N-methylpyrrolidone-based electrolyte modulated CF bond weakening and Interface optimization synergistically enhances Li/CF batteries energy density.

Lithium/fluorinated carbon (Li/CF) batteries have garnered substantial interest from researchers due to their superior energy density and low self-discharge characteristics. However, the strong covalent CF bond in the CF cathode limits its discharge kinetics, affecting the actual power density and operating voltage. In this work, N-methylpyrrolidone (NMP) with high donor number has proposed as the main solvent of the electrolyte to facilitate the breaking of the CF bond through a bimolecular nucleophilic substitution (S2) reaction.

C-reactive protein-to-lymphocyte ratio and hemoglobin-to-red cell distribution width ratio as effective prognostic predictors in pediatric patients with neuroblastoma.

Unlabelled: Inflammatory responses critically influence tumor progression, yet traditional inflammatory biomarkers in neuroblastoma (NB) research lack optimal sensitivity and specificity. This study aimed to evaluate the prognostic value of two pretreatment inflammatory biomarkers: the C-reactive protein-to-lymphocyte ratio (CLR) and hemoglobin-to-red cell distribution width ratio (HRR) in NB patients. A retrospective analysis was conducted on NB patients diagnosed and treated at Shanghai Children's Medical Center (2016-2022).

Integrated single-cell and bulk RNA sequencing analysis establishes a cancer associated fibroblast-related signature for predicting prognosis and therapeutic responses in neuroblastoma.

Background: Cancer-associated fibroblasts (CAFs) greatly contribute to the growth, invasion, metastasis and drug resistance of neuroblastoma (NB). This study aimed to construct a CAF-related prognostic model and identify the immune status of patients with NB via single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq).

Methods: ScRNA-seq data of NB acquired from the Gene Expression Omnibus (GEO) database were used to identify cellular subpopulations.

Analytical model for optical permittivity in direct bandgap semiconductors with Gaussian distributed bandgap energies.

The optical permittivity of monocrystalline direct bandgap semiconductors can be described well by critical point models based on parabolic band approximation (CPPB). However, the optical permittivity of polycrystalline direct bandgap semiconductors like halide perovskite thin films requires a more precise description. Till now, only thermal bandgap fluctuation or exponential decay of density of states is incorporated into the CPPB model.

An AI Agent for Fully Automated Multi-Omic Analyses.

With the fast-growing and evolving omics data, the demand for streamlined and adaptable tools to handle bioinformatics analysis continues to grow. In response to this need, Automated Bioinformatics Analysis (AutoBA) is introduced, an autonomous AI agent designed explicitly for fully automated multi-omic analyses based on large language models (LLMs). AutoBA simplifies the analytical process by requiring minimal user input while delivering detailed step-by-step plans for various bioinformatics tasks.

Behavior, attitude, perception, and knowledge regarding fertility preservation among Chinese pediatric oncologists: a survey in China.

Purpose: Clinical specialists are supposed to inform childhood cancer patients of infertility risk and conduct fertility preservation (FP). However, little is known about whether doctors in China are fully prepared. This study aimed to investigate behavior, attitude, perception, and knowledge regarding FP among pediatric oncological specialists in a nation wide survey, to set the stage for improvements in current clinical practice patterns.

Reference-informed prediction of alternative splicing and splicing-altering mutations from sequences.

Alternative splicing plays a crucial role in protein diversity and gene expression regulation in higher eukaryotes, and mutations causing dysregulated splicing underlie a range of genetic diseases. Computational prediction of alternative splicing from genomic sequences not only provides insight into gene-regulatory mechanisms but also helps identify disease-causing mutations and drug targets. However, the current methods for the quantitative prediction of splice site usage still have limited accuracy.

SANTO: a coarse-to-fine alignment and stitching method for spatial omics.

With the flourishing of spatial omics technologies, alignment and stitching of slices becomes indispensable to decipher a holistic view of 3D molecular profile. However, existing alignment and stitching methods are unpractical to process large-scale and image-based spatial omics dataset due to extreme time consumption and unsatisfactory accuracy. Here we propose SANTO, a coarse-to-fine method targeting alignment and stitching tasks for spatial omics.

HELM-GPT: de novo macrocyclic peptide design using generative pre-trained transformer.

Motivation: Macrocyclic peptides hold great promise as therapeutics targeting intracellular proteins. This stems from their remarkable ability to bind flat protein surfaces with high affinity and specificity while potentially traversing the cell membrane. Research has already explored their use in developing inhibitors for intracellular proteins, such as KRAS, a well-known driver in various cancers.

Reference-informed prediction of alternative splicing and splicing-altering mutations from sequences.

Alternative splicing plays a crucial role in protein diversity and gene expression regulation in higher eukaryotes and mutations causing dysregulated splicing underlie a range of genetic diseases. Computational prediction of alternative splicing from genomic sequences not only provides insight into gene-regulatory mechanisms but also helps identify disease-causing mutations and drug targets. However, the current methods for the quantitative prediction of splice site usage still have limited accuracy.

PPML-Omics: A privacy-preserving federated machine learning method protects patients' privacy in omic data.

Modern machine learning models toward various tasks with omic data analysis give rise to threats of privacy leakage of patients involved in those datasets. Here, we proposed a secure and privacy-preserving machine learning method (PPML-Omics) by designing a decentralized differential private federated learning algorithm. We applied PPML-Omics to analyze data from three sequencing technologies and addressed the privacy concern in three major tasks of omic data under three representative deep learning models.

Ferroptosis Inducers Kill Mesenchymal Stem Cells Affected by Neuroblastoma.

Bone marrow (BM) is the most common site of neuroblastoma (NB) metastasis, and its involvement represents poor patient prognosis. In accordance with the "seed and soil" theory of tumor metastasis, BM provides a favorable environment for NB metastasis while bone marrow mesenchymal stem cells (BMSCs) have been recognized as a central part of tumor stroma formation. Yet, there is currently no effective method for intervening these BMSCs.

Eugenol-Preconditioned Mesenchymal Stem Cell-Derived Extracellular Vesicles Promote Antioxidant Capacity of Tendon Stem Cells and .

Tendon stem cells (TSCs) are often exposed to oxidative stress at tendon injury sites, which impairs their physiological effect as well as therapeutic application. Recently, extracellular vesicles (EVs) derived from bone marrow mesenchymal stem cells (BMSCs) were shown to mediate cell protection and survival under stress conditions. The function of BMSC-EVs may be affected by pretreatment with various factors such as eugenol (EUG)-a powerful antioxidant.

Quantifying functional impact of non-coding variants with multi-task Bayesian neural network.

Motivation: Advances in high-throughput genotyping and sequencing technologies during recent years have revealed essential roles of non-coding regions in gene regulation. Genome-wide association studies (GWAS) suggested that a large proportion of risk variants are located in non-coding regions and remain unexplained by current expression quantitative trait loci catalogs. Interpreting the causal effects of these genetic modifications is crucial but difficult owing to our limited knowledge of how regulatory elements function.

Continuous Draw Spinning of Extra-Long Silver Submicron Fibers with Micrometer Patterning Capability.

Ultrathin metal fibers can serve as highly conducting and flexible current and heat transport channels, which are essential for numerous applications ranging from flexible electronics to energy conversion. Although industrial production of metal fibers with diameters of down to 2 μm is feasible, continuous production of high-quality and low-cost nanoscale metal wires is still challenging. Herein, we report the continuous draw spinning of highly conductive silver submicron fibers with the minimum diameter of ∼200 nm and length of more than kilometers.

Unraveling the enhanced Oxygen Vacancy Formation in Complex Oxides during Annealing and Growth.

The reduction of oxides during annealing and growth in low pressure processes is a widely known problem. We hence investigate the influence of mere annealing and of growth in vacuum systems to shed light on the reasons behind the reduction of perovskites. When comparing the existing literature regarding the reduction of the perovskite model material SrTiO it is conspicuous that one finds different oxygen pressures required to achieve reduction for vacuum annealing and for chemically controlled reducing atmospheres.

Formation mechanism of Ruddlesden-Popper-type antiphase boundaries during the kinetically limited growth of Sr rich SrTiO thin films.

We elucidated the formation process for Ruddlesden-Popper-type defects during pulsed laser deposition of Sr rich SrTiO thin films by a combined analysis of in-situ atomic force microscopy, low energy electron diffraction and high resolution scanning transmission electron microscopy. At the early growth stage of 1.5 unit cells, the excess Sr results in the formation of SrO on the surface, resulting in a local termination change from TiO to SrO, thereby forming a Sr rich (2 × 2) surface reconstruction.

Disentanglement of growth dynamic and thermodynamic effects in LaAlO3/SrTiO3 heterostructures.

The influence of non-equilibrium and equilibrium processes during growth of LaAlO3/SrTiO3 (LAO/STO) heterostructures is analyzed. We investigate the electronic properties of LAO/STO heterostructures obtained at constant growth conditions after annealing in different oxygen atmospheres within the typical growth window (1 × 10(-4) mbar -1 × 10(-2) mbar). The variation of annealing conditions is found to cause a similar change of electronic properties as observed for samples grown in different oxygen pressure.

The influence of the local oxygen vacancy concentration on the piezoresponse of strontium titanate thin films.

In this study, the influence of the local oxygen vacancy concentration on piezoresponse force microscopy (PFM) measurements was investigated. Ultra-thin single-crystalline SrTiO3 thin films were deposited on niobium doped SrTiO3 substrates and analyzed using a combined PFM and local conductive atomic force microscopy (LC-AFM) measurement setup. After applying different polarization voltages between ±2 V and ±5 V to the thin films, we simultaneously observed an anomalous contrast in the piezoresponse amplitude and phase signal as well as a changed local conductivity in the exact same region.

Surface Termination Conversion during SrTiO3 Thin Film Growth Revealed by X-ray Photoelectron Spectroscopy.

Emerging electrical and magnetic properties of oxide interfaces are often dominated by the termination and stoichiometry of substrates and thin films, which depend critically on the growth conditions. Currently, these quantities have to be measured separately with different sophisticated techniques. This report will demonstrate that the analysis of angle dependent X-ray photoelectron intensity ratios provides a unique tool to determine both termination and stoichiometry simultaneously in a straightforward experiment.