Tag: pubmed

Appl Neuropsychol Adult. 2026 Apr 30:1-12. doi: 10.1080/23279095.2026.2655334. Online ahead of print.

ABSTRACT

INTRODUCTION: Recently, research has focused on understanding the assessment and management of Parkinson’s Disease Mild Cognitive Impairment (PD-MCI) (Svenningsson et al., 2012). The primary aim of this two-phase study was to develop a novel cognitive assessment tool, Par-Cog (Parkinson’s Cognition) designed to evaluate PD-MCI.

METHODS: In Phase 1, 20 experts(including Neurologists, Geriatricians, Neuropsychologists, and PD Nurses) were recruited via social media and anonymously completed a survey on Qualtrics, providing feedback on the acceptability and validity of the Par-Cog. The qualitative data were analyzed using the content analysis method proposed by Elo & Kyngäs, 2008, while descriptive statistics analyzed the quantitative data. Phase 2 included 100 cognitively healthy participants from the British Isles, aged between 50 and 79 years, who were randomly assigned to either Group A or Group B (alternating, consecutive order for completing the Par-Cog and Addenbrookes, ACE-III) using Zoom.

RESULTS: In Phase 1, the Par-Cog demonstrated strong face and content validity, with high acceptability reported by experts, particularly Neuropsychologists. In Phase 2, the total and 5 domain Par-Cog scores were normally distributed, showing no floor effects. Significant ceiling effects were found for language and visuospatial scores. Mean-based percentiles were calculated, with Pearson’s correlation and regression analyses revealing significant relationships between age and education with Par-Cog scores (p <.05) except for visuospatial scores. Significant correlations were found between ACE-III and Par-Cog attention, memory, and executive functioning scores (convergent validity, p < .05). Bland Altman plots indicated good agreement between Par-Cog and ACE-III scores, and the internal consistency for Par-Cog total (α = 0.70), memory (α = .60) and executive functioning (α = 0.82) scores were deemed acceptable. The administration of the test did not statistically influence Par-Cog scores (M =.51, 95% CI [-5.78, 4.74], t(98)= -1.95, p= .835).

CONCLUSION: Although the Par-Cog is still in the early stages of development, this study indicates that it serves as an effective remote assessment tool for evaluating PD-MCI, with constructs of acceptability, validity and reliability examined.

PMID:42060784 | DOI:10.1080/23279095.2026.2655334

Int J Older People Nurs. 2026 May;21(3):e70077. doi: 10.1111/opn.70077.

ABSTRACT

BACKGROUND: Most older adults with disabilities in China and across Eastern Asian prefer to age in place, relying on home- and community-based care. Their family caregivers frequently encounter significant challenges, including a pronounced lack of knowledge and skills for providing daily living assistance, highlighting a critical need for accessible, practical training. Furthermore, existing community-based support programmes for caregivers often fail to incorporate an integrated family perspective. This oversight neglects the crucial dynamics and internal interactions within the family unit, which are fundamental to the overall adaptation and resilience of the entire family system.

OBJECTIVE: This study aims to develop a nurse-led, family-oriented resilience intervention programme for caregivers of older adults with disabilities. The programme is designed to enhance caregivers’ practical competencies and to strengthen overall family adaptation within the context of Chinese community settings.

METHOD: We followed the Medical Research Council (MRC) framework for developing and evaluating complex interventions to guide the development process. This involved integrating empirical evidence from our prior studies, identifying relevant theories of family resilience, and validating the preliminary intervention content. We employed a two-round Delphi method with an expert panel to validate the initial programme draft. For each proposed activity, we calculated the coefficient of variation (CV) and Kendall’s coefficient of concordance (Kendall’s W) to assess expert consensus.

RESULT: The two-round Delphi consultation yielded high positive and authority coefficients. In the first round, the mean importance scores for items ranged from 4.19 to 4.96 (overall mean 4.77 ± 0.21), with a coefficient of variation (CV) between 0.04 and 0.16 and Kendall’s W was statistically significant (p < 0.01). In the second round, scores ranged from 4.16 to 4.96 (overall mean 4.82 ± 0.19), with a CV between 0.04 and 0.15, and a significant Kendall’s W (p < 0.01). Based on this expert feedback, we refined the intervention into an 8-week programme, delivered via weekly home visits, integrating two core components: caregiving skill and family resilience. The weekly themes are (1) Getting to know each other; (2) I am not fighting alone (cleaning care and coping, social support for caregivers); (3) Thank you, embrace you (family resilience and internal support); (4) Love flows through communication (dietary care and coping, family communication and coping); (5) Riding the wind and waves together (excretion care and coping, social support for peers); (6) Community with me (mobile care and coping, social support for community); (7) Supplementing energy (safety protection and basic first aid, social support for external systems); and (8) Radiating the caregiver’s radiance (individual self-resilience and self-support).

CONCLUSION: Guided by the MRC framework, we developed a theory-driven, culturally appropriate, nurse-led and family-oriented resilience intervention for caregivers of older adults with disabilities. The program’s flexible delivery allows adaptation to local resources and caregiver needs, help caregivers overcome practical challenges and enhance family resilience. Future research should utilize a three-arm randomized controlled trial to evaluate the feasibility, acceptability and preliminary effectiveness of this complex intervention.

IMPLICATIONS FOR PRACTICE: This nurse-led, family-oriented resilience intervention offers a practical, home-based training programme that equips family caregivers of older adults with disabilities with essential caregiving skills and strategies to strengthen family adaptation, thereby supporting the implementation of community-based aged care services in China and similar Eastern Asian contexts.

PMID:42060783 | DOI:10.1111/opn.70077

J Am Chem Soc. 2026 Apr 30. doi: 10.1021/jacs.6c05446. Online ahead of print.

ABSTRACT

Photochemical upconversion usually relies on intermolecular energy transfer between a sensitizer and an annihilator, followed by triplet-triplet annihilation between two annihilator molecules. Here, we depart from both of these fundamental principles and report upconversion in single molecules via a largely unexplored annihilation process involving doublet and triplet excited states. This approach is independent of diffusion, reduces energy losses by eliminating intersystem crossing and bimolecular triplet-triplet energy transfer, and offers more favorable spin statistics than conventional triplet-triplet annihilation. The molecular design integrates three different excited states: a red-light absorbing doublet state on an Fe^III carbene complex, a long-lived dark triplet state localized on a perylene unit linked covalently to the Fe^III carbene, and a blue fluorescent singlet state on the perylene. By varying the number of attached perylene units from 1 to 4 we gain mechanistic insight and identify the operating regime of unimolecular upconversion that functions not only in fluid solution but also in polymers at room temperature and in frozen glasses at 77 K. Beyond providing a design strategy for diffusion-independent future upconversion architectures, this work establishes unimolecular doublet-triplet annihilation as a fundamentally distinct upconversion concept with strategic advantages over conventional approaches.

PMID:42060771 | DOI:10.1021/jacs.6c05446

Science. 2026 Apr 30;392(6797):506-511. doi: 10.1126/science.aea9297. Epub 2026 Apr 30.

ABSTRACT

How far does peer influence spread through social networks before dissipating? This study investigates the diffusion of smoking behavior in adolescent friendship networks using longitudinal data from two schools (n = 3154 students) in the National Longitudinal Study of Adolescent to Adult Health. Using Stochastic Actor-Oriented Models, we simulate interventions targeting heavy smokers using various strategies (random, in-degree, eigenvector centrality) and coverage (10 to 100%). A new exponential decay model quantifies influence attenuation, revealing indirect peer influences, or spillover effects, up to three steps from targets. Targeting 10 to 30% of central individuals maximizes smoking reductions, but gains plateau beyond 40 to 50% owing to network saturation. In our analyses, the denser network exhibits broader diffusion and slower decay than the larger, sparser network. This decay metric optimizes intervention design across diverse network structures.

PMID:42060764 | DOI:10.1126/science.aea9297

Proc Natl Acad Sci U S A. 2026 May 5;123(18):e2525790123. doi: 10.1073/pnas.2525790123. Epub 2026 Apr 30.

ABSTRACT

Contemporary genomic studies of complex traits, such as genome-wide association studies and polygenic index (PGI) analyses, frequently include the principal components of the genotype matrix (PCs) among their adjustments for population stratification. In this paper, we explore the extent to which we may be discounting direct genetic effects by adjusting for PCs. Using family-based models that control for parental genotype in the UK Biobank, we find that PCs capture direct genetic effects on all nine phenotypes we tested. These effects are generally small, and extremely similar to the population effects of the same PCs. This suggests that PC adjustment indeed diminishes, albeit very slightly, signals of direct genetic effects. Furthermore, we find that adjusting for PCs does not meaningfully alter estimates of the effect of the current PGIs within families. Our findings suggest that, for the phenotypes and populations studied here, direct genetic effects captured by PCs are modest, and adjusting for PCs does not seem to lead to meaningful attenuation in PGI estimates.

PMID:42060716 | DOI:10.1073/pnas.2525790123

Indian J Ophthalmol. 2026 May 1;74(5):690-697. doi: 10.4103/IJO.IJO_3152_25. Epub 2026 Apr 29.

ABSTRACT

Anti-vascular endothelial growth factor (anti-VEGF) therapy is the mainstay of management for diabetic macular edema (DME), but marked variability in response, high injection frequency, and cumulative treatment burden highlight the need for tools that can individualize treatment beyond protocol-driven regimens. Artificial intelligence (AI) offers a pathway toward more individualized risk stratification and prognostic support primarily by capturing statistical associations rather than biological mechanisms. Deep learning systems have achieved great accuracy in detecting diabetic retinopathy (DR) and DME. Several autonomous DR/DME screening solutions are in clinical use. Recent advances have applied supervised machine learning, convolutional neural networks, generative adversarial networks, and ensemble methods to multimodal data from fundus images, baseline and follow-up optical coherence tomography (OCT), along with clinical and biochemical data, to classify likely responders and non-responders. These models automatically quantify and track imaging biomarkers to accurately predict central subfield thickness and vision outcomes after loading doses, and estimate future injection burden. AI-driven decision-support tools analyze vast amounts of patient data, treatment histories, and integrate multimodal data, including fundus images, OCT images, and systemic data to provide recommendations for optimal treatment and follow-up, tailored to each individual profile. The AI systems can potentially generate individualized risk and response profiles that can support decisions on initiating therapy, choosing between agents, tailoring treat-and-extend intervals, and timing switches to steroids or combination strategies. However, issues of generalizability, transparency, workflow integration, and ethical deployment need to be systematically addressed. AI-enabled decision support for patient selection and treatment response prediction is poised to become an integral component of anti-VEGF therapy.

PMID:42060353 | DOI:10.4103/IJO.IJO_3152_25

Traffic Inj Prev. 2026 Apr 30:1-13. doi: 10.1080/15389588.2026.2650661. Online ahead of print.

ABSTRACT

OBJECTIVE: This study aims to investigate the impact of combined fog and nighttime conditions on drivers’ cognitive load during tunnel approach, as reflected through fixation behavior. Specifically, it examines how these compounded adverse conditions influence visual attention patterns, including fixation duration, frequency, and spatial dispersion.

METHODS: A real-world driving experiment was conducted with 30 licensed drivers on the Xinjin Expressway. Eye movement data were collected using a Dikablis Pro eye tracker across four environmental scenarios: clear-day, foggy-day, clear-night, and foggy-night. The analysis focused on the tunnel approach zone, defined as the 10-s travel distance preceding the tunnel portal. Dependent variables included fixation duration, fixation frequency, horizontal fixation deviation, and vertical fixation deviation. One-way ANOVA and Tukey HSD post-hoc tests were employed to compare these metrics across scenarios.

RESULTS: The results revealed systematic variations in fixation behavior with increasing environmental complexity. Fixation duration was longest under foggy-night conditions (689.82 ± 30.4 ms) and shortest under clear-day conditions (325.59 ± 34.52 ms). Fixation frequency decreased progressively, with the highest rate in clear-day conditions (2.85 ± 0.18 Hz) and the lowest in foggy-night conditions (1.55 ± 0.17 Hz). Horizontal fixation deviation was largest in clear-day conditions (18.93 ± 2.91°) and smallest in foggy-night conditions (6.08 ± 1.68°), indicating lateral gaze constriction. Conversely, vertical fixation deviation increased significantly under adverse conditions, peaking in foggy-night scenarios (26.21 ± 3.74°), suggesting compensatory vertical scanning. All pairwise comparisons between scenarios were statistically significant (p < 0.01).

CONCLUSIONS: The combined effects of fog and nighttime conditions significantly elevate drivers’ cognitive load during tunnel approaches, manifesting as prolonged information processing, reduced attentional shifting, lateral visual field narrowing, and compensatory vertical search. These findings confirm the sensitivity of fixation-based metrics as indicators of cognitive load under compounded environmental stressors. The study provides empirical evidence for developing context-aware safety interventions, such as optimized tunnel lighting, adaptive traffic management, and enhanced driver assistance systems, tailored to mitigate cognitive overload in high-risk driving scenarios.

PMID:42060340 | DOI:10.1080/15389588.2026.2650661

J Glob Health. 2026 Apr 30;16:04144. doi: 10.7189/jogh.16.04144.

ABSTRACT

BACKGROUND: While there was a global shift in social interaction and alcohol consumption during the COVID-19 pandemic, their associations with changes in crime rates remain underexplored. We aimed to examine the associations between crime rates and alcohol use within the context of pandemic-related social distancing.

METHODS: We calculated crime rates across crime categories from 2011 to 2022 using crime statistics from the Korean National Police Agency. We estimated two linear regression models with the crime rate as the dependent variable. The first model examined the association of movie attendance (a proxy for social distancing) and the unemployment rate with crime rates. The second model additionally included per capita alcohol consumption to determine how the association between social distancing and crime rates was attenuated when accounting for alcohol use.

RESULTS: As of 2022, 19% of total crimes involved offenders under the influence of alcohol, with particularly high proportions in murder (64%), traffic accidents (47%), arson (32%), violence (28%), and rape (20%). Overall crime rates and offences committed under the influence of alcohol, which had steadily declined from 2011, fell sharply during the COVID-19 pandemic. Both alcohol consumption and social interaction declined during the pandemic. While the rates of overall crime, violence, rape, traffic accidents, and arson were initially associated with social contact, these associations were no longer significant after adjusting for alcohol consumption; instead, strong positive associations with alcohol consumption were observed. The rate of murder was not significantly associated with social contact, but exhibited a significant association only with alcohol consumption.

CONCLUSIONS: The concurrent declines in crime and alcohol consumption, along with the attenuating effect of alcohol in the relationship between social distancing and crime, suggest that addressing social drinking environments may be an effective strategy for reducing crime rates.

PMID:42060338 | DOI:10.7189/jogh.16.04144

J Chem Inf Model. 2026 Apr 30. doi: 10.1021/acs.jcim.5c02937. Online ahead of print.

ABSTRACT

Human β defensin type 3 (hBD-3) is recognized as one of the most intriguing antimicrobial peptides (AMPs) that holds the promise of solving drug resistance issues. hBD-3 can function (disruption of membrane integrity) in high salt environments, where most other AMPs fail. However, its functional mechanism at the molecular level remains elusive. To characterize its structure and dynamics during membrane crossing, long-time (a total of 57.0 μs) all-atom molecular dynamics simulations were conducted on hBD-3 monomers and dimers in both wild-type and analog (in which all three disulfide bonds are broken) forms that are embedded in four types of lipid membranes. Trajectory analysis was carried out using a statistical method─conformational dynamics analysis to calculate contact matrices and then principal component analysis (PCA) and linear discriminant analysis (LDA), in order to discern structural changes upon various physical and chemical perturbations. The result shows that the major collective coordinate primarily distinguishes between the wild-type and analog forms of hBD-3. For the hBD-3 monomer, the analog undergoes significant structural loss due to the lack of stabilizing disulfide bonds; salt exerts a nearly consistent effect on the contact degrees of freedom of the protein, whereas changes in lipid membrane composition have an insignificant effect. For the hBD-3 dimer, no consistent relationship between structure and salt concentration is indicated, and variations in the chemical composition of model bacterial membranes have a limited effect on its dynamics. These results suggest that the wild-type and analog forms of hBD-3 may employ different mechanisms when crossing bacterial membranes. The effect of salt on hBD-3 dynamics can be mitigated by the high net charge density of the protein. Additionally, the hBD-3 dimer can distinguish between model Gram-positive and Gram-negative membranes, whereas the monomer cannot. Overall, these findings provide unique insights into the structure, dynamics, and membrane-disrupting mechanism of hBD-3.

PMID:42060321 | DOI:10.1021/acs.jcim.5c02937

J Nurs Manag. 2026;2026(1):e2150047. doi: 10.1155/jonm/2150047.

ABSTRACT

PURPOSE: This study aimed to evaluate the effectiveness of a nurse-led educational program designed to improve nurse managers’ awareness, knowledge, and attitudes regarding climate change and its health impacts.

BACKGROUND/INTRODUCTION: Climate change is one of the most urgent global public health challenges, jeopardizing key determinants of health such as air quality, access to safe drinking water, food security, and adequate housing. As frontline healthcare providers, nurses are uniquely positioned to identify environmental health risks and promote climate-resilient healthcare practices. Despite this critical role, evidence suggests that nurses’ awareness and preparedness for climate-related health threats are insufficient. Therefore, strengthening climate literacy among nurse leaders is essential to enhance adaptation capacity in health systems.

METHODS: This study used a pretest-posttest experimental design with hospital-level randomization and included 108 nurse managers working in two public hospitals in Istanbul. Participants were randomly assigned to intervention and control groups. The study was conducted between March and June 2025, with data collection carried out between April and May 2025. Data were collected using a Descriptive Information Form and the Climate Change Awareness Scale (CCAS). The intervention group received 90 min of face-to-face training, including theoretical content, case-based learning, and interactive assessment, whereas the control group received a 90-min lecture after data collection on climate change and its health impacts, followed by a brief question-and-answer session. Measurements were taken at baseline, immediately after the intervention, and 1 month later. Data were analyzed using Friedman and Wilcoxon signed-rank tests.

RESULTS/FINDINGS: The intervention group demonstrated significant improvements in total and subscale CCAS scores at the postintervention time point compared with baseline and the control group (p < 0.05). Although a slight decrease was observed at the 1-month follow-up, scores remained higher than pretest levels. In the control group, although small differences were observed in certain subscales in the between-group comparisons, no statistically significant within-group changes were observed between the pretest, posttest, and follow-up scores.

DISCUSSION: The findings suggest that structured and nurse-led climate training for nurse managers has the potential to strengthen climate-related awareness and preparedness capacity.

CONCLUSION: Even short-term training increases nurse managers’ awareness of climate change and health.

TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT06905548.

PMID:42060318 | DOI:10.1155/jonm/2150047