Operando Decoding of Surface Chemical and Thermal Events in Photoelectrocatalysis via a Lab-Around-Microfiber Sensor.

Operando decoding of the key parameters of photo-electric catalysis provides reliable information for catalytic effect evaluation and catalytic mechanism exploration. However, to capture the details of surface-localized and rapid chemical and thermal events at the nanoscale in real-time is highly challenging. A promising approach based on a lab-around-microfiber sensor capable of simulating photo-electric catalytic reactions on the surface of optical fibers as well as monitoring reactant concentration changes and catalytic heat generation processes is demonstrated. Due to the penetration depth of submicron size and the fast response ability of the evanescent field, the lab-around-microfiber sensor overcame the difficulty of reading instantaneous surface parameters in the submicron range. This sensor operando dismantled the changes in reactant concentration and temperature on the catalyst surface induced by light and voltage, respectively. It also decoded the impact of catalyst composition on the adsorption efficiency and catalytic efficiency across various wavelengths and determined the synchronized occurrence of pollutant degradation and catalytic thermal effects. Stable correlations between the real-time parameters and catalytic activities are obtained, helping to provide a basic understanding of the catalytic process and mechanism. This approach fills an important gap in the current monitoring methods of catalytic processes and heat production.

Frequency-domain terahertz optoacoustics for non-contact quantitative detection of gas, liquid, and solid samples.

Terahertz optoacoustics (THz-OA) combines the advantages of abundant molecular characteristic absorptions in a terahertz band and the low attenuation through ultrasonic detection. Frequency-domain THz-OA, benefiting from the compact and the low cost of a continuous-wave THz source, has been used in gas detection and sensing. However, liquid and solid detections are hard to achieve due to the sensitivity limitation of existing technologies. Here we present a high-sensitivity frequency-domain THz-OA system with customized optoacoustic cells to accomplish non-contact quantitative detection of gas, liquid, and solid samples. The relationships between signal amplitudes and sample concentration, volume and temperature are discussed separately, revealing a potential application of this technology.

Facile synthesis of δ-MnO2 biotemplated by waste tobacco stem-silks for enhanced removal of Sb(III).

The elimination of antimony pollution has attracted increasing concerns because of its high toxicity to human health and the natural environment. In this work, biomimetic δ-MnO2 was synthesized by using waste tobacco stem-silks as biotemplate (Bio-δ-MnO2) and used in the capture of Sb(III)from aqueous solution. The tobacco stem-silks not only provided unique wrinkled morphologies but also contained carbon element self-doped into the resulting samples. The maximum Sb(III) adsorption capacity reached 763.4 mg∙g -1, which is 2.06 times higher than δ-MnO2 without template (370.0 mg∙g -1), 4.53 times than tobacco stem-silks carbon (168.5 mg∙g -1), and 10.39 times than commercial MnO2 (73.5 mg∙g -1), respectively. The isotherm and kinetic studies indicated that the adsorption behavior was consistent with the Langmuir isotherm model and the pseudo-second-order kinetic equation. As far as we are aware, the adsorption capacity of Bio-δ-MnO2 is much higher than that of most Sb(III) adsorbents. FT-IR, XPS, SEM, XRD, and Zeta potential analyses showed that the main mechanism for the adsorption of Sb(III) by Bio-δ-MnO2 includes electrostatic attraction, surface complexation, and redox. Overall, this study provides a new sustainable way to convert agricultural wastes to more valuable products such as biomimetic adsorbent for Sb(III) removal in addition to conventional activated carbon and biochar.

Gradient-Based Local Causal Structure Learning.

Finding the causal structure from a set of variables given observational data is a crucial task in many scientific areas. Most algorithms focus on discovering the global causal graph but few efforts have been made toward the local causal structure (LCS), which is of wide practical significance and easier to obtain. LCS learning faces the challenges of neighborhood determination and edge orientation. Available LCS algorithms build on conditional independence (CI) tests, they suffer the poor accuracy due to noises, various data generation mechanisms, and small-size samples of real-world applications, where CI tests do not work. In addition, they can only find the Markov equivalence class, leaving some edges undirected. In this article, we propose a GradieNt-based LCS learning approach (GraN-LCS) to determine neighbors and orient edges simultaneously in a gradient-descent way, and, thus, to explore LCS more accurately. GraN-LCS formulates the causal graph search as minimizing an acyclicity regularized score function, which can be optimized by efficient gradient-based solvers. GraN-LCS constructs a multilayer perceptron (MLP) to simultaneously fit all other variables with respect to a target variable and defines an acyclicity-constrained local recovery loss to promote the exploration of local graphs and to find out direct causes and effects of the target variable. To improve the efficacy, it applies preliminary neighborhood selection (PNS) to sketch the raw causal structure and further incorporates an l1 -norm-based feature selection on the first layer of MLP to reduce the scale of candidate variables and to pursue sparse weight matrix. GraN-LCS finally outputs LCS based on the sparse weighted adjacency matrix learned from MLPs. We conduct experiments on both synthetic and real-world datasets and verify its efficacy by comparing against state-of-the-art baselines. A detailed ablation study investigates the impact of key components of GraN-LCS and the results prove their contribution.

Marriage of a Dual-Plasmonic Interface and Optical Microfiber for NIR-II Cancer Theranostics.

The use of light as a powerful tool for disease treatment has introduced a new era in tumor treatment and provided abundant opportunities for light-based tumor theranostics. This work reports a photothermal theranostic fiber integrating cancer detection and therapeutic functions. Its self-heating effect can be tuned at ultralow powers and used for self-heating detection and tumor ablation. The fiber, consisting of a dual-plasmonic nanointerface and an optical microfiber, can be used to distinguish cancer cells from normal cells, quantify cancer cells, perform hyperthermal ablation of cancer cells, and evaluate the ablation efficacy. Its cancer cell ablation rate reaches 89% in a single treatment. In vitro and in vivo studies reveal quick, deep-tissue photonic hyperthermia in the NIR-II window, which can markedly ablate tumors. The marriage of a dual-plasmonic nanointerface and an optical microfiber presents a novel paradigm in photothermal therapy, offering the potential to surmount the challenges posed by limited light penetration depth, nonspecific accumulation in normal tissues, and inadvertent damage in current methods. This work thus provides insight for the exploration of an integrated theranostic platform with simultaneous functions in cancer diagnostics, therapeutics, and postoperative monitoring for future practical applications.

Plasmonic Coupling on an Optical Microfiber Surface: Enabling Single-Molecule and Noninvasive Dopamine Detection.

Optical fibers can be effective biosensors when employed in early-stage diagnostic point-of-care devices as they can avoid interference from molecules with similar redox potentials. Nevertheless, their sensitivity needs to be improved for real-world applications, especially for small-molecule detection. This work demonstrates an optical microfiber biosensor for dopamine (DA) detection based on the DA-binding-induced aptamer conformational transitions that occur at plasmonic coupling sites on a double-amplified nanointerface. The sensor exhibits ultrahigh sensitivity when detecting DA molecules at the single-molecule level; additionally, this work provides an approach for overcoming optical device sensitivity limits, further extending optical fiber single-molecule detection to a small molecule range (e.g., DA and metal ions). The selective energy enhancement and signal amplification at the binding sites effectively avoid nonspecific amplification of the whole fiber surface which may lead to false-positive results. The sensor can detect single-molecule DA signals in body-fluids. It can detect the released extracellular DA levels and monitor the DA oxidation process. An appropriate aptamer replacement allows the sensor to be used for the detection of other target small molecules and ions at the single-molecule level. This technology offers alternative opportunities for developing noninvasive early-stage diagnostic point-of-care devices and flexible single-molecule detection techniques in theoretical research.

Optical Microfiber with a Gold Nanorods-Black Phosphorous Nanointerface: An Ultrasensitive Biosensor and Nanotherapy Platform.

The detection and therapy of cancers in the early stage significantly alleviate the associated dangers. Optical devices offer new opportunities for these early measures. However, the clinical translation of the existing methods is severely hindered by their relatively low sensitivity or unclear physiological metabolism. Here, an optical microfiber sensor with a drug loading gold nanorod-black phosphorous nanointerface, as an ultrasensitive biosensor and nanotherapy platform, is developed to meet the early-stage requirement. With interface sensitization and functionalization of the hybrid nanointerface, the microfiber sensor presents an ultrahigh sensing performance, achieving the selective detection of the HER2 biomarker with limits of detection of 0.66 aM in buffer solution and 0.77 aM in 10% serum. It can also distinguish breast cancer cells from other cells in the early stage. Additionally, enabled by the interface, the optical microfiber is able to realize cellular nanotherapy, including photothermal/chemotherapy with pump laser coupling after diagnosis, and evaluate therapy results in real time. The immobilization of the interface on the optical microfiber surface prevents the damage to normal cells induced by nanomaterial enrichment, making the device more efficient and intelligent. This study opens up a new avenue for the development of smart optical platforms for sensitive biosensing and precision therapy.

The deubiquitinases UBP12 and UBP13 integrate with the E3 ubiquitin ligase XBAT35.2 to modulate VPS23A stability in ABA signaling.

Ubiquitination-mediated protein degradation in both the 26S proteasome and vacuole is an important process in abscisic acid (ABA) signaling. However, the role of deubiquitination in this process remains elusive. Here, we demonstrate that two deubiquitinating enzymes (DUBs), ubiquitin-specific protease 12 (UBP12) and UBP13, modulate ABA signaling and drought tolerance by deubiquitinating and stabilizing the endosomal sorting complex required for transport-I (ESCRT-I) component vacuolar protein sorting 23A (VPS23A) and thereby affect the stability of ABA receptors in Arabidopsis thaliana. Genetic analysis showed that VPS23A overexpression could rescue the ABA hypersensitive and drought tolerance phenotypes of ubp12-2w or ubp13-1. In addition to the direct regulation of VPS23A, we found that UBP12 and UBP13 also stabilized the E3 ligase XB3 ortholog 5 in A. thaliana (XBAT35.2) in response to ABA treatment. Hence, we demonstrated that UBP12 and UBP13 are previously unidentified rheostatic regulators of ABA signaling and revealed a mechanism by which deubiquitination precisely monitors the XBAT35/VPS23A ubiquitination module in the ABA response.