Electrochemical Sensors for Rapid Cardiovascular Disease Diagnostics.

Cardiovascular diseases (CVDs) remain a leading cause of death, particularly in developing countries, where their incidence continues to rise. Traditional CVD diagnostic methods are often time-consuming and inconvenient, necessitating more efficient alternatives. Rapid and accurate measurement of cardiac biomarkers released into body fluids is critical for early detection, timely intervention, and improved patient outcomes.

Prolonging All-Optical Molecular Electron Spin Coherence in the Tissue Transparency Window.

Coherent electron spin states within paramagnetic molecules hold significant potential for microscopic quantum sensing. However, all-optical coherence measurements amenable to high spatial and temporal resolution under ambient conditions remain a significant challenge. Here we conduct room-temperature, picosecond time-resolved Faraday ellipticity/rotation (TRFE/R) measurements of the electron spin decoherence time in [IrBr].

Measuring Street Built Environments for Children's Use: A Systematic Review of Measurement Tools.

Street-level environments play a vital role in children's development by promoting their physical activity, cognitive growth, and overall development. This study systematically reviews the measurement tools available to assess street environments according to children's needs. This systematic review was conducted according to the PRISMA-COSMIN guidelines.

Unveiling molecular signatures for precision drug design: machine learning insights from trypanothione reductase, PKC-θ, and CB1.

Traditional drug discovery methods like high-throughput screening and molecular docking are slow and costly. This study introduces a machine learning framework to predict bioactivity (pIC₅₀) and identify key molecular properties and structural features for targeting Trypanothione reductase (TR), Protein kinase C theta (PKC-θ), and Cannabinoid receptor 1 (CB1) using data from the ChEMBL database. Molecular fingerprints, generated via PaDEL-Descriptor and RDKit, encoded structural features as binary vectors.

Genesis, Health Benefits, and Future Perspectives of Probiotics: Exploring Endogenous and Exogenous Classes, Innovations, and Research Gaps.

Probiotics are live beneficial microorganisms that confer health benefits to the host when administered in adequate amounts, have gained considerable scientific and commercial interest for their ability to support gut health, strengthen immunity, and reduce disease risk. This review traces the genesis of probiotic science from its origins in traditional fermented foods to contemporary clinical applications, offering a conceptual understanding of its evolution. A clear distinction is drawn between endogenous probiotics, naturally resident in the human microbiome, and exogenous probiotics, introduced via dietary supplements and functional foods.

Tariff Conflicts and Entrenched Interests: The Deepening Deadlock of US Healthcare Reform.

The US healthcare system is characterized by a persistent deadlock, where high costs, low efficiency, and inequity resist fundamental reform. This stalemate is rooted in deep ideological divides, political polarization, a fragmented fiscal structure, and the power of entrenched interest groups. This article analyzes how recent trade protectionist policies, specifically tariffs on pharmaceuticals and their inputs, intersect with this domestic gridlock.

Surface Properties of Colloidal Quantum-Confined One-Dimensional Lepidocrocite Titanates: Insights into their Ion-Induced Gelation.

The surfaces of 1D layered lepidocrocite-structured titanates (1DLs) are negatively charged due to an oxygen-to-titanium atomic ratio >2. This, and their layered structure, allow for facile ion exchange and high colloidal stability, demonstrated by ζ-potentials of ≈ -85 mV at their unadjusted pH of ≈10.4.

Boron-Rich Metallaboranes from κ-N,E-Chelated Ru Complexes (E = S or Se): A Direct Route to Ruthenaboranes.

We have established a new route for boron-rich ruthenaborane clusters utilizing [BH·THF] and a ruthenium precursor featuring chelating ligands. Salt elimination reactions between [K(CHNE)], (E = S; Se) and [RuCl(PPh)], afforded -[Ru(κ--CHNE)(PPh)], -- (-: E = S and -: E = Se). Following the ligand exchange reaction with the 1,2-bis (diphenylphosphino)ethane (dppe) ligand yielded -[Ru(κ--CHNE)(dppe)] (-: E = S; -: E = Se).

A Monte Carlo Method for Estimating Secondary Photon Yields from Beta-emitting Radionuclides Concentrated in Environmental Soil.

External exposure due to secondary photons (predominantly bremsstrahlung) generated from electron source emissions in environmental soil are of concern due to their ability to deposit significant amounts of ionizing energy to organs and tissues within the body. The "condensed history method" employed in many modern Monte Carlo (MC) codes may be used to simulate secondary photon yields (given as photons per beta decay) arising from electron source emissions with relatively few assumptions regarding the secondary photon spatial, energy, and angular dependencies. These yields may in turn be used to derive protection quantities such as secondary photon effective dose rate (DR) and risk coefficients for a variety of idealized external exposure scenarios.

Eco-efficient C-H alkynylation of indoles mechanochemical ruthenium catalysis.

A regioselective C2-alkynylation of indoles ruthenium(II)-catalyzed C-H activation using bromoalkynes is demonstrated under both solution-phase and mechanochemical conditions. The solvent-minimized mechanochemical method delivers comparable yields with reduced reaction time and improved green metrics. Broad substrate scope, gram-scale applicability, and post-functionalization showcase the synthetic utility of this approach.

Predicting complex time series with deep echo state networks.

Although many real-world time series are complex, developing methods that can learn from their behavior effectively enough to enable reliable forecasting remains challenging. Recently, several machine-learning approaches have shown promise in addressing this problem. In particular, the echo state network (ESN) architecture, a type of recurrent neural network where neurons are randomly connected and only the read-out layer is trained, has been proposed as suitable for many-step-ahead forecasting tasks.

Dissecting antimicrobial logic: species-specific strategies for intracellular pathogen defense.

Control of intracellular pathogens is a critical element of host defense. Defining the molecular mechanisms by which the host restricts or eliminates these pathogens may inform the development of novel immunotherapeutics and antimicrobial strategies, particularly in the face of rising antibiotic resistance. In parallel, understanding how pathogens subvert these immune responses may yield new approaches to disrupt virulence rather than viability.

Multiplexed Fluorescent Microarrays on MIL-101(Cr) Thin Films as Luminescent Probes for pH and Disease-Associated Molecules.

Recently, metal-organic frameworks (MOFs) have shown high potential in the field of sensing. However, fluorescent-based detection with MOFs in solution needs complex pre-treatments and has stability issues, complicating measurements and handling for sensing applications. Here, an easy-to-handle and low-cost strategy is introduced to convert MOF-based sensing from solution to surface using scanning probe lithography.

Comparison of 6-hour versus 12-hour cervical ripening balloon protocols in patients with prior cesarean delivery: A retrospective cohort study.

Objective: To compare the mode of delivery and other maternal and neonatal outcomes in patients with one prior cesarean delivery undergoing labor induction with a cervical ripening balloon (CRB) for 6 h versus 12 h.

Methods: This retrospective study compared two protocols for mechanical cervical ripening: CRB placement for 12 h (12-h group, implemented from 2014 to 2017) versus 6 h (6-h group, implemented from 2020 to 2021). The study included patients with one prior low-segment cesarean delivery.

A target responsive benzimidazole-based self-assembled micellar system embedded smart hydrogel: an integrated approach for quantification and removal of phenylbutazone.

The unregulated use and improper disposal of active pharmaceutical ingredients (APIs), particularly phenylbutazone (PBZ), are contaminating water resources and posing serious risks to the food chain. PBZ is a nonsteroidal anti-inflammatory drug (NSAID) commonly used for treating pain and fever in animals, and its persistence in the environment due to inadequate waste management has become a cause of concern. To address this, we report the fabrication of benzimidazole-based self-assembled nanomicelles (R2 NMs) for selective detection and removal of PBZ.

A New Family of Ternary Intermetallic Compounds with Dualistic Atomic Ordering - The ZIP Phases.

A new family of nanostructured ternary intermetallic compounds - named the ZIP phases - is introduced in this work. The ZIP phases exhibit dualistic atomic ordering, i.e.

Grayscale Digital Light Processing 3D Printed Microlens for Scale-Down Self-Focusing Printing.

In modern micro/nano fabrication, 3D printing technology drives industry transformation. However, existing technologies face bottlenecks in improving process efficiency and precision, while also struggling to achieve accurate fabrication of composite 3D microstructures. This study proposes a microlens self-focusing printing technique that integrates digital light processing (DLP) 3D printing with an optical microscope platform.

Protein-Derived Chelating Peptides: Preparation, Conformational Relationships, and Biological Activities.

Metal ions play a vital role in the health of the modern human body, but deficiencies in mineral elements have created health risks worldwide. However, mineral supplements currently available on the market are very limited due to poor solubility, low bioavailability, and the possibility of adverse effects on the gastrointestinal tract. In contrast, protein-derived metal-chelating peptides have received a lot of attention because of their stability, safety, and very high bioavailability.

Unlocking Superior Energy Storage: Multiscale Optimized BNT-Based Capacitors for Low-Field Applications.

Achieving superior energy storage performance in dielectric materials under low electric fields remains a challenge. Most recent advancements require high fields that limit device applicability. Developing dielectric capacitors with high recoverable energy density (W), efficiency (η), and energy-storage coefficient (W/E) at low/moderate fields is critical for safer, compact, and durable electronics.

Electrochemical Dehydration Reaction.

Electrochemical dehydration reaction is a fascinating and underexplored field of research, which has started to attract significant attention in recent years. Dehydration reactions are characterized by the formal removal of water in the course of the transformation, and they are among the most fundamental types of reactions found throughout chemistry. Examples are esterification reactions, amidation reactions, and the synthesis of carbon-heteroatom multiple bonds.

Neuroimaging Data Informed Mood and Psychosis Diagnosis Using an Ensemble Deep Multimodal Framework.

Investigating neuroimaging data to identify brain-based markers of mental illnesses has gained significant attention. Nevertheless, these endeavors encounter challenges arising from a reliance on symptoms and self-report assessments in making an initial diagnosis. The absence of biological data to delineate nosological categories hinders the provision of additional neurobiological insights into these disorders.

Three-dimensional-printed strontium-incorporated β-TCP bioceramic triply periodic minimal surface scaffolds with enhanced angiogenic and osteogenic properties.

Reconstructing bone defects remains a significant challenge in clinical practice, driving the urgent need for advanced artificial grafts that simultaneously promote vascularization and osteogenesis. Addressing the critical trade-off between achieving high porosity/strength and effective bioactivity at safe ion doses, we incorporated strontium (Sr) into β-tricalcium phosphate (β-TCP) scaffolds with a triply periodic minimal surface (TPMS) structure using digital light processing (DLP)-based three-dimensional (3D) printing. Systematically screening Sr concentrations (0-10 mol%), we identified 10 mol% as optimal, leveraging the synergy between the biomimetic TPMS architecture, providing exceptional mechanical strength (up to 1.