Transcranial direct current stimulation (tDCS) is a promising treatment for major depressive disorder (MDD). This study evaluated its antidepressant and cognitive effects as a safe, effective, home-based therapy for MDD.

This double-blind, sham-controlled, randomized trial divided participants into low-intensity (1 mA, n = 47), high-intensity (2 mA, n = 49), and sham (n = 45) groups, receiving 42 daily tDCS sessions, including weekends and holidays, targeting the dorsolateral prefrontal cortex for 30 minutes. Assessments were conducted at baseline and weeks 2, 4, and 6. The primary outcome was cognitive improvement assessed by changes in total accuracy on the 2-back test from baseline to week 6. Secondary outcomes included changes in depressive symptoms (HAM-D), anxiety (HAM-A), and quality of life (QLES). Adverse events were monitored. This trial was registered with ClinicalTrials.gov (NCT04709952).

In the tDCS study, of 141 participants (102 [72.3%] women; mean age 35.7 years, standard deviation 12.7), 95 completed the trial. Mean changes in the total accuracy scores from baseline to week 6 were compared across the three groups using an F-test. Linear mixed-effects models examined the interaction of group and time. Results showed no significant differences among groups in cognitive or depressive outcomes at week 6. Active groups experienced more mild adverse events compared to sham but had similar rates of severe adverse events and dropout.

Home-based tDCS for MDD demonstrated no evidence of effectiveness but was safe and well-tolerated. Further research is needed to address the technical limitations, evaluate broader cognitive functions, and extend durations to evaluate its therapeutic potential.

The depression, obstructive sleep apnea and cognitive impairment (DOC) screen assesses three post-stroke comorbidities, but additional information may be gained from the time to complete the screen. Cognitive screening completion time is rarely used as an outcome measure.

To assess DOC screen completion time as a predictor of cognitive impairment in stroke/transient ischemic attack clinics.

Consecutive English-speaking stroke prevention clinic patients consented to undergo screening and neuropsychological testing (n = 437). DOC screen scores and times were compared to scores on the NINDS-CSC battery using multiple linear regression (controlling for age, sex, education and stroke severity) and receiver operating characteristic (ROC) curve analysis.

Completion time for the DOC screen was 3.8 ± 1.3 minutes. After accounting for covariates, the completion time was a significant predictor of the speed of processing (p = 0.002, 95% CI: −0.016 to −0.004), verbal fluency (p < 0.001, CI: −0.012 to −0.006) and executive function (p = 0.004, CI: −0.006 to −0.001), but not memory. Completion time above 5.5 minutes was associated with a high likelihood of impairment on executive and speed of processing tasks (likelihood ratios 3.9–5.2).

DOC screen completion time is easy to collect in routine care. People needing over 5.5 minutes to be screened likely have deficits in executive functioning and speed of processing – areas commonly impaired, but challenging to screen for, after stroke. DOC screen time provides a simple, feasible approach to assess these under-identified cognitive impairments.

Adolescence is a period marked by highest vulnerability to the onset of depression, with profound implications for adult health. Neuroimaging studies have revealed considerable atrophy in brain structure in these patients with depression. Of particular importance are regions responsible for cognitive control, reward, and self-referential processing. However, the causal structural networks underpinning brain region atrophies in adolescents with depression remain unclear.

This study aimed to investigate the temporal course and causal relationships of gray matter atrophy within the brains of adolescents with depression.

We analyzed T1-weighted structural images using voxel-based morphometry in first-episode adolescent patients with depression (n=80, 22 males; age = 15.57±1.78) and age, gender matched healthy controls (n=82, 25 males; age = 16.11±2.76) to identify the disease stage-specific gray matter abnormalities. Then, with granger causality analysis, we arranged the patients’ illness duration chronologically to construct the causal structural covariance networks that investigated the causal relationships of those atypical structures.

Compared to controls, smaller volumes in ventral medial prefrontal cortex (vmPFC), dorsal anterior cingulate cortex (dACC), middle cingulate cortex (MCC) and insula areas were identified in patients with less than 1 year illness duration, and further progressed to the subgenual ACC, regions of default, frontoparietal networks in longer duration. Causal network results revealed that dACC, vmPFC, MCC and insula were prominent nodes projecting exerted positive causal effects to regions of the default mode and frontoparietal networks. The dACC, vmPFC and insula also had positive projections to the reward network, which included mainly the thalamus, caudate and putamen, while MCC also exerted a positive causal effect on the insula and thalamus.

These findings revealed the progression of structural atrophy in adolescent patients with depression and demonstrated the causal relationships between regions involving cognitive control, reward and self-referential processes.

None Declared

Among the various patient experiences, cancer-related fatigue and sleep disturbances emerge as pivotal aspects that can substantially impact individuals’ quality of life. There exists a relative scarcity of research focusing on the intricate relationship between symptoms, functioning, fatigue, and sleep disturbances in colorectal cancer (CRC) patients.

In this context, the current research endeavors to apply advanced statistical methodologies to elucidate the complex relationships between symptoms, functioning, fatigue, and sleep disturbances. By exploring the intricate web of patient characteristics, clinical factors, psychosocial elements, this study aims to construct a holistic model that not only captures the nuances of colorectal cancer patients’ experiences but also uncovers potential avenues for intervention and support.

In our cross sectional study, we administered the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30), the Quality of Life Questionnaire Colorectal Cancer Module (QLQ-CR29) to 987patients who were surgically-treated for CRC from the tertiary hospital from 2013 through 2018. To confirm the relationship between symptoms of CRC patients, univariable logistic regression was used to examine the potential relationship between independent variables and the occurrence of fatigue and sleep disorders. Least Absolute Shrinkage and Selection Operator (Lasso) was used for variable selection. The selected variables were then applied to a multivariate logistic regression analysis to examine the most influential predictors of fatigue and sleep disturbance. Finally, gaussian graphical models (GGM) were used to identify potential interactions between characteristics, symptoms, functioning, with fatigue, and sleep disturbances in CRC. In this study, Directed Acyclic Graph (DAG) was used to identify causal dependancy and path of variables.

About 10.4% of study participants reported experiencing fatigue. Sleep problems were reported by 15.8% of the study participants. Multivariable logistic regression analysis using Lasso showed that sleep problem (odds ratio [OR]=2.34; 95% CI, 1.03-5.31), physical, role, and emotional functioning, pain, dyspnoea, and appetite loss were significant predictors of fatigue, while emotional functioning, dyspnoea, and appetite loss were significant predictors of sleep problem. The variables that were directly linked to fatigue were role functioning, emotional functioning, dyspnoea, appetite loss, body image and trouble with taste. The variables that were directly linked to sleep problem were emotional functioning and appetite loss.

In conclusion, there were complex relationships between symptoms, functioning, fatigue, and sleep disturbances. The symptom network of CRC patients showed different patterns toward fatigue and sleep.

None Declared

Although behavioral mechanisms in the association among depression, anxiety, and cancer are plausible, few studies have empirically studied mediation by health behaviors. We aimed to examine the mediating role of several health behaviors in the associations among depression, anxiety, and the incidence of various cancer types (overall, breast, prostate, lung, colorectal, smoking-related, and alcohol-related cancers).

Two-stage individual participant data meta-analyses were performed based on 18 cohorts within the Psychosocial Factors and Cancer Incidence consortium that had a measure of depression or anxiety (N = 319 613, cancer incidence = 25 803). Health behaviors included smoking, physical inactivity, alcohol use, body mass index (BMI), sedentary behavior, and sleep duration and quality. In stage one, path-specific regression estimates were obtained in each cohort. In stage two, cohort-specific estimates were pooled using random-effects multivariate meta-analysis, and natural indirect effects (i.e. mediating effects) were calculated as hazard ratios (HRs).

Smoking (HRs range 1.04–1.10) and physical inactivity (HRs range 1.01–1.02) significantly mediated the associations among depression, anxiety, and lung cancer. Smoking was also a mediator for smoking-related cancers (HRs range 1.03–1.06). There was mediation by health behaviors, especially smoking, physical inactivity, alcohol use, and a higher BMI, in the associations among depression, anxiety, and overall cancer or other types of cancer, but effects were small (HRs generally below 1.01).

Smoking constitutes a mediating pathway linking depression and anxiety to lung cancer and smoking-related cancers. Our findings underline the importance of smoking cessation interventions for persons with depression or anxiety.

To assess cost-effectiveness of late time-window endovascular treatment (EVT) in a clinical trial setting and a “real-world” setting.

Data are from the randomized ESCAPE trial and a prospective cohort study (ESCAPE-LATE). Anterior circulation large vessel occlusion patients presenting > 6 hours from last-known-well were included, whereby collateral status was an inclusion criterion for ESCAPE but not ESCAPE-LATE. A Markov state transition model was built to estimate lifetime costs and quality-adjusted life-years (QALYs) for EVT in addition to best medical care vs. best medical care only in a clinical trial setting (comparing ESCAPE-EVT to ESCAPE control arm patients) and a “real-world” setting (comparing ESCAPE-LATE to ESCAPE control arm patients). We performed an unadjusted analysis, using 90-day modified Rankin Scale(mRS) scores as model input and analysis adjusted for baseline factors. Acceptability of EVT was calculated using upper/lower willingness-to-pay thresholds of 100,000 USD/50,000 USD/QALY.

Two-hundred and forty-nine patients were included (ESCAPE-LATE:n = 200, ESCAPE EVT-arm:n = 29, ESCAPE control-arm:n = 20). Late EVT in addition to best medical care was cost effective in the unadjusted analysis both in the clinical trial and real-world setting, with acceptability 96.6%–99.0%. After adjusting for differences in baseline variables between the groups, late EVT was marginally cost effective in the clinical trial setting (acceptability:49.9%–61.6%), but not the “real-world” setting (acceptability:32.9%–42.6%).

EVT for LVO-patients presenting beyond 6 hours was cost effective in the clinical trial setting and “real-world” setting, although this was largely related to baseline patient differences favoring the “real-world” EVT group. After adjusting for these, EVT benefit was reduced in the trial setting, and absent in the real-world setting.

Screen time in infancy is linked to changes in social-emotional development but the pathway underlying this association remains unknown. We aim to provide mechanistic insights into this association using brain network topology and to examine the potential role of parent–child reading in mitigating the effects of screen time.

We examined the association of screen time on brain network topology using linear regression analysis and tested if the network topology mediated the association between screen time and later socio-emotional competence. Lastly, we tested if parent–child reading time was a moderator of the link between screen time and brain network topology.

Infant screen time was significantly associated with the emotion processing-cognitive control network integration (p = 0.005). This network integration also significantly mediated the association between screen time and both measures of socio-emotional competence (BRIEF-2 Emotion Regulation Index, p = 0.04; SEARS total score, p = 0.04). Parent–child reading time significantly moderated the association between screen time and emotion processing-cognitive control network integration (β = −0.640, p = 0.005).

Our study identified emotion processing-cognitive control network integration as a plausible biological pathway linking screen time in infancy and later socio-emotional competence. We also provided novel evidence for the role of parent–child reading in moderating the association between screen time and topological brain restructuring in early childhood.