Social Capital in Boston: Findings From the Social Capital Community Benchmark Survey

Highlights survey findings on the ways in which Bostonians connect and how these social networks benefit the entire community. Ranks community involvement in Boston, including politics, activism in the arts, and tolerance, among forty sites nationwide

The role of dopamine in the accumbens core in the expression of Pavlovian‐conditioned responses

The role of dopamine in reward is a topic of debate. For example, some have argued that phasic dopamine signaling provides a prediction‐error signal necessary for stimulus–reward learning, whereas others have hypothesized that dopamine is not necessary for learning per se , but for attributing incentive motivational value (‘incentive salience’) to reward cues. These psychological processes are difficult to tease apart, because they tend to change together. To disentangle them we took advantage of natural individual variation in the extent to which reward cues are attributed with incentive salience, and asked whether dopamine (specifically in the core of the nucleus accumbens) is necessary for the expression of two forms of Pavlovian‐conditioned approach behavior – one in which the cue acquires powerful motivational properties (sign‐tracking) and another closely related one in which it does not (goal‐tracking). After acquisition of these conditioned responses (CRs), intra‐accumbens injection of the dopamine receptor antagonist flupenthixol markedly impaired the expression of a sign‐tracking CR, but not a goal‐tracking CR. Furthermore, dopamine antagonism did not produce a gradual extinction‐like decline in behavior, but maximally impaired expression of a sign‐tracking CR on the very first trial, indicating the effect was not due to new learning (i.e. it occurred in the absence of new prediction‐error computations). The data support the view that dopamine in the accumbens core is not necessary for learning stimulus–reward associations, but for attributing incentive salience to reward cues, transforming predictive conditional stimuli into incentive stimuli with powerful motivational properties. Ongoing debate exists about dopamine’s exact role in reward‐related processes. We took advantage of natural individual variation in the degree to which reward cues are attributed with motivational value, and asked whether dopamine in the core of the nucleus accumbens is necessary for the performance of two forms of Pavlovian conditioned approach behavior ‐ one in which the cue acquires powerful motivational properties (sign‐tracking) and another related one in which it does not (goal‐tracking). We found that blocking dopamine transmission within the core impaired the expression of sign‐tracking responses, but not goal‐tracking responses.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93510/1/j.1460-9568.2012.08217.x.pd

Detecting early signs of depressive and manic episodes in patients with bipolar disorder using the signature-based model

Recurrent major mood episodes and subsyndromal mood instability cause substantial disability in patients with bipolar disorder. Early identification of mood episodes enabling timely mood stabilisation is an important clinical goal. Recent technological advances allow the prospective reporting of mood in real time enabling more accurate, efficient data capture. The complex nature of these data streams in combination with challenge of deriving meaning from missing data mean pose a significant analytic challenge. The signature method is derived from stochastic analysis and has the ability to capture important properties of complex ordered time series data. To explore whether the onset of episodes of mania and depression can be identified using self-reported mood data.Comment: 12 pages, 3 tables, 10 figure

Deriving information from missing data: implications for mood prediction

The availability of mobile technologies has enabled the efficient collection prospective longitudinal, ecologically valid self-reported mood data from psychiatric patients. These data streams have potential for improving the efficiency and accuracy of psychiatric diagnosis as well predicting future mood states enabling earlier intervention. However, missing responses are common in such datasets and there is little consensus as to how this should be dealt with in practice. A signature-based method was used to capture different elements of self-reported mood alongside missing data to both classify diagnostic group and predict future mood in patients with bipolar disorder, borderline personality disorder and healthy controls. The missing-response-incorporated signature-based method achieves roughly 66\% correct diagnosis, with f1 scores for three different clinic groups 59\% (bipolar disorder), 75\% (healthy control) and 61\% (borderline personality disorder) respectively. This was significantly more efficient than the naive model which excluded missing data. Accuracies of predicting subsequent mood states and scores were also improved by inclusion of missing responses. The signature method provided an effective approach to the analysis of prospectively collected mood data where missing data was common and should be considered as an approach in other similar datasets

Learning to Detect Bipolar Disorder and Borderline Personality Disorder with Language and Speech in Non-Clinical Interviews

Bipolar disorder (BD) and borderline personality disorder (BPD) are both chronic psychiatric disorders. However, their overlapping symptoms and common comorbidity make it challenging for the clinicians to distinguish the two conditions on the basis of a clinical interview. In this work, we first present a new multi-modal dataset containing interviews involving individuals with BD or BPD being interviewed about a non-clinical topic . We investigate the automatic detection of the two conditions, and demonstrate a good linear classifier that can be learnt using a down-selected set of features from the different aspects of the interviews and a novel approach of summarising these features. Finally, we find that different sets of features characterise BD and BPD, thus providing insights into the difference between the automatic screening of the two conditions

Flexural fatigue behavior of rocking bioreactor films

The fields of biopharmaceutical processing and cell therapy are adopting single-use, closed systems throughout their workflows to enhance sterility, minimize waste wash effluent and enable manufacturing flexibility compared to traditional stainless steel bioreactors. One of the key single-use technologies in use is the rocking bioreactor, comprising a polymer film bag (outfitted with ports and sensors) mounted to a tray capable of mixing the contents of the bag and a control system (controlling temperature, agitation, and potentially media perfusion). One of the challenges encountered in rocking bioreactor bags is the fact that upon inflation/filling with media, the originally flat bioreactor bags often develop folds and dimples due to their inflated geometry. These deformations tend to be inconsequential at small volumes and low agitation rates/times, but can lead to flex fatigue failures such as whitening, delamination and through-cracking under more extreme conditions. In practice, these failures are dependent on a number of factors including bag material and volume, mounting geometry, rocking angle and rate, and the duration of culture, making a systematic study of the material properties controlling this behavior difficult and time-consuming. Several flex fatigue testing systems exist in the literature, including Gelbo and Sonntag-Universal, but none of these effectively model the unique geometry and stresses of the rocking bioreactor geometry. To this end, we have developed accelerated test methods to analyze the flexural fatigue behavior of multilayer rocking bioreactor films. These methods enable quality control testing of film lots, and have the potential to compare different film compositions with a rapid and reproducible test, thereby facilitating development of new films. Our test method models the local geometry surrounding the fold/dimple in a rocking bioreactor in a small sample of film, and cycles the sample to accelerate flexural fatigue at the dimple site. Initial results indicate the ability to accelerate film failure from tens of days on a rocking bioreactor platform (using a full bioreactor bag) to tens of hours using less than ten square inches of film. We will discuss the effects of various experimental parameters on film failure, optimization of test procedures and correlation with rocking bioreactor testing in the field

Identifying psychiatric diagnosis from missing mood data through the use of log-signature features

The availability of mobile technologies has enabled the efficient collection of prospective longitudinal, ecologically valid self-reported clinical questionnaires from people with psychiatric diagnoses. These data streams have potential for improving the efficiency and accuracy of psychiatric diagnosis as well predicting future mood states enabling earlier intervention. However, missing responses are common in such datasets and there is little consensus as to how these should be dealt with in practice. In this study, the missing-response-incorporated log-signature method achieves roughly 74.8% correct diagnosis, with f1 scores for three diagnostic groups 66% (bipolar disorder), 83% (healthy control) and 75% (borderline personality disorder) respectively. This was superior to the naive model which excluded missing data and advanced models which implemented different imputation approaches, namely, k-nearest neighbours (KNN), probabilistic principal components analysis (PPCA) and random forest-based multiple imputation by chained equations (rfMICE). The log-signature method provided an effective approach to the analysis of prospectively collected mood data where missing data was common and should be considered as an approach in other similar datasets. Because of treating missing responses as a signal, its superiority also highlights that missing data conveys valuable clinical information

Facilitating Patient Recruitment Process for Research

Introduction The Assessing outcomes of enhanced Chronic disease Care through patient Education and a value-based formulary Study (ACCESS) conducted from the University of Calgary trial is seeking 4700 low-income Albertans over the age of 65 years at high risk for cardiovascular morbidity and mortality. Recruitment efforts using advertising, conventional methods including posters and brochures in pharmacies have been challenging. The use of admail was attempted but fewer than 260 people (out of nearly 122,000 letters mailed) were enrolled. Objectives and Approach The objective was to determine if linking data collected by Alberta Health Service (AHS) could identify eligible patients and facilitate recruitment for the study. We extracted cohorts of data based ICD codes. These patient’s data were linked with Admission, Discharge and Transfer (ADT) and Master Patient Index (MPI) data to pull patient’s names, addresses and postal codes. Deceased and previously contacted patients were eliminated. The final patient name-list from the Analytics team was merged with a notification letter from Research Administration and sent by the data communication team to candidate patients. Interested patients contacted the researchers. Once informed consent was obtained, the data communication team sent the study questionnaire to the patients directly. Results 30,343 eligible patients were identified in Calgary and 23,305 in Edmonton. Out of 13825 people contacted, 304 people were enrolled into the study – a significantly higher rate than using other mail-based methods. Conclusion/Implications By linking various health administrative data, we assisted researchers to identify potential participants who would otherwise be inaccessible and geographically dispersed across Alberta. This effectively facilitated the recruitment process and enabled patients from across the province to participate with minimal investments

Plant Volatiles, Rather than Light, Determine the Nocturnal Behavior of a Caterpillar

Although many organisms show daily rhythms in their activity patterns, the mechanistic causes of these patterns are poorly understood. Here we show that host plant volatiles affect the nocturnal behavior of the caterpillar Mythimna separata. Irrespective of light status, the caterpillars behaved as if they were in the dark when exposed to volatiles emitted from host plants (either uninfested or infested by conspecific larvae) in the dark. Likewise, irrespective of light status, the caterpillars behaved as if they were in the light when exposed to volatiles emitted from plants in the light. Caterpillars apparently utilize plant volatile information to sense their environment and modulate their daily activity patterns, thereby potentially avoiding the threat of parasitism