Safety and efficacy of low-power pure-cut hot snare polypectomy for small nonpedunculated colorectal polyps compared with conventional resection methods: A propensity score matching analysis.

Objectives: Cold snare polypectomy (CSP) is widely performed for small colorectal polyps. However, small colorectal polyps sometimes include high-grade adenomas or carcinomas that require endoscopic resection with electrocautery. This study aimed to evaluate the efficacy and safety of a novel resection technique, hot snare polypectomy with low-power pure-cut current (LPPC-HSP) for small colorectal polyps, compared with CSP and conventional endoscopic mucosal resection (EMR). Methods: Records of patients who underwent CSP, EMR, or LPPC-HSP for nonpedunculated colorectal polyps less than 10 mm between April 2021 and March 2022 were retrospectively evaluated. We analyzed and compared the treatment outcomes of CSP and EMR with those of LPPC-HSP using propensity score matching. Results: After propensity score matching of 396 pairs, an analysis of CSP and LPPC-HSP indicated that LPPC-HSP had a significantly higher R0 resection rate (84% vs. 68%; p < 0.01). Delayed bleeding was observed in only two cases treated with CSP before matching. Perforation was not observed with either treatment. After propensity score matching of 176 pairs, an analysis of EMR and LPPC-HSP indicated that their en bloc and R0 resection rates were not significantly different (99.4% vs. 100%, p = 1.00; 79% vs. 81%, p = 0.79). Delayed bleeding and perforation were not observed with either treatment. Conclusions: The safety of LPPC-HSP was comparable to that of CSP. The treatment outcomes of LPPC-HSP were comparable to those of conventional EMR for small polyps. These results suggest that this technique is a safe and effective treatment for nonpedunculated polyps less than 10 mm.

A cortical field theory - dynamics and symmetries.

We characterise cortical dynamics using partial differential equations (PDEs), analysing various connectivity patterns within the cortical sheet. This exploration yields diverse dynamics, encompassing wave equations and limit cycle activity. We presume balanced equations between excitatory and inhibitory neuronal units, reflecting the ubiquitous oscillatory patterns observed in electrophysiological measurements. Our derived dynamics comprise lowest-order wave equations (i.e., the Klein-Gordon model), limit cycle waves, higher-order PDE formulations, and transitions between limit cycles and near-zero states. Furthermore, we delve into the symmetries of the models using the Lagrangian formalism, distinguishing between continuous and discontinuous symmetries. These symmetries allow for mathematical expediency in the analysis of the model and could also be useful in studying the effect of symmetrical input from distributed cortical regions. Overall, our ability to derive multiple constraints on the fields - and predictions of the model - stems largely from the underlying assumption that the brain operates at a critical state. This assumption, in turn, drives the dynamics towards oscillatory or semi-conservative behaviour. Within this critical state, we can leverage results from the physics literature, which serve as analogues for neural fields, and implicit construct validity. Comparisons between our model predictions and electrophysiological findings from the literature - such as spectral power distribution across frequencies, wave propagation speed, epileptic seizure generation, and pattern formation over the cortical surface - demonstrate a close match. This study underscores the importance of utilizing symmetry preserving PDE formulations for further mechanistic insights into cortical activity.

Beyond seen faults: Zero-shot diagnosis of power circuit breakers using symptom description transfer.

Power circuit breakers (CBs) are vital for the control and protection of power systems, yet diagnosing their faults accurately remains a challenge due to the diversity of fault types and the complexity of their structures. Traditional data-driven methods, although effective, require extensive labeled data for each fault class, limiting their applicability in real-world scenarios where many faults are unseen. This paper addresses these limitations by introducing symptom description transfer-based zero-shot fault diagnosis (SDT-ZSFD), a method that leverages zero-shot learning for fault diagnosis. Our approach constructs a fault symptom description (FSD) framework, which embeds a fault symptom layer between the feature layer and the label layer to facilitate knowledge transfer from seen to unseen fault classes. The method utilizes current and acceleration signals collected during CB operation to extract features. By applying sparse principal component analysis to these signals, we derive high-quality features that are mapped to the FSD framework, enabling effective zero-shot learning. Our method achieves a satisfactory recognition rate by accurately diagnosing unseen faults based on these symptoms. This approach not only overcomes the data scarcity problem but also holds potential for practical applications in power system maintenance. The SDT-ZSFD method offers a reliable solution for CB fault diagnosis and provides a foundation for future improvements in symptom-based zero-shot diagnostic mechanisms and algorithmic robustness.

Improving working memory by electrical stimulation and cross-frequency coupling.

Working memory (WM) is essential for the temporary storage and processing of information required for complex cognitive tasks and relies on neuronal theta and gamma oscillations. Given the limited capacity of WM, researchers have investigated various methods to improve it, including transcranial alternating current stimulation (tACS), which modulates brain activity at specific frequencies. One particularly promising approach is theta-gamma peak-coupled-tACS (TGCp-tACS), which simulates the natural interaction between theta and gamma oscillations that occurs during cognitive control in the brain. The aim of this study was to improve WM in healthy young adults with TGCp-tACS, focusing on both behavioral and neurophysiological outcomes. Thirty-one participants completed five WM tasks under both sham and verum stimulation conditions. Electroencephalography (EEG) recordings before and after stimulation showed that TGCp-tACS increased power spectral density (PSD) in the high-gamma region at the stimulation site, while PSD decreased in the theta and delta regions throughout the cortex. From a behavioral perspective, although no significant changes were observed in most tasks, there was a significant improvement in accuracy in the 14-item Sternberg task, indicating an improvement in phonological WM. In conclusion, TGCp-tACS has the potential to promote and improve the phonological component of WM. To fully realize the cognitive benefits, further research is needed to refine the stimulation parameters and account for individual differences, such as baseline cognitive status and hormonal factors.

Dietary intake, energy availability, and power in men collegiate gymnasts.

Introduction: The purpose was to examine the prevalence of low energy availability (LEA), explore dietary behaviors in men collegiate gymnasts (n = 14), and investigate the relationships between energy availability (EA), body composition, and plyometric performance. Methods: Body composition was measured using air displacement plethysmography. Lower- and upper-body peak power (PWRpeak) and modified reactive strength index (RSImod) were calculated from countermovement jump (CMJ) and plyometric push-up (PP) assessments. Energy expenditure was tracked over 3 days, while daily energy and macronutrient intake were recorded. EA was calculated and used to categorize athletes into LEA and non-LEA groups. Pearson correlation coefficients were used to examine relationships between EA, body composition, and performance metrics. Results: 85.7% of athletes (n = 12) exhibited LEA (20.98 ± 5.2 kcals/kg FFM), with non-LEA athletes (n = 2) marginally surpassing the <30 kcal/kg of fat-free mass (FFM) threshold (30.58 ± 0.2 kcals/kg FFM). The cohort (n = 14) consumed insufficient energy (30.5 ± 4.5 kcal/kg/day) and carbohydrates (3.7 ± 1.1 g/kg/day), resulting in LEA (22.36 ± 5.9 kcal/kg/FFM). EA was not correlated with body composition or performance metrics. Discussion: A high prevalence of LEA may exist in men gymnasts, largely due to a low relative energy and carbohydrate intake.

Cost of Using Laser Powder Bed Fusion to Fabricate a Molten Salt-to-Supercritial Carbon Dioxide Heat Exchanger for Concentrating Solar Power.

Advances in manufacturing technologies and materials are crucial to the commercial deployment of energy technologies. We present the case of concentrating solar power (CSP) with molten salt (MS) thermal storage, where low-cost, high-efficiency heat exchangers (HXs) are needed to achieve cost competitiveness. The materials required to tolerate the extreme operating conditions in CSP systems make it difficult or infeasible to produce them using conventional manufacturing processes. Although it is technically possible to produce HXs with adequate performance using additive manufacturing, specifically laser powder bed fusion (LPBF), here we assess whether doing so is cost-effective. We describe a process-based cost model (PBCM) to estimate the cost of fabricating a MS-to-supercritical carbon dioxide HX using LPBF. The PBCM is designed to identify modifications to designs, process choices, and manufacturing innovations that have the greatest effect on manufacturing cost. Our PBCM identified HX design and LPBF process modifications that reduced projected HX cost from $750 per kilo-Watt thermal (kW-th) ($8/cm3) to $350/kW-th ($6/cm3) using currently available LPBF technology, and down to $220/kW-th ($4/cm3) with improvements in LPBF technology that are likely to be achieved in the near term. The PBCM also informed a redesign of the HX design that reduced projected costs to $140-160/kW-th ($3/cm3).

Comprehensive review on the potential of ultrasound for blue food protein extraction, modification and impact on bioactive properties.

Food security for the increasing global population is a significant challenge of the current times particularly highlighting the protein deficiencies. Plant-based proteins could be considered as alternate source of the protein. The digestibility and PDCASS value of these proteins are still a concern. Blue proteins, the new approach of utilizing the proteins from aquatic sources could be a possible solution as it contains all the essential amino acids. However, the conjugation of these proteins with fats and glycogen interferes with their techno-functional properties and consequently their applicability. The application of power ultrasound for extraction and modification of these proteins from aquatic sources to break open the cellular structure, increase extractability, alter the protein structure and consequently provide proteins with higher bioavailability and bioactive properties could be a potential approach for their effective utilization into food systems. The current review focuses on the application of power ultrasound when applied as extraction treatment, alters the sulphite and peptide bond and modifies protein to elevated digestibility. The degree of alteration is influenced by intensity, frequency, and exposure time. The extracted proteins will serve as a source of essential amino acids. Furthermore, modification will lead to the development of bioactive peptides with different functional applications. Numerous studies reveal that blue proteins have beneficial impacts on amino acid availability, and subsequently food security with higher PDCAAS values. In many cases, converted peptides give anti-hypertensive, anti-diabetic, and anti-oxidant activity. Therefore, researchers are concentrating on ultrasound-based extraction, modification, and application in food and pharmaceutical systems.

Model-implied simulation-based power estimation for correctly specified and distributionally misspecified models: Applications to nonlinear and linear structural equation models.

Closed-form (asymptotic) analytical power estimation is only available for limited classes of models, requiring correct model specification for most applications. Simulation-based power estimation can be applied in almost all scenarios where data following the model can be estimated. However, a general framework for calculating the required sample sizes for given power rates is still lacking. We propose a new model-implied simulation-based power estimation (MSPE) method for the z-test that makes use of the asymptotic normality property of estimates of a wide class of estimators, the M-estimators, and give theoretical justification for the approach. M-estimators include maximum-likelihood, least squares estimates and limited information estimators, but also estimators used for misspecified models, hence, the new simulation-based power modeling method is widely applicable. The MSPE employs a parametric model to describe the relationship between power and sample size, which can then be used to determine the required sample size for a specified power rate. We highlight its performance in linear and nonlinear structural equation models (SEM) for correctly specified models and models under distributional misspecification. Simulation results suggest that the new power modeling method is unbiased and shows good performance with regard to root mean squared error and type I error rates for the predicted required sample sizes and predicted power rates, outperforming alternative approaches, such as the naïve approach of selecting a discrete selection of sample sizes with linear interpolation of power or simple logistic regression approaches. The MSPE appears to be a valuable tool to estimate power for models without an (asymptotic) analytical power estimation.

Ordinal regression models made easy: A tutorial on parameter interpretation, data simulation and power analysis.

Ordinal data such as Likert items, ratings or generic ordered variables are widespread in psychology. These variables are usually analysed using metric models (e.g., standard linear regression) with important drawbacks in terms of statistical inference (reduced power and increased type-1 error) and prediction. One possible reason for not using ordinal regression models could be difficulty in understanding parameters or conducting a power analysis. The tutorial aims to present ordinal regression models using a simulation-based approach. Firstly, we introduced the general model highlighting crucial components and assumptions. Then, we explained how to interpret parameters for a logit and probit model. Then we proposed two ways for simulating data as a function of predictors showing a 2 × 2 interaction with categorical predictors and the interaction between a numeric and categorical predictor. Finally, we showed an example of power analysis using simulations that can be easily extended to complex models with multiple predictors. The tutorial is supported by a collection of custom R functions developed to simulate and understand ordinal regression models. The code to reproduce the proposed simulation, the custom R functions and additional examples of ordinal regression models can be found on the online Open Science Framework repository ( https://osf.io/93h5j).

Job demands, control, social support and mental health in workers of thermal power plants and underground mines: A comparative study.

This descriptive study was conducted to compare the job demands, job control, social support and mental health status of thermal power plant and underground coal mine workers. 158 workers in thermal power plant and 162 workers in underground coal mine participated in the study. The results unearthed that thermal power plant workers had 2.3 times better mental health (p < 0.001 OR = 2.3 CI = 1.50-3.74) and 3.0 times lower job demands (p < 0.001 OR = 3.0 CI = 1.91-4.92) than coal mine workers. In the study, it was determined that mental health was positively affected as job control and social support increased in both thermal power plant and underground mine workers (p < 0.05); there was no significant relationship between job demands and mental health (p > 0.05). These results indicate that underground mine workers are at higher risk in terms of mental health and job demands than thermal power plant workers.

Submaximal eccentric resistance training increases serial sarcomere number and improves dynamic muscle performance in old rats.

The age-related loss of muscle mass is partly accounted for by the loss of sarcomeres in series, contributing to declines in muscle mechanical performance. Resistance training biased to eccentric contractions increases serial sarcomere number (SSN) in young muscle, however, maximal eccentric training in old rats previously did not alter SSN and worsened performance. A submaximal eccentric training stimulus may be more conducive to adaptation for aged muscle. The purpose of this study was to assess whether submaximal eccentric training can increase SSN and improve mechanical function in old rats. Twelve 32-month-old male F344/BN rats completed 4 weeks of submaximal (60% maximum) eccentric plantar-flexion training 3 days/week. Pre- and post-training, we assessed in-vivo maximum isometric torque at a stretched and neutral ankle angle, the passive torque-angle relationship, and the isotonic torque-velocity-power relationship. The soleus and medial gastrocnemius (MG) were harvested for SSN measurements via laser diffraction, with the untrained leg as a control. SSN increased 11% and 8% in the soleus and MG, respectively. Training also shifted optimal torque production towards longer muscle lengths, reduced passive torque 42%, and increased peak isotonic power 23%. Submaximal eccentric training was beneficial for aged muscle adaptations, increasing SSN, reducing muscle passive tension, and improving dynamic contractile performance.

Optogenetic targeting of cortical astrocytes selectively improves NREM sleep in an Alzheimer's disease mouse model.

Alzheimer's disease (AD) is a progressive neurodegenerative condition marked by memory impairments and distinct histopathological features such as amyloid-beta (Aß) accumulations. Alzheimer's patients experience sleep disturbances at early stages of the disease. APPswe/PS1dE9 (APP) mice exhibit sleep disruptions, including reductions in non-rapid eye movement (NREM) sleep, that contribute to their disease progression. In addition, astrocytic calcium transients associated with a sleep-dependent brain rhythm, slow oscillations prevalent during NREM sleep, are disrupted in APP mice. However, at present it is unclear whether restoration of circuit function by targeting astrocytic activity could improve sleep in APP mice. To that end, APP mice expressing channelrhodopsin-2 (ChR2) targeted to astrocytes underwent optogenetic stimulation at the slow oscillation frequency. Optogenetic stimulation of astrocytes significantly increased NREM sleep duration but not duration of rapid eye movement (REM) sleep. Optogenetic treatment increased delta power and reduced sleep fragmentation in APP mice. Thus, optogenetic activation of astrocytes increased sleep quantity and improved sleep quality in an AD mouse model. Astrocytic activity provides a novel therapeutic avenue to pursue for enhancing sleep and slowing AD progression.

Working in a relational way is everything: Perceptions of power and value in a drug policy-making network.

BACKGROUND: The development of drug policies has been a major focus for policy-makers across North America in light of the ongoing public health emergency caused by the overdose crisis. In this context, the current study examined stakeholders' experiences and perceptions of power and value in a drug policy-making process in a North American city using qualitative, questionnaire, and social network data. METHODS: We interviewed 18 people who participated in the development of a drug policy proposal between October 2021 and March 2022. They represented different groups and organizations, including government (n = 3), people who use drugs-led advocacy organizations (n = 5), other drug policy advocacy organizations (n = 5), research (n = 3) and police (n = 2). Most of them identified as men (n = 8) and white (n = 16), and their ages ranged between 30 and 80 years old (median = 50). Social network analysis questionnaires and semi-structured qualitative interviews were administered via Zoom. Social network data were analysed using igraph in R, and qualitative data were analysed using thematic analysis. The analyses explored perceptions of value and power within a drug policy-making network. RESULTS: The policy-making network showed that connections could be found across participants from different groups, with government officials being the most central. Qualitative data showed that inclusion in the network and centrality did not necessarily translate into feeling powerful or valued. Many participants were dissatisfied with the process despite having structurally advantageous positions or self-reporting moderately high quantitative value scores. Participants who viewed themselves as more valued acknowledged many process shortcomings, but they also saw it as more balanced or fair than those who felt undervalued. CONCLUSIONS: While participation can make stakeholders and communities feel valued and empowered, our findings highlight that inclusion, position and diversity of connections in a drug policy-making network do not, in and of itself, guarantee these outcomes. Instead, policy-makers must provide transparent terms of reference guidelines and include highly skilled facilitators in policy discussions. This is particularly important in policy processes that involve historical power imbalances in the context of a pressing public health emergency.

Subjective quasi-vector-based refraction with a conventional phoropter.

PURPOSE: To introduce a novel methodology for subjective refraction based on power vectors with a conventional phoropter. METHODS: A conventional phoropter was used to measure power vector components of refraction (M, J0 and J45) directly by using the sphere power (for M measurement) and the cylinder power combined with the Jackson cross-cylinders (for J0 and J45 measurements). Conventional subjective refraction was also performed, and this result was mathematically transformed into power vector notation for comparison purposes. Visual acuities with the conventional prescription and the quasi-vector-based prescription were compared. RESULTS: Refractive error from 40 healthy participants was measured by conventional and quasi-vector-based subjective refraction. No differences were found between methods for any of the power vector components of refraction (p > 0.21 in all cases). The visual acuity achieved with the prescriptions yielded similar values (p = 0.85). CONCLUSIONS: Subjective refraction can be measured directly in power vector notation using a conventional phoropter without any additional adaptation and computation.

Performance of the multi-U-style structure based flow field for polymer electrolyte membrane fuel cell.

The design of the reactant gas flow field structure in bipolar plates significantly influences the performance of proton exchange membrane fuel cells (PEMFCs). In this study, we introduced four innovative U-shaped flow field designs, namely: In-Out Multi-U, Out-In Multi-U, Distro In-Out Multi-U, and Distro Out-In Multi-U. To investigate the impact of these various flow fields on PEMFC performance, we conducted computational fluid dynamics (CFD) numerical simulations, validated through model experiments. Our results indicate that the Distro Out-In Multi-U flow field offers notable advantages compared to the conventional parallel flow field (CPFF) and conventional serpentine flow field (CSFF). These benefits include reduced inlet and outlet pressures, lower liquid water content, more uniform liquid water distribution, and a more even current density distribution. Furthermore, the Distro Out-In Multi-U design demonstrates improved efficiency, consuming less H2 (91.9%) than the CSFF while achieving a higher net power density output (10.1%). As a result, for the same power output, the Distro Out-In Multi-U utilizes only 83.5% of the H2 consumed by the CSFF. In summary, the U-shaped structured flow field exhibits superior output performance, enhanced energy efficiency, and improved resistance to flooding. These findings suggest that the U-shaped flow field design holds significant potential as a reactive flow field for PEMFCs.

Design of retrofit flue gas (CO2) scrubber for dependable clean energy at the Duvha Coal Power Plant.

The coal-fired power sector is facing unprecedented pressure due to the shift to low-carbon energy sources and the need to prevent climate change. It is imperative to incorporate advanced technologies into conventional coal-fired power plants to enhance their efficiency, flexibility, and environmental sustainability. One advantage of post-combustion CCS methods is that they may be retrofitted into power plants that are already in place. The goal of this work is to design a CO2 flue gas cleaning retrofit system that will meet the most stringent air quality regulations in an operational coal power station in Southern Africa. It will operate and expedite the removal of undesired gas (CO2) in order to attain ideal requirements for air quality in one of Southern Africa's current coal-fired power plants, the Duvha Coal Power Plant. This study is based on chemical absorption, and explores the mechanistic design of the scrubber, which was accomplished through simple computations and Ansys simulations. The approach for developing a wet CO2 scrubber and LSTG system is based on chemical absorption and is integrated with a pilot plant. The results of the parametric study provide a foundation for a comprehensive industrial system design for South Africa's coal-powered industry. The results show that the scrubber's cylinder height and diameter can be used for an LSTG system and are appropriate for CO2 gas flow and capture. The application of the suggested scrubber design and the LTSG's contributions will allow the coal power station to operate with minimal GHG emissions released into the atmosphere. Instead of shutting down coal power facilities, this cleaning system that completely absorbs CO2 emissions can be used to maintain a robust power infrastructure, rather than being phased out. This will boost the power plant's efficiency over its initial operating efficiency and benefit the nation's economy and the power industry.

Importance of different topographic, biometric, and retinal parameters for calculating IOL power.

The objective is to evaluate the parameters significantly related to calculating the power of the implanted lens and to determine the importance of different biometric, retina, and corneal aberrations variables. A retrospective cross-sectional observational study used a database of 422 patients who underwent cataract surgery at the Oftalvist Center in Almeria between January 2021 and December 2022. A random forest based on machine learning techniques was proposed to classify the importance of preoperative variables for calculating IOL power. Correlations were explored between implanted IOL power and the most important variables in random forests. The importance of each variable was analyzed using the random forest technique, which established a ranking of feature selections based on different criteria. A positive correlation was found with the random forest variables. Selection: axial length (AL), keratometry preoperative, anterior chamber depth (ACD), measured from corneal epithelium to lens, corneal diameter, lens constant, and astigmatism aberration. The variables coma aberration (p-value = 0,12) and macular thickness (p-value = 0,10) were almost slightly significant. In cataract surgery, the implanted IOL power is mainly correlated with axial length, anterior chamber depth, corneal diameter, lens constant, and preoperative keratometry. New variables such as astigmatism and anterior coma aberration and retina variables such as the preoperative central macular thickness could be included in the new generation of biometric formulas based on artificial intelligence techniques.

Are Wild Prey Sufficient for the Top Predators in the Lowland Protected Areas of Nepal?

A balanced equilibrium between carnivores and their prey is crucial for maintaining ecosystem sustainability. In this study, we applied the predator-prey power law equation to assess the balance between the biomass densities of carnivores and their wild prey within Nepal's lowland protected areas during 2013, 2018, and 2022. The estimated value of the power law exponent k for predator-prey biomass was 0.71 (95% CI = 0.39-1.05), indicating an approximate threefold increase in predator biomass density for every fivefold increase in prey biomass density. Consequently, this creates a systematically bottom-heavy predator-prey biomass pyramid. This finding, consistent with the k = 3/4 trophic biomass scaling across ecosystems, suggests that predator biomass is proportionally sustained by prey biomass, indicating a balance between top predators and their wild prey in Nepal's lowland protected areas. We further demonstrated it is possible to retain the overall power law exponent while jointly measuring intraguild competition between two predators with canonical correlation analysis. This understanding opens avenues for future research directed toward unraveling the factors that drive these consistent growth patterns in ecological communities.

Gender and couple status differences in advance care planning: a cross-sectional study.

Background: Past studies have shown mixed results on how gender and living with a spouse or partner impact advance care planning (ACP). Few if any have tested for the interaction between these two variables. Objective: We examined how gender and couple status interact to impact the use of ACP practices including written instructions, designating a durable power of attorney for healthcare (DPOAHC), and discussing one's decisions with others. Design: We used cross-sectional data taken from the Health and Retirement Study, a longitudinal study of adults over the age of 50 in the United States. Methods: Data are from 632 respondents who died between the 2016 core survey and the 2018 exit survey. Participants had completed the 2016 survey and had a proxy informant complete the 2018 exit survey after their death. Generalized linear mixed models were used to test for main effects and interactions. Results: Women were more likely than men to designate a DPOAHC and to discuss their wishes with others. Women living without a partner were more likely than men living without a partner and coupled households to discuss their wishes with family or others. Conclusion: Both gender and couple status are important variables associated with ACP practices. Healthcare providers may want to reach out to women living within a coupled household and men living without a partner to ensure that they know the benefits of ACP.

Are men and women living with a partner less likely to make plans for the type of medical treatment they prefer at the end of life? Why was the study done? To see if men and women living alone or with a partner were more likely to make plans for the type of medical treatment they preferred at the end of life. We examined whether they had written plans, designated someone to make decisions for them, or discussed their wishes with other family members or healthcare providers before they died. What did the researchers do? The research team used survey data from the Health and Retirement Study in the United States on 632 people who had completed a survey in 2016 and died within two years. A family member or friend completed a survey after the person's death reporting on their preferences for end-of-life medical care. What did the researchers find? Women were more likely than men to designate another person to make medical decisions for them and to discuss their wishes with others. Single women were more likely than single men and people living with a partner to discuss their wishes with family or others. What do the findings mean? Women living alone may be more likely to see the benefits of making their end-of-life medical care wishes known to others. Men living alone were the least likely to make their wishes known. Healthcare providers may want to keep these differences in mind when reaching out to patients to explain the benefits of making plans for medical treatments in the future.

Smartphone-Based Sit-to-Stand Analysis for Mobility Assessment in Middle Age.

Background and Objectives: Mobility can decline in middle age and growing evidence highlights the importance of assessing mobility at this stage of life. Smartphone-based accelerometry during sit-to-stand has been shown to identify mobility impairments, but its utility in detecting subtle mobility deterioration in middle age has not been tested. This study aimed to examine whether smartphone-based accelerometry data measured during sit-to-stand tests performed on a regular chair and a cushioned sofa could be useful for detecting subtle changes in mobility in middle age. Research Design and Methods: Twenty-three young (25.0 ± 2.5 years), 25 middle-aged (52.0 ± 5.2 years), and 17 older adults (70.0 ± 4.1 years) performed the 5-times sit-to-stand test on both a standard chair and a sofa. A smartphone attached to the participants' lower back was used to measure lower-limb muscle power, maximal vertical velocity (MVV) during rising, the duration of the total task and the subphase of transition from sitting to standing (SiToSt), and repetition variability using the dynamic time warping method. Results: Middle-aged adults had reduced lower-limb muscle power compared to young adults (5.25 ±â€…1.08 vs 6.19 ±â€…1.38 W/kg, p = .034), being more pronounced on the sofa (6.23 ±â€…1.61 vs 8.08 ±â€…2.17 W/kg, p = .004). Differences between middle-aged and young adults in terms of MVV (p = .011) and SiToSt duration (p = .038) were only detected on the sofa, and the middle-aged adults showed less variability compared to the older adults on the chair (p = .018). There was no difference in total task duration between the middle-aged group and the young or older adults in either condition. Discussion and Implications: Most common tests are limited in their ability to detect early mobility deterioration in midlife due to a ceiling effect. Our results, which show the potential of smartphone-based sit-to-stand assessment in detecting subtle mobility decline in midlife, could serve as a screening tool for this purpose.