), and mixed type ( n=30). The differences of symptom improvement between the three subtypes before and after training were compared by SPSS 23.0 software. Results:(1) In terms of response control (a total of 9 items), there was no statistical significance in the attention deficit group before and after treatment (all P>0.05). In the hyperactivity group, the scores of visual and auditory response control, full scale response control, auditory prudence and auditory consistency, visual focus quotient and visual consistency before treatment were significantly lower than those after treatment(all P<0.05). In the mixed group, the scores of visual and auditory response control, full scale response control, auditory prudence, visual consistency, and visual prudence before treatment were significantly lower than those after treatment(all P<0.05). In terms of attention (a total of 9 items), the scores of auditory vigilance, auditory attention, visual attention, full scale attention, visual vigilance and visual speed in the attention deficit group before treatment were significantly lower than those after treatment(all P<0.05). The scores of visual attention, full scale attention, visual focus quotient (all P<0.01), auditory attention and visual speed (all P<0.05) in hyperactivity group before treatment were significantly lower than those after treatment. In the mixed group, the scores of the other 8 items before treatment were significantly lower than those after treatment (all P<0.01, auditory focus quotient were P<0.05), except that the auditory speed had no statistical significance before and after treatment.(2)After EEG biofeedback training, the changes of IVA-CPT scores of the three groups before and after treatment(visual response control (-2.76±24.39), (19.55±19.94), (12.93±25.30), F=3.932, P=0.025), (full scale response control (2.38±20.77), (21.27±15.86), (15.43±25.69), F=3.158, P=0.050), (full scale attention (18.43±27.44), (11.36±11.40), (26.23±18.41), F=4.692, P=0.016), (auditory vigilance (20.23±42.65), (6.55±10.20), (33.63±36.30), F=7.160, P=0.002), (visual vigilance (19.48±28.55), (5.27±10.62), (33.27±28.26), F=10.876, P<0.001), (visual focus quotient (-2.24±23.67), (14.45±13.79), (12.83±21.91), F=3.669, P=0.031) were statistically significant. After LSD comparison, the changes of visual control and total control scores in the attention deficit group before and after treatment were significantly lower than those in the impulse hyperactivity group (all P<0.05) and the mixed group (all P<0.05). In the three items of total attention score, auditory vigilance and visual vigilance, the changes of impulsivity hyperactivity group before and after treatment were significantly lower than those of mixed group ( P=0.050, P<0.05, P<0.01, respectively). The changes of visual attention quotient in the attention deficit group before and after treatment were significantly lower than those in the impulse hyperactivity group and the mixed group (all P<0.05). Conclusion:EEG biofeedback has clinical efficacy in the three groups of subtypes of ADHD, but the efficacy is different, and individualized EEG training programs should be developed for different subtypes of children on the basis of standard TBR therapy protocol.
ABSTRACT
Clostridium acetobutylicum is an important strain for bio-butanol formation. In recent years, gene-editing technology is widely used for developing the hyper-butanol-production strains. In this study, three genes (cac1251, cac2118 and cac2125) encoding cell division proteins (RodA, DivIVA and DivIB) in C. acetobutylicum were knocked out. The cac2118-knockout strain had changed its cell morphology to spherical-shape during the solventogenesis, and obtained a higher butanol yield of 0.19 g/g, increasing by 5.5%, compared with the wild type strain. The glucose utilization and butanol production of cac1251-knockout strain decreased by 33.9% and 56.3%, compared the with wild type strain, reaching to 47.3 g/L and 5.6 g/L. The cac1251-knockout strain and cac2125-knockout strain exhibited poor cell growth with cell optical density decreased by 40.4% and 38.3%, respectively, compared with that of the wild type strain. The results indicate that cell division protein DivIVA made the differences in the regulation of cell morphology and size. Cell division proteins RodA and DivIB played significant roles in the regulation of cell division, and affected cell growth, as well as solventogenesis metabolism.
Subject(s)
Butanols , Cell Division/genetics , Clostridium acetobutylicum/genetics , Fermentation , Gene Knockout Techniques , SolventsABSTRACT
The quantity of biomass, glucose concentration and ethanol concentration are important parameters in ethanol fermentation. Traditional methods are usually based on samples for off-line measurement, which not only requires multiple instruments for test and analysis but also consumes notable time and effort, and therefore is inconvenient for real-time process control and optimization. In this study, an in-situ detection method based on the near-infrared (NIR) spectroscopy is proposed for measuring the above process parameters in real time. The in-situ measurement is carried out by using an immersion type NIR spectroscopy. A multi-output prediction model for simultaneously estimating the quantity of glucose, biomass and ethanol is established based on a multi-output least-squares support vector regression algorithm. The experimental results show that the proposed method can precisely measure the quantity of glucose, biomass and ethanol during the ethanol fermentation process. Compared to the existing partial-least-squares method for modeling and prediction of individual components, the proposed method could evidently improve the measurement accuracy and reliability.
Subject(s)
Ethanol , Fermentation , Least-Squares Analysis , Reproducibility of Results , Spectroscopy, Near-InfraredABSTRACT
Objective To verify the applicability of mental health dual-factor theory in normal population and understand the mental health of them.Methods According to Keyes' theory of mental health,the questionnaire was used to investigate the negative and positive psychological health of 1900 normal population.Then,confirmatory factor analysis was carried out.Result The fitting index of the dual-Factor model in Zhejiang group was more ideal by comparing the different models(x2/df=3.63,RMR=0.04,RMSEA =0.095).In the people of Zhejiang province,69.8％ were completely mentally healthy,9.4％ were troubled,7.3％ were vulnerable,13.5％ were symptomatic but content.The distribution results were consistent with those of foreign researches.The results between the six-point method and Keyes' method were significantly different(x2=187.5,P＜0.01).In this study,a combination of PHQ-9,GAD-7 and GHQ-12 was used in the study,and 22.9％ of the population were screened for mental illness.Conclusion The dual-Factor model of mental health is suitable for normal population.Mental health can be assessed by warwick-edinburgh mental well-being scale(WEMWBS),PHQ-9,GAD-7 and GHQ-12.
ABSTRACT
Ethanol tolerance of self-flocculating yeast SPSC01 was studied in a 3-L bioreactor under fed-batch culture. Yeast floc populations with the average sizes around 100, 200, 300, and 400 microm were obtained by adjusting the mechanical stirring rates of the fermentation system. When subjected to 20% (V/V) ethanol shock for 6 h at 30 degrees C, the remained cell viability was 3.5%, 26.7%, 48.8% and 37.6% for the aforementioned four floc populations, respectively. The highest ethanol yield 85.5% was achieved for the 300 microm flocs, 7.2% higher than that of the 100 microm flocs. The amounts of trehalose and ergosterol (including free ergosterol and total ergosterol) were positively correlated with the average size distributions from 100 to 300 microm. However, in the 400 microm flocs, the content of trehalose and ergosterol decreased, which coincided with its reduced ethanol tolerance compared to that of the 300 microm flocs. Furthermore, when subjected to 15% (V/V) ethanol shock at 30 degrees C, the equilibrium nucleotide concentration and plasma membrane permeability coefficient(P') of the 300 microm flocs accounted for only 43% and 52% respectively of those of the 100 microm and 200 microm populations. The effect of floc size distribution on the ethanol tolerance of the self-flocculating yeast strain SPSC01 was closely related to plasma membrane permeability. An optimal floc size distribution with the highest ethanol tolerance and ethanol production level could be obtained by controlling mechanical stirring speed of the bioreactor, which provides basis for the process optimization of fuel ethanol production using this self-flocculating strain.