Panda-UV Unlocks Deeper Protein Characterization with Internal Fragments in Ultraviolet Photodissociation Mass Spectrometry.

Ultraviolet photodissociation (UVPD) mass spectrometry unlocks insights into the protein structure and sequence through fragmentation patterns. While N- and C-terminal fragments are traditionally relied upon, this work highlights the critical role of internal fragments in achieving near-complete sequencing of protein. Previous limitations of internal fragment utilization, owing to their abundance and potential for random matching, are addressed here with the development of Panda-UV, a novel software tool combining spectral calibration, and Pearson correlation coefficient scoring for confident fragment assignment. Panda-UV showcases its power through comprehensive benchmarks on three model proteins. The inclusion of internal fragments boosts identified fragment numbers by 26% and enhances average protein sequence coverage to a remarkable 93% for intact proteins, unlocking the hidden region of the largest protein carbonic anhydrase II in model proteins. Notably, an average of 65% of internal fragments can be identified in multiple replicates, demonstrating the high confidence of the fragments Panda-UV provided. Finally, the sequence coverages of mAb subunits can be increased up to 86% and the complementary determining regions (CDRs) are nearly completely sequenced in a single experiment. The source codes of Panda-UV are available at https://github.com/PHOENIXcenter/Panda-UV.

Synergistic dual-phase air electrode enables high and durable performance of reversible proton ceramic electrochemical cells.

Reversible proton ceramic electrochemical cells are promising solid-state ion devices for efficient power generation and energy storage, but necessitate effective air electrodes to accelerate the commercial application. Here, we construct a triple-conducting hybrid electrode through a stoichiometry tuning strategy, composed of a cubic phase Ba0.5Sr0.5Co0.8Fe0.2O3-δ and a hexagonal phase Ba4Sr4(Co0.8Fe0.2)4O16-δ. Unlike the common method of creating self-assembled hybrids by breaking through material tolerance limits, the strategy of adjusting the stoichiometric ratio of the A-site/B-site not only achieves strong interactions between hybrid phases, but also can efficiently modifies the phase contents. When operate as an air electrode for reversible proton ceramic electrochemical cell, the hybrid electrode with unique dual-phase synergy shows excellent electrochemical performance with a current density of 3.73 A cm-2 @ 1.3 V in electrolysis mode and a peak power density of 1.99 W cm-2 in fuel cell mode at 650 °C.

Sparking potential over 1200 V by a falling water droplet.

Hydrovoltaic technology has achieved notable breakthroughs in electric output via using the moving boundary of electric double layer, but the output voltage induced by droplets is saturated around 350 volts, and the underlying mechanism remains to be further clarified. Here, we show that falling water droplets can stably spark an unprecedented voltage up to 1200 volts within microseconds that they contact an electrode placed on top of an electret surface, approaching the theoretical upper limit. This sparking potential can be explained and described by a comprehensive model considering the water-electrode contact dynamics from both the macroscale droplet spreading and the microscale electric double layer formation, as well as the presence of a circuit capacitance. It is demonstrated that a droplet-induced electric spark is sufficient to directly ionize gas at atmospheric pressure and split water into hydrogen and oxygen, showing wide application potential in fields of green energy and intelligence.

6-Plex mdSUGAR Isobaric-Labeling Guide Fingerprint Embedding for Glycomics Analysis.

Glycans are vital biomolecules with diverse functions in biological processes. Mass spectrometry (MS) has become the most widely employed technology for glycomics studies. However, in the traditional data-dependent acquisition mode, only a subset of the abundant ions during MS1 scans are isolated and fragmented in subsequent MS2 events, which reduces reproducibility and prevents the measurement of low-abundance glycan species. Here, we reported a new method termed 6-plex mdSUGAR isobaric-labeling guide fingerprint embedding (MAGNI), to achieve multiplexed, quantitative, and targeted glycan analysis. The glycan peak signature was embedded by a triplicate-labeling strategy with a 6-plex mdSUGAR tag, and using ultrahigh-resolution mass spectrometers, the low-abundance glycans that carry the mass fingerprints can be recognized on the MS1 spectra through an in-house developed software tool, MAGNIFinder. These embedded unique fingerprints can guide the selection and fragmentation of targeted precursor ions and further provide rich information on glycan structures. Quantitative analysis of two standard glycoproteins demonstrated the accuracy and precision of MAGNI. Using this approach, we identified 304 N-glycans in two ovarian cancer cell lines. Among them, 65 unique N-glycans were found differentially expressed, which indicates a distinct glycosylation pattern for each cell line. Remarkably, 31 N-glycans can be quantified in only 1 × 103 cells, demonstrating the high sensitivity of our method. Taken together, our MAGNI method offers a useful tool for low-abundance N-glycan characterization and is capable of determining small quantitative differences in N-glycan profiling. Therefore, it will be beneficial to the field of glycobiology and will expand our understanding of glycosylation.

Simulation Analysis of Equibiaxial Tension Tests for Rubber-like Materials.

For rubber-like materials, there are three popular methods of equibiaxial tension available: inflation tension, equibiaxial planar tension, and radial tension. However, no studies have addressed the accuracy and comparability of these tests. In this work, we model the tension tests for a hyperelastic electroactive polymer (EAP) membrane material using finite element method (FEM) and investigate their experimental accuracy. This study also analyzes the impact of apparatus structure parameters and specimen dimensions on experimental performances. Additionally, a tensile efficiency is proposed to assess non-uniform deformation in equibiaxial planar tension and radial tension tests. The sample points for calculating deformation in inflation tensions should be taken near the top of the inflated balloon to obtain a more accurate characteristic curve; the deformation simulation range will be constrained by the material model and its parameters within a specific limit (λ ≈ 1.9); if the inflation hole size is halved, the required air pressure must be doubled to maintain equivalent stress and strain values, resulting in a reduction in half in inflation height and decreased accuracy. The equibiaxial planar tension test can enhance uniform deformation and reduce stress errors to as low as 2.1% (at λ = 4) with single-corner-point tension. For circular diaphragm specimens in radial tension tests, increasing the number of cuts and using larger punched holes results in more uniform deformation and less stress error, with a minimum value of 3.83% achieved for a specimen with 24 cuts and a 5 mm punched hole. In terms of tensile efficiency, increasing the number of tensile points in the equibiaxial planar tension test can improve it; under radial tension, increasing the number of cuts and decreasing the diameter of the punched hole on the specimen has a hedging effect. The findings of this study are valuable for accurately evaluating various equibiaxial tension methods and analyzing their precision, as well as providing sound guidance for the effective design of testing apparatus and test plans.

Application of Medical Image Navigation Technology in Minimally Invasive Puncture Robot.

Microneedle puncture is a standard minimally invasive treatment and surgical method, which is widely used in extracting blood, tissues, and their secretions for pathological examination, needle-puncture-directed drug therapy, local anaesthesia, microwave ablation needle therapy, radiotherapy, and other procedures. The use of robots for microneedle puncture has become a worldwide research hotspot, and medical imaging navigation technology plays an essential role in preoperative robotic puncture path planning, intraoperative assisted puncture, and surgical efficacy detection. This paper introduces medical imaging technology and minimally invasive puncture robots, reviews the current status of research on the application of medical imaging navigation technology in minimally invasive puncture robots, and points out its future development trends and challenges.

Ex Situ Reconstruction-Shaped Ir/CoO/Perovskite Heterojunction for Boosted Water Oxidation Reaction.

The oxygen evolution reaction (OER) is the performance-limiting step in the process of water splitting. In situ electrochemical conditioning could induce surface reconstruction of various OER electrocatalysts, forming reactive sites dynamically but at the expense of fast cation leaching. Therefore, achieving simultaneous improvement in catalytic activity and stability remains a significant challenge. Herein, we used a scalable cation deficiency-driven exsolution approach to ex situ reconstruct a homogeneous-doped cobaltate precursor into an Ir/CoO/perovskite heterojunction (SCI-350), which served as an active and stable OER electrode. The SCI-350 catalyst exhibited a low overpotential of 240 mV at 10 mA cm-2 in 1 M KOH and superior durability in practical electrolysis for over 150 h. The outstanding activity is preliminarily attributed to the exponentially enlarged electrochemical surface area for charge accumulation, increasing from 3.3 to 175.5 mF cm-2. Moreover, density functional theory calculations combined with advanced spectroscopy and 18O isotope-labeling experiments evidenced the tripled oxygen exchange kinetics, strengthened metal-oxygen hybridization, and engaged lattice oxygen oxidation for O-O coupling on SCI-350. This work presents a promising and feasible strategy for constructing highly active oxide OER electrocatalysts without sacrificing durability.

Passive Gate-Tunable Kinetic Photovoltage along Semiconductor-Water Interfaces.

Moving boundaries of electric double layer at solid-liquid interface enables unprecedented persistent energy conversion and provokes a kinetic photovoltaic effect by moving an illumination region along the semiconductor-water interface. Here, we report a transistor-inspired gate modulation of kinetic photovoltage by applying a bias at the semiconductor-water interface. The kinetic photovoltage of both p-type and n-type silicon samples can be facilely switched on/off, stemming from the electrical-field-modulated surface band bending. In contrast to the function of solid-state transistors relying on external sources, passive gate modulation of the kinetic photovoltage is achieved simply by introducing a counter electrode with materials of desired electrochemical potential. This architecture provides the ability to modulate the kinetic photovoltage over three orders of magnitude and opens up a new way for self-powered optoelectronic logic devices.

Bioresource Upgrade for Sustainable Energy, Environment, and Biomedicine.

We conceptualize bioresource upgrade for sustainable energy, environment, and biomedicine with a focus on circular economy, sustainability, and carbon neutrality using high availability and low utilization biomass (HALUB). We acme energy-efficient technologies for sustainable energy and material recovery and applications. The technologies of thermochemical conversion (TC), biochemical conversion (BC), electrochemical conversion (EC), and photochemical conversion (PTC) are summarized for HALUB. Microalgal biomass could contribute to a biofuel HHV of 35.72 MJ Kg-1 and total benefit of 749 $/ton biomass via TC. Specific surface area of biochar reached 3000 m2 g-1 via pyrolytic carbonization of waste bean dregs. Lignocellulosic biomass can be effectively converted into bio-stimulants and biofertilizers via BC with a high conversion efficiency of more than 90%. Besides, lignocellulosic biomass can contribute to a current density of 672 mA m-2 via EC. Bioresource can be 100% selectively synthesized via electrocatalysis through EC and PTC. Machine learning, techno-economic analysis, and life cycle analysis are essential to various upgrading approaches of HALUB. Sustainable biomaterials, sustainable living materials and technologies for biomedical and multifunctional applications like nano-catalysis, microfluidic and micro/nanomotors beyond are also highlighted. New techniques and systems for the complete conversion and utilization of HALUB for new energy and materials are further discussed.

Application of Marine Natural Products against Alzheimer's Disease: Past, Present and Future.

Alzheimer's disease (AD), a neurodegenerative disease, is one of the most intractable illnesses which affects the elderly. Clinically manifested as various impairments in memory, language, cognition, visuospatial skills, executive function, etc., the symptoms gradually aggravated over time. The drugs currently used clinically can slow down the deterioration of AD and relieve symptoms but cannot completely cure them. The drugs are mainly acetylcholinesterase inhibitors (AChEI) and non-competitive N-methyl-D-aspartate receptor (NDMAR) antagonists. The pathogenesis of AD is inconclusive, but it is often associated with the expression of beta-amyloid. Abnormal deposition of amyloid and hyperphosphorylation of tau protein in the brain have been key targets for past, current, and future drug development for the disease. At present, researchers are paying more and more attention to excavate natural compounds which can be effective against Alzheimer's disease and other neurodegenerative pathologies. Marine natural products have been demonstrated to be the most prospective candidates of these compounds, and some have presented significant neuroprotection functions. Consequently, we intend to describe the potential effect of bioactive compounds derived from marine organisms, including polysaccharides, carotenoids, polyphenols, sterols and alkaloids as drug candidates, to further discover novel and efficacious drug compounds which are effective against AD.

High-Entropy Perovskite Oxide: A New Opportunity for Developing Highly Active and Durable Air Electrode for Reversible Protonic Ceramic Electrochemical Cells.

Reversible proton ceramic electrochemical cell (R-PCEC) is regarded as the most promising energy conversion device, which can realize efficient mutual conversion of electrical and chemical energy and to solve the problem of large-scale energy storage. However, the development of robust electrodes with high catalytic activity is the main bottleneck for the commercialization of R-PCECs. Here, a novel type of high-entropy perovskite oxide consisting of six equimolar metals in the A-site, Pr1/6La1/6Nd1/6Ba1/6Sr1/6Ca1/6CoO3-δ (PLNBSCC), is reported as a high-performance bifunctional air electrode for R-PCEC. By harnessing the unique functionalities of multiple elements, high-entropy perovskite oxide can be anticipated to accelerate reaction rates in both fuel cell and electrolysis modes. Especially, an R-PCEC utilizing the PLNBSCC air electrode achieves exceptional electrochemical performances, demonstrating a peak power density of 1.21 W cm-2 for the fuel cell, while simultaneously obtaining an astonishing current density of - 1.95 A cm-2 at an electrolysis voltage of 1.3 V and a temperature of 600 °C. The significantly enhanced electrochemical performance and durability of the PLNBSCC air electrode is attributed mainly to the high electrons/ions conductivity, fast hydration reactivity and high configurational entropy. This research explores to a new avenue to develop optimally active and stable air electrodes for R-PCECs.

A Novel Wearable Soft Glove for Hand Rehabilitation and Assistive Grasping.

In order to assist patients with finger rehabilitation training and grasping objects, we propose a new type of soft rehabilitation gloves (SRGs), which has both flexion/extension and abduction/adduction movement function for every finger. This paper describes the structure design of the bending actuator and rotating actuator, the fabrication process of the soft actuator, and the implementation of the soft wearable gloves based on a fabric glove. FEM simulation analysis and experiments were conducted to characterize the mechanical behavior and performance of the soft glove in terms of the angle output and force output upon pressurization. To operate this soft wearable glove, we designed the hardware system for SRGs with a flexible strain sensor and force sensor in the loop and introduced a force/position hybrid PID control algorithm to regulate the pressure inputted. Experiment evaluation focused on rehabilitation training gestures; motions and the precise grasping assistance function were executed. The rotating actuator between each finger can supply abduction/adduction motion manner for patients, which will improve rehabilitation effect. The experimental results demonstrated that the developed SRGs have the potential to improve hand movement freedom and the range of grasping successfully.

Model Analysis and Experimental Investigation of Soft Pneumatic Manipulator for Fruit Grasping.

With the superior ductility and flexibility brought by compliant bodies, soft manipulators provide a nondestructive manner to grasp delicate objects, which has been developing gradually as a rising focus of soft robots. However, the unexpected phenomenon caused by environmental effects, leading to high internal nonlinearity and unpredictable deformation, makes it challenging to design, model, and control soft manipulators. In this paper, we designed a soft pneumatically actuated manipulator consisting of four soft actuators, as well as a flange, and investigated the influence of structural parameters on the output characteristics of the manipulator through finite element analysis (FEA). To enhance the bending deformation of the soft actuator, annular rings were employed on the soft actuator. A mathematical model for the bending deformation of air cavities was established to explore the relationship between the driving pressure and the bending angle based on the Yeoh strain energy function. Moreover, an end-output force model was established to depict the variation of the force output with the bending angle of the soft actuator, which was then experimentally validated by adopting the manufactured manipulator. The soft actuator studied in this paper can bend from 0° to 110° under an applied pressure of 0-60 kPa, and the maximum grasping load of the soft manipulator is 5.8 N. Finally, practical tests were conducted to assess the adaptability of the soft manipulator when grasping delicate fruits, such as apples, pears, tomatoes, and mangoes, demonstrating its broad application prospects in nondestructive fruit harvesting.

Ultrafast rectifying counter-directional transport of proton and metal ions in metal-organic framework-based nanochannels.

Bioinspired control of ion transport at the subnanoscale has become a major focus in the fields of nanofluidics and membrane separation. It is fundamentally important to achieve rectifying ion-specific transport in artificial ion channels, but it remains a challenge. Here, we report a previously unidentified metal-organic framework nanochannel (MOF NC) nanofluidic system to achieve unidirectional ultrafast counter-directional transport of alkaline metal ions and proton. This highly effective ion-specific rectifying transport behavior is attributed to two distinct mechanisms for metal ions and proton, elucidated by theoretical simulations. Notably, the MOF NC exhibits ultrafast proton conduction stemming from ultrahigh proton mobility, i.e., 11.3 × 10-7 m2 /V·s, and low energy barrier of 0.075 eV in MIL-53-COOH subnanochannels. Furthermore, the MOF NC shows excellent osmotic power-harvesting performance in reverse electrodialysis. This work expects to inspire further research into multifunctional biomimetic ion channels for advanced nanofluidics, biomimetics, and separation applications.

Hydrogen spillover in complex oxide multifunctional sites improves acidic hydrogen evolution electrocatalysis.

Improving the catalytic efficiency of platinum for the hydrogen evolution reaction is valuable for water splitting technologies. Hydrogen spillover has emerged as a new strategy in designing binary-component Pt/support electrocatalysts. However, such binary catalysts often suffer from a long reaction pathway, undesirable interfacial barrier, and complicated synthetic processes. Here we report a single-phase complex oxide La2Sr2PtO7+δ as a high-performance hydrogen evolution electrocatalyst in acidic media utilizing an atomic-scale hydrogen spillover effect between multifunctional catalytic sites. With insights from comprehensive experiments and theoretical calculations, the overall hydrogen evolution pathway proceeds along three steps: fast proton adsorption on O site, facile hydrogen migration from O site to Pt site via thermoneutral La-Pt bridge site serving as the mediator, and favorable H2 desorption on Pt site. Benefiting from this catalytic process, the resulting La2Sr2PtO7+δ exhibits a low overpotential of 13 mV at 10 mA cm-2, a small Tafel slope of 22 mV dec-1, an enhanced intrinsic activity, and a greater durability than commercial Pt black catalyst.

Carbon Black/PDMS Based Flexible Capacitive Tactile Sensor for Multi-Directional Force Sensing.

Flexible sensing tends to be widely exploited in the process of human-computer interactions of intelligent robots for its contact compliance and environmental adaptability. A novel flexible capacitive tactile sensor was proposed for multi-directional force sensing, which is based on carbon black/polydimethylsiloxane (PDMS) composite dielectric layer and upper and lower electrodes of carbon nanotubes/polydimethylsiloxane (CNTs/PDMS) composite layer. By changing the ratio of carbon black, the resolution of carbon black/PDMS composite layer increases at 4 wt%, and then decreases, which was explained according to the percolation theory of the conductive particles in the polymer matrix. Mathematical model of force and capacitance variance was established, which can be used to predict the value of the applied force. Then, the prototype with carbon black/PDMS composite dielectric layer was fabricated and characterized. SEM observation was conducted and a ratio was introduced in the composites material design. It was concluded that the resolution of carbon sensor can reach 0.1 N within 50 N in normal direction and 0.2 N in 0-10 N in tangential direction with good stability. Finally, the multi-directional force results were obtained. Compared with the individual directional force results, the output capacitance value of multi-directional force was lower, which indicated the amplitude decrease in capacity change in the normal and tangential direction. This might be caused by the deformation distribution in the normal and tangential direction under multi-directional force.

Atomic cerium modulated palladium nanoclusters exsolved ferrite catalysts for lean methane conversion.

The active and stable palladium (Pd) based catalysts for CH4 conversion are of great environmental and industrial significance. Herein, we employed N2 as an optimal activation agent to develop a Pd nanocluster exsolved Ce-incorporated perovskite ferrite catalyst toward lean methane oxidation. Replacing the traditional initiator of H2, the N2 was found as an effective driving force to selectively touch off the surface exsolution of Pd nanocluster from perovskite framework without deteriorating the overall material robustness. The catalyst showed an outstanding T50 (temperature of 50% conversion) plummeting down to 350°C, outperforming the pristine and H2-activated counterparts. Further, the combined theoretical and experimental results also deciphered the crucial role that the atomically dispersed Ce ions played in both construction of active sites and CH4 conversion. The isolated Ce located at the A-site of perovskite framework facilitated the thermodynamic and kinetics of the Pd exsolution process, lowering its formation temperature and promoting its quantity. Moreover, the incorporation of Ce lowered the energy barrier for cleavage of C─H bond, and was dedicated to the preservation of highly reactive PdOx moieties during stability measurement. This work successfully ventures uncharted territory of in situ exsolution to provide a new design thinking for a highly performed catalytic interface.

Cation-Deficiency-Dependent CO2 Electroreduction over Copper-Based Ruddlesden-Popper Perovskite Oxides.

We report an effective strategy to enhance CO2 electroreduction (CER) properties of Cu-based Ruddlesden-Popper (RP) perovskite oxides by engineering their A-site cation deficiencies. With La2-x CuO4-δ (L2-x C, x=0, 0.1, 0.2, and 0.3) as proof-of-concept catalysts, we demonstrate that their CER activity and selectivity (to C2+ or CH4 ) show either a volcano-type or an inverted volcano-type dependence on the x values, with the extreme point at x=0.1. Among them, at -1.4 V, the L1.9 C delivers the optimal activity (51.3 mA cm-2 ) and selectivity (41.5 %) for C2+ , comparable to or better than those of most reported Cu-based oxides, while the L1.7 C exhibits the best activity (25.1 mA cm-2 ) and selectivity (22.1 %) for CH4 . Such optimized CER properties could be ascribed to the favorable merits brought by the cation-deficiency-induced oxygen vacancies and/or CuO/RP hybrids, including the facilitated adsorption/activation of key reaction species and thus the manipulated reaction pathways.

Research on Classification Model of Panax notoginseng Taproots Based on Machine Vision Feature Fusion.

The existing classification methods for Panax notoginseng taproots suffer from low accuracy, low efficiency, and poor stability. In this study, a classification model based on image feature fusion is established for Panax notoginseng taproots. The images of Panax notoginseng taproots collected in the experiment are preprocessed by Gaussian filtering, binarization, and morphological methods. Then, a total of 40 features are extracted, including size and shape features, HSV and RGB color features, and texture features. Through BP neural network, extreme learning machine (ELM), and support vector machine (SVM) models, the importance of color, texture, and fusion features for the classification of the main roots of Panax notoginseng is verified. Among the three models, the SVM model performs the best, achieving an accuracy of 92.037% on the prediction set. Next, iterative retaining information variables (IRIVs), variable iterative space shrinkage approach (VISSA), and stepwise regression analysis (SRA) are used to reduce the dimension of all the features. Finally, a traditional machine learning SVM model based on feature selection and a deep learning model based on semantic segmentation are established. With the model size of only 125 kb and the training time of 3.4 s, the IRIV-SVM model achieves an accuracy of 95.370% on the test set, so IRIV-SVM is selected as the main root classification model for Panax notoginseng. After being optimized by the gray wolf optimizer, the IRIV-GWO-SVM model achieves the highest classification accuracy of 98.704% on the test set. The study results of this paper provide a basis for developing online classification methods of Panax notoginseng with different grades in actual production.

Tuning Reconstruction Level of Precatalysts to Design Advanced Oxygen Evolution Electrocatalysts.

Surface reconstruction engineering is an effective strategy to promote the catalytic activities of electrocatalysts, especially for water oxidation. Taking advantage of the physicochemical properties of precatalysts by manipulating their structural self-reconstruction levels provide a promising methodology for achieving suitable catalysts. In this review, we focus on recent advances in research related to the rational control of the process and level of surface transformation ultimately to design advanced oxygen evolution electrocatalysts. We start by discussing the original contributions to surface changes during electrochemical reactions and related factors that can influence the electrocatalytic properties of materials. We then present an overview of current developments and a summary of recently proposed strategies to boost electrochemical performance outcomes by the controlling structural self-reconstruction process. By conveying these insights, processes, general trends, and challenges, this review will further our understanding of surface reconstruction processes and facilitate the development of high-performance electrocatalysts beyond water oxidation.