Browse Articles

Cardiac phenotype in hereditary transthyretin amyloidosis: correlations between fibril types and 99mTc-DPD uptake

Abstract Variant transthyretin amyloidosis is a systemic disease. In Sweden, the Val30Met variant is the most prevalent. Val30Met presents in two phenotypes: an early-onset form dominated by polyneuropathy and a late-onset form frequently accompanied by cardiomyopathy. These phenotypes are associated with two amyloid fibril types. Type A fibrils, contain both fragmented and full-length transthyretin, whereas type B fibrils contain only full-length transthyretin. Fibril type has been linked to differences in cardiac tracer uptake on 99mTc-DPD scintigraphy. A total of 152 patients with confirmed variant transthyretin amyloidosis evaluated at Umeå University Hospital, Sweden, were included. Age at disease onset and cardiac involvement, investigated by echocardiography, Troponin-T, and NT-proBNP, were assessed in relation to fibril type in abdominal fat and scintigraphic findings. Eighty-five patients had type A fibrils and sixty-seven had type B fibrils. Type A patients were older at diagnosis and had pathologic scintigraphies and more severe cardiac involvement. A subset of type B patients (15%) exhibited cardiac tracer uptake and had cardiac characteristics and age at disease onset similar to those with type A fibrils. Even though there was a strong correlation with findings in abdominal fat pad biopsies, results from 99mTc-DPD scintigraphy correlated better with clinical phenotype.

Using AI to enhance healthcare resource management and allocation: A focus on the autism community in Alabama

This study investigates the potential of artificial intelligence, particularly Natural Language Processing and large-scale language models, to improve resource management and service access for individuals with autism in Alabama. The research aims to explore and evaluate the potential of AI-driven tools to address challenges in navigating complex datasets and supporting social work practices. We designed and tested AI systems, including general language models, domain-specific chatbots powered by advanced language models, and a Retrieval-Augmented Generation framework. A standardized set of queries was used to simulate real-world scenarios encountered by social workers engaged in autism service coordination. System performance was evaluated based on precision, recall, and response accuracy. Results demonstrated that the Retrieval-Augmented Generation (RAG) framework achieved superior performance compared to traditional NLP methods and general-purpose language models, attaining approximately 90–96% precision and recall across evaluated query types. RAG outperformed the domain-specific GPT-4 chatbot by approximately 5–12 percentage points in F1 score, with the largest gains observed for queries requiring geographic specificity, multiple constraints, or complex contextual understanding. The integration of domain-specific retrieval significantly enhanced the accuracy, contextual relevance, and usability of generated responses. The findings highlight the transformative potential of AI-driven tools in improving social work efficiency and enhancing healthcare equity. By streamlining care coordination and delivering accurate, contextually relevant information, these systems offer scalable solutions to improve access to autism-related services. Future research should focus on addressing data quality, minimizing biases, and ensuring ethical deployment to build trust and support widespread adoption of these tools.

A 2.7 kV AlGaN/GaN high electron mobility transistor with an anti-parallel low turn-on voltage GaN Schottky barrier diode

In this work, AlGaN/GaN reverse conduction HEMTs (RC-HEMTs) integrated with anti-parallel Schottky barrier diodes (SBDs) are demonstrated. Benefiting from the idealized Schottky interface of AlGaN/GaN SBDs with recessed anode, which enables direct contact between GaN channel and anode metal, low reverse turn-on voltage (VR-T) of −0.75 V and high ION/IOFF ratio of 8.5 × 107 are obtained. Based on the randomly measured 100 RC-HEMTs with LGD of 15 μm, ultra-high VR-T uniformity with standard deviation of 18 mV and forward on-resistance (RON) uniformity with standard deviation of 0.3 Ω mm are calculated, respectively. Furthermore, the breakdown voltage of the fabricated AlGaN/GaN RC-HEMT with a 30-μm LGD can reach 2.7 kV, which shows great promise for medium-voltage power applications.

Distance-based temporal similarity metrics for adaptive channel selection in multi-modal EEG-fNIRS BCI frameworks

An inflammatory biomarker panel for prediabetes classification using interpretable machine learning

Objective Prediabetes is a silent condition that often goes undetected. However, timely interventions could prevent its progression to type 2 diabetes. Traditional glycemic markers, such as hemoglobin A1c (HbA1c), have limitations, creating a need for new diagnostic biomarkers. In this study, our objective was to develop an interpretable machine learning model using biomarkers related to oxidative stress, inflammation, and lipid metabolism to classify prediabetes independently of traditional glycemic markers, such as HbA1c. We also compared multiple biomarker panels to determine which biomarkers offer the highest predictive accuracy. Methods We developed and validated interpretable machine learning models using clinical and biomarker data from 545 participants (405 healthy controls and 140 with prediabetes). To ensure robust and generalizable findings, we employed a nested cross-validation technique, managed feature collinearity using the variance inflation factor (VIF), and interpreted the final model with Shapley Additive exPlanations (SHAP) [Kapoor S, Narayanan A. Patterns. 4(9):100804 (2023); Vabalas A, et al. PLoS One. 14(11):e0224365 (2019); Lundberg SM, Lee SI. Adv Neural Inf Process Syst. 30:4768–77 (2017)]. Results Our approach identified a distinct panel of inflammatory biomarkers (IL-10, IGF-1, and CRP) capable of classifying prediabetes independently of traditional glycemic markers. This non-glycemic model achieved a promising Area Under the Curve (AUC) of 0.711 on holdout validation, establishing inflammation as a key and measurable indicator of early metabolic dysfunction. Conclusion Our findings introduce a novel panel of inflammatory biomarkers that show promise in the identification of prediabetes independently of traditional glucose-based measures. By highlighting inflammation as an early indicator of metabolic dysfunction, this approach may enhance precision in the detection of prediabetes. Longitudinal studies with larger and more diverse populations are essential to clinically validate these biomarkers and confirm their value in improving the early diagnosis and management of metabolic health.

Transition from one-step to stepwise propagation of a positive streamer with varying pulse durations in an argon plasma jet

Atmospheric pressure plasma jet normally behaves as a positive streamer, whose head is honored as a powerful chemical reactor that can produce active species for various applications. Revealing and understanding the streamer dynamics are of great significance to optimize the plasma for various applications. In this Letter, the dynamic transition from one-step propagation to stepwise propagation of the positive streamer is reported through varying duration (Δt) of a pulse voltage. Results indicate that per voltage cycle, there are two discharges occurring at the falling edge and the rising edge of the pulse voltage, respectively, which are separately referred to as Df and Dr. Comparatively, Dr has a higher intensity than Df. Moreover, the integral intensity for Df and Dr increases with increasing Δt. Fast photography reveals that the positive streamer fulfills the propagation in one step with wider Δt, while it undergoes the stepwise propagation with narrower Δt. The stepwise propagation is attributed to the negative ions left by the previous negative streamer. In addition, spatial distributions of streamer velocity and excited electron temperature are also analyzed from the role of negative ions. Moreover, electron density, electron temperature, and gas temperature are compared for the different behaviors of the positive streamer. These results provide a new approach to manipulate the streamer dynamics behaviors.

Inverse multi-principal element alloys design via conditional wasserstein generative adversarial network

Expression of Concern: MAML1 Acts Cooperatively with EGR1 to Activate EGR1-Regulated Promoters: Implications for Nephrogenesis and the Development of Renal Cancer

Selenium-containing amino acid passivated deep-red perovskite quantum dot light-emitting diodes

Perovskite quantum dot (QD) light-emitting diodes (LEDs) typically exhibit a trade-off between emission efficiency and spectral stability. This compromise primarily arises from nonradiative recombination losses attributed to Pb2+ defects, halide phase segregation, and self-doping effects. In this study, we employ an environmentally friendly ligand exchange strategy utilizing short-chain selenium-containing L-seleno-methylselenocysteine (L-SeMSC) to passivate defects in perovskite QDs and replace the high-resistive long-chain ligands of oleate and oleylammonium. Theoretical and experimental findings indicate that the oxygen lone pair electrons from the carboxyl group in L-SeMSC effectively coordinate with Pb2+ defects on the surface of CsPb(Br/I)3 QDs, while the positively charged amino group inhibits halide ion migration. This coordination significantly enhances the photoluminescence quantum yield, thermal and air stability, and electroluminescence performance. The optimal LED achieves a maximum brightness of 2222.4 cd m−2 and an external quantum efficiency (EQE) of 17.18% at 654 nm, surpassing the performance of the control device, which exhibits a maximum brightness of 524.2 cd m−2 and an EQE of 8.94%, characterized by unstable luminescence emission. This study underscores the critical role of selenium-containing amino acids in enhancing the performance and stability of perovskite QD LEDs.

Retraction Note: Novel design of a dual-band microstrip antenna array for 6G mmWave applications

Correction: Lack of genetic differentiation in yellowfin tuna has conservation implications in the Eastern Pacific Ocean

Data‐Driven Modeling of <i>N,N′</i> ‐Dioxide/Metal‐Catalyzed Asymmetric Michael Additions

Abstract Rational catalyst design and accurate selectivity prediction remain major challenges in asymmetric synthesis, which is critical for improving and innovating existing catalytic systems. Among them, chiral N , N ′‐dioxide/metal complexes have emerged as a powerful and broadly effective class of privileged catalysts, yet systematic tools for understanding and optimizing their performance remain underdeveloped. Here, we present an integrated data platform that unifies literature curation, mechanistic modeling, and predictive analytics to support intelligent catalyst selection for asymmetric N , N ′‐dioxide/metal‐catalyzed Michael additions. We curated over 2,000 reactions from two decades of research into a chemically annotated, machine‐readable dataset encompassing catalyst structure, reaction conditions, and stereochemical outcomes. This dataset enabled global statistical analyses of application patterns across metal–ligand–substrate combinations and supported a modeling framework that combines intermediate‐informed data augmentation with similarity‐weighted tuning, which improved predictive ability on reactions involving previously unseen substrates. Comprehensive experimental validations covering diverse substrates, ligands, and metals confirmed the model's robustness and transferability across a wide selectivity range, including the accurate identification of new highly enantioselective transformations. These findings highlight the value of data‐integrated platforms in advancing the development of new reactions within complex asymmetric systems and provide an intelligent framework for future expansion of the N , N ′‐dioxide catalysis.

Impact of nitrogen and oxygen interstitials on niobium SRF cavity performance

Superconducting radio frequency (SRF) cavities are the leading technology for highly efficient particle acceleration, and their performance can be significantly enhanced through the controlled introduction of interstitial impurities into bulk niobium. Nitrogen doping has demonstrated a substantial reduction in surface resistance, which improves the quality factor of the cavities. More recently, oxygen doping has emerged as a promising alternative, demonstrating comparable reductions in surface resistance. In this study, we combine cavity measurements on 1.3 GHz niobium SRF cavities subjected to a range of nitrogen- and oxygen-based treatments with material characterizations performed on cavity cutouts processed under identical conditions. This approach allows us to quantitatively assess the contribution of each impurity to the reduction of surface resistance. We find that nitrogen is ten times more effective than oxygen in reducing surface resistance at 16 MV/m. We also observe an additive effect of O and N impurities in reducing RT. We discuss these results in the context of field-dependent nonequilibrium superconductivity, gap enhancement, and hydrogen trapping mechanisms.

Molecular analysis of somatic mutations at the HPRT locus in lymphocytes of human population exposed to chronic high background natural radiation

Abstract Populations residing in high-level natural radiation areas (HLNRA) along the monazite-rich coastal belt of Kerala, India, are chronically exposed to low-dose ionizing radiation, with lifetime cumulative doses exceeding 1000 mGy. Although the biological effects of acute high-dose exposures are well established, the long-term health consequences of chronic low-dose or low-dose-rate ionizing radiation (LDIR) remain poorly understood. To address this knowledge gap, we examined the frequency and molecular spectrum of somatic mutations at the hypoxanthine–guanine phosphoribosyltransferase ( HPRT ) locus-a sensitive biomarker of mutagenesis-in peripheral blood lymphocytes from 37 healthy adults residing in normal-level (NLNRA, N = 12) and high-level (HLNRA, N = 25) natural radiation areas. Using a T-lymphocyte cloning assay, PCR-based molecular profiling, and sequence-tagged site (STS) analysis, we found no significant difference in HPRT mutant frequency ( p  = 0.43), mutation spectrum ( p  = 0.52), or deletion subtype distribution ( p  = 0.69) between HLNRA and NLNRA groups. The extent of genomic deletions, spanning 0.09–1.19 Mb, was also comparable between HLNRA and NLNRA populations. However, gene expression profiling revealed significant alterations in DNA repair genes, including KU80 , DDB2 , MSH6 , PCNA , and RAD50 , suggesting that HPRT mutation may influence DNA damage response pathways. Our findings indicate that chronic exposure to natural background radiation does not elevate somatic mutation frequency or induce large-scale genomic alterations but may modulate DNA damage response and repair gene regulation. This study provides critical human data for refining low-dose radiation risk models and understanding mechanisms of genome stability and adaptation in chronically exposed populations.

Alterations in bone malformation in the absence of the endosomal SNAREs Vti1a and Vti1b

The Qb-SNAREs (soluble N-ethylmaleimide-sensitive-factor attachment receptor) Vti1a and Vti1b participate in membrane fusion in the endosomal system of mammalian cells and are partially redundant. While double deficiency of Vti1a -/- Vti1b -/- (DKO) is perinatal lethal, double heterozygous Vti1a +/- Vti1b +/- (DHET) mice presented no phenotypic alterations when compared to wild-type mice. To investigate the physiological role of these proteins, this study focused on the analysis of embryonic DKO versus DHET mice. The size and weight of E18.5 DKO embryos were significantly lower when compared with those of DHET littermates and wild-type embryos. Furthermore, we observed alterations in skeletal development of DKO embryos, mainly in the front limbs, ribs, clavicles and sternum. A lumbar vertebra was missing in DKO embryos and the palate was not closed in 50% of these embryos.

Interfacial Microgel Self‐Assembly Engineered for Superionic Conduction in PVDF Electrolyte

ABSTRACT In this work, we propose an ion‐mediated interfacial microgel self‐assembly strategy, enabling the construction of a conduction network with optimized ion coordination to overcome the intrinsic limitations of PVDF‐based electrolytes. As prepared M (D) —PVDF‐HFP electrolyte shows remarkable ionic conductivity (4.54 × 10 −4 S cm −1 at room temperature), high Li + transference number (0.63), and a 4.8 V‐wide operating window. Galvanostatic electrochemical impedance spectroscopy and finite element method simulations demonstrate rapid response and a high and uniform Li + flux under operating conditions. Consequently, symmetric cells display stable Li plating/stripping for &gt;5,000 h with an overpotential of only 136.4 mV at 0.1 mA cm −2 (25 °C). Furthermore, all‐solid‐state cells employing a LiNi 0.8 Co 0.1 Mn 0.1 O 2 cathode delivered an initial reversible specific capacity of 181.08 mAh g −1 , even under a high areal capacity load of approximately 2.0 mAh cm −2 . Our work is an innovative exploration to induce uniform Li + flux in heterogeneous polymer electrolyte and highlights the importance of internal interface behavior in solid‐state polymer electrolytes.

Analysis of a novel heterojunction thermoradiative structure

The heterojunction thermoradiative design introduced here has a recombination-photon emission layer in its junction, as does the homojunction thermoradiative device. However, the heterojunction structure has this layer separated from the energy source by semiconductor legs. This allows the Thompson effect to occur and results in a significant increase in electrical power density capabilities.

Boundary sensitive-net-based lumbar vertebra segmentation and spondylolisthesis measurement

Experiences of people living with HIV who have participated in psychological interventions: Protocol for a qualitative meta-analysis

Introduction Mental health problems among people living with HIV have been widely documented, including a high burden of common mental disorders. Despite the demonstrated effectiveness of various psychological interventions, there is limited understanding of how these interventions are experienced and evaluated by participants themselves. A key factor in ensuring successful implementation lies in how individuals interpret and emotionally respond to an intervention—specifically, whether they perceive it as meaningful, appropriate, and aligned with their expectations and needs. This qualitative meta-analysis aims to explore the subjective therapeutic experiences of people living with HIV who have participated in psychological interventions, with a particular focus on their acceptability and the perceived impact on psychological well-being. Methods and analysis A qualitative meta-analysis will be conducted following the descriptive-interpretive approach, which enables the identification and synthesis of meaning units from participants’ narratives. The review will include qualitative and mixed-methods studies, with a clearly distinguishable qualitative component, published between January 1, 2000 and February 23, 2026, focusing on the therapeutic experiences of people living with HIV who have received psychological interventions for common mental health problems. A comprehensive search will be performed in MEDLINE (via PubMed), MEDLINE (EBSCOhost), Scopus, Web of Science, APA PsycINFO and SciELO. Methodological quality will be assessed using the CASP tool, and confidence in the findings will be evaluated through GRADE-CERQual. The data analysis will follow the descriptive-interpretive meta-analysis approach. Data management and thematic analysis will be supported by Microsoft Excel, Rayyan and/or ATLAS.ti. Expected results This review is expected to identify key experiential themes that reflect how people living with HIV perceive and evaluate psychological interventions, including the aspects they find most helpful, challenging, or relevant. Findings will contribute to a better understanding of the acceptability of such interventions and offer practical insights for improving their design, delivery, and contextual adaptation. Dissemination The results of this review will be disseminated through publication in a peer-reviewed journal and presentations at scientific conferences related to mental health, HIV, and qualitative research. The findings are expected to inform the development of more acceptable and culturally sensitive psychological interventions for people living with HIV.

Synergistic phase regulation and heterojunction engineering achieve ultrahigh-energy density in ferroelectric polymers

Ferroelectric polymers are constrained in high-power energy storage capacitors (ESCs) due to their hysteresis losses and low breakdown strength. We tackle this challenge via a dual-pronged strategy encompassing molecular-scale ferroelectric phase regulation and nanoscale heterojunction engineering. The incorporation of trifluoroethylene units into poly(vinylidene fluoride)-chlorotrifluoroethylene disrupts the ferroelectric long-range order, inducing a relaxor state with dynamic polar nanoregions (PNRs) to minimize hysteresis. Simultaneously, ZnO@ZnS nanoparticles refine PNRs and introduce deep charge traps via interfacial band engineering, thereby drastically suppressing electrical conduction. This synergistic strategy employs phase regulation to reduce dipolar loss and heterojunction engineering to curb conduction loss, leading to a greatly increased breakdown strength and reduced dissipation. The resulting nanocomposite achieves a high discharged energy density of 23.8 J cm−3 at 550 MV m−1 with 80% efficiency and robust cycling stability (&amp;gt;5000 cycles) and establishes a transformative pathway for ultrahigh-performance ESCs.