ObjectiveTo examine the efficacy and safety of combined transcranial direct current stimulation (tDCS) and working memory training (WMT) in enhancing the cognitive functions for individuals with mild neurocognitive disorder due to AD (NCD‐AD).MethodsIn this double‐blind, sham‐controlled randomized clinical trial (RCT), 201 patients with NCD‐AD were randomly assigned for a 4‐week intervention of either a combination of tDCS and WMT, sham tDCS and WMT, or tDCS and control cognitive training (CCT). Global cognition and domain‐specific cognitive function were assessed before and after the intervention with Alzheimer's disease assessment scale‐cognitive subscale (ADAS‐Cog), category verbal fluency test, logical memory, digit, and visual span tests.ResultsStudy participants did not show intervention group differences in baseline demographics, or cognitive characteristics (ANOVA). Cognitive enhancement was found across three groups after 4 weeks intervention. Combined tDCS‐WMT group showed significantly greater improvement compared with single‐modality groups in delayed recall (P = 0.043, η 2 = 0.036) and working memory capacity (P = 0.04, η 2 = 0.038) at 4th week, and logical memory at 12th week (P = 0.042, η 2 = 0.037). Adverse events, including skin lesions (2.2%), were similar between groups.InterpretationtDCS or WMT could be a safe, feasible, and effective intervention for individuals with NCD‐AD. A combination of tDCS and WMT presents greater cognitive enhancement, which may highlight the potential synergistic effects of combined modality intervention on cognition.

ObjectivesMental health problems are prevalent during the COVID-19 pandemic, but their effect on adherence to precautionary measures is not well understood. Given that psychological morbidities are associated with lower treatment adherence, and that precautionary measures are important in containing the spread of COVID-19, this study aims to determine if people with mental health problems have lower adherence to precautionary measures against COVID-19.DesignWe conducted a cross-sectional territory-wide online survey between 17 June and 31 July 2020 during the COVID-19 pandemic. Clinically significant mental health problems, adherence to precautionary behaviours, and confounding factors such as sociodemographic factors and self-reported physical health were assessed.SettingThe link to the questionnaire was disseminated to the general population in all 18 districts of Hong Kong using various social media platforms.Participants1036 individuals completed the survey. Of them, 1030 met the inclusion criteria of being adult Hong Kong residents.Primary outcomeAdherence to precautionary measures against COVID-19, including wearing face mask, frequent handwashing, household disinfection, social distancing, minimising unnecessary travel, and stocking up on food and daily essentials.ResultsOf the 1030 participants, 166 (16.1%) had clinically significant mental health problems. Interestingly, they were more likely to stock up on food and daily essentials during the pandemic (7 (4.2%) vs 15 (1.7%), p=0.04; unadjusted OR=2.49, 95% CI=1.00 to 6.21, p<0.05) and had a lesser tendency to stop social distancing even if the pandemic subsides (86 (51.8%) vs 513 (59.4%), p=0.07; unadjusted OR=0.74, 95% CI=0.53 to 1.03, p=0.07). The latter association remained significant after adjusting for the confounding factors (adjusted OR=0.68, 95% CI=0.48 to 0.96, p=0.03).ConclusionsContrary to our hypothesis, people who are mentally unwell might go beyond the recommended precautionary measures. Our findings highlight the need to identify mental health problems and provide care and support for those who might go too far with precautionary measures.Trial registration numberChiCTR 2000033936.

Image-guided repetitive transcranial magnetic stimulation (rTMS) has shown clinical effectiveness in senior adults with co-occurring depression and cognitive impairment, yet the imaging markers for predicting the treatment response are less investigated. In this clinical trial, we examined the efficacy and sustainability of 10 Hz rTMS for the treatment of depression and cognitive impairment in major neurocognitive disorder (NCD) patients and tested the predictive values of imaging-informed radiomic features in response to rTMS treatment. Fifty-five major NCD patients with depression were randomly assigned to receive a 3-week rTMS treatment of either active 10 Hz rTMS (n = 27) or sham rTMS (n = 28). Left dorsolateral prefrontal cortex (DLPFC) was the predefined treatment target. Based on individual structural magnetic resonance imaging scans, surface-based analysis was conducted to quantitatively measure the baseline radiomic features of left DLPFC. Severity of depression, global cognition and the serum brain-derived neurotrophic factor (BDNF) level were evaluated at baseline, 3-, 6-and 12-week follow-ups. Logistic regression analysis revealed that advanced age, higher baseline cognition and randomized group were associated with the remission of depression. Increased cortical thickness and gyrification in left DLPFC were the significant predictors of clinical remission and cognitive enhancement. A 3-week course of 10 Hz rTMS is an effective adjuvant treatment for rapid ameliorating depressive symptoms and enhancing cognitive function. Pre-treatment radiomic features of the stimulation target can predict the response to rTMS treatment in major NCD. Cortical thickness and folding of treatment target may serve as

BackgroundThe COVID-19 pandemic has imposed a profound negative impact on the mental health and wellbeing of societies and individuals worldwide. Older adults may be more vulnerable to the mental health effects of the pandemic, either directly from the infection itself or indirectly through the preventive measures. However, the existing literature on mental health in the older age groups has not been consistent so far. The aim of this study was therefore to assess the prevalence of common mental disorders (CMD; including depression and anxiety disorders) given their association with dementia risk, and to further examine age-related differences between older (≥60 years old) and younger (18–59 years old) adult's psychological status during the COVID-19 pandemic.MethodThis was a secondary analysis of a cross-sectional survey-study conducted during the second wave of COVID-19 pandemic in Hong Kong. The survey was disseminated through different social media platforms to the general population and included sociodemographic questions, self-reported physical health, and previous encounter with SARS or COVID-19. CMD was the primary outcome and was assessed using the 6-item Kessler Scale. A total of 1030 adults fulfilled inclusion criteria.ResultsThe prevalence of CMD during the pandemic was 16.1%. Compared to younger adults, older adults were significantly less likely to have a CMD (unadjusted OR = 0.07, 95% CI = 0.02–0.30, p &lt; 0.001), with 18.1% of younger adults having CMD compared to 1.6% in the older cohort. Age differences remained significant after controlling for sociodemographic factors, physical health, and previous encounter with SARS or COVID-19 (adjusted OR = 0.12, 95% CI = 0.02–0.57, p = 0.008).ConclusionCommon mental disorders are highly prevalent during the COVID-19 pandemic in Hong Kong, though older adults appeared to be less affected mentally. Present findings highlight the urgent need to implement measures and strategies to mitigate the mental health problems, with particular attention to the younger cohort. Given their association with higher dementia risk, early detection and treatment of depression and anxiety disorders will be of critical importance in providing some relief to the already pressurized dementia burden in the longer term.

RNA-Seq is widely used to capture transcriptome dynamics across tissues from different biological entities even across biological conditions, with the aim of understanding the contribution of gene activities to phenotypes of biosamples. However, due to variation from tissues and biological entities (or other biological conditions), joint analysis of bulk RNA expression profiles across multiple tissues from a number of biological entities to achieve the aim is hindered. Moreover, it is crucial to consider interactions between biological variables. For example, different brain disorders may have heterogeneous effects across brain regions. Thus, modeling the disorder-region interaction can shed light on the heterogeneity. To address these key challenges, we propose a general and flexible statistical framework, INSIDER (https://github.com/kai0511/insider), based on matrix factorization. INSIDER decomposes variation from different biological variables into a shared low-rank latent space. In particular, it considers interactions between biological variables and introduces the elastic net penalty to induce sparsity, thus facilitating interpretation. In the framework, the biological variables and interaction terms can be defined based on the research questions and study design. Besides, it enables us to compute the 'adjusted' expression profiles for biological variables that control variation from other biological variables. Lastly, it allows various downstream analyses, such as clustering donors with donor representations, revealing development trajectory in its application to the BrainSpan data, and uncovering mechanisms underlying variables like phenotype and interactions between biological variables (e.g., phenotypes and tissues).