stDiff: a diffusion model for imputing spatial transcriptomics through single-cell transcriptomics.

Spatial transcriptomics (ST) has become a powerful tool for exploring the spatial organization of gene expression in tissues. Imaging-based methods, though offering superior spatial resolutions at the single-cell level, are limited in either the number of imaged genes or the sensitivity of gene detection. Existing approaches for enhancing ST rely on the similarity between ST cells and reference single-cell RNA sequencing (scRNA-seq) cells. In contrast, we introduce stDiff, which leverages relationships between gene expression abundance in scRNA-seq data to enhance ST. stDiff employs a conditional diffusion model, capturing gene expression abundance relationships in scRNA-seq data through two Markov processes: one introducing noise to transcriptomics data and the other denoising to recover them. The missing portion of ST is predicted by incorporating the original ST data into the denoising process. In our comprehensive performance evaluation across 16 datasets, utilizing multiple clustering and similarity metrics, stDiff stands out for its exceptional ability to preserve topological structures among cells, positioning itself as a robust solution for cell population identification. Moreover, stDiff's enhancement outcomes closely mirror the actual ST data within the batch space. Across diverse spatial expression patterns, our model accurately reconstructs them, delineating distinct spatial boundaries. This highlights stDiff's capability to unify the observed and predicted segments of ST data for subsequent analysis. We anticipate that stDiff, with its innovative approach, will contribute to advancing ST imputation methodologies.

Spatial enrichment and genomic analyses reveal the link of NOMO1 with amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a severe motor neuron disease with uncertain genetic predisposition in most sporadic cases. Spatial architecture of cell types and gene expression is the basis of cell-cell interactions, biological function and disease pathology, but is not well investigated in human motor cortex, a key ALS relevant brain region. Recent studies indicated single nucleus transcriptomic features of motor neuron vulnerability in ALS motor cortex. However, it remains largely unclear what is the brain regional vulnerability of ALS-associated genes, and what is the genetic link between region-specific genes and ALS risk. Here, we developed an entropy-weighted differential gene expression matrix-based tool (SpatialE) to identify the spatial enrichment of gene sets in spatial transcriptomics (ST). We benchmarked SpatialE against another enrichment tool (Multimodal Intersection Analysis, MIA) using ST data from both human and mouse brain tissues. To investigate regional vulnerability, we analyzed three human motor cortex and two dorsolateral prefrontal cortex tissues for spatial enrichment of ALS-associated genes. We also used Cell2location to estimate the abundance of cell types in ALS-related cortex layers. To dissect the link of regionally expressed genes and ALS risk, we performed burden analyses of rare loss-of-function (LOF) variants detected by whole-genome sequencing in ALS patients and controls, and then analyzed differential gene expression in the TargetALS RNA-seq dataset. SpatialE showed more accurate and specific spatial enrichment of regional cell type markers than MIA in both mouse brain and human dorsolateral prefrontal cortex. Spatial transcriptomic analyses of human motor cortex showed heterogenous cell types and spatial gene expression profiles. We found that 260 manually curated ALS-associated genes are significantly enriched in layer 5 (L5) motor cortex, with abundant expression of upper motor neurons and L5 excitatory neurons. Burden analyses of rare LOF variants in L5-associated genes nominated NOMO1 as a novel ALS-associated gene in a combined sample set of 6,814 ALS patients and 3,324 controls (P = 0.029). Gene expression analyses in central nervous system tissues revealed down-regulation of NOMO1 in ALS, which is consistent with a LOF disease mechanism. In conclusion, our integrated ST and genomic analyses identified regional brain vulnerability in ALS and the association of a L5 gene (NOMO1) with ALS risk.

Strain Engineering of Ion-Coordinated Nanochannels in Nanocellulose.

Expanding the interlayer spacing plays a significant role in improving the conductivity of a cellulose-based conductor. However, it remains a challenge to regulate the cellulose nanochannel expanded by ion coordination. Herein, starting from multiscale mechanics, we proposed a strain engineering method to regulate the interlayer spacing of the cellulose nanochannels. First-principles calculations were conducted to select the most suitable ions for coordination. Large-scale molecular dynamics simulations were performed to reveal the mechanism of interlayer spacing expansion by the ion cross-linking. Combining the shear-lag model, we established the relationship between interfacial cross-link density and interlayer spacing of an ion-coordinated cellulose nanochannel. Consequently, fast ion transport and current regulation were realized via the strain engineering of nanochannels, which provides a promising strategy for the current regulation of a cellulose-based conductor.

Anisotropic Fracture of Two-Dimensional Ta2NiSe5.

Anisotropic two-dimensional materials present a diverse range of physical characteristics, making them well-suited for applications in photonics and optoelectronics. While mechanical properties play a crucial role in determining the reliability and efficacy of 2D material-based devices, the fracture behavior of anisotropic 2D crystals remains relatively unexplored. Toward this end, we herein present the first measurement of the anisotropic fracture toughness of 2D Ta2NiSe5 by microelectromechanical system-based tensile tests. Our findings reveal a significant in-plane anisotropic ratio (∼3.0), accounting for crystal orientation-dependent crack paths. As the thickness increases, we observe an intriguing intraplanar-to-interplanar transition of fracture along the a-axis, manifesting as stepwise crack features attributed to interlayer slippage. In contrast, ruptures along the c-axis surprisingly exhibit persistent straightness and smoothness regardless of thickness, owing to the robust interlayer shear resistance. Our work affords a promising avenue for the construction of future electronics based on nanoribbons with atomically sharp edges.

A Drug Molecule-Modified Graphene Field-Effect Transistor Nanosensor for Rapid, Label-Free, and Ultrasensitive Detection of Estrogen Receptor α Protein.

Estrogen receptor α (ERα) is an important biomarker in breast cancer diagnosis and treatment. Sensitive and accurate detection of ERα protein expression is crucial in guiding selection of an appropriate therapeutic strategy to improve the effectiveness and prognosis of breast cancer treatment. Herein, we report a liquid-gated graphene field-effect transistor (FET) biosensor that enables rapid, sensitive, and label-free detection of the ERα protein by employing a novel drug molecule as a capture probe. The drug molecule was synthesized and subsequently immobilized onto the sensing surface of the fabricated graphene FET, which was able to distinguish the ERα-positive from the ERα-negative protein. The developed sensor not only demonstrated a low detection limit (LOD: 2.62 fM) but also achieved a fast response to ERα protein samples within 30 min. Moreover, depending on the relationship between the change of dirac point and the ERα protein concentrations, the dissociation constant (Kd) was estimated to be 7.35 ± 0.06 pM, indicating that the drug probe-modified graphene FET had a good affinity with ERα protein. The nanosensor was able to analyze ERα proteins from 36 cell samples lysates. These results show that the graphene FET sensor was able to differentiate between ERα-positive and ERα-negative cells, indicating a promising biosensor for the ultrasensitive and rapid detection of ERα protein without antibody labeling.

Advances in Atomically Dispersed Metal and Nitrogen Co-Doped Carbon Catalysts for Advanced Oxidation Technologies and Water Remediation: From Microenvironment Modulation to Non-Radical Mechanisms.

Atomically dispersed metal and nitrogen co-doped carbon catalysts (M-N-C) have been attracting tremendous attentions thanks to their unique MNx active sites and fantastic catalytic activities in advanced oxidation technologies (AOTs) for water remediation. However, precisely tailoring the microenvironment of active sites at atomic level is still an intricate challenge so far, and understanding of the non-radical mechanisms in persulfate activation exists many uncertainties. In this review, latest developments on the microenvironment modulation strategies of atomically dispersed M-N-C catalysts including regulation of central metal atoms, regulation of coordination numbers, regulation of coordination heteroatoms, and synergy between single-atom catalysts (SACs) with metal species are systematically highlighted and discussed. Afterwards, progress and underlying limitations about the typical non-radical pathways from production of singlet oxygen, electron transfer mechanism to generation of high-valent metal species are well demonstrated to inspire intrinsic insights about the mechanisms of M-N-C/persulfate systems. Lastly, perspectives for the remaining challenges and opportunities about the further development of carbon-based SACs in environment remediation are also pointed out. It is believed that this review will be much valuable for the further design of active sites in M-N-C/persulfate catalytic systems and promote the wide application of SACs in various fields.

Ultra-high Q-factor quasi-BIC BaTiO3 metasurface for electro-optic modulation.

Metasurfaces play a crucial role in trapping electromagnetic waves with specific wavelengths, serving as a significant platform for enhancing light-matter interactions. In all kinds of dynamic modulation metasurfaces, electro-optic modulation metasurfaces have attracted much attention due to its advantages of fast, stable and high efficiency. In order to respond to the extremely weak refractive index change of the electro-optical effect of the materials, the metasurfaces are required to support optical signals with high Q values. The quasi-bound state in the continuum (Q-BIC) is often used to enhance the light-field modulation capability of metasurfaces and to improve the modulation sensitivity of electro-optic modulators due to its ability to generate high Q-factor resonances. However, the design of an electro-optic modulation metasurface that facilitates the application of voltage and achieves modulation efficiency of nearly 100% is still in urgent need of development. In this study, single-crystal BTO metasurfaces are modeled using finite-difference time-domain method, and the structural symmetry is broken to introduce a Q-BIC resonance to generate a high Q-factor optical signal of 2.45 × 104 for high-depth electro-optic modulation. By simulating an applied electric field of 143 V/mm on the metasurface, a slight refractive index change of BTO of 8 × 10-4 was produced, leading to an electro-optical intensity modulation depth of 100%. Furthermore, the nanostructure of the metasurface was carefully designed to facilitate nano-fabrication and voltage application, and it is ideal for the development of low-power, CMOS-compatible, and miniaturized electro-optic modulation devices. Although the results of this study are based on simulations, they provide a crucial theoretical basis and guidance for the realization of efficient and realistic design of dynamic metasurfaces.

SLC25A17 inhibits autophagy to promote triple-negative breast cancer tumorigenesis by ROS-mediated JAK2/STAT3 signaling pathway.

BACKGROUND: SLC25A17, a peroxisomal solute carrier, has been implicated in various physiological and pathological processes. However, its precise roles and underlying mechanisms in triple-negative breast cancer (TNBC) remain incompletely understood. METHODS: The expression and survival data of breast cancer were derived from TCGA and GEO databases. A variety of in vitro assays were conducted, including proliferation, apoptosis, cell cycle, migration, and invasion. Reactive oxygen species (ROS) were measured by immunofluorescence microscopy and flow cytometry. The levels of autophagy were assessed by mRFP-GFP-LC3 confocal microscopy scanning, western blotting, and electron microscopy. RESULTS: SLC25A17 was highly expressed in breast cancer tissues, which was found to be associated with unfavorable prognosis. Functional assays demonstrated that SLC25A17 knockdown suppressed proliferation, epithelial-mesenchymal transition (EMT), migration, and invasion. Moreover, it prompted apoptosis and autophagy. On the other hand, SLC25A17 knockdown promoted autophagy through triggering ROS accumulation, which was counteracted by N-acetyl-l-cysteine (NAC). Furthermore, the pro-apoptotic effect of SLC25A17 knockdown was reversed when treated with autophagy inhibitor 3-MA in TNBC cells, suggesting that SLC25A17 knockdown-induced autophagic cell death. Mechanistically, SLC25A17 performed its function through regulation JAK2/STAT3 signaling in TNBC. In a nude mice xenograft study, SLC25A17 knockdown markedly decreased breast tumor growth and metastasis. CONCLUSION: SLC25A17 up-regulation may be a critical factor driving TNBC progression by modulating ROS production and autophagy. Consequently, targeting SLC25A17 could be an effective therapeutic strategy against TNBC.

Advanced Separator Materials for Enhanced Electrochemical Performance of Lithium-Sulfur Batteries: Progress and Prospects.

Lithium-sulfur (Li-S) batteries are promising energy storage devices owing to their high theoretical specific capacity and energy density. However, several challenges, including volume expansion, slow reaction kinetics, polysulfide shuttle effect and lithium dendrite formation, hinder their commercialization. Separators are a key component of Li-S batteries. Traditional separators, made of polypropylene and polyethylene, have certain limitations that should be addressed. Therefore, this review discusses the basic properties and mechanisms of Li-S battery separators, focuses on preparing different functionalized separators to mitigate the shuttle effect of polysulfides. This review also introduces future research trends, emphasizing the potential of separator functionalization in advancing the Li-S battery technology.

From Ethylene Glycol to Glycolic Acid: Electrocatalytic Conversion on Pt-Group Metal Surfaces.

Ethylene glycol (EG) is one of the most attractive platform molecules derived from biomass and waste plastics. Thus, the selective electrooxidation of ethylene glycol (EGOR) into value-added chemicals (especially glycolic acid (GA)) can promote its recycling and upgrading. However, the understanding of the EG-to-GA process on Pt-group metal (PGM) electrodes is far limited now. It has been shown that the Pt and Pd electrodes could show considerable EGOR activity but not Rh and Ir electrodes. Meanwhile, EGOR mainly produces the glycolate, oxalate, and formate on Pt and Pd electrodes, whereas it can obtain minute amounts of glycolate and oxalate on Rh and Ir electrodes. Impressively, the selectivity of glycolate on Pt and Pd electrodes can be over 85% (apparent Faradaic efficiency) in alkaline media, although the stability should be further improved through interfacial tuning and/or engineering. This work might deepen the fundamental understanding of the EGOR process on the nature of PGM electrodes.

Self-assembly mechanism, physicochemical analyses and application performance investigations of branched alkyl glycosides with alcohol ether carboxylic acids of varied epoxide numbers.

Green surfactants, specifically alkyl glycosides and fatty alcohol ether carboxylic acids, are known for their biocompatibility, multiresponsiveness, and versatile applications, garnering significant attention in the realms of green and colloid chemistry. This study systematically investigated the mechanism underlying micelle formation within aqueous solutions comprising alcohol ether carboxylic acids featuring diverse EO group chain quantities (AEC-nH, where n equals 5, 7, and 9) and branched alkyl glycosides (IG). The elucidation of these mechanisms sheds light on their prospective application properties. It was observed that the self-assembly of micelles in these hybrid systems is predominantly influenced by hydrogen bonding, electrostatic interactions, and hydrophobic forces. The spherical-rod morphology of the micelles responds to the varying numbers of EO group chains, with an increased number of EO leading to the formation of rod-like micelles, which exhibit relative instability, while a decreased number of EO results in the formation of spherical micelles with relative stability. Additionally, by means of kinetic analysis, it was determined that the micelle formation process of the three hybrid systems is driven by enthalpy, and a mixed diffusion-kinetics adsorption mechanism is involved in the adsorption process. These findings significantly impact their application properties. This report stands as the first exploration of the synergistic mechanisms and application performance of two types of green surfactants in aqueous solutions, considering the influence of different numbers of EO group chains. Not only does it provide fundamental insights into their properties, but it also offers novel perspectives on the applications of green surface activation.

NVAM-Net: deep learning networks for reconstructing high-quality fiber orientation distributions.

PURPOSE: Diffusion magnetic resonance imaging (dMRI) is a widely used non-invasive method for investigating brain anatomical structures. Conventional techniques for estimating fiber orientation distribution (FOD) from dMRI data often neglect voxel-level spatial relationships, leading to ambiguous associations between target voxels and their neighbors, which, in turn, adversely impacts FOD accuracy. This study aims to address this issue by introducing a novel neural network, the neighboring voxel attention mechanism network (NVAM-Net), designed to reconstruct high-quality FOD images. METHODS: The NVAM-Net leverages a Transformer architecture and incorporates two innovative attention mechanisms: voxel attention and surface attention. These mechanisms are specifically designed to capture overlooked features among neighboring voxels. The processed features are subsequently passed through two fully connected layers, further enhancing FOD estimation accuracy by separately estimating spherical harmonics (SH) coefficients of varying orders. RESULTS: The experimental findings, based on the Human Connectome Project (HCP) dataset, reveal that the reconstructed super-resolution FOD images achieve results comparable to those obtained through more advanced dMRI acquisition protocols. These results underscore the NVAM-Net's robust performance in reconstructing multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD). CONCLUSION: In summary, this research underscores the NVAM-Net's advantages and practical feasibility in reconstructing high-quality FOD images. It provides a reliable reference point for clinical applications in the field of diffusion magnetic resonance imaging.

Association between C-reactive protein/albumin ratio and all-cause mortality in patients with stroke: Evidence from NHANES cohort study.

BACKGROUND AND AIMS: The inflammatory nutritional status is widely associated with the long-term prognosis of non-fatal stroke. The objective of this study is to examine the correlation between the C-reactive protein to albumin ratio (CAR), a new marker indicating both inflammatory and nutritional status, and the overall mortality rate among stroke patients. METHODS AND RESULTS: Data were obtained from the National Health and Nutrition Examination Survey (NHANES) database and corresponding public-use mortality data from the linked National Death Index (NDI). The study utilized maximally selected rank statistics to determine the optimal cutoff points for the CAR. Subsequently, participants were stratified into higher- and lower-CAR groups based on these cutoff points. The Kaplan-Meier survival method was used to study overall survival probability. Multivariable Cox proportional regression models were employed to calculate the Hazard Ratio (HR) and corresponding confidence interval (CI). Restricted cubic spline (RCS) model was applied to detect potential non-linear relationship between CAR and mortality risk. Furthermore, stratified and sensitive analyses were performed to examine the robustness and reliability of the results. The study, encompassing 1043 participants with an average age of 64.61 years, identified a cutoff value of 0.32 for CAR, with notable variances observed across gender and age cohorts. Over an average follow-up period of 116 months, 679 instances of all-cause mortality were documented. Kaplan-Meier survival analysis unveiled noteworthy disparities in survival probabilities between groups categorized by high and low CAR levels (p = 0.00081). Continuous CAR analysis consistently demonstrated a positive correlation between elevated CAR values and heightened risk (HR = 1.78 (1.36, 2.33)) of all-cause mortality among stroke patients. Similarly, individuals in the high CAR group exhibited adjusted HR of 1.34 (0.96, 1.89) for all-cause mortality compared to their low CAR counterparts. Subgroup and sensitive analysis consistently reinforced these findings. Smoothing curve fitting further validated CAR's significance as a prognostic indicator of all-cause mortality, indicating a linear relationship. CONCLUSION: Elevated CAR is associated with increased long-term risk of mortality for individuals who have experienced a stroke, suggesting that CAR could serve as a survival indicator.

Bridge effect on charge transfer and energy transfer in fullerene-chromophore dyads.

Fullerene-chromophore dyads have attracted a great deal of research interest because these complexes can be potentially designed as nanoscale artificial photosynthetic centers, in which the chromophore and fullerene function as the electron donor and acceptor, respectively. The basic operation of this dyad-type artificial reaction center is photoinduced electron transfer from the donor to the acceptor. The fullerene and chromophore are usually covalently linked so that sufficient electronic coupling between these two moieties can facilitate the electron transfer. However, other deactivation pathways for the chromophore excited state, such as energy transfer to the fullerene, may reduce the quantum yield of the photoinduced electron transfer. Here, a series of C60-perylene dyads is exploited to interrogate the effect of the linkage on deactivation mechanisms of the chromophore excited state. For the C60-perylene dyads with a single or double bond bridge, we find that the decay of the singlet state of the chromophore is dominated by the electron transfer, and the corresponding time constant is determined to be 45 ps. On the other hand, for the dyad with a triple bond bridge, the singlet state of the chromophore is quickly quenched through energy transfer to fullerene, and the time constant is as short as 7.9 ps. Our finding suggests that the bond order of the bridge in the fullerene-chromophore dyads can be utilized to control the deactivation pathways of the excited state.

A portable transistor immunosensor for fast identification of porcine epidemic diarrhea virus.

Widespread distribution of porcine epidemic diarrhea virus (PEDV) has led to catastrophic losses to the global pig farming industry. As a result, there is an urgent need for rapid, sensitive and accurate tests for PEDV to enable timely and effective interventions. In the present study, we develop and validate a floating gate carbon nanotubes field-effect transistor (FG CNT-FET)-based portable immunosensor for rapid identification of PEDV in a sensitive and accurate manner. To improve the affinity, a unique PEDV spike protein-specific monoclonal antibody is prepared by purification, and subsequently modified on FG CNT-FET sensor to recognize PEDV. The developed FET biosensor enables highly sensitive detection (LoD: 8.1 fg/mL and 100.14 TCID50/mL for recombinant spike proteins and PEDV, respectively), as well as satisfactory specificity. Notably, an integrated portable platform consisting of a pluggable FG CNT-FET chip and a portable device can discriminate PEDV positive from negative samples and even identify PEDV and porcine deltacoronavirus within 1 min with 100% accuracy. The portable sensing platform offers the capability to quickly, sensitively and accurately identify PEDV, which further points to a possibility of point of care (POC) applications of large-scale surveillance in pig breeding facilities.

The establishment of diseased human whole organ model by normothermic machine perfusion technique: Principle of concept.

BACKGROUND: The global incidence of liver diseases is rising, yet there remains a dearth of precise research models to mimic these diseases. The use of normothermic machine perfusion (NMP) to study diseased livers recovered from liver transplantation (LT) recipients presents a promising avenue. Accordingly, we have developed a machine perfusion system tailored specifically for the human whole diseased livers and present our experience from the NMP of diseased livers. METHODS: Six diseased livers recovered from LT recipients with different diagnoses were collected. The diseased livers were connected to the machine perfusion system that circulated tailored perfusate, providing oxygen and nutrients. The pressure and flow of the system were recorded, and blood gas analysis and laboratory tests of perfusate and bile were examined to analyze the function of the diseased livers. Liver tissues before and after NMP were collected for histological analysis. RESULTS: Experiments showed that the system maintained the diseased livers in a physiological state, ensuring stable hemodynamics and a suitable partial pressure of oxygen and carbon dioxide. The results of blood gas analysis and laboratory tests demonstrated a restoration and sustenance of metabolism with minimal damage. Notably, a majority of the diseased livers exhibited bile production continuously, signifying their vivid functional integrity. The pathological characteristics remained stable before and after NMP. CONCLUSION: We successfully established the machine perfusion system tailored specifically for diseased human whole livers. Through the application of this system, we have developed a novel in vitro model that faithfully recapitulates the main features of human liver disease. This model holds immense promise as an advanced disease modeling platform, offering profound insights into liver diseases and potential implications for research and therapeutic development.

Maternal inulin supplementation ameliorates prenatal methamphetamine exposure-induced hepatotoxicity and restores gut microbiota in mouse offspring.

Prenatal exposure to methamphetamine (METH) is an issue of global concern due to its adverse effects on offspring, particularly its impact on liver health, an area still not fully understood. Inulin, a recognized prebiotic, is thought to potentially ameliorate these developmental disorders and toxic injuries in progeny. To investigate the effects of prenatal METH exposure on the liver and the role of gut microbiota, we established a murine model, the subjects of which were exposed to METH prenatally and subsequently treated with inulin. Our findings indicate that prenatal METH exposure causes liver damage in offspring, as evidenced by a decreased liver index, histopathological changes, diminished glycogen synthesis, hepatic dysfunction, and alterations in mRNA profiles. Furthermore, it impairs the antioxidant system and induces oxidative stress, possibly due to changes in cecal microbiota and dysregulation of bile acid homeostasis. However, maternal inulin supplementation appears to restore the gut microbiota in offspring and mitigate the hepatotoxic effects induced by prenatal METH exposure. Our study provides definitive evidence of METH's transgenerational hepatotoxicity and suggests that maternal inulin supplementation could be an effective preventive strategy.

The gut microbiota contributes to methamphetamine-induced reproductive toxicity in male mice.

Methamphetamine (METH) is a psychostimulant drug belonging to the amphetamine-type stimulant class, known to exert male reproductive toxicity. Recent studies suggest that METH can disrupt the gut microbiota. Furthermore, the gut-testis axis concept has gained attention due to the potential link between gut microbiome dysfunction and reproductive health. Nonetheless, the role of the gut microbiota in mediating the impact of METH on male reproductive toxicity remains unclear. In this study, we employed a mouse model exposed to escalating doses of METH to assess sperm quality, testicular pathology, and reproductive hormone levels. The fecal microbiota transplantation method was employed to investigate the effect of gut microbiota on male reproductive toxicity. Transcriptomic, metabolomic, and microbiological analyses were conducted to explore the damage mechanism to the male reproductive system caused by METH. We found that METH exposure led to hormonal disorders, decreased sperm quality, and changes in the gut microbiota and testicular metabolome in mice. Testicular RNA sequencing revealed enrichment of several Gene Ontology terms associated with reproductive processes, as well as PI3K-Akt signaling pathways. FMT conveyed similar reproductive damage from METH-treated mice to healthy recipient mice. The aforementioned findings suggest that the gut microbiota plays a substantial role in facilitating the reproductive toxicity caused by METH, thereby highlighting a prospective avenue for therapeutic intervention in the context of METH-induced infertility.

A tailored ratiometric fluorescent sensor based on CdTe and MgF2 quantum dots for trace N-ethylpentylone detection.

The development of low-cost and highly sensitive ratiometric fluorescence sensor, CdTe@MIPs/MgF2, for N-Ethylpentylone (NEP) detection in wastewater samples is described. In this system, CdTe@MIPs (λex = 370, λem = 570) are employed as the receptor and response unit for NEP, with MgF2 (λex = 370, λem = 470) as the reference signal to enhance stability. Under optimal conditions, the sensor shows fluorescent quenching response at 570 nm to NEP in linear range of 2-200 nM, with LOD of 0.6 nM. The sensor also demonstrates significant selectivity for NEP over other analogues and interferents, making it ideal for practical applications in wastewater analysis. This approach is potentially more cost-effective and sensitive than conventional mass spectrometry in detecting abused substances in sewage. Additionally, the MgF2 fluorescent nano-material was first-ever developed and investigated, which may be significant in future research.

Spatially confined dual-emission nanoprobes assembled from silicon nanoparticles and gold nanoclusters for ratiometric biosensing.

Gold nanoclusters (AuNCs) possess weak intrinsic fluorescence, limiting their sensitivity in biosensing applications. This study addresses these limitations by developing a spatially confined dual-emission nanoprobe composed of silicon nanoparticles (SiNPs) and AuNCs. This amplified and stabilized fluorescence mechanism overcomes the limitations associated with using AuNCs alone, achieving superior sensitivity in the sensing platform. The nanoprobe was successfully employed for ratiometric detection of bleomycin (BLM) in serum samples, operating at an excitation wavelength of 365 nm, with emission wavelengths at 480 nm and 580 nm. The analytical performance of the system is distinguished by a linear detection range of 0-3.5 µM, an impressive limit of detection (LOD) of 35.27 nM, and exceptional recoveries ranging from 96.80 to 105.9%. This innovative approach significantly enhances the applicability and reliability of AuNC-based biosensing in complex biological media, highlighting its superior analytical capabilities.