Leukoaraiosis, or white matter rarefaction, is a common imaging finding in aging and is presumed to reflect vascular disease. When severe in presentation, potential congenital or acquired etiologies are investigated, prompting referral for neuropsychological evaluation in addition to neuroimaging. T2-weighted imaging is the most common magnetic resonance imaging (MRI) approach to identifying white matter disease. However, more advanced diffusion MRI techniques may provide additional insight into mechanisms that influence the abnormal T2 signal, especially when clinical presentations are discrepant with imaging findings.

We present a case of a 74-year-old woman with severe leukoaraoisis. She was examined by a neurologist, neuropsychologist, and rheumatologist, and completed conventional (T1, T2-FLAIR) MRI, diffusion tensor imaging (DTI), and advanced single-shell, high b-value diffusion MRI (i.e., fiber ball imaging [FBI]).

The patient was found to have few neurological signs, no significant cognitive impairment, a negative workup for leukoencephalopathy, and a positive antibody for Sjogren’s disease for which her degree of leukoaraiosis would be highly atypical. Tractography results indicate intact axonal architecture that was better resolved using FBI rather than DTI.

This case illustrates exceptional cognitive resilience in the face of severe leukoaraiosis and the potential for advanced diffusion MRI to identify brain reserve.

Implementation of genome-scale sequencing in clinical care has significant challenges: the technology is highly dimensional with many kinds of potential results, results interpretation and delivery require expertise and coordination across multiple medical specialties, clinical utility may be uncertain, and there may be broader familial or societal implications beyond the individual participant. Transdisciplinary consortia and collaborative team science are well poised to address these challenges. However, understanding the complex web of organizational, institutional, physical, environmental, technologic, and other political and societal factors that influence the effectiveness of consortia is understudied. We describe our experience working in the Clinical Sequencing Evidence-Generating Research (CSER) consortium, a multi-institutional translational genomics consortium.

A key aspect of the CSER consortium was the juxtaposition of site-specific measures with the need to identify consensus measures related to clinical utility and to create a core set of harmonized measures. During this harmonization process, we sought to minimize participant burden, accommodate project-specific choices, and use validated measures that allow data sharing.

Identifying platforms to ensure swift communication between teams and management of materials and data were essential to our harmonization efforts. Funding agencies can help consortia by clarifying key study design elements across projects during the proposal preparation phase and by providing a framework for data sharing data across participating projects.

In summary, time and resources must be devoted to developing and implementing collaborative practices as preparatory work at the beginning of project timelines to improve the effectiveness of research consortia.

The effect of minor orthopaedic day surgery (MiODS) on patient’s mood.

A prospective population-based cohort study of 148 consecutive patients with age above 18 and less than 65, an American Society of Anaesthesiology (ASA) score of 1, and the requirement of general anaesthesia (GA) were included. The Medical Outcomes Study – Short Form 36 (SF-36), Beck Anxiety Inventory (BAI) and Beck Depression Inventory (BDI) were used pre- and post-operatively.

The mean physical component score of SF-36 before surgery was 45.3 (SD = ±10.1) and 8 weeks following surgery was 44.9 (SD = ±11.04) [n = 148, p = 0.51, 95% CI = (−1.03 to 1.52)]. For the measurement of the changes in mood using BDI, BAI and SF-36, latent construct modelling was employed to increase validity. The covariance between mood pre- and post-operatively (cov = 69.44) corresponded to a correlation coefficient, r = 0.88 indicating that patients suffering a greater number of mood symptoms before surgery continue to have a greater number of symptoms following surgery. When the latent mood constructs were permitted to have different means the model fitted well with χ2 (df = 1) = 0.86 for which p = 0.77, thus the null hypothesis that MiODS has no effect on patient mood was rejected.

MiODS affects patient mood which deteriorates at 8 weeks post-operatively regardless of the pre-operative patient mood state. More importantly patients suffering a greater number of mood symptoms before MiODS continue to have a greater number of symptoms following surgery.

Cardiovascular risk prediction tools are important for cardiovascular disease (CVD) prevention, however, which algorithms are appropriate for people with severe mental illness (SMI) is unclear.

To determine the cost-effectiveness using the net monetary benefit (NMB) approach of two bespoke SMI-specific risk algorithms compared to standard risk algorithms for primary CVD prevention in those with SMI, from an NHS perspective.

A microsimulation model was populated with 1000 individuals with SMI from The Health Improvement Network Database, aged 30–74 years without CVD. Four cardiovascular risk algorithms were assessed; (1) general population lipid, (2) general population BMI, (3) SMI-specific lipid and (4) SMI-specific BMI, compared against no algorithm. At baseline, each cardiovascular risk algorithm was applied and those high-risk (> 10%) were assumed to be prescribed statin therapy, others received usual care. Individuals entered the model in a ‘healthy’ free of CVD health state and with each year could retain their current health state, have cardiovascular events (non-fatal/fatal) or die from other causes according to transition probabilities.

The SMI-specific BMI and general population lipid algorithms had the highest NMB of the four algorithms resulting in 12 additional QALYs and a cost saving of approximately £37,000 (US$ 58,000) per 1000 patients with SMI over 10 years.

The general population lipid and SMI-specific BMI algorithms performed equally well. The ease and acceptability of use of a SMI-specific BMI algorithm (blood tests not required) makes it an attractive algorithm to implement in clinical settings.

The authors have not supplied their declaration of competing interest.

Osteoporosis was not a public health concern in black South African (SA) women, until recently when it was reported that the prevalence of vertebral fractures was 9.1% in black compared to 5.0% in white SA women. Accordingly, this study aimed to measure bone mineral density (BMD) of older black SA women and to investigate its association with risk factors for osteoporosis, including strength, muscle and fat mass, dietary intake and objectively measured physical activity (PA).

Older black SA women (age, 68 (range; 60–85 years) n = 122) completed sociodemographic and quantitative food frequency questionnaires (QFFQ), fasting venous blood samples (25-hydroxycholecalciferol: Vitamin D-25), 24 h urine collection (estimate protein intake), grip strength and PA monitoring (activPAL). Dual-energy x-ray absorptiometry (DXA) scans of the hip (femoral neck and total) and lumbar spine determined BMD and whole-body scans for fat and fat-free soft tissue mass (FFSTM). WHO classifications were used to determine osteopenia (t-score -2.5 to -1), and osteoporosis (t-score < -2.5).

At the lumbar spine 34.4% of the women (n = 42) had osteopenia and 19.7% (n = 24) had osteoporosis. Osteopenia at the left femoral neck was 32% (n = 40) and osteoporosis was 13.1% (n = 16) of participants. The total left hip BMD indicated osteopenia in 27.9% (n = 34) and osteoporosis in 13.1% (n = 16) of participants. Multinomial regression revealed no differences in age (y) or frequency of falls in the past year between all groups (p = 0.727). Compared to those with normal BMD, participants with osteoporosis at the hip neck and lumbar spine were shorter, weighed less and had a lower body mass index (BMI) (all p < 0.05). When adjusted for height, the osteoporotic group (hip neck and lumbar spine) had lower trunk fat (% whole body), FFSTM (kg) and grip strength (kg), compared to those with normal BMD (p < 0.05). Only protein intake (g; 24 h urine analyses) was lower in women with osteoporosis (all sites) compared to those with normal BMD. Fat, carbohydrate and micronutrient intakes (relative to total daily energy intake), and vitamin D concentrations were not associated with BMD (all sites). Number of daily step count and stepping time (min) were inversely associated with BMI (p < 0.05), but not with BMD (all sites; p > 0.05).

A high prevalence of osteopenia and osteoporosis was evident at the lumbar spine and hip in older black SA women. This study highlights the importance of strength, body composition, and protein intake in maintaining BMD and preventing the development of osteoporosis in older women.

Maternal inflammation in early pregnancy has been identified epidemiologically as a prenatal pathogenic factor for the offspring's later mental illness. Early newborn manifestations of the effects of maternal inflammation on human fetal brain development are largely unknown.

Maternal infection, depression, obesity, and other factors associated with inflammation were assessed at 16 weeks gestation, along with maternal C-reactive protein (CRP), cytokines, and serum choline. Cerebral inhibition was assessed by inhibitory P50 sensory gating at 1 month of age, and infant behavior was assessed by maternal ratings at 3 months of age.

Maternal CRP diminished the development of cerebral inhibition in newborn males but paradoxically increased inhibition in females. Similar sex-dependent effects were seen in mothers' assessment of their infant's self-regulatory behaviors at 3 months of age. Higher maternal choline levels partly mitigated the effect of CRP in male offspring.

The male fetal-placental unit appears to be more sensitive to maternal inflammation than females. Effects are particularly marked on cerebral inhibition. Deficits in cerebral inhibition 1 month after birth, similar to those observed in several mental illnesses, including schizophrenia, indicate fetal developmental pathways that may lead to later mental illness. Deficits in early infant behavior follow. Early intervention before birth, including prenatal vitamins, folate, and choline supplements, may help prevent fetal development of pathophysiological deficits that can have life-long consequences for mental health.

This study investigated whether higher maternal choline levels mitigate effects of marijuana on fetal brain development. Choline transported into the amniotic fluid from the mother activates α7-nicotinic acetylcholine receptors on fetal cerebro-cortical inhibitory neurons, whose development is impeded by cannabis blockade of their cannabinoid-1(CB1) receptors.

Marijuana use was assessed during pregnancy from women who later brought their newborns for study. Mothers were informed about choline and other nutrients, but not specifically for marijuana use. Maternal serum choline was measured at 16 weeks gestation.

Marijuana use for the first 10 weeks gestation or more by 15% of mothers decreased newborns' inhibition of evoked potentials to repeated sounds (d’ = 0.55, p < 0.05). This effect was ameliorated if women had higher gestational choline (rs = −0.50, p = 0.011). At 3 months of age, children whose mothers continued marijuana use through their 10th gestational week or more had poorer self-regulation (d’ = −0.79, p < 0.05). This effect was also ameliorated if mothers had higher gestational choline (rs = 0.54, p = 0.013). Maternal choline levels correlated with the children's improved duration of attention, cuddliness, and bonding with parents.

Prenatal marijuana use adversely affects fetal brain development and subsequent behavioral self-regulation, a precursor to later, more serious problems in childhood. Stopping marijuana use before 10 weeks gestational age prevented these effects. Many mothers refuse to cease use because of familiarity with marijuana and belief in its safety. Higher maternal choline mitigates some of marijuana's adverse effects on the fetus.

Movement disorders associated with exposure to antipsychotic drugs are common and stigmatising but underdiagnosed.

To develop and evaluate a new clinical procedure, the ScanMove instrument, for the screening of antipsychotic-associated movement disorders for use by mental health nurses.

Item selection and content validity assessment for the ScanMove instrument were conducted by a panel of neurologists, psychiatrists and a mental health nurse, who operationalised a 31-item screening procedure. Interrater reliability was measured on ratings for 30 patients with psychosis from ten mental health nurses evaluating video recordings of the procedure. Criterion and concurrent validity were tested comparing the ScanMove instrument-based rating of 13 mental health nurses for 635 community patients from mental health services with diagnostic judgement of a movement disorder neurologist based on the ScanMove instrument and a reference procedure comprising a selection of commonly used rating scales.

Interreliability analysis showed no systematic difference between raters in their prediction of any antipsychotic-associated movement disorders category. On criterion validity testing, the ScanMove instrument showed good sensitivity for parkinsonism (90%) and hyperkinesia (89%), but not for akathisia (38%), whereas specificity was low for parkinsonism and hyperkinesia, and moderate for akathisia.

The ScanMove instrument demonstrated good feasibility and interrater reliability, and acceptable sensitivity as a mental health nurse-administered screening tool for parkinsonism and hyperkinesia.

None.