The fidelity of transcription in human cells.

To determine the error rate of transcription in human cells, we analyzed the transcriptome of H1 human embryonic stem cells with a circle-sequencing approach that allows for high-fidelity sequencing of the transcriptome. These experiments identified approximately 100,000 errors distributed over every major RNA species in human cells. Our results indicate that different RNA species display different error rates, suggesting that human cells prioritize the fidelity of some RNAs over others. Cross-referencing the errors that we detected with various genetic and epigenetic features of the human genome revealed that the in vivo error rate in human cells changes along the length of a transcript and is further modified by genetic context, repetitive elements, epigenetic markers, and the speed of transcription. Our experiments further suggest that BRCA1, a DNA repair protein implicated in breast cancer, has a previously unknown role in the suppression of transcription errors. Finally, we analyzed the distribution of transcription errors in multiple tissues of a new mouse model and found that they occur preferentially in neurons, compared to other cell types. These observations lend additional weight to the idea that transcription errors play a key role in the progression of various neurological disorders, including Alzheimer's disease.

Recent Progress on Phase Engineering of Nanomaterials.

As a key structural parameter, phase depicts the arrangement of atoms in materials. Normally, a nanomaterial exists in its thermodynamically stable crystal phase. With the development of nanotechnology, nanomaterials with unconventional crystal phases, which rarely exist in their bulk counterparts, or amorphous phase have been prepared using carefully controlled reaction conditions. Together these methods are beginning to enable phase engineering of nanomaterials (PEN), i.e., the synthesis of nanomaterials with unconventional phases and the transformation between different phases, to obtain desired properties and functions. This Review summarizes the research progress in the field of PEN. First, we present representative strategies for the direct synthesis of unconventional phases and modulation of phase transformation in diverse kinds of nanomaterials. We cover the synthesis of nanomaterials ranging from metal nanostructures such as Au, Ag, Cu, Pd, and Ru, and their alloys; metal oxides, borides, and carbides; to transition metal dichalcogenides (TMDs) and 2D layered materials. We review synthesis and growth methods ranging from wet-chemical reduction and seed-mediated epitaxial growth to chemical vapor deposition (CVD), high pressure phase transformation, and electron and ion-beam irradiation. After that, we summarize the significant influence of phase on the various properties of unconventional-phase nanomaterials. We also discuss the potential applications of the developed unconventional-phase nanomaterials in different areas including catalysis, electrochemical energy storage (batteries and supercapacitors), solar cells, optoelectronics, and sensing. Finally, we discuss existing challenges and future research directions in PEN.

Biosynthesis of CuTe Nanorods with Large Molar Extinction Coefficients for NIR-II Photoacoustic Imaging.

Photoacoustic imaging (PAI) in the second near-infrared region (NIR-II), due to deeper tissue penetration and a lower background interference, has attracted widespread concern. However, the development of NIR-II nanoprobes with a large molar extinction coefficient and a high photothermal conversion efficiency (PCE) for PAI and photothermal therapy (PTT) is still a big challenge. In this work, the NIR-II CuTe nanorods (NRs) with large molar extinction coefficients ((1.31 ± 0.01) × 108 cm-1·M-1 at 808 nm, (7.00 ± 0.38) × 107 cm-1·M-1 at 1064 nm) and high PCEs (70% at 808 nm, 48% at 1064 nm) were synthesized by living Staphylococcus aureus (S. aureus) cells as biosynthesis factories. Due to the strong light-absorbing and high photothermal conversion ability, the in vitro PA signals of CuTe NRs were about 6 times that of indocyanine green (ICG) in both NIR-I and NIR-II. In addition, CuTe NRs could effectively inhibit tumor growth through PTT. This work provides a new strategy for developing NIR-II probes with large molar extinction coefficients and high PCEs for NIR-II PAI and PTT.

Biosynthesis of NIR-II Ag2Se Quantum Dots with Bacterial Catalase for Photoacoustic Imaging and Alleviating-Hypoxia Photothermal Therapy.

Developing the second near-infrared (NIR-II) photoacoustic (PA) agent is of great interest in bioimaging. Ag2Se quantum dots (QDs) are one kind of potential probe for applications in NIR-II photoacoustic imaging (PAI). However, the surfaces with excess anions of Ag2Se QDs, which increase the probability of nonradiative transitions of excitons benefiting PA imaging, are not conducive to binding electron donor ligands for potential biolabeling and imaging. In this study, Staphylococcus aureus (S. aureus) cells are driven for the biosynthesis of Ag2Se QDs with catalase (CAT). Biosynthesized Ag2Se (bio-Ag2Se-CAT) QDs are produced in Se-enriched environment of S. aureus and have a high Se-rich surface. The photothermal conversion efficiency of bio-Ag2Se-CAT QDs at 808 and 1064 nm is calculated as 75.3% and 51.7%, respectively. Additionally, the PA signal responsiveness of bio-Ag2Se-CAT QDs is ≈10 times that of the commercial PA contrast agent indocyanine green. In particular, the bacterial CAT is naturally attached to bio-Ag2Se-CAT QDs surface, which can effectively relieve tumor hypoxia. The bio-Ag2Se-CAT QDs can relieve heat-initiated oxidative stress while undergoing effective photothermal therapy (PTT). Such biosynthesis method of NIR-II bio-Ag2Se-CAT QDs opens a new avenue for developing multifunctional nanomaterials, showing great promise for PAI, hypoxia alleviation, and PTT.

Ligand-Assisted Phase Engineering of Nanomaterials.

ConspectusThe synthesis of monodisperse colloidal nanomaterials with well-defined structures is important for both fundamental research and practical application. To achieve it, wet-chemical methods with the usage of various ligands have been extensively explored to finely control the structure of nanomaterials. During the synthesis, ligands cap the surface and thus modulate the size, shape, and stability of nanomaterials in solvents. Besides these widely investigated roles of ligands, it has been recently discovered that ligands can affect the phase of nanomaterials, i.e., their atomic arrangement, providing an effective strategy to realize the phase engineering of nanomaterials (PEN) by selecting appropriate ligands. Nanomaterials normally exist in the phases that are thermodynamically stable in their bulk states. Previous studies have shown that under high temperature or high pressure, nanomaterials can exist in unconventional phases which are unattainable in the bulks. Importantly, nanomaterials with unconventional phases exhibit unique properties and functions different from conventional-phase ones. Consequently, it is feasible to utilize the PEN to tune the physicochemical properties and application performance of nanomaterials. During wet-chemical synthesis, ligands binding to the surface of nanomaterials can modify their surface energy, which could significantly affect the Gibbs free energy of nanomaterials and thus determine the stability of different phases, making it possible to obtain nanomaterials with unconventional phases at mild reaction conditions. For instance, a series of Au nanomaterials with unconventional hexagonal phases have been prepared with the assistance of oleylamine. Therefore, the rational design and selection of different ligands and deep understanding of their effect on the phase of nanomaterials would significantly accelerate the development of PEN and the discovery of novel functional nanomaterials for diverse applications.In this Account, we briefly summarize the recent progress in ligand-assisted PEN, elaborating the important roles of different ligands in the direct synthesis of nanomaterials with unconventional crystal phases and amorphous phase as well as the phase transformation of nanomaterials. We first introduce the background of this research topic, highlighting the concept of PEN and why ligands can modulate the phase of nanomaterials. Then we discuss the usage of four kinds of ligands, i.e., amines, fatty acids, sulfur-containing ligands, and phosphorus-containing ligands, in phase engineering of different nanomaterials, especially metal, metal chalcogenide, and metal oxide nanomaterials. Finally, we provide our personal views of the challenges and future promising research directions in this exciting field.

AlphaLISA-Based Immunoassay for Detection of Troponin T in Serum of Patients with Acute Myocardial Infarction.

Survival and prognosis of patients with acute myocardial infarction (AMI) are highly dependent on rapid and accurate diagnosis of myocardial damage. Troponin T is the primary diagnostic biomarker and is widely used in clinical practice. Amplified luminescent proximity homogeneous assay (AlphaLISA) may provide a solution to rapidly detect a small amount of analyte through molecular interactions between special luminescent donor beads and acceptor bead. Here, a double-antibody sandwich assay was introduced into AlphaLISA for rapid detection for early diagnosis of AMI and disease staging evaluation. The performance of the assay was evaluated. The study found that the cTnT assay has a linear range of 48.66 to 20,000 ng/L with a limit of detection of 48.66 ng/L. In addition, the assay showed no cross-reactivity with other classic biomarkers of myocardial infarction and was highly reproducible with intra- and inter-batch coefficients of variation of less than 10%, notably, only 3 min was taken, which is particularly suitable for clinical diagnosis. These results suggest that our method can be conveniently applied in the clinic to determine the severity of the patient's condition.

Multiparametric MRI-based fusion radiomics for predicting telomerase reverse transcriptase (TERT) promoter mutations and progression-free survival in glioblastoma: a multicentre study.

PURPOSE: This study evaluated the performance of multiparametric magnetic resonance imaging (MRI)-based fusion radiomics models (MMFRs) to predict telomerase reverse transcriptase (TERT) promoter mutation status and progression-free survival (PFS) in glioblastoma patients. METHODS: We retrospectively analysed 208 glioblastoma patients from two hospitals. Quantitative imaging features were extracted from each patient's T1-weighted, T1-weighted contrast-enhanced, and T2-weighted preoperative images. Using a coarse-to-fine feature selection strategy, four radiomics signature models were constructed based on the three MRI sequences and their combination for TERT promoter mutation status and PFS; model performance was subsequently evaluated. Subgroup analyses were performed by the radiomics signature of TERT promoter mutation status and PFS to distinguish patients who could benefit from prolonged temozolomide chemotherapy cycles. RESULTS: TERT promoter mutation status was best predicted by MMFR, with an area under the curve (AUC) of 0.816 and 0.812 for the training and internal validation sets, respectively. The external test set also achieved stable and optimal prediction results (AUC, 0.823). MMFR better predicted patient PFS compared with the single-sequence radiomics signature in the test set (C-index, 0.643 vs 0.561 vs 0.620 vs 0.628). Subgroup analyses showed that more than six cycles of postoperative temozolomide chemotherapy were associated with improved PFS for patients in class 2 (high TERT promoter mutation and high survival rates; HR, 0.222; 95% CI, 0.054 - 0.923; p = 0.025). CONCLUSION: MMFR is an effective method to predict TERT promoter mutations and PFS in patients with glioblastoma. Moreover, subgroup analysis could differentiate patients who may benefit from prolonged TMZ chemotherapy cycles.

Fractionation of metals in soil for strawberry cultivation: Effect on metal migration in food chain and application in risk assessment.

Although trace metals in strawberry production system have attracted growing attention, little is known about metal fractionation in soil for strawberry cultivation. We hypothesized that the metal fractions in soil influenced by strawberry production had significant effect on food chain transport of metals and their risk in soil. Here, samples of strawberries and soil were gathered in the Yangtze River Delta, China to verify the hypothesis. Results showed that the acid-soluble Cr, Cd, and Ni in soil for strawberry cultivation were 21.5%-88.3% higher than those in open field soil, which enhanced uptake and bioaccessible levels of these metals in strawberries. Overall, the ecological, mobility, and health risks of Pb, Zn, Ni, and Cu in soil were at a low level. However, the ecological risk of bioavailable Cd, mobility risk of Cd, and cancer risk of bioavailable Cr in over 70% of the soil samples were at moderate, high, and acceptable levels, respectively. Since the increased acid-soluble Cr and Ni in soil were related to soil acidification induced by strawberry production, nitrogen fertilizer application should be optimized to prevent soil acidification and reduce transfer of Cr and Ni. Additionally, as Cd and organic matter accumulated in soil, the acid-soluble Cd and the ecological and mobility risks of Cd in soil were enhanced. To decrease transfer and risk of Cd in soil, organic fertilizer application should be optimized to mitigate Cd accumulation, alter organic matter composition, and subsequently promote the transformation of bioavailable Cd into residual Cd in soil.

Joint effects of heat-humidity compound events on drowning mortality in Southern China.

BACKGROUND: Several previous studies have examined the association of ambient temperature with drowning. However, no study has investigated the effects of heat-humidity compound events on drowning mortality. METHODS: The drowning mortality data and meteorological data during the five hottest months (May to September) were collected from 46 cities in Southern China (2013-2018 in Guangdong, Hunan and Zhejiang provinces). Distributed lag non-linear model was first conducted to examine the association between heat-humidity compound events and drowning mortality at city level. Then, meta-analysis was employed to pool the city-specific exposure-response associations. Finally, we analysed the additive interaction of heat and humidity on drowning mortality. RESULTS: Compared with wet-non-hot days, dry-hot days had greater effects (excess rate (ER)=32.34%, 95% CI: 24.64 to 40.50) on drowning mortality than wet-hot days (ER=14.38%, 95%CI: 6.80 to 22.50). During dry-hot days, males (ER=42.40%, 95% CI: 31.92 to 53.72), adolescents aged 0-14 years (ER=45.00%, 95% CI: 21.98 to 72.35) and urban city (ER=36.91%, 95% CI: 23.87 to 51.32) showed higher drowning mortality risk than their counterparts. For wet-hot days, males, adolescents and urban city had higher ERs than their counterparts. Attributable fraction (AF) of drowning attributed to dry-hot days was 23.83% (95% CI: 21.67 to 26.99) which was significantly higher than that for wet-hot days (11.32%, 95% CI: 9.64 to 13.48%). We also observed that high temperature and low humidity had an additive interaction on drowning mortality. CONCLUSION: We found that dry-hot days had greater drowning mortality risk and burden than wet-hot days, and high temperature and low humidity might have synergy on drowning mortality.

High-performance electrosorption of lanthanum ion by Mn3O4-loaded phosphorus-doped porous carbon electrodes via capacitive deionization.

Transition-metal-oxide@heteroatom doped porous carbon composites have attracted considerable research interest because of their large theoretical adsorption capacity, excellent electrical conductivity and well-developed pore structure. Herein, Mn3O4-loaded phosphorus-doped porous carbon composites (Mn3O4@PC-900) were designed and fabricated for the electrosorption of La3+ in aqueous solutions. Due to the synergistic effect between Mn3O4 and PC-900, and the active sites provided by Mn-O-Mn, C/PO, C-P-O and Mn-OH, Mn3O4@PC-900 exhibits high electrosorption performance. The electrosorption value of Mn3O4@PC-900 was 45.34% higher than that of PC-900, reaching 93.02 mg g-1. Moreover, the adsorption selectivity reached 87.93% and 89.27% in La3+/Ca2+ and La3+/Na+ coexistence system, respectively. After 15 adsorption-desorption cycles, its adsorption capacity and retention rate were 50.34 mg g-1 and 54.12%, respectively. The electrosorption process is that La3+ first accesses the pores of Mn3O4@PC-900 to generate an electric double layer (EDL), and then undergoes further Faradaic reaction with Mn3O4 and phosphorus-containing functional groups through intercalation, surface adsorption and complexation. This work is hoped to offer a new idea for exploring transition-metal-oxide @ heteroatom doped porous carbon composites for separation and recovery of rare earth elements (REEs) by capacitive deionization.

Assessment of rainfall-derived inflow and infiltration in sewer systems with machine learning approaches.

Rainfall-derived inflow/infiltration (RDII) modelling during heavy rainfall events is essential for sewer flow management. In this study, two machine learning algorithms, random forest (RF) and long short-term memory (LSTM), were developed for sewer flow prediction and RDII estimation based on field monitoring data. The study implemented feature engineering for extracting physically significant features in sewer flow modelling and investigated the importance of the relevant features. The results from two case studies indicated the superior capability of machine learning models in RDII estimation in the combined and separated sewer systems, and LSTM model outperformed the two models. Compared to traditional methods, machine learning models were capable of simulating the temporal variation in RDII processes and improved prediction accuracy for peak flows and RDII volumes in storm events.

A dynamic one-dimensional model for simulating unsteady air-water stratified flow in sewer pipes.

Ventilation is paramount in sanitary and stormwater sewer systems to mitigate odor problems and avert pressure surges. Existing numerical models have constraints in practical applications in actual sewer systems due to insufficient airflow modeling or suitability only for steady-state conditions. This research endeavors to formulate a mathematical model capable of accurately simulating various operational conditions of sewer systems under the natural ventilation condition. The dynamic water flow is modeled using a shock-capturing MacCormack scheme. The dynamic airflow model amalgamates energy and momentum equations, circumventing laborious pressure iteration computations. This model utilizes friction coefficients at interfaces to enhance the description of the momentum exchange in the airflow and provide a logical explanation for air pressure. A systematic analysis indicates that this model can be easily adapted to include complex boundary conditions, facilitating its use for modeling airflow in real sewer networks. Furthermore, this research uncovers a direct correlation between the air-to-water flow rate ratio and the filling ratio under natural ventilation conditions, and an empirical formula encapsulating this relationship is derived. This finding offers insights for practical engineering applications.

Numerical study on hydraulic characteristics of rotating stepped dropshafts in deep urban tunnels.

As an important component of the deep tunnel drainage system for dealing with urban waterlogging, the rotating stepped dropshaft has been proposed due to its small air entrainment. However, the hydraulic characteristics inside the shaft still need to be fully studied. In this study, the flow patterns, water velocity, and pressure in the rotating stepped dropshaft under different flow rates and geometric parameters were studied using a three-dimensional numerical model. The results show that increasing the central angle of the step and reducing the step height can both reduce the terminal velocity. A theoretical formula for predicting the terminal velocity was established and well validated. The connection between the shaft and the outlet pipe poses a severe threat to the structural safety due to alternating positive and negative pressures. Wall-attached swirling flow generates a circular high-pressure zone at the bottom of the dropshaft and the larger the flow rate, the greater the pressure gradient at the center of the bottom. By using the momentum theorem and considering the impact pressure range of the swirling flow, the shaft bottom pressure can be predicted reasonably well.

Peritumoral Radiomics for Identification of Telomerase Reverse Transcriptase Promoter Mutation in Patients With Glioblastoma Based on Preoperative MRI.

Purpose: To evaluate the value of intra- and peritumoral deep learning (DL) features based on multi-parametric magnetic resonance imaging (MRI) for identifying telomerase reverse transcriptase (TERT) promoter mutation in glioblastoma (GBM). Methods: In this study, we included 229 patients with GBM who underwent preoperative MRI in two hospitals between November 2016 and September 2022. We used four 2D Convolutional Neural Networks (GoogLeNet, DenseNet121, VGG16, and MobileNetV3-Large) to extract intra- and peritumoral DL features. The Mann-Whitney U test, Pearson correlation analysis, least absolute shrinkage and selection operator, and logistic regression analysis were used for feature selection and construction of DL radiomics (DLR) signatures in different regions. These multi-parametric and multi-region signatures were combined to identify TERT promoter mutation. The area under the receiver operating characteristic curve (AUC) was used to evaluate the effects of the signatures. Results: The signatures based on the DL features from the peritumoral regions with expansion distances of 2 mm, 8 mm, and 10 mm using the GoogLeNet architecture correlated with the optimal AUC values (test set: .823, .753, and .768) in the T2-weighted, T1-weighted contrast-enhanced, and T1-weighted images. Using the stacking fusion method, DLR with multi-parameter and multi-region fusion achieved the best discrimination with AUC values of .948 and .902 in the training and test sets, respectively. Conclusions: The radiomics model based on the fusion of multi-parameter MRI intra- and peritumoral DLR signatures may help to identify TERT promoter mutation in patients with GBM.

Clinical Assessment of Magnetic Resonance Spectroscopy and Diffusion-Weighted Imaging in Diffuse Glioma: Insights Into Histological Grading and IDH Classification.

PURPOSE: To assess the diagnostic utility of clinical magnetic resonance spectroscopy (MRS) and diffusion-weighted imaging (DWI) in distinguishing between histological grading and isocitrate dehydrogenase (IDH) classification in adult diffuse gliomas. METHODS: A retrospective analysis was conducted on 247 patients diagnosed with adult diffuse glioma. Experienced radiologists evaluated DWI and MRS images. The Kruskal-Wallis test examined differences in DWI and MRS-related parameters across histological grades, while the Mann-Whitney U test assessed molecular classification. Receiver Operating Characteristic (ROC) curves evaluated parameter effectiveness. Survival curves, stratified by histological grade and IDH classification, were constructed using the Kaplan-Meier test. RESULTS: The cohort comprised 141 males and 106 females, with ages ranging from 19 to 85 years. The Kruskal-Wallis test revealed significant differences in ADC mean, Cho/NAA, and Cho/Cr concerning glioma histological grade (P < .01). Subsequent application of Dunn's test showed significant differences in ADC mean among each histological grade (P < .01). Notably, Cho/NAA exhibited a marked distinction between grade 2 and grade 3/4 gliomas (P < .01). The Mann-Whitney U test indicated that only ADC mean showed statistical significance for IDH molecular classification (P < .01). ROC curves were constructed to demonstrate the effectiveness of the specified parameters. Survival curves were also delineated to portray survival outcomes categorized by histological grade and IDH classification. Conclusions: Clinical MRS demonstrates efficacy in glioma histological grading but faces challenges in IDH classification. Clinical DWI's ADC mean parameter shows significant distinctions in both histological grade and IDH classification.

A Collaborative Approach for Metal Pollution Assessment in Production System of Plastic-Shed Vegetables Near Industrial Areas.

A collaborative assessment approach, including impact index of comprehensive quality (IICQ), food pollution index (FPI), and single factor pollution index (PI), was used to simultaneously select priority metal pollutants and assess metal contamination status in the plastic-shed soil (PSS)-vegetable system of the industrial towns situated in the Yangtze River Delta, China. Overall, significant Cr increment as well as Cd and Cu pollution in PSS existed, which was related to anthropogenic activities, especially industrial wastewater irrigation. The evaluation using PI and FPI demonstrated that priority metal pollutants were Cu and Cd in PSS while Cr and Cd in vegetables. Additionally, the estimation using IICQ method revealed that 23.3% and 13.3% of the sampling sites were sub-moderately and heavily contaminated by metals, respectively. These sites especially with heavy pollution need priority pollution management. These data will be beneficial to metal pollution control in PSS-vegetable system around industrial areas.

Feasibility of using Vis-NIR spectroscopy and PXRF spectrometry to estimate regional soil cadmium concentration.

Conventionally, soil cadmium (Cd) measurements in the laboratory are expensive and time-consuming, involving complex processes of sample preparation and chemical analysis. This study aimed to identify the feasibility of using sensor data of visible near-infrared reflectance (Vis-NIR) spectroscopy and portable X-ray fluorescence spectrometry (PXRF) to estimate regional soil Cd concentration in a time- and cost-saving manner. The sensor data of Vis-NIR and PXRF, and Cd concentrations of 128 surface soils from Yunnan Province, China, were measured. Outer-product analysis (OPA) was used for synthesizing the sensor data and Granger-Ramanathan averaging (GRA) was applied to fuse the model results. Artificial neural network (ANN) models were built using Vis-NIR data, PXRF data, and OPA data, respectively. Results showed that: (1) ANN model based on PXRF data performed better than that based on Vis-NIR data for soil Cd estimation; (2) Fusion methods of both OPA and GRA had higher predictive power (R2) = 0.89, ratios of performance to interquartile range (RPIQ) = 4.14, and lower root mean squared error (RMSE) = 0.06, in ANN model based on OPA fusion; R2 = 0.88, RMSE = 0.06, and RPIQ = 3.53 in GRA model) than those based on either Vis-NIR data or PXRF data. In conclusion, there exists a great potential for the combination of OPA fusion and ANN to estimate soil Cd concentration rapidly and accurately.

Band Gap Engineering Improves Three-Photon Luminescence of Quantum Dots for Deep Brain Imaging.

Three-photon fluorescence microscopy (3PFM) has emerged as a promising tool in monitoring the structures and functions of the brain. Compared to the various imaging technologies, 3PFM enables a deep-penetrating depth attributed to tighter excitation confinement and suppressed photon scattering. However, the shortage of three-photon probes with a large absorption cross section (σ3) substantially limits its uses. Herein, CdSe/CdS/ZnS quantum dots (QDs) with enhanced 3PF performance were synthesized via the band gap engineering strategy. The introduction of a CdS interlayer with optimized thickness between the emitting CdSe core and the ZnS shell significantly enhanced the 3P absorption cross section of QDs, which originated from the intrinsic piezoelectric polarization effect and the change of the core/shell structure from type-I to quasi-type-II. In addition, the outer ZnS layer compensated the poor electronic passivation of CdS, providing a high level of passivation for the improvement of quantum yield as well as the 3P action cross section of QDs. Under the excitation of a 1600 nm femtosecond laser, PEGylated CdSe/CdS/ZnS QDs were used for in vivo 3PFM imaging of cerebral vessels with high resolution. A tiny capillary with a diameter of 0.8 µm could be resolved at the imaging depth of 1550 µm in a mouse brain with an opened skull. A penetration depth of 850 µm beneath the skull was also achieved using a mouse model with an intact skull.

Activatable Lanthanide Nanoprobes with Dye-Sensitized Second Near-Infrared Luminescence for in Vivo Inflammation Imaging.

Lanthanide nanoparticles exhibit unique photophysical properties and thus emerge as promising second near-infrared (NIR-II) optical agents. However, the limited luminescence brightness hampers their construction of activatable NIR-II probes. Herein, we report the synthesis of dye-sensitized lanthanide nanoprobes (NaGdF4:Nd/ICG; indocyanine green (ICG)) and their further development for in vivo activatable imaging of hypochlorite (ClO-). Dye sensitization using ICG not only shifts the optimal doping concentration of Nd3+ from 5 to 20 mol % but also leads to a 5-fold NIR-II enhancement relative to the ICG-free counterpart. Mechanistic studies reveal that such a luminescence enhancement of NaGdF4:Nd at high Nd3+ concentration is ascribed to an alleviated cross-relaxation effect due to the broad absorption of ICG and faster energy transfer process. Taking advantage of dye oxidation, the nanoprobes enable activatable NIR-II imaging of hypochlorous acid (ClO-) in a drug-induced lymphatic inflammation mouse model. This work thus provides a simple, yet effective luminescence enhancement strategy for constructing lanthanide nanoprobes at higher activator doping concentration toward activatable NIR-II molecular imaging.

Establishment of 11-dehydro-thromboxane B2 time-resolved immunoassay and application in membranous nephropathy.

BACKGROUND: 11-Dehydro-thromboxane B2 (11-dehydro-TXB2) is the final stable metabolite of thromboxane A2 (TXA2) and is involved in thrombus formation. Patients with membranous nephropathy (MN) are prone to thromboembolism events. METHODS: Time-resolved fluorescence immunoassay (TRFIA) for 11-dehydro-TXB2 was established by indirect competitive method. The coated 11-dehydro-TXB2-BSA conjugate was used to bind the 11-dehydro-TXB2 antibody competitively to the 11-dehydro-TXB2 antigen in the samples, followed by Eu3+-labeled goat anti-mouse IgG antibody, to detect 11-dehydro-TXB2. This study measured 11-dehydro-TXB2 concentrations in serum samples from healthy individuals and patients with MN. RESULTS: The linear range of TRFIA was 16.38-2000 pg/mL, the sensitivity was 4.70 pg/mL, the average coefficients of variation from intra-assay and inter-assay were 3.50% and 4.95%, respectively, and the recovery was 99.38%. The serum level of 11-dehydro-TXB2 in patients with MN was significantly higher than that in healthy subjects (P < 0.05). The serum 11-dehydro-TXB2 concentration detected by TRFIA was highly consistent with that by ELISA (ρ = 0.900). DISCUSSION: This study successfully established a new highly sensitive method for the detection of 11-dehydro-TXB2 in serum. 11-Dehydro-TXB2 has great potential in evaluating the risk of thromboembolic events in patients with MN and is expected to be applied to other thromboembolic-related diseases.