Arterial stiffness is a major contributor to cardiovascular diseases. Because current methods of measuring arterial stiffness are technically demanding, the purpose of this study was to develop a simple method of evaluating arterial stiffness using oscillometric blood pressure measurement. Blood pressure was conventionally measured in the left upper arm of 173 individuals using an inflatable cuff. Using the time series of occlusive cuff pressure and the amplitudes of pulse oscillations, we calculated local slopes of the curve between the decreasing cuff pressure and corresponding arterial volume. Whole pressure-volume curve was derived from numerical integration of the local slopes. The curve was fitted using an equation and we identified a numerical coefficient of the equation as an index of arterial stiffness (Arterial Pressure-volume Index, API). We also measured brachial-ankle (baPWV) PWV and carotid-femoral (cfPWV) PWV using a vascular testing device and compared the values with API. Furthermore, we assessed carotid arterial compliance using ultrasound images to compare with API. The slope of the calculated pressure-volume curve was steeper for compliant (low baPWV or cfPWV) than stiff (high baPWV or cfPWV) arteries. API was related to baPWV (r = -0.53, P < 0.05), cfPWV (r = -0.49, P < 0.05), and carotid arterial compliance (r = 0.32, P < 0.05). A stepwise multiple regression analysis demonstrated that baPWV and carotid arterial compliance were the independent determinants of API, and that API was the independent determinant of baPWV and carotid arterial compliance. These results suggest that our method can simply and simultaneously evaluate arterial stiffness and blood pressure based on oscillometric measurements of blood pressure.

Patients affected by Attention-Deficit/Hyperactivity Disorder (ADHD) are characterized by impaired executive functioning and/or attention deficits. Our study aim is to determine whether the outcomes measured by the Attention Network Task (ANT), i.e., the reaction times (RTs) to specific target and cue conditions and alerting, orienting, and conflict (or executive control) effects are affected by cognitive training with a Dual n-back task. We considered three groups of young adult participants: ADHD patients without medication (ADHD), ADHD with medication (MADHD), and age/education-matched controls. Working memory training consisted of a daily practice of 20 blocks of Dual n-back task (approximately 30 min per day) for 20 days within one month. Participants of each group were randomly assigned into two subgroups, the first one with an adaptive mode of difficulty (adaptive training), while the second was blocked at the level 1 during the whole training phase (1-back task, baseline training). Alerting and orienting effects were not modified by working memory training. The dimensional analysis showed that after baseline training, the lesser the severity of the hyperactive-impulsive symptoms, the larger the improvement of reaction times on trials with high executive control/conflict demand (i.e., what is called Conflict Effect), irrespective of the participants’ group. In the categorical analysis, we observed the improvement in such Conflict Effect after the adaptive training in adult ADHD patients irrespective of their medication, but not in controls. The ex-Gaussian analysis of RT and RT variability showed that the improvement in the Conflict Effect correlated with a decrease in the proportion of extreme slow responses. The Dual n-back task in the adaptive mode offers as a promising candidate for a cognitive remediation of adult ADHD patients without pharmaceutical medication.

Physiome.jp (http://physiome.jp) is a portal site inaugurated in 2007 to support model-based research in physiome and systems biology. At Physiome.jp, several tools and databases are available to support construction of physiological, multi-hierarchical, large-scale models. There are three databases in Physiome.jp, housing mathematical models, morphological data, and time-series data. In late 2013, the site was fully renovated, and in May 2015, new functions were implemented to provide information infrastructure to support collaborative activities for developing models and performing simulations within the database framework. This article describes updates to the databases implemented since 2013, including cooperation among the three databases, interactive model browsing, user management, version management of models, management of parameter sets, and interoperability with applications.

The utility of big data in spontaneous adverse drug reactions (ADRs) reporting systems has improved the pharmacovigilance process. However, identifying culprit drugs in ADRs remains challenging, although it is one of the foremost steps to managing ADRs. Aiming to estimate the likelihood of prescribed drugs being culprit drugs for given ADRs, we devised a Bayesian estimation model based on the Japanese Adverse Drug Events Reports database. After developing the model, a validation study was conducted with 67 ADR reports with a gross of 1,387 drugs (67 culprit drugs and 1,320 concomitant drugs) prescribed and recorded at Yamaguchi University Hospital. As a result, the model estimated a culprit drug of ADRs with acceptable accuracy (area under the receiver operating characteristic curve 0.93 (95% confidence interval 0.88–0.97)). The estimation results provided by the model to healthcare practitioners can be used as one clue to determine the culprit drugs for various ADRs, which will improve the management of ADRs by shortening the treatment turnaround time and increasing the precision of diagnosis, leading to minimizing the adverse effects on patients.

Background: The efficacy of antifibrotic agents in idiopathic pulmonary fibrosis (IPF) has been demonstrated and early introduction is recommended, especially in patients with preserved performance status (PS). We aimed to determine the proportion of untreated IPF cases using real-world data and to assess the factors associated with non-intervention. Methods: A prospective observational study using questionnaires was performed on 518 patients with interstitial lung disease (ILD) and their attending physicians who visited a clinic, general hospital, or tertiary respiratory center between December 2019 and October 2020. Patients responded with subjective symptoms and PS, whereas physicians responded with diagnosis, treatment, and reasons for their treatment choices. Principal component analysis (PCA) was performed using age, sex, BMI, medical facility, specialized tests, and symptom severity. Results: We included 207 patients with IPF. Among them, 168 has a good PS (<= 2), which could be indicative of treatment; 130 (77.4%) were not treated with antifibrotic agents. The PCA revealed a trend consistent with that of antifibrotic agent therapy and the distribution of medical facilities, with a treatment intervention rate of 16% in general hospitals and 62% in tertiary respiratory centers. In general hospitals, low symptom severity (PS, mMRC, and no use of long-term oxygen therapy) was a relevant factor for non-intervention with antifibrotic agents (p < 0.001). Conclusion: Antifibrotic treatment interventions varied by facility in cases with good PS. Patients with milder symptoms are not being treated early in general hospitals and more collaboration between general hospitals and specialized facilities is necessary.