High-Pressure Synthesis of Metastable Superhydride PdH by Using Amorphous Pd as a Starting Material.

Pressure has been considered as a versatile and promising means in the discovery of metal superhydrides. However, although a series of metastable metal hydrides with excellent superconducting properties have been predicted through theoretical calculations, it is still challenging to obtain metal hydrides with metastable phases via a high-pressure synthetic route. Herein, we have successfully fabricated a metastable PdH superhydride using amorphous Pd nanoparticles (NPs) as a starting material at ∼32.

Controlling nephron precursor differentiation to generate proximal-biased kidney organoids with emerging maturity.

The kidney maintains fluid homeostasis by reabsorbing essential compounds and excreting waste. Proximal tubule cells, crucial for reabsorbing sugars, ions, and amino acids, are highly susceptible to injury, often leading to pathologies necessitating dialysis or transplants. Human pluripotent stem cell-derived kidney organoids offer a platform to model renal development, function, and disease, but proximal nephron differentiation and maturation in these structures is incomplete.

Temperature effects on single cavitation bubble dynamics under the free field condition: Experimental and theoretical investigations on water.

This paper examines how water temperature affects the dynamics of a single cavitation bubble in free field conditions. Both experimental and theoretical approaches are employed to explore the bubble dynamics in water under different temperatures. A series of single bubble experiments are conducted in water using the capacitive discharge method, with water temperature ranging from room temperature to near boiling point under atmospheric pressure.

Development and Application in Stroke of an Aldehyde nanoparticle-based Amplified Luminescent Proximity Homogeneous Assay for Rapid Quantitative Measurement of Serum Copeptin.

The timing of onsets is a critical factor in preventing disability in stroking patients. Developing a faster and more accurate diagnostic method is essential. Copeptin, as a stable surrogate for arginine vasopressin, has emerged as a novel and reliable serum biomarker for stroke.

Expansion of human pluripotent stem cell-induced nephron progenitor cells (iNPCs) and the generation of nephron organoids from iNPCs.

Nephron progenitor cells (NPCs) have a central role in kidney organogenesis: they self-renew and differentiate into nephrons, the functional units of the kidney. Human pluripotent stem cells (hPSCs) can transiently produce induced nephron progenitor-like cells (iNPCs), which then differentiate into nephron organoids. Here, we describe a protocol to purify and expand the hPSC-derived iNPCs in a regular monolayer culture format with an optimized iNPC culture medium.

Enabling generalized zero-shot learning towards unseen domains by intrinsic learning from redundant LLM semantics.

Generalized zero-shot learning (GZSL) focuses on recognizing seen and unseen classes against domain shift problem where data of unseen classes may be misclassified as seen classes. However, existing GZSL is still limited to seen domains. In the current work, we study cross-domain GZSL (CDGZSL) which addresses GZSL towards unseen domains.

PLA2R1 and HLA-DQA1 SNP in patients with primary membranous nephropathy.

Background: Primary membranous nephropathy is a widely recognized autoimmune disease associated with podocyte antigens; the most important autoantigen is PLA2R1. PLA2R1 and HLA-DQA1 play important roles in the production of pathogenic antibodies. The purpose of this study was to observe the relationship between gene polymorphisms and primary membranous nephropathy and explore the clinical functional clues of PLA2R1 and HLA-DQA1 genes affecting treatment responsiveness.

Establishment of a YKL-40 time-resolved Immunoassay and Application in Diabetic Kidney Disease.

To develop a highly sensitive, wide-linear-range time-resolved fluorescence immunoassay (TRFIA) to detect serum YKL-40 and to measure its concentrations in patients with diabetic kidney disease (DKD). A double-antibody sandwich method was employed to establish the YKL-40 TRFIA, which utilizes two antibodies targeting distinct epitopes on the YKL-40 antigen (a coating antibody and a labeled antibody). The assay's linearity, sensitivity, accuracy, specificity, and recovery rate were evaluated.

Mechanistic Perspectives on Radiation-Induced Skin Injury and the Protective Effects of Berberine.

Background: Radiation-induced skin injury (RISI) is a common complication of radiotherapy, affecting up to 95% of cancer patients. It manifests as acute erythema and ulceration or chronic fibrosis and telangiectasia, severely compromising patients' quality of life. The pathogenesis of RISI involves oxidative stress, inflammation, DNA damage, and cellular senescence.

Anti-PLA2R IgG4-to-IgG Ratio Helps to Predict Remission of PLA2R-Associated Primary Membranous Nephropathy.

Background And Aims: PLA2R-associated primary membranous nephropathy (PMN) was classified as IgG4-associated autoimmune disease in which anti-PLA2R antibody is predominantly IgG4 subclass. Our objective was to explore the capability of anti-PLA2R IgG4-to-IgG ratio for predicting remission in PLA2R-associated PMN patients.

Methods: 143 patients with anti-PLA2R IgG ≥14 RU/ml were biopsy-confirmed as PLA2R-associated PMN.

Ce Single Atom-Engineered Amorphous/Crystalline Nanosheets for Enhanced Alkaline Water Electrolysis.

Designing nanocatalysts with fast water dissociation kinetics is key to achieving the industrial current density of the cathodic hydrogen evolution reaction (HER) for green hydrogen production via water electrolysis, which remains a grand challenge. Here, leverage single-atom engineering,a Ce single-atom-doped amorphous RuO nanosheet featuring abundant amorphous/crystalline nanojunctions, namely, ac-CeRuO is successfully developed. When employed as a catalyst for alkaline HER, the ac-CeRuO catalyst displays an overpotential of only 8.

Incremental Learning-Enabled Fault Diagnosis of Dynamic Systems: A Comprehensive Review.

Effective fault diagnosis is crucial for maintaining the reliability and safety of industrial systems. Incremental learning, which enables models to continuously update and adapt to new data or emerging fault classes without complete retraining, has recently gained attention as a promising solution for addressing nonstationary data streams in fault diagnosis applications. Nevertheless, most existing review articles on fault diagnosis adopt a broad perspective, primarily discussing general techniques such as deep learning and transfer learning, without providing a dedicated focus on incremental learning strategies.

Bioinspired phosphorylated cellulose nanocrystals-based multi-crosslinked binder for enhanced stability and sustainability in silicon anodes.

Silicon (Si) is a promising anode for high-energy-density batteries, but its ~300 % volume expansion causes particle fracture and electrode instability. Effective binders are essential for maintaining electrode integrity. Inspired by the adhesion mechanism of natural ivy, we developed a small-molecule-enhanced polymer binder derived from phosphorylated cellulose nanocrystals (PCNCs) and acrylic acid rosin to enhance the electrochemical and mechanical performance of Si anodes.

Multimodal prediction based on ultrasound for response to neoadjuvant chemotherapy in triple negative breast cancer.

Pathological complete response (pCR) can guide surgical strategy and postoperative treatments in triple-negative breast cancer (TNBC). In this study, we developed a Breast Cancer Response Prediction (BCRP) model to predict the pCR in patients with TNBC. The BCRP model integrated multi-dimensional longitudinal quantitative imaging features, clinical factors and features from the Breast Imaging Data and Reporting System (BI-RADS).

Dual-port laparoscopic myomectomy: a balanced yet potentially more optimal surgical approach.

Objective: This study aimed to compare the perioperative outcomes of single-incision laparoscopic surgery (SILS) and dual-port laparoscopic myomectomy in patients with solitary uterine fibroids.

Methods: This retrospective observational study included 162 patients who underwent laparoscopic myomectomy for solitary fibroids from January 2022 to December 2023 at a single tertiary center. Patients were divided into a SILS group ( = 77) and a dual-port group ( = 85).

EKG-AC: A New Paradigm for Process Industrial Optimization Based on Offline Reinforcement Learning With Expert Knowledge Guidance.

Operation optimization plays a crucial role in process control, directly influencing product quality and profitability. Reinforcement learning (RL), with its capabilities in autonomous learning and dynamic adaptability, has become a promising solution in this domain. However, its real-world application is constrained by the high costs and risks associated with its interactions with environments.

Early Tirofiban Infusion after Intravenous Thrombolysis for Stroke.

Background: Intravenous thrombolysis remains a standard treatment for acute ischemic stroke within 4.5 hours after onset. Vascular reocclusion may occur after intravenous thrombolysis and may be preventable with an antiplatelet agent within the first 24 hours after thrombolysis.

Analysis of the learning curve for transvaginal natural orifice transluminal endoscopic surgery in ovarian cystectomy.

Objective: This study aimed to evaluate the learning curve for transvaginal natural orifice transluminal endoscopic surgery (vNOTES) in ovarian cystectomy and to identify perioperative factors influencing operative time.

Methods: This prospective observational study included 39 patients who underwent vNOTES ovarian cystectomy at Chengdu Women's and Children's Central Hospital between June 2022 and June 2024. Patients were grouped into two surgical phases based on the operating team's self-assessed proficiency.

Optimizing monitoring strategies for urban drainage systems via bilayer iterative clustering.

Online monitoring is increasingly essential for the effective management and operation of urban sewer systems, yet resource limitations necessitate careful planning of sensor deployment. This study aims to address the impact of time lags on monitoring point selection in urban drainage systems using unsupervised machine learning techniques. A novel method is introduced to determine the optimal number and placement of sensors in manholes, using cluster analysis informed by simulated time-series data.

Development and application of an ultrasensitive immunoassay for antiphospholipase A2 receptor antibodies in the differential diagnosis of membranous nephropathy.

: to develop an ultrasensitive time-resolved fluoroimmunoassay (TRFIA) for anti-PLA2R IgG to improve serological diagnosis of primary membranous nephropathy (PMN). The three-step indirect TRFIA uses signal cascade amplification to enhance sensitivity while maintaining specificity, aiming to increase positive detection rates in PMN patients and evaluate analytical performance and clinical utility in 65 PMN patients (including 34 patients with negative Elisa test values), disease controls, and healthy controls. : the ultrasensitive PLA2R-IgG-TRFIA had a sensitivity of 0.

Regulates Apoptotic Signaling to Mitigate Renal Ischemia-Reperfusion Injury and Enhance Chemotherapy Sensitivity.

Chemotherapy sensitivity in renal carcinoma may be influenced by renal ischemia-reperfusion injury (RIRI). This study elucidates the underlying mechanism by investigating the regulatory role of . The public dataset was downloaded, and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were used to analyze functional and pathway enrichment of genes in the most significant modules.

MultiCubeNet: Multitask deep learning for molecular subtyping and prognostic prediction in gliomas.

Background: Gliomas, the most prevalent type of primary brain tumors, require precise molecular characterization for effective diagnosis and treatment. Despite advancements in radiomics, simultaneous prediction of key molecular markers, such as isocitrate dehydrogenase () mutation, co-deletion, and telomerase reverse transcriptase () promoter mutation, along with prognosis, remains challenging. We aimed to develop and validate a deep learning (DL) model capable of simultaneously predicting key genetic molecular markers and prognosis in gliomas.

Latent class growth analysis of dynamic PaCo patterns and clinical outcomes in acute brain injury.

To analyze dynamic patterns of arterial carbon dioxide partial pressure (PaCO₂) using latent class growth analysis in acute brain injury patients and investigate their associations with 28-day ICU mortality and 60-day in-hospital mortality. This retrospective study utilized the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. We applied latent class growth analysis to analyze PaCO₂ dynamic patterns during the first 72 h after ICU admission in adult patients with acute brain injury.

Berberine in the treatment of radiation-induced skin injury: insights from proteomics and network pharmacology.

Background: Radiation-induced skin injury (RISI) is a notable complication of cancer radiotherapy, impacting patients' quality of life. Existing interventions mainly address symptoms, with limited success in targeting the fundamental mechanisms. Berberine (BBR), a bioactive compound recognized for its anti-inflammatory, antioxidant, and anti-fibrotic characteristics, presents a compelling option for treating RISI.