Category: Nevin Manimala

Support Care Cancer. 2026 Apr 23;34(5):455. doi: 10.1007/s00520-026-10688-w.

ABSTRACT

PURPOSE: Survivors of nasopharyngeal carcinoma (NPC) frequently suffer from a prolonged reduction in quality of life (QoL) following successful treatment. This study investigates the determinants of QoL among NPC survivors, with a focus on the temporal evolution post-treatment and the influence of socioeconomic and clinical factors.

METHODS: In this cross-sectional study, NPC patients who received treatment in the last 10 years and underwent follow-up at our institute from 2021 to 2023 were enrolled. They completed the EuroQol five-dimension (EQ-5D), World Health Organization Quality of Life-Brief (WHOQOL-BREF), Sinonasal Outcome Test 22 (SNOT-22), Eustachian Tube Dysfunction Questionnaire-7 (ETDQ-7), and Eating Assessment Tool-10 (EAT-10). Kernel smoothing techniques were applied to delineate the trends in QoL scores, and linear mixed models were utilized for evaluating the unadjusted and adjusted influences of household income and other predictors on QoL.

RESULTS: Out of 248 participants, 355 QoL evaluations were performed. Kernel-smoothed trajectories revealed that higher household income correlated with superior QoL scores throughout the majority of the post-treatment timeline. Although initial analyses showed that both higher household income and Karnofsky Performance Scale (KPS) scores were predictive of better generic and condition-specific QoL, the effect of income was attenuated upon adjusting for KPS in the multivariate analysis. Mediation analysis indicated that the association between income and QoL was partly mediated by the patients’ performance status.

CONCLUSION: Performance status is a pivotal mediator in the interplay between socioeconomic status and QoL outcomes in NPC survivors. These insights underscore the need for prospective studies to confirm these relationships.

PMID:42020823 | DOI:10.1007/s00520-026-10688-w

Pediatr Res. 2026 Apr 22. doi: 10.1038/s41390-026-04929-1. Online ahead of print.

ABSTRACT

BACKGROUND: Studies have reported conflicting findings regarding whether attention-deficit/hyperactivity disorder (ADHD) and neurostimulant (NS) treatment influence growth. The study aimed to evaluate the impact of ADHD and NS-treatment on adult height (AH), while accounting for individual expected height.

METHODS: Retrospective controlled cohort study using a nationwide healthcare provider database. Children born 1995-2003 were classified into: (1) untreated ADHD, (2) NS-treated ADHD, and (3) controls, followed until AH (girls ≥17 years, boys ≥19 years). Observed height index (OHI) = individual AH ÷ sex-specific mean AH of controls. Expected height index (EHI) = individual’s MPH ÷ sex-specific mean MPH of controls. Normalized height deviance (NHD) = OHI – EHI. ADHD impact = mean NHD(untreated ADHD) – mean NHD(controls). NS-treatment impact = mean NHD(NS-treated) – mean NHD(untreated ADHD). Significance was set at p ≤ 0.05. Effect sizes reported as Cohen’s d and f.

RESULTS: The cohort included 17,517 children with ADHD (5671 untreated; 11,846 NS-treated) and 47,258 controls. Girls’ ADHD impact was -0.28% (p < 0.001; Cohen’s d = 0.08), and in boys -0.11% (p = 0.12; Cohen’s d = 0.03). Girls’ NS-treatment impact was -0.26% (p = 0.005, Cohen’s d = 0.07), in boys -0.10% (p = 0.25).

CONCLUSIONS: ADHD and NS-treatment were associated with negligible effect sizes in girls and non-significant differences in boys.

IMPACT: After accounting for individual familial genetic height potential, ADHD and neurostimulant treatment are associated with statistically detectable but clinically negligible differences in adult height. Introduces normalized height deviance (NHD), a genetics-adjusted measure that distinguishes true growth effects from delayed maturation. Uses a large, nationwide cohort followed to adult height, resolving long-standing inconsistencies in prior growth studies. Provides reassurance that ADHD and neurostimulant treatment do not meaningfully impair final adult stature and supports informed clinical decision-making.

PMID:42020798 | DOI:10.1038/s41390-026-04929-1

Commun Chem. 2026 Apr 22. doi: 10.1038/s42004-026-02020-8. Online ahead of print.

ABSTRACT

Water-soluble functionalized fullerenes commonly referred to as fullerenols, fullerols or polyhydroxy fullerenes are widely used in photonics, catalysis, and biomedicine, yet their molecular structures have been assumed to consist solely of hydroxyl groups for nearly three decades. This assumption remains despite persistent mismatches between calculated and experimental vibrational and optical spectra as well as expected and observed chemical reactivity. Here we combine Fourier transform infrared (FTIR) and absorption (UV-Vis) spectroscopy, X-ray photoelectron spectroscopy (XPS), targeted chemical derivatization, and computational quantum chemistry to resolve this discrepancy. We show that only a polyoxy-fullerene architecture incorporating counterion-coordinated carbonyl and hemiketal groups alongside hydroxyls reproduces both the characteristic FTIR features and the experimental UV-Vis absorption profile. A purely hydroxylated fullerene model fails to capture the dominant FTIR band and asymmetric ultraviolet absorption. Oxime-formation experiments chemically validate the presence of carbonyl and hemiketal groups. This structural reassignment resolves long-standing inconsistencies in fullerene chemistry, corrects a pervasive misinterpretation in the literature, and establishes a framework for rationally tuning the optical and chemical properties of functionalized nanocarbons.

PMID:42020770 | DOI:10.1038/s42004-026-02020-8

Nature. 2026 Apr 22. doi: 10.1038/s41586-026-10549-w. Online ahead of print.

ABSTRACT

Large language models sometimes produce confident, plausible falsehoods (“hallucinations”), limiting their reliability^1,2. Prior work has offered numerous explanations and effective mitigations such as retrieval and tool use³, consistency-based self-verification⁴, and reinforcement learning from human feedback⁵. Nonetheless, the problem persists even in state-of-the-art language models^6,7. Here we show how next-word prediction and accuracy-based evaluations inadvertently reward unwarranted guessing. Initially, next-word pretraining creates statistical pressure toward hallucination even with idealized error-free data: using learning theory^8,9, we show that facts lacking repeated support in training data (such as one-off details) yield unavoidable errors, while recurring regularities (such as grammar) do not. Subsequent training stages aim to correct such errors. However, dominant headline metrics like accuracy systematically reward guessing over admitting uncertainty. To align incentives, we suggest two additions to the classic approach of adding error penalties to evaluations to control abstention^10,11. First, we propose “open-rubric” evaluations that explicitly state how errors are penalized (if at all), which test whether a model modulates its abstentions to stated stakes while optimizing accuracy. Second, since hallucination-specific benchmarks rarely make leaderboards¹², we suggest using open-rubric variants of existing evaluations, to reverse their guessing incentives. Reframing hallucination as an incentive problem opens a practical path toward more reliable language models.

PMID:42020757 | DOI:10.1038/s41586-026-10549-w

Nature. 2026 Apr 22. doi: 10.1038/s41586-026-10380-3. Online ahead of print.

ABSTRACT

Human cooperation is dynamic and often declines even under favourable conditions^1-4. Many prevailing theories explain the decrease of cooperation in terms of strategic behaviour or learning, framed as evidence of rational behaviour or progression towards rationality^5-9. Here we show that a key source of long-term decline derives from deviations from rational behaviour that systematically vary over time. We analyse a natural social dilemma in the field-that is, group lending in Sierra Leone-tracking cooperative dynamics over a five-year period. Borrowers enter a joint-liability contract, structured so that if the group loan is not repaid in full, all members lose access to future credit¹⁰. This produces a threshold social dilemma with incentives to free-ride^11,12. The dataset includes 47,931 group payments made by 7,108 borrowers, augmented with a two-stage cluster sample of semi-structured interviews. We find a statistically robust pattern of punctuated decline driven by behavioural mechanisms¹³. Cooperation rates start out high but gradually decline due to decreases in group members’ cooperative motivation and effort. Sharp rebounds occur when loans are restarted and clients resensitized to their cooperative responsibilities, even though the group membership and dilemma structure are largely unchanged. This pattern persists over the five-year observation window, but with each successive restart the subsequent decline is more rapid. The findings have direct implications for preventing behavioural decline in cooperative programmes and institutions.

PMID:42020732 | DOI:10.1038/s41586-026-10380-3

Mol Psychiatry. 2026 Apr 22. doi: 10.1038/s41380-026-03606-3. Online ahead of print.

ABSTRACT

Neuropsychiatric disorders exhibit complex polygenic architectures, yet the cell-type-specific mechanisms underlying most risk loci remain unclear. Here, we integrate single-cell expression quantitative trait locus (sc-eQTL) data from brain and blood tissues with genome-wide association studies (GWAS) of six neuropsychiatric disorders (schizophrenia (SCZ), Parkinson’s disease (PD), bipolar disorder (BP), major depressive disorder (MDD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD)) to systematically identify putative causal genes at cellular resolution. Employing summary-data-based Mendelian randomization (SMR) across diverse neuronal and immune cell types, we discovered 345 cell-type-specific risk genes for various diseases, including both replicated candidates (such as MAPT in astrocytes for SCZ and PD and FLOT1 in excitatory neurons and inhibitory neurons for SCZ, BP and MDD) and novel associations (such as APTX in microglia for SCZ). Cross-disorder analyses revealed shared pathways in synaptic function and immune regulation. In contrast, disease-specific and tissue-specific patterns were observed across different disorders. Strikingly, we found that brain-derived risk genes exhibited significantly higher cell-type specificity than those identified in blood, underscoring the more focused cellular context of genetic effects in the central nervous system. Our findings suggest that neuropsychiatric disorders arise from a combination of neuronal dysfunction and immune system dysregulation. The study demonstrates how cell-type-specific mapping uncovers etiological mechanisms obscured in bulk-tissue analyses, proving novel information for clarifying the biological mechanism of gene expression implicated in the development of the six neuropsychiatric disorders.

PMID:42020718 | DOI:10.1038/s41380-026-03606-3

Commun Biol. 2026 Apr 22. doi: 10.1038/s42003-026-10030-4. Online ahead of print.

ABSTRACT

Most existing transcriptome wide association studies (TWASs) of Alzheimer’s Disease (AD) dementia only use bulk RNA-seq data and a single statistical method. Here, we utilize an omnibus TWAS (TWAS-O) pipeline that leverages multiple complementary statistical methods to integrate the snRNA-seq dataset (n = 415) of the dorsolateral prefrontal cortex (DLPFC) and the latest GWAS data of AD dementia. We fine-map TWAS risk genes by gene-based conditional analysis and conducted validation analyses by the analogous omnibus proteome-wide association studies (PWAS-O) using bulk proteomics data of DLPFC (n = 716). We identify 223 unique cell-type-aware TWAS risk genes from 350 associations across six major brain cell-types, including 91 fine-mapped independent associations, 11 of which are novel. By PWAS-O, we identify 21 significant PWAS risk genes, including 13 independent associations, which validated 31.9% independent cell-type-aware TWAS associations. By protein-protein interaction network analyses, our novel cell-type-aware TWAS findings are linked to established AD risk genes such as APOE, BIN1, and MAPT.

PMID:42020711 | DOI:10.1038/s42003-026-10030-4

Neurocrit Care. 2026 Apr 23. doi: 10.1007/s12028-026-02525-z. Online ahead of print.

ABSTRACT

OBJECTIVE: Although delayed cerebral ischemia (DCI) and hydrocephalus contribute to poor outcomes after aneurysmal subarachnoid hemorrhage (aSAH), it remains unclear whether improved subarachnoid hematoma clearance translates into better long-term outcomes and through which mechanisms. We investigated the association between hematoma clearance and long-term outcomes and quantified the mediating effects of DCI and shunt-dependent hydrocephalus.

METHODS: We retrospectively analyzed patients with aSAH who underwent aneurysmal clipping between April 2012 and March 2024 at a single center. Hematoma burden was assessed using the Hijdra sum score (HSS). Hematoma clearance was defined as the percentage reduction in HSS between admission and days 7‒10 and dichotomized using the median (91.5%). Poor outcome was defined as a modified Rankin Scale (mRS) score ≥ 3 at 6 months. Multivariate logistic regression analyses and causal mediation analyses were performed to assess direct and indirect effects of hematoma clearance on long-term outcomes mediated by DCI and shunt-dependent hydrocephalus.

RESULTS: A total of 442 patients were included. Poor hematoma clearance was independently associated with poor 6-month outcomes [odds ratio (OR) 2.32, p = 0.003], DCI (OR 1.83, p = 0.025), and shunt-dependent hydrocephalus (OR 2.55, p < 0.001). Mediation analysis showed that shunt-dependent hydrocephalus mediated approximately 22% of the total effect of poor clearance on poor outcome [average causal mediation effect (ACME) 0.035, p < 0.001], whereas mediation via DCI was smaller and did not reach statistical significance (ACME 0.020 p = 0.078). A substantial direct effect independent of these mediators was observed.

CONCLUSIONS: Poor hematoma clearance after aSAH is associated with worse long-term outcomes, partly mediated by shunt-dependent hydrocephalus and to a lesser extent by DCI. However, a large proportion of the effect appears to be independent of these pathways, suggesting the involvement of additional mechanisms beyond DCI and hydrocephalus.

PMID:42020688 | DOI:10.1007/s12028-026-02525-z

Sci Rep. 2026 Apr 22. doi: 10.1038/s41598-026-49505-z. Online ahead of print.

NO ABSTRACT

PMID:42020664 | DOI:10.1038/s41598-026-49505-z

Top Curr Chem (Cham). 2026 Apr 22;384(2):17. doi: 10.1007/s41061-026-00552-0.

ABSTRACT

Rare-earth high-entropy oxides (RE-HEOs) represent a distinct class of entropy-stabilized ceramics in which multiple lanthanide cations occupy a common crystallographic sublattice, generating strong chemical disorder, lattice distortion, and complex defect landscapes. Unlike transition-metal-based high-entropy oxides, RE-HEOs are governed by localized 4f electronic states, weak crystal-field coupling, and variable redox chemistry, leading to emergent structural, electronic, magnetic, and optical phenomena that challenge conventional solid-state descriptions. This review provides a physics-oriented analysis of RE-HEOs, focusing on the thermodynamic foundations of configurational entropy stabilization, the interplay between enthalpy, entropy, and kinetic trapping, and the consequences of severe chemical disorder for crystal structure and phase stability. We review how lattice distortion, oxygen vacancy disorder, and cation randomness modify phonon spectra, ionic transport pathways, and electronic structures, with particular emphasis on the role of localized 4f states, defect-induced in-gap levels, and disorder-broadened excitation spectra. Spectroscopic manifestations of disorder including crystal-field relaxation, line broadening, lifetime modification, and energy transfer processes are discussed within a unified framework linking local symmetry breaking to macroscopic response. We further discuss the optoelectronic properties of RE-HEOs, including photoluminescence from intra-4f transitions, upconversion mechanisms, and disorder-induced modifications of radiative lifetimes and quantum efficiency. The application landscape spans both energy conversion (electrocatalysis, solid oxide fuel cells, thermal barrier coatings) and optoelectronic technologies (phosphors, scintillators, optical thermometry, and anti-counterfeiting). Likewise, we assess theoretical and computational approaches, including density functional theory with strong correlation corrections, statistical thermodynamics, and emerging machine-learning models, highlighting their ability and current limitations in capturing disorder-driven physics in multi-component oxides. Finally, we identify open questions central to condensed-matter physics, including the nature of entropy-stabilized metastability, the limits of band theoretical descriptions in highly disordered 4f systems, and the role of configurational entropy in tuning electron-phonon and defect interactions. By consolidating experimental and theoretical insights, this review establishes RE-HEOs as a platform for exploring disorder-dominated solid-state physics beyond conventional crystalline oxides.

PMID:42020651 | DOI:10.1007/s41061-026-00552-0