Browse Articles

Plasma exchange therapy for the post COVID-19 condition: a phase II, double-blind, placebo-controlled, randomized trial

Longevity of neonicotinoid seed treatments in cotton seedlings under various deficit irrigation levels

Ultra-low extracorporeal volume microfluidic leukapheresis is safe and effective in a rat model

Abstract Leukapheresis is a potentially life-saving therapy for children with symptomatic hyperleukocytosis. However, the standard centrifugation-based approach exposes pediatric patients to significant complications due to its large extracorporeal volume, high flow rates, and considerable platelet loss. Here, we tested whether performing cell separation with a high-throughput microfluidic technology could alleviate these limitations. In vitro, our microfluidic devices removed ~85% of large leukocytes and ~90% of spiked leukemic blasts from undiluted human whole blood, while minimizing platelet losses. Multiplexed devices connected in parallel allowed for faster, clinically relevant flow rates in vitro with no difference in leukocyte collection efficiency. When connected to Sprague-Dawley rats, the devices removed large leukocytes with ~80% collection efficiency, reducing the leukocyte count in recirculating blood by nearly half after a 3-hour procedure. Evaluation of plasma biomarkers and end-organ histology revealed no adverse effects compared to sham control. Overall, our study suggests that microfluidics-based leukapheresis is safe and effective at selectively removing leukocytes from circulation, with separation performance sufficiently high to ultimately enable low extracorporeal volume leukapheresis in children.

Vibration response analysis of simply supported girder bridges using millimeter-wave radar measurements

Additively-manufactured monocrystalline YBCO superconductor

Abstract Single-crystal microstructures enable high-performance YBa2Cu3O7-x superconductors which are however limited to simple shapes due to their brittleness. Additive manufacturing can fabricate YBa2Cu3O7-x superconductor with complex shapes, albeit with a polycrystalline microstructure. Here, we demonstrate a route to grow single-crystals from 3D-ink-printed, polycrystalline, sintered superconducting YBa2Cu3O7-x (YBCO or Y123) + Y2BaCuO5 (Y211), manufacturing objects with complex architectures displaying both high critical current density (Jc=2.1 × 104 A.cm–2, 77 K) and high critical temperature (Tc= 88-89.5 K). An ink containing precursor powders (Y2O3, BaCO3, and CuO) is 3D-extruded into complex geometries and then reaction-sintered to obtain polycrystalline Y123 + Y211. A seed is then utilized to transform these 3D-printed parts from polycrystal to monocrystal via the melt growth method. The geometric details of 3D-printed parts survive the process without slumping, sagging or collapse, despite the long-term presence of liquid above the peritectic temperature. Origami structures can be created by sheet folding after 3D-printing. This additive approach enables the facile fabrication of superconducting devices with complex shapes and architectures, such as advanced undulator magnets to generate synchrotron radiation and microwave cavities for dark-matter axion search. This work highlights the potential of additive manufacturing for producing monocrystalline cuprate superconductors and opens the door to additive manufacturing of other monocrystalline functional ceramic or semiconductor materials.

Wide-field OCT volumetric segmentation using semi-supervised CNN and transformer integration

Drop-shaped microgrooves guide unidirectional cell migration for enhanced endothelialization

Research on prediction of nanocrystalline alloy hysteresis properties based on long short-term memory network

Activating inert non-defect sites in Bi catalysts using tensile strain engineering for highly active CO2 electroreduction

Evodiamine inhibits programmed cell death ligand 1 expression via the PI3K/AKT signaling pathway to regulate antitumor immunity in melanoma

Deviatoric stress-induced transition of self-trapped exciton emissions

Association between resting heart rate and prognosis in patients with gastric cancer

Author Correction: On the longevity and inherent hermeticity of silicon-ICs: evaluation of bare-die and PDMS-coated ICs after accelerated aging and implantation studies

Proper likelihood functions for parameter estimation in S-shaped models of unperturbed tumor growth

Cortical representations of affective pain shape empathic fear in male mice

Seasonal variations and risk assessment of microplastic contamination in agricultural soil and associated macroinvertebrates in Egypt

Abstract Contamination by microplastics (MPs) has the potential to rank among the world’s most significant environmental issues. Despite the fact that MP contamination is a global problem, little is known about the time variation of MPs in agricultural soil and its faunal communities which represent a key role to risk assessment. This study represents a first field investigation regarding the MP concentrations in agricultural ecosystem in Egypt. Our study investigates the seasonal fluctuations of MPs in soil and its common fauna in a citrus orchard (Citrus sinensis) in Egypt’s Sohag Governorate. Moreover, this work aimed to identify how feeding strategies and body size of the selected fauna affect the no. of MPs ingested. The greatest mean concentration of MPs in soil was observed in summer (664 ± 90.20 items/kg) dry weight. However the lowest was recorded in autumn (354 ± 70.92 items/kg). Aporrectodea caliginosa (earthworms) was more contaminated with MPs (6.84 ± 2.5 item/individual annually) than Anisolabis maritima (earwigs) (2.06 ± 0.86 item/individual annually). When comparing between taxa without considering the size of the organisms, earwigs showed higher MPs concentrations (ranged from 117.93 ± 5.23 to 244.38 ± 4.57 items/gm wet weight) than the earthworms (ranged from 25.62 ± 2.43 to 51.66 ± 4.05 items/gm wet weight). Our results found that blue and red colors were the predominant colors in the soil and the selected fauna. Also, polyester fibers (PES) were the most popular type of microplastics, followed by fractions of polyethylene (PE) and polypropylene (PP). Interestingly, the reduction in the MP particles in the present taxa was observed compared to those in the soil. Pollution load index (PLI) value varied across seasons, with the lowest recorded in autumn due to reduced MPs abundance. The Hazard (H) index indicates a moderate risk (level III) due to high polyester abundance and a low hazard score (4) across all seasons. Our results represent a starting point for further studies on the impact of MPs on soil organisms in various agricultural soils.

Controlling crystallization in covalent organic frameworks to facilitate photocatalytic hydrogen production

Abstract The catalytic performance, depending on the surface nature, is ubiquitous in photocatalysis. However, surface engineering for organic photocatalysts through structural modulation has long been neglected. Here, we propose a zone crystallization strategy for covalent organic frameworks (COFs) that enhances surface ordering through regulator-induced amorphous-to-crystalline transformation. Dynamic simulations show that attaching monofunctional regulators to the surface of spherical amorphous precursor improves surface dynamic reversibility, increasing crystallinity from the inside out. The resulting COF microspheres display surface-enhanced crystallinity and uniform spherical morphology. The visible photocatalytic hydrogen evolution rate reaches 126 mmol g–1 h–1 for the simplest β-ketoenamine-linked COF and 350 mmol gCOF –1 h–1 for SiO2@COF with minimal Pt cocatalysts. Mechanism studies indicate that surface crystalline domains build the surface electrical fields to accumulate photogenerated electrons and diminish electron transfer barriers between the COF and Pt interface. This work bridges the gap between microscopic molecules and macroscopic properties, allowing tailored design of crystalline organic photocatalysts.

MF59-based lipid nanocarriers for paclitaxel delivery: optimization and anticancer evaluation

Abstract Breast cancer is the most common invasive cancer in women worldwide, necessitating innovative therapeutic strategies to enhance treatment efficacy and safety. This study focuses on the development and optimization of novel paclitaxel (PTX)-loaded nanostructured lipid carriers (NLCs) that incorporate components of MF59, an oil-in-water emulsion adjuvant approved for use in influenza vaccines and known for its safety in humans. The formulation of these NLCs is designed to overcome significant challenges in PTX delivery, particularly its poor solubility and the side effects associated with traditional formulations containing Cremophor EL. We prepared two sets of NLC formulations using different liquid-to-solid lipid ratios through hot melt ultrasonication. Characterization of the selected formulations, NLCPre and NLCLec, was conducted using dynamic light scattering (DLS), scanning electron microscopy (SEM), Fourier-transform infrared (FT-IR) spectroscopy, and ultraviolet-visible (UV-Vis) spectroscopy. The mean diameters were 120.6 ± 36.4 nm and 112 ± 41.7 nm, with encapsulation efficiencies (EE) of 85% and 82%, and drug loading (DL) of 4.25% and 4.1%, respectively for NLCPre and NLCLec. In vitro cytotoxicity assays demonstrated that these MF59-based NLCs effectively target MCF-7 (Michigan Cancer Foundation) breast cancer cells while minimizing toxicity to normal HDF (human dermal fibroblasts) cells, thus enhancing the therapeutic index of PTX and offering promising clinical implications for breast cancer treatment.

Endosomal trafficking participates in lipid droplet catabolism to maintain lipid homeostasis

Deep structured learning with vision intelligence for oral carcinoma lesion segmentation and classification using medical imaging

Abstract Oral carcinoma (OC) is a toxic illness among the most general malignant cancers globally, and it has developed a gradually significant public health concern in emerging and low-to-middle-income states. Late diagnosis, high incidence, and inadequate treatment strategies remain substantial challenges. Analysis at an initial phase is significant for good treatment, prediction, and existence. Despite the current growth in the perception of molecular devices, late analysis and methods near precision medicine for OC patients remain a challenge. A machine learning (ML) model was employed to improve early detection in medicine, aiming to reduce cancer-specific mortality and disease progression. Recent advancements in this approach have significantly enhanced the extraction and diagnosis of critical information from medical images. This paper presents a Deep Structured Learning with Vision Intelligence for Oral Carcinoma Lesion Segmentation and Classification (DSLVI-OCLSC) model for medical imaging. Using medical imaging, the DSLVI-OCLSC model aims to enhance OC’s classification and recognition outcomes. To accomplish this, the DSLVI-OCLSC model utilizes wiener filtering (WF) as a pre-processing technique to eliminate the noise. In addition, the ShuffleNetV2 method is used for the group of higher-level deep features from an input image. The convolutional bidirectional long short-term memory network with a multi-head attention mechanism (MA-CNN‐BiLSTM) approach is utilized for oral carcinoma recognition and identification. Moreover, the Unet3 + is employed to segment abnormal regions from the classified images. Finally, the sine cosine algorithm (SCA) approach is utilized to hyperparameter-tune the DL model. A wide range of simulations is implemented to ensure the enhanced performance of the DSLVI-OCLSC method under the OC images dataset. The experimental analysis of the DSLVI-OCLSC method portrayed a superior accuracy value of 98.47% over recent approaches.