Objective To understand the latest research developments of the formation mechanism of psammoma body in human tumors and related issues. Methods Related domestic and foreign literatures were widely referred, analyzed, and reviewed. Results Psammoma body is unique pathological calcification in some tumors, which is arranged in concentric, laminar circles microscopically. Psammoma body is commonly seen in thyroid papillary carcinoma, meningiomas, ovarian serous papillary carcinoma, and so on. Conclusions Although arranged in concentric, laminar circles microscopically in tumor, the formation process of psammoma body is not entirely the same in different tumors. A comprehensive and objective understanding of psammoma body would be useful in cancer diagnosis and treatment.
The causes of mental disorders are complex, and early recognition and early intervention are recognized as effective way to avoid irreversible brain damage over time. The existing computer-aided recognition methods mostly focus on multimodal data fusion, ignoring the asynchronous acquisition problem of multimodal data. For this reason, this paper proposes a framework of mental disorder recognition based on visibility graph (VG) to solve the problem of asynchronous data acquisition. First, time series electroencephalograms (EEG) data are mapped to spatial visibility graph. Then, an improved auto regressive model is used to accurately calculate the temporal EEG data features, and reasonably select the spatial metric features by analyzing the spatiotemporal mapping relationship. Finally, on the basis of spatiotemporal information complementarity, different contribution coefficients are assigned to each spatiotemporal feature and to explore the maximum potential of feature so as to make decisions. The results of controlled experiments show that the method in this paper can effectively improve the recognition accuracy of mental disorders. Taking Alzheimer's disease and depression as examples, the highest recognition rates are 93.73% and 90.35%, respectively. In summary, the results of this paper provide an effective computer-aided tool for rapid clinical diagnosis of mental disorders.
Stroke is a common and frequently-occurring disease, which seriously endangers human health. Rehabilitation treatment can effectively reduce the disability rate of stroke and improve the quality of life. The tertiary rehabilitation treatment system for stroke can effectively improve the motor function of stroke patients and improve the quality of life. This paper focuses on the choices and methods of physical therapy and occupational therapy at all levels of the hospitals and in different periods of the disease. It also aims to summarize the tertiary rehabilitation strategy for motor dysfunction in stroke patients, to provide references for all levels of hospitals and communities, achieve standardization and unification of rehabilitation treatment, as well as the rehabilitation efficacy of homogeneity.
The incidence of tinnitus is very high, which can affect the patient’s attention, emotion and sleep, and even cause serious psychological distress and suicidal tendency. Currently, there is no uniform and objective method for tinnitus detection and therapy, and the mechanism of tinnitus is still unclear. In this study, we first collected the resting state electroencephalogram (EEG) data of tinnitus patients and healthy subjects. Then the power spectrum topology diagrams were compared of in the band of δ (0.5–3 Hz), θ (4–7 Hz), α (8–13 Hz), β (14–30 Hz) and γ (31–50 Hz) to explore the central mechanism of tinnitus. A total of 16 tinnitus patients and 16 healthy subjects were recruited to participate in the experiment. The results of resting state EEG experiments found that the spectrum power value of tinnitus patients was higher than that of healthy subjects in all concerned frequency bands. The t-test results showed that the significant difference areas were mainly concentrated in the right temporal lobe of the θ and α band, and the temporal lobe, parietal lobe and forehead area of the β and γ band. In addition, we designed an attention-related task experiment to further study the relationship between tinnitus and attention. The results showed that the classification accuracy of tinnitus patients was significantly lower than that of healthy subjects, and the highest classification accuracies were 80.21% and 88.75%, respectively. The experimental results indicate that tinnitus may cause the decrease of patients’ attention.
Cerebral amyloid angiopathy (CAA) is an age-dependent disease affecting older subjects. CAA is characterized by lobar intracerebral hemorrhage (ICH), lobar cerebral microbleeds (CMBs), nontraumatic subarachnoid hemorrhage, and cortical superficial siderosis (cSS), which is the main causes of spontaneous intracranial hemorrhage in the elderly. If a patient had experienced dementia, psychiatric symptoms, recurrent or multiple lobar hemorrhage, the possibility of CAA should be considered. Epilepsy can be associated with CAA. Literature studies had found that CAA-related inflammation are predisposing factors for the development of epilepsy. It is a unique subtype of CAA, which is a form of inflammation and a rare clinical manifestation of sporadic CAA. CAA-ri is a special type of central nervous system vasculitis. Once CAA patients had exhibited atypical clinical manifestations, such as headache, epilepsy, behavioral changes, focal neurological signs, consciousness impairment combined with asymmetric T2 weighted magnetic resonance imaging high signal lesions, clinicians had to consider it maybe CAA-ri. Although CAA- ri is rare, timely diagnosis is important because once seizure had occured, which may indicated the inflammation in CAA patients may had reached a very serious level. Therefore, timely identification and treatment are particularly important. Literature shows that most patients responded well to immunosuppressants. Because of its uncommon, researches on epilepsy in CAA mainly focused on case reports currently, and there were many controversies about its pathological mechanism, treatment and prognosis. This article mainly reviews the incidence rate , pathological mechanism, treatment and prognosis of epilepsy in CAA.
The electroencephalogram (EEG) signal is a general reflection of the neurophysiological activity of the brain, which has the advantages of being safe, efficient, real-time and dynamic. With the development and advancement of machine learning research, automatic diagnosis of Alzheimer’s diseases based on deep learning is becoming a research hotspot. Started from feedforward neural networks, this paper compared and analysed the structural properties of neural network models such as recurrent neural networks, convolutional neural networks and deep belief networks and their performance in the diagnosis of Alzheimer’s disease. It also discussed the possible challenges and research trends of this research in the future, expecting to provide a valuable reference for the clinical application of neural networks in the EEG diagnosis of Alzheimer’s disease.
目的:观察脑出血急性期血凝动态变化规律,为治疗提供理论依据。方法:检测36例脑出血患者病后第1天、第3天、第5天、第10天、凝固启动时间(CST)、凝固达峰值时间(MCT)、最大凝固程度(MCE)、凝血酶原(FⅡ)、纤维蛋白原(Fg)和44例健康体检者的相同指标。结果:与对照组比较,脑出血组病后第1天、第3天、第5天,第10天的MCE、Fg、FⅡ增高(Plt;0.05)。结论:脑出血病后10天血凝显著增高,提示脑出血患者急性期应慎用止血剂和清除脑血肿。