Tag: pubmed

Mol Biol Evol. 2026 Apr 30:msag111. doi: 10.1093/molbev/msag111. Online ahead of print.

ABSTRACT

At the molecular level, selection pressures often act on protein structural features, yet most evolutionary analyses remain confined to linear sequences. Early structure-informed approaches improved interpretability by mapping single-site metrics onto protein structures, and later methods introduced 3D sliding windows to capture spatially clustered signals missed by linear window approaches. These frameworks, however, are restricted to predefined statistics and narrowly defined 3D window types, limiting the scope of questions that can be addressed. We developed an R package, evo3D, as a new framework for structure-informed evolutionary analysis that supports a wide range of downstream statistics and scales from simple to complex structures. evo3D extracts structure-informed multiple sequence alignment subsets (spatial haplotypes), making the structure-informed unit of analysis directly available to users. The framework supports fixed-count and fixed-distance spatial windows, introduces residue and codon analysis modes, and extends to multimers, interfaces, and multiple structural models through a single wrapper, run_evo3d(). We demonstrate evo3D’s utility by performing an epitope-level diversity scan of Hepatitis C virus E1/E2 complex, identifying conserved spatial neighbourhoods missed by linear sliding windows, and by evaluating evo3D’s scalability on the octameric Chikungunya virus E1/E2 assembly. Importantly, evo3D formalises the core components of structure-informed analysis of molecular evolution and removes technical barriers. As a result, the framework streamlines the evaluation of evolutionary patterns directly within 3D structural contexts, and we anticipate its wide application in molecular evolution studies. The package is available at github.com/bbroyle/evo3D.

PMID:42060840 | DOI:10.1093/molbev/msag111

Eur J Endocrinol. 2026 Apr 30;194(5):567-577. doi: 10.1093/ejendo/lvag054.

ABSTRACT

OBJECTIVE: Dysnatremia is the most common electrolyte abnormality detected during hospitalizations and outpatient visits and is associated with adverse outcomes in older adults. However, data on its prevalence and incidence in community-dwelling older individuals remain limited. This study aimed to estimate the prevalence and incidence of dysnatremia in this population across 5 European countries (Austria, France, Germany, Portugal, and Switzerland).

DESIGN: Observational analysis of DO-HEALTH, a 3-year multicenter clinical trial including 2157 community-dwelling, generally healthy adults aged 70 years and older.

METHODS: Sodium blood levels were collected at baseline, 12, 24, and 36 months. Dysnatremia was defined as sodium levels <135 mmol/L (hyponatremia) or >145 mmol/L (hypernatremia). Baseline prevalence and 3-year incidence were estimated overall and by predefined subgroups based on sex, age, country of residence, body mass index, prevalent chronic conditions, polypharmacy, and use of thiazide-like diuretics.

RESULTS: At baseline, 2141 participants (99.3%) had available sodium data. The prevalence of dysnatremia was 3.4% (2.4% hyponatremia; 1.0% hypernatremia), with higher prevalence in participants aged ≥75 years (4.8%) and those using thiazide or thiazide-like diuretics (5.4%). Over 3 years, 150 participants (7.0%) experienced at least 1 episode of dysnatremia (3.8% hyponatremia; 3.2% hypernatremia). Higher incidence of dysnatremia was observed among participants living in Switzerland, using thiazide or thiazide-like diuretics, and with prevalent dysnatremia at baseline.

CONCLUSIONS: Dysnatremia, previously linked to adverse outcomes in older adults, was observed in a non-negligible proportion of generally healthy, community-dwelling older individuals. These findings provide valuable epidemiologic data and identify subgroups that may warrant closer clinical attention.

PMID:42060832 | DOI:10.1093/ejendo/lvag054

Indian J Pharmacol. 2026 May 1;58(3):239-249. doi: 10.4103/ijp.ijp_924_25. Epub 2026 May 1.

ABSTRACT

OBJECTIVES: The objective of the study was to assess the burden of polypharmacy and potentially inappropriate medications (PIMs) among geriatric patients and evaluate the impact of a structured deprescribing approach in these patients.

SUBJECTS AND METHODS: Elderly outpatients (≥60 years) with polypharmacy were included. Data on prescribed, over-the-counter (OTC), and traditional medicines were collected through a structured questionnaire and detailed patient interviews. Deprescribing was carried out using Sivagnanam G’s “S and S” approach (Seek, Screen, Save, Sever, Sensitize, and Supervise) adapted from Scott et al.

RESULTS: Among 385 participants, polypharmacy was prevalent in 182 participants (47.27%) with a mean of 6.5 drugs/prescription. Among participants with polypharmacy, PIMs were noted in 131 (72%) with an average of 1.64 PIMs identified per each inappropriate prescription. PIMs increased with an increase in the number of comorbidities and medication count. A total of 215 PIMs were identified and recommended for deprescribing. These were mainly drugs to be avoided in the elderly (34.88%), OTC PIMs (17.21%), traditional medicines (13.02%), and drug-drug interactions (9.77%). Deprescribing reduced the mean drug count per prescription to 4.86 with a potential to decrease adverse drug reactions by 16.4%, and also lowered daily prescription costs from INR 51.91 to INR 32.70, saving INR 576.42 per patient per month.

CONCLUSION: Polypharmacy and PIMs are widely prevalent among elderly patients, significantly increasing the risk of ADEs. Structured deprescribing effectively reduced medication burden, improved safety, and decreased healthcare costs. These findings highlight the need for routine deprescribing interventions to optimize geriatric medication management.

PMID:42060808 | DOI:10.4103/ijp.ijp_924_25

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