Effect of a three-dimensional nanotube array substrate on photocatalytic conversion performance of CO gas to methanol by amine-loaded CuO/ZnO catalysts.

The photocatalytic conversion of CO gas into energy-dense hydrocarbons holds the potential to address both environmental and energy problems. Catalysts consisting of CuO clusters/nanoparticles and ZnO nanorods on a metallic nanotube array (MeNTA) silicon substrate were utilized for CO reduction. The surface of the catalysts was modified with 3-amino-propyltriethoxysilane (APTES), the amine terminal of which can selectively bind CO gas.

Doxorubicin-loaded Polymeric Biotin-PEG-SeSe-PBLA Micelles with surface Binding of Biotin-Mediated Cancer Cell Targeting and Redox-Responsive Drug release for enhanced anticancer efficacy.

Biotin receptors are overexpressed in various cancer cell types, essential in tumor development, metabolism, and metastasis. Chemotherapeutic agents may be more effective and have fewer adverse effects if they specifically target the biotin receptors on cancer cells. Polymeric micelles (PMs) with nanoscale size via the EPR effect to accumulate near tumor tissue.

Polyelectrolyte-coated liposomes microfluidically assembled in one-step for enhancing cell endocytosis and in-vivo immune responses.

To enhance the cellular uptake of liposomes, we prepared conventional liposomes with targeting molecules and surface-charged liposomes and evaluated their potential as nano-carriers and vaccine adjuvants by comparing their endocytosis efficiencies using immune cells. Surface-charged liposomes were synthesized via a one-step microfluidic method, which provided a novel, simple, fast, and highly reproducible method for preparing liposomes. Flow cytometry revealed that cationic polyelectrolyte-coated liposomes exhibited higher endocytosis efficiencies (of up to a factor of 100) in A774A.

Three-dimensional Au-MnO nanostructure as an agent of synergistic cancer therapy: chemo-/photodynamic and photothermal approaches.

The design of multimodal cancer therapy was focused on reaching an efficient process and minimizing harmful effects on patients. In the present study, the Au-MnO nanostructures have been successfully constructed and produced as novel multipurpose photosensitive agents simultaneously for photodynamic therapy (PDT), photothermal therapy (PTT), and chemodynamic therapy (CDT). The prepared AuNPs were conjugated with MnO NPs by its participation in the thermal decomposition process of KMnO confirmed by X-ray diffraction (XRD), transmission electron microscopy (TEM), and Fourier transform infrared (FTIR) spectroscopy (FT-IR).

Potential usage of boron modified carbon nanodots as a marker candidate for coronavirus disease (COVID-19) antibody detection.

The global outbreak of COVID-19 in December 2019 has highlighted rapid and accurate diagnostic tools for effective intervention. While the RT-PCR test offers 86 % sensitivity, uncertainties often require supplementary screening. This research investigates how carbon dots (CDs) can be utilized as markers for COVID-19 antibodies, taking advantage of their biocompatibility and low toxicity.

B and N Codoped Cellulose-Supported Ag-/Bi-Doped Mo(S,O) Trimetallic Sulfo-Oxide Catalyst for Photocatalytic H Evolution Reaction and 4-Nitrophenol Reduction.

Cellulose plays a significant role in designing efficient and stable cellulose-based metallic catalysts, owing to its surface functionalities. Its hydroxyl groups are used as anchor sites for the nucleation and growth of metallic nanoparticles and, as a result, improve the stability and catalytic activity. Meanwhile, cellulose is also amenable to surface modifications to be more suitable for incorporating and stabilizing metallic nanoparticles.

Enhancing Ionic Selectivity and Osmotic Energy by Using an Ultrathin Zr-MOF-Based Heterogeneous Membrane with Trilayered Continuous Porous Structure.

Designing a nanofluidic membrane with high selectivity and fast ion transport property is the key towards high-performance osmotic energy conversion. However, most of reported membranes can produce power density less than commercial benchmark (5 W/m), due to the imbalance between ion selectivity and permeability. Here, we report a novel nanoarchitectured design of a heterogeneous membrane with an ultrathin and dense zirconium-based UiO-66-NH metal-organic framework (MOF) layer and a highly aligned and interconnected branched alumina nanochannel membrane.

Improving medical students recognizing surgery of glioblastoma removal/decompressive craniectomy via physical lifelike brain simulator training.

Background: This study aims to investigate the benefits of employing a Physical Lifelike Brain (PLB) simulator for training medical students in performing craniotomy for glioblastoma removal and decompressive craniectomy.

Methods: This prospective study included 30 medical clerks (fifth and sixth years in medical school) at a medical university. Before participating in the innovative lesson, all students had completed a standard gross anatomy course as part of their curriculum.

Nanomaterials in the treatment and diagnosis of rheumatoid arthritis: Advanced approaches.

Rheumatoid arthritis (RA), a chronic inflammatory condition that affects persons between the ages of 20 and 40, causes synovium inflammation, cartilage loss, and joint discomfort as some of its symptoms. Diagnostic techniques for RA have traditionally been split into two main categories: imaging and serological tests. However, significant issues are associated with both of these methods.

Deep learning to assess microsatellite instability directly from histopathological whole slide images in endometrial cancer.

Molecular classification, particularly microsatellite instability-high (MSI-H), has gained attention for immunotherapy in endometrial cancer (EC). MSI-H is associated with DNA mismatch repair defects and is a crucial treatment predictor. The NCCN guidelines recommend pembrolizumab and nivolumab for advanced or recurrent MSI-H/mismatch repair deficient (dMMR) EC.

A hierarchical model of accelerating factors to promote urban renewal and reconstruction of unsafe and old buildings.

The issue of urban renewal is complex and multifaceted. In this study, six specialists in the construction industry were invited to conduct audio interviews, which were compiled into verbatim text. The key phrases were extracted by Grounded theory, and three levels of coding were retrieved.

A Study on the Dilational Modulus Measurement of Polyacrylic Acid Films at Air-Water Interface by Pendant Bubble Tensiometry.

The dilational modulus (E) of polymer films has been commonly measured using the oscillating ring/bubble/drop methods with an external force, and often without specifying the state of the adsorbed film. This study explores an approach where E was determined from the relaxations of surface tension (ST) and surface area (SA) of natural perturbations, in which ST and SA were monitored using a pendant bubble tensiometer. The E of the adsorbed film of PAA (polyacrylic acid) was evaluated for aqueous solutions at C = 5 × 10 g/cm, [MW = 5, 25, and 250 (kDa)].

Leveraging a rationally designed veliparib-based anilide eliciting anti-leukemic effects for the design of pH-responsive polymer nanoformulation.

Careful recruitment of the components of the HDAC inhibitory template culminated in veliparib-based anilide 8 that elicited remarkable cell growth inhibitory effects against HL-60 cell lines mediated via dual modulation of PARP [(IC (PARP1) = 0.02 nM) and IC (PARP2) = 1 nM)] and HDACs (IC value = 0.05, 0.

Mass Spectrometry-Based Analyses of Carbon Nanodots: Structural Elucidation.

Carbon nanodots (CNDs) are nanomaterials with ubiquitous applications in health for diagnosis and treatments. The key to enhancing the applications of carbon nanodots in various fields lies on how deep its structure is understood. Here, we review the mass spectroscopy (MS) techniques employed for carbon nanodot analysis.

Protector-free, non-plasmonic silver quantum clusters by femtosecond pulse laser irradiation: binding on nanocellulose filaments for improved catalytic activity and cycling performance.

This study introduces a new, facile method to synthesize silver clusters from aqueous silver ion solution by using high intensity femtosecond pulse laser irradiation. The particles obtained in the absence of reducing or capping agents are 1-17 nm in size and presented quantum properties, as characterized by fluorescence, but did not exhibit plasmon signals, which is not a common characteristic of conventional silver nanoparticles. In a further development, small silver quantum clusters (∼1 nm) were bound to wet-spun filaments of cellulose nanofibrils by pulsed laser irradiation.

NT-proBNP point-of-care testing for predicting mortality in end-stage renal disease: A survival analysis.

This study examines the predictive value of elevated N-terminal-pro brain natriuretic peptide (NT-pro BNP) levels for mortality among patients with end-stage renal disease (ESRD). Data from 768 ESRD patients, excluding those with cancer or lost follow-up, were analyzed using Kaplan-Meier curves and Cox proportional hazards models over three years. Results indicated that patients with very high NT-pro BNP levels had shorter average survival times and a significantly higher risk of mortality (hazard ratio 1.

Two-dimensional metal-organic framework for post-synthetic immobilization of graphene quantum dots for photoluminescent sensing.

Immobilization of graphene quantum dots (GQDs) on a solid support is crucial to prevent GQDs from aggregation in the form of solid powder and facilitate the separation and recycling of GQDs after use. Herein, spatially dispersed GQDs are post-synthetically coordinated within a two-dimensional (2D) and water-stable zirconium-based metal-organic framework (MOF). Unlike pristine GQDs, the obtained GQDs immobilized on 2D MOF sheets show photoluminescence in both suspension and dry powder.

Comparative Study of the Impurity Effect on SnAgCu and SnZn Solder Joints with Electrodeposited Cu.

Sn-3Ag-0.5Cu (SAC305)- and Sn-9Zn-based alloys (Sn-Zn-X, X = Al, In) are lead-free solders used in the fabrication of solder joints with Cu metallization. Electroplating is a facile technology used to fabricate Cu metallization.

Large-volume RT-LAMP enables extraction-free amplification of HIV RNA from fingerstick plasma.

Background: Point-of-care (POC) nucleic acid amplification tests (NAAT) can significantly expand testing coverage, which is critical for infectious disease diagnostics and monitoring. The development of various isothermal amplification techniques greatly simplifies NAATs, but the cumbersome nucleic acid extraction step remains a bottleneck for the POC. Alternatively, extraction-free amplification, where crude samples are directly added into the assay, substantially simplifies the workflow.

Recent advances in synergistic use of GQD-based hydrogels for bioimaging and drug delivery in cancer treatment.

Graphene quantum dot (GQD) integration into hydrogel matrices has become a viable approach for improving drug delivery and bioimaging in cancer treatment in recent years. Due to their distinct physicochemical characteristics, graphene quantum dots (GQDs) have attracted interest as adaptable nanomaterials for use in biomedicine. When incorporated into hydrogel frameworks, these nanomaterials exhibit enhanced stability, biocompatibility, and responsiveness to external stimuli.

Comparative assessment of established and deep learning-based segmentation methods for hippocampal volume estimation in brain magnetic resonance imaging analysis.

In this study, our objective was to assess the performance of two deep learning-based hippocampal segmentation methods, SynthSeg and TigerBx, which are readily available to the public. We contrasted their performance with that of two established techniques, FreeSurfer-Aseg and FSL-FIRST, using three-dimensional T1-weighted MRI scans (n = 1447) procured from public databases. Our evaluation focused on the accuracy and reproducibility of these tools in estimating hippocampal volume.

Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains.

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these limitations, we propose a pan-genome-based machine learning approach to advance our understanding of AMR gene repertoires and uncover possible feature sets for precise AMR classification.