Modulatory Effect of Low-Intensity Transcranial Ultrasound Stimulation on Behaviour and Neural Oscillation in Mouse Models of Alzheimer's Disease.

Transcranial ultrasound stimulation (TUS) is a noninvasive brain neuromodulation technique. The application of TUS for Alzheimer's disease (AD) therapy has not been widely studied. In this study, a long-term course (28 days) of TUS was used to stimulate the hippocampus of APP/PS1 mice. We examined the modulatory effect of TUS on behavior and neural oscillation in AD mice. We found that TUS can 1) improve the learning and memory abilities of AD mice; 2) reduce the phase-amplitude coupling of delta-epsilon, delta-gamma and theta-gamma frequency bands of local field potential, and increase the relative power of epsilon frequency bands in AD mice; 3) reduce the spike firing rate of interneurons and inhibit the phase-locked angle deflection between the theta frequency bands and the spikes of the two types of neurons that develops with the progression of the disease in AD mice. In summary, we demonstrate that TUS could effectively improve cognitive behavior and modulate neural oscillation with AD.

Multimodal evaluation of the effects of low-intensity ultrasound on cerebral blood flow after traumatic brain injury in mice.

Traumatic brain injury (TBI) is one of the leading causes of death and disability worldwide, and destruction of the cerebrovascular system is a major factor in the cascade of secondary injuries caused by TBI. Laser speckle imaging (LSCI)has high sensitivity in detecting cerebral blood flow. LSCI can visually show that transcranial focused ultrasound stimulation (tFUS) treatment stimulates angiogenesis and increases blood flow. To study the effect of tFUS on promoting angiogenesis in Controlled Cortical impact (CCI) model. tFUS was administered daily for 10 min and for 14 consecutive days after TBI. Cerebral blood flow was measured by LSCI at 1, 3, 7 and 14 days after trauma. Functional outcomes were assessed using LSCI and neurological severity score (NSS). After the last test, Nissl staining and vascular endothelial growth factor (VEGF) were used to assess neuropathology. TBI can cause the destruction of cerebrovascular system. Blood flow was significantly increased in TBI treated with tFUS. LSCI, behavioral and histological findings suggest that tFUS treatment can promote angiogenesis after TBI.

Effect of Repeated Application of Flos Daturae on Sedative and Hypnotic in Mice.

Insomnia is one of the most common sleep-related diseases. In traditional Chinese medicine, Flos daturae has been used as a traditional herbal totreatment of sizens of diseases. The research objective was to investigate the sedative and hypnotic effects of Flos Daturae. Kunming mice were divided into control group, Estazolam (positive drug, 0.0005 g/kg) group and Flos Daturae groups (0.01, 0.02, 0.04g/kg) with random, ig once a day for 7 days. The central sedative effect of flos Daturae on the spontaneous activity of mice was observed using the locomotive activity test, and the hypnotic effect of Flos Daturae was observed in mice using the direct sleep test and the sleep latency with synergistic supra-and sub-threshold doses of pentobarbital sodium. Flos Daturae (0.04g/kg) significantly inhibited mice locomotive activity (P<0.05) and had no direct sleeping effect (P>0.05), increased the number rate of sleep (P<0.05), and significantly shortening sleep latency (P<0.05), enhanced pentobarbital sodium-induced sleep. Flos Daturae possesses have sedative-hypnotic properties.

Preoperative assessment of high-grade endometrial cancer using a radiomic signature and clinical indicators.

Aim: To develop and validate a radiomics-based combined model (ModelRC) to predict the pathological grade of endometrial cancer. Methods: A total of 403 endometrial cancer patients from two independent centers were enrolled as training, internal validation and external validation sets. Radiomic features were extracted from T2-weighted images, apparent diffusion coefficient map and contrast-enhanced 3D volumetric interpolated breath-hold examination images. Results: Compared with the clinical model and radiomics model, ModelRC showed superior performance; the areas under the receiver operating characteristic curves were 0.920 (95% CI: 0.864-0.962), 0.882 (95% CI: 0.779-0.955) and 0.881 (95% CI: 0.815-0.939) for the training, internal validation and external validation sets, respectively. Conclusion: ModelRC, which incorporated clinical and radiomic features, exhibited excellent performance in the prediction of high-grade endometrial cancer.

Accurate preoperative evaluation of the pathological grade of endometrial carcinoma is very important for the selection of treatment and prognosis. This study tried to develop a simple combined model based on radiomic features from endometrial carcinoma MRI and clinical features of patients. Compared with the clinical model and the radiomic model, the combined model showed superior performance. Therefore, this combined model would help patients and clinicians to make more rational decisions when choosing treatment strategies.

Deep learning and radiomics to predict the mitotic index of gastrointestinal stromal tumors based on multiparametric MRI.

Introduction: Preoperative evaluation of the mitotic index (MI) of gastrointestinal stromal tumors (GISTs) represents the basis of individualized treatment of patients. However, the accuracy of conventional preoperative imaging methods is limited. The aim of this study was to develop a predictive model based on multiparametric MRI for preoperative MI prediction. Methods: A total of 112 patients who were pathologically diagnosed with GIST were enrolled in this study. The dataset was subdivided into the development (n = 81) and test (n = 31) sets based on the time of diagnosis. With the use of T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) map, a convolutional neural network (CNN)-based classifier was developed for MI prediction, which used a hybrid approach based on 2D tumor images and radiomics features from 3D tumor shape. The trained model was tested on an internal test set. Then, the hybrid model was comprehensively tested and compared with the conventional ResNet, shape radiomics classifier, and age plus diameter classifier. Results: The hybrid model showed good MI prediction ability at the image level; the area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), and accuracy in the test set were 0.947 (95% confidence interval [CI]: 0.927-0.968), 0.964 (95% CI: 0.930-0.978), and 90.8 (95% CI: 88.0-93.0), respectively. With the average probabilities from multiple samples per patient, good performance was also achieved at the patient level, with AUROC, AUPRC, and accuracy of 0.930 (95% CI: 0.828-1.000), 0.941 (95% CI: 0.792-1.000), and 93.6% (95% CI: 79.3-98.2) in the test set, respectively. Discussion: The deep learning-based hybrid model demonstrated the potential to be a good tool for the operative and non-invasive prediction of MI in GIST patients.

Multi-Parameter MR Radiomics Based Model to Predict 5-Year Progression-Free Survival in Endometrial Cancer.

Background: Relapse is the major cause of mortality in patients with resected endometrial cancer (EC). There is an urgent need for a feasible method to identify patients with high risk of relapse. Purpose: To develop a multi-parameter magnetic resonance imaging (MRI) radiomics-based nomogram model to predict 5-year progression-free survival (PFS) in EC. Methods: For this retrospective study, 202 patients with EC followed up for at least 5 years after hysterectomy. A radiomics signature was extracted from T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC) and a dynamic contrast-enhanced three-dimensional volumetric interpolated breath-hold examination (3D-VIBE). The radiomics score (RS) was calculated based on the least absolute shrinkage and selection operator (LASSO) regression. We have developed a radiomics based nomogram model (ModelN) incorporating the RS and clinical and conventional MR (cMR) risk factors. The performance was evaluated by the receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA). Results: The ModelN demonstrated a good calibration and satisfactory discrimination, with a mean area under the curve (AUC) of 0.840 and 0.958 in the training and test cohorts, respectively. In comparison with clinical prediction model (ModelC), the discrimination ability of ModelN showed an improvement with P < 0.001 for the training cohort and P=0.032 for the test cohort. Compared to the radiomics prediction model (ModelR), ModelN discrimination ability showed an improvement for the training cohort with P = 0.021, with no statistically significant difference in the test cohort (P = 0.106). Calibration curves suggested a good fit for probability (Hosmer-Lemeshow test, P = 0.610 and P = 0.956 for the training and test cohorts, respectively). Conclusion: This multi-parameter nomogram model incorporating clinical and cMR findings is a valid method to predict 5-year PFS in patients with EC.

Detecting dopaminergic neuronal degeneration using diffusion tensor imaging in a rotenone-induced rat model of Parkinson's disease: fractional anisotropy and mean diffusivity values.

Dopamine content in the basal ganglia is strongly associated with the degree of dopaminergic neuron loss in the substantia nigra pars compacta. Symptoms of Parkinson's disease might not arise until more than 50% of the substantia nigra pars compacta is lost and the dopamine content in the basal ganglia is reduced by more than 80%. Greater diagnostic sensitivity and specificity would allow earlier detection of Parkinson's disease. Diffusion tensor imaging is a recently developed magnetic resonance imaging technique that measures mean diffusivity and fractional anisotropy, and responds to changes in brain microstructure. When the microscopic barrier (including cell membranes, microtubules and other structures that interfere with the free diffusion of water) is destroyed and extracellular fluid volume accumulates, the mean diffusivity value increases; when the integrity of the microstructure (such as myelin) is destroyed, fractional anisotropy value decreases. However, there is no consensus as to whether these changes can reflect the early pathological alterations in Parkinson's disease. Here, we established a rat model of Parkinson's disease by injecting rotenone (or sunflower oil in controls) into the right substantia nigra. Diffusion tensor imaging results revealed that in the stages of disease, at 1, 2, 4, and 6 weeks after rotenone injection, fractional anisotropy value decreased, but mean diffusivity values increased in the right substantia nigra in the experimental group. Fractional anisotropy values were lower at 4 weeks than at 6 weeks in the right substantia nigra of rats from the experimental group. Mean diffusivity values were markedly greater at 1 week than at 6 weeks in the right corpus striatum of rats from the experimental group. These findings suggest that mean diffusivity and fractional anisotropy values in the brain of rat models of Parkinson's disease 4 weeks after model establishment can reflect early degeneration of dopaminergic neurons. The change in fractional anisotropy values after destruction of myelin integrity is likely to be of greater early diagnostic significance than the change in mean diffusivity values.

P2X3, but not P2X1, receptors mediate ATP-activated current in neurons innervating tooth-pulp.

We developed a method that allows us to label nociceptive neurons innervating tooth-pulp in rat trigeminal ganglion neurons using a retrograde fluorescence-tracing method, to record ATP-activated current in freshly isolated fluorescence-labeled neurons and to conduct single cell immunohistochemical staining for P2X1 and P2X3 subunits in the same neuron. Three types of ATP-activated current in these neurons (F, I and S) were recorded. The cells exhibiting the type F current mainly showed positive staining for P2X3, but negative staining for P2X1. The results provide direct and convincing evidence at the level of single native nociceptive neurons for correlation of the characteristics of ATP-activated currents with their composition of P2X1 and P2X3 subunits and cell size. The results also suggest that the P2X3, but not P2X1, is the main subunit that mediates the fast ATP-activated current in nociceptive neurons.

Application of T2 measurement on gradient echo T2-weighted imaging in differential diagnosis of intracranial hemorrhage and calcification.

BACKGROUND: Differential diagnosis of intracranial hemorrhage and calcification is a common problem encountered in clinical imaging diagnosis. The purpose of this study was to investigate the feasibility of T2 measurement on gradient echo (GRE) T2-weighted imaging (T2WI) in differential diagnosis of intracranial hemorrhage and calcification. METHODS: Thirty-eight hemorrhagic foci in 18 patients and 11 calcification foci in seven patients were included in this study. The diagnosis of hemorrhage and calcification was confirmed in all cases with enhanced T2 weighted angiography (ESWAN) magnetic resonance imaging (MRI) and CT respectively. The significance for the difference of T2 value between the central and peripheral areas of hemorrhage and calcification lesions was tested with univariate analysis of variance. RESULTS: The detection rate of GRE T2 WI on intracranial hemorrhage was 1.9-fold higher than that of CT, especially for the hemorrhage in the brainstem and cerebellum. However, GRE T2WI was far less sensitive to calcification than CT. There was a significant difference in the T2 value between the central area of hemorrhage and calcification (P < 0.001), though no difference in the T2 value was obtained between the peripheral area of hemorrhage and calcification (P > 0.05). CONCLUSIONS: Quantitative measurement of T2 value on GRE T2 WI with a single MRI examination provides a fast, convenient, and effective means in differential diagnosis between intracranial hemorrhage and calcification, which may thus reduce the medical cost and save precious time for clinical management.

Effect of bis(7)-tacrine on cognition in rats with chronic cerebral ischemia.

Bis(7)-tacrine (B7T), a novel dimeric acetyl cholinesterase (AChE) inhibitor, has multiple neuroprotective activities against neuronal damage. However, its therapeutic effects in chronic cerebral ischemia remain unknown. In the present study, adult male Sprague-Dawley rats were subjected with permanent ligation of the bilateral common carotid arteries to investigate the roles of B7T on cognitive function, neuronal apoptosis and neurogenesis in the hippocampus. Results from spatial navigation test showed that chronic cerebral ischemia impaired spatial learning, B7T treatment shorten escape latency of ischemia rats as compared with saline-treated rats. Probe trial test indicated that spatial memory deficit of chronic cerebral ischemic animals was reversed by B7T treatment. Immunohistochemical results showed that B7T reduced neuronal apoptosis in the hippocampal CA1 region as compared with ischemia rats, and B7T treatment increased neurogenesis in the hippocampus. These findings suggest that B7T may exert its neuroprotective effects by inhibiting apoptosis and promoting neurogenesis in 2VO rats.