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Noninvasive assessment of oxidative stress in pelvic organ prolapse: a feasibility study
Unravelling the Dynamic Modulation of Copper (Oxy)Hydroxides for Electrocatalytic Organic Nucleophile Oxidation
Abstract Electrocatalytic nucleophile oxidation (NOR) is pivotal for renewable energy and sustainable synthesis, yet the ambiguous nature of active sites hinders catalyst design. Herein, we thoroughly investigate the dynamic activation of CuO under NOR using surface voltammetry, in situ Raman, and impedance spectroscopies. Direct voltametric and spectroscopic evidences reveal that the adsorbed hydroxyl‐bridged Cu δ+ ‐oxy species (μ 2 ‐OH‐Cu δ+ ‐oxy, 2 ≤ δ ≤ 3) are the catalytically active centers for the reaction. Experimental–theoretical synergy reveals that the dynamic μ 2 ‐OH‐Cu δ+ ‐oxy interacts with stabilized OH* to form a dual‐site, dictating the structure–activity relationship. This mechanism enables near‐quantitative conversion of 5‐hydroxymethylfurfural to 2,5‐furandicarboxylic acid (97.1% yield/Faradaic efficiency) with > 100 h stability. The mechanistic insights we obtained show broad applicability across various nucleophilic substrates, where substituent effects, carbon chain flexibility, and α‐hydrogen mobility govern reactivity variations. This study establishes dynamic active center engineering as a universal strategy for designing transition‐metal (oxy)hydroxide catalysts, bridging electrocatalysis and precision organic synthesis.
Metabolic factors are associated with a higher risk of conventional adenoma in males during surveillance colonoscopy: findings from a South Australian cohort
Impact of dexmedetomidine administration on mortality in patients with cardiac arrest: a propensity score matching analysis of the MIMIC-IV database
Assessment of a VoIP steganalysis method based on statistical analysis and deep neural network
The Parkinson's Disease Drug Tolcapone and Analogues are Potent Glycomimetic Lectin Inhibitors of <i>Pseudomonas aeruginosa</i> LecA
Abstract The notorious pathogen Pseudomonas aeruginosa relies on the lectin LecA for host cell adhesion, invasion, and biofilm formation. Motivated by the pressing need for new anti‐infective therapies caused by antimicrobial resistance, inhibitors of LecA are under investigation. Complementary to the use of carbohydrate‐based inhibitors, we have previously identified catechols as weak but specific ligands of LecA, constituting a novel class of non‐carbohydrate glycomimetics. By growing the initial millimolar fragment hits, we identified Tolcapone as a promising compound. To gain insight into the structure‐activity relationship (SAR) of catechols as LecA binders, more than 3,200 compounds of the Roche in‐house library were experimentally screened in a competitive binding assay at three concentrations. Of these, 48 compounds were chosen for further investigation, resulting in compounds equipotent to aryl galactosides, the current epitome of LecA inhibition. X‐ray crystallography and saturation transfer difference (STD) NMR spectroscopy revealed conserved interactions of the catechol moiety in the glycan binding site of LecA and rationalized the observed SAR. Our findings demonstrate that it is possible to develop potent non‐carbohydrate glycomimetic lectin inhibitors. This work paves the way for a new avenue of research towards innovative anti‐infective drugs. In a more general perspective, such small molecules also hold potential to challenge the hegemony of antibodies for lectin inhibition in clinical use.
Upcycling of Waste Plastics into Carboxylic Acids for Biodegradable Surfactants
Abstract This work outlines a process for producing high‐purity (>95%) carboxylate surfactants from post‐consumer recycled high‐density polyethylene (PCR‐HDPE). The approach involves the thermal depolymerization of PCR‐HDPE via pyrolysis, followed by fractional distillation to isolate C9–C14 olefins. These olefins undergo hydroformylation using cobalt carbonyl catalysts to generate aldehydes, which are subsequently oxidized to carboxylic acids using Pinnick oxidation under mild aqueous‐phase conditions. Neutralization of the resulting carboxylic acids with sodium hydroxide produces plastic‐derived carboxylate surfactants (PDCs) in the form of sodium carboxylates. Subsequent purification steps ensure surfactant‐grade purity and enable accurate assessment of physicochemical properties. The resulting PDCs are evaluated for critical micelle concentration (CMC), foamability, surface tension reduction, and calcium ion tolerance, demonstrating competitive behavior with conventional anionic carboxylate surfactants. This route provides a sustainable alternative for surfactant production, reducing reliance on fossil‐derived feedstocks and valorizing plastic waste streams through chemical upcycling.
Association between lifetime co-use of classic psychedelics and cannabis and prostate cancer diagnosis among US adults 50 years and older
Exploring a New Family of (Phosphinochalcogenoyl)Europocenes for Magneto‐Optical Thermometry
Abstract The development of novel materials based on lanthanide metallocenes remains a valuable endeavour, due to the synthetic accessibility, compositional tunability, and impressive magnetic and luminescent properties of this class of well‐studied compounds. Europium(II) complexes are particularly interesting in this regard, given the relative stability, strong paramagnetism, and characteristic Laporte‐allowed 5d→4f emission of this ion. In this study, we tap into the powerful class of phosphinocyclopentadienyl ligands to develop a novel family of potassium (bis(dimethylamino)phosphinochalcogenoyl)cyclopentadienides K[C 5 Me 4 (PCh(NMe 2 ) 2 ] of sulfur, selenium, and tellurium, and explore their coordination chemistry with Eu II . These ligands readily form homoleptic europocenes where the pendant phosphine chalcogenide arms also coordinate the europium center, and these are characterized via single‐crystal X‐ray diffraction, absorbance, and photoluminescence spectroscopy. Characterization via magnetic circular dichroism (MCD) spectroscopy reveals that these complexes act as extremely sensitive probes for MCD‐based magneto‐optical thermometry, reaching relative thermal sensitivities up to 170 % K −1 at cryogenic temperatures, with temperature uncertainties as low as 0.003 K. These complexes represent the first examples of organometallic MCD thermometers, and their remarkable properties and interesting structures highlight the promise of this new class of ligands and the utility of the Eu II ion in lanthanide‐based functional materials research.
Single-layer silicon metalens for broadband achromatic focusing and wide field of view
Abstract Achieving simultaneous broadband achromatic focusing and a wide field of view remains a significant challenge for metalenses. In this work, we begin with a quadratic phase profile, enabling full field-of-view designs, and apply dispersion engineering to minimize variations of the focal length across wavelengths, thereby substantially reducing both longitudinal and transverse chromatic aberrations. This is accomplished using only the propagation phase in a single layer of waveguide-like rectangular meta-atoms, without relying on geometric phase contributions. The fabricated metalens experimentally demonstrates a field of view of $$86^{\circ }$$ , along with a tenfold reduction in focal length variations with wavelength compared to a conventional quadratic metalens, achieving a measured relative shift as low as 1.3% across the 1.5 µm - 1.6 µm range (limited by our experimental setup). This improvement also results in a constant focusing efficiency in the considered wavelength range, where a reference quadratic metalens exhibits a nearly twofold reduction. These experimental results validate the effectiveness of our design strategy in simultaneously enhancing the operational bandwidth and field of view of metalenses. The demonstrated performance can directly benefit beam steering applications in the near-infrared wavelength range and provides a path toward achromatic, wide field-of-view metalenses in the visible range for imaging systems.
A Band‐Orientation Co‐Anchoring Strategy for the Design of a High‐Performance Mid‐Infrared Nonlinear Optical Crystal
Abstract Mid‐infrared (MIR) nonlinear optical (NLO) crystals have long been pursued, yet the realization of a balance among key performance metrics remains a formidable challenge. Herein, we propose a band‐orientation co‐anchoring strategy to precisely regulate the band structures and module spatial arrangement for the rational design of high‐performance MIR NLO crystals. Leveraging the deep‐ultraviolet NLO KBe 2 BO 3 F 2 (KBBF) as a template, a novel MIR NLO Rb 3 ZnV 4 O 12 Br (RZVB) crystal was successfully obtained through multimodule substitution. Importantly, the tailored tetrahedral hybridization mode effectively anchors the conduction band minimum—dominated by d 0 cations—at a higher energy level and suppresses d–d transitions. Concurrently, structural confinement within the KBBF‐derived lattice enforces the optimal alignment of distorted tetrahedra. Furthermore, RZVB displays an unprecedented second harmonic generation (SHG) enhancement mechanism, arising from a unique cross‐module electron transfer. Consequently, RZVB exhibits superior linear and NLO performances, including a wide bandgap (3.25 eV), high laser threshold damage (1.07 GW/cm 2 @1064 nm), broad transmission window (0.382–7.6 µm), moderate birefringence (0.06@589.3 nm) and the strongest SHG response (7.7 × KDP@1064 nm and 1.45 × AGS@2.09 µm) among vanadates with bandgap exceeding 3 eV. This work presents a high‐performance MIR NLO crystal and establishes a bottom‐up, broadly applicable design paradigm for the tailored development of next‐generation crystalline materials.
SLICED: A secure and adaptive cloud–iot framework for low-latency e-learning environments
A new hybrid model for improving outlier detection using combined autoencoder and variational autoencoder
Abstract In this paper, we propose a new hybrid model, called AVE, that integrates the strengths of Autoencoder (AE) and Variational Autoencoder (VAE) to enhance outlier detection for numerous high-dimensional datasets. The proposed architecture leverages the reconstruction strengths of AE and the regularized latent space of VAE to build a stable framework for anomaly detection. Our experimental evaluation is conducted on 16 standard test sets from various domains. The results show that the AVE architecture outperforms the standalone architecture of AE, VAE, and other compared algorithms. The AVE architecture, specifically, achieves an average precision of 0.6925 and an average ROC-AUC of 0.8902 across the subsets of this test set. It surpasses the second-best architecture by 25.99% for precision and 5.47% for ROC-AUC. It surpasses AE and VAE architectures by 67.26% and 45.44% in precision, and by 7.71% and 10.03% in ROC-AUC, respectively. It achieves the best accuracy on 12 of the 16 datasets and the optimal ROC-AUC on 5 of them. Our findings demonstrate that AVE is a more reliable and precise method for detecting outliers, particularly in complex, high-dimensional datasets, making it an effective solution for real-world applications.
Combined effect of biochar, manure and compost on canola growth, yield parameters and soil chemical properties
Buried Interface Modification for High Performance and Stable Inverted Perovskite Solar Cells
Abstract Residual stress can cause distortion of the perovskite lattice, resulting in the formation of local defects such as dislocation and vacancy. These defects serve as non‐radiative recombination centers and significantly affect the stability of perovskite films. In this study, triphenylamine derivative (TAPC) was designed as an effective passivating agent. The resulting modified molecular layer established a gradient arrangement of thermal expansion coefficients between the hole transport layer (HTL) and the perovskite, effectively mitigating stress accumulation within the perovskite film. This modification concurrently enhanced hole transport capability and optimized the energy level alignment. Consequently, the power conversion efficiency (PCE) of the optimized perovskite solar cell (PSCs) increased from 24.22% to 26.05%, with the fill factor (FF) rising from 83.2% to 85.2%. Furthermore, the device achieved the lowest open‐circuit voltage ( V oc ) loss reported for comparable 1.55 eV bandgap PSCs, while maintaining excellent long‐term stability. Importantly, this strategy also enabled a corresponding flexible PSC (F‐PSCs) to achieve a remarkable PCE of 24.39%. Collectively, these results demonstrate a promising pathway for buried interface modification of perovskite films and the fabrication of high‐performance F‐PSCs.
Long-COVID research just got a big funding boost: will it find new treatments?
Assessment of the risk of osteoporotic bone fracture in postmenopausal women using machine learning methods
Isomeric Π Conjugated Covalent Organic Frameworks with Tunable Nitrogen Topologies for Integrated Gold Adsorption and Photoreduction
Abstract Gold recovery from electronic waste (e‐waste) presents a significant materials challenge, as conventional systems lack structural tunability, exhibit poor metal selectivity, and fail to integrate adsorption and photoreduction functionalities effectively. Herein, we present a topology‐guided strategy based on two isomeric π‐conjugated covalent organic frameworks (COFs) (v‐2D‐COF‐Dz and v‐2D‐COF‐Pz), incorporating diazine (ortho‐N) and pyrazine (para‐N) units, respectively, for integrated gold adsorption and photoreduction. The nitrogen topology not only stabilizes the π‐conjugated backbone but also significantly modulates the frameworks’ optoelectronic and redox properties. Notably, v‐2D‐COF‐Dz exhibits a markedly higher Au 3 ⁺ adsorption capacity (2465 versus 1854 mg g −1 ), attributed to enhanced interfacial electron localization and directional charge transfer to Au 3 ⁺ centers. Both frameworks achieve over 99% gold extraction from real e‐waste leachates under visible‐light irradiation. Spectroscopic characterization and DFT analysis reveal that nitrogen topology governs metal coordination strength and electronic coupling, enabling precise Au–Cl bond activation. This work establishes a nitrogen‐topology‐directed design paradigm for light‐driven, COF‐based precious metal recovery systems.
Association between metabolic syndrome and chronic kidney disease in the Brazilian population, a cross-sectional analysis
AI-based modeling of CO2 footprint in geopolymer concrete production containing GGBFS as a by-product from the iron industry
Abstract This study investigates the CO 2 footprint (CF) of geopolymer concrete (GPC) produced using ground granulated blast-furnace slag (GGBFS), an industrial by-product and alternative to ordinary Portland cement. Given the diversity of influential variables and the necessity for repeated testing due to changing materials and conditions, an artificial intelligence (AI)-based framework is considered an effective strategy to diminish reliance on experimental work. A novel hybrid model combining artificial neural network and biogeography-based optimization (ANN-BBO) is developed to predict the CF associated with GGBFS-based GPC production. The model incorporates 25 key variables related to precursor content and its chemical composition, activator content and characteristics, aggregate content, mix design, and curing conditions. Through rigorous evaluation using statistical metrics, error histograms, and k -fold cross-validation, the proposed ANN-BBO model demonstrated high accuracy, with 89% of its predictions falling within a 5% error margin compared to 62% for the single ANN, indicating a 27% improvement in prediction accuracy. Sensitivity analysis enhanced interpretability by identifying the superplasticizer and coarse aggregate as the key positive and negative contributors to the CF, while also suggesting that 400 kg/m 3 of GGBFS is the ideal content for maximizing compressive strength and minimizing carbon emissions in GGBFS-based GPC production.