Endoplasmic reticulum-targeting fluorescence turn-on probe for nitric oxide detection in living cells and serum samples.

Nitric oxide (NO) is an important gas signaling molecule, and endoplasmic reticulum (ER) stress induced by NO may be related to the pathogenesis of many diseases. Therefore, the development of ER-targeted fluorescent probes for NO is of great significance to investigate the relationship between ER stress and NO concentration changes in related diseases. Herein, an ER-targeted fluorescent probe (ER-Np) for sensing NO was constructed. ER-Np was served as an excellent tool for detection NO with high selectivity, sensitivity and ER-targetable ability. Moreover, fluorescence imaging experiments indicated that ER-Np is capable of imaging NO in living cells. Impressively, visualization of endogenous NO production during dithiothreitol (DTT)-induced ER stress in living cells was successfully observed. In addition, we found that serum NO levels were upregulated in epilepsy children, which opens up a new avenue for further understanding the relationship between the diagnostic of epilepsy.

Optimal Trough Concentration of Tacrolimus in Pediatric Patients With Primary Nephrotic Syndrome.

The trough concentration (C0) of tacrolimus in children with nephrotic syndrome (NS) has rarely been explored, so its target level was based on transplant research. This study aimed to determine the optimal tacrolimus C0 in NS children. Data from primary NS children treated with tacrolimus at Wuhan Children's Hospital in the last 10 years were retrospectively collected. According to the cutoff C0 analyzed by receiver-operator characteristics (ROC) analysis, patients were divided into very low- (< 4 ng/mL), low- (4-5 ng/mL), medium- (5-7 ng/mL), and high-concentration (7-10 ng/mL) groups. A total of 196 patients were enrolled for primary outcome analysis. Compared to medium-concentration group, only the very low-concentration group obtained significant inferior primary outcomes, including overall remission rate, relapse-free survival rate, and relapse rate at 6 months. For secondary outcomes, the very low-concentration group experienced more frequent treatment failure in 12 months, whereas the high-concentration group suffered a higher risk of adverse events than the medium-concentration group. For steroid-resistant NS, very low- and low-concentration groups required longer time to achieve remission compared to medium-concentration group. For steroid-sensitive NS, the very low-concentration group suffered a higher relapse frequency than medium-concentration group. Lastly, the dose of tacrolimus required for children with different CYP3A5 genotypes with or without Wuzhi capsules was analyzed. In conclusion, tacrolimus may be targeted to C0 of 4-7 ng/mL during the first 6 months in children with NS. For steroid-resistant NS, C0 of 5-7 ng/mL can achieve a rapid remission.

Efficacy and safety of levetiracetam for migraine prophylaxis in children: a systematic review and meta-analysis.

Background: Levetiracetam (LEV), an antiepileptic drug, has been effective in adult migraine prevention but lacks extensive research in children. This study evaluates LEV's efficacy and safety for pediatric migraine prophylaxis. Methods: We reviewed randomized controlled trials (RCTs) and non-RCTs in major databases through 8 January 2024, focusing on four efficacy endpoints and adverse drug reactions (ADRs). Data synthesis involved pooled relative risks or odds ratios for dichotomous outcomes and mean differences for continuous outcomes, using fixed- or random-effects models as appropriate. Results: Eight studies with 190 participants showed that after taking LEV, the mean headache frequency decreased 5.19 per month (MD: -5.19, 95% CI: -7.11 to -3.27, p < 0.00001) and improved headache-free rates to 28% (95% CI: 0.17-0.41). More than 83% experienced a >50% reduction in monthly headache frequency. The migraine disability score decreased by 33.51 points (MD: -33.51, 95% CI: -38.46 to -28.55, p < 0.00001). ADR incidence did not significantly differ between LEV and control groups (RR: 1.06, 95% CI: 0.39 to 2.85, p = 0.91), with an overall ADR rate of 18% (95% CI: 0.13-0.24). The most common ADR was irritability (12%), leading to treatment discontinuation in 13% of cases (95% CI: 0.05-0.30). Conclusion: LEV has shown good efficacy in preventing pediatric migraines. However, its safety requires further confirmation through more extensive and well-designed RCTs. Systematic Review Registration: Identifier PROSPERO CRD42024497643.

Selenium-Doped Seeded Growth of Truncated Octahedral Gold Nanocrystals with Surface Concavities for Surface-Enhanced Raman Spectroscopy.

Concave nanocrystals stand out as a testament to the importance of the nanoscale morphology in dictating the functional properties of materials. In this report, we introduce a facile synthesis method for producing gold (Au) nanocrystals with a truncated octahedral morphology that features surface concavities (Au CNTOs). The incorporation of selenium (Se) doping into the truncated octahedral Au seeds was essential for their enlargement and the formation of concave structures. By simply adjusting the quantity of seeds, we could control the size of the nanocrystals while maintaining their distinctive morphology and surface concavity. The formation mechanism suggests that Se doping likely passivates the side faces, thereby slowing growth and promoting atomic deposition at the edges and corners. The resulting Se-doped Au CNTOs exhibited strong localized surface plasmon resonance (LSPR) absorptions in the visible spectrum and the SERS performance of their assemblies was demonstrated through crystal violet detection, reaching enhancement factors around 105. This study presents an innovative approach to synthesizing concave Au nanocrystals through the incorporation of selenium during a seeded growth process, offering insights into the strategic design of plasmonic nanostructures.

Photothermal Synergistic Effect Induces Bimetallic Cooperation to Modulate Product Selectivity of CO2 Reduction on Different CeO2 Crystal Facets.

Product selectivity of solar-driven CO2 reduction and H2O oxidation reactions has been successfully controlled by tuning the spatial distance between Pt/Au bimetallic active sites on different crystal facets of CeO2 catalysts. The replacement depth of Ce atoms by monatomic Pt determines the distance between bimetallic sites, while Au clusters are deposited on the surface. This space configuration creates a favourable microenvironment for the migration of active hydrogen species (*H). The *H is generated via the activation of H2O on monatomic Pt sites and migrate towards Au clusters with a strong capacity for CO2 adsorption. Under concentrated solar irradiation, selectivity of the (100) facet towards CO is 100 %, and the selectivity of the (110) and (111) facets towards CH4 is 33.5 % and 97.6 %, respectively. Notably, the CH4 yield on the (111) facet is as high as 369.4 µmol/g/h, and the solar-to-chemical energy efficiency of 0.23 % is 33.8 times higher than that under non-concentrated solar irradiation. The impacts of high-density flux photon and thermal effects on carriers and *H migration at the microscale are comprehensively discussed. This study provides a new avenue for tuning the spatial distance between active sites to achieve optimal product selectivity.

Non-Hermitian Delocalization in a Two-Dimensional Photonic Quasicrystal.

Theoretical and experimental studies suggest that both Hermitian and non-Hermitian quasicrystals show localization due to the fractal spectrum and to the transition to diffusive bands via exceptional points, respectively. Here, we present an experimental study of a dodecagonal photonic quasicrystal based on electromagnetically induced transparency in a Rb vapor cell. First, we observe the suppression of the wave packet expansion in the Hermitian case. We then discover a new regime, where increasing the non-Hermiticity leads to delocalization, demonstrating that the behavior in non-Hermitian quasicrystals is richer than previously thought.

Exploring Geometric Chirality in Nanocrystals for Boosting Solar-to-Hydrogen Conversion.

Advancing catalyst design is pivotal for the enhancement of photocatalytic processes in renewable energy conversion. The incorporation of structural chirality into conventional inorganic solar hydrogen nanocatalysts promises a significant transformation in catalysis, a feature absent in this field. Here we unveil the unexplored potential of geometric chirality by creating a chiral composite that integrates geometric chiral Au nanoparticles (NPs) with two-dimensional C3N4 nanosheets, significantly boosting photocatalytic H2 evolution beyond the achiral counterparts. The superior performance is driven by the geometric chirality of Au NPs, which facilitates efficient charge carrier separation through the favorable C3N4-chiral Au NP interface and chiral induced spin polarization, and exploits high-activity facets within the concave surfaces of chiral Au NPs. The resulting synergistic effect leads to a remarkable increase in photocatalytic H2 evolution, with an apparent quantum yield of 44.64% at 400 nm. Furthermore, we explore the selective polarized photo-induced carrier separation behavior, revealing a distinct chiral-dependent photocatalytic HER performance. Our work advances the design and utilization of chiral inorganic nanostructures for superior performance in energy conversion processes.

Concentrated solar CO2 reduction in H2O vapour with >1% energy conversion efficiency.

H2O dissociation plays a crucial role in solar-driven catalytic CO2 methanation, demanding high temperature even for solar-to-chemical conversion efficiencies <1% with modest product selectivity. Herein, we report an oxygen-vacancy (Vo) rich CeO2 catalyst with single-atom Ni anchored around its surface Vo sites by replacing Ce atoms to promote H2O dissociation and achieve effective photothermal CO2 reduction under concentrated light irradiation. The high photon flux reduces the apparent activation energy for CH4 production and prevents Vo from depletion. The defects coordinated with single-atom Ni, significantly promote the capture of charges and local phonons at the Ni d-impurity orbitals, thereby inducing more effective H2O activation. The catalyst presents a CH4 yield of 192.75 µmol/cm2/h, with a solar-to-chemical efficiency of 1.14% and a selectivity ~100%. The mechanistic insights uncovered in this study should help further the development of H2O-activating catalysts for CO2 reduction and thereby expedite the practical utilization of solar-to-chemical technologies.

Co-sensitization of Copper Indium Gallium Disulfide and Indium Sulfide on Zinc Oxide Nanostructures: Effect of Morphology in Electrochemical Carbon Dioxide Reduction.

Recent advances in nanoparticle materials can facilitate the electro-reduction of carbon dioxide (CO2) to form valuable products with high selectivity. Copper (Cu)-based electrodes are promising candidates to drive efficient and selective CO2 reduction. However, the application of Cu-based chalcopyrite semiconductors in the electrocatalytic reduction of CO2 is still limited. This study demonstrated that novel zinc oxide (ZnO)/copper indium gallium sulfide (CIGS)/indium sulfide (InS) heterojunction electrodes could be used in effective CO2 reduction for formic acid production. It has been determined that Faradaic efficiencies for formic acid production using ZnO nanowire (NW) and nanoflower (NF) structures vary due to structural and morphological differences. A ZnO NW/CIGS/InS heterojunction electrode resulted in the highest efficiency of 77.2% and 0.35 mA cm-2 of current density at a -0.24 V (vs. reversible hydrogen electrode) bias potential. Adding a ZTO intermediate layer by the spray pyrolysis method decreased the yield of formic acid and increased the yield of H2. Our work offers a new heterojunction electrode for efficient formic acid production via cost-effective and scalable CO2 reduction.

Integration of Co Single Atoms and Ni Clusters on Defect-Rich ZrO2 for Strong Photothermal Coupling Boosts Photocatalytic CO2 Reduction.

We report a solvothermal method for the synthesis of an oxygen vacancy-enriched ZrO2 photocatalyst with Co single atoms and Ni clusters immobilized on the surface. This catalyst presents superior performance for the reduction of CO2 in H2O vapor, with a CO yield reaching 663.84 µmol g-1 h-1 and a selectivity of 99.52%. The total solar-to-chemical energy conversion efficiency is up to 0.372‰, which is among the highest reported values. The success, on one hand, depends on the Co single atoms and Ni clusters for both extended spectrum absorption and serving as dual-active centers for CO2 reduction and H2O dissociation, respectively; on the other hand, this is attributed to the enhanced photoelectric and thermal effect induced by concentrated solar irradiation. We demonstrate that an intermediate impurity state is formed by the hybridization of the d-orbital of single-atom Co with the molecular orbital of H2O, enabling visible-light-driven excitation over the catalyst. In addition, Ni clusters play a crucial role in altering the adsorption configuration of CO2, with the localized surface plasmon resonance effect enhancing the activation and dissociation of CO2 induced by visible-near-infrared light. This study provides valuable insights into the synergistic effect of the dual cocatalyst toward both efficient photothermal coupling and surface redox reactions for solar CO2 reduction.

Defect Engineering Simultaneously Regulating Exciton Dissociation in Carbon Nitride and Local Electron Density in Pt Single Atoms Toward Highly Efficient Photocatalytic Hydrogen Production.

The high exciton binding energy (Eb) and sluggish surface reaction kinetics have severely limited the photocatalytic hydrogen production activity of carbon nitride (CN). Herein, a hybrid system consisting of nitrogen defects and Pt single atoms is constructed through a facile self-assembly and photodeposition strategy. Due to the acceleration of exciton dissociation and regulation of local electron density of Pt single atoms along with the introduction of nitrogen defects, the optimized Pt-MCT-3 exhibits a hydrogen production rate of 172.0 µmol h-1 (λ ≥ 420 nm), ≈41 times higher than pristine CN. The apparent quantum yield for the hydrogen production is determined to be 27.1% at 420 nm. The experimental characterizations and theoretical calculations demonstrate that the nitrogen defects act as the electron traps for the exciton dissociation, resulting in a decrease of Eb from 86.92 to 43.20 meV. Simultaneously, the stronger interaction between neighboring nitrogen defects and Pt single atoms directionally drives free electrons to aggregate around Pt single atoms, and tailors the d-band electrons of Pt, forming a moderate binding strength between Pt atoms and H* intermediates.

Fatty Amine-Mediated Synthesis of Hierarchical Copper Sulfide Nanoflowers for Efficient NIR-II Photothermal Conversion and Antibacterial Performance.

Non-noble metal photothermal materials have recently attracted increasing attention as unique alternatives to noble metal-based ones due to advantages like earth abundance, cost-effectiveness, and large-scale application capability. In this study, hierarchical copper sulfide (CuS) nanostructures with tunable flower-like morphologies and dimensional sizes are prepared via a fatty amine-mediated one-pot polyol synthesis. In particular, the addition of fatty amines induces a significant decrease in the overall particle size and lamellar thickness, and their morphologies and sizes could be tuned using different types of fatty amines. The dense stacking of nanosheets with limited sizes in the form of such a unique hierarchical architecture facilitates the interactions of the electromagnetic fields between adjacent nanoplates and enables the creation of abundant hot-spot regions, thus, benefiting the enhanced second near-infrared (NIR-II) light absorptions. The optimized CuS nanoflowers exhibit a photothermal conversion efficiency of 37.6%, realizing a temperature increase of nearly 50 °C within 10 min under 1064 nm laser irradiations at a power density of 1 W cm-2. They also exhibit broad-spectrum antibacterial activity, rendering them promising candidates for combating a spectrum of bacterial infections. The present study offers a feasible strategy to generate nanosheet-based hierarchical CuS nanostructures and validates their promising use in photothermal conversion, which could find important use in NIR-II photothermal therapy.

Nanotip-Induced Electric Field for Hydrogen Catalysis.

Local electric field induced by the lightning-rod effect attracts great attention for regulating the local microenvironment and electronic properties of active sites. Nevertheless, local electric-field-assisted applications are mainly limited to metals with strong surface plasmonic resonance properties (e.g., Au, Ag, and Cu). Herein, we fabricate RuCu snow-like nanosheets (SNSs) with high-curvature nanotips for enhancing the hydrogen oxidation reaction (HOR) and hydrogen evolution reaction (HER). Theoretical simulations show that RuCu SNSs can induce a strong local electric field around the sharp nanotips, which favors the accumulation of OH- for HOR and H+ for HER. Cu incorporation can modulate the binding strength of OH* and H*, leading to significantly enhanced HOR and HER performance. Impressively, the mass activity of RuCu SNSs for alkaline HOR is 31.3 times higher than that of RuCu nanocrystals without sharp tips. Besides, the required overpotential for reaching 10 mA cm-2 during HER over RuCu SNSs is 14.0 mV.

dz2 Band Links Frontier Orbitals and Charge Carrier Dynamics of Single-Atom Cocatalyst-Aided Photocatalytic H2 Production.

The Cu single-atom catalyst (SAC) supported on TiO2 exhibits outstanding efficacy in photocatalytic hydrogen evolution. The precise operational mechanism remains a subject of ongoing debate. The focus resides with the interplay linking heightened catalytic activity, dynamic valence state alterations of Cu atoms, and their hybridization with H2O orbitals, manifested in catalyst color changes. Taking anatase TiO2 (101) as a prototypical surface, we perform ab initio quantum dynamics simulation to reveal that the high activity of the Cu-SAC is due to the quasi-planar coordination structure of the Cu atom after H2O adsorption, allowing it to trap photoexcited hot electrons and inject them into the hybridized orbital between Cu and H2O. The observed alterations in the valence state and the coloration can be attributed to the H atom released during H2O dissociation and adsorbed onto the lattice O atom neighboring the Cu-SAC. Notably, this adsorption of H atoms puts the Cu-SAC into an inert state, as opposed to an activating effect reported previously. Our work clarifies the relationship between the high photocatalytic activity and the local dynamic atomic coordination structure, providing atomistic insights into the structural changes occurring during photocatalytic reactions on SACs.

Photothermally driven decoupling of gas evolution at the solid-liquid interface for boosted photocatalytic hydrogen production.

The slow mass transfer, especially the gas evolution process at the solid-liquid interface in photocatalytic water splitting, restricts the overall efficiency of the hydrogen evolution reaction. Here, we report a novel gas-solid photocatalytic reaction system by decoupling hydrogen generation from a traditional solid-liquid interface. The success relies on annealing commercial melamine sponge (AMS) for effective photothermal conversion that leads to rapid water evaporation. The vapor flows towards the photocatalyst covering the surface of the AMS and is split by the catalyst therein. This liquid-gas/gas-solid coupling system avoids the formation of photocatalytic bubbles at the solid-liquid interface, leading to significantly improved mass transfer and conversion. Utilizing CdS nanorods anchored by highly dispersed nickel atoms/clusters as a model photocatalyst, the highest hydrogen evolution rate from water splitting reaches 686.39 µmol h-1, which is 5.31 times that of the traditional solid-liquid-gas triphase system. The solar-to-hydrogen (STH) efficiency can be up to 2.06%. This study provides a new idea for the design and construction of efficient practical photocatalytic systems.

Fermi Level Pinning in Concentrated Light-Induced Band Edge Tuning Maximizes Photocatalytic Solar-to-Hydrogen Efficiency.

Here, we demonstrate a concentrated light-induced band edge tuning effect in photocatalytic hydrogen production. This band movement along with Femi level pinning leads to two distinct catalytic behaviors upon irradiation flux increase. Specifically, the concentration of the light promotes more long-lived carriers bound to the surface electronic states, progressively boosting energy conversion efficiency to a maximum value. Afterward, efficiency diminishes gradually due to poor carrier transfer. This work offers critical insights into efficient and economical photocatalytic hydrogen production.

Accelerating the Design of High-Energy-Density Hydrocarbon Fuels by Learning from the Data.

In the ZINC20 database, with the aid of maximum substructure searches, common substructures were obtained from molecules with high-strain-energy and combustion heat values, and further provided domain knowledge on how to design high-energy-density hydrocarbon (HEDH) fuels. Notably, quadricyclane and syntin could be topologically assembled through these substructures, and the corresponding assembled schemes guided the design of 20 fuel molecules (ZD-1 to ZD-20). The fuel properties of the molecules were evaluated by using group-contribution methods and density functional theory (DFT) calculations, where ZD-6 stood out due to the high volumetric net heat of combustion, high specific impulse, low melting point, and acceptable flash point. Based on the neural network model for evaluating the synthetic complexity (SCScore), the estimated value of ZD-6 was close to that of syntin, indicating that the synthetic complexity of ZD-6 was comparable to that of syntin. This work not only provides ZD-6 as a potential HEDH fuel, but also illustrates the superiority of learning design strategies from the data in increasing the understanding of structure and performance relationships and accelerating the development of novel HEDH fuels.

Sphingolipid metabolism in brain insulin resistance and neurological diseases.

Sphingolipids, as members of the large lipid family, are important components of plasma membrane. Sphingolipids participate in biological signal transduction to regulate various important physiological processes such as cell growth, apoptosis, senescence, and differentiation. Numerous studies have demonstrated that sphingolipids are strongly associated with glucose metabolism and insulin resistance. Insulin resistance, including peripheral insulin resistance and brain insulin resistance, is closely related to the occurrence and development of many metabolic diseases. In addition to metabolic diseases, like type 2 diabetes, brain insulin resistance is also involved in the progression of neurodegenerative diseases including Alzheimer's disease and Parkinson's disease. However, the specific mechanism of sphingolipids in brain insulin resistance has not been systematically summarized. This article reviews the involvement of sphingolipids in brain insulin resistance, highlighting the role and molecular biological mechanism of sphingolipid metabolism in cognitive dysfunctions and neuropathological abnormalities of the brain.

Modeling the protein binding non-linearity in population pharmacokinetic model of valproic acid in children with epilepsy: a systematic evaluation study.

Background: Several studies have investigated the population pharmacokinetics (popPK) of valproic acid (VPA) in children with epilepsy. However, the predictive performance of these models in the extrapolation to other clinical environments has not been studied. Hence, this study evaluated the predictive abilities of pediatric popPK models of VPA and identified the potential effects of protein binding modeling strategies. Methods: A dataset of 255 trough concentrations in 202 children with epilepsy was analyzed to assess the predictive performance of qualified models, following literature review. The evaluation of external predictive ability was conducted by prediction- and simulation-based diagnostics as well as Bayesian forecasting. Furthermore, five popPK models with different protein binding modeling strategies were developed to investigate the discrepancy among the one-binding site model, Langmuir equation, dose-dependent maximum effect model, linear non-saturable binding equation and the simple exponent model on model predictive ability. Results: Ten popPK models were identified in the literature. Co-medication, body weight, daily dose, and age were the four most commonly involved covariates influencing VPA clearance. The model proposed by Serrano et al. showed the best performance with a median prediction error (MDPE) of 1.40%, median absolute prediction error (MAPE) of 17.38%, and percentages of PE within 20% (F20, 55.69%) and 30% (F30, 76.47%). However, all models performed inadequately in terms of the simulation-based normalized prediction distribution error, indicating unsatisfactory normality. Bayesian forecasting enhanced predictive performance, as prior observations were available. More prior observations are needed for model predictability to reach a stable state. The linear non-saturable binding equation had a higher predictive value than other protein binding models. Conclusion: The predictive abilities of most popPK models of VPA in children with epilepsy were unsatisfactory. The linear non-saturable binding equation is more suitable for modeling non-linearity. Moreover, Bayesian forecasting with prior observations improved model fitness.