Tissue engineers and stem cell biologists have made exciting progress toward creating simplified models of human heart muscles or aligned monolayers to help bridge a longstanding gap between experimental animals and clinical trials. However, no existing human in vitro systems provide the direct measures of cardiac performance as a pump. Here, we developed a next-generation in vitro biomimetic model of pumping human heart chamber, and demonstrated its capability for pharmaceutical testing. From human pluripotent stem cell (hPSC)-derived ventricular cardiomyocytes (hvCM) embedded in collagen-based extracellular matrix hydrogel, we engineered a three-dimensional (3D) electro-mechanically coupled, fluid-ejecting miniature human ventricle-like cardiac organoid chamber (hvCOC). Structural characterization showed organized sarcomeres with myofibrillar microstructures. Transcript and RNA-seq analyses revealed upregulation of key Ca-handling, ion channel, and cardiac-specific proteins in hvCOC compared to lower-order 2D and 3D cultures of the same constituent cells. Clinically-important, physiologically complex contractile parameters such as ejection fraction, developed pressure, and stroke work, as well as electrophysiological properties including action potential and conduction velocity were measured: hvCOC displayed key molecular and physiological characteristics of the native ventricle, and showed expected mechanical and electrophysiological responses to a range of pharmacological interventions (including positive and negative inotropes). We conclude that such "human-heart-in-a-jar" technology could facilitate the drug discovery process by providing human-specific preclinical data during early stage drug development.

Objective To assess the potential association between prenatal use of antidepressants and the risk of attention-deficit/hyperactivity disorder (ADHD) in offspring. Design Population based cohort study. Setting Data from the Hong Kong population based electronic medical records on the Clinical Data Analysis and Reporting System. Participants 190 618 children born in Hong Kong public hospitals between January 2001 and December 2009 and followed-up to December 2015. Main outcome measure Hazard ratio of maternal antidepressant use during pregnancy and ADHD in children aged 6 to 14 years, with an average follow-up time of 9.3 years (range 7.4-11.0 years). Results Among 190 618 children, 1252 had a mother who used prenatal antidepressants. 5659 children (3.0%) were given a diagnosis of ADHD or received treatment for ADHD. The crude hazard ratio of maternal antidepressant use during pregnancy was 2.26 (P<0.01) compared with non-use. After adjustment for potential confounding factors, including maternal psychiatric disorders and use of other psychiatric drugs, the adjusted hazard ratio was reduced to 1.39 (95% confidence interval 1.07 to 1.82, P=0.01). Likewise, similar results were observed when comparing children of mothers who had used antidepressants before pregnancy with those who were never users (1.76, 1.36 to 2.30, P<0.01). The risk of ADHD in the children of mothers with psychiatric disorders was higher compared with the children of mothers without psychiatric disorders even if the mothers had never used antidepressants (1.84, 1.54 to 2.18, P<0.01). All sensitivity analyses yielded similar results. Sibling matched analysis identified no significant difference in risk of ADHD in siblings exposed to antidepressants during gestation and those not exposed during gestation (0.54, 0.17 to 1.74, P=0.30). Conclusions The findings suggest that the association between prenatal use of antidepressants and risk of ADHD in offspring can be partially explained by confounding by indication of antidepressants. If there is a causal association, the size of the effect is probably smaller than that reported previously.

BackgroundSpecialist services for the treatment of attention deficit hyperactivity disorder (ADHD) in adulthood in Hong Kong are yet to be developed. This study aims to explore the experiences of adolescents and young adults with ADHD in accessing treatment and services, coping with ADHD-related impairment, and their expectations of future treatment in Hong Kong.MethodQualitative interviews were conducted with a semi-structured guide. Forty young adult patients aged between 16 and 23 were included in the study. The interview recordings were transcribed verbatim and anonymised. Data were analysed with a thematic approach based on key principles of Grounded Theory.ResultsFour meta-themes were developed: Accessing ADHD diagnosis and treatment services; ADHD-related impairment; Experience of ADHD treatments; and Attitudes and expectations of future ADHD treatment. The role of parents and schools were highly significant in accessing services for patients diagnosed with ADHD in childhood. In general, ADHD affected every aspect of patients' lives including academic outcome, employment, family and social relationships. Medications were the principal treatment for ADHD amongst the interviewees and were reported to be generally effective. Half of the patients received non-pharmacological treatments in childhood but these effects were reported to be temporary. There was general consensus that the needs of patients with ADHD could not be met by the current service. In particular, there is a lack of specialist service for adults with ADHD, follow-up by different clinicians, and insufficient provision of non-pharmacological treatments.ConclusionThe findings suggest that further development of specialist ADHD services and non-pharmacological options for young adults are essential to meet their diverse needs with a holistic approach.

The objectives of the study were to utilize tumor size data from 10 Phase II/III atezolizumab studies across five solid tumor types to estimate tumor growth inhibition (TGI) metrics and assess the impact of TGI metrics and baseline prognostic factors on overall survival (OS) for each tumor type. TGI metrics were estimated from bi-exponential models and post-treatment longitudinal data of 6699 patients. TGI-OS full models were built using parametric survival regression by including all significant baseline covariates from the Cox univariate analysis, followed by a backward elimination step. The model performance was evaluated for each trial by simulating 1000 times OS distributions and hazard ratio (HR) of the atezolizumab-containing arms vs. respective controls.Tumor growth rate estimate (KG) was the most significant predictor of OS across all tumor types. Several baseline prognostic factors, such as inflammatory status (C-reactive protein, albumin, and/or neutrophil-to-lymphocyte ratio), tumor burden (sum of longest diameters, number of metastatic sites, and/or presence of liver metastases), Eastern Cooperative Oncology Group performance status and lactate dehydrogenase were also highly significant across multiple studies in the final multivariate models. TGI-OS models adequately described the OS distribution. The model-predicted HRs indicate good model performance across the 10 studies, with observed HRs within the 95% prediction intervals for all study arms vs. control.Multivariate TGI-OS models developed for different solid tumor types were able to predict treatment effect with various atezolizumab monotherapy or combination regimens and could be used to support design and analysis of future studies.

Traditional drug discovery is an inefficient process. Human pluripotent stem cell‐derived cardiomyocytes can potentially fill the gap between animal and clinical studies, but conventional two‐dimensional cultures inadequately recapitulate the human cardiac phenotype. Here, we systematically examined the pharmacological responses of engineered human ventricular‐like cardiac tissue strips (hvCTS) and organoid chambers (hvCOC) to 25 cardioactive compounds covering various drug classes. While hvCTS effectively detected negative and null inotropic effects, the sensitivity to positive inotropes was modest. We further quantified the predictive capacity of hvCTS in a blinded screening, with accuracies for negative, positive, and null inotropic effects at 100%, 86%, and 80%, respectively. Interestingly, hvCOC, with a pro‐maturation milieu that yields physiologically complex parameters, displayed enhanced positive inotropy. Based on these results, we propose a two‐tiered screening system for avoiding false positives and negatives. Such an approach would facilitate drug discovery by leading to better overall success.

SummaryAccurately predicting cardioactive effects of new molecular entities for therapeutics remains a daunting challenge. Immense research effort has been focused toward creating new screening platforms that utilize human pluripotent stem cell (hPSC)-derived cardiomyocytes and three-dimensional engineered cardiac tissue constructs to better recapitulate human heart function and drug responses. As these new platforms become increasingly sophisticated and high throughput, the drug screens result in larger multidimensional datasets. Improved automated analysis methods must therefore be developed in parallel to fully comprehend the cellular response across a multidimensional parameter space. Here, we describe the use of machine learning to comprehensively analyze 17 functional parameters derived from force readouts of hPSC-derived ventricular cardiac tissue strips (hvCTS) electrically paced at a range of frequencies and exposed to a library of compounds. A generated metric is effective for then determining the cardioactivity of a given drug. Furthermore, we demonstrate a classification model that can automatically predict the mechanistic action of an unknown cardioactive drug.

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This systematic review assesses the association between prenatal antidepressant exposure and risk of ADHD in children. Electronic databases were searched up to 25 July 2017. Observational studies examining this association were included in the review and meta-analysis was conducted where appropriate. Eight relevant studies were identified. The seven studies included in the meta-analysis comprised a total of 2,886,502 children. The pooled estimates comparing prenatal exposure to non-exposure showed an adjusted rate ratio (aRR) of 1.39 (95%CI 1.21-1.61). Similarly, an increased risk was found comparing previous antidepressant users and non-users: aRR = 1.56 (95%CI 1.25-1.95). The relationship between maternal psychiatric conditions and ADHD in children yielded an aRR of 1.90 (95%CI 1.47-2.45). Three studies conducted sibling-matched analyses with aRR of 0.94 (95%CI 0.75-1.16). These data suggest that the observed association between prenatal use of antidepressants and risk of ADHD in offspring can be partially explained by confounding by indication because the results from sibling-matched analyses do not support an increased risk of ADHD in discordant exposed siblings.