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Abstract Marine carbon cycle processes are important for taking up atmospheric CO2 thereby reducing climate change. Net primary and export production are important pathways of carbon from the surface to the deep ocean where it is stored for millennia. Climate change can interact with marine ecosystems via changes in the ocean stratification and ocean circulation. In this study we use results from the Community Earth System Model version 2 (CESM2) to assess the effect of a changing climate on biological production and phytoplankton composition in the high latitude North Atlantic Ocean. We find a shift in phytoplankton type dominance from diatoms to small phytoplankton which reduces net primary and export productivity. Using a conceptual carbon‐cycle model forced with CESM2 results, we give a rough estimate of a positive phytoplankton composition‐atmospheric CO2 feedback of approximately 60 GtCO2/°C warming in the North Atlantic which lowers the 1.5° and 2.0°C warming safe carbon budgets.

BackgroundNotwithstanding the benefits of heat and moisture exchangers (HMEs) in both clinical research and practice, a gap exists between the optimal physiological humidification created through the nasal function and the humidification capacity of HMEs for patients after total laryngectomy. In this study, 5 new HMEs (Provox Life) specialized for situational use with improved humidification capacities were evaluated. ObjectiveThis study aims to evaluate the effectiveness of the existing HMEs, assess the potential effectiveness of the new HMEs, and elicit expert judgments on the new HMEs’ expected effectiveness and impact on health care use. MethodsFirst, a rapid literature review (RLR) was performed to identify evidence on the clinical outcomes, health outcomes, and complications of HMEs in patients who underwent laryngectomy. Second, semistructured interviews with German experts (n=4) were conducted to validate the findings of the RLR and identify reasonable expectations regarding the potential of the new HMEs. Third, a structured expert elicitation among German experts (n=19) was used to generate quantitative evidence on the expected effectiveness of the new HMEs in clinical and health outcomes. ResultsThe RLR (n=10) demonstrated that HME use by patients has advantages compared with no HME use concerning breathing resistance, tracheal dryness and irritation, mucus production and plugging, frequency of cough and forced expectorations, sleep quality, voice quality, use of physiotherapy, tracheobronchitis or pneumonia episodes, quality of life, and patient satisfaction. From the expert interviews and structured expert elicitation, it was found that, on average, experts expect that compared with the second-generation HMEs, the new HMEs will lead to a decrease in tracheal dryness or irritation (51%, SD 24%, of patients), mucus plug events (33%, SD 32%, of patients), mucus production (53%, SD 22%, of patients), physiotherapy (0.74, SD 0.70, days) and pulmonary infections (34%, SD 32%) and an increase or improvement in speech quality (25%, SD 23%, of patients), social contacts (13%, SD 18%), quality of life (33%, SD 30%), and patient satisfaction (44%, SD 30%). An improvement in breathing (53%, SD 28%, of patients) and shortness of breath (48%, SD 25%, of patients) was expected. The average number of daily cough periods and forced expectorations was expected to be 2.95 (SD 1.61) and 2.46 (SD 1.42), respectively. Experts expect that, on average, less than half of the patients will experience sleeping problems (48%, SD 22%) and psychosocial problems (24%, SD 20%). ConclusionsAccording to German experts, it is expected that the new HMEs with improved humidification levels will lead to additional (clinical) effectiveness on pulmonary health and an improved overall quality of life of patients compared with the currently available HMEs.

The identification of patient-specific disease mechanisms and druggable targets is crucial for precision medicine in glioblastoma. Here, the authors show that comparing patients-matched glioma-initiating cells with neural stem cells enables the discovery of patient-specific mechanisms of disease and the identification of effective drugs

There is an increased demand for motivated high school students to enter postsecondary STEM fields. Agriscience education is an innovative curriculum that can motivate students and spark interest in STEM. To recruit students to such programs, we must understand what motivates them. The purpose of this study was to determine how the secondary agriculture students conceptualized their motivation to learn agriscience. A descriptive-correlational research design was utilized with a modified version of the Science Motivation Questionnaire II (SMQ II) used as the survey instrument. Overall, students were found to have moderate levels of motivation in agriscience courses. Grade motivation and self-efficacy were found to be the motivational constructs that meant the most to students. Students were least motivated by self-determination. Getting an A and the chance to receive higher grades in their agriculture science courses were found to be the highest motivators. Researchers found that there were no significant correlations between gender or grade level and motivation to learn science. Females generally had higher motivation within self-determination and grade motivation than males. Additional research is needed in this area to determine what factors may exist that are preventing highly efficacious females from choosing STEM careers.

There are a number of key features which make olfaction difficult to study; subjective processes of odor detection, discrimination and identification, and individualistic odor hedonic perception and associated odor memories. In this systematic review we explore the role functional near-infrared spectroscopy (fNIRS) has played in understanding olfactory perception in humans. fNIRS is an optical neuroimaging technique able to measure changes in brain hemodynamics and oxygenation related to neural electrical activity. Adhering to PRISMA guidelines, results of this search found that generally the majority of studies involving healthy adult subjects observed increased activity in response to odors. Other population types were also observed, such as infants, individuals with autism, attention deficit hyperactivity disorder (ADHD), post-traumatic stress disorder (PTSD), mild cognitive impairment (MCI) and dysosmia. fNIRS coverage heavily favored the prefrontal cortex, temporal and parietal regions. This review finds that odor induced cortical activation is dependent on multiple factors, such as odorant type, gender and population type. This review also finds that there is room for improvement in areas such as participant diversity, use of wearable fNIRS systems, physiological monitoring and multi-distance channels.

Background: Workplace health promotion (WHP) interventions have limited effects on the health of employees with low socioeconomic position (SEP). This paper argues that this limited effectiveness can be partly explained by the methodology applied to evaluate the intervention, often a randomised controlled trial (RCT). Frequently, the desired outcomes of traditional evaluations may not match employees’—and in particular employees with low SEP—needs and lifeworld. Furthermore, traditional evaluation methodologies do not function well in work settings characterised by change resulting from internal and external developments. Objective: In this communication, responsive evaluation is proposed as an alternative approach to evaluating WHP interventions. Responsive evaluation’s potential added value for WHP interventions for employees with low SEP in particular is described, as well as how the methodology differs from RCTs. The paper also elaborates on the different scientific philosophies underpinning the two methodologies as this allows researchers to judge the suitability and quality of responsive evaluation in light of the corresponding criteria for good science.

The use of technology to facilitate remote patient monitoring and virtual care is desirable due to the challenges of providing healthcare during the COVID-19 pandemic and the need for more efficient and effective methods to care for the expanding older adult population. Further, the collection and sharing of patient generated health data (PGHD) through these technologies holds promise with respect to improving outcomes and reducing the cost of care by facilitating the early detection and treatment of cognitive and health problems. Despite the potential benefits of these technologies, their promise might be hampered by low rates of acceptance and adoption among older adults. In an online survey, we assessed community-dwelling older adults’ (N = 92) attitudes towards the use of wearable and mobile technologies for (1) predicting cognitive decline, (2) assisting with adherence to healthy activities, and (3) collecting self-report data to understand current and predict future health states. Participants generally agreed hypothetical technology solutions would be useful (M = 4.20, SD = 0.70 on a 1–5 agreement scale; 5 = “strongly agree”), that they were interested in learning more about these technologies (M = 4.04, SD = 0.74), and that they would be willing to adopt these technologies (M = 3.83, SD = 0.93), though attitudes varied. Although participants were generally positive toward these technologies, they were relatively neutral in terms of their agreement that privacy of generated data was a concern (M = 2.92, SD = 1.02). Privacy concerns were associated with lower interest and willingness to adopt. More positive general technology attitudes and higher mobile device proficiency were associated with greater acceptance and willingness to adopt these technologies. Finally, poorer self-rated health was related to negative attitudes toward these technologies. These findings highlight barriers and potential targets for intervention to increase uptake of these and similar technologies among older adults who may be reluctant to adopt remote monitoring technologies.

We describe a subset of glioblastoma, the most prevalent malignant adult brain tumour, harbouring a bias towards hypomethylation at defined differentially methylated regions. This epigenetic signature correlates with an enrichment for an astrocytic gene signature, which together with the identification of enriched predicted binding sites of transcription factors known to cause demethylation and to be involved in astrocytic/glial lineage specification, point to a shared ontogeny between these glioblastomas and astroglial progenitors. At functional level, increased invasiveness, at least in part mediated by SRPX2, and macrophage infiltration characterise this subset of glioblastoma.

As the population ages, the number of older adults experiencing mild cognitive impairment (MCI), Alzheimer's disease, and other forms of dementia will increase dramatically over the next few decades. Unfortunately, cognitive changes associated with these conditions threaten independence and quality of life. To address this, researchers have developed promising cognitive training interventions to help prevent or reverse cognitive decline and cognitive impairment. However, the promise of these interventions will not be realized unless older adults regularly engage with them over the long term, and like many health behaviors, adherence to cognitive training interventions can often be poor. To maximize training benefits, it would be useful to be able to predict when adherence lapses for each individual, so that support systems can be personalized to bolster adherence and intervention engagement at optimal time points. The current research uses data from a technology-based cognitive intervention study to recognize patterns in participants' adherence levels and predict their future adherence to the training program. We leveraged the feature learning capabilities of deep neural networks to predict patterns of adherence for a given participant, based on their past behavior. A separate, personalized model was trained for each participant to capture individualistic features of adherence. We posed the adherence prediction as a binary classification problem and exploited multivariate time series analysis using an adaptive window size for model training. Further, data augmentation techniques were used to overcome the challenge of limited training data and enhance the size of the dataset. To the best of our knowledge, this is the first research effort to use advanced machine learning techniques to predict older adults' daily adherence to cognitive training programs. Experimental evaluations corroborated the promise and potential of deep learning models for adherence prediction, which furnished highest mean F-scores of 75.5, 75.5, and 74.6% for the Convolution Neural Network (CNN), Long Short-Term Memory (LSTM) network, and CNN-LSTM models respectively.

Introduction: Pre-exposure prophylaxis (PrEP) is a key therapeutic strategy for HIV prevention. Descovy® is the most recently approved oral agent for PrEP. Despite availability, there continues to be suboptimal PrEP use among at-risk individuals. Social media platforms have a role in disseminating health information, to include education on PrEP. Material and methods: A content analysis was conducted of “tweets” posted on Twitter® during the initial year of Descovy’s FDA approval for PrEP. The coding schema captured content related to the indication, appropriate use, costs, and safety profile of Descovy. Results: Most tweets provided information on target population, dosing strategy, and side effects of Descovy. Information on costs and appropriate use was frequently missing. Conclusion: Health educators and providers should be aware of gaps in social media messaging concerning PrEP and should educate patients to ensure they are well informed when considering PrEP.

Patients treated for classic Hodgkin lymphoma (CHL) have a reported 13-fold increased risk of developing subsequent non-Hodgkin lymphoma (NHL). In light of the growing awareness of CHL mimickers, this study re-assesses this risk based on an in-depth pathology review of a nationwide cohort of patients diagnosed with CHL in the Netherlands (2006-2013) and explores the spectrum of CHL mimickers. Among 2,669 patients with biopsy-proven CHL, 54 were registered with secondary NHL. On review, CHL was confirmed in 25/54 patients. In six of these, the subsequent lymphoma was a primary mediastinal B-cell lymphoma/mediastinal gray zone lymphoma, biologically related to CHL and 19/25 were apparently unrelated B-cell NHL. In 29/54 patients, CHL was reclassified as NHL, including T-cell lymphomas with secondary Hodgkin-like B-blasts (n=15), Epstein Barr virus-positive diffuse large B-cell lymphoma (n=8), CD30+ T-cell lymphoma (n=3) and indolent B-cell proliferations (n=3). Higher age, disseminated disease at presentation, extensive B-cell marker expression and association with Epstein-Barr virus were identified as markers to alert for CHL mimickers. Based on these data, the risk of developing NHL after CHL treatment was re-calculated to 3.6-fold (standardized incidence ratio 3.61; confidence interval: 2.29-5.42). In addition, this study highlights the clinicopathological pitfalls leading to misinterpretation of CHL and consequences for the care of individual patients, interpretation of trials and epidemiological assessments.

Over the past few decades, researchers have argued that playing action video games can substantially improve cognitive abilities and enhance learning. However, consensus has not been reached regarding the mechanisms through which action game experience facilitates superior performance on untrained perceptually and cognitively demanding transfer tasks. We argue that analysis of behaviors engaged in during transfer task performance may provide key insights into answering this question. In the current investigation, we examined potential action game effects in the context of a complex psychomotor task, the Space Fortress (SF) game, that allows for the detailed examination of player behaviors beyond aggregate score reports. Performance (game score) was compared between action video game players (VGPs) and non-gamers (nVGPs) in two different control interface conditions (keyboard or joystick), followed by analyses of behaviors associated with superior performance. Against expectations, VGPs displayed superior performance only in the keyboard condition, suggesting that the action gamer advantage may not generalize to less-familiar control interfaces. Performance advantages were specifically associated with more efficient ship control behaviors by VGPs. Findings highlight how process-tracing approaches may provide insight into the nature of, and mechanisms producing, action gamers' advantages on learning untrained tasks.