ObjectiveTo determine the feasibility as well as the attitudes among caregivers of children and adolescents with epilepsy and adult patients with epilepsy in China towards the use of smart phone applications (apps) for the management of seizures. MethodsThe caregivers of children and adolescents with epilepsy, ages ranging from 0 to 17 years old and adult patients who were more than 18 years old, were enrolled in the study from the Epilepsy Prevention and Cure Center of West China Hospital within the time period from June to December 2015. A questionnaire gauging the attitudes towards using apps for seizure management was administered to the 502 epilepsy patients and 390 caregivers of children and adolescents with epilepsy. ResultsAmong adult patients, they were more likely to use an app in those who were young, lived in cities, had higher education, had a stable employment and had frequent seizures (P=0.002, P<0.001, P=0.001, P<0.001, P=0.01). Among caregivers of children and adolescents with epilepsy, participants were more likely to use an app in those who were male (P=0.03), had a higher education level, a higher annual household income as well as stable job (P<0.001, P<0.001, P=0.02). ConclusionThe results of this study imply a favorable attitude towards the use of apps for seizure management among adult patients and caregivers of children and adolescents with epilepsy. The use of such apps in China represents a promising strategy among caregivers for seizure management.
Objective To compare the in vitro release and transdermal capability between Erhuang gel paste and its ointment. Methods Strat-M membrane and advanced Franz diffusion cell were used to conduct the in vitro release and transdermal experiment. The content of osthole, the effective component of the key herb radix angelicae tuhuo in the preparations was quantitatively determined by high performance liquid chromatography (HPLC) method to determine the in vitro release rate, transdermal quantity and transdermal rate. Results The transdermal penetration formula of Erhuang gel paste was Ln=0.443 6t+1.350 9, r=0.964 4. The cumulative in vitro release rate, transdermal quantity and transdermal rate were respectively 62.90%, 0.067 2 mg/g and 20.82%. The transdermal penetration formula of Erhuang ointment was Ln=0.205 1t-0.244 7, r=0.995 6. The cumulative in vitro release rate, transdermal quantity and transdermal rate were respectively 77.64%, 0.013 1mg/g and 9.36%. Conclusion The transdermal capability of Erhuang gel paste is obviously better than its ointment, and the gel paste is more convenient to use and is unlikely to cause allergic reactions.
Objective To explore the correlation and diagnostic value of neutrophil-to-lymphocyte ratio (NLR) and red blood cell distribution width (RDW) in peripheral blood of patients with exacerbation of chronic obstructive pulmonary disease (COPD). Methods One hundred patients with acute exacerbation of COPD who were hospitalized in the hospital between January 2019 and October 2020 were selected as exacerbation group, and another 100 patients with stable COPD who received treatment during the same time period were enrolled as stable group. The general data of patients were collected, and blood samples were collected to detect hemoglobin (Hb), platelet count (PLT), white blood cell count (WBC), neutrophil count, lymphocyte count and RDW, and the NLR was calculated. The correlation between the detection indicators was analyzed and receiver operating characteristic (ROC) curve was drawn to analyze the detection significance of related indicators. Results There were no statistical differences in the levels of Hb and PLT between the exacerbation group and the stable group (P>0.05). The levels of WBC, NLR, RDW and high-sensitivity C-reactive protein (hs-CRP) in the exacerbation group were significantly higher than those in the stable group (all P<0.05). NLR in the patients with acute exacerbation of COPD was positively correlated with serological indicators of WBC and hs-CRP (all P<0.05). ROC curve showed that the sensitivity and specificity of NLR in the diagnosis of acute exacerbation of COPD were 92.0% and 68.0% respectively, those of RDW were 91.0% and 58.0% respectively, those of hs-CRP were 77.0% and 71.0% respectively, and those of NLR+RDW were 90.0% and 73.0% respectively. NLR had the highest diagnostic specificity, RDW had the highest diagnostic sensitivity, and NLR+RDW had the best diagnostic efficiency. Conclusions Serological indicators of WBC, hs-CRP, NLR and RDW in patients with acute exacerbation of COPD will be abnormally increased, and NLR has a positive correlation with WBC and hs-CRP. NLR and RDW have high specificity and high sensitivity respectively in the diagnosis of patients with exacerbation of COPD, and their detection can strengthen the diagnosis and mastery of disease in patients.
Accurate reconstruction of tissue elasticity modulus distribution has always been an important challenge in ultrasound elastography. Considering that existing deep learning-based supervised reconstruction methods only use simulated displacement data with random noise in training, which cannot fully provide the complexity and diversity brought by in-vivo ultrasound data, this study introduces the use of displacement data obtained by tracking in-vivo ultrasound radio frequency signals (i.e., real displacement data) during training, employing a semi-supervised approach to enhance the prediction accuracy of the model. Experimental results indicate that in phantom experiments, the semi-supervised model augmented with real displacement data provides more accurate predictions, with mean absolute errors and mean relative errors both around 3%, while the corresponding data for the fully supervised model are around 5%. When processing real displacement data, the area of prediction error of semi-supervised model was less than that of fully supervised model. The findings of this study confirm the effectiveness and practicality of the proposed approach, providing new insights for the application of deep learning methods in the reconstruction of elastic distribution from in-vivo ultrasound data.
High-grade serous ovarian cancer has a high degree of malignancy, and at detection, it is prone to infiltration of surrounding soft tissues, as well as metastasis to the peritoneum and lymph nodes, peritoneal seeding, and distant metastasis. Whether recurrence occurs becomes an important reference for surgical planning and treatment methods for this disease. Current recurrence prediction models do not consider the potential pathological relationships between internal tissues of the entire ovary. They use convolutional neural networks to extract local region features for judgment, but the accuracy is low, and the cost is high. To address this issue, this paper proposes a new lightweight deep learning algorithm model for predicting recurrence of high-grade serous ovarian cancer. The model first uses ghost convolution (Ghost Conv) and coordinate attention (CA) to establish ghost counter residual (SCblock) modules to extract local feature information from images. Then, it captures global information and integrates multi-level information through proposed layered fusion Transformer (STblock) modules to enhance interaction between different layers. The Transformer module unfolds the feature map to compute corresponding region blocks, then folds it back to reduce computational cost. Finally, each STblock module fuses deep and shallow layer depth information and incorporates patient's clinical metadata for recurrence prediction. Experimental results show that compared to the mainstream lightweight mobile visual Transformer (MobileViT) network, the proposed slicer visual Transformer (SlicerViT) network improves accuracy, precision, sensitivity, and F1 score, with only 1/6 of the computational cost and half the parameter count. This research confirms that the proposed algorithm model is more accurate and efficient in predicting recurrence of high-grade serous ovarian cancer. In the future, it can serve as an auxiliary diagnostic technique to improve patient survival rates and facilitate the application of the model in embedded devices.
ObjectiveTo study the cytokine changes in the cerebrospinal fluid (CSF) of mesial temporal lobe epilepsy (MTLE) patients, and the mechanism of the development of hippocampal sclerosis. MethodsFifty MTLE patients who sought treatment from January 2013 to March 2014 were included in the study. Clinical features were investigated. All CSF samples of the 59 patients along with 19 samples of the control group were tested for 12 common cytokines using a chemokine magnetic bead panel. Data were statistically analyzed. ResultsClinical features showed no significant difference between hippocampal sclerosis and non-hippocampal sclerosis patients. Interleukin (IL)-1 receptor antagonist (RA), IL-4 and IL-9 expression decreased, and tumor necrosis factor (TNF)-α, IL-3 and IL-5 expression increased. Up-regulation of TNF-α was significantly different between hippocampal sclerosis and non-hippocampal sclerosis patients. ConclusionIL-1RA, IL-3, IL-4, IL-5 and IL-9 changes may be non-specific seizure-related cytokine regulation. TNF-α is associated with hippocampal sclerosis pathology. TNF-α is a possible pathological element in hippocampal sclerosis development.
In recent years, due to the emergence of ultrafast ultrasound imaging technology, the sensitivity of detecting slow and micro blood flow with ultrasound has been dramatically improved, and functional ultrasound imaging (fUSI) has been developed. fUSI is a novel technology for neurological imaging that utilizes neurovascular coupling to detect the functional activity of the central nervous system (CNS) with high spatiotemporal resolution and high sensitivity, which is dynamic, non-invasive or minimally invasive. fUSI fills the gap between functional magnetic resonance imaging (fMRI) and optical imaging with its high accessibility and portability. Moreover, it is compatible with electrophysiological recording and optogenetics. In this paper, we review the developments of fUSI and its applications in neuroimaging. To date, fUSI has been used in various animals ranging from mice to non-human primates, as well as in clinical surgeries and bedside functional brain imaging of neonates. In conclusion, fUSI has great potential in neuroscience research and is expected to become an important tool for neuroscientists, pathologists and pharmacologists.