Determining infectious cross-transmission events in healthcare settings involves manual surveillance of case clusters by infection control personnel, followed by strain typing of clinical/environmental isolates suspected in said clusters. Recent advances in genomic sequencing and cloud computing now allow for the rapid molecular typing of infecting isolates.

To facilitate rapid recognition of transmission clusters, we aimed to assess infection control surveillance using whole-genome sequencing (WGS) of microbial pathogens to identify cross-transmission events for epidemiologic review.

Clinical isolates of Staphylococcus aureus, Enterococcus faecium, Pseudomonas aeruginosa, and Klebsiella pneumoniae were obtained prospectively at an academic medical center, from September 1, 2016, to September 30, 2017. Isolate genomes were sequenced, followed by single-nucleotide variant analysis; a cloud-computing platform was used for whole-genome sequence analysis and cluster identification.

Most strains of the 4 studied pathogens were unrelated, and 34 potential transmission clusters were present. The characteristics of the potential clusters were complex and likely not identifiable by traditional surveillance alone. Notably, only 1 cluster had been suspected by routine manual surveillance.

Our work supports the assertion that integration of genomic and clinical epidemiologic data can augment infection control surveillance for both the identification of cross-transmission events and the inclusion of missed and exclusion of misidentified outbreaks (ie, false alarms). The integration of clinical data is essential to prioritize suspect clusters for investigation, and for existing infections, a timely review of both the clinical and WGS results can hold promise to reduce HAIs. A richer understanding of cross-transmission events within healthcare settings will require the expansion of current surveillance approaches.

UK Biobank is a well-characterised cohort of over 500 000 participants that offers unique opportunities to investigate multiple diseases and risk factors.

An online mental health questionnaire completed by UK Biobank participants was expected to expand the potential for research into mental disorders.

An expert working group designed the questionnaire, using established measures where possible, and consulting with a patient group regarding acceptability. Case definitions were defined using operational criteria for lifetime depression, mania, anxiety disorder, psychotic-like experiences and self-harm, as well as current post-traumatic stress and alcohol use disorders.

157 366 completed online questionnaires were available by August 2017. Comparison of self-reported diagnosed mental disorder with a contemporary study shows a similar prevalence, despite respondents being of higher average socioeconomic status than the general population across a range of indicators. Thirty-five per cent (55 750) of participants had at least one defined syndrome, of which lifetime depression was the most common at 24% (37 434). There was extensive comorbidity among the syndromes. Mental disorders were associated with high neuroticism score, adverse life events and long-term illness; addiction and bipolar affective disorder in particular were associated with measures of deprivation.

The questionnaire represents a very large mental health survey in itself, and the results presented here show high face validity, although caution is needed owing to selection bias. Built into UK Biobank, these data intersect with other health data to offer unparalleled potential for crosscutting biomedical research involving mental health.

G.B. received grants from the National Institute for Health Research during the study; and support from Illumina Ltd. and the European Commission outside the submitted work. B.C. received grants from the Scottish Executive Chief Scientist Office and from The Dr Mortimer and Theresa Sackler Foundation during the study. C.S. received grants from the Medical Research Council and Wellcome Trust during the study, and is the Chief Scientist for UK Biobank. M.H. received grants from the Innovative Medicines Initiative via the RADAR-CNS programme and personal fees as an expert witness outside the submitted work.

Although childhood adversity is a potent determinant of psychopathology, relatively little is known about how the characteristics of adversity exposure, including its developmental timing or duration, influence subsequent mental health outcomes. This study compared three models from life course theory (recency, accumulation, sensitive period) to determine which one(s) best explained this relationship.

Prospective data came from the Avon Longitudinal Study of Parents and Children (n = 7476). Four adversities commonly linked to psychopathology (caregiver physical/emotional abuse; sexual/physical abuse; financial stress; parent legal problems) were measured repeatedly from birth to age 8. Using a statistical modeling approach grounded in least angle regression, we determined the theoretical model(s) explaining the most variability (r2) in psychopathology symptoms measured at age 8 using the Strengths and Difficulties Questionnaire and evaluated the magnitude of each association.

Recency was the best fitting theoretical model for the effect of physical/sexual abuse (girls r2 = 2.35%; boys r2 = 1.68%). Both recency (girls r2 = 1.55%) and accumulation (boys r2 = 1.71%) were the best fitting models for caregiver physical/emotional abuse. Sensitive period models were chosen alone (parent legal problems in boys r2 = 0.29%) and with accumulation (financial stress in girls r2 = 3.08%) more rarely. Substantial effect sizes were observed (standardized mean differences = 0.22–1.18).

Child psychopathology symptoms are primarily explained by recency and accumulation models. Evidence for sensitive periods did not emerge strongly in these data. These findings underscore the need to measure the characteristics of adversity, which can aid in understanding disease mechanisms and determining how best to reduce the consequences of exposure to adversity.

Internet cognitive–behavioural therapy (iCBT) for panic disorder of up to 10 lessons is well established. The utility of briefer programmes is unknown.

To determine the efficacy and effectiveness of a five-lesson iCBT programme for panic disorder.

Study 1 (efficacy): Randomised controlled trial comparing active iCBT (n=27) and waiting list control participants (n=36) on measures of panic severity and comorbid symptoms. Study 2 (effectiveness): 330 primary care patients completed the iCBT programme under the supervision of primary care practitioners.

iCBT was significantly more effective than waiting list control in reducing panic (g=0.97, 95% CI 0.34 to 1.61), distress (g=0.92, 95% CI 0.28 to 1.55), disability (g=0.81, 95% CI 0.19 to 1.44) and depression (g=0.79, 95% CI 0.17 to 1.41), and gains were maintained at 3 months post-treatment (iCBT group). iCBT remained effective in primary care, but lower completion rates were found (56.1% in study 2 v. 63% in study 1). Adherence appeared to be related to therapist contact.

The five-lesson Panic Program has utility for treating panic disorder, which translates to primary care. Adherence may be enhanced with therapist contact.

Low birth weight has been inconsistently associated with risk of developing affective disorders, including major depressive disorder (MDD). To date, studies investigating possible associations between birth weight and bipolar disorder (BD), or personality traits known to predispose to affective disorders such as neuroticism, have not been conducted in large cohorts.

To assess whether very low birth weight (<1500 g) and low birth weight (1500–2490 g) were associated with higher neuroticism scores assessed in middle age, and lifetime history of either MDD or BD. We controlled for possible confounding factors.

Retrospective cohort study using baseline data on the 83 545 UK Biobank participants with detailed mental health and birth weight data. Main outcomes were prevalent MDD and BD, and neuroticism assessed using the Eysenck Personality Inventory Neuroticism scale - Revised (EPIN-R)

Referent to normal birth weight, very low/low birth weight were associated with higher neuroticism scores, increased MDD and BD. The associations between birth weight category and MDD were partially mediated by higher neuroticism.

These findings suggest that intrauterine programming may play a role in lifetime vulnerability to affective disorders.