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Impact of Enterococcus faecium 129 BIO 3B-R on Helicobacter pylori eradication therapy side effects in adult patients: a randomized, double-blind, placebo-controlled study
Evolving roles of MET as a therapeutic target in NSCLC and beyond
Author Correction: MicroRNA-33b inhibits breast cancer metastasis by targeting HMGA2, SALL4 and Twist1
The microbiota in radiotherapy-induced cancer immunosurveillance
Author Correction: Evaluation of novel and traditional anthropometric indices for predicting metabolic syndrome and its components: a cross-sectional study of the Nepali adult population
Hybrid Active Sites in Coordination Polymers Enable Ampere‐Level Acetylene Semihydrogenation in Membrane Electrode Assembly Systems
Abstract Electrocatalytic acetylene semihydrogenation in membrane electrode assembly systems promises a sustainable pathway for ethylene production, yet faces challenges in catalyst performance and durability. Herein, we developed a Cu coordination polymer with hybrid sites that synergistically integrate open Cu sites and N‐heterocyclic carbenes. These hybrid sites bestow the coordination polymer with acetylene gasophilicity, hydrophobicity toward water, and readily accessible active Cu sites, which energetically facilitate acetylene absorption and vinyl intermediate formation, thereby enabling efficient ethylene production at ampere‐level current densities. In a membrane electrode assembly electrolyzer with pure acetylene, this polymeric catalyst achieved high ethylene Faradaic efficiency of 93.1% at −0.5 A cm −2 and 83.3% at −1.0 A cm −2 , with stable operation for 100 h at −0.5 A cm −2 . Notably, even with a 15% coal‐derived acetylene at a flow rate of 60 standard cubic centimeters per minute, this catalyst system demonstrated 64.4% ethylene energy efficiency and durable performance over 200 h at −0.5 A. This work advances the design of highly stable and active polymeric catalysts for electrocatalytic acetylene semihydrogenation.
Decoding and spatial mapping of acoustic noise in the neonatal intensive care unit
Abstract The neonatal intensive care unit (NICU) is a critical care setting where premature infants face continuous exposure to elevated noise levels, often exceeding international safety guidelines. While the risks of excessive acoustic exposure are well established, strategies for real-time noise monitoring and mitigation in operational NICUs remain underexplored. In this study, we propose an exploratory framework that integrates spatially distributed sound sensors, acoustic heatmap visualization, and machine learning-based classification to analyze and categorize noise events in a high-density NICU setting. The analysis identified persistent high-noise zones near incubators and entryways, with staff movement and alarm-related activities causing significant sound level spikes—particularly during the noon shift. Additionally, a random forest classifier achieved 85.5% accuracy in distinguishing clinical activity patterns based on environmental acoustic data. While not intended for urgent alerting, this framework demonstrates the potential of using ambient sound profiles for non-critical event recognition and environmental monitoring in the NICU.
EHA–EMN Evidence-Based Guidelines for diagnosis, treatment and follow-up of patients with multiple myeloma
Effect of hydrodynamics and mass transfer processes on biomass production of Synechococcus HS-9 cultivated using rectangular airlift photobioreactors with baffles
Efficacy of modified biochar for enhancing maize photosynthesis and yield under various irrigation regimes
A new first-line option for advanced-stage anal squamous cell carcinoma
X-ray near-field multi-slice ptychography for in-situ imaging
Abstract In-situ imaging of chemical reactions can provide valuable insight into nanoparticle growth and structural evolution. Hard X-ray imaging is an excellent tool for this purpose, as it combines high spatial resolution with high penetration depth, allowing for realistic reaction environments. While far-field ptychography is a well-established method at synchrotron radiation sources, its near-field analog has received less attention. In this work we show that near-field multi-slice ptychography is a competitive method for high-resolution in-situ imaging by studying the formation of gold nanocages via galvanic replacement. Our work extends near-field X-ray ptychography to sub-50 nm spatial resolution by using multilayer Laue lenses. These high numerical aperture optics enable to distinguish sample layers that are separated by less than 100 µm by multi-slicing techniques.
Role of novel immunotherapy combinations in the management of advanced-stage hepatocellular carcinoma
Exploring the preferences of college students for horticultural therapy activities based on a new classification framework
Ecological management of the microbiota in patients with cancer
Exceptional Second Harmonic Generation in Ultraviolet Nonlinear Optical Oxyfluoroniobate Crystals via Structural Fingerprint Optimization of Polar Chains
Abstract Partial fluorination of oxides has positioned oxyfluorides as a promising class of nonlinear optical (NLO) materials owing to their balanced optical properties. However, effectively arranging optical chromophores to achieve strong optical nonlinearity remains challenging. In this study, we explore the structural chemistry of 1 [NbOF 4 ] ∞ chain‐based oxyfluoroniobates and establish a molecular geometric framework to quantify key structural fingerprint factors , namely, the ∠(O─Nb─O′) bond angle, χ [F,Nb,Nb′,F′] torsion angle, chain alignment, and distortion of [NbO 2 F 4 ] nodes. Theoretical calculations confirm that these factors critically influence second harmonic generation (SHG) activity. By integrating π‐conjugated biuret (C 2 H 5 N 3 O 2 ) molecules with optimally aligned 1 [NbOF 4 ] ∞ chains, we synthesized (H 3 O)(Biu) 2 (NbOF 4 ) (Biu = biuret), a crystal exhibiting a record‐breaking SHG response, reaching 10.8 times that of KH 2 PO 4 , among transition metal (TM) oxyfluorides. Its moderate birefringence (Δ n = 0.062 @1064 nm) and wide band gap ( E g = 4.50 eV) further support its potential as a high‐performance ultraviolet (UV) NLO material. These results highlight the power of structural fingerprint optimization in fully activating polar chains and offer a new strategy for designing next‐generation UV NLO crystals with enhanced SHG performance.
Critical period of weed-crop competition in irrigated chickpea as a tool for judicious weed control
From ASCO 2025
Comparison of segmentation performance of cnns, vision transformers, and hybrid networks for paranasal sinuses with sinusitis on CT images
Abstract Accurate segmentation of the paranasal sinuses, including the frontal sinus (FS), ethmoid sinus (ES), sphenoid sinus (SS), and maxillary sinus (MS), plays an important role in supporting image-guided surgery (IGS) for sinusitis, facilitating safer intraoperative navigation by identifying anatomical variations and delineating surgical landmarks on CT imaging. To the best of our knowledge, no comparative studies of convolutional neural networks (CNNs), vision transformers (ViTs), and hybrid networks for segmenting each paranasal sinus in patients with sinusitis have been conducted. Therefore, the objective of this study was to compare the segmentation performance of CNNs, ViTs, and hybrid networks for individual paranasal sinuses with varying degrees of anatomical complexity and morphological and textural variations caused by sinusitis on CT images. The performance of CNNs, ViTs, and hybrid networks was compared using Jaccard Index (JI), Dice similarity coefficient (DSC), precision (PR), recall (RC), and 95% Hausdorff Distance (HD95) for segmentation accuracy metrics and the number of parameters (Params) and inference time (IT) for computational efficiency. The Swin UNETR hybrid network outperformed the other networks, achieving the highest segmentation scores, with a JI of 0.719, a DSC of 0.830, a PR of 0.935, and a RC of 0.758, and the lowest HD95 value of 10.529 with the smallest number of the model architectural parameter, with 15.705 M Params. Also, CoTr, another hybrid network, demonstrated superior segmentation performance compared to CNNs and ViTs, and achieved the fastest inference time with 0.149 IT. Compared with CNNs and ViTs, hybrid networks significantly reduced false positives and enabled more precise boundary delineation, effectively capturing anatomical relationships among the sinuses and surrounding structures. This resulted in the lowest segmentation errors near critical surgical landmarks. In conclusion, hybrid networks may provide a more balanced trade-off between segmentation accuracy and computational efficiency, with potential applicability in clinical decision support systems for sinusitis.