Elevated amygdala responses to emotional faces in youths with chronic irritability or bipolar disorder

AbstractA major controversy in child psychiatry is whether bipolar disorder (BD) presents in children as severe, non-episodic irritability (operationalized here as severe mood dysregulation, SMD), rather than with manic episodes as in adults. Both classic, episodic BD and SMD are severe mood disorders characterized by deficits in processing emotional stimuli. Neuroimaging techniques can be used to test whether the pathophysiology mediating these deficits are similar across the two phenotypes. Amygdala dysfunction during face emotion processing is well-documented in BD, but little is known about amygdala dysfunction in chronically irritable youth. We compared neural activation in SMD (n=19), BD (n=19), and healthy volunteer (HV; n=15) youths during an implicit face-emotion processing task with angry, fearful and neutral expressions. In the right amygdala, both SMD and BD exhibited greater activity across all expressions than HV. However, SMD and BD differed from each other and HV in posterior cingulate cortex, posterior insula, and inferior parietal lobe. In these regions, only SMD showed deactivation in response to fearful expressions, whereas only BD showed deactivation in response to angry expressions. Thus, during implicit face emotion processing, youth with BD and those with SMD exhibit similar amygdala dysfunction but different abnormalities in regions involved in information monitoring and integration

Clinical essentialising: a qualitative study of doctors’ medical and moral practice

While certain substantial moral dilemmas in health care have been given much attention, like abortion, euthanasia or gene testing, doctors rarely reflect on the moral implications of their daily clinical work. Yet, with its aim to help patients and relieve suffering, medicine is replete with moral decisions. In this qualitative study we analyse how doctors handle the moral aspects of everyday clinical practice. About one hundred consultations were observed, and interviews conducted with fifteen clinical doctors from different practices. It turned out that the doctors’ approach to clinical cases followed a rather strict pattern across specialities, which implied transforming patients’ diverse concerns into specific medical questions through a process of ‘essentialising’: Doctors broke the patient’s story down, concretised the patient’s complaints and categorised the symptoms into a medical sense. Patients’ existential meanings were removed, and the focus placed on the patients’ functioning. By essentialising, doctors were able to handle a complex and ambiguous reality, and establish a medically relevant problem. However, the process involved a moral as well as a practical simplification. Overlooking existential meanings and focusing on purely functional aspects of patients was an integral part of clinical practice and not an individual flaw. The study thus questions the value of addressing doctors’ conscious moral evaluations. Yet doctors should be aware that their daily clinical work systematically emphasises beneficence at the expense of others—that might be more important to the patient

Performing television history

An expanded conception of performance study can disturb current theoretical and historical assumptions about television’s medial identity. The article considers how to write histories of the dominant forms and assumptions about performance in British and American television drama, and analyses how acting is situated in relation to the multiple meaning-making components of television. A longitudinal, wide-ranging analysis is briefly sketched to show that the concept of performance, from acting to the display of television’s mediating capability, can extend to the analysis of how the television medium ‘performed’ its own identity to shape its distinctiveness in specific historical circumstances

Suitability Of Nitisinone In Alkaptonuria 1 (SONIA 1): an international, multicentre, randomised, open-label, no-treatment controlled, parallel-group, dose-response study to investigate the effect of once daily nitisinone on 24-h urinary homogentisic acid excretion in patients with alkaptonuria after 4 weeks of treatment.

BACKGROUND: Alkaptonuria (AKU) is a serious genetic disease characterised by premature spondyloarthropathy. Homogentisate-lowering therapy is being investigated for AKU. Nitisinone decreases homogentisic acid (HGA) in AKU but the dose-response relationship has not been previously studied. METHODS: Suitability Of Nitisinone In Alkaptonuria 1 (SONIA 1) was an international, multicentre, randomised, open-label, no-treatment controlled, parallel-group, dose-response study. The primary objective was to investigate the effect of different doses of nitisinone once daily on 24-h urinary HGA excretion (u-HGA24) in patients with AKU after 4 weeks of treatment. Forty patients were randomised into five groups of eight patients each, with groups receiving no treatment or 1 mg, 2 mg, 4 mg and 8 mg of nitisinone. FINDINGS: A clear dose-response relationship was observed between nitisinone and the urinary excretion of HGA. At 4 weeks, the adjusted geometric mean u-HGA24 was 31.53 mmol, 3.26 mmol, 1.44 mmol, 0.57 mmol and 0.15 mmol for the no treatment or 1 mg, 2 mg, 4 mg and 8 mg doses, respectively. For the most efficacious dose, 8 mg daily, this corresponds to a mean reduction of u-HGA24 of 98.8% compared with baseline. An increase in tyrosine levels was seen at all doses but the dose-response relationship was less clear than the effect on HGA. Despite tyrosinaemia, there were no safety concerns and no serious adverse events were reported over the 4 weeks of nitisinone therapy. CONCLUSIONS: In this study in patients with AKU, nitisinone therapy decreased urinary HGA excretion to low levels in a dose-dependent manner and was well tolerated within the studied dose range. TRIAL REGISTRATION NUMBER: EudraCT number: 2012-005340-24. Registered at ClinicalTrials.gov: NCTO1828463

Seasonal malaria chemoprevention packaged with malnutrition prevention in northern Nigeria: A pragmatic trial (SMAMP study) with nested case-control.

Integrating seasonal malaria chemoprevention (SMC), recommended by the WHO since 2012 to prevent malaria infection, with nutrition interventions may improve health outcomes and operational efficiencies. This study assessed the effects of co-packaging interventions on distribution coverage, nutrition, and clinical malaria outcomes in northern Nigeria. From August to November 2014, community volunteers delivered sulfadoxine-pyrimethamine and amodiaquine (SP-AQ) door-to-door each month to approximately 7,000 children aged 6-24 months in seven wards of Madobi, Kano State, Nigeria. In three of the wards children additionally received a lipid-based nutrient supplement (LNS-medium quantity), Plumpy Doz. Coverage, adherence, and anthropometric outcomes were assessed through baseline, midline, and endline household surveys. A facility-based case-control study was also conducted to estimate impact on clinical malaria outcomes. Coverage of SP-AQ was similar between arms at 89% (n = 2,409 child-months [88-90%]) in the SP-AQ only arm and 90% (n = 1,947 child-months [88-92%]) in the SP-AQ plus LNS arm (p = 0.52). Coverage of LNS was 83% (n = 2,409 child-months [81-84%]). Whilst there were marked changes in anthropometric status between baseline, midline and endline, these were largely accounted for by socioeconomic status and must be interpreted with care due to possible measurement issues, especially length-based indices. Overall nutritional status of our most robust measure, weight-for-age, does appear to have improved by endline, but was similar in the two study arms, suggesting no additional benefit of the LNS. While the odds of clinical malaria among those who received the intended intervention were lower in each study arm compared to children who did not receive interventions (SP-AQ only OR = 0.23 [0.09-0.6]; SP-AQ plus LNS OR = 0.22 [0.09-0.55]), LNS was not shown to have an additional impact. Coverage of SMC was high regardless of integrating LNS delivery into the SMC campaign. Supplementation with LNS did not appear to impact nutritional outcomes, but appeared to enhance the impact of SP-AQ on clinical odds of malaria. These results indicate that combining nutritional interventions with seasonal malaria chemoprevention in high-risk areas can be done successfully, warranting further exploration with other products or dosing. Trial Registration: ISRCTN 11413895

Probabilistic Programming

Probabilistic programs are usual functional or imperative programs with two added constructs: (1) the ability to draw values at random from distributions, and (2) the ability to condition values of variables in a program via observations. Models from diverse application areas such as computer vision, coding theory, cryptographic protocols, biology and reliability analysis can be written as probabilistic programs. Probabilistic inference is the problem of computing an explicit representation of the probability distribution implicitly specified by a probabilistic program. Depending on the application, the desired output from inference may vary-we may want to estimate the expected value of some function f with respect to the distribution, or the mode of the distribution, or simply a set of samples drawn from the distribution. In this paper, we describe connections this research area called \Probabilistic Programming" has with programming languages and software engineering, and this includes language design, and the static and dynamic analysis of programs. We survey current state of the art and speculate on promising directions for future research

Probabilistic machine learning and artificial intelligence.

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.The author acknowledges an EPSRC grant EP/I036575/1, the DARPA PPAML programme, a Google Focused Research Award for the Automatic Statistician and support from Microsoft Research.This is the author accepted manuscript. The final version is available from NPG at http://www.nature.com/nature/journal/v521/n7553/full/nature14541.html#abstract