The coronavirus disease 2019 (COVID-19) pandemic has resulted in shortages of personal protective equipment (PPE), underscoring the urgent need for simple, efficient, and inexpensive methods to decontaminate masks and respirators exposed to severe acute respiratory coronavirus virus 2 (SARS-CoV-2). We hypothesized that methylene blue (MB) photochemical treatment, which has various clinical applications, could decontaminate PPE contaminated with coronavirus.

The 2 arms of the study included (1) PPE inoculation with coronaviruses followed by MB with light (MBL) decontamination treatment and (2) PPE treatment with MBL for 5 cycles of decontamination to determine maintenance of PPE performance.

MBL treatment was used to inactivate coronaviruses on 3 N95 filtering facepiece respirator (FFR) and 2 medical mask models. We inoculated FFR and medical mask materials with 3 coronaviruses, including SARS-CoV-2, and we treated them with 10 µM MB and exposed them to 50,000 lux of white light or 12,500 lux of red light for 30 minutes. In parallel, integrity was assessed after 5 cycles of decontamination using multiple US and international test methods, and the process was compared with the FDA-authorized vaporized hydrogen peroxide plus ozone (VHP+O3) decontamination method.

Overall, MBL robustly and consistently inactivated all 3 coronaviruses with 99.8% to >99.9% virus inactivation across all FFRs and medical masks tested. FFR and medical mask integrity was maintained after 5 cycles of MBL treatment, whereas 1 FFR model failed after 5 cycles of VHP+O3.

MBL treatment decontaminated respirators and masks by inactivating 3 tested coronaviruses without compromising integrity through 5 cycles of decontamination. MBL decontamination is effective, is low cost, and does not require specialized equipment, making it applicable in low- to high-resource settings.

Cognitive deficits affect a significant proportion of patients with bipolar disorder (BD). Problems with sustained attention have been found independent of mood state and the causes are unclear. We aimed to investigate whether physical parameters such as activity levels, sleep, and body mass index (BMI) may be contributing factors.

Forty-six patients with BD and 42 controls completed a battery of neuropsychological tests and wore a triaxial accelerometer for 21 days which collected information on physical activity, sleep, and circadian rhythm. Ex-Gaussian analyses were used to characterise reaction time distributions. We used hierarchical regression analyses to examine whether physical activity, BMI, circadian rhythm, and sleep predicted variance in the performance of cognitive tasks.

Neither physical activity, BMI, nor circadian rhythm predicted significant variance on any of the cognitive tasks. However, the presence of a sleep abnormality significantly predicted a higher intra-individual variability of the reaction time distributions on the Attention Network Task.

This study suggests that there is an association between sleep abnormalities and cognition in BD, with little or no relationship with physical activity, BMI, and circadian rhythm.

Prader-Willi Syndrome (PWS) is a genetically determined neurodevelopmental disorder which occurs in approximately 1 in 22000 births.

Parents of subjects with genetically confirmed PWS (participating in the First National Irish PWS study) were asked to fill in a demographic questionnaire, The Child Behaviour Checklist 6–18 (CBCL/6–18), Brief Symptom Inventory (BSI). The age, gender and IQ matched control group was collected through Special Schools.

Both groups (PWS and Controls) were comprised of 24 children. Internalizing problems score was higher in children with PWS than controls (T mean score (62.02 (SD = 10.17) vs. 58.13 (SD = 7.53) p < . 05). The comparison of PWS and control group along CBCL/6–18 syndromes profiles indicated that children with PWS had more sever somatic problems (mean T 63.50 SD = 8.41 vs. 56.13 SD = 6.31, p< .05), social problems (mean T 64.71 SD = 8.95 vs. 58.79 SD = 9.41, p < .05), thoughts problems (mean T 67.71 SD = 9.71 vs. 58.04 SD = 7.17, p < .05) and were more withdrawn/depressed (mean T 64.04 SD = 9.11 vs. 55.46 SD = 6.48, p < .05). Borderline difficulties were detected for the affective, somatic and ADHD CBCL DSM orientated subscales in PWS group with PWS children having significantly more somatic (mean T 63.05 SD = 8.33 vs. 52.00 SD = 6.48, P < .05) and affective (mean T 66.22 SD = 8.51, vs. 60.08 SD = 6.829 P < .05) problems than controls. The analysis of BSI scales revealed that parents of PSW children in comparison to controls had more somatization, phobic anxiety, obsessive compulsion, and anxiety problems.

PWS represents a complex psychological disorder with multiple areas of disturbances.

Bipolar disorder (BD) is associated with attentional and processing abnormalities. Such abnormalities are also seen in healthy subjects with sleep disruption. We hypothesised cognitive abnormalities in BD patients would be worse in those with objectively verified sleep abnormalities.

Forty-six BD patients and 42 controls had comprehensive sleep/circadian rhythm assessment over 21 days alongside mood questionnaires. Cognitive function was assessed with a range of tasks including Psychomotor Vigilance Test (PVT), Attention Network Task (ANT) and Digit Symbol Substitution Test (DSST). BD participants with normal and abnormal sleep were compared with age- and sex-matched controls.

BD patients had longer response times and made more lapses (responses >500 ms) than controls on the PVT (both p < 0.001). However, patients with normal sleep patterns did not differ from controls while those with sleep abnormalities did (p < 0.001). An identical pattern of effects were seen with the ANT response times, with the abnormality in bipolar abnormal sleepers related to the executive attentional network. Similarly, patients made fewer correct responses on the DSST compared with the controls (p < 0.001). Bipolar normal sleepers did not differ while those with abnormal sleep did (p < 0.001). All these differences were seen in bipolar abnormal sleepers who were euthymic (p < 0.01) and across the main abnormal sleep phenotypes.

We confirm impairment in attention and processing speed in BD. Rather than sleep abnormalities exacerbating such dysfunction, the impairments were confined to bipolar abnormal sleepers, consistent with sleep disturbance being the main driver of cognitive dysfunction.

Subjective reports of insomnia and hypersomnia are common in bipolar disorder (BD). It is unclear to what extent these relate to underlying circadian rhythm disturbance (CRD). In this study we aimed to objectively assess sleep and circadian rhythm in a cohort of patients with BD compared to matched controls.

Forty-six patients with BD and 42 controls had comprehensive sleep/circadian rhythm assessment with respiratory sleep studies, prolonged accelerometry over 3 weeks, sleep questionnaires and diaries, melatonin levels, alongside mood, psychosocial functioning and quality of life (QoL) questionnaires.

Twenty-three (50%) patients with BD had abnormal sleep, of whom 12 (52%) had CRD and 29% had obstructive sleep apnoea. Patients with abnormal sleep had lower 24-h melatonin secretion compared to controls and patients with normal sleep. Abnormal sleep/CRD in BD was associated with impaired functioning and worse QoL.

BD is associated with high rates of abnormal sleep and CRD. The association between these disorders, mood and functioning, and the direction of causality, warrants further investigation.

Late-life depression (LLD) is associated with a decline in physical activity. Typically this is assessed by self-report questionnaires and, more recently, with actigraphy. We sought to explore the utility of a bespoke activity monitor to characterize activity profiles in LLD more precisely.

The activity monitor was worn for 7 days by 29 adults with LLD and 30 healthy controls. Subjects underwent neuropsychological assessment and quality of life (QoL) (36-item Short-Form Health Survey) and activities of daily living (ADL) scales (Instrumental Activities of Daily Living Scale) were administered.

Physical activity was significantly reduced in LLD compared with controls (t = 3.63, p < 0.001), primarily in the morning. LLD subjects showed slower fine motor movements (t = 3.49, p < 0.001). In LLD patients, activity reductions were related to reduced ADL (r = 0.61, p < 0.001), lower QoL (r = 0.65, p < 0.001), associative learning (r = 0.40, p = 0.036), and higher Montgomery–Åsberg Depression Rating Scale score (r = −0.37, p < 0.05).

Patients with LLD had a significant reduction in general physical activity compared with healthy controls. Assessment of specific activity parameters further revealed the correlates of impairments associated with LLD. Our study suggests that novel wearable technology has the potential to provide an objective way of monitoring real-world function.

Hippocampal volume reductions in major depression have been frequently reported. However, evidence for functional abnormalities in the same region in depression has been less clear. We investigated hippocampal function in depression using functional magnetic resonance imaging (fMRI) and neuropsychological tasks tapping spatial memory function, with complementing measures of hippocampal volume and resting blood flow to aid interpretation.

A total of 20 patients with major depressive disorder (MDD) and a matched group of 20 healthy individuals participated. Participants underwent multimodal magnetic resonance imaging (MRI): fMRI during a spatial memory task, and structural MRI and resting blood flow measurements of the hippocampal region using arterial spin labelling. An offline battery of neuropsychological tests, including several measures of spatial memory, was also completed.

The fMRI analysis showed significant group differences in bilateral anterior regions of the hippocampus. While control participants showed task-dependent differences in blood oxygen level-dependent (BOLD) signal, depressed patients did not. No group differences were detected with regard to hippocampal volume or resting blood flow. Patients showed reduced performance in several offline neuropsychological measures. All group differences were independent of differences in hippocampal volume and hippocampal blood flow.

Functional abnormalities of the hippocampus can be observed in patients with MDD even when the volume and resting perfusion in the same region appear normal. This suggests that changes in hippocampal function can be observed independently of structural abnormalities of the hippocampus in depression.

Attentional impairment is a core cognitive feature of major depressive disorder (MDD) and bipolar disorder (BD). However, little is known of the characteristics of response time (RT) distributions from attentional tasks. This is crucial to furthering our understanding of the profile and extent of cognitive intra-individual variability (IIV) in mood disorders.

A computerized sustained attention task was administered to 138 healthy controls and 158 patients with a mood disorder: 86 euthymic BD, 33 depressed BD and 39 medication-free MDD patients. Measures of IIV, including individual standard deviation (iSD) and coefficient of variation (CoV), were derived for each participant. Ex-Gaussian (and Vincentile) analyses were used to characterize the RT distributions into three components: mu and sigma (mean and standard deviation of the Gaussian portion of the distribution) and tau (the ‘slow tail’ of the distribution).

Compared with healthy controls, iSD was increased significantly in all patient samples. Due to minimal changes in average RT, CoV was only increased significantly in BD depressed patients. Ex-Gaussian modelling indicated a significant increase in tau in euthymic BD [Cohen's d = 0.39, 95% confidence interval (CI) 0.09–0.69, p = 0.011], and both sigma (d = 0.57, 95% CI 0.07–1.05, p = 0.025) and tau (d = 1.14, 95% CI 0.60–1.64, p < 0.0001) in depressed BD. The mu parameter did not differ from controls.

Increased cognitive variability may be a core feature of mood disorders. This is the first demonstration of differences in attentional RT distribution parameters between MDD and BD, and BD depression and euthymia. These data highlight the utility of applying measures of IIV to characterize neurocognitive variability and the great potential for future application.

Previous studies of neurocognitive performance in bipolar disorder (BD) have focused predominantly on euthymia. In this study we aimed to compare the neurocognitive profile of BD patients when depressed with healthy controls and explore the component structure of neurocognitive processes in these populations.

Cognitive tests of attention and executive function, immediate memory, verbal and visuospatial learning and memory and psychomotor speed were administered to 53 patients with a SCID-verified diagnosis of BD depression and 47 healthy controls. Test performance was assessed in terms of statistical significance, effect size and percentile standing. Principal component analysis (PCA) was used to explore underlying cognitive factor structure.

Multivariate analysis revealed an overall group effect, depressed BD patients performing significantly worse than controls. Patients performed significantly worse on 18/26 measures examined, with large effect sizes (d > 0.8) on tests of speed of processing, verbal learning and specific executive/working memory processes. Almost all tests produced at least one outcome measure on which ∼25–50% of the BD sample performed at more than 1 standard deviation (s.d.) below the control mean. Between 20% and 34% of patients performed at or below the fifth percentile of the control group in working memory, verbal learning and memory, and psychomotor/processing speed. PCA highlighted overall differences between groups, with fewer extracted components and less specificity in patients.

Overall, neurocognitive test performance is significantly reduced in BD patients when depressed. The use of different methods of analysing cognitive performance is highlighted, along with the relationship between processes, indicating important directions for future research.

We report three cases of lateral outfracture of the inferior turbinate, which demonstrate a range of changes in the size, position and shape of the inferior turbinate.

During a study of the validity of computer modelling of nasal airflow, computed tomography scans of the noses of patients who had undergone lateral outfracture of the inferior turbinate were collected. The pre-operative scan was compared with the post-operative scan six weeks later.

In one patient, there was only a small lateral displacement of the inferior turbinate. In the other two cases, appreciable reduction in the volume of one inferior turbinate was noted, in addition to minor changes in the shape.

Lateral outfracture of the inferior turbinate produces varied and inconsistent changes in morphology which may affect the shape, size and position of the turbinate.

Electronic medical records (EMR) provide a unique opportunity for efficient, large-scale clinical investigation in psychiatry. However, such studies will require development of tools to define treatment outcome.

Natural language processing (NLP) was applied to classify notes from 127 504 patients with a billing diagnosis of major depressive disorder, drawn from out-patient psychiatry practices affiliated with multiple, large New England hospitals. Classifications were compared with results using billing data (ICD-9 codes) alone and to a clinical gold standard based on chart review by a panel of senior clinicians. These cross-sectional classifications were then used to define longitudinal treatment outcomes, which were compared with a clinician-rated gold standard.

Models incorporating NLP were superior to those relying on billing data alone for classifying current mood state (area under receiver operating characteristic curve of 0.85–0.88 v. 0.54–0.55). When these cross-sectional visits were integrated to define longitudinal outcomes and incorporate treatment data, 15% of the cohort remitted with a single antidepressant treatment, while 13% were identified as failing to remit despite at least two antidepressant trials. Non-remitting patients were more likely to be non-Caucasian (p<0.001).

The application of bioinformatics tools such as NLP should enable accurate and efficient determination of longitudinal outcomes, enabling existing EMR data to be applied to clinical research, including biomarker investigations. Continued development will be required to better address moderators of outcome such as adherence and co-morbidity.

Abnormal diffusion parameters are reported in specific brain regions and white matter tracts in bipolar disorder.

To investigate whether these abnormalities are generalised, and thus evident in large regions of white matter.

Diffusion parameters were measured at several regions in the corpus callosum and in deep/periventricular white matter in 28 currently euthymic patients with bipolar disorder and controls. White matter hyperintensity loads were assessed.

Comparing the whole data-sets using the sign test, in the group with bipolar disorder, mean diffusivity was greater at all 15 sites (P<0.001) and fractional anisotropy was reduced at 13 (P<0.01). The effect of diagnosis was significant for callosal mean diffusivity and fractional anisotropy and for deep/periventricular mean diffusivity (MANCOVA). Comparing individual regions (Mann–Whitney U-test), prefrontal and periventricular mean diffusivity were significantly increased; callosal and occipital fractional anisotropy were significantly reduced. Former substance use and lithium were possible confounding factors. Periventricular white matter hyperintensities were associated with significantly increased periventricular mean diffusivity in individuals with bipolar disorder.

Generalised white matter microstructural abnormalities may exist in bipolar disorder, possibly exacerbated by past substance use and ameliorated by lithium.