Resiliency among older adults receiving lung cancer treatment (ROAR-LCT): A novel supportive care intervention for older adults with advanced lung cancer.

INTRODUCTION: Novel supportive care interventions designed for an aging population with lung cancer are urgently needed. We aimed to determine the feasibility of a novel supportive care physical therapy (PT) plus progressive muscle relaxation (PMR) intervention delivered to older adults with advanced lung cancer in the United States (US). MATERIALS AND METHODS: This clinical trial, Resiliency Among Older Adults Receiving Lung Cancer Treatment (ROAR-LCT: NCT04229381), recruited adults aged ≥60 years with unresectable stage III/IV non-small cell (NSCLC) or small cell lung cancer (SCLC) receiving cancer treatment at The James Thoracic Oncology Center (planned enrollment, N = 20). There were no exclusion criteria pertaining to performance status, laboratory values, prior cancer diagnoses, comorbidities, or brain metastases. Participants were evaluated by PT and psychology and given an exercise pedaler, resistance bands, a relaxation voice recording, and instructions at study initiation. Participants were evaluated in-person by PTs and psychologists at the start and end of the 12-session intervention, with the intervening sessions conducted via virtual health. Participants completed self-reported measures of functional status, symptoms, and mood longitudinally with the following instruments: EQ-5D-5L, Patient Health Questionnaire-9, and General Anxiety Disorder-7. PT assessments included the Short Physical Performance Battery (SPPB) and the two-minute walk test. Feasibility was defined as at least 60% of participants completing at least 70% of all intervention sessions. Optional gut microbiome samples and activity monitoring data (ActiGraph®) were also collected. RESULTS: The ROAR-LCT study concluded after consenting 22 patients. Among the 22 consented, 18 (81.8%) started the intervention; 11 participants (61.1%) completed at least 70% of all study sessions. All participants with SCLC completed the intervention. Reasons for withdrawal included progression of disease or hospitalization. The majority (88.9%) of patients who started were able to complete at least one virtual health session. Participants' functional status, SPPB, depression, and anxiety scores were stable from pre- to post-intervention. Participants who withdrew had worse baseline scores across domains. Seven microbiome and six ActiGraph® samples were collected. DISCUSSION: This is one of the first PT + PMR supportive care interventions using virtual health among older adults with advanced lung cancer to achieve feasibility in the US.

Baseline Frontoparietal Gray Matter Volume Predicts Executive Function Performance in Aging and Mild Cognitive Impairment at 24-Month Follow-Up.

Background: Executive dysfunction in mild cognitive impairment (MCI) has been associated with gray matter atrophy. Prior studies have yielded limited insight into associations between gray matter volume and executive function in early and late amnestic MCI (aMCI). Objective: To examine the relative importance of predictors of executive function at 24 months and relationships between baseline regional gray matter volume and executive function performance at 24-month follow-up in non-demented older adults. Methods: 147 participants from the Alzheimer's Disease Neuroimaging Initiative (mean age = 70.6 years) completed brain magnetic resonance imaging and neuropsychological testing and were classified as cognitively normal (n = 49), early aMCI (n = 60), or late aMCI (n = 38). Analyses explored the importance of demographic, APOEɛ4, biomarker (p-tau/Aß42, t-tau/Aß42), and gray matter regions-of-interest (ROI) variables to 24-month executive function, whether ROIs predicted executive function, and whether relationships varied by baseline diagnostic status. Results: Across all participants, baseline anterior cingulate cortex and superior parietal lobule volumes were the strongest predictors of 24-month executive function performance. In early aMCI, anterior cingulate cortex volume was the strongest predictor and demonstrated a significant interaction such that lower volume related to worse 24-month executive function in early aMCI. Educational attainment and inferior frontal gyrus volume were the strongest predictors of 24-month executive function performance for cognitively normal and late aMCI groups, respectively. Conclusions: Baseline frontoparietal gray matter regions were significant predictors of executive function performance in the context of aMCI and may identify those at risk of Alzheimer's disease. Anterior cingulate cortex volume may predict executive function performance in early aMCI.

Establishing the feasibility of exercise breaks during university lectures.

It is important that principles of laboratory-based studies with implications for academic performance be implemented in naturalistic learning environments to gauge their feasibility. Here, an adaptation of a laboratory-based study of exercise breaks during a single video lecture was implemented during large, in-person lectures at Ohio State University for the duration of a semester. The rationale for this approach was based on findings that research participants who took exercise breaks during a video lecture were more likely to be on task towards the end of the lecture and performed significantly better on a multiple choice exam. The current project had three goals: (1) Establish the feasibility of integrating student-led exercise breaks during in-person lectures in a large university setting (2) Provide practical guidelines for implementing exercise breaks during in-person lectures (3) Provide preliminary evidence of positive effects of exercise breaks in a higher-education setting. One to two student-led exercise breaks (5 min each) were implemented during each 80 min, in-person lecture for the duration of a semester in four upper level Psychology courses with student enrollment ranging from 20 to 93 students (total enrollment = 223 students). Students reported that the exercise breaks were a strength of the courses and a positive experience, including self-reported improvement in attention to lecture content. Self-reported quantitative data indicated that exercise breaks improved attention, increased course enjoyment, and enhanced peer engagement. Compared to other classes, the students preferred exercise breaks during lectures. The current approach establishes the feasibility of integrating exercise breaks in a large, in-person university lecture environment for the duration of a semester with preliminary data indicating a positive impact on attention, engagement, and enjoyment. Practical guidelines for implementing exercise breaks during in-person lectures are provided.

25 Years of thermomorphogenesis research: milestones and perspectives.

In 1998, Bill Gray and colleagues showed that warm temperatures trigger arabidopsis hypocotyl elongation in an auxin-dependent manner. This laid the foundation for a vibrant research discipline. With several active members of the 'thermomorphogenesis' community, we here reflect on 25 years of elevated ambient temperature research and look to the future.

Examining cross-sectional and longitudinal relationships between multidomain physical fitness metrics, education, and cognition in Black older adults.

A limited number of studies examine cognitive aging in Black or African American older adults. The purpose of this study was to explore the relationship between health-related fitness metrics, education, and cognition at baseline and over a 4-year follow-up in a sample of 321 Black or African American older adults in the Health and Retirement Study (HRS). Physical fitness was assessed with measures of gait speed, peak expiratory flow, grip strength, and body mass index. Global cognition was assessed with an adapted version of the Telephone Interview for Cognitive Status (TICS). Analyses of relative importance and hierarchical multiple regression were used to examine baseline cross-sectional relationships. Multiple logistic regression was used to examine prospective relationships with longitudinal cognitive status. Education was the strongest predictor of global cognition at baseline and follow-up. More years of education significantly increased the odds of maintaining cognitive status at 4-year follow-up. After accounting for education, gait speed was independently associated with baseline cognitive performance and accounted for additional variance. Grip strength, peak expiratory flow, and body mass index were not significantly associated with cognition. The results indicated that modifiable variables, including years of educational attainment and gait speed, were more strongly associated with global cognition than other modifiable variables including body mass index, grip strength, and peak expiratory flow. The lack of observed associations between other fitness variables and cognition may be attributable to the brief assessment methods implemented, which was necessitated by the large-scale, epidemiological approach of the HRS.

Partial Least Squares Regression Analysis of Alzheimer's Disease Biomarkers, Modifiable Health Variables, and Cognitive Change in Older Adults with Mild Cognitive Impairment.

BACKGROUND: Prior work has shown that certain modifiable health, Alzheimer's disease (AD) biomarker, and demographic variables are associated with cognitive performance. However, less is known about the relative importance of these different domains of variables in predicting longitudinal change in cognition. OBJECTIVE: Identify novel relationships between modifiable physical and health variables, AD biomarkers, and slope of cognitive change over two years in a cohort of older adults with mild cognitive impairment (MCI). METHODS: Metrics of cardiometabolic risk, stress, inflammation, neurotrophic/growth factors, and AD pathology were assessed in 123 older adults with MCI at baseline from the Alzheimer's Disease Neuroimaging Initiative (mean age = 73.9; SD = 7.6; mean education = 16.0; SD = 3.0). Partial least squares regression (PLSR)-a multivariate method which creates components that best predict an outcome-was used to identify whether these physiological variables were important in predicting slope of change in episodic memory or executive function over two years. RESULTS: At two-year follow-up, the two PLSR models predicted, respectively, 20.0% and 19.6% of the variance in change in episodic memory and executive function. Baseline levels of AD biomarkers were important in predicting change in both episodic memory and executive function. Baseline education and neurotrophic/growth factors were important in predicting change in episodic memory, whereas cardiometabolic variables such as blood pressure and cholesterol were important in predicting change in executive function. CONCLUSION: These data-driven analyses highlight the impact of AD biomarkers on cognitive change and further clarify potential domain specific relationships with predictors of cognitive change.

Posttraumatic stress symptom severity predicts cognitive decline beyond the effect of Alzheimer's disease biomarkers in Veterans.

Chronic stress is a risk factor for dementia but whether it explains unique variance in cognitive decline in older adults above Alzheimer's disease (AD) biomarkers is unknown. In a preclinical cohort of Vietnam Veterans, we examined the relationship between posttraumatic stress disorder (PTSD) symptom severity, AD biomarkers of beta-amyloid (Aß) and tau, and change in cognitive performance on two widely-used screeners, the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). Analyses indicated that PTSD symptom severity was associated with a greater decline on the MMSE (p < 0.04) and MoCA (p < 0.024) after adjusting for biomarkers of AD, notably on the attention scale of the MoCA and the memory index of the MMSE. These analyses survived multiple comparison corrections. Taken together, PTSD symptom severity is associated with accelerated cognitive decline. Treating PTSD should be considered instrumental to maintaining cognitive function as adults age.

PlantACT! - how to tackle the climate crisis.

Greenhouse gas (GHG) emissions have created a global climate crisis which requires immediate interventions to mitigate the negative effects on all aspects of life on this planet. As current agriculture and land use contributes up to 25% of total GHG emissions, plant scientists take center stage in finding possible solutions for a transition to sustainable agriculture and land use. In this article, the PlantACT! (Plants for climate ACTion!) initiative of plant scientists lays out a road map of how and in which areas plant scientists can contribute to finding immediate, mid-term, and long-term solutions, and what changes are necessary to implement these solutions at the personal, institutional, and funding levels.

Burning questions for a warming and changing world: 15 unknowns in plant abiotic stress.

We present unresolved questions in plant abiotic stress biology as posed by 15 research groups with expertise spanning eco-physiology to cell and molecular biology. Common themes of these questions include the need to better understand how plants detect water availability, temperature, salinity, and rising carbon dioxide (CO2) levels; how environmental signals interface with endogenous signaling and development (e.g. circadian clock and flowering time); and how this integrated signaling controls downstream responses (e.g. stomatal regulation, proline metabolism, and growth versus defense balance). The plasma membrane comes up frequently as a site of key signaling and transport events (e.g. mechanosensing and lipid-derived signaling, aquaporins). Adaptation to water extremes and rising CO2 affects hydraulic architecture and transpiration, as well as root and shoot growth and morphology, in ways not fully understood. Environmental adaptation involves tradeoffs that limit ecological distribution and crop resilience in the face of changing and increasingly unpredictable environments. Exploration of plant diversity within and among species can help us know which of these tradeoffs represent fundamental limits and which ones can be circumvented by bringing new trait combinations together. Better defining what constitutes beneficial stress resistance in different contexts and making connections between genes and phenotypes, and between laboratory and field observations, are overarching challenges.

Partial Least Squares Analysis of Alzheimer's Disease Biomarkers, Modifiable Health Variables, and Cognition in Older Adults with Mild Cognitive Impairment.

OBJECTIVES: To identify novel associations between modifiable physical and health variables, Alzheimer's disease (AD) biomarkers, and cognitive function in a cohort of older adults with Mild Cognitive Impairment (MCI). METHODS: Metrics of cardiometabolic risk, stress, inflammation, neurotrophic/growth factors, AD, and cognition were assessed in 154 MCI participants (Mean age = 74.1 years) from the Alzheimer's Disease Neuroimaging Initiative. Partial Least Squares analysis was employed to examine associations among these physiological variables and cognition. RESULTS: Latent variable 1 revealed a unique combination of AD biomarkers, neurotrophic/growth factors, education, and stress that were significantly associated with specific domains of cognitive function, including episodic memory, executive function, processing speed, and language, representing 45.2% of the cross-block covariance in the data. Age, body mass index, and metrics tapping basic attention or premorbid IQ were not significant. CONCLUSIONS: Our data-driven analysis highlights the significant relationships between metrics associated with AD pathology, neuroprotection, and neuroplasticity, primarily with tasks tapping episodic memory, executive function, processing speed, and verbal fluency rather than more basic tasks that do not require mental manipulation (basic attention and vocabulary). These data also indicate that biological metrics are more strongly associated with episodic memory, executive function, and processing speed than chronological age in older adults with MCI.

Root plasticity under abiotic stress.

Abiotic stresses increasingly threaten existing ecological and agricultural systems across the globe. Plant roots perceive these stresses in the soil and adapt their architecture accordingly. This review provides insights into recent discoveries showing the importance of root system architecture (RSA) and plasticity for the survival and development of plants under heat, cold, drought, salt, and flooding stress. In addition, we review the molecular regulation and hormonal pathways involved in controlling RSA plasticity, main root growth, branching and lateral root growth, root hair development, and formation of adventitious roots. Several stresses affect root anatomy by causing aerenchyma formation, lignin and suberin deposition, and Casparian strip modulation. Roots can also actively grow toward favorable soil conditions and avoid environments detrimental to their development. Recent advances in understanding the cellular mechanisms behind these different root tropisms are discussed. Understanding root plasticity will be instrumental for the development of crops that are resilient in the face of abiotic stress.

Machine learning identifies novel markers predicting functional decline in older adults.

The ability to carry out instrumental activities of daily living, such as paying bills, remembering appointments and shopping alone decreases with age, yet there are remarkable individual differences in the rate of decline among older adults. Understanding variables associated with a decline in instrumental activities of daily living is critical to providing appropriate intervention to prolong independence. Prior research suggests that cognitive measures, neuroimaging and fluid-based biomarkers predict functional decline. However, a priori selection of variables can lead to the over-valuation of certain variables and exclusion of others that may be predictive. In this study, we used machine learning techniques to select a wide range of baseline variables that best predicted functional decline in two years in individuals from the Alzheimer's Disease Neuroimaging Initiative dataset. The sample included 398 individuals characterized as cognitively normal or mild cognitive impairment. Support vector machine classification algorithms were used to identify the most predictive modality from five different data modality types (demographics, structural MRI, fluorodeoxyglucose-PET, neurocognitive and genetic/fluid-based biomarkers). In addition, variable selection identified individual variables across all modalities that best predicted functional decline in a testing sample. Of the five modalities examined, neurocognitive measures demonstrated the best accuracy in predicting functional decline (accuracy = 74.2%; area under the curve = 0.77), followed by fluorodeoxyglucose-PET (accuracy = 70.8%; area under the curve = 0.66). The individual variables with the greatest discriminatory ability for predicting functional decline included partner report of language in the Everyday Cognition questionnaire, the ADAS13, and activity of the left angular gyrus using fluorodeoxyglucose-PET. These three variables collectively explained 32% of the total variance in functional decline. Taken together, the machine learning model identified novel biomarkers that may be involved in the processing, retrieval, and conceptual integration of semantic information and which predict functional decline two years after assessment. These findings may be used to explore the clinical utility of the Everyday Cognition as a non-invasive, cost and time effective tool to predict future functional decline.

Acute Effects of High-intensity Resistance Exercise on Cognitive Function.

The purpose of the present study was to examine the influence of an acute bout of high-intensity resistance exercise on measures of cognitive function. Ten men (Mean ± SD: age = 24.4 ± 3.2 yrs; body mass = 85.7 ± 11.8 kg; height = 1.78 ± 0.08 m; 1 repetition maximum (1RM) = 139.0 ± 24.1 kg) gave informed consent and performed a high-intensity 6 sets of 10 repetitions of barbell back squat exercise at 80% 1RM with 2 minutes rest between sets. The Automated Neuropsychological Assessment Metrics (ANAM) was completed to assess various cognitive domains during the familiarization period, immediately before, and immediately after the high-intensity resistance exercise bout. The repeated measures ANOVAs for throughput scores (r·m-1) demonstrated significant mean differences for the Mathematical Processing task (MTH; p < 0.001, η2p = 0.625) where post hoc pairwise comparisons demonstrated that the post-fatigue throughput (32.0 ± 8.8 r·m-1) was significantly greater than the pre-fatigue (23.8 ± 7.4 r·m-1, p = 0.003, d = 1.01) and the familiarization throughput (26.4 ± 5.3 r·m-1, p = 0.024, d = 0.77). The Coded Substitution-Delay task also demonstrated significant mean differences (CDD; p = 0.027, η2p = 0.394) with post hoc pairwise comparisons demonstrating that the post-fatigue throughput (49.3 ± 14.4 r·m-1) was significantly less than the pre-fatigue throughput (63.2 ± 9.6 r·m-1, p = 0.011, d = 1.14). The repeated measures ANOVAs for reaction time (ms) demonstrated significant mean differences for MTH (p < 0.001, η2p = 0.624) where post hoc pairwise comparisons demonstrated that the post-fatigue reaction time (1885.2 ± 582.8 ms) was significantly less than the pre-fatigue (2518.2 ± 884.8 ms, p = 0.005, d = 0.85) and familiarization (2253.7 ± 567.6 ms, p = 0.009, d = 0.64) reaction times. The Go/No-Go task demonstrated significant mean differences (GNG; p = 0.031, η2p = 0.320) with post hoc pairwise comparisons demonstrating that the post-fatigue (285.9 ± 16.3 ms) was significantly less than the pre-fatigue (298.5 ± 12.1 ms, p = 0.006, d = 0.88) reaction times. High-intensity resistance exercise may elicit domain-specific influences on cognitive function, characterized by the facilitation of simple cognitive tasks and impairments of complex cognitive tasks.

On the evolution of plant thermomorphogenesis.

Plants have a remarkable capacity to acclimate to their environment. Acclimation is enabled to a large degree by phenotypic plasticity, the extent of which confers a selective advantage, especially in natural habitats. Certain key events in evolution triggered adaptive bursts necessary to cope with drastic environmental changes. One such event was the colonization of land 400-500 mya. Compared to most aquatic habitats, fluctuations in abiotic parameters became more pronounced, generating significant selection pressure. To endure these harsh conditions, plants needed to adapt their physiology and morphology and to increase the range of phenotypic plasticity. In addition to drought stress and high light, high temperatures and fluctuation thereof were among the biggest challenges faced by terrestrial plants. Thermomorphogenesis research has emerged as a new sub-discipline of the plant sciences and aims to understand how plants acclimate to elevated ambient temperatures through changes in architecture. While we have begun to understand how angiosperms sense and respond to elevated ambient temperature, very little is known about thermomorphogenesis in plant lineages with less complex body plans. It is unclear when thermomorphogenesis initially evolved and how this depended on morphological complexity. In this review, we take an evolutionary-physiological perspective and generate hypotheses about the emergence of thermomorphogenesis.

Body Mass Index and Polygenic Risk for Alzheimer's Disease Predict Conversion to Alzheimer's Disease.

Body mass index (BMI) is a risk factor for Alzheimer's disease (AD) although the relationship is complex. Obesity in midlife is associated with increased risk for AD, whereas evidence supports both higher and lower BMI increasing risk for AD in late life. This study examined the influence of individual differences in genetic risk for AD to further clarify the relationship between late-life BMI and conversion to AD. Participants included 52 individuals diagnosed as having mild cognitive impairment (MCI) at baseline who converted to AD within 24 months and 52 matched MCI participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. BMI was measured at baseline. Genetic risk for AD was assessed via genome-wide polygenic risk scores. Conditional logistic regression models were run to determine if BMI and polygenic risk predicted conversion to AD. Results showed an interaction between BMI and genetic risk, such that individuals with lower BMI and higher polygenic risk were more likely to convert to AD relative to individuals with higher BMI. These results remained significant after adjusting for cerebrospinal fluid biomarkers of AD. Exploratory sex-stratified analyses revealed this relationship only remained significant in males. These results show that higher genetic risk in the context of lower BMI predicts conversion to AD in the next 24 months, particularly among males. These findings suggest that genetic risk for AD in the context of lower BMI may serve as a prodromal risk factor for future conversion to AD.

Hot topic: Thermosensing in plants.

Plants alter their morphology and cellular homeostasis to promote resilience under a variety of heat regimes. Molecular processes that underlie these responses have been intensively studied and found to encompass diverse mechanisms operating across a broad range of cellular components, timescales and temperatures. This review explores recent progress throughout this landscape with a particular focus on thermosensing in the model plant Arabidopsis. Direct temperature sensors include the photosensors phytochrome B and phototropin, the clock component ELF3 and an RNA switch. In addition, there are heat-regulated processes mediated by ion channels, lipids and lipid-modifying enzymes, taking place at the plasma membrane and the chloroplast. In some cases, the mechanism of temperature perception is well understood but in others, this remains an open question. Potential novel thermosensing mechanisms are based on lipid and liquid-liquid phase separation. Finally, future research directions of high temperature perception and signalling pathways are discussed.

Genetic Risk for Alzheimer's Disease Moderates the Association Between Medial Temporal Lobe Volume and Episodic Memory Performance Among Older Adults.

BACKGROUND: A complex set of interactions between biological, genetic, and environmental factors likely underlies the development of Alzheimer's disease (AD). Identifying which of these factors is most associated with AD is important for early diagnosis and treatment. OBJECTIVE: We sought to examine genetic risk and structural brain volume on episodic memory in a sample of older adults ranging from cognitively normal to those diagnosed with AD. METHODS: 686 adults (55-91 years old) completed a 3T MRI scan, baseline cognitive assessments, and biospecimen collection through the Alzheimer's Disease Neuroimaging Initiative. Hierarchical linear regression analyses examined main and interaction effects of medial temporal lobe (MTL) volume and polygenic hazard score (PHS), indicating genetic risk for AD, on a validated episodic memory composite score. RESULTS: Genetic risk moderated the relationship between MTL volume and memory, such that individuals with high PHS and lower hippocampal and entorhinal volume had lower memory composite scores [ΔF (1,677) = 4.057, p = 0.044, ΔR2 = 0.002]. Further analyses showed this effect was driven by the left hippocampus [ΔF(1,677) = 5.256, p = 0.022, ΔR2 = 0.003] and right entorhinal cortex [ΔF (1,677) = 6.078, p = 0.014, ΔR2 = 0.003]. CONCLUSIONS: Among those with high genetic risk for AD, lower volume was associated with poorer memory. Results suggest that the interaction between AD genetic risk and MTL volume increases the likelihood for memory impairment among older adults. Results from this study suggest that genetic risk and brain volume should be considered key factors in tracking cognitive decline.