Individuals at risk for bipolar disorder (BD) have a wide range of genetic and non-genetic risk factors, like a positive family history of BD or (sub)threshold affective symptoms. Yet, it is unclear whether these individuals at risk and those diagnosed with BD share similar gray matter brain alterations.

In 410 male and female participants aged 17–35 years, we compared gray matter volume (3T MRI) between individuals at risk for BD (as assessed using the EPIbipolar scale; n = 208), patients with a DSM-IV-TR diagnosis of BD (n = 87), and healthy controls (n = 115) using voxel-based morphometry in SPM12/CAT12. We applied conjunction analyses to identify similarities in gray matter volume alterations in individuals at risk and BD patients, relative to healthy controls. We also performed exploratory whole-brain analyses to identify differences in gray matter volume among groups. ComBat was used to harmonize imaging data from seven sites.

Both individuals at risk and BD patients showed larger volumes in the right putamen than healthy controls. Furthermore, individuals at risk had smaller volumes in the right inferior occipital gyrus, and BD patients had larger volumes in the left precuneus, compared to healthy controls. These findings were independent of course of illness (number of lifetime manic and depressive episodes, number of hospitalizations), comorbid diagnoses (major depressive disorder, attention-deficit hyperactivity disorder, anxiety disorder, eating disorder), familial risk, current disease severity (global functioning, remission status), and current medication intake.

Our findings indicate that alterations in the right putamen might constitute a vulnerability marker for BD.

Individuals with bipolar disorder are commonly correctly diagnosed a decade after symptom onset. Machine learning techniques may aid in early recognition and reduce the disease burden. As both individuals at risk and those with a manifest disease display structural brain markers, structural magnetic resonance imaging may provide relevant classification features.

Following a pre-registered protocol, we trained linear support vector machine (SVM) to classify individuals according to their estimated risk for bipolar disorder using regional cortical thickness of help-seeking individuals from seven study sites (N = 276). We estimated the risk using three state-of-the-art assessment instruments (BPSS-P, BARS, EPIbipolar).

For BPSS-P, SVM achieved a fair performance of Cohen's κ of 0.235 (95% CI 0.11–0.361) and a balanced accuracy of 63.1% (95% CI 55.9–70.3) in the 10-fold cross-validation. In the leave-one-site-out cross-validation, the model performed with a Cohen's κ of 0.128 (95% CI −0.069 to 0.325) and a balanced accuracy of 56.2% (95% CI 44.6–67.8). BARS and EPIbipolar could not be predicted. In post hoc analyses, regional surface area, subcortical volumes as well as hyperparameter optimization did not improve the performance.

Individuals at risk for bipolar disorder, as assessed by BPSS-P, display brain structural alterations that can be detected using machine learning. The achieved performance is comparable to previous studies which attempted to classify patients with manifest disease and healthy controls. Unlike previous studies of bipolar risk, our multicenter design permitted a leave-one-site-out cross-validation. Whole-brain cortical thickness seems to be superior to other structural brain features.

The purpose of this study was to pilot safety and tolerability of a 1-week aerobic exercise program during the post-acute phase of concussion (14–25 days post-injury) by examining adherence, symptom response, and key functional outcomes (e.g., cognition, mood, sleep, postural stability, and neurocognitive performance) in young adults.

A randomized, non-blinded pilot clinical trial was performed to compare the effects of aerobic versus non-aerobic exercise (placebo) in concussion patients. The study enrolled three groups: 1) patients with concussion/mild traumatic brain injury (mTBI) randomized to an aerobic exercise intervention performed daily for 1-week, 2) patients with concussion/mTBI randomized to a non-aerobic (stretching and calisthenics) exercise program performed daily for 1-week, and 3) non-injured, no intervention reference group.

Mixed-model analysis of variance results indicated a significant decrease in symptom severity scores from pre- to post-intervention (mean difference = −7.44, 95% CI [−12.37, −2.20]) for both concussion groups. However, the pre- to post-change was not different between groups. Secondary outcomes all showed improvements by post-intervention, but no differences in trajectory between the groups. By three months post-injury, all outcomes in the concussion groups were within ranges of the non-injured reference group.

Results from this study indicate that the feasibility and tolerability of administering aerobic exercise via stationary cycling in the post-acute time frame following post-concussion (14–25 days) period are tentatively favorable. Aerobic exercise does not appear to negatively impact recovery trajectories of neurobehavioral outcomes; however, tolerability may be poorer for patients with high symptom burden.

We summarize some of the past year's most important findings within climate change-related research. New research has improved our understanding about the remaining options to achieve the Paris Agreement goals, through overcoming political barriers to carbon pricing, taking into account non-CO2 factors, a well-designed implementation of demand-side and nature-based solutions, resilience building of ecosystems and the recognition that climate change mitigation costs can be justified by benefits to the health of humans and nature alone. We consider new insights about what to expect if we fail to include a new dimension of fire extremes and the prospect of cascading climate tipping elements.

A synthesis is made of 10 topics within climate research, where there have been significant advances since January 2020. The insights are based on input from an international open call with broad disciplinary scope. Findings include: (1) the options to still keep global warming below 1.5 °C; (2) the impact of non-CO2 factors in global warming; (3) a new dimension of fire extremes forced by climate change; (4) the increasing pressure on interconnected climate tipping elements; (5) the dimensions of climate justice; (6) political challenges impeding the effectiveness of carbon pricing; (7) demand-side solutions as vehicles of climate mitigation; (8) the potentials and caveats of nature-based solutions; (9) how building resilience of marine ecosystems is possible; and (10) that the costs of climate change mitigation policies can be more than justified by the benefits to the health of humans and nature.

How do we limit global warming to 1.5 °C and why is it crucial? See highlights of latest climate science.

Aetiology of protein-losing enteropathy in single-ventricle type CHD is multi-factorial.

We describe two Fontan patients with protein-losing enteropathy who presented with cytomegalovirus-associated colitis.

Fontan patients display risk factors for cytomegalovirus-induced gastroenteropathy that may affect lymph angiogenesis, disease development, and progression.

Cytomegalovirus enteropathy may be common among Fontan patients who suffer from protein-losing enteropathy. Polymerase chain reaction is important for detection.

To identify whether picky eating during childhood is associated with dietary intake, weight status and disordered eating behaviour during young adulthood.

A population-based study using data from young adults who responded online or by mail to the third wave of the Project EAT (Eating and Activity in Teens and Young Adults) study in 2008–2009. Participants retrospectively reported the extent to which they were a picky eater in childhood, sociodemographic characteristics, disordered eating behaviours, usual dietary intake, and weight and height.

Participants were initially recruited in the Minneapolis/St. Paul metropolitan area of Minnesota, USA, in 1998–1999.

The analytic sample included 2275 young adults (55 % female, 48 % non-Hispanic White, mean age 25·3 (sd 1·6) years).

Young adults who reported picky eating in childhood were found to currently have lower intakes of fruit, vegetables and whole grains, and more frequent intakes of snack foods, sugar-sweetened beverages and foods from fast-food restaurants. No associations were observed between picky eating in childhood and young adults’ weight status, use of weight-control strategies or report of binge eating.

While young adults who report picky eating during childhood are not at higher risk for disordered eating, those who were picky eaters tend to have less healthy dietary intake. Food preferences and dietary habits established by picky eaters during childhood may persist into adulthood.

Through this study we aimed to assess the educational level and employment status of adults with CHD in Germany.

Data were acquired from an online survey carried out in 2015 by the German National Register for Congenital Heart Defects. A total of 1458 adults with CHD participated in the survey (response rate: 37.6%). For 1198 participants, detailed medical information, such as main cardiac diagnosis and information from medical reports, was available.

Of the participants surveyed (n=1198), 54.5% (n=653) were female, and the mean age was 30 years. The majority of respondents (59.4%) stated that they had high education levels and that they were currently employed (51.1%). Patients with simple CHD had significantly higher levels of education (p<0.001) and were more likely to be employed (p=0.01) than were patients with complex CHD.

More than half of the participants had high education levels and the majority were employed. The association between CHD and its severity and individuals’ educational attainment should be investigated more closely in future studies.