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High-temperature affordable flexible polymer-based pressure sensors integrated with repeatable early fire warning service are strongly desired for harsh environmental applications, yet their creation remains challenging. This work proposed an approach for preparing such advanced integrated sensors based on silver nanoparticles and an ammonium polyphosphate (APP)-modified laminar-structured bulk wood sponge (APP/Ag@WS). Such integrated sensors demonstrated excellent fire warning performance, including a short response time (minimum of 0.44 s), a long-lasting alarm time (>750 s), and reliable repeatability. Moreover, it achieved high-temperature affordable flexible pressure sensing that exhibited an almost unimpaired working range of 0–7.5 kPa and a higher sensitivity (in the low-pressure range, maximum to 226.03 kPa–1) after fire. The high stability was attributed to reliable structural elasticity, and the wood-derived amorphous carbon is capable of repeatable fire warnings. Finally, a Ag@APP/WS-based wireless fire alarm system that realized reliable house fire accident detection was demonstrated, showing great promise for smart firefighting application.

The cause of epilepsy with or without developmental disorders was unidentified in a significant proportion of patients. Whole exome sequencing was performed in three unrelated patients with early-onset epilepsy, with or without developmental delay and intellectual disability. We identified de novo heterozygous variants (p.Arg119Trp, p.Val99_Ser102del, c.260_263 + 11delinsGCCCA) in the ATP6V0Cgene, which encodes a subunit of vacuolar ATPase. Three-dimensional protein modeling showed that the variant p.Arg119Trp in ATP6V0C affected the hydrogen bonds with the 115thand 123rdresidues, and the protein stability. The p.Val99_Ser102del and c.260_263 + 11delinsGCCCA variants in the other two patients resulted in a loss of function with microdeletion or splicing effects. Their seizures and psychomotor developmental outcomes were different, and all patients had a good prognosis. Our study provides evidence that de novo heterozygous ATP6V0Cvariants are related to epilepsy and associated with or without developmental delay.

In digital cameras, we find a major limitation: the image and video form inherited from a film camera obstructs it from capturing the rapidly changing photonic world. Here, we present vform, a bit sequence array where each bit represents whether the accumulation of photons has reached a threshold, to record and reconstruct the scene radiance at any moment. By employing only consumer-level complementary metal–oxide semiconductor (CMOS) sensors and integrated circuits, we have developed a spike camera that is 1000× faster than conventional cameras. By treating vform as spike trains in biological vision, we have further developed a spiking neural network (SNN)-based machine vision system that combines the speed of the machine and the mechanism of biological vision, achieving high-speed object detection and tracking 1000× faster than human vision. We demonstrate the utility of the spike camera and the super vision system in an assistant referee and target pointing system. Our study is expected to fundamentally revolutionize the image and video concepts and related industries, including photography, movies, and visual media, and to unseal a new SNN-enabled speed-free machine vision era.

Metal ions on surfaces of various materials as bulk matrices, doped structural units, or functionalized active sites play critical roles in the establishment of physical and chemical properties. Characterization of surface-bound metal ions and metal ion-coupled electron transfer are urgently needed for the determination of material structures as well as for understanding the relationship to macroscopic properties and technological applications. We present here a mass spectrometric (MS) technique that allows the monitoring of metal ion-coupled electron transfer along with spatial distributions, identities, quantities, valences, redox activities, and associated anions. It is based on the coordination of metal ions with chelators that are redox/photo active. Upon the irradiation of a focused laser beam, metal ions on material surfaces that are covered with chelators are evaporated, ionized, and detected with MS. This technique clearly reveals ligand–metal/metal–ligand and ligand-bridged electron transfers through MS or tandem MS/MS experiments. MS images of metal ions on material surfaces with the spatial resolution down to the sub-micrometer level have been obtained. It has been applied to the monitoring of hot electron transfer, leftover positive metal ions in localized surface plasmon resonance, and photocatalytic activities of crystalline facets of TiO2.

Lipids represent a large family of compounds with highly diverse structures that are involved in complex biological processes. A photocatalytic technique of on-tissue epoxidation of C=C double bonds has been developed for in situ mass spectrometric identification and spatial imaging of positional isomers of lipids. It is based on the plasmonic hot-electron transfer from irradiated gold nanowires to redox-active organic matrix compounds that undergo bond cleavages and generate hydroxyl radicals in nanoseconds. Intermediate radical anions and negative fragment ions have been unambiguously identified. Under the irradiation of a pulsed laser of the third harmonic of Nd3+:YAG (355 nm), the hydroxyl radical-driven epoxidation of unsaturated lipids with different numbers of C=C bonds can be completed in nanoseconds with high yields of up to 95%. Locations of C=C bonds were recognized with diagnostic fragment ions that were produced by either collision with an inert gas or auto-fragmentation resulting from the impact of energetic hot electrons and vibrational excitation. This technique has been applied to the analysis of breast cancer tissues of mice models without extensive sample processes. It was experimentally demonstrated that C=C bonds may be formed at different positions of not only regular mono- or poly-unsaturated fatty acids but also other odd-numbered long-chain fatty acids.

The quality of Chinese herbal medicine (CHM) raw materials is essential, and mass spectrometry (MS)-based technologies have been playing key roles in the quality control of CHMs. However, the use of miniature mass spectrometry (mini-MS) for quality control of CHMs has rarely been reported. In this work, we developed a rapid analytical method for the quality evaluation of CHMs based on paper spray ionization (PSI)-mini-MS/MS. The quality evaluation of Lygodium japonicum(Thunb.) Sw. was used as an example. Following a “multi-component” quality evaluation strategy, nine active constituents of L. japonicumwere selected to be used as analytes for quality control. We confirmed that the precursor–product ion information in the MS/MS spectra of each analyte in the herbal extracts was consistent with the standards. Also, we developed a mini-MS-based quantitative method for each analyte using its quantification ion. The quantitative methodology was rigorously validated using quality control samples. Finally, the quality evaluation of L. japonicumwas carried out using the established MS/MS method combined with statistical analysis. A wide range of common quality issues with L. japonicumcan be effectively determined, including whether it is adulterated with sand and distinguishing among different parts and species. This study demonstrates that mini-MS for quality evaluation of CHMs is feasible. Mini-MS for quality evaluation of herbal medicines will potentially have a good prospect due to its many advantages such as low cost, low power consumption, and portability in the future.

BackgroundAlthough retinitis pigmentosa (RP) is the most common type of hereditary retinal dystrophy, approximately 25%–45% of cases remain without a molecular diagnosis. von Willebrand factor A domain containing 8 (VWA8) encodes a mitochondrial matrix-targeted protein; its molecular function and pathogenic mechanism in RP remain unexplained.MethodsFamily members of patients with RP underwent ophthalmic examinations, and peripheral blood samples were collected for exome sequencing, ophthalmic targeted sequencing panel and Sanger sequencing. The importance of VWA8in retinal development was demonstrated by a zebrafish knockdown model and cellular and molecular analysis.ResultsThis study recruited a Chinese family of 24 individuals with autosomal-dominant RP and conducted detailed ophthalmic examinations. Exome sequencing analysis of six patients revealed heterozygous variants in VWA8, namely, the missense variant c.3070G>A (p.Gly1024Arg) and nonsense c.4558C>T (p.Arg1520Ter). Furthermore, VWA8expression was significantly decreased both at the mRNA and protein levels. The phenotypes of zebrafish with VWA8knockdown are similar to those of clinical individuals harbouring VWA8variants. Moreover, VWA8defects led to severe mitochondrial damage, resulting in excessive mitophagy and the activation of apoptosis.ConclusionsVWA8plays a significant role in retinal development and visual function. This finding may provide new insights into RP pathogenesis and potential genes for molecular diagnosis and targeted therapy.

Simple saccharides have a variety of biological functions, but their structural diversity and inherent structural features pose a major challenge for rapid analysis. In this work, we developed a derivative-free and ion mobility-free method for the rapid analysis of monosaccharides and disaccharides using paper spray tandem mass spectrometry. Trimeric cluster ions consisting of saccharide analytes, ligands and transition metal ions are used as precursor ions. We defined the R-value as the ratio of the intensity of the product ion that loses one molecule of ligand over the intensity of the product ion that loses one molecule of saccharide viacollision induced dissociation (CID). The species and conformation of simple saccharides can be easily differentiated by calculating this R-value. With the capability of directly analyzing clinical samples using paper spray ionization, our method can be used to rapidly quantify the molar ratio of galactose to glucose in dried plasma samples to aid in the diagnosis of galactosemia. The analytical strategy provided herein has good potential to be applied to a wide range of saccharide analysis applications in the future.

Burns often cause loss of skin barrier protection, fluid exudation, and local tissue edema, which hinder functional recovery. Effectively improving the quality of deep burn wound healing, shortening the wound healing time, and reducing tissue fluid leakage are urgent problems in the medical field. Human mesenchymal stem cells (MSCs) can effectively stabilize vascular endothelial injury. Fetal dermal MSCs (FDMSCs) are a newly discovered source of MSCs derived from the skin of accidentally aborted fetuses. However, the effect of FDMSCs on vascular permeability remains poorly understood. In this study, conditioned media from FDMSCs (F-CM) extracted from fetal skin tissue was prepared. The effect of F-CM on vascular permeability was evaluated using the internal circulation method FITC-dextran in vivo, and several in vitro assays, including cell viability assay, transwell permeability test, immunofluorescence, and western blotting. Altogether, our results demonstrate that F-CM could inhibit burn-induced microvascular hyperpermeability by increasing the protein expression levels of occludin and VE-cadherin, while restoring the expression of endothelial F-actin, and providing the foundation of a novel therapy for the treatment of burns with F-CM.

Purpose: Frailty and Circadian Syndrome (CircS) are prevalent among the elderly, yet the link between them remains underexplored. This study aims to examine the association between CircS and frailty, particularly focusing on the impact of various CircS components on frailty. Materials and methods: We conducted a cross-sectional analysis using data from the National Health and Nutrition Examination Survey (NHANES) spanning 2007 to 2018. The 49-item Frailty Index (FI) was employed to assess frailty. To understand the prevalence of CircS in relation to frailty, we applied three multivariate logistic regression models. Additionally, subgroup and interaction analyses were performed to investigate potential modifying factors. Results: The study included 8,569 participants. In fully adjusted models, individuals with CircS showed a significantly higher risk of frailty compared to those without CircS (Odds Ratio [OR] = 2.18, 95% Confidence Interval [CI]: 1.91–2.49, p< 0.001). A trend of increasing frailty risk with greater CircS component was observed (trend test p< 0.001). Age (p= 0.01) and race (p= 0.02) interactions notably influenced this association, although the direction of effect was consistent across subgroups. Sensitivity analysis further confirmed the strength of this relationship. Conclusion: This study identifies a strong positive correlation between CircS and frailty in the elderly. The risk of frailty escalates with an increasing number of CircS components. These findings highlight the intricate interplay between circadian syndrome and frailty in older adults, offering valuable insights for developing targeted prevention and intervention strategies.

A cell-based ambient Venturi autosampling device was established for the monitoring of dynamic cell secretions in response to chemical stimulations in real time with temporal resolution on the order of a second. Detection of secretory products of cells and screening of bioactive compounds are primarily performed on an ambient autosampling probe and matrix-assisted laser desorption ionization (MALDI) mass spectrometry. It takes advantage of the Venturi effect in which the fluid flowing through an inlet capillary tube is automatically fed into a parallel array of multiple outlet capillaries. Cells are incubated inside the inlet capillary tube that is connected with either a syringe pump or liquid chromatography (LC) for the transfer of single compounds or mixtures, respectively. Secretory products were continuously pushed into the outlet capillaries and then spotted into a compressed thin film of the matrix material 9-aminoacridine for MALDI mass spectrometric imaging. In physiological pH, without the use of high voltages and without the use of chemical derivatizations, this platform can be applied to the direct assay of neurotransmitters or other secretory products released from cells in response to the stimulation of individual compounds or LC-separated eluates of natural mixtures. It provides a new way to identify bioactive compounds with a detection limit down to 0.04 fmol/pixel.

Protonation/deprotonation is the well-recognized mass spectrometric mechanism in matrix-assisted laser desorption ionization of organic molecules but not for metal ions with different oxidation states. We describe herein a soft evaporation and ionization technique for metal ions based on iodination/de-iodination in metal–iodide cluster ionization (MICI). It is not only able to determine identities and oxidation states of metal ions but also reveal spatial distributions and isotope ratios in response to physiological or environmental changes. A long chain alcohol 1-tetradecanol with no functional groups that can absorb laser irradiation was used to cover and prevent samples from direct laser ablation. Upon the irradiation of the third harmonic Nd3+:YAG (355 nm, 3 ns), iohexol containing three covalently bonded iodine atoms instantly generates negative iodide ions that can quantitatively form clusters with at least 14 essential metal ions present in plants. The detection limits vary with different metal ions down to low fmol. MICI eliminates the atomization process that obscures metal charges in inductively coupled plasma mass spectrometry. Because only metal ions can be iodinated with iohexol, interferences from the abundant organic molecules of plants that are confronted by secondary ion mass spectrometry (SIMS) are also greatly decreased.

The performance of terahertz (THz) detectors based on two-dimensional electron gas (2DEG) with the aid of a subwavelength gratings coupler depends critically on the amplitude difference of an electric field with positive and negative scattering orders. An efficient method was proposed to enhance the current response of the AlGaN/GaN material in the frequency range from 0 to 5 THz under oblique incidence of THz radiation with asymmetric gratings, where the optimal incidence angle exists. The case of symmetric gratings was also studied for comparison. The results will be useful for the theoretical and experimental optimization of grating-assisted THz detectors without electrical bias.

A neuroprosthesis is a type of precision medical device that is intended to manipulate the neuronal signals of the brain in a closed-loop fashion, while simultaneously receiving stimuli from the environment and controlling some part of a human brain or body. Incoming visual information can be processed by the brain in millisecond intervals. The retina computes visual scenes and sends its output to the cortex in the form of neuronal spikes for further computation. Thus, the neuronal signal of interest for a retinal neuroprosthesis is the neuronal spike. Closed-loop computation in a neuroprosthesis includes two stages: encoding a stimulus as a neuronal signal, and decoding it back into a stimulus. In this paper, we review some of the recent progress that has been achieved in visual computation models that use spikes to analyze natural scenes that include static images and dynamic videos. We hypothesize that in order to obtain a better understanding of the computational principles in the retina, a hypercircuit view of the retina is necessary, in which the different functional network motifs that have been revealed in the cortex neuronal network are taken into consideration when interacting with the retina. The different building blocks of the retina, which include a diversity of cell types and synaptic connections—both chemical synapses and electrical synapses (gap junctions)—make the retina an ideal neuronal network for adapting the computational techniques that have been developed in artificial intelligence to model the encoding and decoding of visual scenes. An overall systems approach to visual computation with neuronal spikes is necessary in order to advance the next generation of retinal neuroprosthesis as an artificial visual system.

Metal-organic frameworks (MOFs) provide great prospective in the photodegradation of pollutants. Nevertheless, the poor separation and recovery hamper their pilot- or industrial-scare applications because of their microcrystalline features. Herein, this challenge can be tackled by integrating Cu-MOFs into an alginate substrate to offer environmentally friendly, sustainable, facile separation, and high-performance MOF-based hydrogel photocatalysis platforms. The CuII-MOF 1and CuI-MOF 2were initially synthesized through a direct diffusion and single-crystal to single-crystal (SCSC) transformation method, respectively, and after the immobilization into alginate, more effective pollutant decontamination was achieved viathe synergistic effect of the adsorption feature of hydrogel and in situphotodegradation of Cu-MOFs. Specifically, Cu-MOF-alginate composites present an improved and nearly completed Cr(VI) elimination at a short time of 15-25 min. Additionally, the congo red (CR) decolorization can be effectively enhanced in the presence of Cr(VI), and 1-alginate showed superior simultaneous decontamination efficiency of CR and Cr(VI) with 99% and 78%, respectively. Furthermore, Cu-MOF-alginate composites can maintain a high pollutant removal after over 10 continuous cycles (95% for CR after 14 runs, and 90% for Cr(VI) after 10 runs). Moreover, the Cr(VI)/CR degradation mechanism for Cu-MOF-alginate composite was investigated.

Lead halide perovskites with good optoelectronic properties and high attenuation of high-energy radiation are great candidates for X-ray radiation detectors. Large area, dense, and thick films or wafers are a prerequisite for these applications. In this paper, a one-step heat-assisted high-pressure press method is developed to directly prepare a large (the largest has a diameter of 80 mm) and thickness- and shape-controlled phase-pure organic–inorganic hybrid CH3NH3PbI3wafer of densely packed large microcrystals from raw powder materials. Meanwhile, this method uses no solvent to achieve essentially 100% material utilization. The obtained wafers show good ambipolar carrier mobilities of ∼20 cm2V–1s–1and a μτproduct as high as 3.84 × 10–4cm2V–1. Under an X-ray source using an acceleration voltage of 40 kV, the perovskite wafer-based X-ray detector shows an X-ray sensitivity as large as 1.22 × 105μC Gyair–1cm–2under a 10 V bias, the highest reported for any perovskite material. The method provides a convenient strategy for producing large perovskite wafers with good optoelectronic properties, which will facilitate the development of large perovskite devices.

Malware is an intentionally created malicious software that still poses a serious threat in cyberspace. Android malware has become one of the most significant online threats in recent years due to its increase in prevalence. Even though a lot of work has gone into identifying and categorizing Android malware, problems including data theft, difficulties identifying Android malware, and time-consuming detection remain unresolved. To overcome this issue, this paper proposed a Deep Learning (DL) Based Malware Attack DetectoR in Android Smartphones using LinkNET (MADRAS-NET) which effectively detects and mitigates the types of malwares in Android devices. The Max Abs Scaler receives a set of data as input first for pre-processing. Following pre-processing, the output is sent to LinkNET for classification. LinkNET uses the pre-processed data to identify malware, and then divides the output into three groups: real users, Penetho malware, and FakeAV malware. Lastly, the AndMal2020 dataset, which detects and classifies malware as well as malware families, is used to evaluate the suggested MADRAS-NET approach. The suggested LinkNET achieves a maximum accuracy of 99.81%, while other models, such as the Deep Belief Network (DBN) at 96.75%, the Generative Adversarial Network (GAN) at 94.42%, and the Long Short Term Memory Network (LSTM) at 93.11%, achieve similar results. The comparison of the MADRAS-NET model with the LSTM, GAN, and DBN frameworks indicates its better performance.

Sol–gel silica doped with different amount of sec-octylphenoxyl acetic acid (CA12) was prepared using sol–gel method and characterized by scanning electron microscopy and thermogravimetric analysis. The adsorption behavior of methylene blue (MB) from aqueous solution onto sol–gel silica doped with CA12 (SSC) was studied. Batch experiments were carried out to measure the adsorption as a function of equilibrium time, pH of the solution, initial MB concentration and temperature. The results showed that the contents of CA12 were 0, 4.4%, 5.1% and 7.5% for SSC-0, SSC-1, SSC-2 and SSC-3, respectively. The adsorption equilibrium was reached within 8 h for SSC-0, 5 h for SSC-1, 2 h for SSC-2 and SSC-3. With the increase of the content of CA12, the equilibrium time decreased, which may be due to their increased pore structure. Both the pseudo-first-order and pseudo-second-order kinetics models fitted the data well. The higher adsorption amount was found at neutral and basic conditions, and the lower adsorption amount was found at lower pH. The adsorption data for MB on SSC were consistent with the Langmuir isotherm equation. The maximum adsorption capacities of MB on SSC-0, SSC-1, SSC-2 and SSC-3 were 23.8, 32.4, 46.3 and 65.9 mg g–1, respectively. The thermodynamics properties indicated that the adsorption processes were spontaneous and endothermic nature.

Finding the complete functional circuits of neurons is a challenging problem in brain research. Here, we present a protocol, based on visual stimuli and spikes, for obtaining the complete circuit of recorded neurons using spike-triggered nonnegative matrix factorization. We describe steps for data preprocessing, inferring the spatial receptive field of the subunits, and analyzing the module matrix. This approach identifies computational components of the feedforward network of retinal ganglion cells and dissects the network structure based on natural image stimuli.

To screen active constituents of traditional Chinese medicines (TCMs) as potential virulence inhibitors of Salmonellapathogenicity island III (SPI-3).

Background: Due to the tradition of carbohydrate-rich diet, challenges exist for ketogenic diet (KD) implementation in Northwest China. This study was aimed to investigate the efficacy and tolerability of KD therapy administered with gradual initiation protocols in Chinese children with pharmacoresistant epilepsy in Northwest China. Methods: In this single-center study, 55 children with drug-resistant epilepsy were enrolled from June 2013 to June 2019. The efficacy of KD, reasons for discontinuation, duration of retention and rate of adverse events were evaluated. Results: Fifty-five children aged from 2.2 months to 169.7 months were included, with a median age at KD initiation of 14.1 months, and 32 cases (58.2%) responded to the diet therapy at the last contact. The responder rates were 16.4% (9/55), 36.4% (20/55), 30.9% (17/55), 27.3% (15/55) at 1, 3, 6 and 12 months, respectively. Univariate analysis indicated that the duration of epilepsy and the duration of KD therapy were predictors for KD effectiveness. Poor compliance and lack of response were main reasons for discontinuation of KD. There are a few side effects of KD, most of which were minor. Conclusions: The KD therapy with a gradual-initiation protocol is effective and tolerable for children with drug-resistant epilepsy in Northwest China. Early start of KD and KD duration of more than 6 months may be predictive factors for KD efficacy.

Coronary artery disease (CAD) is a cardiovascular disease characterized by atherosclerosis, angiogenesis, thrombogenesis, inflammation, etc. Xintong granule (XTG) is considered a practical therapeutic strategy in China for CAD. Although its therapeutic role in CAD has been reported, the molecular mechanisms of XTG in CAD have not yet been explored.A network pharmacology approach including drug-likeness (DL) evaluation, oral bioavailability (OB) prediction, protein-protein interaction (PPI) network construction and analysis, and Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses was used to predict the active ingredients, potential targets, and molecular mechanisms of XTG associated with the treatment of CAD. Molecular docking analysis was performed to investigate the interactions between the active compounds and the underlying targets.Fifty-one active ingredients of XTG and 294 CAD-related targets were screened for analysis. Gene Ontology enrichment analysis showed that the therapeutic targets of XTG in CAD are mainly involved in blood circulation and vascular regulation. KEGG pathway analysis indicated that XTG intervenes in CAD mainly through the regulation of fluid shear stress and atherosclerosis, the AGE-RAGE signaling pathway in diabetic complications, and the relaxin signaling pathway. Molecular docking analysis showed that each key active ingredient (quercetin, luteolin, kaempferol, stigmasterol, resveratrol, fisetin, gamma-sitosterol, and beta-sitosterol) of XTG can bind to the core targets of CAD (AKT1, JUN, RELA, MAPK8, NFKB1, EDN1, and NOS3).The present study revealed the CAD treatment-related active ingredients, underlying targets, and potential molecular mechanisms of XTG acting by regulating fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, and relaxin signaling pathway.

Background: Umbilical cord-derived mesenchymal stem cells (UC-MSCs) are considered to be multipotent mesenchymal stem cells that are easily induced to differentiate into functional osteoblasts both in vitro and in vivo. Osterix (Osx), a novel zinc-⃞nger-containing transcription factor of the Sp family, is required for osteoblast differentiation and bone formation.

A crucial question in data science is to extract meaningful information embedded in high-dimensional data into a low-dimensional set of features that can represent the original data at different levels. Wavelet analysis is a pervasive method for decomposing time-series signals into a few levels with detailed temporal resolution. However, obtained wavelets are intertwined and over-represented across levels for each sample and across different samples within one population. Here, using neuroscience data of simulated spikes, experimental spikes, calcium imaging signals, and human electrocorticography signals, we leveraged conditional mutual information between wavelets for feature selection. The meaningfulness of selected features was verified to decode stimulus or condition with high accuracy yet using only a small set of features. These results provide a new way of wavelet analysis for extracting essential features of the dynamics of spatiotemporal neural data, which then enables to support novel model design of machine learning with representative features.

Zhaofei Yu, a young principal investigator (PI), and Shanshan Jia, a PhD student, explain the importance of data science in their research. They have developed a method to extract information from high-dimensional data based on wavelet decompositions using simulated and experimental neuroscience data. This method is not only beneficial for neuroscientists, but it might also be helpful to anyone who deals with high-dimensional data.

An unmediated hydrogen peroxide (H2O2) biosensor was prepared by co‐immobilizing hemoglobin (Hb) with platinum nanoparticles enhanced poly(chloromethyl thiirane) cross‐linked chitosan (CCCS‐PNs) hybrid film. CCCS could provide a biocompatible microenvironment for Hb and PNs could accelerate the electron transfer between Hb and the electrode. Spectroscopic analysis indicated that the immobilized Hb could maintain its native structure in the CCCS‐PNs hybrid film. Entrapped Hb exhibited direct electrochemistry for its heme Fe(III)/Fe(II) redox couples at −0.396 V in the CCCS‐PNs hybrid film, as well as peroxidase‐like activity to the reduction of hydrogen peroxide without the aid of an electron mediator.

Traditional models of retinal system identification analyze the neural response to artificial stimuli using models consisting of predefined components. The model design is limited to prior knowledge, and the artificial stimuli are too simple to be compared with stimuli processed by the retina. To fill in this gap with an explainable model that reveals how a population of neurons work together to encode the larger field of natural scenes, here we used a deep-learning model for identifying the computational elements of the retinal circuit that contribute to learning the dynamics of natural scenes. Experimental results verify that the recurrent connection plays a key role in encoding complex dynamic visual scenes while learning biological computational underpinnings of the retinal circuit. In addition, the proposed models reveal both the shapes and the locations of the spatiotemporal receptive fields of ganglion cells.

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