ObjectiveTo explore the effect of chronic unpredictable mild stress (CUMS) on the reproductive function of mice and provide a suitable animal model for reproduction and stress. MethodsA total of 240 female Kunming mice were feed for 5 days, and then divided randomly into the control group (n=90) and experimental group (n=150). The mice in the experimental group were stressed by 9 chronic mild unpredictable stress factors for 4 weeks and validated by open field test and sucrose consumption test. We administrated pregnant mare serum gonadotropin (PMSG)/human chorionic gonadotropin (HCG) for induction of superovulation and observed the ovarian response and embryo development potential. ResultsAfter 4-week CUMS stimulation, the weight gain, 2% sugar consumption test and open field test were significantly different between the mice in two groups (P>0.05). After PMSG/HCG was administrated, the antra follicles and preovulatory follicles significantly reduced significantly in the experiment group than that in the control group (P<0.05); the number of oocytes, fertilization rate, 2-cell embryos, D4 embryos, blastocysts, high quality embryo rate and D5 bed points were all significantly decreased in the experiment group than those in the control group (P<0.05). ConclusionThe CUMS female Kunming mice model is a kind of emotional stress animal model with low reproductive function, which is effective, operable and repeatable; it could be used for further study on the mechanism of reproductive medicine.
With the wide application of deep learning technology in disease diagnosis, especially the outstanding performance of convolutional neural network (CNN) in computer vision and image processing, more and more studies have proposed to use this algorithm to achieve the classification of Alzheimer’s disease (AD), mild cognitive impairment (MCI) and normal cognition (CN). This article systematically reviews the application progress of several classic convolutional neural network models in brain image analysis and diagnosis at different stages of Alzheimer’s disease, and discusses the existing problems and gives the possible development directions in order to provide some references.
Objective To understand the new characteristics of clinical symptoms of patients with mild COVID-19 during the prevalence of SARS-CoV-2 Omicron, and provide basis for better prevention and treatment of COVID-19.Methods A cross-sectional retrospective study was conducted with WeChat questionnaire among medical staff with COVID-19 recently, who come from the Third Affiliated Hospital of Chongqing Medical University and The Second Affiliated Hospital of Army Medical University.Results A total of 630 valid questionnaires was received. 99.2% of infected people had been vaccinated against COVID-19. 2.4% of infected persons developed pneumonia and 2.1% were hospitalized. The most common symptoms after infection were coughing (89.7%), fever (83.0%), fatigue (84.1%), headache and dizziness (75.7%), muscle soreness (72.7%), sore throat (62.1%), nasal congestion and runny nose (60.6%), expectoration (71.6%), anorexia (58.0%) and taste loss (40.2%). The incidence of gastrointestinal symptoms and cardiovascular symptoms was relatively low (17.8% and 31.0% respectively). The severity of self-reported symptoms of most infected persons was moderate or severe. The proportion of serious symptoms reported was coughing (23.8%), sore throat (27.0%), headache and dizziness (17.9%). The severity of symptoms reported by young group (<35 years old) was significantly higher than that of older group (>35 years old). Fever was the highest at 38 to 39 ℃ (52.4%). 77.0% of fever sustained for 1 to 3 days. At the time of investigation, the viral detection turned negative in 60.6% of infected people, and the time of turning negative was mostly 7 to 10 days. More than half of the infected persons still had different symptoms, among which cough (43.7%) and fatigue (23.8%) were the most common.Conclusions Most subjects with mild COVID-19 infection have obvious upper respiratory tract and systemic symptoms, the most prominent is the high incidence of cough, which has become a new feature of omicron infection. And most of the infected people have moderate to severe symptoms, and the younger ones have more severer symptoms.
Normal brain aging and a serious of neurodegenerative diseases may lead to decline in memory, attention and executive ability and poorer quality of life. The mechanism of the decline is not clear now and is still a hot issue in the fields of neuroscience and medicine. A large number of researches showed that resting state functional brain networks based functional magnetic resonance imaging (fMRI) are sensitive and susceptive to the change of cognitive function. In this paper, the researches of brain functional connectivity based on resting fMRI in recent years were compared, and the results of subjects with different levels of cognitive decline including normal brain aging, mild cognitive impairment (MCI) and Alzheimer’s disease (AD) were reviewed. And the changes of brain functional networks under three different levels of cognitive decline are introduced in this paper, which will provide the basis for the detection of normal brain aging and clinical diseases.
Objective To investigate the effect of mild hypothermia on neurological function in rats with spinal cord injury (SCI) based on the adenosine monophosphate activated protein kinase (AMPK)/Nod-like receptor protein 3 (NLRP3) pathway. MethodsFifty 7-8 weeks old SPF male Sprague Dawley rats were used to establish rat model of SCI by Allen’s method. Among them, 48 successfully modeled rats were randomly divided into SCI group, mild hypothermia group (SCI+mild hypothermia treatment), and Compound C group (SCI+mild hypothermia+intraperitoneal injection of 20 mg/kg AMPK/NLRP3 pathway inhibitor Compound C), with 16 rats in each group. Another 16 normal rats with laminectomy were selected as sham-operation group. Basso-Beattie-Bresnahan (BBB) score was used to evaluate the motor ability of rats at 1, 3, 7, 14 days after treatment. After 14 days, the rats were sacrificed, and the spinal cord histopathological morphology was observed by HE staining, the neuronal apoptosis in spinal cord tissue was detected by TUNEL assay, and the serum levels of interleukin 2 (IL-2), IL-6, transforming growth factor β1 (TGF-β1), malondialdehyde (MDA), and superoxide dismutase (SOD) were detected by ELISA. The expressions of AMPK/NLRP3 pathway proteins in spinal cord tissue, including B-cell lymphoma 2 (Bcl-2), Bcl-2-associated X protein (Bax), and cleaved-Caspase-9 were detected by Western blot. Results At 1 day after treatment, the rats in SCI group, mild hypothermia group, and Compound C group did not recover their motor ability. With the prolongation of time, the motor function of rats in each group gradually recovered. Among them, the BBB score of SCI group was significantly lower than that of sham-operation group and mild hypothermia group (P<0.05), and the BBB score of Compound C group was significantly lower than that of mild hypothermia group (P<0.05). Compared with the sham-operation group, the SCI group displayed obvious pathological changes in the spinal cord tissue, with disordered tissue architecture, inflammatory infiltration, and blurred interstitial boundaries. The neuronal apoptosis rate, Bax/Bcl-2 ratio, cleaved Caspase-9 expression, NLRP3 protein expression, serum IL-2, IL-6, and MDA levels were elevated, whereas serum TGF-β1, SOD levels, and spinal cord phosphorylation AMPK/AMPK protein expression significantly decreased (P<0.05). Compared with the SCI group, the above phenomena significantly improved in the mild hypothermia group (P<0.05), while the Compound C group showed the opposite trend of change compared to the mild hypothermia group (P<0.05). Conclusion Mild hypothermia can attenuate neurological dysfunction after SCI in rats, potentially by activating the AMPK/NLRP3 pathway.
Alzheimer's disease (AD) is a typical neurodegenerative disease, which is clinically manifested as amnesia, loss of language ability and self-care ability, and so on. So far, the cause of the disease has still been unclear and the course of the disease is irreversible, and there has been no cure for the disease yet. Hence, early prognosis of AD is important for the development of new drugs and measures to slow the progression of the disease. Mild cognitive impairment (MCI) is a state between AD and healthy controls (HC). Studies have shown that patients with MCI are more likely to develop AD than those without MCI. Therefore, accurate screening of MCI patients has become one of the research hotspots of early prognosis of AD. With the rapid development of neuroimaging techniques and deep learning, more and more researchers employ deep learning methods to analyze brain neuroimaging images, such as magnetic resonance imaging (MRI), for early prognosis of AD. Hence, in this paper, a three-dimensional multi-slice classifiers ensemble based on convolutional neural network (CNN) and ensemble learning for early prognosis of AD has been proposed. Compared with the CNN classification model based on a single slice, the proposed classifiers ensemble based on multiple two-dimensional slices from three dimensions could use more effective information contained in MRI to improve classification accuracy and stability in a parallel computing mode.
Objective To explore the therapeutic effect of mild hypothermia on the inflammatory response, organ function and outcome in perioperative patients with acute Stanford type A aortic dissection (AAAD). Methods From February 2017 to February 2018, 56 patients with AAAD admitted in our department were enrolled and randomly allocated into two groups including a control group and an experimental group. After deep hypothermia circulatory arrest during operation, in the control group (n=28), the patients were rewarmed to normal body temperatures (36 to 37 centigrade degree), and which would be maintained for 24 hours after operation. While in the experimental group (n=28), the patients were rewarmed to mild hypothermia (34 to 35 centigrade degree), and the rest steps were the same to the control group. The thoracic drainage volume and the incidence of shivering at the first 24 hours after operation, inflammatory indicators and organ function during perioperation, and outcomes were compared between the two groups. There were 20 males and 8 females at age of 51.5±8.7 years in the control group, 24 males and 4 females at age of 53.3±11.2 years in the experimental group.Results There was no obvious difference in the basic information and operation information in patients between the two groups. Compared to the control group, at the 24th hour after operation, the level of peripheral blood matrix metalloproteinases (MMPs) was lower than that in the experimental group (P=0.008). In the experimental group, after operation, the awakening time was much shorter (P=0.008), the incidence of bloodstream infection was much lower (P=0.019). While the incidence of delirium, acute kidney injury (AKI), hepatic insufficiency, mechanical ventilation duration, intensive care unit (ICU) stays, or hospital mortality rate showed no statistical difference. And at the first 24 hours after operation, there was no difference in the thoracic drainage volume between the two groups, and no patient suffered from shivering. Conclusion The mild hypothermia therapy is able to shorten the awakening time and reduce the incidence of bloodstream infection after operation in the patients with AAAD, and does not cause the increase of thoracic drainage volume or shivering.
Mild cognitive impairment (MCI) is a clinical transition state between age-related cognitive decline and dementia. Researchers can use neuroimaging and neurophysiological techniques to obtain structural and functional information about the human brain. Using this information researchers can construct the brain network based on complex network theory. The literature on graph theory shows that the large-scale brain network of MCI patient exhibits small-world property, which ranges intermediately between Alzheimer's disease and that in the normal control group. But brain connectivity of MCI patients presents topologically structural disorder. The disorder is significantly correlated to the cognitive functions. This article reviews the recent findings on brain connectivity of MCI patients from the perspective of multimodal data. Specifically, the article focuses on the graph theory evidences of the whole brain structural and functional and the joint covariance network disorders. At last, the article shows the limitations and future research directions in this field.
The cognitive impairment of type 2 diabetes patients caused by long-term metabolic disorders has been the current focus of attention. In order to find the related electroencephalogram (EEG) characteristics to the mild cognitive impairment (MCI) of diabetes patients, this study analyses the EEG synchronization with the method of multi-channel synchronization analysis--S estimator based on phase synchronization. The results showed that the S estimator values in each frequency band of diabetes patients with MCI were almost lower than that of control group. Especially, the S estimator values decreased significantly in the delta and alpha band, which indicated the EEG synchronization decrease. The MoCA scores and S value had a significant positive correlation in alpha band.
We in the present research proposed a classification method that applied infomax independent component analysis (ICA) to respectively extract single modality features of structural magnetic resonance imaging (sMRI) and positron emission tomography (PET). And then we combined these two features by using a method of weight combination. We found that the present method was able to improve the accurate diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI). Compared AD to healthy controls (HC): the study achieved a classification accuracy of 93.75%, with a sensitivity of 100% and a specificity of 87.64%. Compared MCI to HC: classification accuracy was 89.35%, with a sensitivity of 81.85% and a specificity of 99.36%. The experimental results showed that the bi-modality method performed better than the individual modality in comparison to classification accuracy.