Browse Articles

Seismic constraints on glacier density

Abstract Terrestrial ice bodies are important regulators of climate and sea level variations. They influence the water cycle, provide fresh water and energy for human society, and contribute to the living basis of numerous ecosystems. Understanding the structure and dynamics of land ice requires knowledge of its mass density, which is essential for ice core climatology and estimates of mass balance components, such as mass loss, ice discharge and surface melt. We combine densely sampled fiber-optic sensing data from strong serendipitous anthropogenic sources with Hamiltonian Monte Carlo sampling to extract direct seismic constraints on firn density (i.e. the transitional layer between fresh snow and glacial ice). Our approach avoids biases introduced by subjective regularization choices, does not require empirical scaling relations from seismic wave speeds to density, and provides reliable uncertainty estimates. We demonstrate that high-quality surface-wave overtone data can directly constrain density to around 100 m depth. Commonly used scaling relations from seismic wave speeds to density, however, fail to reproduce resolvable details of glacial density structure, and they tend to deviate from direct constraints on the order of ±10 %. Consequently, ice mass inferred from seismic wave speed may be incorrect by a similar amount.

A machine learning approach to risk based asset allocation in portfolio optimization

Ultranarrow electroluminescence from magnetic excitons in the van der Waals antiferromagnetic semiconductor NiPS3

Correction: Deep learning assisted LDPC decoding for 5G IoT networks in fading environments

Soil total nitrogen prediction based on multi-temporal synthetic Sentinel-2 images under different land use types

First-principles full-dimensional modelling of vibrational energy transfer of molecule scattering from metal surfaces

Analysis of soil-pile interaction considering slope effect in integral abutment jointless bridges (IAJBs) under cyclic loading

Prevalence, clinical characteristics, and associated factors of molar-incisor hypomineralisation among schoolchildren: a cross-sectional study in the Vietnamese Northern provinces

Abstract This study aimed to analyse the prevalence, clinical status of Molar-incisor hypomineralisation (MIH), and associated factors in schoolchildren from Northern provinces in Vietnam. A cross-sectional study was performed in 2024 among 1834 7- to 11-year-old schoolchildren across three provinces. MIH and enamel defects were diagnosed using the European Academy of Paediatric Dentistry criteria. Clinical dental examinations were undertaken, and parental questionnaires collected relevant background information. The overall MIH prevalence was 12.7% (95% CI 11.2–14.3%). The lower left first permanent molar was the most affected tooth. For incisors, the upper right central incisor was most involved. Common clinical presentations included white or creamy demarcated opacities, lesions involving less than one-third of the tooth surface, and severe lesions. Except for age, there were no significant relationships between MIH and gender, geography, or most prenatal, perinatal, and postnatal factors. Postnatal pneumonia was significantly associated with MIH (OR = 1.49; 95% CI 1.000035–2.24). Hypomineralised second primary molars (HSPM) were observed in 7.1% of children (95% CI 5.96–8.36%) and increased the risk of MIH significantly (OR = 8.48; 95% CI 5.81–12.39). This study provided population-based data on MIH in Vietnam and contextualized it within global findings, highlighting the importance of early diagnosis and management, while acknowledging recent translational perspectives under the broader concept of molar hypomineralisation (MH).

Plastic hepatocyte states limit liver cancer development

Abstract The liver has remarkable regenerative capacity owing to the boundless proliferative potential of hepatocytes. During liver injury, sustained regeneration must be balanced by mechanisms limiting overgrowth and tumorigenesis. Epithelial plasticity is frequently observed during liver damage and is thought to mediate production of biliary epithelial cells (BECs) or hepatocytes, depending on tissue needs. Here we show that hepatocytes persisting in plastic states are present in virtually all liver injury contexts, representing the predominant outcome of hepatocyte reprogramming rather than their full BEC conversion. By developing tools to trap mouse hepatocytes in plastic states in vivo and using models of regeneration and transplantation, we show that plastic hepatocytes are refractory to proliferation cues from the microenvironment. Unlike terminally differentiated hepatocytes, plastic hepatocytes resist proliferation driven by endogenous oncogenic stimuli. Thus, acquisition of plastic states represents a protective mechanism that constrains hepatocyte proliferation, limiting overgrowth and tumorigenesis during liver disease.

Novel conductive polycarbazolic polymer embedded with palladium nanoparticles as a highly sensitive electrochemical sensor for hydrazine detection

Abstract To meet the demand for sensitive, trace-level hydrazine detection, we present a novel, high-sensitivity electrochemical sensor. We synthesized a novel carbazole-based conducting polymer (CRCP) as a distinctive host matrix, demonstrating exceptional stability, high redox potential, and excellent electrochemical properties. Subsequently, we developed an innovative electrochemical sensor by controllably embedding Pd nanoparticles (Pd) into this as-synthesized CRCP matrix using a simple cyclic voltammetry (CV) method to create a highly efficient Pd/PCz@GCE system for sensitive detection of hydrazine in alkaline media. The modified electrode exhibited significant electrocatalytic activity towards hydrazine oxidation. Notably, the FE-SEM analysis revealed an even distribution of spherical Pd nanoparticles (measuring 62–98 nm) across the polymer surface, a key factor that enhances electrocatalytic performance. It has a low detection limit of 0.084 μM, high sensitivity (56.64 μA Μm −1  cm −2 ), and excellent selectivity and is comparable or superior to previously reported sensors. The sensor offers a broad linear detection range (0.3–100 μM), and its performance is reproducible, repeatable, and stable. Kinetic studies revealed a diffusion-controlled process at the electrode surface. The effectiveness of the Pd/PCz@GCE was evaluated in real samples. These results indicate that the Pd/PCz@GCE sensor could serve as a reliable and practical platform for sensitive hydrazine detection in environmental analysis.

Optimizing DCD donor liver function with resveratrol during machine perfusion

Solvent-mediated chirality inversion in orthogonal hierarchical assembly of achiral carbene-anchored gold cluster

A lactylation-related gene signature predicts metastasis and prognosis in breast cancer

Predictive value of subharmonic-aided pressure estimation for diagnosing clinically significant portal hypertension

A noncanonical polyamine from bacteria antagonizes host mitochondrial function

Altered expression of LINC03091 and LINC03090 LncRNAs in bipolar disorder: a case-control study

Abstract Long non-coding RNAs (lncRNAs) are widely expressed and play an essential role in gene regulation through various transcriptional and post-transcriptional mechanisms. Recent findings have highlighted the role of lncRNAs in sustaining cellular homeostasis and neurogenesis within the brain. An increasing number of reports have identified dysregulated lncRNAs linked to psychiatric disorders, including bipolar disorder (BD). We analyzed the expression levels of LRRC2-AS1, LINC03091, and LINC03090 lncRNAs in the blood samples of 50 patients with BD and 50 healthy individuals matched by age, sex, and ethnicity. RNA extraction and cDNA synthesis were performed, followed by real-time polymerase chain reaction to quantify lncRNA expression levels. Receiver operating characteristic (ROC) curve analysis was used to assess the biomarker potential. Furthermore, the relationship between gene expression levels and BD comorbidities was explored. Our findings revealed a significant enhancement in LINC03091 and LINC03090 expression in patients with BD compared with healthy subjects ( P  < 0.0001 and P  = 0.02, respectively). However, the expression levels of LRRC2-AS1 was not significant ( P  = 0.69). ROC curve analysis indicated that LINC03091 (AUC = 0.74, P  < 0.0001) and LINC03090 (AUC = 0.64, P  = 0.01) expression levels could effectively differentiate patients from healthy controls. Considering these results, LINC03091 and LINC03090 may have a crucial role in BD and could serve as biomarkers for diagnostic and predictive applications.

Quantifying and modeling respirable dust and crystalline silica exposure in rice mills using the CART algorithm

Structural basis for human chondroitin sulfate chain polymerization

Abstract Chondroitin sulfates are complex polysaccharide chains that regulate various biological processes at the cell surface and within the extracellular matrix. Here, we identify four heterodimeric complexes responsible for chondroitin sulfate chain polymerization in humans: CHSY1-CHPF, CHSY1-CHPF2, CHSY3-CHPF, and CHSY3-CHPF2. Using a custom-tailored in vitro glycosylation assay based on chemo-enzymatically synthesized fluorescent substrates, we demonstrate that all four complexes exhibit chain polymerization activity. The cryo-EM structure of the CHSY3-CHPF complex provides molecular insights into the chondroitin sulfate chain polymerization reaction. The architecture of the catalytic sites suggests that CHSY1 and CHSY3 are enzymatically active, while CHPF and CHPF2 primarily play a stabilizing role. Mutational analysis of purified enzyme complexes, combined with an in cellulo complementation assay, confirms that only CHSY1 and CHSY3 have bifunctional glycosyltransferase activities. Based on the spatial arrangement of the catalytic sites, we propose that chondroitin sulfate chain polymerization follows a non-processive, distributive mechanism.

A hybrid recurrent neural network and optimization framework for intelligent mobile robot navigation in smart manufacturing

Measurement and modeling of rizatriptan in supercritical CO2 for pharmaceutical processing

Abstract This study examines the solubility of rizatriptan, a migraine medication, in supercritical carbon dioxide. The goal is to promote environmentally friendly drug manufacturing methods, such as antisolvent precipitation via supercritical fluids. Solubility levels were evaluated at temperatures ranging from 308.2 K to 338.2 K and pressures ranging from 12 to 30 MPa. These evaluations produced mole fraction values ranging from 0.24 × 10 −4 to 4.19 × 10 −4 and dissolution concentrations ranging from 0.008 g/L to 0.302 g/L. An estimated crossover pressure of approximately 15 MPa was identified, resulting from the interaction between the compound’s vapor pressure and the fluid’s density. Seven density-based models such as Chrastil, Bartle, Kumar–Johnston (K–J), and Mendez–Santiago–Teja (MST), Bian et al. and Sodeifian et al. (Ⅰ and Ⅱ) models were implemented. The Sodeifian et al. model (Ⅱ) demonstrated the strongest alignment (AARD = 7.78%, R 2 = 0.990). Key extracted thermodynamic metrics include the overall enthalpy (38.06 kJ/mol), the enthalpy associated with vaporization (50.55 kJ/mol), and the enthalpy linked to solvation (− 12.49 kJ/mol). Additionally, three thermodynamic equations Peng–Robinson, Soave–Redlich–Kwong, and regular solution were examined. The regular solution model produced the best results (AARD = 6.89%, R 2 = 0.991). These results provide reliable data and simulation models that can improve supercritical carbon dioxide methodologies, and advance eco-friendly drug production strategies.