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Particle decoration enables solution-processed perovskite integration with fully-textured silicon for efficient tandem solar cells
Get PDFPerovskite/silicon tandem solar cells can exceed Shockley-Queisser limit, but achieving complete coverage of 2-4 μm pyramids on industrial fully-textured silicon with solution-processed perovskite film remains challenging. We address this issue by spray-coating alumina particles onto fully-textured silicon, creating a super-hydrophilic rough surface that both enhances wet film coverage and provides guided nucleation sites. Although super-hydrophilic effect enhances wetting, it alone is insufficient to achieve complete coverage of pyramids by perovskite film. Beyond enhanced wetting, alumina particles promote uniform nucleation at particle-decorated sites across pyramids by lowering nucleation barrier and suppressing valley-preferred nucleation, which enables near-conformal deposition of perovskite film on pyramids. Additionally, alumina particles reduce nonradiative recombination and extend carrier lifetimes. Using this approach, we achieve a efficiency of 32.74% for perovskite/silicon tandem solar cells with one-step solution-processed perovskite on fully-textured silicon. This strategy offers a pathway for seamless integration of perovskite and silicon photovoltaics into high-performance tandem devices
Immediate or early skin‐to‐skin contact for mothers and their healthy newborn infants
Get PDFRATIONALE: Research supports the beneficial effects of immediate maternal-infant skin-to-skin contact (SSC) after all modes of birth on breastfeeding/lactation and neonatal physiology, but little is known about how it might influence maternal physiology, including postpartum blood loss and placental separation time. Despite the findings from the 2016 Cochrane review of skin-to-skin contact, and although the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF) recommend immediate, continuous, uninterrupted SSC after birth, newborn infants are still separated from their mothers during this period in many settings. SSC is less common in low-income and lower-middle-income countries (World Bank classification), which suggests country income level could impact breastfeeding exclusivity. This update integrates the evidence found since 2015 into the review. OBJECTIVES: To assess the effects of immediate skin-to-skin contact (< 10 minutes postbirth) or early skin-to-skin contact (10 minutes-24 hours postbirth) compared with existing hospital practices (standard contact) on the establishment and maintenance of breastfeeding and on maternal and infant physiology among healthy newborn infants and their mothers. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, and CINAHL up to 22 March 2024 and two trial registers up to 3 July 2025, along with reference checking and contact with experts. ELIGIBILITY CRITERIA: Randomized controlled trials that compared immediate or early SSC with other hospital care after a vaginal or cesarean birth. Participants were mothers and their healthy full-term or late preterm newborns (≥ 34 weeks' gestation). Infants admitted to the neonatal intensive care unit were excluded. OUTCOMES: Our critical outcomes included exclusive breastfeeding, infant axillary temperature, infant blood glucose levels, infant SCRIP score (cardiorespiratory stability), placental separation time/duration of the third stage of labor, and maternal blood loss. RISK OF BIAS: We used Cochrane's original risk of bias 1 tool (RoB 1). We assessed the risk of performance and detection bias separately for subjective and objective outcomes. SYNTHESIS METHODS: We conducted random-effects meta-analysis where there was substantial heterogeneity and fixed-effect meta-analysis for infant blood glucose and SCRIP score. We calculated the summary risk ratio (RR) and 95% confidence interval (CI) using the Mantel-Haenszel method for dichotomous outcomes. We calculated the mean difference (MD) and 95% CI using inverse variance for continuous outcomes, except infant SCRIP score, where we used the standardized mean difference (SMD). We used the GRADE approach to summarize the certainty of evidence. INCLUDED STUDIES: We added 26 new trials (3775 mother-infant pairs) to this update for a total of 69 trials (7290 mother-infant pairs). Most studies (43/69) compared immediate SSC with standard hospital care. Ten studies included late preterm infants, and 15 included children born by cesarean delivery. Thirty-two trials were conducted in high-income countries, 25 in upper-middle-income countries, and 12 in lower-middle-income countries. Fifty-six studies contributed data to the meta-analyses. No included trial met all the criteria for high-quality methodology and reporting. Many analyses had statistical heterogeneity due to considerable differences between SSC and control group conditions. SYNTHESIS OF RESULTS: Breastfeeding/lactation SSC compared with standard contact probably increases rates of exclusive breastfeeding at hospital discharge to one month postbirth (RR 1.36, 95% CI 1.19 to 1.56; I² = 62%; 12 studies; 1556 mother-infant pairs; moderate-certainty evidence) and at six weeks to six months postbirth (RR 1.38, 95% CI 1.09 to 1.74; I² = 87%; 11 studies; 1135 mother-infant pairs; moderate-certainty evidence), though both analyses had substantial heterogeneity. Infant physiological stability SSC compared with standard contact probably increases infant axillary temperature, but the MD of 0.28 °C is not clinically meaningful (MD 0.28, 95% CI 0.14 to 0.41; I² = 95%; 11 studies; 1349 infants; moderate-certainty evidence). SSC probably increases blood glucose levels measured in mg/dL (MD 10.49, 95% CI 8.39 to 12.59; I² = 0%; 3 studies; 114 infants; moderate-certainty evidence). Infants who have SSC may also have higher SCRIP scores overall, indicating more optimal cardiorespiratory stabilization. However, the trials reporting this outcome had small sample sizes, and the clinical significance was unclear because trialists reported averages of multiple time points (SMD 1.24, 95% CI 0.76 to 1.72; I² = 0%; 2 studies; 81 infants; low-certainty evidence). Maternal physiology SSC may result in little to no difference in placental separation time/duration of the third stage of labor in minutes (MD -2.26, 95% CI -5.04 to 0.52; I² = 88%; 4 studies; 450 mothers; low-certainty evidence) and maternal postpartum blood loss in mL (MD -145.92, 95% CI -416.96 to 125.11; I² = 97%; 2 studies; 143 mothers; very low-certainty evidence), although these results should be interpreted with caution due to high heterogeneity and the small number of studies. AUTHORS' CONCLUSIONS: This review supports immediate SSC after birth, regardless of mode of birth, for mothers and their healthy full-term and late preterm infants in middle-income and high-income countries. No included studies were conducted in low-income countries. SSC probably promotes exclusive breastfeeding and improves infant thermoregulation and blood glucose levels. In addition, SSC may increase infant stabilization measured by the SCRIP score. The evidence about maternal physiological outcomes was inconclusive. Future research should prioritize methodological rigor. This includes providing clear descriptions of interventions and standard contact, carefully selecting relevant outcomes, and using reliable and objective measurement tools. Understudied areas include: the impact of medications and anesthetics, in terms of dose-response and other variables during SSC; biological and psychosocial mechanisms; additional physiological effects of SSC; and longer-term impacts. Instances of harm should be recorded. As WHO/UNICEF recommends immediate, uninterrupted SSC as the standard of care, randomizing to separation of mother and newborn may no longer be justifiable. FUNDING: This Cochrane review had no dedicated funding. REGISTRATION: Review Update (2016) https://doi.org/10.1002/14651858.CD003519.pub4 Review Update (2012) https://doi.org/10.1002/14651858.CD003519.pub3 Review Update (2007) https://doi.org/10.1002/14651858.CD003519.pub2 Original review (2003) https://doi.org/10.1002/14651858.CD003519 Protocol (2002) DOI unavailable
A quantitative, Bayesian-informed approach to gene-specific variant classification: Updated Expert Panel recommendations improve classification of TP53 germline variants for Li-Fraumeni syndrome
Get PDFBackground Germline pathogenic variants in TP53 cause Li-Fraumeni syndrome, with significantly elevated cancer risk from infancy. Accurate classification of TP53 variants is essential to guide clinical management and surveillance, yet many variants remain classified as variants of uncertain significance (VUS). To improve classification accuracy and reduce the proportion of VUS, the ClinGen TP53 Variant Curation Expert Panel (VCEP) has updated its specifications. MethodsT he updated specifications incorporate the latest ClinGen recommendations and methodological advances, providing greater granularity for multiple evidence types, and also introduce the novel use of variant allele fraction as evidence of pathogenicity, particularly in the context of clonal hematopoiesis. Whenever feasible, the VCEP followed a data-driven approach using likelihood ratio-based quantitative analyses to guide code application and determine strength modifications, while also factoring in expert judgment. Proposed modifications were first discussed in working group meetings and then subjected to comprehensive review during monthly general VCEP meetings to reach consensus. Results The performance of new specifications was compared to that of the old specifications for 43 pilot variants, and led to both decreased VUS and increased certainty, with clinically meaningful classifications for 93% of variants. Conclusions The updated TP53 specfications are expected to reduce VUS rates, increase inter-laboratory concordance, and improve medical management for individuals with germline TP53 variants. The most current version is available at the ClinGen Criteria Specifications Registry (CSpec): https://cspec.genome.network/cspec/ui/svi/svi/GN009
The ABCs of PEMs: Using Artificial Intelligence to Enhance the Readability of Patient Educational Materials in Pediatric Orthopaedics
Get PDFBackground While the AMA and NIH recommend patient educational materials (PEMs) be written at a 6th-grade reading level, studies consistently show that PEMs in orthopaedics are written at the 10th-grade level or higher. This mismatch disproportionately affects patients with limited health literacy, who are at increased risk for poor clinical outcomes. This study investigates the potential of artificial intelligence (AI) platforms, including ChatGPT and OpenEvidence, to generate PEMs in pediatric orthopaedics that reach readability standards without sacrificing clinical accuracy. Methods Fifty-one of the most common pediatric orthopedic conditions were selected using the AAOS OrthoInfo PEM database. For each condition, PEMs were generated using two AI platforms: ChatGPT-4 and Open Evidence utilizing a standardized prompt requesting a 6th grade level explanation that included relevant anatomy, symptoms, physical exam findings, and treatment options. Readability was assessed using eight validated readability metrics via the Python Textstat library. PEMs were scored for accuracy and completeness by four blinded, pediatric orthopedic surgeons. Interrater reliability was assessed using intraclass correlation coefficients (ICC), and statistical comparisons were performed using paired t-tests. Results ChatGPT-generated PEMs had the lowest average reading grade level (8.7) compared to OrthoInfo (10.8) and Open Evidence (10.1). OrthoInfo PEMs were rated highest for accuracy and completeness (Total Accuracy: 6.95; Total Completeness: 6.98), compared to Chat GPT (Total Accuracy: 6.15; Total Completeness: 5.90) and Open Evidence (Total Accuracy: 3.25; Total Completeness: 3.05), but ChatGPT approached OrthoInfo in several subdomains, including treatment descriptions, timeline, and follow-up recommendations. Conclusions This study demonstrates the promise of AI platforms in generating readable, patient-friendly educational materials in pediatric orthopedics. While OrthoInfo remains the gold standard in content accuracy and completeness, it falls short of national readability guidelines. AI tools like ChatGPT and OpenEvidence produced significantly more readable PEMs and, in some categories, approached the quality of expert-validated materials. These findings suggest a potential role for AI-assisted content creation in bridging the health literacy gap. However, concerns surrounding accuracy, hallucinations, and source transparency must be addressed before AI-generated PEMs can be safely integrated into clinical practice. Level of evidence I
Distal Radius Interventions for Fracture Treatment (DRIFT) trial: study protocol for a multicentre randomised clinical trial of completely translated distal radius fractures at paediatric hospitals in North America
Get PDFDistal radius fractures are the most common fractures seen in the emergency department in children in the USA. However, no established or standardised guidelines exist for the optimal management of completely displaced fractures in younger children. The proposed multicentre randomised trial will compare functional outcomes between children treated with fracture reduction under sedation versus children treated with simple immobilisation. Participants aged 4–10 years presenting to the emergency department with 100% dorsally translated metaphyseal fractures of the radius less than 5 cm from the distal radial physis will be recruited for the study. Those patients with open fractures, other ipsilateral arm fractures (excluding ulna), pathologic fractures, bone diseases, or neuromuscular or metabolic conditions will be excluded. Participants who agree to enrol in the trial will be randomly assigned via a minimal sufficient balance algorithm to either sedated reduction or in situ immobilisation. A sample size of 167 participants per arm will provide at least 90% power to detect a difference in the primary outcome of Patient-Reported Outcomes Measurement Information System Upper Extremity computer adaptive test scores of 4 points at 1 year from treatment. Primary analyses will employ a linear mixed model to estimate the treatment effect at 1 year. Secondary outcomes include additional measures of perceived pain, complications, radiographic angulation, satisfaction and additional procedures (revisions, refractures, reductions and reoperations). Ethical approval was obtained from the following local Institutional Review Boards: Advarra, serving as the single Institutional Review Board, approved the study (Pro00062090) in April 2022. The Hospital for Sick Children (Toronto, ON, Canada) did not rely on Advarra and received separate approval from their local Research Ethics Board (REB; REB number: 1000079992) on 19 July 2023. Results will be disseminated through publication in peer-reviewed journals and presentations at international conference meetings. NCT05131685
The Evolving Role of Critical Access Hospitals in Rural Physician Training
Get PDFThis cross-sectional study examines the prevalence of critical access hospital–based training and compares these sites with other rural teaching hospitals to understand potential for expansion
Multiple polygenic score approach in colorectal cancer risk prediction
Get PDFRecent studies have demonstrated that for various diseases, incorporating polygenic risk scores (PRSs) for other traits and diseases into the PRS-based risk prediction model may improve predictive performance – known as Multiple Polygenic Score (MPS) approach. We aimed to examine whether the MPS approach improves colorectal cancer (CRC) risk prediction. We included 2,187 non-CRC PRSs from the polygenic Score (PGS) Catalog and used machine learning (ML) models to select the most predictive non-CRC PRSs, utilizing individual-level data from 31,257 CRC cases and 33,408 controls. An independent dataset from the Genetic Epidemiology Research in Adult Health and Aging (GERA) cohort (4,852 cases and 67,939 controls) was randomly split into subsets for model estimation and validation. The model combined MPS with two existing CRC-PRSs based on known loci and genome-wide genotyping. We then assessed model performance by calculating the area under the receiver operating curve (AUC) in the validation set and performed 1,000 bootstrapped iterations to evaluate AUC improvements. The ML model selected 337 non-CRC PRSs predictive of CRC risk. Adding MPS to the CRC-PRSs significantly improved AUC by 0.017 (95% CI: 0.011–0.022, p < 0.0001) when combined with known-loci CRC-PRS, 0.005 (95% CI: 0.002–0.007, p = 0.0005) with genome-wide CRC-PRS, and 0.004 (95% CI: 0.002–0.006, p = 0.0005) with both the known loci and genome-wide CRC-PRSs. These findings demonstrate MPS’s potential to refine CRC risk prediction models and highlight opportunities for further advancements in risk prediction.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-21956-w
Frame-attentive dynamic link prediction: uncovering narrative resonance in social networks with large language model
Get PDFPredicting the evolution of dynamic social networks is a fundamental challenge in computational social science. Traditional methods that rely on network structure or surface level textual features often fail to capture the latent ideological drivers governing user interactions. In this paper, we propose that the formation of future social ties is primarily driven by alignment with evolving narrative frames rather than simple textual similarity. To test this hypothesis, we introduce a novel framework for frame-attentive dynamic link prediction. First, we develop an LLM driven pipeline that integrates hierarchical community detection with bottom up abstractive summarization to induce structured semantic frames from unstructured user discourse. Second, we construct a dual layer heterogeneous graph that explicitly models both social structure (user-user interactions) and ideological alignment (user-frame connections). Finally, we propose a frame-attentive graph representation learning mechanism to generate user embeddings that are grounded in this socio-semantic context. Extensive experiments on two large scale geopolitics datasets from Weibo and X (Twitter) demonstrate the superiority of our approach. Our model significantly outperforms a wide range of strong baselines, achieving up to a 33.5% improvement in AUC-ROC and an 89% Precision@100. Ablation studies and temporal analyses further confirm that the LLM-induced frames provide a more robust and predictive signal for social dynamics than conventional features. This work provides strong empirical evidence for the narrative resonance hypothesis and offers a powerful new paradigm for modeling the evolution of online social networks
AI-Enabled Technologies and Biomarker Analysis for the Early Identification of Autism and Related Neurodevelopmental Disorders
Get PDFBackground: Autism spectrum disorder (ASD) and related neurodevelopmental conditions are a significant public health concern, with diagnostic delays hindering timely intervention. Traditional assessments often lead to waiting times exceeding a year. Advances in artificial intelligence (AI) and biomarker-based screening offer objective, efficient alternatives for early identification. Objective: This review synthesizes the latest evidence for AI-enabled technologies aimed at improving early ASD identification. Modalities covered include eye-tracking, acoustic analysis, video- and sensor-based behavioral screening, neuroimaging, molecular/genetic assays, electronic health record prediction, and home-based digital applications or apps. This manuscript critically evaluates their diagnostic accuracy, clinical feasibility, scalability, and implementation hurdles, while highlighting regulatory and ethical considerations. Findings: Across modalities, machine learning approaches demonstrate strong accuracy and specificity in ASD detection. Eye-tracking and voice-acoustic classifiers reliably differentiate for autistic children, while home-video analysis and Electronic Health Record (EHR)-based algorithms show promise for scalable screening. Multimodal integration significantly enhances predictive power. Several tools have received Food and Drug Administration clearance, signaling momentum for wider clinical deployment. Issues persist regarding equity, data privacy, algorithmic bias, and real-world performance. Conclusions: AI-enabled screeners and diagnostic aids have the potential to transform ASD detection and access to early intervention. Integrating these technologies into clinical workflows must safeguard equity, privacy, and clinician oversight. Ongoing longitudinal research and robust regulatory frameworks are essential to ensure these advances benefit diverse populations and deliver meaningful outcomes for children and families
The role of organizational characteristics in intervention sustainment: findings from a quantitative analysis in 42 HIV testing clinics in Vietnam
Get PDFBackground Evidence-based intervention (EBI) sustainment is one of public health’s largest translational research problems. Fewer than half of public health EBIs are sustained long-term, and sustainment challenges are even more pressing in low and middle-income countries (LMICs). Organizational characteristics, including organizations’ inner structures, culture, and climate, may play a key role in EBI sustainment. However, little quantitative research has examined these relationships, particularly in LMICs.
Methods In this observational study, we assessed the association between baseline organizational characteristics and EBI sustainment within a cluster randomized implementation trial in Vietnam testing strategies to scale-up Systems Navigation and Psychosocial Counseling (SNaP) for people who inject drugs (PWID) living with HIV across 42 HIV testing clinics. From the Exploration, Preparation, Implementation, and Sustainment (EPIS) Framework, five baseline organizational characteristics were selected for investigation: 1) organizational readiness for implementing change; 2) implementation leadership; 3) implementation climate; 4) percent PWID; and 5) staff workload. Six to ten months post-study completion, clinic staff and leadership completed a survey that included the Provider Report of Sustainment Scale (PRESS), a measure of EBI sustainment across a clinic. We conducted clinic-level simple and multiple linear regression analyses to evaluate the association between organizational characteristics and sustainment.
Results 218 participants (94% completion rate) completed the PRESS survey. All implementation scales had good individual-level internal consistency reliability. Clinics with high organizational readiness to change at baseline had significantly greater SNaP sustainment than clinics with low organizational readiness to change (ß = 1.91, p = 0.015). None of the other organizational characteristics were associated with sustainment, controlling for study arm.
Conclusions We identified the importance of organizational readiness for SNaP sustainment in Vietnam. This study adds to the evidence base around the relationship between organizational characteristics and HIV intervention sustainment and could inform the development of future sustainment strategies. We also identified several areas for organizational characteristic and sustainment measure advancement, including the need for pragmatic sustainment measures that also capture EBI adaptation. This research demonstrates that assessing clinics’ organizational readiness pre-implementation and providing tailored support to those with low readiness scores could improve HIV intervention sustainment for key populations