Dual-emissive europium doped UiO-66-based ratiometric light-up biosensor for highly sensitive detection of histidinemia biomarker.

BACKGROUND: Lanthanide metal-organic frameworks (Ln-MOFs) are a kind of emerging crystalline porous materials with high fluorescence and easy-to-tunable properties, making them ideal for sensing applications. However, current Ln-MOFs based fluorescent probes are primarily single-emissive or fluorescence-quenched, which greatly limited the detection performances such as sensitivity, accuracy and repeatability, thereby hindering their applications in efficient target monitoring and related disease diagnosis. To address these issues, the reasonable design of Ln-MOFs equipped with dual fluorescence emissions and light-up mode is urgently needed for a high-performance biosensor. RESULTS: A dual-emissive europium doped UiO-66 (Eu@UiO-66-NH2-PMA)-based ratiometric fluorescent biosensing platform was constructed for highly sensitive and selective detection of the histidinemia biomarker-histidine (His). Eu@UiO-66-NH2-PMA (pyromellitic acid abbreviated as PMA) was synthesized utilizing a post-synthetic modification method via coordination interactions between the free -COOH of UiO-66-NH2-PMA and Eu3+, which exhibited characteristic peaks of broad ligand emission and sharp Eu3+ emissions simultaneously. Considering that Cu2+ had the excellent fluorescence quenching ability toward Eu3+ and superior affinity with His, it was deliberately introduced into the Eu@UiO-66-NH2-PMA, acting as active sites for target His responsiveness. The Eu@UiO-66-NH2-PMA/Cu2+/His ternary competition system demonstrated a low detection limit of 74 nM, excellent selectivity and good anti-interference capability that allowed for sensitive analysis of His levels in milk and human serum samples. SIGNIFICANCE: Attributing to the superior luminescent properties, good stability and self-calibration capability of Eu@UiO-66-NH2-PMA, the developed ratiometric light-up sensing platform enabled sensitive, selective and credible analysis of His in complex practical samples, which might provide an available tool for food nutrition guideline and diagnostic applications of His related diseases.

Quantum-Memory-Enhanced Preparation of Nonlocal Graph States.

Graph states are an important class of multipartite entangled states. Previous experimental generation of graph states and in particular the Greenberger-Horne-Zeilinger (GHZ) states in linear optics quantum information schemes is subjected to an exponential decay in efficiency versus the system size, which limits its large-scale applications in quantum networks. Here, we demonstrate an efficient scheme to prepare graph states with only a polynomial overhead using long-lived atomic quantum memories. We generate atom-photon entangled states in two atomic ensembles asynchronously, retrieve the stored atomic excitations only when both sides succeed, and further project them into a four-photon GHZ state. We measure the fidelity of this GHZ state and further demonstrate its applications in the violation of Bell-type inequalities and in quantum cryptography. Our work demonstrates the prospect of efficient generation of multipartite entangled states in large-scale distributed systems with applications in quantum information processing and metrology.

Predictive performance of reported vancomycin population pharmacokinetic model in patients with different renal function status, especially those with augmented renal clearance.

BACKGROUND: There is a significant correlation between augmented renal clearance (ARC) and lower serum trough concentrations of vancomycin (VCM) during therapy. There is a need to evaluate the predictive performance of the population pharmacokinetic (PPK) model used for individual calculation of dosage regimens in ARC patients. OBJECTIVE: Our study aimed to estimate the predictive performance differences of the reported VCM PPK software JPKD-vancomycin and SmartDose in patients with varying renal function status, especially those with ARC. METHODS: Patients receiving VCM treatment from May 2014 to December 2019 were enrolled, and divided into the ARC group, the normal renal function (NRF) group, and the impaired renal function (IRF) group. VCM dosage, trough concentration, area under the curve (AUC) and pharmacokinetic parameters were compared among the three groups. The predictive performance of PPK software was expressed using absolute prediction error (APE), sensitivity, specificity, and regression coefficient (r2) of linear regression analysis between the measured VCM trough concentration and the predicted trough concentration. RESULTS: A total of 388 patients were included: 86 patients in the ARC group, 241 patients in the NRF group, and 61 patients in the IRF group. The daily dose of the adjusted regimen in the ARC group was higher than in the NRF group, but the trough concentration was significantly lower than in the NRF group (2.8±0.6 g vs 1.9±0.6 g, p<0.001; 10.5±5.1 mg/L vs 12.9±6.8 mg/L, p=0.030). The percentage of trough concentrations lower than 10 mg/L was 84.9% in the ARC group. Compared with the APE of the initial dosage regimen, the APE of the adjusted regimen calculated by JPKD was lower in the ARC group (p=0.041) and the NRF group (p＜0.001). Specificity of JPKD and SmartDose in the ARC group was higher than in the NRF group (p<0.001; p<0.001). According to the linear regression analysis, the coefficients of determination (r2) were all >0.6 for the initial regimen and adjusted regimen of VCM in the ARC and NRF groups, and the r2 of the adjusted regimen of JPKD was >0.8 in the ARC and NRF groups. In the IRF group, 31.1% of patients had a change in serum creatinine (Scr) level of >50%. The r2 increased from 0.527 to 0.7347 in SmartDose and from 0.55 to 0.7802 in JPKD when using Scr at the sampling time. The ARC group showed a significant decrease in AUC (p<0.001) and an increase in clearance rate (p<0.001) when compared to the NRF group. CONCLUSION: ARC was significantly associated with subtherapeutic serum VCM concentration. The pharmacokinetic parameters of VCM were diverse in patients with different renal function status. The PPK model JPKD and SmartDose had a good predictive performance for predicting VCM trough concentrations of the ARC and NRF patients, especially using JPKD for prediction of the adjusted regimen. The change of Scr is a main factor affecting the accuracy of software prediction.

Vancomycin in neonatal sepsis: predictive performance of a Chinese neonatal population pharmacokinetic model and clinical efficacy evaluation.

BACKGROUND: In the neonatal population, individual calculation and adjustment of vancomycin (VCM) doses has been recommended based on population pharmacokinetics (PPK) methods. OBJECTIVE: Our previous study established a Chinese neonatal VCM PPK model. The main goal of this study was to evaluate the predictive performance of this PPK model for VCM trough concentration. METHODS: The data on neonatal severe infection patients treated with VCM were retrospectively collected. The predictive performance of this PPK model was expressed using mean prediction error (MPE), mean absolute prediction error (MAPE), sensitivity and specificity. Linear regression analysis was used to compare predicted and measured VCM concentrations. We drew the receiver operating characteristic (ROC) curve to evaluate the predictive efficacy of the ratio of area under the concentration-time curve over 24 hours to minimum inhibitory concentration (AUC0-24/MIC) and trough concentration for clinical efficacy. RESULTS: A total of 40 neonates with Gram-positive bacterial sepsis were included. After VCM treatment, 32 (80%) neonates were clinically cured. Eight cases were a clinical failure: the trough concentrations and AUC0-24 were lower than that of the clinical cure patients (8.70±4.30 vs 14.30±4.50 mg/L, p=0.003; 404.30±122.80 vs 515.40±131.70, p=0.037). The measured and predicted trough concentration were 11.16 (5.96, 16.53) mg/L and 10.13 (6.61, 15.73) mg/L, respectively. The MPE and MAPE were 4.62% and 13.26% (5.30%, 25.88%), respectively. The proportion of MAPE <30% in the adjusted regimen was higher than the initial regimen (89.66% vs 65.00%, p=0.039). Predictions of sensitivity and specificity by this PPK model were 88.24% and 94.29%, respectively. The coefficients of determination of linear regression analysis were 0.9171 and 0.9009 for the initial and adjusted regimen, respectively. The AUC0-24 was correlated with the trough concentration (r=0.587, p<0.001). The ROC curve indicated that the optimal cut-off points for predicting clinical efficacy were AUC0-24/MIC >425.47 and trough concentration >9.45 mg/L. CONCLUSION: This PPK model has good predictive performance in Chinese neonatal patients. Both AUC0-24/MIC and trough concentration can predict the clinical efficacy of antibacterial treatment.

Spinal CCK contributes to somatic hyperalgesia induced by orofacial inflammation combined with stress in adult female rats.

In some chronic primary pain conditions such as temporomandibular disorder (TMD) and fibromyalgia syndrome (FMS), mild or chronic stress enhances pain. TMD and FMS often occur together, but the underlying mechanisms are unclear. The purpose of this study was to investigate the role of cholecystokinin (CCK) in the spinal cord in somatic hyperalgesia induced by orofacial inflammation combined with stress. Somatic hyperalgesia was detected by the thermal withdrawal latency and mechanical withdrawal threshold. The expression of CCK1 receptors, CCK2 receptors, ERK1/2 and p-ERK1/2 in the spinal cord was examined by Western blot. After the stimulation of orofacial inflammation combined with 3 day forced swim, the expression of CCK2 receptors and p-ERK1/2 protein in the L4-L5 spinal dorsal horn increased significantly, while the expression of CCK1 receptors and ERK1/2 protein remained unchanged. Intrathecal injection of the CCK2 receptor antagonist YM-022 or mitogen-activated protein kinase (MAPK) kinase (MEK) inhibitor PD98059 blocked somatic hyperalgesia induced by orofacial inflammation combined with stress. Intrathecal administration of the MEK inhibitor blocked somatic sensitization caused by the CCK receptor agonist CCK8. The CCK2 receptor antagonist YM-022 significantly reduced the expression of p-ERK1/2. These data indicate that upregulation of CCK2 receptors through the MAPK pathway contributes to somatic hyperalgesia in this comorbid pain model. Thus, CCK2 receptors and MAPK pathway may be potential targets for the treatment of TMD comorbid with FMS.

Boronate carbon nanoparticles featuring efficient FRET for activatable two-photon fluorescence imaging of sialic acid surface-abundant tumor cells.

Two-photon carbon-based nanoprobes hold great potential for biomedical applications as a result of their advantages of low fluorescence background, deep tissue imaging penetration and enhanced spatial resolution. However, the development of an activatable two-photon fluorescence carbon-based nanoprobe that simultaneously has the ability to target desired organs or cells is highly desired but remained a largely unsolved challenge. Herein, we developed boronate affinity BCNP@MnO2 nanocomposites, constructed by one step in situ growth of MnO2 nanosheets on the surface of aminophenylboronic acid-functionalized CNPs (BCNPs) via a redox reaction, which can feature efficient fluorescence energy transfer quenching to the BCNPs, allowing for tumor-specific affinity recognition and two-photon fluorescence activation imaging. By utilizing the inherent two-photon optical properties and sialic acid (SA) specific targeting ability of the BCNPs, good biocompatibility of the nanocomposites as well as highly sensitive and selective responses of MnO2 nanosheets towards GSH, the developed nanocomposites have demonstrated specific two-photon fluorescence activation imaging in target cancer cells and nude mouse tissues. Therefore, our proposed novel strategy could be used for monitoring GSH-triggered two-photon fluorescence activation events in SA-overexpressed cancer cells and has promising applications in both biological exploration and clinical diagnosis.

A Regression Model to Predict Augmented Renal Clearance in Critically Ill Obstetric Patients and Effects on Vancomycin Treatment.

Background: Augmented renal clearance (ARC) risk factors and effects on vancomycin (VCM) of obstetric patients were possibly different from other populations based on pathophysiological characteristics. Our study was to establish a regression model for prediction of ARC and analyze the effects of ARC on VCM treatment in critically ill obstetric patients. Methods: We retrospectively included 427 patients, grouped into ARC and non-ARC patients. Logistic regression analysis was used to analyze the factors related to ARC. Receiver operating characteristic (ROC) curve was drawn to evaluate the predictive value of the model for ARC. Patients who received VCM therapy were collected. The published VCM population pharmacokinetic (PPK) model was used to calculate pharmacokinetic parameters. A linear regression analysis was made between the predicted and measured concentrations. Results: Of the 427 patients, ARC was present in 201 patients (47.1%). The independent risk factors of ARC were heavier, greater gestational age, higher albumin level, fewer caesarean section, severe preeclampsia and vasoactive drug; more infection, hypertriglyceridemia and acute pancreatitis. We established the above nine-variable prediction regression model and calculated the predicted probability. ROC curve showed that the predicted probability of combined weight, albumin and gestational age had better sensitivity (70.0%) and specificity (89.8%) as well as the maximal area under the curve (AUC, AUC = 0.863). 41 cases received VCM; 21 cases (51.2%) had ARC. The initial trough concentration in ARC patients was lower than in non-ARC patients (7.9 ± 3.2 mg/L vs 9.5 ± 3.3 mg/L; p = 0.033). Comparing the predicted trough concentration of two published VCM PPK models with the measured trough concentration, correlation coefficients (r) were all more than 0.8 in the ARC group and non-ARC group. AUC was significantly decreased in the ARC group (p = 0.003; p = 0.013), and clearance (CL) increased in the ARC group (p < 0.001; p = 0.008) when compared with the non-ARC group. Conclusion: ARC is a common state in critically ill obstetric patients. The regression model of nine variables had high predictive value for predicting ARC. The published VCM PPK models had good predictive performance for predicting trough concentrations of obstetric patients. Pharmacokinetic parameters of VCM are different in ARC obstetric patients, which results in enhanced VCM clearance and decreased trough concentration.

DNAzyme cascade circuits in highly integrated DNA nanomachines for sensitive microRNAs imaging in living cells.

DNA molecular probes have emerged as powerful tools for fluorescence imaging of microRNAs (miRNAs) in living cells and thus elucidating functions and dynamics of miRNAs. In particular, the highly integrated DNA probes that can be able to address the robustness, sensitivity and consistency issues in a single assay system were highly desired but remained largely unsolved challenge. Herein, we reported for the first time that the development of the novel DNA nanomachines that split-DNAzyme motif was highly integrated in a single DNA triangular prism (DTP) reactor and can undergo target-activated DNAzyme catalytic cascade circuits, allowing amplified sensing and imaging of tumor-related microRNA-21 (miR-21) in living cells. The DNA nanomachines have shown dynamic responses for target miR-21 with excellent sensitivity and selectivity and demonstrated the potential for living cell imaging of miR-21. With the advantages of facile modular design and assembly, high biostability, low cytotoxicity and excellent cellular internalization, the highly integrated DNA nanomachines enabled accurate and effective monitoring of miR-21 expression levels in living cells. Therefore, our developed strategy may afford a reliable and robust nanoplatform for tumor diagnosis and for related biological research.

[Symbiotic bacteria facilitate algal growth and oil biosynthesis in Scenedesmus obliquus]. / å ±ç”ŸèŒä¿ƒè¿›æ–œç”Ÿæ 藻生长和油脂合成.

We isolated bacteria from the phycosphere of Scenedesmus obliques and sequenced 16S rDNAs to establish algae-bacterial co-culture systems. Further, we examined effects of the bacteria on algal growth, and parameters associated with physio-biochemical and oil-producing characteristics of S. obliquus. Seven bacterial strains were isolated, including Micrococcus (strains 1-1, 1-2 and 1-3), Pseudomonas sp. (strains 2-1 and 2-2), Exiguobacterium (strain-3) and Staphylococcus sp. (strain-4). Among them, two bacteria (strain 1-2 and strain 2-1) were characterized as the dominant growth-promoting bacterial strains, which significantly increased algal growth, pigment production, and oil enrichment. After eight days cultivation under microalgal-bacterial (strain 1-2) symbiotic systemat at an initial ratio of 1:10, biomass of S. obliquus was 4.27 g·L-1, about 46.0% higher than that of the control. The contents of chlorophyll a, chlorophyll b and carotenoids were increased by 12.1%, 16.7% and 25.0%, respectively. Oil content was increased by 14.0% and reached to 25.7%, and the oleic acid content was significantly higher than that of the control and up to 16.4%. When co-cultured with Pseudomonas sp. (strain 2-1) for eight days at an initial ratio of 1:5, algal biomass, chlorophyll a, chlorophyll b and carotenoids contents were higher than that of the control by 47.9%, 16.0%, 17.5% and 19.9%, respectively. The total oil (27.1%) and oleic acid (18.2%) contents were increased by 20.4% and 64.0%, respectively. We concluded that Micrococcus (strain 1-2) and Pseudomonas sp. (strain 2-1) could significantly promote algal growth and increase oil production by their beneficial interaction with S. obliques, which could be potentially used in commercial production of S. obliques.

Effects of the ephemeral stream on plant species diversity and distribution in an alluvial fan of arid desert region: An application of a low altitude UAV.

Biodiversity conservation, plant growth and spatial distribution of plant species are the central issues in contemporary community ecology. Ephemeral stream may influence soil properties, which in turn may determine biodiversity and function of an ecosystem in alluvial fan of arid desert region. Ephemeral stream is one of the most common natural disturbances, yet the effects of the ephemeral stream on plant communities in terms of species diversity and plant species distribution remain poorly studied. In this study, the information of species distribution, ephemeral stream beds ('washes'), and the characteristics of plant growth, i.e. height, crown area, were interpreted at different heights using the images of low altitude unmanned aerial vehicle (UAV). After that, soil properties such as soil texture (sand, silt and clay), soil water content, pH, soil organic matter, soil electric conductivity, soil bulk density and the percentage of gravel content, and their relationships with UAV data were assessed in order to explore the influences of ephemeral stream on species diversity, plant growth characteristics and species distribution in an alluvial fan of arid desert region. The results showed that deep-rooted plants were only distributed in washes whereas shallow-rooted plants were distributed in both washes and the outside of washes ('non-washes'). Species richness was significantly higher in washes than that in non-washes whereas the opposite pattern was true for abundance. Soil properties, plant height and crown area were higher in washes than that in non-washes. Plant height, crown area and the total number of individual plants increased with increasing wash width and per unit length of stream flow. This study highlights that the coupling factors of ephemeral stream, such as soil erosion, particle transport and sedimentation, can dramatically cause changes in soil properties and total number of individual plants, and hence, can influence species diversity, plant growth characteristics and spatial distribution of plant species in an alluvial fan of arid desert regions.

Analysis of late diagnosis and its influencing factors of newly reported HIV/AIDS in Guizhou Province from 2014 to 2018 / 中华疾病控制杂志

Objective To find late diagnosis and its influencing factors of newly reported HIV/AIDS in Guizhou Province from 2014 to 2018. Methods Through the Chinese National Comprehensive HIV/AIDS Prevention and Care Information System,all newly reported HIV/AIDS cases from 2014 to 2018 in Guizhou Province were analyzed and related factors of late diagnosis were analyzed using binary Logistic regression model. Results From 2014 to 2018, there were 33 611 newly reported HIV/AIDS cases in Guizhou Province, and the late diagnosis rates of newly reported cases were 35.46%, 34.49%, 38.35%, 39.74% and 38.80% respectively. The analysis showed that the proportion of late diagnosis cases from medical institutions increased year by year ( 2=64.603,P<0.001). By analyzing the late diagnosis rate of cases from different sample sources, medical institutions was significantly higher than that reported by voluntary counseling and testing, positive spouses or sexual partners( 2=276.033,P<0.001). Multivariate analysis showed that gender, marital status, route of transmission, occupation, ethnicity and source of samples were associated with the late diagnosis of newly reported cases (all P<0.05). Conclusions It shows a slow upward trend of late diagnosis rate among HIV/AIDS reported in Guizhou Province from 2014 to 2018.On the one hand, it is of great significance to continue to strengthen the publicity and education of the whole population in Guizhou , in order to improve the awareness of HIV active detection. On the other hand, we should continue to expand HIV testing in Guizhou Province to improve the early detection level of HIV/AIDS.

Mortality analysis among HIV/AIDS cases in Guizhou Province from 1995 to 2017 / 中华疾病控制杂志

Objective To investigate the distribution of death among human immunodeficiency virus/acquired immuno deficiency syndrome(HIV/AIDS) cases in Guizhou Province from 1995 to 2017. Methods The HIV/AIDS death cases from 1995 to 2017 were downloaded from “Chinese National Comprehensive HIV/AIDS Prevention and care Information system” in Guizhou Province and were analyzed. Results From 1995 to 2017, Guizhou Province reported a total of 43 794 HIV/AIDS cases and 11 527 deaths according to current address. After excluding missing persons, the HIV/AIDS mortality rate of the province was 29.8%. The proportion of reported HIV/AIDS cases died in the same year ( 21995-2012=139.5, P<0.001; 22012-2015=28.2, P<0.001) and the proportion of HIV/AIDS cases ( 21995-2012=109.1, P<0.001; 22012-2014=57.2, P<0.001) who survived at the beginning but died later in the year all showed a trend being low-high-low. In the analysis of the detection history of death cases, the detection proportion of cluster of differentiation 4(CD4) T-cell and the proportion of antiviral treatment had been increasing year by year. The analysis of the cause of death found that the proportion of death caused by AIDS increased firstly and then declined, and the proportion of death due to excessive drug abuse showed a trend of declining year by year. Conclusions The mortality rate of HIV/AIDS in Guizhou Province was still high, and decreased rather slow. Expanding the coverage of HIV monitoring and screening is one of the key tasks of AIDS prevention and control. CD4+T-cell testing and free antiviral treatment should be strengthened to reduce the mortality rate of HIV/AIDS in Guizhou Province in the future.

NOON States of Nine Quantized Vibrations in Two Radial Modes of a Trapped Ion.

We develop a deterministic method to generate and verify arbitrarily high NOON states of quantized vibrations (phonons), through the coupling to the internal state. We experimentally create the entangled states up to N=9 phonons in two vibrational modes of a single trapped ^{171}Yb^{+} ion. We observe an increasing phase sensitivity of the generated NOON state as the number of phonons N increases and obtain the fidelity from the contrast of the phase interference and the population of the phonon states through the two-mode projective measurement, which are significantly above the classical bound. We also measure the quantum Fisher information of the generated state and observe Heisenberg scaling in the lower bounds of phase sensitivity as N increases. Our scheme is generic and applicable to other photonic or phononic systems such as circuit QED systems or nanomechanical oscillators, which have Jaynes-Cummings-type of interactions.

Tumor-selective catalytic nanosystem for activatable theranostics.

A novel tumor-selective catalytic nanosystem that enables efficient chemodynamic therapy (CDT) and activatable fluorescence imaging in H2O2-rich tumor microenvironments has been developed.

Tumor-Targeted Graphitic Carbon Nitride Nanoassembly for Activatable Two-Photon Fluorescence Imaging.

Unique physicochemical characteristics of graphitic carbon nitride (g-CN) nanosheets suit them to be a useful tool for two-photon fluorescence bioimaging. Current g-CN nanosheets based imaging probes typically use the "always-on" design strategies, which may suffer from increased fluorescence background and limited contrast. To advance corresponding applications, g-CN nanosheets based activatable two-photon fluorescence probes remain to be explored. For the first time, we developed an activatable two-photon fluorescence probe, constructed from a nanoassembly of g-CN nanosheets and hyaluronic acid (HA)-gold nanoparticles (HA-AuNPs), for detection and imaging of hyaluronidase (HAase) in cancer cells. The deliberately introduced HA in our design not only functions as the buffering layer for stabilizing AuNPs and inducing corresponding self-assembly on g-CN nanosheets but also as a pilot for targeting HA receptors overexpressed on cancer cell surfaces. Our results show that the developed nanoassembly enables specific detection and activatable imaging of HAase in cancer cells and deep tissues, with superb signal-to-background ratio and high sensitivity. This nanoassembly can afford a promising platform for highly specific and sensitive imaging of HAase and for related cancer diagnosis.

Corrigendum: Experimental Certification of Random Numbers via Quantum Contextuality.

This corrects the article DOI: 10.1038/srep01627.

Enhancement of the Intrinsic Peroxidase-Like Activity of Graphitic Carbon Nitride Nanosheets by ssDNAs and Its Application for Detection of Exosomes.

The present work investigates the capability of single-stranded DNA (ssDNA) in enhancing the intrinsic peroxidase-like activity of the g-C3N4 nanosheets (NSs). We found that ssDNA adsorbed on g-C3N4 NSs could improve the catalytic activity of the nanosheets. The maximum reaction rate of the H2O2-mediated TMB oxidation catalyzed by the ssDNA-NSs hybrid was at least 4 times faster than that obtained with unmodified NSs. The activity enhancement could be attributed to the strong interaction between TMB and ssDNA mediated by electrostatic attraction and aromatic stacking and by both the length and base composition of the ssDNA. The high catalytic activity of the ssDNA-NSs hybrid permitted sensitive colorimetric detection of exosomes if the aptamer against CD63, a surface marker of exosome, was employed in hybrid construction. The sensor recognized the differential expression of CD63 between the exosomes produced by a breast cancer cell line (MCF-7) and a control cell line (MCF-10A). Moreover, a similar trend was detected in the circulating exosomes isolated from the sera samples collected from breast cancer patients and healthy controls. Our work sheds lights on the possibility of using ssDNA to enhance the peroxidase-like activity of nanomaterials and demonstrates the high potential of the ssDNA-NSs hybrid in clinical diagnosis using liquid biopsy.

Efficient representation of quantum many-body states with deep neural networks.

Part of the challenge for quantum many-body problems comes from the difficulty of representing large-scale quantum states, which in general requires an exponentially large number of parameters. Neural networks provide a powerful tool to represent quantum many-body states. An important open question is what characterizes the representational power of deep and shallow neural networks, which is of fundamental interest due to the popularity of deep learning methods. Here, we give a proof that, assuming a widely believed computational complexity conjecture, a deep neural network can efficiently represent most physical states, including the ground states of many-body Hamiltonians and states generated by quantum dynamics, while a shallow network representation with a restricted Boltzmann machine cannot efficiently represent some of those states.One of the challenges in studies of quantum many-body physics is finding an efficient way to record the large system wavefunctions. Here the authors present an analysis of the capabilities of recently-proposed neural network representations for storing physically accessible quantum states.

Graphitic Carbon Nitride Nanosheets-Based Ratiometric Fluorescent Probe for Highly Sensitive Detection of H2O2 and Glucose.

Graphitic carbon nitride (g-C3N4) nanosheets, an emerging graphene-like carbon-based nanomaterial with high fluorescence and large specific surface areas, hold great potential for biosensor applications. Current g-C3N4 nanosheets based fluorescent biosensors majorly rely on single fluorescent intensity reading through fluorescence quenching interactions between the nanosheets and metal ions. Here we report for the first time the development of a novel g-C3N4 nanosheets-based ratiometric fluorescence sensing strategy for highly sensitive detection of H2O2 and glucose. With o-phenylenediamine (OPD) oxidized by H2O2 in the presence of horseradish peroxidase (HRP), the oxidization product can assemble on the g-C3N4 nanosheets through hydrogen bonding and π-π stacking, which effectively quenches the fluorescence of g-C3N4 while delivering a new emission peak. The ratiometric signal variations enable robust and sensitive detection of H2O2. On the basis of the glucose converting into H2O2 through the catalysis of glucose oxidase, the g-C3N4-based ratiometric fluorescence sensing platform is also exploited for glucose assay. The developed strategy is demonstrated to give a detection limit of 50 nM for H2O2 and 0.4 µM for glucose, at the same time, it has been successfully used for glucose levels detection in human serum. This strategy may provide a cost-efficient, robust, and high-throughput platform for detecting various species involving H2O2-generation reactions for biomedical applications.

Melanin-Like Nanoquencher on Graphitic Carbon Nitride Nanosheets for Tyrosinase Activity and Inhibitor Assay.

Graphitic C3N4 (g-C3N4) nanosheets are a type of emerging graphene-like carbon-based nanomaterials with high fluorescence and large specific surface areas that hold great potential for biosensor applications. However, current g-C3N4 based biosensors have prevailingly been limited to coordination with metal ions, and it is of great significance to develop new designs for g-C3N4 nanosheets based biosensors toward biomarkers of general interest. We report the development of a novel g-C3N4 nanosheet-based nanosensor strategy for highly sensitive, single-step and label-free detection of tyrosinase (TYR) activity and its inhibitor. This strategy relies on the catalytic oxidation of tyrosine by TYR into melanin-like polymers, which form a nanoassembly on the g-C3N4 nanosheets and quench their fluorescence. This strategy was demonstrated to provide excellent selectivity and superior sensitivity and to enable rapid screening for TYR inhibitors. Therefore, the developed approach might create a useful platform for diagnostics and drugs screening for TYR-based diseases including melanoma cancer.