Search

As the agricultural use of ENMs becomes more prevalent, the exposure of plants to these nanomaterials has emerged as a significant abiotic stress. Researchers have previously explored plant responses to ENMs through non-targeted proteomics studies, revealing qualitative insights into protein-level responses to abiotic stress. However, there remains a knowledge gap in understanding the molecular mechanisms underlying these responses. This study aims to bridge that gap by employing targeted proteomics, which involves the quantitative measurement of a specific set of ENM-responsive proteins. Unlike non-targeted approaches, targeted proteomics allows for high-quality quantification of pre-selected signature peptides associated with targeted proteins. This approach is valuable for hypothesis-driven experiments and provides detailed insights into the perturbations in biological pathways triggered by ENMs.A key focus of the study was the optimization of targeted plant proteomics methods to ensure high reproducibility of results. By refining signature peptide selection, liquid chromatography with tandem mass spectrometry (LC-MS/MS) analytical methods, and sample preparation, the study establishes a robust workflow for the specific quantification of ENMs-responsive proteins. The investigation then applied the optimized targeted proteomics approach to explore the responses of crop plants, specifically Triticum aestivum (wheat), to copper (Cu) based nano-pesticide (Cu(OH)2-NP) and molybdenum (Mo) based nano-fertilizer (MoO3-NP). The study measured protein and metabolite levels in different plant tissues exposed to these ENMs through root or leaf routes. Joint pathway analysis was employed to comprehensively understand the changes in both protein and metabolite levels, providing a holistic view of the molecular responses. The study optimized targeted proteomics methods, revealing the phenol extraction method with fresh plant tissue and trypsin digestion as the best for sample p

The extensive use of glyphosate-based herbicides and its high solubility in water have led to its accumulation in aquatic environments, posing a risk to the ecological environment and human health. Therefore, an effective method for removing glyphosate from wastewater is urgently needed. Herein, a novel nanosized lanthanum peroxide–loaded biochar composite (n-LBC) was prepared using a simple precipitation method, in which biochar served as a dispersant and catalyst to improve the oxidation ability of nanosized lanthanum peroxide. Compared with other common metal peroxide systems, n-LBC exhibited better oxidation ability and achieved a glyphosate removal efficiency of 99.6%. Moreover, n-LBC retained the self-buffering effect of lanthanum peroxide and thus remained effective over a wide pH range, overcoming the problem of pH elevation observed in other metal peroxide systems. The mechanism for glyphosate removal was found to be a combined process of electrostatic attraction, oxidation, and inner-sphere complex formation. Most glyphosate could be oxidized to H2PO 4− by breaking the C–N bonds, and H2PO4 − could be attracted to the material surface simultaneously by electrostatic attraction, forming La–O–P inner-sphere complexes. Thus, n-LBC is a simple and highly effective material for glyphosate removal.

Modern life is essentially homochiral, containing D-sugars in nucleic acid backbones and L-amino acids in proteins. Since coded proteins are theorized to have developed from a prebiotic RNA World, the homochirality of L-amino acids observed in all known life presumably resulted from chiral transfer from a homochiral D-RNA World. This transfer would have been mediated by aminoacyl-RNAs defining the genetic code. Previous work on aminoacyl transfer using tRNA mimics has suggested that aminoacylation using D-RNA may be inherently biased toward reactivity with L-amino acids, implying a deterministic path from a D-RNA World to L-proteins. Using a model system of self-aminoacylating D-ribozymes and epimerizable activated amino acid analogs, we test the chiral selectivity of 15 ribozymes derived from an exhaustive search of sequence space. All of the ribozymes exhibit detectable selectivity, and a substantial fraction react preferentially to produce the D-enantiomer of the product. Furthermore, chiral preference is conserved within sequence families. These results are consistent with the transfer of chiral information from RNA to proteins but do not support an intrinsic bias of D-RNA for L-amino acids. Different aminoacylation structures result in different directions of chiral selectivity, such that L-proteins need not emerge from a D-RNA World.

In the context of internationalization and interdisciplinarity in higher education, student diversity in collaborative learning settings is recognized as a valuable educational resource. It provides all students with opportunities for intercultural experiences and competence development. Integrating students' diverse cultures in group work improves the quality of cross-boundary interactions and knowledge synthesis, enabling them to address complex real-world problems. It also improves individual diversity attitudes, openness, cultural empathy, and social initiative, preparing students for the global workforce and team-based environments. Despite the recognized potential of diversity as a resource in education, effectively integrating both disciplinary and national cultures in group settings is often impeded by challenges such as students’ limited engagement due to uncertainty and intergroup biases, and the urgent need for innovative practices from educators and institutions. Addressing these challenges is crucial to maximizing the benefits of cultural diversity in student group work. This dissertation aims to answer a central research question: "Under which conditions can diversity in a collaborative learning setting provide added value for students' thriving?" It applies a consistent theoretical framework, the Categorization-Elaboration Model, and considers perceptions of benefits and costs, goal orientation, quality of intercultural interaction, and intercultural competence development of both international and domestic students. It explores teachers’ teaching practices, self-regulation, and needed support, constructed the concept of teacher-initiated diversity climate, evaluates the impacts of interdisciplinary programs on students’ competences development, and discusses their interactions in leveraging the added value of diversity in groups to boost students’ learning.

Mercury is a hazardous pollutant of global concern. While advances have been made in identifying the detrimental effects caused by Hg species in phytoplankton, knowledge gaps remain regarding the metabolomic perturbations induced by inorganic mercury (Hg(II)) and monomethylmercury (MeHg) in these organisms. Diatoms represent a major phytoplankton group essential in various global biogeochemical cycles. The current study combined targeted metabolomics, bioaccumulation, and physiological response assays to investigate metabolic perturbations in diatom Cyclotella meneghiniana exposed for 2 h to nanomolar concentrations of Hg(II) and MeHg. Our findings highlight that such exposures induce reprogramming of the metabolism of amino acids, nucleotides, fatty acids, carboxylic acids and antioxidants. These alterations were primarily mercury-species dependent. MeHg exposure induced more pronounced reprogramming of the metabolism of diatoms than Hg(II), which led to less pronounced effects on ROS generation, membrane permeability and chlorophyll concentrations. Hg(II) treatments presented distinct physiological responses, with more robust metabolic perturbations at higher exposures. The present study provides first-time insights into the main metabolic alterations in diatom C. meneghiniana during short-term exposure to Hg species, deepening our understanding of the molecular basis of these perturbations.

Colorectal cancer (CRC) is one of the most common types of malignant cancers worldwide. Although molecularly targeted therapies have significantly improved treatment outcomes, most of these target inhibitors are resistant. Novel inhibitors as potential anti-cancer drug candidates are still needed to be discovered. Therefore, in the present study, we synthesized a novel 4-(1,3,4-thiadiazole-2-ylthio)pyrimidine derivative (compound 4) using fragment- and structure-based techniques and then investigated the anti-cancer effect and underlying mechanism of anti-CRC. The results revealed that compound 4 significantly inhibited HCT116 cell proliferation with IC50 values of 8.04 ± 0.94 µmol L–1 after 48 h and 5.52 ± 0.42 µmol L–1 after 72 h, respectively. Compound 4 also inhibited colony formation, migration, and invasion of HCT116 cells in a dose-dependent manner, as well as inducing cell apoptosis and arresting the cell cycle in the G2/M phase. In addition, compound 4 was able to inhibit the activation of the MEK/ERK signaling in HCT116 cells. And compound 4 yielded the same effects as the MEK inhibitor U0126 on cell apoptosis and MEK/ERK-related proteins. These findings suggested that compound 4 inhibited cell proliferation and growth, and induced cell apoptosis, indicating its use as e a novel and potent anti-cancer agent against CRC via the MEK/ERK signaling pathway.

As a versatile class of semiconductors, diketopyrrolopyrrole (DPP)-based conjugated polymers are well suited for applications of next-generation plastic electronics because of their excellent and tunable optoelectronic properties via a rational design of chemical structures. However, it remains a challenge to unravel and eventually influence the correlation between their solution-state aggregation and solid-state microstructure. In this contribution, the solution-state aggregation of high molecular weight PDPP3T is effectively enhanced by solvent selectivity, and a fibril-like nanostructure with short-range and long-range order is generated and tuned in thin films. The predominant role of solvent quality on polymer packing orientation is revealed, with an orientational transition from a face-on to an edge-on texture for the same PDPP3T. The resultant edge-on arranged films lead to a significant improvement in charge transport in transistors, and the field-effect hole mobility reaches 2.12 cm2 V−1 s−1 with a drain current on/off ratio of up to 108. Our findings offer a new strategy for enhancing the device performance of polymer electronic devices.

To address the challenge of identifying hidden danger in substations from unstructured text, a novel dynamic analysis method is proposed. We first extract relevant information from the unstructured text, and then leverages a flexible distributed search engine built on Elastic-Search to handle the data. Following this, the hidden Markov model is employed to train the data within the engine. The Viterbi algorithm is integrated to decipher the hidden state sequences, facilitating the segmentation and labeling of entities related to hidden dangers. The final step involves using the Neo4j graph database to dynamically create a knowledge graph that visualizes hidden dangers in the substation. The effectiveness of the proposed method is demonstrated through a case analysis from a specific substation with hidden dangers revealed in the text records.

Despite the promising performance of existing visual models on public benchmarks, the critical assessment of their robustness for real-world applications remains an ongoing challenge. To bridge this gap, we propose an explainable visual dataset, XIMAGENET-12, to evaluate the robustness of visual models. XIMAGENET-12 consists of over 200K images with 15,410 manual semantic annotations. Specifically, we deliberately selected 12 categories from ImageNet, representing objects commonly encountered in practical life. To simulate real-world situations, we incorporated six diverse scenarios, such as overexposure, blurring, and color changes, etc. We further develop a quantitative criterion for robustness assessment, allowing for a nuanced understanding of how visual models perform under varying conditions, notably in relation to the background. We make the XIMAGENET-12 dataset and its corresponding code openly accessible at \url{https://sites.google.com/view/ximagenet-12/home}. We expect the introduction of the XIMAGENET-12 dataset will empower researchers to thoroughly evaluate the robustness of their visual models under challenging conditions., Comment: Paper accepted by Synthetic Data for Computer Vision Workshop @ IEEE CVPR 2024

Item does not contain fulltext

Combination of transcriptomics, metabolomics and physiology studies highlighted the nanoparticle size- and concentration-dependent disturbance in algal metabolism induced by nTiO2.

Nano-sized titanium dioxide (nTiO2) is one of the most commonly used materials, however the knowledge about the molecular basis for metabolic and physiological changes in phytoplankton is yet to be explored. In the present study we use a combination of targeted metabolomics, transcriptomics and physiological response studies to decipher the metabolic perturbation in green alga Chlamydomonas reinhardtii exposed for 72 h to increasing concentrations (2, 20, 100 and 200 mg L-1) of nTiO2 with primary sizes of 5, 15 and 20 nm. Results show that the exposure to all three nTiO2 materials induced perturbation of the metabolism of amino acids, nucleotides, fatty acids, tricarboxylic acids, antioxidants but not in the photosynthesis. The alterations of the most responsive metabolites were concentration and primary size-dependent despite the significant formation of micrometer-size aggregates and their sedimentation. The metabolic perturbations corroborate the observed physiological responses and transcriptomic results and confirmed the importance of oxidative stress as a major toxicity mechanism for nTiO2. Transcriptomics revealed also an important influence of nTiO2 treatments on the transport, adenosine triphosphate binding cassette transporters, and metal transporters, suggesting a perturbation in a global nutrition of the microalgal cell, which was most pronounced for exposure to 5 nm nTiO2. The present study provides for the first-time evidence for the main metabolic perturbations in green alga C. reinhardtii exposed to nTiO2 and helps to improve biological understanding of the molecular basis of these perturbations.

Contains fulltext : 250977.pdf (Publisher’s version ) (Open Access)

Metabolomics characterizes low-molecular-weight molecules involved in different biochemical reactions and provides an integrated assessment of the physiological state of an organism. By using liquid chromatography-mass spectrometry targeted metabolomics, we examined the response of green alga Chlamydomonas reinhardtii to sublethal concentrations of inorganic mercury (IHg) and monomethylmercury (MeHg). We quantified the changes in the levels of 93 metabolites preselected based on the disturbed metabolic pathways obtained in a previous transcriptomics study. Metabolites are downstream products of the gene transcription; hence, metabolite quantification provided information about the biochemical status of the algal cells exposed to Hg compounds. The results showed that the alga adjusts its metabolism during 2 h exposure to 5 × 10-9 and 5 × 10-8 mol L-1 IHg and MeHg by increasing the level of various metabolites involved in amino acid and nucleotide metabolism, photorespiration, and tricarboxylic acid (TCA) cycle, as well as the metabolism of fatty acids, carbohydrates, and antioxidants. Most of the metabolic perturbations in the alga were common for IHg and MeHg treatments. However, the exposure to IHg resulted in more pronounced perturbations in the fatty acid and TCA metabolism as compared with the exposure to MeHg. The observed metabolic perturbations were generally consistent with our previously published transcriptomics results for C. reinhardtii exposed to the comparable level of IHg and MeHg. The results highlight the potential of metabolomics for toxicity evaluation, especially to detect effects at an early stage of exposure prior to their physiological appearance.

Metabolomics is an emerging tool to understand the potential implications of nanotechnology, particularly for agriculture. Although molybdenum (Mo) is a known plant micronutrient, little is known of its metabolic perturbations. Here, corn and wheat seedlings were exposed to MoO3 nanoparticles (NPs) and the corresponding bioavailable Mo6+ ion at moderate and excessive levels through root exposures. Physiologically, corn was more sensitive to Mo, which accumulated up to 3.63 times more Mo than wheat. In contrast, metabolomics indicated 21 dysregulated metabolites in corn leaves and 53 in wheat leaves. Five more metabolomic pathways were perturbed in wheat leaves compared to corn leaves. In addition to the overall metabolomics analysis, we also analyzed individual metabolite classes (e.g., amino acids, organic acids, etc.), yielding additional dysregulated metabolites in plant tissues: 7 for corn and 7 for wheat. Most of these were amino acids as well as some sugars. Additional significantly dysregulated metabolites (e.g., asparagine, fructose, reduced glutathione, mannose) were identified in both corn and wheat, due to Mo NP exposure, by employing individual metabolite group analysis. Targeted metabolite analysis of individual groups is thus important for finding additional significant metabolites. We demonstrate the value of metabolomics to study early stage plant responses to NP exposure.

Contains fulltext : 230494.pdf (publisher's version ) (Closed access)

Aliovalent doping is widely adopted to tune the electronic structure of transition-metal oxides for design of low-cost, active electrocatalysts. Here, using single-crystalline thin films as model electrocatalysts, the structure-activity relationship of Fe states doping in perovskite LaNiO3 for oxygen evolution reaction (OER) is studied. Fe4+ state is found to be crucial for enhancing the OER activity of LaNiO3, dramatically increasing the activity by six times, while Fe3+ has negligible effect. Spectroscopic studies and DFT calculations indicate Fe4+ states enhance the degree of Ni/Fe 3d and O 2p hybridization, and meanwhile produce down-shift of the unoccupied density of states towards lower energies. Such electronic features reduce the energy barrier for interfacial electron transfer for water oxidization by 0.2 eV. Further theoretical calculations and H/D isotope experiments reveal the electronic states associated with Fe4+-O2−-Ni3+ configuration accelerate the deprotonation of *OH to *O (rate-determining step), and thus facilitate fast OER kinetics.

Metabolomics characterizes low-molecular-weight molecules involved in different biochemical reactions and provides an integrated assessment of the physiological state of an organism. By using liquid chromatography-mass spectrometry targeted metabolomics, we examined the response of green alga Chlamydomonas reinhardtii to sublethal concentrations of inorganic mercury (IHg) and monomethylmercury (MeHg). We quantified the changes in the levels of 93 metabolites preselected based on the disturbed metabolic pathways obtained in a previous transcriptomics study. Metabolites are downstream products of the gene transcription; hence, metabolite quantification provided information about the biochemical status of the algal cells exposed to Hg compounds. The results showed that the alga adjusts its metabolism during 2 h exposure to 5 × 10-9 and 5 × 10-8 mol L-1 IHg and MeHg by increasing the level of various metabolites involved in amino acid and nucleotide metabolism, photorespiration, and tricarboxylic acid (TCA) cycle, as well as the metabolism of fatty acids, carbohydrates, and antioxidants. Most of the metabolic perturbations in the alga were common for IHg and MeHg treatments. However, the exposure to IHg resulted in more pronounced perturbations in the fatty acid and TCA metabolism as compared with the exposure to MeHg. The observed metabolic perturbations were generally consistent with our previously published transcriptomics results for C. reinhardtii exposed to the comparable level of IHg and MeHg. The results highlight the potential of metabolomics for toxicity evaluation, especially to detect effects at an early stage of exposure prior to their physiological appearance.

Metabolomics is an emerging tool to understand the potential implications of nanotechnology, particularly for agriculture. Although molybdenum (Mo) is a known plant micronutrient, little is known of its metabolic perturbations. Here, corn and wheat seedlings were exposed to MoO3 nanoparticles (NPs) and the corresponding bioavailable Mo6+ ion at moderate and excessive levels through root exposures. Physiologically, corn was more sensitive to Mo, which accumulated up to 3.63 times more Mo than wheat. In contrast, metabolomics indicated 21 dysregulated metabolites in corn leaves and 53 in wheat leaves. Five more metabolomic pathways were perturbed in wheat leaves compared to corn leaves. In addition to the overall metabolomics analysis, we also analyzed individual metabolite classes (e.g., amino acids, organic acids, etc.), yielding additional dysregulated metabolites in plant tissues: 7 for corn and 7 for wheat. Most of these were amino acids as well as some sugars. Additional significantly dysregulated metabolites (e.g., asparagine, fructose, reduced glutathione, mannose) were identified in both corn and wheat, due to Mo NP exposure, by employing individual metabolite group analysis. Targeted metabolite analysis of individual groups is thus important for finding additional significant metabolites. We demonstrate the value of metabolomics to study early stage plant responses to NP exposure.

Contains fulltext : 230494.pdf (publisher's version ) (Closed access)

Contains fulltext : 230494.pdf (publisher's version ) (Closed access)

Introduction: Foodborne diseases are a growing public health problem and have caused a large burden of disease in China. This study analyzed epidemiological characteristics of foodborne diseases in China in 2020 to provide a scientific basis for prevention and control measures. Methods: Data were collected from 30 of 31 provincial-level administrative divisions (PLADs) in the mainland of China, excluding Xizang (Tibet) Autonomous Region, via the National Foodborne Disease Outbreaks Surveillance System. The number and proportion of outbreaks, illnesses, hospitalizations, deaths by setting, pathogen-food category pairs and etiology were calculated. Results: In 2020, 7,073 foodborne disease outbreaks were reported, resulting in 37,454 illnesses and 143 deaths. Among the identified pathogens, microbial pathogens were the most common confirmed etiology, accounting for 41.7% of illnesses. Poisonous mushrooms caused the largest proportion of outbreaks (58.0%) and deaths (57.6%). For venues where foodborne disease outbreaks occur, household had the highest number of outbreaks (4,140) and deaths (128), and catering service locations caused the largest proportion of illnesses (59.9%). Outbreaks occurring between June and September accounted for 62.8% of total outbreaks. Conclusions: Foodborne disease outbreaks mainly occurred in households. Microbial pathogens remained the top cause of outbreak-associated illnesses. Poisonous mushrooms were ranked the top cause of deaths in private homes in China. The supervision and management of food safety and health education should be strengthened to reduce the burden of foodborne diseases. Publicity should be increased to reduce the incidence of mushroom poisonings in families, and supervision and management of food should be strengthened to reduce microbial contamination.

Black-box heterogeneous treatment effect (HTE) models are increasingly being used to create personalized policies that assign individuals to their optimal treatments. However, they are difficult to understand, and can be burdensome to maintain in a production environment. In this paper, we present a scalable, interpretable personalized experimentation system, implemented and deployed in production at Meta. The system works in a multiple treatment, multiple outcome setting typical at Meta to: (1) learn explanations for black-box HTE models; (2) generate interpretable personalized policies. We evaluate the methods used in the system on publicly available data and Meta use cases, and discuss lessons learnt during the development of the system., Comment: Camera-ready version for KDD 2022. Previously titled "Distilling Heterogeneity: From Explanations of Heterogeneous Treatment Effect Models to Interpretable Policies". A short version was presented at MIT CODE 2021

© 2020 The Authors. Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd. Billions of wireless sensing devices must be powered for IoT applications. Collecting energy from the ambient environment to power sensor nodes is a promising solution. Solar energy has been one of the main sources of ambient energy due to its availability, higher power density, and the maturity of the solar photovoltaic industry. However, there are many scenarios (indoor environment, outdoor environment during nighttime, poor weather conditions, underground, etc) where ambient solar energy is either not available or not sufficient for practical applications. For such scenarios, other renewable sources of energy must be sought. Typically, not enough power is collected from one ambient source to charge sensor nodes for continuous operation. In this work, we present a multi-source energy harvester that collects RF and thermal energy (both available 24 hours) from the ambient environment simultaneously. The RF energy harvester is multi-band and collects power from GSM (900, 1800 MHz) and 3G (2100 MHz). The thermal harvester converts diurnal temperature fluctuations to electrical energy using high thermal effusivity phase change material. Extensive field testing has been performed in three different conditions—outdoors, indoors, and buried underground—to highlight the usefulness of the multi-source energy harvester in all these environments. When one source is disabled, the harvester still generates energy from the remaining active source and can enable continuous operation of futuristic IoT sensors. As a proof of concept, a real-world IoT application is demonstrated, where temperature and humidity sensors are powered by the multi-source energy harvester. Continuous robust operation of the sensors and wireless data transmission after each 3.7 seconds are expected when both harvesters operate in full mode. Scenarios, where only single thermal energy h

Introduction: Mushroom poisoning was the leading cause of foodborne disease outbreaks and outbreak-associated deaths in China. Mushroom poisoning outbreak surveillance can provide insight into the epidemiological characteristics of mushroom poisonings and guide policymaking and health education to reduce illnesses and deaths. Methods: Foodborne Disease Outbreak Surveillance System was upgraded in 2011 to collect foodborne disease outbreaks in China. Mushroom poisoning outbreaks during 2010-2020 were selected to analyze geographical distribution, seasonal distribution, and setting of food preparation. Results: A total of 10,036 outbreaks, which resulted in 38,676 illnesses and 788 deaths, were reported in this period. Mushroom poisonings occurred all over the country, but with highest incidence in the southwest and central China. Overall, 84.6% outbreaks were associated with food prepared in households, followed by 8.7% in street stalls, and 2.5% in canteens. Mushroom poisoning outbreaks clearly exhibited seasonality, and the peak season was summer through autumn. Outbreaks occurring between May and October accounted for 94.1% of total outbreaks, 92.4% illnesses, and 97.2% deaths. Conclusions: Mushroom poisoning is a food safety issue of higher concern in China. Targeted health education is essential to reduce mushroom poisoning, especially in southwest China. Citizens are advised to not collect or eat wild mushrooms.

What is already known on this topic? Vibrio parahaemolyticus (V. parahaemolyticus) is frequently resistant to common antimicrobials such as ampicillin and generally highly susceptible to most clinically used antimicrobials. What is added by this report? V. parahaemolyticus were highly resistant to cefazolin and ampicillin: 94.4% and 37.0%, respectively. However, it was below 3% resistance to all 10 other antimicrobials including clinically relevant agents and even imipenem. The overall levels of antimicrobial resistance and multidrug resistance were 95.1% and 3.3%, respectively. The distribution of antimicrobial resistance and the multidrug resistance had regional, temporal, sexual, and isolated source strain variation. What are the implications for public health practice? This study provides data on drug resistance of V. parahaemolyticus in Chinese clinical settings, which will help develop a public health strategy.

This paper studies the subspace clustering problem in which data points collected from high-dimensional ambient space lie in a union of linear subspaces. Subspace clustering becomes challenging when the dimension of intersection between subspaces is large and most of the self-representation based methods are sensitive to the intersection between the span of clusters. In sharp contrast to the self-representation based methods, a recently proposed clustering method termed Innovation Pursuit, computed a set of optimal directions (directions of innovation) to build the adjacency matrix. This paper focuses on the Innovation Pursuit Algorithm to shed light on its impressive performance when the subspaces are heavily intersected. It is shown that in contrast to most of the existing methods which require the subspaces to be sufficiently incoherent with each other, Innovation Pursuit only requires the innovative components of the subspaces to be sufficiently incoherent with each other. These new sufficient conditions allow the clusters to be strongly close to each other. Motivated by the presented theoretical analysis, a simple yet effective projection based technique is proposed which we show with both numerical and theoretical results that it can boost the performance of Innovation Pursuit.

Jianhao Huang,1,&ast; Weiwei Li,2,&ast; Suosu Wei,3,&ast; Xing Zhou,1 Yuechou Nong,1 Jingxia Sun,1 Zhenwei Zhai,1 Wensheng Lu1 1Department of Endocrinology and Metabolism, Guangxi Academy of Medical Sciences and the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, 530021, People’s Republic of China; 2The Office of Guangxi Academy of Medical Sciences and the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, 530021, People’s Republic of China; 3Editorial Board of Chinese Journal of New Clinical Medicine, Guangxi Academy of Medical Sciences and the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, 530021, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Wensheng Lu Email lws2613676@sohu.comAim: The purpose of this study was to explore the association between estimated glomerular filtration rate (eGFR) and clinical outcomes in patients with diabetic foot osteomyelitis (DFO).Methods: This was a retrospective observational study. A total of 199 patients with DFO were recruited and divided into three groups by eGFR: normal kidney function group (eGFR ≥ 90), mildly decreased kidney function group (eGFR 60– 89) and moderately to severely decreased kidney function group (eGFR < 60). The patients were followed-up for a median of 36 months, and the study outcomes were all-cause mortality and major cardiovascular adverse events (MACE). Cox proportional hazard models were used to assess the association between eGFR and the outcomes, and a stratified analysis by sex was conducted.Results: During follow-up, all-cause mortality occurred in 51 (25.63%) patients among 199 participants, 54 (28.72%) had MACE in 188 participants and 26 (48.15%) of them died. After fully adjusting for potential confounders, compared to eGFR < 90 mL/min/1.73 m2, eGFR ≥ 90 mL/min/1.73 m2 had lower incidence of all-cause mortality (HR = 0.43, 95% CI: 0.22â€

Silver nanoparticles (AgNPs) are one of the most used engineered nanomaterials. Despite progress in assessing their environmental implications, knowledge gaps exist concerning the metabolic perturbations induced by AgNPs on phytoplankton, essential organisms in global biogeochemical cycles and food-web dynamics. We combine targeted metabolomics, biouptake and physiological response studies to elucidate metabolic perturbations in alga Poterioochromonas malhamensis induced by AgNPs and dissolved Ag. We show time-dependent perturbation of the metabolism of amino acids, nucleotides, fatty acids, tricarboxylic acids, photosynthesis and photorespiration by both Ag-treatments. The results suggest that dissolved Ag ions released by AgNPs are the major toxicity driver; however, AgNPs internalized in food vacuoles contributed to the perturbation of amino acid metabolism, TCA cycle and oxidative stress. The metabolic perturbations corroborate the observed physiological responses. We highlight the potential of metabolomics as a tool for understanding the molecular basis for these metabolic and physiological changes, and for early detection of stress.

Hematite (Fe2O3) is a well-known oxide semiconductor suitable for photoelectrochemical (PEC) water splitting and industry gas sensing. It is widely known that Sn doping of Fe2O3 can enhance the device performance, yet the underlying mechanism remains elusive. In this work, we determine the relationship between electronic structure, optical properties, and PEC activity of Sn-doped Fe2O3 by studying highly crystalline, well-controlled thin films prepared by pulsed laser deposition (PLD). We show that Sn doping substantially increases the n-type conductivity of Fe2O3, and the conduction mechanism is better described by a small-polaron hopping (SPH) model. Only 0.2% Sn doping significantly reduces the activation energy barrier for SPH conduction from at least 0.5 eV for undoped Fe2O3 to 0.14 eV for doped ones. A combination of X-ray photoemission, X-ray absorption spectroscopy, and DFT calculations reveals that the Fermi level gradually shifts toward the conduction band minimum with Sn doping. A localized Fe2+-like gap state is observed at the top of the valence band, accounting for the SPH conduction. Interestingly, different from the literature, only 0.2% Sn doping in Fe2O3 significantly improves the PEC activity, while more Sn decreases it. The improved PEC activity is partially attributed to an increased band bending potential which facilitates the charge separation at the space charge region. The reduced activation energy barrier for SPH will facilitate the transport of photoexcited carriers for the enhanced PEC, which is of interest for further carrier dynamics study.

Perovskite transition metal oxides are promising non-precious metal electrocatalysts for promoting the oxygen evolution reaction (OER) in many electrochemical energy conversion devices. This work reports a systematic study of the relation between the electronic structure and OER performance of perovskite La1-xSrxFeO3 (0 ≤ x ≤ 1). The partial substitution of La for Sr in LaFeO3 results in the oxidation of Fe3+ to Fe4+ and substantially enhances OER activity. A comprehensive X-ray spectroscopic study reveals a strong correlation of the enhanced OER activity with these Fe4+ states. The presence of Fe4+ leads to a stronger Fe-O bond due to stronger Fe 3d-O 2p orbital hybridization and shifts the energy position of the valence band (VB) to EF. Such an electronic modulation optimizes the surface adsorption energetics of ∗OH intermediates, contributing to faster OER kinetics. Furthermore, a new unoccupied state is created at ∼0.9 eV below the conduction band. This hole state reduces the energy barrier for electron transfer from 1.34 eV to 0.44 eV, thereby facilitating charge transfer at the interface. The Fe4+-induced electronic states responsible for higher OER activity have implications for the understanding of structure-activity relationships in other Fe-based electrocatalysts such as highly active Fe-doped NiOOH.

Silver nanoparticles (AgNPs) are one of the most used engineered nanomaterials. Despite progress in assessing their environmental implications, knowledge gaps exist concerning the metabolic perturbations induced by AgNPs on phytoplankton, essential organisms in global biogeochemical cycles and food-web dynamics. We combine targeted metabolomics, biouptake and physiological response studies to elucidate metabolic perturbations in alga Poterioochromonas malhamensis induced by AgNPs and dissolved Ag. We show time-dependent perturbation of the metabolism of amino acids, nucleotides, fatty acids, tricarboxylic acids, photosynthesis and photorespiration by both Ag-treatments. The results suggest that dissolved Ag ions released by AgNPs are the major toxicity driver; however, AgNPs internalized in food vacuoles contributed to the perturbation of amino acid metabolism, TCA cycle and oxidative stress. The metabolic perturbations corroborate the observed physiological responses. We highlight the potential of metabolomics as a tool for understanding the molecular basis for these metabolic and physiological changes, and for early detection of stress.

Thin (approximately 10 nm) oxide buffer layers grown over lead-halide perovskite device stacks are critical for protecting the perovskite against mechanical and environmental damage. However, the limited perovskite stability restricts the processing methods and temperatures (≤110 °C) that can be used to deposit the oxide overlayers, with the latter limiting the electronic properties of the oxides achievable. In this work, we demonstrate an alternative to existing methods that can grow pinhole-free TiOx (x ~ 2) films with the requisite thickness in <1 min without vacuum. This technique is atmospheric pressure chemical vapor deposition (AP-CVD). The rapid but soft deposition enables growth temperatures of ≥180 °C to be used to coat perovskites with or without a protective layer of PC61BM. This is ≥ 70 °C higher than achievable by current methods and results in more conductive TiOx films, boosting solar cell efficiencies by >2%. Likewise, when AP-CVD SnOx (x ~ 2) is grown directly on the perovskite, there is also minimal structural damage to the underlying perovskite layer. The SnOx layer is pinhole-free and conformal. When used to cover perovskite devices with a PC61BM electron transport layer, shunting due to the pinholes in the spin-coated PC61BM is reduced, resulting in increases in the steady-state efficiency from 16.5% (no SnOx) to 19.4% (60 nm SnOx), with fill factors reaching 84%. This work shows AP-CVD to be a versatile technique for growing oxides on thermally-sensitive materials. © 2020 Elsevier Ltd

The random wind power that accounts for a growing proportion in power systems imposes higher challenge on the reliable operation of power system under uncertain circumstances. Since forecasted values of wind speed are accessible to system operators in advance, the corresponding calculated pre-schedule can be regarded as a reference for the stochastic economic dispatch (SED) problem. Existing methods seldom take the pre-schedule into account when determining an optimal dispatch solution, and the resulting dispatch solutions generally differ greatly from the pre-schedule. In this paper, aiming to readjust from the reference schedule as little as possible, the mean-tracking model is proposed for the first time to search for optimal dispatch solutions with the minimal expectation of generation cost and the minimal tracking errors, among which the tracking errors is implemented to each generator unit in terms of minimizing the deviation in generation cost between the trial solution and the pre-schedule. Moreover, the affine decision rule is applied in this paper to distribute the uncertain wind power proportionally to each generator unit. To guarantee the stable operation of power systems, the voltage operating limits are considered to ensure the voltage on each bus remains within the security margins of voltage. Numerical experiments are carried out on a modified IEEE-30 bus system, and simulation results demonstrate the effectiveness of the proposed mean-tracking model for the SED problem.

Yufan Jian,1,2,* Meina Zhao,1,2,* Jinyi Cao,1,* Tingting Fan,1 Wei Bu,1 Yang Yang,3 Weiwei Li,1 Wei Zhang,1 Yi Qiao,1 Jingwen Wang,1 Aidong Wen1,2 1Department of Pharmacy, Xijing Hospital, The Fourth Military Medical University, Xi’an 710032, People’s Republic of China; 2College of Pharmacy, Shannxi University of Chinese Medicine, Xianyang 712046, People’s Republic of China; 3Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, People’s Republic of China*These authors contributed equally to this workCorrespondence: Tingting Fan; Aidong WenDepartment of Pharmacy, Xijing Hospital, The Air Force Military Medical University, Xi’an 710032, People’s Republic of ChinaEmail fanting0427@163.com; adwen-2004@hotmail.comAim: The aim of this study was to develop a GX1-modified nanostructured lipid carrier (NLCs) and to evaluate its ability to improve the anti-gastric cancer tumor effects of paclitaxel (PTX).Main Methods: The GX1-modified NLCs were synthesized and loaded with PTX (GX1-PTX-NLCs) by emulsion solvent evaporation technique. The anti-tumor activity and pharmacodynamics were then evaluated by in vitro cell studies and animal experiments.Key Findings: The GX1-modified NLCs were successfully synthesized and confirmed by 1H NMR and MALDI-TOF-MS. PTX-loaded NLCs produced particles with average size distribution less than or equal to 222 nm and good drug loading and entrapment efficiency. In vitro studies demonstrated that GX1-PTX-NLCs had a more obvious inhibitory effect on Co-HUVEC cells than PTX and unmodified PTX-NLCs. The cellular uptake results also showed that GX1-PTX-NLCs were largely concentrated in Co-HUVEC cells, and the uptake rates of GX1-PTX-NLCs in Co-HUVEC were higher than those of the free drug and the PTX-NLC. In vivo studies demonstrated that GX1-PTX-NLCs possess strong anti-tumor effect and showed higher tumor growth inhibition and lower toxicity in nude mice

Organic photovoltaic cells (OPVs) have attracted broad attention and become a very energetic field after the emergence of nonfullerene acceptors. Long-lifetime triplet excitons are expected to be good candidates for efficiently harvesting a photocurrent. Parallel with the development of OPVs based on singlet materials (S-OPVs), the potential of triplet materials as photoactive layers has been explored. However, so far, OPVs employing triplet materials in a bulk heterojunction have not exhibited better performance than S-OPVs. Here, the recent progress of representative OPVs based on triplet materials (T-OPVs) is briefly summarized. Based on that, the performance limitations of T-OPVs are analyzed. The shortage of desired triplet materials with favorable optoelectronic properties for OPVs, the tradeoff between long lifetime and high binding energy of triplet excitons, as well as the low charge mobility in most triplet materials are crucial issues restraining the efficiencies of T-OPVs. To overcome these limitations, first, novel materials with desired optoelectronic properties are urgently demanded; second, systematic investigation on the contribution and dynamics of triplet excitons in T-OPVs is necessary; third, close multidisciplinary collaboration is required, as proved by the development of S-OPVs., Funding Agencies|Knut and Alice Wallenberg foundation [2016.0059]; STINT funds for the Joint China-Sweden Mobility programme; Swedish Government Research Area in Materials Science on Functional Materials at Linkoping University Faculty Grant SFO-Mat-LiU [200900971]; China Scholarship Council (CSC); NSFC of China [51711530040, 51473086, 51773207, 91633301]; MOST [2017YFA0204702, 2018YFA0208504]

Organic photovoltaic cells (OPVs) have attracted broad attention and become a very energetic field after the emergence of nonfullerene acceptors. Long-lifetime triplet excitons are expected to be good candidates for efficiently harvesting a photocurrent. Parallel with the development of OPVs based on singlet materials (S-OPVs), the potential of triplet materials as photoactive layers has been explored. However, so far, OPVs employing triplet materials in a bulk heterojunction have not exhibited better performance than S-OPVs. Here, the recent progress of representative OPVs based on triplet materials (T-OPVs) is briefly summarized. Based on that, the performance limitations of T-OPVs are analyzed. The shortage of desired triplet materials with favorable optoelectronic properties for OPVs, the tradeoff between long lifetime and high binding energy of triplet excitons, as well as the low charge mobility in most triplet materials are crucial issues restraining the efficiencies of T-OPVs. To overcome these limitations, first, novel materials with desired optoelectronic properties are urgently demanded; second, systematic investigation on the contribution and dynamics of triplet excitons in T-OPVs is necessary; third, close multidisciplinary collaboration is required, as proved by the development of S-OPVs., Funding Agencies|Knut and Alice Wallenberg foundation [2016.0059]; STINT funds for the Joint China-Sweden Mobility programme; Swedish Government Research Area in Materials Science on Functional Materials at Linkoping University Faculty Grant SFO-Mat-LiU [200900971]; China Scholarship Council (CSC); NSFC of China [51711530040, 51473086, 51773207, 91633301]; MOST [2017YFA0204702, 2018YFA0208504]

In this work, the first diketopyrrolopyrrole (DPP) based donor-acceptor macrocyclic conjugated molecule was developed and its application in organic electronics was systematically studied. Macrocyclic molecules, as a fragment of armchair carbon nanotubes, have emerged as functional materials in materials chemistry, but the materials are always limited to cycloparaphenylenes. Using the donor-acceptor design strategy that has been widely used in high performance conjugated polymers for macrocyclic molecules, it will significantly broaden their species with tunable optical and electrical properties. Herein, we synthesize a well-defined macrocyclic molecule containing four electron-deficient DPP units alternating with electron-rich thiophenes. The new molecule was found to show high solubility, near-infrared absorption spectra and 3D charge transport properties. The new macrocyclic molecule as an electron acceptor was applied to non-fullerene organic solar cells, exhibiting an initial efficiency of 0.49%, while the linear molecule with a similar backbone only showed a very low efficiency of 0.03%. Our results demonstrate that donor-acceptor macrocyclic conjugated materials have great potential application in organic electronics., Funding Agencies|MOST [2017YFA0204702, 2018YFA0208504]; NSFC of China [51773207, 21574138, 51603209, 91633301]; Strategic Priority Research Program of the Chinese Academy of Sciences [XDB12030200]; Knut and Alice Wallenberg Foundation [2016.0059]; Swedish Government Research Area in Materials Science on Functional Materials at Linkoping University (Faculty Grant SFO-Mat-LiU) [200900971]; China Scholarship Council [CSC201606920028, CSC201708370115]

In this work, the first diketopyrrolopyrrole (DPP) based donor-acceptor macrocyclic conjugated molecule was developed and its application in organic electronics was systematically studied. Macrocyclic molecules, as a fragment of armchair carbon nanotubes, have emerged as functional materials in materials chemistry, but the materials are always limited to cycloparaphenylenes. Using the donor-acceptor design strategy that has been widely used in high performance conjugated polymers for macrocyclic molecules, it will significantly broaden their species with tunable optical and electrical properties. Herein, we synthesize a well-defined macrocyclic molecule containing four electron-deficient DPP units alternating with electron-rich thiophenes. The new molecule was found to show high solubility, near-infrared absorption spectra and 3D charge transport properties. The new macrocyclic molecule as an electron acceptor was applied to non-fullerene organic solar cells, exhibiting an initial efficiency of 0.49%, while the linear molecule with a similar backbone only showed a very low efficiency of 0.03%. Our results demonstrate that donor-acceptor macrocyclic conjugated materials have great potential application in organic electronics., Funding Agencies|MOST [2017YFA0204702, 2018YFA0208504]; NSFC of China [51773207, 21574138, 51603209, 91633301]; Strategic Priority Research Program of the Chinese Academy of Sciences [XDB12030200]; Knut and Alice Wallenberg Foundation [2016.0059]; Swedish Government Research Area in Materials Science on Functional Materials at Linkoping University (Faculty Grant SFO-Mat-LiU) [200900971]; China Scholarship Council [CSC201606920028, CSC201708370115]

In this work, the first diketopyrrolopyrrole (DPP) based donor-acceptor macrocyclic conjugated molecule was developed and its application in organic electronics was systematically studied. Macrocyclic molecules, as a fragment of armchair carbon nanotubes, have emerged as functional materials in materials chemistry, but the materials are always limited to cycloparaphenylenes. Using the donor-acceptor design strategy that has been widely used in high performance conjugated polymers for macrocyclic molecules, it will significantly broaden their species with tunable optical and electrical properties. Herein, we synthesize a well-defined macrocyclic molecule containing four electron-deficient DPP units alternating with electron-rich thiophenes. The new molecule was found to show high solubility, near-infrared absorption spectra and 3D charge transport properties. The new macrocyclic molecule as an electron acceptor was applied to non-fullerene organic solar cells, exhibiting an initial efficiency of 0.49%, while the linear molecule with a similar backbone only showed a very low efficiency of 0.03%. Our results demonstrate that donor-acceptor macrocyclic conjugated materials have great potential application in organic electronics., Funding Agencies|MOST [2017YFA0204702, 2018YFA0208504]; NSFC of China [51773207, 21574138, 51603209, 91633301]; Strategic Priority Research Program of the Chinese Academy of Sciences [XDB12030200]; Knut and Alice Wallenberg Foundation [2016.0059]; Swedish Government Research Area in Materials Science on Functional Materials at Linkoping University (Faculty Grant SFO-Mat-LiU) [200900971]; China Scholarship Council [CSC201606920028, CSC201708370115]

Clinical drug dosing would, ideally, be informed by high-precision, patient-specific data on drug metabolism. The direct determination of patient-specific drug pharmacokinetics ("peaks and troughs"), however, currently relies on cumbersome, laboratory-based approaches that require hours to days to return pharmacokinetic estimates based on only one or two plasma drug measurements. In response clinicians often base dosing on age, body mass, pharmacogenetic markers, or other indirect estimators of pharmacokinetics despite the relatively low accuracy of these approaches. Here, in contrast, we explore the use of indwelling electrochemical aptamer-based (E-AB) sensors as a means of measuring pharmacokinetics rapidly and with high precision using a rat animal model. Specifically, measuring the disposition kinetics of the drug tobramycin in Sprague-Dawley rats we demonstrate the seconds resolved, real-time measurement of plasma drug levels accompanied by measurement validation via HPLC-MS on ex vivo samples. The resultant data illustrate the significant pharmacokinetic variability of this drug even when dosing is adjusted using body weight or body surface area, two widely used pharmacokinetic predictors for this important class of antibiotics, highlighting the need for improved methods of determining its pharmacokinetics.

Considering the unstable inversion of ill-conditioned intermediate matrix required in each integral arc in the short-arc approach presented in Chen et al. (2015), an optimized short-arc method via stabilizing the inversion is proposed. To account for frequency-dependent noise in observations, a noise whitening technique is implemented in the optimized short-arc approach. Our study shows the optimized short-arc method is able to stabilize the inversion and eventually prolong the arc length to 6 hours. In addition, the noise whitening method is able to mitigate the impacts of low-frequency noise in observations. Using the optimized short-arc approach, a refined time series of GRACE monthly models called Tongji-Grace2018 has been developed. The analyses allow us to derive the following conclusions: (a) during the analyses over the river basins (i.e. Amazon, Mississippi, Irrawaddy and Taz) and Greenland, the correlation coefficients of mass changes between Tongji-Grace2018 and others (i.e. CSR RL06, GFZ RL06 and JPL RL06 Mascon) are all over 92 and the corresponding amplitudes are comparable; (b) the signals of Tongji-Grace2018 agree well with those of CSR RL06, GFZ RL06, ITSG-Grace2018 and JPL RL06 Mascon, while Tongji-Grace2018 and ITSG-Grace2018 are less noisy than CSR RL06 and GFZ RL06; (c) clearer global mass change trend and less striping noise over oceans can be observed in Tongji-Grace2018 even only using decorrelation filtering; and (d) for the tests over Sahara, over 36 and 19 of noise reductions are achieved by Tongji-Grace2018 relative to CSR RL06 in the cases of using decorrelation filtering and combined filtering, respectively.

In this work, the first diketopyrrolopyrrole (DPP) based donor-acceptor macrocyclic conjugated molecule was developed and its application in organic electronics was systematically studied. Macrocyclic molecules, as a fragment of armchair carbon nanotubes, have emerged as functional materials in materials chemistry, but the materials are always limited to cycloparaphenylenes. Using the donor-acceptor design strategy that has been widely used in high performance conjugated polymers for macrocyclic molecules, it will significantly broaden their species with tunable optical and electrical properties. Herein, we synthesize a well-defined macrocyclic molecule containing four electron-deficient DPP units alternating with electron-rich thiophenes. The new molecule was found to show high solubility, near-infrared absorption spectra and 3D charge transport properties. The new macrocyclic molecule as an electron acceptor was applied to non-fullerene organic solar cells, exhibiting an initial efficiency of 0.49%, while the linear molecule with a similar backbone only showed a very low efficiency of 0.03%. Our results demonstrate that donor-acceptor macrocyclic conjugated materials have great potential application in organic electronics., Funding Agencies|MOST [2017YFA0204702, 2018YFA0208504]; NSFC of China [51773207, 21574138, 51603209, 91633301]; Strategic Priority Research Program of the Chinese Academy of Sciences [XDB12030200]; Knut and Alice Wallenberg Foundation [2016.0059]; Swedish Government Research Area in Materials Science on Functional Materials at Linkoping University (Faculty Grant SFO-Mat-LiU) [200900971]; China Scholarship Council [CSC201606920028, CSC201708370115]

This work reports a fundamental study on the relationship of the electronic structure, catalytic activity and surface reconstruction process of Fe doped NiS2 (FexNi1-xS2) for the oxygen evolution reaction (OER). A combined photoemission and X-ray absorption spectroscopic study reveals that Fe doping introduces more occupied Fe 3d6 states at the top of the valence band and thereby induces a metallic phase. Meanwhile, Fe doping also significantly increases the OER activity and results in much better stability with the optimum found for Fe0.1Ni0.9S2. More importantly, we performed detailed characterization to track the evolution of the structure and composition of the catalysts after different cycles of OER testing. Our results further confirmed that the catalysts gradually transform into amorphous (oxy)hydroxides which are the actual active species for the OER. However, a fast phase transformation in NiS2 is accompanied by a decrease of OER activity, because of the formation of a thick insulating NiOOH layer limiting electron transfer. On the other hand, Fe doping retards the process of transformation, because of a shorter Fe-S bond length (2.259 Å) than Ni-S (2.400 Å), explaining the better electrochemical stability of Fe0.1Ni0.9S2. These results suggest that the formation of a thin surface layer of NiFe (oxy)hydroxide as an active OER catalyst and the remaining Fe0.1Ni0.9S2 as a conductive core for fast electron transfer is the base for the high OER activity of FexNi1-xS2. Our work provides important insight and design principle for metal chalcogenides as highly active OER catalysts.

In this work, the first diketopyrrolopyrrole (DPP) based donor-acceptor macrocyclic conjugated molecule was developed and its application in organic electronics was systematically studied. Macrocyclic molecules, as a fragment of armchair carbon nanotubes, have emerged as functional materials in materials chemistry, but the materials are always limited to cycloparaphenylenes. Using the donor-acceptor design strategy that has been widely used in high performance conjugated polymers for macrocyclic molecules, it will significantly broaden their species with tunable optical and electrical properties. Herein, we synthesize a well-defined macrocyclic molecule containing four electron-deficient DPP units alternating with electron-rich thiophenes. The new molecule was found to show high solubility, near-infrared absorption spectra and 3D charge transport properties. The new macrocyclic molecule as an electron acceptor was applied to non-fullerene organic solar cells, exhibiting an initial efficiency of 0.49%, while the linear molecule with a similar backbone only showed a very low efficiency of 0.03%. Our results demonstrate that donor-acceptor macrocyclic conjugated materials have great potential application in organic electronics., Funding Agencies|MOST [2017YFA0204702, 2018YFA0208504]; NSFC of China [51773207, 21574138, 51603209, 91633301]; Strategic Priority Research Program of the Chinese Academy of Sciences [XDB12030200]; Knut and Alice Wallenberg Foundation [2016.0059]; Swedish Government Research Area in Materials Science on Functional Materials at Linkoping University (Faculty Grant SFO-Mat-LiU) [200900971]; China Scholarship Council [CSC201606920028, CSC201708370115]

Clinical drug dosing would, ideally, be informed by high-precision, patient-specific data on drug metabolism. The direct determination of patient-specific drug pharmacokinetics ("peaks and troughs"), however, currently relies on cumbersome, laboratory-based approaches that require hours to days to return pharmacokinetic estimates based on only one or two plasma drug measurements. In response clinicians often base dosing on age, body mass, pharmacogenetic markers, or other indirect estimators of pharmacokinetics despite the relatively low accuracy of these approaches. Here, in contrast, we explore the use of indwelling electrochemical aptamer-based (E-AB) sensors as a means of measuring pharmacokinetics rapidly and with high precision using a rat animal model. Specifically, measuring the disposition kinetics of the drug tobramycin in Sprague-Dawley rats we demonstrate the seconds resolved, real-time measurement of plasma drug levels accompanied by measurement validation via HPLC-MS on ex vivo samples. The resultant data illustrate the significant pharmacokinetic variability of this drug even when dosing is adjusted using body weight or body surface area, two widely used pharmacokinetic predictors for this important class of antibiotics, highlighting the need for improved methods of determining its pharmacokinetics.