Multivariate brain prediction of heart rate and skin conductance responses to social threat

Psychosocial stressors induce autonomic nervous system (ANS) responses in multiple body systems that are linked to health risks. Much work has focused on the common effects of stress, but ANS responses in different body systems are dissociable and may result from distinct patterns of cortical–subcortical interactions. Here, we used machine learning to develop multivariate patterns of fMRI activity predictive of heart rate (HR) and skin conductance level (SCL) responses during social threat in humans (N = 18). Overall, brain patterns predicted both HR and SCL in cross-validated analyses successfully (r(HR) = 0.54, r(SCL) = 0.58, both p < 0.0001). These patterns partly reflected central stress mechanisms common to both responses because each pattern predicted the other signal to some degree (r(HR→SCL) = 0.21 and r(SCL→HR) = 0.22, both p < 0.01), but they were largely physiological response specific. Both patterns included positive predictive weights in dorsal anterior cingulate and cerebellum and negative weights in ventromedial PFC and local pattern similarity analyses within these regions suggested that they encode common central stress mechanisms. However, the predictive maps and searchlight analysis suggested that the patterns predictive of HR and SCL were substantially different across most of the brain, including significant differences in ventromedial PFC, insula, lateral PFC, pre-SMA, and dmPFC. Overall, the results indicate that specific patterns of cerebral activity track threat-induced autonomic responses in specific body systems. Physiological measures of threat are not interchangeable, but rather reflect specific interactions among brain systems. SIGNIFICANCE STATEMENT We show that threat-induced increases in heart rate and skin conductance share some common representations in the brain, located mainly in the vmPFC, temporal and parahippocampal cortices, thalamus, and brainstem. However, despite these similarities, the brain patterns that predict these two autonomic responses are largely distinct. This evidence for largely output-measure-specific regulation of autonomic responses argues against a common system hypothesis and provides evidence that different autonomic measures reflect distinct, measurable patterns of cortical–subcortical interactions

RNA-binding proteins to assess gene expression states of co-cultivated cells in response to tumor cells

BACKGROUND: Tumors and complex tissues consist of mixtures of communicating cells that differ significantly in their gene expression status. In order to understand how different cell types influence one another's gene expression, it will be necessary to monitor the mRNA profiles of each cell type independently and to dissect the mechanisms that regulate their gene expression outcomes. RESULTS: In order to approach these questions, we have used RNA-binding proteins such as ELAV/Hu, poly (A) binding protein (PABP) and cap-binding protein (eIF-4E) as reporters of gene expression. Here we demonstrate that the epitope-tagged RNA binding protein, PABP, expressed separately in tumor cells and endothelial cells can be used to discriminate their respective mRNA targets from mixtures of these cells without significant mRNA reassortment or exchange. Moreover, using this approach we identify a set of endothelial genes that respond to the presence of co-cultured breast tumor cells. CONCLUSION: RNA-binding proteins can be used as reporters to elucidate components of operational mRNA networks and operons involved in regulating cell-type specific gene expression in tissues and tumors

The risk and protective factors of heightened prenatal anxiety and depression during the COVID-19 lockdown

While pregnant women are already at-risk for developing symptoms of anxiety and depression, this is heightened during the COVID-19 pandemic. We compared anxiety and depression symptoms, as indicators of psychological distress, before and during COVID-19, and investigated the role of partner, social network and healthcare support on COVID-19-related worries and consequently on psychological distress. A national survey, conducted during the first lockdown in The Netherlands, assessed COVID-19 experiences and psychological distress (N = 1421), whereas a comparison sample (N = 1439) was screened for psychological distress in 2017–2018. During COVID-19, the percentage of mothers scoring above the questionnaires’ clinical cut-offs doubled for depression (6% and 12%) and anxiety (24% and 52%). Women reported increased partner support during COVID-19, compared to pre-pandemic, but decreased social and healthcare support. Higher support resulted in lower COVID-19-related worries, which in turn contributed to less psychological distress. Results suggest that a global pandemic exerts a heavy toll on pregnant women’s mental health. Psychological distress was substantially higher during the pandemic than the pre-pandemic years. We identified a protective role of partner, social, and healthcare support, with important implications for the current and future crisis management. Whether increased psychological distress is transient or persistent, and whether and how it affects the future generation remains to be determined

Hyperacute Directional Hearing and Phonotactic Steering in the Cricket (Gryllus bimaculatus deGeer)

Background: Auditory mate or prey localisation is central to the lifestyle of many animals and requires precise directional hearing. However, when the incident angle of sound approaches 0u azimuth, interaural time and intensity differences gradually vanish. This poses a demanding challenge to animals especially when interaural distances are small. To cope with these limitations imposed by the laws of acoustics, crickets employ a frequency tuned peripheral hearing system. Although this enhances auditory directionality the actual precision of directional hearing and phonotactic steering has never been studied in the behaviourally important frontal range. Principal Findings: Here we analysed the directionality of phonotaxis in female crickets (Gryllus bimaculatus) walking on an open-loop trackball system by measuring their steering accuracy towards male calling song presented at frontal angles of incidence. Within the range of 630u, females reliably discriminated the side of acoustic stimulation, even when the sound source deviated by only 1u from the animal’s length axis. Moreover, for angles of sound incidence between 1u and 6u the females precisely walked towards the sound source. Measuring the tympanic membrane oscillations of the front leg ears with a laser vibrometer revealed between 0u and 30u a linear increasing function of interaural amplitude differences with a slope of 0.4 dB/u. Auditory nerve recordings closely reflected these bilateral differences in afferent response latency and intensity that provide the physiological basis for precise auditory steering

Added Predictive Value of Female-Specific Factors and Psychosocial Factors for the Risk of Stroke in Women Under 50

Background and Objectives: Female-specific factors and psychosocial factors may be important in the prediction of stroke but are not included in prediction models that are currently used. We investigated whether addition of these factors would improve the performance of prediction models for the risk of stroke in women younger than 50 years.Methods: We used data from the Stichting Informatievoorziening voor Zorg en Onderzoek, population-based, primary care database of women aged 20-49 years without a history of cardiovascular disease. Analyses were stratified by 10-year age intervals at cohort entry. Cox proportional hazards models to predict stroke risk were developed, including traditional cardiovascular factors, and compared with models that additionally included female-specific and psychosocial factors. We compared the risk models using the c-statistic and slope of the calibration curve at a follow-up of 10 years. We developed an age-specific stroke risk prediction tool that may help communicating the risk of stroke in clinical practice.Results: We included 409,026 women with a total of 3,990,185 person-years of follow-up. Stroke occurred in 2,751 women (incidence rate 6.9 [95% CI 6.6-7.2] per 10,000 person-years). Models with only traditional cardiovascular factors performed poorly to moderately in all age groups: 20-29 years: c-statistic: 0.617 (95% CI 0.592-0.639); 30-39 years: c-statistic: 0.615 (95% CI 0.596-0.634); and 40-49 years: c-statistic: 0.585 (95% CI 0.573-0.597). After adding the female-specific and psychosocial risk factors to the reference models, the model discrimination increased moderately, especially in the age groups 30-39 (Δc-statistic: 0.019) and 40-49 years (Δc-statistic: 0.029) compared with the reference models, respectively.Discussion: The addition of female-specific factors and psychosocial risk factors improves the discriminatory performance of prediction models for stroke in women younger than 50 years.</p

Added Predictive Value of Female-Specific Factors and Psychosocial Factors for the Risk of Stroke in Women Under 50

Background and Objectives: Female-specific factors and psychosocial factors may be important in the prediction of stroke but are not included in prediction models that are currently used. We investigated whether addition of these factors would improve the performance of prediction models for the risk of stroke in women younger than 50 years.Methods: We used data from the Stichting Informatievoorziening voor Zorg en Onderzoek, population-based, primary care database of women aged 20-49 years without a history of cardiovascular disease. Analyses were stratified by 10-year age intervals at cohort entry. Cox proportional hazards models to predict stroke risk were developed, including traditional cardiovascular factors, and compared with models that additionally included female-specific and psychosocial factors. We compared the risk models using the c-statistic and slope of the calibration curve at a follow-up of 10 years. We developed an age-specific stroke risk prediction tool that may help communicating the risk of stroke in clinical practice.Results: We included 409,026 women with a total of 3,990,185 person-years of follow-up. Stroke occurred in 2,751 women (incidence rate 6.9 [95% CI 6.6-7.2] per 10,000 person-years). Models with only traditional cardiovascular factors performed poorly to moderately in all age groups: 20-29 years: c-statistic: 0.617 (95% CI 0.592-0.639); 30-39 years: c-statistic: 0.615 (95% CI 0.596-0.634); and 40-49 years: c-statistic: 0.585 (95% CI 0.573-0.597). After adding the female-specific and psychosocial risk factors to the reference models, the model discrimination increased moderately, especially in the age groups 30-39 (Δc-statistic: 0.019) and 40-49 years (Δc-statistic: 0.029) compared with the reference models, respectively.Discussion: The addition of female-specific factors and psychosocial risk factors improves the discriminatory performance of prediction models for stroke in women younger than 50 years.</p

Added Predictive Value of Female-Specific Factors and Psychosocial Factors for the Risk of Stroke in Women Under 50

Background and Objectives: Female-specific factors and psychosocial factors may be important in the prediction of stroke but are not included in prediction models that are currently used. We investigated whether addition of these factors would improve the performance of prediction models for the risk of stroke in women younger than 50 years.Methods: We used data from the Stichting Informatievoorziening voor Zorg en Onderzoek, population-based, primary care database of women aged 20-49 years without a history of cardiovascular disease. Analyses were stratified by 10-year age intervals at cohort entry. Cox proportional hazards models to predict stroke risk were developed, including traditional cardiovascular factors, and compared with models that additionally included female-specific and psychosocial factors. We compared the risk models using the c-statistic and slope of the calibration curve at a follow-up of 10 years. We developed an age-specific stroke risk prediction tool that may help communicating the risk of stroke in clinical practice.Results: We included 409,026 women with a total of 3,990,185 person-years of follow-up. Stroke occurred in 2,751 women (incidence rate 6.9 [95% CI 6.6-7.2] per 10,000 person-years). Models with only traditional cardiovascular factors performed poorly to moderately in all age groups: 20-29 years: c-statistic: 0.617 (95% CI 0.592-0.639); 30-39 years: c-statistic: 0.615 (95% CI 0.596-0.634); and 40-49 years: c-statistic: 0.585 (95% CI 0.573-0.597). After adding the female-specific and psychosocial risk factors to the reference models, the model discrimination increased moderately, especially in the age groups 30-39 (Δc-statistic: 0.019) and 40-49 years (Δc-statistic: 0.029) compared with the reference models, respectively.Discussion: The addition of female-specific factors and psychosocial risk factors improves the discriminatory performance of prediction models for stroke in women younger than 50 years.</p

Effectiveness of a Self-Management Intervention to Promote an Active Lifestyle in Persons With Long-Term Spinal Cord Injury: The HABITS Randomized Clinical Trial

Background. Most people with long-term spinal cord injury (SCI) have a very inactive lifestyle. Higher activity levels have been associated with health benefits and enhanced quality of life. Consequently, encouraging an active lifestyle is important and behavioral interventions are needed to establish durable lifestyle changes. Objective. The Healthy Active Behavioral Intervention in SCI (HABITS) study was aimed to evaluate the effectiveness of a structured self-management intervention to promote an active lifestyle in inactive persons with long-term SCI. Methods. This assessor-blinded randomized controlled trial was conducted at 4 specialized SCI units in the Netherlands. Sixty-four individuals with long-term SCI (>10 years), wheelchair-user and physically inactive, were included. Participants were randomized to either a 16-week self-management intervention consisting of group meetings and individual counseling and a book, or to a control group that only received information about active lifestyle by one group meeting and a book. Measurements were performed at baseline, 16 weeks, and 42 weeks. Primary outcome measures were self-reported physical activity and minutes per day spent in wheelchair driving. Secondary outcomes included perceived behavioral control (exercise self-efficacy, proactive coping), stages of change concerning exercise, and attitude toward exercise. Results. Mixed models analyses adjusted for age, sex, level of SCI, time since injury, baseline body mass index, and location did not show significant differences between the intervention and control groups on the primary and secondary outcomes (P ≥.05). Conclusions. A structured 16-week self-management intervention was not effective to change behavior toward a more active lifestyle and to improve perceived behavioral control, stages of change, and attitude

Classification of Molecular Subtypes of High-Grade Serous Ovarian Cancer by MALDI-Imaging.

Despite the correlation of clinical outcome and molecular subtypes of high-grade serous ovarian cancer (HGSOC), contemporary gene expression signatures have not been implemented in clinical practice to stratify patients for targeted therapy. Hence, we aimed to examine the potential of unsupervised matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) to stratify patients who might benefit from targeted therapeutic strategies. Molecular subtyping of paraffin-embedded tissue samples from 279 HGSOC patients was performed by NanoString analysis (ground truth labeling). Next, we applied MALDI-IMS paired with machine-learning algorithms to identify distinct mass profiles on the same paraffin-embedded tissue sections and distinguish HGSOC subtypes by proteomic signature. Finally, we devised a novel approach to annotate spectra of stromal origin. We elucidated a MALDI-derived proteomic signature (135 peptides) able to classify HGSOC subtypes. Random forest classifiers achieved an area under the curve (AUC) of 0.983. Furthermore, we demonstrated that the exclusion of stroma-associated spectra provides tangible improvements to classification quality (AUC = 0.988). Moreover, novel MALDI-based stroma annotation achieved near-perfect classifications (AUC = 0.999). Here, we present a concept integrating MALDI-IMS with machine-learning algorithms to classify patients according to distinct molecular subtypes of HGSOC. This has great potential to assign patients for personalized treatment