Suppressing c-FOS expression by G-quadruplex ligands inhibits osimertinib-resistant non-small cell lung cancer

BACKGROUND

Osimertinib is the first-line therapy for patients with non-small cell lung cancer harboring epidermal growth factor receptor-activating alterations. Although osimertinib has been shown to elicit profound patient responses, cancer cells frequently develop additional alterations that sustain their proliferation capacity. This acquired resistance represents a substantial hurdle in precision medicine for patients with lung cancer.

METHODS

The biological and cellular properties of the G-quadruplex ligand BMVC-8C3O and its anticancer activities were evaluated in non-small cell lung carcinomas. In addition, combined treatment with BMVC-8C3O and osimertinib was evaluated for its effects on the growth of osimertinib-resistant tumors in vivo.

RESULTS

We demonstrate that BMVC-8C3O effectively suppresses c-FOS expression by stabilizing G-rich sequences located at the c-FOS promoter. The suppression c-FOS expression by BMVC-8C3O increases the sensitivity of acquired resistant cancer cells to osimertinib. Combining BMVC-8C3O and osimertinib has a synergistic effect in inhibiting the growth of acquired resistant cancers both in vitro and in mouse models. The combined inhibitory effect is not limited to BMVC-8C3O, either: several G-quadruplex ligands show varying levels of inhibition activity. We also show that simultaneous inhibition of both the c-FOS and PI3K/AKT pathways by BMVC-8C3O and osimertinib synergistically inhibits the growth of acquired resistant cancer cells.

CONCLUSION

These findings unveil a synthetic lethal strategy to prevent and inhibit epidermal growth factor receptor-altered lung cancers with acquired osimertinib resistance. G-quadruplex ligands have the potential to be integrated into current osimertinib-based treatment regimens.

Plasma acylcarnitine in elderly Taiwanese: as biomarkers of possible sarcopenia and sarcopenia

BACKGROUND

Sarcopenia is defined as the disease of muscle loss and dysfunction. The prevalence of sarcopenia is strongly age-dependent. It could bring about disability, hospitalization, and mortality. The purpose of this study was to identify plasma metabolites associated with possible sarcopenia and muscle function to improve disease monitoring and understand the mechanism of muscle strength and function decline.

METHODS

The participants were a group of healthy older adult who live in retirement homes in Asia (Taiwan) and can manage their daily lives without assistance. The participants were enrolled and divided into four groups: control (Con, n = 57); low physical function (LPF, n = 104); sarcopenia (S, n = 63); and severe sarcopenia (SS, n = 65) according to Asian countries that used Asian Working Group for Sarcopenia (AWGS) criteria. The plasma metabolites were used and the results were calculated as the difference between the control and other groups.

RESULTS

Clinical parameters, age, gender, body mass index (BMI), hand grip strength (HGS), gait speed (GS), blood urea nitrogen (BUN), hemoglobin, and hematocrit were significantly different between the control and LPF groups. Metabolite patterns of LPF, S, and SS were explored in our study. Plasma kynurenine (KYN) and acylcarnitines (C0, C4, C6, and C18:1-OH) were identified with higher concentrations in older Taiwanese adults with possible sarcopenia and S compared to the Con group. After multivariable adjustment, the data indicate that age, BMI, and butyrylcarnitine (C4) are more important factors to identify individuals with low physical function and sarcopenia.

CONCLUSION

This metabolomic study raises the importance of acylcarnitines on muscle mass and function. It suggests that age, BMI, BUN, KYN, and C4/Cr can be important evaluation markers for LPF (AUC: 0.766), S (AUC: 0.787), and SS (AUC: 0.919).

Lactoferrin targeting INTL1 receptor inhibits hepatocellular carcinoma progression via apoptosis and cell cycle signaling pathways

Hepatocellular carcinoma (HCC) constitutes 90% of liver cancer cases and ranks as the third leading cause of cancer-related mortality, necessitating urgent development of alternative therapies. Lactoferrin (LF), a natural iron-binding glycoprotein with reported anticancer effects, is investigated for its potential in liver cancer treatment, an area with limited existing studies. This study focuses on evaluating LF's anti-liver cancer effects on HCC cells and assessing the preventive efficacy of oral LF administration in a murine model. Data showed that LF exerted anti-proliferative effects on HepG2, Hep3B, and SK-Hep1 cells while having no cytotoxicity on healthy liver cells (FL83B). Mechanistically, LF induces mitochondrial-mediated apoptosis and G0/G1 cell cycle arrest in HepG2 cells, associated with increased phosphorylation of p38 MAPK and JNK for apoptosis, and ERK phosphorylation for cell cycle arrest. Intelectin-1 (INTL1) is identified as the receptor facilitating LF endocytosis in HepG2 cells, and downregulation of INTL1 inhibits LF-induced signaling pathways. Notably, oral LF administration prevents HCC development in nude mice with orthotopic HepG2 cell injection. This study unveils the mechanistic basis of LF action in HepG2 cells, showcasing its potential in HCC prevention. Importantly, we report the novel identification of INTL1 as the LF receptor in HepG2 cells, providing valuable insights for future exploration of LF and its derivatives in liver cancer therapy.

The natural tannins oligomeric proanthocyanidins and punicalagin are potent inhibitors of infection by SARS-CoV-2

The Coronavirus Disease 2019 (COVID-19) pandemic continues to infect people worldwide. While the vaccinated population has been increasing, the rising breakthrough infection persists in the vaccinated population. For living with the virus, the dietary guidelines to prevent virus infection are worthy of and timely to develop further. Tannic acid has been demonstrated to be an effective inhibitor of coronavirus and is under clinical trial. Here we found that two other members of the tannins family, oligomeric proanthocyanidins (OPCs) and punicalagin, are also potent inhibitors against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with different mechanisms. OPCs and punicalagin showed inhibitory activity against omicron variants of SARS-CoV-2 infection. The water extractant of the grape seed was rich in OPCs and also exhibited the strongest inhibitory activities for viral entry of wild-type and other variants in vitro. Moreover, we evaluated the inhibitory activity of grape seed extractants (GSE) supplementation against SARS-CoV-2 viral entry in vivo and observed that serum samples from the healthy human subjects had suppressive activity against different variants of SARS-CoV-2 Vpp infection after taking GSE capsules. Our results suggest that natural tannins acted as potent inhibitors against SARS-CoV-2 infection, and GSE supplementation could serve as healthy food for infection prevention.

The 20-million-year old lair of an ambush-predatory worm preserved in northeast Taiwan

The feeding behavior of the giant ambush-predator "Bobbit worm" (Eunice aphroditois) is spectacular. They hide in their burrows until they explode upwards grabbing unsuspecting prey with a snap of their powerful jaws. The still living prey are then pulled into the sediment for consumption. Although predatory polychaetes have existed since the early Paleozoic, their bodies comprise mainly soft tissue, resulting in a very incomplete fossil record, and virtually nothing is known about their burrows and behavior beneath the seafloor. Here we use morphological, sedimentological, and geochemical data from Miocene strata in northeast Taiwan to erect a new ichnogenus, Pennichnus. This trace fossil consists of an up to 2 m long, 2-3 cm in diameter, L-shaped burrow with distinct feather-like structures around the upper shaft. A comparison of Pennichnus to biological analogs strongly suggests that this new ichnogenus is associated with ambush-predatory worms that lived about 20 million years ago.

Characterizing approach behavior of Drosophila melanogaster in Buridan's paradigm

The Buridan's paradigm is a behavioral task designed for testing visuomotor responses or phototaxis in fruit fly Drosophila melanogaster. In the task, a wing-shortened fruit fly freely moves on a round platform surrounded by a 360° white screen with two vertical black stripes placed at 0° and 180°. A normal fly will tend to approach the stripes one at a time and move back and forth between them. A variety of tasks developed based on the Buridan's paradigm were designed to test other cognitive functions such as visual spatial memory. Although the movement patterns and the behavioral preferences of the flies in the Buridan's or similar tasks have been extensively studies a few decades ago, the protocol and experimental settings are markedly different from what are used today. We revisited the Buridan's paradigm and systematically investigated the approach behavior of fruit flies under different stimulus settings. While early studies revealed an edge-fixation behavior for a wide stripe in the initial visuomotor responses, we did not discover such tendency in the Buridan's paradigm when observing a longer-term behavior up to minutes, a memory-task relevant time scale. Instead, we observed robust negative photoaxis in which the flies approached the central part of the dark stripes of all sizes. In addition, we found that stripes of 20°-30° width yielded the best performance of approach. We further varied the luminance of the stripes and the background screen, and discovered that the performance depended on the luminance ratio between the stripes and the screen. Our study provided useful information for designing and optimizing the Buridan's paradigm and other behavioral tasks that utilize the approach behavior.

Use of Geopolymer and Carbon Fiber-Reinforced Polymer for Repairing Reinforced Concrete Deck Soffit

This study aimed to assess the feasibility of utilizing geopolymer for repairing reinforced concrete beams. Three types of beam specimens were fabricated: benchmark specimens without any grooves, rectangular-grooved beams, and square-grooved beams. The repair materials employed included geopolymer material, and epoxy resin mortar, while carbon fiber sheets were used as reinforcement in select cases. The repair materials were applied to the rectangular and square-grooved specimens, with the carbon fiber sheets attached to the tension side of the specimens. To evaluate the flexural strength of the concrete specimens, a third-point loading test was conducted. The test results indicated that the geopolymer exhibited higher compressive strength and shrinkage rate compared to the epoxy resin mortar. Furthermore, the specimens reinforced with carbon fiber sheets demonstrated even greater strength than the benchmark specimens. In terms of flexural strength under cyclic third-point loading tests, the carbon fiber-reinforced specimens exhibited the ability to withstand over 200 cycles of repeated loading at 0.8 times the ultimate load. In contrast, the benchmark specimens could only withstand seven cycles. These findings highlight that the use of carbon fiber sheets not only enhances compressive strength but also improves resistance to cyclic loading.

Brugada syndrome in Japan and Europe: a genome-wide association study reveals shared genetic architecture and new risk loci

BACKGROUND AND AIMS

Brugada syndrome (BrS) is an inherited arrhythmia with a higher disease prevalence and more lethal arrhythmic events in Asians than in Europeans. Genome-wide association studies (GWAS) have revealed its polygenic architecture mainly in European populations. The aim of this study was to identify novel BrS-associated loci and to compare allelic effects across ancestries.

METHODS

A GWAS was conducted in Japanese participants, involving 940 cases and 1634 controls, followed by a cross-ancestry meta-analysis of Japanese and European GWAS (total of 3760 cases and 11 635 controls). The novel loci were characterized by fine-mapping, gene expression, and splicing quantitative trait associations in the human heart.

RESULTS

The Japanese-specific GWAS identified one novel locus near ZSCAN20 (P = 1.0 × 10-8), and the cross-ancestry meta-analysis identified 17 association signals, including six novel loci. The effect directions of the 17 lead variants were consistent (94.1%; P for sign test = 2.7 × 10-4), and their allelic effects were highly correlated across ancestries (Pearson's R = .91; P = 2.9 × 10-7). The genetic risk score derived from the BrS GWAS of European ancestry was significantly associated with the risk of BrS in the Japanese population [odds ratio 2.12 (95% confidence interval 1.94-2.31); P = 1.2 × 10-61], suggesting a shared genetic architecture across ancestries. Functional characterization revealed that a lead variant in CAMK2D promotes alternative splicing, resulting in an isoform switch of calmodulin kinase II-δ, favouring a pro-inflammatory/pro-death pathway.

CONCLUSIONS

This study demonstrates novel susceptibility loci implicating potentially novel pathogenesis underlying BrS. Despite differences in clinical expressivity and epidemiology, the polygenic architecture of BrS was substantially shared across ancestries.

Photocatalytic Papers Comprising Au@SnO2 Nanocrystals Immobilized on Cellulose Nanofibers for Sustainable Dye Degradation

This work presents the synthesis, characterization, and photocatalytic performance of a sophisticated photocatalytic paper comprising Au@SnO2 core@shell nanocrystals immobilized on cellulose nanofibers (CNF). The Au@SnO2/CNF nanocrystal immobilized paper (NIP) is employed as photocatalysts for degradation of rhodamine B (RhB) under simulated sunlight irradiation. Results reveal that the Au@SnO2/CNF NIP exhibits a notable photocatalytic activity driven by efficient charge separation at the interface of Au and SnO2. Mechanistic insights into the degradation process indicate that photoexcited electrons in the Au core reduce dissolved oxygen to form superoxide radicals, while photogenerated holes in the SnO2 valence band oxidize water to generate hydroxyl radicals. These reactive oxygen species, along with the separated holes themselves, contribute to RhB degradation. Importantly, the Au@SnO2/CNF NIP demonstrates remarkable recyclability toward RhB degradation, retaining 88% of its initial activity after 18 degradation cycles, highlighting its potential for sustainable environmental remediation applications.

AutoTemplate: enhancing chemical reaction datasets for machine learning applications in organic chemistry

This paper presents AutoTemplate, an innovative data preprocessing protocol, addressing the crucial need for high-quality chemical reaction datasets in the realm of machine learning applications in organic chemistry. Recent advances in artificial intelligence have expanded the application of machine learning in chemistry, particularly in yield prediction, retrosynthesis, and reaction condition prediction. However, the effectiveness of these models hinges on the integrity of chemical reaction datasets, which are often plagued by inconsistencies like missing reactants, incorrect atom mappings, and outright erroneous reactions. AutoTemplate introduces a two-stage approach to refine these datasets. The first stage involves extracting meaningful reaction transformation rules and formulating generic reaction templates using a simplified SMARTS representation. This simplification broadens the applicability of templates across various chemical reactions. The second stage is template-guided reaction curation, where these templates are systematically applied to validate and correct the reaction data. This process effectively amends missing reactant information, rectifies atom-mapping errors, and eliminates incorrect data entries. A standout feature of AutoTemplate is its capability to concurrently identify and correct false chemical reactions. It operates on the premise that most reactions in datasets are accurate, using these as templates to guide the correction of flawed entries. The protocol demonstrates its efficacy across a range of chemical reactions, significantly enhancing dataset quality. This advancement provides a more robust foundation for developing reliable machine learning models in chemistry, thereby improving the accuracy of forward and retrosynthetic predictions. AutoTemplate marks a significant progression in the preprocessing of chemical reaction datasets, bridging a vital gap and facilitating more precise and efficient machine learning applications in organic synthesis. SCIENTIFIC CONTRIBUTION: The proposed automated preprocessing tool for chemical reaction data aims to identify errors within chemical databases. Specifically, if the errors involve atom mapping or the absence of reactant types, corrections can be systematically applied using reaction templates, ultimately elevating the overall quality of the database.

Protein Kinase C-Delta Mediates Cell Cycle Reentry and Apoptosis Induced by Amyloid-Beta Peptide in Post-Mitotic Cortical Neurons

Amyloid-beta peptide (Aβ) is a neurotoxic constituent of senile plaques in the brains of Alzheimer's disease (AD) patients. The detailed mechanisms by which protein kinase C-delta (PKCδ) contributes to Aβ toxicity is not yet entirely understood. Using fully differentiated primary rat cortical neurons, we found that inhibition of Aβ25-35-induced PKCδ increased cell viability with restoration of neuronal morphology. Using cyclin D1, proliferating cell nuclear antigen (PCNA), and histone H3 phosphorylated at Ser-10 (p-Histone H3) as the respective markers for the G1-, S-, and G2/M-phases, PKCδ inhibition mitigated cell cycle reentry (CCR) and subsequent caspase-3 cleavage induced by both Aβ25-35 and Aβ1-42 in the post-mitotic cortical neurons. Upstream of PKCδ, signal transducers and activators of transcription (STAT)-3 mediated PKCδ induction, CCR, and caspase-3 cleavage upon Aβ exposure. Downstream of PKCδ, aberrant neuronal CCR was triggered by overactivating cyclin-dependent kinase-5 (CDK5) via calpain2-dependent p35 cleavage into p25. Finally, PKCδ and CDK5 also contributed to Aβ25-35 induction of p53-upregulated modulator of apoptosis (PUMA) in cortical neurons. Together, we demonstrated that, in the post-mitotic neurons exposed to Aβs, STAT3-dependent PKCδ expression triggers calpain2-mediated p35 cleavage into p25 to overactivate CDK5, thus leading to aberrant CCR, PUMA induction, caspase-3 cleavage, and ultimately apoptosis.

TGFβ1 induces CXCL1 to promote stemness features in lung cancer

Chemokines critically orchestrate the tumorigenesis, metastasis, and stemness features of cancer cells that lead to poor outcomes. High plasma levels of transforming growth factor-β1 (TGFβ1) correlate with poor prognostic features in advanced lung cancer patients, thus suggesting the importance of TGFβ1 in the lung tumor microenvironment. However, the role of chemokines in TGFβ1-induced tumor stemness features remains unclear. Here, we clarify the previously undocumented role of CXCL1 in TGFβ1-induced lung cancer stemness features. CXCL1 and its receptor CXCR2 were significantly upregulated in TGFβ1-induced lung cancer stem cells (CSCs). CXCL1 silencing (shCXCL1) suppressed stemness gene expression, tumorsphere formation, colony formation, drug resistance, and in vivo tumorigenicity in TGFβ1-induced lung tumorspheres. Immunohistochemistry staining showed that patients with stage II/III lung cancer had higher expression levels of CXCL1. The levels of CXCL1 were positively associated with lymph node metastasis and correlated with the expression of the CSC transcription factor Oct-4. Furthermore, online database analysis revealed that CXCL1 expression was negatively correlated with lung cancer survival in patients. Patients with high TGFβ1/CXCL1/CD44 co-expression had a worse survival rate. We suggest that CXCL1 serves as a crucial factor in TGFβ1-induced stemness features of lung cancer.

Disease Burden of 30 Cancer Groups in Taiwan from 2000 to 2021

BACKGROUND

Assessment of the morbidity and mortality burden of cancers and their evolving trends is crucial for making informed policy decisions and effective resource allocation. We aimed to examine the burden of cancer in Taiwan from 2000 to 2021 using a national population-based database.

METHODS

Linking data from the Taiwan Cancer Registry and National Death Registry, we calculated years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life years (DALYs) for 30 specific cancer groups. Our methodology aligns with the Global Burden of Disease Study.

RESULTS

In Taiwan, from 2000 to 2021, the age-standardized cancer mortality rate decreased by 13.8%, while the prevalence rate increased by 80.5%. In 2021, the age-standardized DALYs for total cancer were 3784.2 per 100,000 population. In 2021, in Taiwan, lung, liver, and colorectal cancers were the leading contributors to cancer-related DALYs for men, whereas breast, lung, and colorectal cancers were predominant for women. Life expectancy decomposition analysis revealed distinct patterns by sex, with significant gains for specific cancers from 2000 to 2021: cervical, stomach, and liver cancers in women (0.20, 0.13, and 0.12 years, respectively) and liver, lung, and stomach cancers in men (0.37, 0.17, and 0.17 years, respectively).

CONCLUSION

Our finding of declining cancer DALY rates in Taiwan over the past two decades may reflect improvements in cancer control, particularly the significant decrease in liver and lung cancer burden. However, the rising burden of breast cancer and the sustained impact of colorectal and oral cancers warrant targeted attention in health policies, resource allocation, and research to reduce healthcare costs and improve quality of life.

Single-Layer Hexagonal Boron Nitride Nanopores as High-Performance Ionic Gradient Power Generators

Atomically thin two-dimensional (2D) materials have emerged as promising candidates for efficient energy harvesting from ionic gradients. However, the exploration of robust 2D atomically thin nanopore membranes, which hold sufficient ionic selectivity and high ion permeability, remains challenging. Here, the single-layer hexagonal boron nitride (hBN) nanopores are demonstrated as various high-performance ion-gradient nanopower harvesters. Benefiting from the ultrathin atomic thickness and large surface charge (also a large Dukhin number), the hBN nanopore can realize fast proton transport while maintaining excellent cation selectivity even in highly acidic environments. Therefore, a single hBN nanopore achieves the pure osmosis-driven proton-gradient power up to ≈3 nW under 1000-fold ionic gradient. In addition, the robustness of hBN membranes in extreme pH conditions allows the ionic gradient power generation from acid-base neutralization. Utilizing 1 m HCl/KOH, the generated power can be promoted to an extraordinarily high level of ≈4.5 nW, over one magnitude higher than all existing ionic gradient power generators. The synergistic effects of ultrathin thickness, large surface charge, and excellent chemical inertness of 2D single-layer hBN render it a promising membrane candidate for harvesting ionic gradient powers, even under extreme pH conditions.

Mild behavioural impairment in Parkinson's disease: a systematic review

Behavioural symptoms are common manifestations of Parkinson's disease (PD). Early behavioural symptoms characterise mild behavioural impairment (MBI). The prevalence and intensity of MBI in people with PD (PwP) have been studied across various cohorts. However, methodological differences have obscured our understanding of MBI in these individuals. This systematic review examines and synthesises findings from relevant studies, enhancing understanding of the symptoms and implications of MBI in PD. Nine studies from five separate research institutions were identified. The conceptualisation of MBI varied considerably, affecting the reported prevalence rates of MBI in individuals with early-stage PD. Among PwP, MBI was associated higher education and impaired cognition. Affective dysregulation and impulse control disorders were primary contributors to MBI; abnormal perception was least contributor. This systematic review underscores the specific characteristics and incidence of MBI in early-stage PD. Mood and impulse control disorders are primary concerns associated with MBI. Future longitudinal studies are required to clarify the progression of these symptoms and evaluate MBI's potential as an indicator for PD-related dementia or increased dependency.

Achieving Low Dissipation Factors and Low Dielectric Constants via Thermally Stable Naphthalene-Based Poly(ester-imide)s with Fluorine Groups

In recent years, polyimides (PIs) and their functional derivatives (i.e., poly(ester-imide)s (PEIs), poly(amide-imide)s (PAIs), etc.) have gained more attention in the microelectronic and optoelectronic industries because of their excellent thermal-mechanical stabilities, heat resistance, dielectric properties, and solution processabilities. Nevertheless, developing PIs with low dielectric constants (Dk) and low dissipation factors (Df) at high frequencies (≥10 GHz) is crucial for advanced mobile communications and high-frequency applications. Therefore, to achieve low dielectric properties in both Dk and Df at high frequencies, using PEIs with strong electron-withdrawing fluorine groups is a good synthetic strategy. Herein, a series of PEIs with trifluoromethyl (-CF3) groups are prepared from 2,2'-bis(trifluoromethyl)-[1,1'-biphenyl]-4,4'-diamine (TFMB), 1,4-phenylene bis(1,3-dioxo-1,3-dihydroisobenzofuran-5-carboxylate) (TAHQ), and naphthalene-2,6-diyl bis(1,3-dioxo-1,3-dihydroisobenzofuran-5-carboxylate) (NPDA) monomers. In addition, the molar ratio of TAHQ/NPDA modulates the comprehensive performances of the derived PEI films, and each performance of the PEI films is addressed in detail. From the theoretical calculations, when increasing the NPDA ratio from 0 to 100% in the TFMB/TAHQ system, the molar free volume increases and balances the polarizability and linearity, which is beneficial for achieving low dielectric properties. As a result, all the PEI films exhibit excellent thermal stabilities with thermal decomposition temperature at 5% weight loss (Td5%) over 470 °C and glass transition temperature (Tg) at 215-250 °C. In addition, all the PEI films show decent coefficients of thermal expansion (CTE) in the range of 16-40 ppm/°C and good mechanical stabilities. Moreover, all PEI films exhibit low dielectric properties at high frequencies. When increasing the NPDA concentration from 0 to 100%, both Dk/Df values gradually decrease from 3.19/0.00322 for PEI-NPDA-0 to 2.90/0.00174 for PEI-NPDA-100 at a 10 GHz frequency. Particularly, the Df values are one of the lowest values under the 10 GHz frequency. The results demonstrate that preparing PEI backbones with fluorine groups is a good synthetic strategy for achieving low dielectric properties at higher frequencies.

Topology Optimization Enables High-Q Metasurface for Color Selectivity

Nonlocal metasurfaces, exemplified by resonant waveguide gratings (RWGs), spatially and angularly configure optical wavefronts through narrow-band resonant modes, unlike the broad-band and broad-angle responses of local metasurfaces. However, forward design techniques for RWGs remain constrained at lower efficiency. Here, we present a topology-optimized metasurface resonant waveguide grating (MRWG) composed of titanium dioxide on a glass substrate capable of operating simultaneously at red, yellow, green, and blue wavelengths. Through adjoint-based topology optimization, while considering nonlocal effects, we significantly enhance its diffraction efficiency, achieving numerical efficiencies up to 78% and Q-factors as high as 1362. Experimentally, we demonstrated efficiencies of up to 59% with a Q-factor of 93. Additionally, we applied our topology-optimized metasurface to color selectivity, producing vivid colors at 4 narrow-band wavelengths. Our investigation represents a significant advancement in metasurface technology, with potential applications in see-through optical combiners and augmented reality platforms.

Cross-population enhancement of PrediXcan predictions with a gnomAD-based east Asian reference framework

Over the past decade, genome-wide association studies have identified thousands of variants significantly associated with complex traits. For each locus, gene expression levels are needed to further explore its biological functions. To address this, the PrediXcan algorithm leverages large-scale reference data to impute the gene expression level from single nucleotide polymorphisms, and thus the gene-trait associations can be tested to identify the candidate causal genes. However, a challenge arises due to the fact that most reference data are from subjects of European ancestry, and the accuracy and robustness of predicted gene expression in subjects of East Asian (EAS) ancestry remains unclear. Here, we first simulated a variety of scenarios to explore the impact of the level of population diversity on gene expression. Population differentiated variants were estimated by using the allele frequency information from The Genome Aggregation Database. We found that the weights of a variants was the main factor that affected the gene expression predictions, and that ~70% of variants were significantly population differentiated based on proportion tests. To provide insights into this population effect on gene expression levels, we utilized the allele frequency information to develop a gene expression reference panel, Predict Asian-Population (PredictAP), for EAS ancestry. PredictAP can be viewed as an auxiliary tool for PrediXcan when using genotype data from EAS subjects.

Problem-solving method and cooperative learning model in nursing education: a single-group pre-post-test study

BACKGROUND

Prior studies suggest that traditional teaching methods often fail to accommodate students' individual differences, needs, problem-solving skills, and cooperative learning abilities. This study evaluates the effectiveness of a problem-solving method (PSM) and cooperative learning model (CLM) in nursing education, with a focus on their impact on nursing students' progress in Paediatric Nursing (PN).

METHODS

A single-group pre-post-test was employed from September 2021 to January 2022. A convenience sample of 51 third-year nursing students enrolled in the PN course at Da-Yeh University, Taiwan, participated in the study. The intervention consisted of an 18-week PN course that was conducted from September 22, 2021 to January 25, 2022 (every Thursday, 13:20 - 16:10). Quantitative questionnaires were administered at three intervals: the first, ninth, and eighteenth weeks of the semester. The research tools included a Basic Information Form (BIF) and the Quantitative Learning Effectiveness Score (QLES). Data were analysed using descriptive statistics, analysis of variance (ANOVA) tests, and linear regression analysis.

RESULTS

The post-test results at Week 9 revealed that students' self-perceived PSM, self-perceived problem-solving ability, and self-perceived cooperative learning were significantly greater than their baseline scores (p < 0.05). Similarly, the post-test results at Week 18 indicated that students' self-perceived problem-solving ability, learning satisfaction, and quantitative learning effectiveness were significantly greater than their baseline scores (p < 0.05).

CONCLUSION

This study highlights the benefits of incorporating PSM and CLM into nursing education. The findings suggest that these approaches can enhance learning effectiveness and provide valuable insights into improving PN outcomes for nursing students.

Carvedilol Confers Ferroptosis Resistance in HL-1 Cells by Upregulating GPX4, FTH1, and FTL1 and Inducing Metabolic Remodeling Under Hypoxia/Reoxygenation

Hypoxia/reoxygenation (HR) often occurs under cardiac pathological conditions, and HR-induced oxidative stress usually leads to cardiomyocyte damage. Carvedilol, a non-selective β-blocker, is used clinically to treat cardiac ischemia diseases. Moreover, Carvedilol has also been reported to have an antioxidant ability by reducing lipid peroxidation. However, the mechanism of Carvedilol to inhibit lipid peroxidation is still elusive. To explore the protective mechanism of Carvedilol to resist lipid peroxidation on cardiomyocytes, HL-1 cells were cultured under normoxia, hypoxia, and HR and treated with Carvedilol to investigate the alteration on metabolism, protein expression, and mRNA level to explain its oxidative mechanism. The study found that Carvedilol upregulated glutathione peroxidase 4 (GPX4) protein expression to resist HR-induced lipid peroxidation by metabolic remodeling under HR. Also, Carvedilol promoted ferroptosis-related genes, ferritin heavy chain 1 (FTH1) and ferritin light chain 1 (FTL1) mRNA levels, to reduce lipid peroxidation under both hypoxia and HR. In conclusion, our study explores a mechanism by which Carvedilol inhibits ferroptosis by upregulating GPX4, FTH1, and FTL1 levels to downregulate lipid peroxidation under HR. The study provides a potential strategy for using Carvedilol in clinical applications, inspiring further research and development in the area of heart diseases.

Association between parental well-being and preschooler stress measured as hair cortisol concentration: A prospective cohort study

Hair cortisol concentration (HCC) is a valuable biomarker for evaluating chronic stress in preschoolers. However, few studies have explored early life HCC and its associated factors. This prospective cohort study analysed the HCC in children aged 6-48 months and its associations with parental HCC as well as positive and negative parental mental health outcomes. We used data from the ongoing Longitudinal Examination Across Prenatal and Postpartum Health in Taiwan (LEAPP-HIT) project, conducted in Taipei between 2020 and 2024. Hair samples were collected from both parents and children in 177 families (91 samples obtained during pregnancy and 86 during the postpartum period). The parents also completed self-reported questionnaires. Multiple linear regression was conducted to analyse the data. We observed a significant positive correlation between parents' and preschoolers' HCC. Furthermore, maternal depression (adjusted beta coefficient [aβ] = 0.09, 95% confidence interval [CI] = 0.02, 0.16) and perceived stress (aβ = 0.15, 95% CI = 0.02, 0.26) were positively associated with preschoolers' HCC. By contrast, higher maternal eudaimonia was associated with lower HCC in preschoolers (aβ = -0.11, 95% CI = -0.20, -0.01). For parents, maternal depression, anxiety, and perceived stress were independently associated with an increased HCC during the postnatal period, whereas maternal eudaimonia was negatively associated with HCC. Our results indicate that both mothers and fathers affect children's responses to stress. Assessment of cortisol stress hormone concentrations through hair samples can be a key means of detecting preschoolers' stress levels and enabling early intervention.

Enhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks

Accurately predicting activation energies is crucial for understanding chemical reactions and modeling complex reaction systems. However, the high computational cost of quantum chemistry methods often limits the feasibility of large-scale studies, leading to a scarcity of high-quality activation energy data. In this work, we explore and compare three innovative approaches (transfer learning, delta learning, and feature engineering) to enhance the accuracy of activation energy predictions using graph neural networks, specifically focusing on methods that incorporate low-cost, low-level computational data. Using the Chemprop model, we systematically evaluated how these methods leverage data from semiempirical quantum mechanics (SQM) calculations to improve predictions. Delta learning, which adjusts low-level SQM activation energies to align with high-level CCSD(T)-F12a targets, emerged as the most effective method, achieving high accuracy with substantially reduced data requirements. Notably, delta learning trained with just 20-30% of high-level data matched or exceeded the performance of other methods trained with full data sets, making it advantageous in data-scarce scenarios. However, its reliance on transition state searches imposes significant computational demands during model application. Transfer learning, which pretrains models on large data sets of low-level data, provided mixed results, particularly when there was a mismatch in the reaction distributions between the training and target data sets. Feature engineering, which involves adding computed molecular properties as input features, showed modest gains, particularly in thermodynamic properties. Our study highlights the trade-offs between accuracy and computational demand in selecting the best approach for enhancing activation energy predictions. These insights provide valuable guidelines for researchers aiming to apply machine learning in chemical reaction engineering, helping to balance accuracy with resource constraints.

A large language model framework for literature-based disease-gene association prediction

With the exponential growth of biomedical literature, leveraging Large Language Models (LLMs) for automated medical knowledge understanding has become increasingly critical for advancing precision medicine. However, current approaches face significant challenges in reliability, verifiability, and scalability when extracting complex biological relationships from scientific literature using LLMs. To overcome the obstacles of LLM development in biomedical literature understating, we propose LORE, a novel unsupervised two-stage reading methodology with LLM that models literature as a knowledge graph of verifiable factual statements and, in turn, as semantic embeddings in Euclidean space. LORE captured essential gene pathogenicity information when applied to PubMed abstracts for large-scale understanding of disease-gene relationships. We demonstrated that modeling a latent pathogenic flow in the semantic embedding with supervision from the ClinVar database led to a 90% mean average precision in identifying relevant genes across 2097 diseases. This work provides a scalable and reproducible approach for leveraging LLMs in biomedical literature analysis, offering new opportunities for researchers to identify therapeutic targets efficiently.

ShiNyP: Unlocking SNP-Based Population Genetics-AI-Assisted Platform for Rapid and Interactive Visual Exploration

Efficient and accessible analysis of genome-wide single nucleotide polymorphism data is vital for advancing molecular biology, evolutionary genetics, and breeding research. However, current analytical pipelines are often fragmented and require command-line expertise, limiting accessibility for many researchers. Here, we present ShiNyP, an interactive R/Shiny platform that integrates all popular single nucleotide polymorphism analysis modules within a single and intuitive user interface, supporting the entire workflow from data import and quality control to population structure inference, diversity analysis, selective scan, and core collection. ShiNyP accommodates datasets from haploid, diploid, and polyploid species and automates the generation of over 70 publication-ready visualizations and summary tables. A distinctive feature is its automated report module, which employs generative AI to deliver structured, interpretable narratives of complex statistical results. Performance benchmarks demonstrate that ShiNyP efficiently processes large-scale datasets on standard hardware. The ShiNyP platform is freely available at https://github.com/TeddYenn/ShiNyP, providing an efficient, reproducible, and user-friendly solution for population genomics research.

Confinement Accelerates Water Oxidation Catalysis: Evidence from In Situ Studies

Basic insight into the structural evolution of electrocatalysts under operating conditions is of substantial importance for designing water oxidation catalysts. The first-row transition metal-based catalysts present state-of-the-art oxygen evolution reaction (OER) performance under alkaline conditions. Apparently, confinement has become an exciting strategy to boost the performance of these catalysts. The van der Waals (vdW) gaps of transition metal dichalcogenides are acknowledged to serve as a suitable platform to confine the first-row transition metal catalysts. This study focuses on confining Ni(OH)2 nanoparticle in the vdW gaps of 2D exfoliated SnS2 (Ex-SnS2 ) to accelerate water oxidation and to guarantee long term durability in alkaline solutions. The trends in oxidation states of Ni are probed during OER catalysis. The in situ studies confirm that the confined system produces a favorable environment for accelerated oxygen gas evolution, whereas the un-confined system proceeds with a relatively slower kinetics. The outstanding OER activity and excellent stability, with an overpotential of 300 mV at 100 mA cm-2 and Tafel slope as low as 93 mV dec-1 results from the confinement effect. This study sheds light on the OER mechanism of confined catalysis and opens up a way to develop efficient and low-cost electrocatalysts.