Cognitive Effect of Transcranial Direct Current Stimulation on Left Dorsolateral Prefrontal Cortex in Mild Alzheimer's Disease: A Randomized, Double-Blind, Cross-Over Small-Scale Exploratory Study.

Background: Transcranial direct current stimulation (tDCS) is considered a potential therapeutic instrument for Alzheimer's disease (AD) because it affects long-term synaptic plasticity through the processes of long-term potentiation and long-term depression, thereby improving cognitive ability. Nevertheless, the efficacy of tDCS in treating AD is still debated. Dorsal lateral prefrontal cortex is the main role in executive functions. Objective: We investigate the cognitive effects of tDCS on AD patients. Methods: Thirty mild AD patients aged 66-86 years (mean = 75.6) were included in a double-blind, randomized, sham-controlled crossover study. They were randomly assigned to receive 10 consecutive daily sessions of active tDCS (2 mA for 30 min) or a sham intervention and switched conditions 3 months later. The anodal and cathodal electrodes were placed on the left dorsal lateral prefrontal cortex and the right supraorbital area, respectively. Subjects underwent various neuropsychological assessments before and after the interventions. Results: The results showed that tDCS significantly improved Cognitive Abilities Screening Instrument scores, especially on the items of "concentration and calculation", "orientation", "language ability", and "categorical verbal fluency". Mini-Mental State Examination and Wisconsin Card Sorting Test scores in all domains of "concept formation", "abstract thinking", "cognitive flexibility", and "accuracy" also improved significantly after tDCS. For the sham condition, no difference was found between the baseline scores and the after-intervention scores on any of the neuropsychological tests. Conclusion: >: Using tDCS improves the cognition of AD patients. Further large size clinical trials are necessary to validate the data.

Spontaneous Breathing and Pendelluft in Patients with Acute Lung Injury: A Narrative Review.

Acute respiratory distress syndrome (ARDS) is characterized by acute-onset rapid-deteriorating inflammatory lung injury. Although the preservation of spontaneous breathing may have physiological benefits in oxygenation, increasing evidence shows that vigorous spontaneous breathing may aggravate lung injury (i.e., patient self-inflicted lung injury). Increased lung stress and pendelluft, which is defined as intrapulmonary gas redistribution without a significant change in tidal volume, are important mechanisms of patient self-inflicted lung injury. The presence of pendelluft may be considered a surrogate marker of vigorous inspiratory effort, which can cause the dependent lung to overstretch. In this review, we summarized three major methods for electrical impedance tomography-based pendelluft monitoring. Future studies are warranted to compare and validate the different methods of pendelluft estimation in patients with ARDS.

The Effect of Agomelatine in Behavioral and Psychological Symptoms of Dementia.

Objective: Moderate and severe behavioral and psychological symptoms of dementia (BPSD) often need medical treatment to improve symptoms. Agomelatine is a selective melatonergic (MT1/MT2) agonist that has normalizing effects on disturbed circadian rhythms and disrupted sleep-wake cycles. Its activity of 5HT-2C receptor antagonism is associated with lessening depression and anxiety and increasing slow-wave sleep. Based on past clinical records and current findings it suggests that agomelatine can improve BPSD for patients. This retrospective cohort study was designed to compare the BPSD before and after using agomelatine. Methods: Records of dementia cases who had ever received agomelatine treatment for BPSD in a general hospital setting during the past 2.5 years were identified and reviewed. Scores from before and after 3 months of treatment with agomelatine were collected for Neuropsychiatric Inventory (NPI), Brief Psychiatric Rating Scale (BPRS), and Clinical Global Impression (CGI) to compare and analyze the difference of psychological and behavioral symptoms pre- and post-agomelatine used. Results: Records of 144 cases of dementia with BPSD who had ever used agomelatine from January 2015 to June 2017 were collected. All of the 112 cases had BPRS and CGI scores, of which 75 cases had additional NPI scores. Among these 112 cases, the BPRS and CGI scores were significantly improved in all types of dementia. NPI scores indicated that the use of agomelatine alleviated obvious symptoms and decreased overall distress, especially in the depression/poor mood, anxiety, and sleep/night behavior. Conclusion: It is consistent with an effective result of agomelatine in improving BPSD.

Separation of Heart and Lung-related Signals in Electrical Impedance Tomography Using Empirical Mode Decomposition.

BACKGROUND: Electrical impedance tomography (EIT) can be used for continuous monitoring of pulmonary ventilation. However, no proper method has been developed for the separation of pulmonary ventilation and perfusion signals and the measurement of the associated ventilation/ perfusion (V/Q) ratio. Previously, various methods have been used to extract these components; however, these have not been able to effectively separate and validate cardiac- and pulmonary- related images. AIMS: This study aims at validating and developing a novel method to separate cardiac- and pulmonary- related components based on the EIT simulation field of view and to simultaneously reconstruct the individual images instantly. METHODS: Our approach combines the advantages of the principal component analysis (PCA) and processes that originally measure EIT data instead of handling a series of EIT images, thus introducing the empirical mode decomposition (EMD). The PCA template functions for cardiacrelated imaging and intrinsic mode functions (IMFs) of EMD for lung-related imaging are then adapted to input signals. RESULTS: The proposed method enables the separation of cardiac- and lung-related components by adjusting the proportion of the key components related to lung imaging, which are the fourth component (PC4) and the first component (IMF1) in PCA- and EMD-based methods, respectively. The preliminary results on the application of the method to real human EIT data revealed the consistently better performance and optimal computation compared with previous methods. CONCLUSION: This study proposes a novel method for applying EIT to evaluate the best time of V/Q matching on the cardiovascular and respiratory systems; this aspect can be investigated in future research.

Muscle Mass Measurement Using Machine Learning Algorithms with Electrical Impedance Myography.

Sarcopenia is a wild chronic disease among elderly people. Although it does not entail a life-threatening risk, it will increase the adverse risk due to the associated unsteady gait, fall, fractures, and functional disability. The import factors in diagnosing sarcopenia are muscle mass and strength. The examination of muscle mass must be carried in the clinic. However, the loss of muscle mass can be improved by rehabilitation that can be performed in non-medical environments. Electronic impedance myography (EIM) can measure some parameters of muscles that have the correlations with muscle mass and strength. The goal of this study is to use machine learning algorithms to estimate the total mass of thigh muscles (MoTM) with the parameters of EIM and body information. We explored the seven major muscles of lower limbs. The feature selection methods, including recursive feature elimination (RFE) and feature combination, were used to select the optimal features based on the ridge regression (RR) and support vector regression (SVR) models. The optimal features were the resistance of rectus femoris normalized by the thigh circumference, phase of tibialis anterior combined with the gender, and body information, height, and weight. There were 96 subjects involved in this study. The performances of estimating the MoTM used the regression coefficient (r2) and root-mean-square error (RMSE), which were 0.800 and 0.929, and 1.432 kg and 0.980 kg for RR and SVR models, respectively. Thus, the proposed method could have the potential to support people examining their muscle mass in non-medical environments.

Using Self-Administered Game-Based Cognitive Assessment to Screen for Degenerative Dementia: A Pilot Study.

BACKGROUND: The earlier detection of dementia is needed as cases increase yearly in the aging populations of Taiwan and the world. In recent years, the global internet usage rate has gradually increased among older people. To expand dementia screening and provide timely medical intervention, a simple self-administrated assessment tool to assist in easily screening for dementia is needed. OBJECTIVE: The two-part goal of this pilot study was, first, to develop a Game-Based Cognitive Assessment (GBCA) tool, and then, to evaluate its validity at early screening for patients with cognitive impairment. METHOD: The researchers recruited 67 patients with neurocognitive disorders (NCDs) and 57 healthy controls (HCs). Each participant underwent the GBCA and other clinical cognitive assessments (CDR, CASI, and MMSE), and filled out a questionnaire evaluating their experience of using the GBCA. Statistical analyses were used to measure the validity of the GBCA at screening for degenerative dementia. RESULTS: The average GBCA scores of the HC and NCD groups were 87 (SD = 7.9) and 52 (SD = 21.7), respectively. The GBCA correlated well with the CASI (r2 = 0.90, p < 0.001) and with the MMSE (r2 = 0.92, p < 0.001), indicating concurrent validity. The GBCA cut-off of 75/76 corresponded to measurements of sensitivity, specificity, and area under curve of 85.1%, 91.5%, and 0.978, respectively. The positive predictive value was 91.9%, and the negative predictive value was 84.4%. The results of the user-experience questionnaire for the HC and NCD groups were good and acceptable, respectively. CONCLUSION: The GBCA is an effective and acceptable tool for screening for degenerative dementia.

Higher Periwound Temperature Associated with Wound Healing of Pressure Ulcers Detected by Infrared Thermography.

Visual and empirical assessments do not enable the early detection of wound deterioration or necroses. No suitable objective indicator for predicting poor wound-healing is currently available. We used infrared thermography to determine the association between wound temperature and pressure-wound healing. We examined patients with grades 2-4 pressure ulcers from a medical center in southern Taiwan and recorded the temperatures of the wound bed, periwound, and normal skin using infrared thermographic cameras. A total of 50 pressure ulcers and 248 infrared-thermography temperature records were analyzed. Normal skin temperature was not related to pressure ulcer wound healing. In a multivariate analysis, higher malnutrition universal-screening-tool scores were associated with poor wound-healing (p = 0.020), and higher periwound-temperature values were associated with better wound-healing (p = 0.028). In patients who had higher periwound-skin temperature than that of the wound bed, that result was also associated with better wound-healing (p = 0.002). Wound-bed and periwound temperatures differed significantly with the grade of the pressure ulcer, and a high periwound temperature was positively correlated with wound healing. Infrared thermography can objectively serve as indicators for assessing pressure-ulcer healing.

Semi-Siamese U-Net for separation of lung and heart bioimpedance images: A simulation study of thorax EIT.

Electrical impedance tomography (EIT) is widely used for bedside monitoring of lung ventilation status. Its goal is to reflect the internal conductivity changes and estimate the electrical properties of the tissues in the thorax. However, poor spatial resolution affects EIT image reconstruction to the extent that the heart and lung-related impedance images are barely distinguishable. Several studies have attempted to tackle this problem, and approaches based on decomposition of EIT images using linear transformations have been developed, and recently, U-Net has become a prominent architecture for semantic segmentation. In this paper, we propose a novel semi-Siamese U-Net specifically tailored for EIT application. It is based on the state-of-the-art U-Net, whose structure is modified and extended, forming shared encoder with parallel decoders and has multi-task weighted losses added to adapt to the individual separation tasks. The trained semi-Siamese U-Net model was evaluated with a test dataset, and the results were compared with those of the classical U-Net in terms of Dice similarity coefficient and mean absolute error. Results showed that compared with the classical U-Net, semi-Siamese U-Net exhibited performance improvements of 11.37% and 3.2% in Dice similarity coefficient, and 3.16% and 5.54% in mean absolute error, in terms of heart and lung-impedance image separation, respectively.

U-Net-based approach for automatic lung segmentation in electrical impedance tomography.

OBJECTIVE: Electrical impedance tomography (EIT) is a non-invasive technique that constitutes a promising tool for real-time imaging and long-term monitoring of the ventilation distribution at bedside. However, clinical monitoring and diagnostic evaluations depend on various methods to assess ventilation-dependent parameters useful for ventilation therapy. This study develops an automatic, robust, and rapidly accessible method for lung segmentation that can be used to define appropriate regions-of-interest (ROIs) within EIT images. APPROACH: To date, available methods for patients with defected lungs have the disadvantage of not being able to identify lung regions because of their poor ventilation responses. Furthermore, the challenges related to the identification of lung areas in EIT images are attributed to the low spatial resolution of EIT. In this study, a U-Net-based automatic lung segmentation model is used as a postprocessor to transform the original EIT image to a lung ROI image and refine the inherent conductivity distribution of the original EIT image. The trained U-Net network is capable of performing an automatic segmentation of conductivity changes in EIT images without requiring prior information. MAIN RESULTS: The experimental design of this study was based on a finite element method (FEM) phantom used to assess the feasibility and effectiveness of the proposed method, and evaluation of the trained models on the test dataset was performed using the Dice similarity coefficient (DSC) and the mean absolute error (MAE). The FEM experimental results yielded values of 0.0065 for MAE, and values >0.99 for DSC in simulations. SIGNIFICANCE: The use of a deep-learning-based approach attained automatic and convenient segmentation of lung ROIs into distinguishable images, which represents a direct benefit for regional lung ventilation-dependent parameter extraction and analysis. However, further investigations and validation are warranted in real human datasets with different physiology conditions with CT cross-section dataset to refine the suggested model.

Brain Structural Magnetic Resonance Imaging for Joint Independent Component Analysis in Schizophrenic Patients.

BACKGROUND: In past magnetic resonance imaging studies, normal participants and schizophrenia patients have usually been compared using imaging processing modes with only one parameter. A more extensive evaluation of significant differences between gray and white matter in Schizophrenic patents was necessary. METHODS: Voxel based morphometry was used to separate brain images into gray matter and white matter. Then, the images were mapped to Montreal Neurological Institute space, and DARTEL analytic template was applied for image calibration with statistical parametric mapping. Finally, joint independent component analysis was employed to analyze the gray and white matter of brain images from Schizophrenic patients and normal controls. In this study, joint independent component analysis was used to discriminate clinical differences in magnetic resonance imaging signals between Schizophrenic patients and normal controls. RESULTS: Region of interest analyses has repeatedly shown gray matter reduction in the superior temporal gyrus of Schizophrenic patients. CONCLUSION: These results strongly support previous studies regarding brain volume in schizophrenic patients. The connection networks in frontal and temporal lobes evidently did not differ between normal participants and schizophrenia patients.

Analysis of EEG entropy during visual evocation of emotion in schizophrenia.

BACKGROUND: In this study, the international affective picture system was used to evoke emotion, and then the corresponding signals were collected. The features from different points of brainwaves, frequency, and entropy were used to identify normal, moderately, and markedly ill schizophrenic patients. METHODS: The signals were collected and preprocessed. Then, the signals were separated according to three types of emotions and five frequency bands. Finally, the features were calculated using three different methods of entropy. For classification, the features were divided into different sections and classification using support vector machine (principal components analysis on 95%). Finally, simple regression and correlation analysis between the total scores of positive and negative syndrome scale and features were used. RESULTS: At first, we observed that to classify normal and markedly ill schizophrenic patients, the identification result was as high as 81.5%, and therefore, we further explored moderately and markedly ill schizophrenic patients. Second, the identification rate in both moderately and markedly ill schizophrenic patient was as high as 79.5%, which at the Fz point signal in high valence low arousal fragments was calculated using the ApEn methods. Finally, the total scores of positive and negative syndrome scale were used to analyze the correlation with the features that were the five frequency bands at the Fz point signal. The results show that the p value was less than .001 at the beta wave in the 15-18 Hz frequency range.

A Correlative Classification Study of Schizophrenic Patients with Results of Clinical Evaluation and Structural Magnetic Resonance Images.

Patients with schizophrenia suffer from symptoms such as hallucination and delusion. There are currently a number of publications that discuss the treatment, diagnosis, prognosis, and damage in schizophrenia. This study utilized joint independent component analysis to process the images of GMV and WMV and incorporated the Wisconsin card sorting test (WCST) and the positive and negative syndrome scale (PANSS) to examine the correlation of obtained brain characteristics. We also used PANSS score to classify schizophrenic patients into acute and subacute cases, to analyze the brain structure differences. Finally, we used brain structure images and the error rate of the WCST as eigenvalues in support vector machine learning and classification. The results of this study showed that the frontal and temporal lobes of a normal brain are more apparent than those of a schizophrenia brain. The highest level of classification recognition reached 91.575%, indicating that the WCST error rate and characteristic changes in brain structure volume can be used to effectively distinguish schizophrenia and normal brains. Similarly, this result confirmed that the WCST and brain structure volume are correlated with the differences between schizophrenia and normal participants.

Can Parameters Other than Minimal Axial Diameter in MRI and PET/CT Further Improve Diagnostic Accuracy for Equivocal Retropharyngeal Lymph Nodes in Nasopharyngeal Carcinoma?

PURPOSE: Minimal axial diameter (MIAD) in magnetic resonance imaging (MRI) was recognized as the most useful parameter in diagnosing lateral retropharyngeal lymph (LRPL) nodes in nasopharyngeal carcinoma (NPC). This study aims to explore the additional nodal parameters in MRI and positron emission tomography-computed tomography for increasing the prediction accuracy. MATERIALS AND METHODS: A total of 663 LRPL nodes were retrospectively collected from 335 patients with NPC. The LRPL nodes ascertained on follow-up MRI were considered positive for metastases. First, the optimal cutoff value of each parameter was derived for each parameter. In addition, neural network (NN) nodal evaluation was tested for all combinations of three parameters, namely MIAD, maximal axial diameter (MAAD), and maximal coronal diameter (MACD). The optimal approach was determined through brute force attack, and the results of two methods were compared using a bootstrap sampling method. Second, the mean standard uptake value (NSUVmean) was added as the fourth parameter and tested in the same manner for 410 nodes in 219 patients. RESULTS: In first and second analysis, the accuracy rate (percentage) for the MIAD was 89.0% (590/663) and 89.0% (365/410), with the optimal cutoff values being 6.1 mm and 6.0 mm, respectively. With the combination of all three and four parameters, the accuracy rate of the NN was 89% (288/332) and 88.8% (182/205), respectively. In prediction, the optimal combinations of the three and four parameters resulted in correct identification of three (accuracy: 593/663, 89.4%) and six additional nodes (371/410, 90.5%), representing 4% (3/73) and 13.3% (6/45) decreases in incorrect prediction, respectively. CONCLUSION: NPC LRPL nodes with an MIAD ≥ 6.1 mm are positive. Among nodes with an MIAD < 6.1 mm, if the NSUVmean ≥ 2.6 or MACD ≥ 25 mm and MAAD ≥ 8 mm, the nodes are positive; otherwise, they are negative.

Electrical impedance tomography monitoring in acute respiratory distress syndrome patients with mechanical ventilation during prolonged positive end-expiratory pressure adjustments.

BACKGROUND/PURPOSE: The time required to reach oxygenation equilibrium after positive end-expiratory pressure (PEEP) adjustments in mechanically ventilated patients with acute respiratory distress syndrome (ARDS) is unclear. We used electrical impedance tomography to elucidate gas distribution and factors related to oxygenation status following PEEP in patients with ARDS. METHODS: Nineteen mechanically ventilated ARDS patients were placed on baseline PEEP (PEEPB) for 1 hour, PEEPB - 4 cmH2O PEEP (PEEPL) for 30 minutes, and PEEPB + 4 cmH2O PEEP (PEEPH) for 1 hour. Tidal volume and respiratory rate were similar. Impedance changes, respiratory parameters, and arterial blood gases were measured at baseline, 5 minutes, and 30 minutes after PEEPL, and 5 minutes, 15 minutes, 30 minutes, and 1 hour after PEEPH. RESULTS: PaO2/fraction of inspired oxygen (P/F ratio) decreased quickly from PEEPB to PEEPL, and stabilized 5 minutes after PEEPL. However the P/F ratio progressively increased from PEEPL to PEEPH, and a significantly higher P/F ratio and end-expiratory lung impedance were found at 60 minutes compared to 5 minutes after PEEPH. The end-expiratory lung impedance level significantly correlated with P/F ratio (p < 0.001). With increasing PEEP, dorsal ventilation significantly increased; however, regional ventilation did not change over time with PEEP level. CONCLUSION: Late improvements in oxygenation following PEEP escalation are probably due to slow recruitment in ventilated ARDS patients. Electrical impedance tomography may be an appropriate tool to assess recruitment and oxygenation status in patients with changes in PEEP.

GPS-based outdoor activity pattern recording and analysis system.

In this paper, a recording and analysis system is designed and developed for outdoor activity patterns characterization. Some mental problems of aging, especially the occurrence of dementia, are not easily noticed in early stage. In this study, the proposed system is employed for outdoor activity patterns analysis. From the pattern analysis, the abnormal activity which is different from the usual patterns may be differentiated and warned. The proposed system integrates the tablet PC and GPS to track and to detect the occurrence of abnormal condition off-line. In the beginning, the sequence of GPS data is segmented in time frame, and represented in vector form for data reduction. Some filtering technique is also applied for noise reduction.

Electrical impedance spectroscopy as electrical biopsy for monitoring radiation sequelae of intestine in rats.

Electrical impedance is one of the most frequently used parameters for characterizing material properties. The resistive and capacitive characteristics of tissue may be revealed by electrical impedance spectroscopy (EIS) as electrical biopsy. This technique could be used to monitor the sequelae after irradiation. In this study, rat intestinal tissues after irradiation were assessed by EIS system based on commercially available integrated circuits. The EIS results were fitted to a resistor-capacitor circuit model to determine the electrical properties of the tissue. The variations in the electrical characteristics of the tissue were compared to radiation injury score (RIS) by morphological and histological findings. The electrical properties, based on receiver operation curve (ROC) analysis, strongly reflected the histological changes with excellent diagnosis performance. The results of this study suggest that electrical biopsy reflects histological changes after irradiation. This approach may significantly augment the evaluation of tissue after irradiation. It could provide rapid results for decision making in monitoring radiation sequelae prospectively.

Using Akaike information criterion and minimum mean square error mode in compensating for ultrasonographic errors for estimation of fetal weight by new operators.

OBJECTIVES: The accuracy of ultrasound (US) measurements is operator dependent. In order to decrease the operator-dependent errors in estimated fetal weight (EFW), a model selection analysis was undertaken to select significant compensation weighting factors on ultrasonographic parameters to support artificial neural network (ANN), and thus to enhance the accuracy of fetal weight estimation. MATERIALS AND METHODS: In total, 2127 singletons were examined by prenatal US within 3 days before delivery for ANN development, and another 100 cases were selected from new operators for evaluation. First, correlation analysis was used to analyze the differences between the prenatal and postnatal parameters. Second, Akaike information criterion (AIC) was used to determine the number of database partition and optimal weightings for compensating the input parameters of the ANN model. Finally, minimum mean squared error (MMSE) mode was utilized to determine the optimal EFW. RESULTS: EFW of the proposed compensation model using AIC and MMSE showed mean absolute percent error of 5.1 ± 3.1% and mean absolute error of 158.9 ± 96.2 g. When comparing the accuracy of EFW, our model using AIC and MMSE was superior to those conventional EFW formulas (all p < 0.05). CONCLUSION: We proved that performing the parameter compensation (by AIC) and model compensations (by MMSE) for the ANN model can improve EFW accuracy. Our AIC-MMSE model of EFW will contribute to the improvement of accuracy when adding new US datasets measured by new operators.

The correlation between extracellular resistance by electrical biopsy and the ratio of optical low staining area in irradiated intestinal tissues of rats.

BACKGROUND: Electrical biopsy illustrates a tissue's electrical properties by electrical impedance spectroscopy. However, electrical biopsy parameters are different from conventional morphological-based examinations. The correlation between electrical biopsy and the morphological observation has not been checked. Considering the tissue responses to injury, extracellular resistance should be most sensitive with the accumulation of fluid in tissue, and it is expected to increase the ratio of optical low staining area on histological images. In this study, we calculated the ratio of optical low staining area of sampled histological images and compared with the results of electrical biopsy to verify the hypothesis of that the extracellular resistance of electrical biopsy most highly correlates with the ratio of optical low staining area on histological images. METHODS: The irradiated intestinal tissues of rats after different latent period were used for study. The sampled tissues were measured by electrical impedance spectroscopy for electrical biopsy and the microscopic images were acquired. The sampled histological images were transformed into the Hue-Saturation-Density (HSD) colour model to decouple the stain density. The ratio of optical low staining area on histological images was computed to quantify the morphological changes. The results were related to the parameters from electrical biopsy according to three element circuit model by Spearman's rank correlation test. RESULTS: The ratio of optical low staining area varied as well as the tissue's electrical parameters. The extracellular resistance (Re) and intracellular resistance (Ri) by electrical biopsy tended to increase with the ratio of low staining area decreasing. The membrane capacitance (Cm) by electrical biopsy tended to increase with the ratio of optical low staining area increasing. The extracellular resistance (Re) of electrical biopsy was the parameter most highly correlated with the ratio of optical low staining area with a correlation coefficient of -0.757 (p < 0.001). CONCLUSIONS: The results of this report confirm the hypothesis and support the idea that electrical biopsy results reflect the changes in tissues seen in conventional histological findings in a sense of conventional histological knowledge, and this approach may have a great potential for augmenting the pathological diagnosis of tissues.

Effects of paliperidone extended release on the symptoms and functioning of schizophrenia.

BACKGROUND: We aimed to explore relations between symptomatic remission and functionality evaluation in schizophrenia patients treated with paliperidone extended-release (ER), as seen in a normal day-to-day practice, using flexible dosing regimens of paliperidone ER. We explored symptomatic remission rate in patients treated with flexibly dosed paliperidone ER by 8 items of Positive and Negative Syndrome Scale (PANSS) and change of Personal and Social Performance (PSP) scale. METHOD: This was a 12-week multicenter, open-label, prospective clinical study conducted in in-patient and out-patient populations. Flexible dosing in the range 3-12 mg/day was used throughout the study. All subjects attended clinic visits on weeks 0, 4, 8, and 12 as usual clinical practice for the 12-week observation period. Data were summarized with respect to demographic and baseline characteristics, efficacy measurement with PANSS scale, PSP, and social functioning score, and safety observations. Descriptive statistics were performed to identify the retention rate at each visit as well as the symptomatic remission rate. Summary statistics of average doses the subjects received were based on all subjects participating in the study. RESULTS: A total of 480 patients were enrolled. Among them, 426 patients (88.8%) had evaluation at week 4 and 350 (72.9%) completed the 12-week evaluation. Patients with at least moderate severity of schizophrenia were evaluated as "mild" or better on PANSS scale by all 8 items after 12 weeks of treatment with paliperidone ER. There was significant improvement in patients' functionality as measured by PSP improvement and score changes. Concerning the other efficacy parameters, PANSS total scale, PSP total scale, and social functioning total scale at the end of study all indicated statistically significant improvement by comparison with baseline. The safety profile also demonstrated that paliperidone ER was well-tolerated without clinically significant changes after treatment administration. CONCLUSIONS: Although the short-term nature of this study may limit the potential for assessing improvements in function, it is noteworthy that in the present short-term study significant improvements in patient personal and social functioning with paliperidone ER treatment were observed, as assessed by PSP scale. TRIAL REGISTRATION: Clinical Trials. PAL-TWN-MA3.

Electrical biopsy of irradiated intestinal tissue with a simple electrical impedance spectroscopy system for radiation enteropathy in rats--a pilot study.

Electrical impedance is one of the most often used parameters for characterizing material properties, especially in biomedical applications. Electrical impedance spectroscopy (EIS), used for revealing both resistive and capacitive characteristics, is good for use in tissue characterization. In this study, a portable and simple EIS system based on a commercially available chip was used to assess rat intestinal tissues following irradiation. The EIS results were fitted to a resistor and capacitor electrical circuit model to solve the electrical properties of the tissue. The variation in the tissue's electrical characteristics was compared to the morphological and histological findings. From the experimental results, it was clear that the electrical properties, based on receiver operation curve analysis, demonstrated good detection performance relative to the histological changes. The electrical parameters of the tissues could be used to distinguish the tissue's status for investigation, which introduced a concept of 'electrical biopsy', and this 'electrical biopsy' approach may be used to complement histological examinations.