Browse Articles

Enhancing CAR- and TCR-mediated targeting of cancer via an immune synapse-stabilizing receptor

Sustainable and interpretable heart disease prediction: a clinical decision support approach for biomedical healthcare applications

Short-range order in high entropy carbides

Abstract High-entropy carbides (HECs) are a new class of materials with properties that are promising for applications in extreme environments, involving high temperature, corrosion, and high ion-flux. In HECs, multiple principal cations form solid solutions, similar to medium/high-entropy alloys (M/HEA). However, mixing of atoms can be non-ideal, resulting in chemical short-range order (CSRO). CSRO has been already reported in M/HEAs, cation-disordered oxides, and high-entropy oxides and in many cases, it was found to have significant impact on materials properties. CSRO in covalently-bonded high-entropy ceramics has not been observed so far, and its potential impact on materials properties is unknown. In contrast to M/HEAs, in HECs only one of the sublattices forms a solid solution, and therefore it is unclear whether the concept of CSRO extends to HECs. Here, we report the observation of CSRO in multiple HECs using a combination of atomistic simulations and scanning transmission electron microscopy. We find that CSRO in HECs can be controlled by both selection of chemical elements and heat treatment, and it significantly improves radiation resistance, although it is not the only factor. Our findings expand the understanding of CSRO to HECs and provide a pathway for design of new materials for extreme environments.

Integrative metabolomic and single-cell transcriptomic analysis of recurrent condyloma acuminatum in humans

Interfacial dipole engineering by self-assembled molecules in n-i-p and p-i-n perovskite solar cells

Efficient target detection method based on wavelet transform and progressive feature pyramid network: a case study of power grid inspection

Regulating interfacial water for oxygen transfer to benzylic C(sp3)–H bonds via Ni-activated tungsten-oxygen covalency

Improved sleep quality is independently associated with decision-making recovery in panic disorder: a longitudinal study

Abstract Cognitive impairments are frequently observed in patients with panic disorder (PD), yet the relationship between sleep quality and cognitive recovery remains underexplored. This study investigated whether improvements in sleep quality during routine psychiatric care are prospectively associated with changes in decision-making in PD. Eighty-one patients with PD and 81 healthy controls were assessed using standardized clinical and cognitive measures, including the Pittsburgh Sleep Quality Index and Iowa Gambling Task. After three months of naturalistic follow-up, 38 patients were reassessed. Patients with PD initially exhibited significantly poorer sleep quality, more severe symptoms, and greater cognitive impairment than controls. Over the follow-up period, both clinical symptoms and sleep quality improved. Notably, improvements in sleep quality were independently associated with better performance on the Iowa Gambling Task, suggesting a relationship with decision-making performance. Changes in executive function showed only a non-significant trend in relation to sleep improvement. These findings suggest that improved sleep quality is independently associated with cognitive improvements, particularly decision-making, in PD. Addressing sleep disturbances in clinical care may be crucial for optimizing cognitive outcomes in patients with panic disorder.

Topology of the Cell Membrane Interface for the Physical Re-Encoding of Neural Signals

Machine learning for microscopy data analytics targeting real-time optical characterization of semiconductor nanocrystals

Abstract Semiconductor nanocrystals with uniform morphology and composition are expected to show consistent responses during light-matter interactions. However, microscopy reveals significant variations in their photoluminescence blinking patterns, even under identical experimental conditions. This discrepancy arises from differences in crystal defects and nonradiative trap states. As a result, heterogeneous blinking patterns serve as valuable indicator of material quality, uncovering several concealed features through statistical analysis of large datasets. Nonetheless, efficient segregation and analysis of numerous blinking trajectories remain a challenge due to laborious calculations, computational bottlenecks, and manual intervention. In this study, we introduce a robust unsupervised machine learning (UML) assisted module to cluster high-dimensional blinking patterns in near-real-time, while calculating category-wise power spectral densities (PSD) to investigate active traps. Furthermore, we explore the impact of data preprocessing on clustering performance. The ‘clustering-segregation-analysis’ (UML-PSD) methodology demonstrates versatility, paving a way to advance contemporary (micro)spectroscopy, specifically for rapid and cost-effective optical characterization of semiconductor nanocrystals.

Mediating the role of medical coping styles among psychosocial factors in breast cancer patients with type C personality

High quality-factor terahertz phonon-polaritons in layered lead iodide

ZenBand: a numerical solver of photonic crystals with a graphical user interface

Abstract We developed an open-source Plane Wave Expansion Method solver using Python and a custom Tkinter library to solve a design oriented problem of photonic crystal dispersion for known classical examples, custom geometries, and symmetries. Such structures are capable of light confinement, omnidirectional reflection, beam collimation and negative refraction. We dive deeper into the diagonally anisotropic photonic crystals, whose Plane Wave Expansion algorithm is directly embedded in the application. The user interface is present in the developer’s repository link: https://github.com/ZenTunturi/ZenBand.

Bell correlations between momentum-entangled pairs of 4He* atoms

The weight-adjusted waist index predicts sarcopenia in community-dwelling older adults in a nationwide multicenter prospective study

Loss-of-function mutations in the melanocortin-2-receptor (mc2r) lead to skin hyperpigmentation in teleost fish

Abstract Melanocortins regulate pigmentation via melanocortin receptors (MCRs), which are highly conserved across vertebrates. Unlike other MCRs, the melanocortin 2 receptor (MC2R) is exclusively activated by ACTH; however, its role in pigmentation remains unclear. Using CRISPR/Cas9-generated mc2r knockout zebrafish, we demonstrated that the loss of mc2r in zebrafish results in impaired interrenal steroidogenesis and pronounced hyperpigmentation characterized by an increased number of melanophores and xanthophores while preserving normal patterning. Transcriptomic analyses revealed the upregulation of genes involved in melanosome formation, melanin synthesis, lipid metabolism, and carotenoid accumulation. These findings demonstrate that, in addition to controlling steroidogenesis, mc2r plays a key role in pigment cell development and metabolic regulation.

Distinct gut microbiome signatures associated with sedentary behavior improvement following rehabilitation in chronic obstructive pulmonary disease patients with higher functional exercise capacity

Chemical Synthesis of Native ADP-Ribosylated Oligonucleotides Enables Analysis of DNA ADP-Ribosylation Hydrolase Specificity

Explainable attention based few shot LSTM for intrusion detection in imbalanced cyber physical system networks

DNS fingerprint based on user activity