Systematic Synthesis of Tetrathia[8]circulenes: The Influence of Peripheral Substituents on the Structures and Properties in Solution and Solid States.

We developed the diversity-oriented approach for the synthesis of tetrathia[8]circulenes with a variety of peripheral substituents. Iridium-catalyzed direct C-H borylation of tetrathienylene provided 1,4,7,10-tetraboryltetrathienylene as a major product. 1,4,7,10-Tetraboryltetrathienylene served as an a key intermediate to achieve the selective synthesis of octasubstituted or tetrasubstituted tetrathia[8]circulenes via rhodium-catalyzed annulation with symmetric internal alkynes or sequential Sonogashira-Hagihara coupling and base-promoted intramolecular cyclization. A variety of substituents were installed at the peripheral positions of tetrathia[8]circulenes systematically. The self-assembling behavior of tetrathia[8]circulenes was investigated using 1H NMR and AFM measurements. The number and the chain length of alkyl groups exerted a significant influence on the aggregation ability and the crystal packing structures of tetrathia[8]circulenes in both solution and solid states. We also found that the molecular arrangement of the self-assembled tetrathia[8]circulene molecules affected the hole mobility assessed by the FP-TRMC method.

Synthesis of Tetrasilatetrathia[8]circulenes by a Fourfold Intramolecular Dehydrogenative Silylation of C-H Bonds.

The first two examples of a tetrasilatetrathia[8]circulene were synthesized in two steps from a tetraiodotetrathienylene by using a fourfold intramolecular dehydrogenative silylation of C-H bonds as the key step. A single-crystal X-ray diffraction analysis revealed that tetrasilatetrathia[8]circulene contains a perfectly planar [8]radialene skeleton. The excited-state dynamics of tetrasilatetrathia[8]circulene were evaluated by steady-state and time-resolved spectroscopic measurements, revealing an efficient intersystem crossing in the excited state.

Malposition of a pulmonary artery catheter in the left ventricle: a case report.

BACKGROUND: Placement of pulmonary artery catheters may be associated with a variety of complications. We present a case where a pulmonary artery catheter was accidentally advanced into the left ventricle by perforating the intraventricular septum. CASE PRESENTATION: A 73-year-old woman underwent mitral valve dysfunction. A pulmonary artery catheter could not pass the tricuspid valve under general anesthesia, which was manually advanced via the right ventricle during surgery. After valve replacement, systolic pulmonary artery pressure was higher than radial arterial blood pressure. Transesophageal echocardiography (TEE) revealed the tip of the catheter in the left ventricle. The catheter was withdrawn and then advanced to the pulmonary artery under monitoring of TEE. Transseptal shunt flow gradually decreased and finally disappeared. The surgery was completed without additional procedures. CONCLUSIONS: Although ventricular septal perforation is rare, it should be recognized as a potential complication of pulmonary artery catheter insertion.

Dementia Screening Based on SVM Using Qualitative Drawing Error of Clock Drawing Test.

In the welfare of the elderly, it is important to detect the signs of dementia at an early stage and prevent it from becoming serious. We evaluated the performance of SVM-based cognitive function classification models and investigated the drawing features that contribute to distinguishing the severity of cognitive functions. Clock drawing test (CDT) was conducted on three groups of elderly people with different degrees of cognitive impairment. Feature selection was applied to the qualitative drawing features of the CDT, and a two-class classification model was constructed using support vector machine. The results showed that the five features related to conceptual deficits and spatial and planning deficits could be used to classify the dementia group and healthy control group with 79 % accuracy, and all the features showed statistically significant differences. It is suggested that these qualitative drawing features of the CDT can be applied to dementia screening.

Improving Real-Time Brain State Classification of Motor Imagery Tasks During Neurofeedback Training.

In this study, we investigated the effect of the dynamic changes in brain activation during neurofeedback training in the classification of the different brain states associated with the target tasks. We hypothesized that ongoing activation patterns could change during neurofeedback session due to learning effects and, in the process, could affect the performance of brain state classifiers trained using data obtained prior to the session. Using a motor imagery paradigm, we then examined the application of an incremental training approach where classifiers were continuously updated in order to account for these activation changes. Our results confirmed our hypothesis that neurofeedback training could be associated with dynamic changes in brain activation characterized by an initially more widespread brain activation followed by a more focused and localized activation pattern. By continuously updating the trained classifiers after each feedback run, significant improvement in accurately classifying the different brain states associated with the target motor imagery tasks was achieved. These findings suggest the importance of taking into account brain activation changes during neurofeedback in order to provide more reliable and accurate feedback information to the participants, which is critical for an effective neurofeedback application.

Easy Screening for Mild Alzheimer's Disease and Mild Cognitive Impairment from Elderly Speech.

OBJECTIVE: This study presents a novel approach for early detection of cognitive impairment in the elderly. The approach incorporates the use of speech sound analysis, multivariate statistics, and data-mining techniques. We have developed a speech prosody-based cognitive impairment rating (SPCIR) that can distinguish between cognitively normal controls and elderly people with mild Alzheimer's disease (mAD) or mild cognitive impairment (MCI) using prosodic signals extracted from elderly speech while administering a questionnaire. Two hundred and seventy-three Japanese subjects (73 males and 200 females between the ages of 65 and 96) participated in this study. The authors collected speech sounds from segments of dialogue during a revised Hasegawa's dementia scale (HDS-R) examination and talking about topics related to hometown, childhood, and school. The segments correspond to speech sounds from answers to questions regarding birthdate (T1), the name of the subject's elementary school (T2), time orientation (Q2), and repetition of three-digit numbers backward (Q6). As many prosodic features as possible were extracted from each of the speech sounds, including fundamental frequency, formant, and intensity features and mel-frequency cepstral coefficients. They were refined using principal component analysis and/or feature selection. The authors calculated an SPCIR using multiple linear regression analysis. CONCLUSION: In addition, this study proposes a binary discrimination model of SPCIR using multivariate logistic regression and model selection with receiver operating characteristic curve analysis and reports on the sensitivity and specificity of SPCIR for diagnosis (control vs. MCI/mAD). The study also reports discriminative performances well, thereby suggesting that the proposed approach might be an effective tool for screening the elderly for mAD and MCI.

Improved Volitional Recall of Motor-Imagery-Related Brain Activation Patterns Using Real-Time Functional MRI-Based Neurofeedback.

Motor imagery (MI), a covert cognitive process where an action is mentally simulated but not actually performed, could be used as an effective neurorehabilitation tool for motor function improvement or recovery. Recent approaches employing brain-computer/brain-machine interfaces to provide online feedback of the MI during rehabilitation training have promising rehabilitation outcomes. In this study, we examined whether participants could volitionally recall MI-related brain activation patterns when guided using neurofeedback (NF) during training. The participants' performance was compared to that without NF. We hypothesized that participants would be able to consistently generate the relevant activation pattern associated with the MI task during training with NF compared to that without NF. To assess activation consistency, we used the performance of classifiers trained to discriminate MI-related brain activation patterns. Our results showed significantly higher predictive values of MI-related activation patterns during training with NF. Additionally, this improvement in the classification performance tends to be associated with the activation of middle temporal gyrus/inferior occipital gyrus, a region associated with visual motion processing, suggesting the importance of performance monitoring during MI task training. Taken together, these findings suggest that the efficacy of MI training, in terms of generating consistent brain activation patterns relevant to the task, can be enhanced by using NF as a mechanism to enable participants to volitionally recall task-related brain activation patterns.

Synthesis of Tetraaza[8]circulenes from Tetrathia[8]circulenes through an SNAr-Based Process.

The synthesis of highly planar tetraaza[8]circulenes from tetrathia[8]circulenes through oxidation followed by a nucleophilic aromatic substitution reaction with arylamines is presented. Photophysical and electrochemical properties of tetraaza[8]circulenes were investigated and compared to those of tetrathia[8]circulenes. The tetraaza[8]circulene exhibited bright fluorescence both in solution and solid states.

Detection of mild Alzheimer's disease and mild cognitive impairment from elderly speech: Binary discrimination using logistic regression.

In this research, we have developed a novel data-mining approach for detection of cognitive impairment, SPCIR (Speech Prosody-Based Cognitive Impairment Rating), which can discriminate between mild cognitive impairment and mild Alzheimer's disease from elderly using prosodic sign extracted from elderly speech during questionnaire test. This paper proposes a binary discrimination model of SPCIR using multivariate logistic regression and model selection using receiver operating characteristic (ROC) curve analysis, and reports the sensitivity and specificity of SPCIR for diagnosis (control; mild cognitive impairment/mild Alzheimer's disease).

Diversity-oriented synthesis of tetrathia[8]circulenes by sequential C-H borylation and annulation.

We have succeeded in the diversity-oriented synthesis of tetrathia[8]circulenes by sequential C-H borylation and annulation from cyclic tetrathiophene, and time-resolved microwave conductivity studies have proved that the intrinsic hole mobilities of tetrathia[8]circulenes are dependent on the chain length of the alkyl substituents at the peripheral positions.

Early detection of cognitive impairment in the elderly based on Bayesian mining using speech prosody and cerebral blood flow activation.

With the aim of providing computer aided diagnosis of dementia, we have developed a non-invasive screening system of the elderly with cognitive impairment. In our previous research, we have studied two data-mining approaches by focusing on speech-prosody and cerebral blood flow (CBF) activation during cognitive tests. On the power of these research results, this paper presents a prosody-CBF hybrid screening system of the elderly with cognitive impairment based on a Bayesian approach. The system is constructed by SPCIR (Speech Prosody-Based Cognitive Impairment Rating) based cutoff as the 1st screening, and, as the 2nd screening, two-phase Bayesian classifier for discriminating among elderly individuals with three clinical groups: elderly individuals with normal cognitive abilities (NC), patients with mild cognitive impairment (MCI), and Alzheimer's disease (AD). This paper also reports the screening examination and discusses the cost-effectiveness and the discrimination performance of the proposed system for early detection of cognitive impairment in elderly subjects.