Fabrication of Multi-Layered Paper-Based Supercapacitor Anode by Growing Cu(OH)2 Nanorods on Oxygen Functional Groups-Rich Sponge-Like Carbon Fibers.

This work addresses the challenges in developing carbon fiber paper-based supercapacitors (SCs) with high energy density by focusing on the limited capacity of carbon fiber. To overcome this limitation, a sponge-like porous carbon fiber paper enriched with oxygen functional groups (OFGs) is prepared, and Cu(OH)2 nanorods are grown on its surface to construct the SC anode. This design results in a multi-layered carbon fiber paper-based electrode with a specific structure and enhanced capacitance. The Cu(OH)2 @PCFP anode exhibits an areal capacitance of 547.83 mF cm-2 at a current density of 1 mA cm-2 and demonstrates excellent capacitance retention of 99.8% after 10 000 cycles. Theoretical calculations further confirm that the Cu(OH)2 /OFGs-graphite heterostructure exhibits higher conductivity, facilitating faster charge transfer. A solid-state SC is successfully assembled using Ketjen Black@PCFP as the cathode and KOH/PVA as the gel electrolyte. The resulting device exhibits an energy density of 0.21 Wh cm-2 at 1.50 mW cm-2 , surpassing the performance of reported Cu(OH)2 SCs. This approach, combining materials design with an understanding of underlying mechanisms, not only expands the range of electrode materials but also provides valuable insights for the development of high-capacity energy storage devices.

HOXA1 silencing inhibits cisplatin resistance of oral squamous cell carcinoma cells via IκB/NF-κB signaling pathway.

The resistance of oral squamous cell carcinoma (OSCC) cells to cisplatin remains a tough nut to crack in OSCC therapy. Homeobox A1 (HOXA1) overexpression has been detected in head and neck squamous carcinoma (HNSC). Accordingly, this study aims to explore the potential role and mechanism of HOXA1 on cisplatin resistance in OSCC. The expression of HOXA1 in HNSC and its role in overall survival (OS) rate of OSCC patients were analyzed by bioinformatic analysis. Following transfection as needed, OSCC cells were induced by different concentrations of cisplatin, and the cell viability and apoptosis were evaluated by cell counting kit-8 and flow cytometry assays. The mRNA and protein expression levels of HOXA1 and the phosphorylation of IκBα and p65 were determined by real-time quantitative PCR and western blot. HOXA1 expression level was upregulated in HNSC tissues and OSCC cells. Overexpressed HOXA1 was correlated with a low OS rate of OSCC patients. Cisplatin exerted an anti-cancer effect on OSCC cells. HOXA1 silencing or cisplatin suppressed OSCC cell viability, boosted the apoptosis, and repressed the phosphorylation of IκBα and p65. Intriguingly, the combination of HOXA1 silencing and cisplatin generated a stronger anti-cancer effect on OSCC cells than their single use. HOXA1 silencing attenuates cisplatin resistance of OSCC cells via IκB/NF-κB signaling pathway, hinting that HOXA1 is a biomarker associated with OSCC and HOXA1 silencing can enhance the sensitivity of OSCC cells to cisplatin.

Nitrogen-doped-carbon-coated hexagonal cobalt oxyhydroxide/reduced graphene oxide nanocomposite for sensitive and selective detection of nitrite in human hepatoma cells.

Selective and sensitive determination of nitrite is of great importance in practical application. In the present work, a novel nitrite sensing platform was built based on the fabrication of nitrogen-doped-carbon-coated hexagonal cobalt oxyhydroxide (CN@CoOOH) on reduced graphene oxide (RGO) using zeolitic imidazolate framework (ZIF)-67 as a precursor. The CN@CoOOH/RGO nanocomposite was confirmed by UV-visible spectroscopy, Fourier transform infrared spectroscopy, x-ray photoelectron spectrum, transmission electron microscopy, scanning electron microscopy, and x-ray diffraction. We applied the nanocomposite to detect nitrite selectively and sensitively through amperometry for the first time. The anodic current values increased with the addition of nitrite. Therefore, the concentrations of nitrite were quantitatively detected using a CN@CoOOH/RGO based sensor. A wider linear range of 0.1 to 7000 µM was obtained with a lower detection limit of 10 nM (S/N = 3). The proposed method was also applied to detect nitrite released from normal liver cells and human hepatoma cells.

A novel anodic electrochemiluminescence behavior of sulfur-doped carbon nitride nanosheets in the presence of nitrogen-doped carbon dots and its application for detecting folic acid.

The application of carbon dots as a coreactant for Ru(bpy)32+ (where bpy is 2,2'-bipyridine) electrochemiluminescence (ECL) has been widely studied. However, the high cost of Ru(bpy)32+ and its derivatives has prohibited its widespread use in ECL biosensors. Herein, a novel anodic ECL system based on sulfur-doped graphitic carbon nitride nanosheets (S-g-C3N4 NSs) and nitrogen-doped carbon dots (N-CDs) is presented. In this ECL system, N-CDs serve as a new ECL coreactant that can significantly enhance the anodic ECL signal of S-g-C3N4 NSs (approximately 83 times) under optimal conditions. The possible ECL response mechanism of the S-g-C3N4 NSs/N-CDs system is proposed in detail on the basis of cyclic voltammograms, ECL-time curves, and ECL spectra. Furthermore, the ECL signal of the S-g-C3N4 NSs/N-CDs system was quenched by folic acid (FA), which was chosen as a model analyte to study the potential application of the new ECL system. The ECL intensity decreased linearly with the concentration of FA in the range from 0.05 to 200 µM. The detection limit for FA measurement is 16 nM (signal-to-noise ratio of 3). The proposed new ECL system has many advantages over traditional approaches, such as low toxicity and excellent biocompatibility. Especially, the proposed approach can detect FA in diluted human serum samples with satisfactory recoveries, indicating promising application for bioanalysis. Graphical abstract.

Access to C4-Functionalized Quinolines via Copper-Catalyzed Tandem Annulation of Alkynyl Imines with Diazo Compounds.

An efficient synthesis of C4-functionalized quinolines through copper-catalyzed tandem annulation of alkynyl imines with diazo compounds is described. This transformation involves an in situ formation of allene and intramolecular electrocyclization, which features high efficiency, mild reaction conditions, easy operation, and broad functional-group tolerance. A wide variety of C4-functionalized quinolines were provided in up to 92% yield for 33 examples.

A layer discrete particle based soft contact model in corroded rebar monitoring using linear and nonlinear ultrasonic guided waves.

In offshore reinforced concrete (RC) structures, the phenomenon of rebar corrosion is widespread, seriously threatening the durability of the structures. However, the issue of rebar corrosion detection especially for the early corrosion situation is also challengeable. It is of great significance to use ultrasonic guided waves (UGWs) for monitoring the situation of the rebar corrosion entire process. In this paper, a mechanical model was used to establish the relationship between different rebar corrosion expansion states and layer-surface contact pressures in the layered RC components with radial cracks. Based on this model, a soft pressure-dependent contact 2D model in Abaqus was used to simulate the local corrosion layer. A linear and nonlinear signal joint analysis (LNSJA) method using PZT-based UGWs was proposed to monitor rebar corrosions, and an LNSJA-based rebar corrosion damage index (RCDI) for corroded RC components was proposed. The proposed method which can effectively detect both the micro- and macro-thickness as well as local area of rebar corrosion layer was validated by the relevant experiment and finite element analysis (FEA).

IMPA-Net: Interpretable Multi-Part Attention Network for Trustworthy Brain Tumor Classification from MRI.

Deep learning (DL) networks have shown attractive performance in medical image processing tasks such as brain tumor classification. However, they are often criticized as mysterious "black boxes". The opaqueness of the model and the reasoning process make it difficult for health workers to decide whether to trust the prediction outcomes. In this study, we develop an interpretable multi-part attention network (IMPA-Net) for brain tumor classification to enhance the interpretability and trustworthiness of classification outcomes. The proposed model not only predicts the tumor grade but also provides a global explanation for the model interpretability and a local explanation as justification for the proffered prediction. Global explanation is represented as a group of feature patterns that the model learns to distinguish high-grade glioma (HGG) and low-grade glioma (LGG) classes. Local explanation interprets the reasoning process of an individual prediction by calculating the similarity between the prototypical parts of the image and a group of pre-learned task-related features. Experiments conducted on the BraTS2017 dataset demonstrate that IMPA-Net is a verifiable model for the classification task. A percentage of 86% of feature patterns were assessed by two radiologists to be valid for representing task-relevant medical features. The model shows a classification accuracy of 92.12%, of which 81.17% were evaluated as trustworthy based on local explanations. Our interpretable model is a trustworthy model that can be used for decision aids for glioma classification. Compared with black-box CNNs, it allows health workers and patients to understand the reasoning process and trust the prediction outcomes.

Ratiometric electrochemical aptasensor with strand displacement for insulin detection in blood samples.

BACKGROUND: Diabetes patients suffer either from insulin deficiency or resistance with a high risk of severe long-term complications, thus the quantitative assessment of insulin level is highly desired for diabetes surveillance and management. Utilizing insulin-capturing aptamers may facilitate the development of affordable biosensors however, their rigid G-quadruplex structures impair conformational changes of the aptamers and diminish the sensor signals. RESULTS: Here we report on a ratiometric, electrochemical insulin aptasensor which is achieved by hybridization of an insulin-capturing aptamer and a partially complementary ssDNA to break the rigid G-quadruplex structures. To improve the durability of the aptasensor, the capturing aptamer was immobilized on gold electrodes via two dithiol-phosphoramidite functional groups while methoxy-polyethylene glycol thiol was used as a blocking molecule. The exposure of the sensor to insulin-containing solutions induced the dissociation of the hybridized DNA accompanied by a conformational rearrangement of the capturing aptamer back into a G-quadruplex structure. The reliability of sensor readout was improved by the adoption of an AND logic gate utilizing anthraquinone and methylene blue redox probes associated to the aptamer and complementary strand, respectively. Our aptasensor possessed an improved detection limit of 0.15 nM in comparison to aptasensors without strand displacement. SIGNIFICANCE: The sensor was adapted for detection in real blood and is ready for future PoC diagnostics. The capability of monitoring the insulin level in an affordably manner can improve the treatment for an increasing number of patients in developed and developing nations. The utilization of low-cost and versatile aptamer receptors together with the engineering of ratiometric electrochemical signal recording has the potential to considerably advance the current insulin detection technology toward multi-analyte diabetes sensors.

A facile strategy to fabricate high-barrier, water- and oil-repellent paper with carboxymethyl cellulose/collagen fiber/modified polyvinyl alcohol.

Due to the increasingly serious environmental and human health hazards brought by traditional food packaging materials, paper-based packaging materials have become increasingly popular among consumers in recent years. Currently, the fabrication of fluorine-free degradable water- and oil-repellent paper using low-cost bio-based polymers by a simple method is a hot subject in the field of food packaging. In this work, we used carboxymethyl cellulose (CMC), collagen fiber (CF), and modified polyvinyl alcohol (MPVA) to create coatings that were impervious to water and oil. The homogeneous mixture of CMC and CF generated electrostatic adsorption to impart excellent oil repellency to the paper. PVA was chemically modified by sodium tetraborate decahydrate, and the MPVA coating imparted excellent water-repellent properties to the paper. Finally, the water- and oil-proof paper showed excellent water repellency (Cobb value: 1.12 g/m2), oil repellency (kit rating: 12/12), low air permeability (0.3 µm/Pa·s), and stronger mechanical properties (4.19 kN/m). This non-fluorinated degradable water- and oil-repellent paper with high barrier properties prepared by a convenient method is expected to be in widespread use in the food packaging field.

Water and oil-resistant paper materials based on sodium alginate/hydroxypropyl methylcellulose/polyvinyl butyral/nano-silica with biodegradable and high barrier properties.

Despite many technical challenges in the development of safe and environmentally friendly food packaging paper materials with excellent water and oil resistance using simple methods, producing paper-based functional materials using bio-based polymers is currently an important topic in the food packaging industry. In this study, novel water and oil-resistant coatings for the paper were developed through the combination of sodium alginate (SA), hydroxypropyl methylcellulose (HPMC), polyvinyl butyral (PVB), and hydrophobic silica nanoparticles (HSNPs). To impart oil-repellency to paper, SA and HPMC were first mixed uniformly and coated on the base paper, which was pre-treated with calcium chloride solution. A compact and tough coating layer was formed on paper due to the hydrogen bonding between SA and HPMC molecules, and the crosslinking between SA and Ca2+ ions in the base paper. High water resistance of the paper was achieved through the coating of PVB and HSNPs on top of the coating of SA/HPMC. The final coated paper demonstrated outstanding oil resistance (kit rating: 12/12), water resistance (Cobb value: 4.23 g/m2), low water vapor transmission rate (100 g/m2·24 h), and improved mechanical properties. This fluorine-free, and biodegradable barrier paper will find excellent applications in the food packaging industry.

Truncated Electrochemical Aptasensor with Enhanced Antifouling Capability for Highly Sensitive Serotonin Detection.

Accurate determination of serotonin (ST) provides insight into neurological processes and enables applications in clinical diagnostics of brain diseases. Herein, we present an electrochemical aptasensor based on truncated DNA aptamers and a polyethylene glycol (PEG) molecule-functionalized sensing interface for highly sensitive and selective ST detection. The truncated aptamers have a small size and adopt a stable stem-loop configuration, which improves the accessibility of the aptamer for the analyte and enhances the sensitivity of the aptasensor. Upon target binding, these aptamers perform a conformational change, leading to a variation in the Faraday current of the redox tag, which was recorded by square wave voltammetry (SWV). Using PEG as blocking molecules minimizes nonspecific adsorption of other interfering molecules and thus endows an enhanced antifouling ability. The proposed electrochemical aptamer sensor showed a wide range of detection lasting from 0.1 nM to 1000 nM with a low limit of detection of 0.14 nM. Owing to the unique properties of aptamer receptors, the aptasensor also exhibits high selectivity and stability. Furthermore, with the reduced unspecific adsorption, assaying of ST in human serum and artificial cerebrospinal fluid (aCSF) showed excellent performance. The reported strategy of utilizing antifouling PEG describes a novel approach to building antifouling aptasensors and holds great potential for neurochemical investigations and clinical diagnosis.

A Combined Plasmonic and Electrochemical Aptasensor Based on Gold Nanopit Arrays for the Detection of Human Serum Albumin.

Electrochemical and optical platforms are commonly employed in designing biosensors. However, one signal readout can easily lead to inaccuracies due to the effect of nonstandard test procedures, different operators, and experimental environments. We have developed a dual-signal protocol that combined two transducer principles in one aptamer-based biosensor by simultaneously performing electrochemical- and extraordinary optical transmission (EOT)-based plasmonic detection using gold nanopit arrays (AuNpA). Compared with full hole structures, we found that nanopits, that did not fully penetrate the gold film, not only exhibited a better plasmonic bandwidth and refractive index sensitivity both in the finite-difference time-domain simulation and in experiments by shielding the gold/quartz mode but also enlarged the electrochemical active surface area. Therefore, the periodic non-fully penetrating AuNpA were modified with ferrocene-labeled human serum albumin aptamer receptors. The formation of the receptor layer and human serum albumin binding complex induced a conformational change, which resulted in variation in the electron transfer between the electro-active ferrocene units and the AuNpA surface. Simultaneously, the binding event caused a surface plasmon polaritons wavelength shift corresponding to a change in the surface refractive index. Interestingly, although both transducers recorded the same binding process, they led to different limits of detection, dynamic ranges, and sensitivities. The electrochemical transducer showed a dynamic detection range from 1 nM to 600 µM, while the optical transducer covered high concentrations from 100 µM to 600 µM. This study not only provides new insights into the design of plasmonic nanostructures but also potentially opens an exciting avenue for dual-signal disease diagnosis and point-of-care testing applications.

Optimal path generation in scala tympani and path planning for robotic cochlear implant of perimodiolar electrode.

In this study, a new idea of the optimal path generation method was proposed and a path planning strategy for robotic cochlear implant of perimodiolar electrode was designed. The centerline of scala tympani channel was taken as the optimal implant path of the perimodiolar electrode, which aimed to reduce the damage of the electrode to the cochlea during implantation. First, the three-dimensional cochlear model was reconstructed based on the micro-computed tomography images of cochlea, and it was re-segmented to obtain the cross sections of the scala tympani at different angles. Then, the image processing method was used to determine the central point of the scala tympani cross sections. The cubic B-spline interpolation method was used to fit these discrete central points to generate the optimal path. Finally, the coordinate information of the optimal path was combined with the stylet extraction state of perimodiolar electrode to conduct the path planning for robotic cochlear implant, and the result was sent to the robot for kinematic inverse solution to obtain the robot motion trajectory. The robotic cochlear implant experiment was performed with the model of scala tympani. The results showed that the maximum implant force based on path planning was 0.084 N, and the maximum implant force without path planning was 0.134 N. The optimal path generation and the path planning method effectively help to reduce the damage of the electrode to the cochlea.

Learning a discriminant graph-based embedding with feature selection for image categorization.

Graph-based embedding methods are very useful for reducing the dimension of high-dimensional data and for extracting their relevant features. In this paper, we introduce a novel nonlinear method called Flexible Discriminant graph-based Embedding with feature selection (FDEFS). The proposed algorithm aims to classify image sample data in supervised learning and semi-supervised learning settings. Specifically, our method incorporates the Manifold Smoothness, Margin Discriminant Embedding and the Sparse Regression for feature selection. The weights add ℓ2,1-norm regularization for local linear approximation. The sparse regression implicitly performs feature selection on the original features of data matrix and of the linear transform. We also provide an effective solution method to optimize the objective function. We apply the algorithm on six public image datasets including scene, face and object datasets. These experiments demonstrate the effectiveness of the proposed embedding method. They also show that proposed the method compares favorably with many competing embedding methods.

Nitrogen doped carbon dots for turn-off fluorescent detection of alkaline phosphatase activity based on inner filter effect.

The abnormal expression level of alkaline phosphatase (ALP) will lead to serious diseases. Therefore, a sensitive and rapid assay for ALP activity monitoring is of vital importance. In this work, a fluorescence turn-off approach for the detection of ALP is designed on the basis of nitrogen doped carbon dots (N-CDs), which were synthesized by one-step hydrothermal method and applied as signal readout. p-Nitrophenylphosphate (PNPP) can be hydrolyzed into p-nitrophenol (PNP) by ALP and their absorption peaks are different under alkaline conditions, so it was chosen as the ALP substrate. The absorption spectrum of PNP has good overlap with the excitation and emission spectra of N-CDs, thus the fluorescence of N-CDs can be effectively quenched by PNP via the inner filter effect (IFE). Consequently, quantitative detection of ALP is realized because the relative fluorescence intensity is linearly with the ALP activity in a wide range from 0.05 to 40 U L-1. The detection limit is 0.02 U L-1 (S/N = 3), which is much lower than the normal level of serum ALP in adults (about 40-190 U L-1). Moreover, the assay was successfully applied to evaluate ALP inhibitor efficiency and screen ALP inhibitors in drug discovery. It is also demonstrated that N-CDs possesses low cytotoxicity, excellent biocompatibility and photostability, and can be successfully applied in vivo fluorescence imaging, showing great potential in clinical applications.

Multi-rigid-body modeling and simulation of perimodiolar cochlear electrode arrays.

This study presented a method that decomposes perimodiolar electrodes into multi-rigid bodies for the study on the shape variation of cochlear perimodiolar electrode. The coordinates of electrode array were obtained by capturing the shape varying image of the perimodiolar electrodes with the stylet extracted. Subsequently, the increment of the angle variation and the length of each link were obtained. Fourier compensation fitting method was developed using the three fitting methods to compare and analyze the increment of the angle variation of the perimodiolar electrode multi-rigid model. This can not only ensure that the initial angle of the joint is consistent with the actual angle of the perimodiolar electrode, but also fully reflect the varying trend of the joint angle of the multi-rigid model of the perimodiolar electrode. The simulation of the shape variation of the perimodiolar electrode multi-rigid-body model was performed using this method in the ADAMS simulation platform. According to the simulation results, the precise and continuous shape variation of perimodiolar electrodes can be obtained using this method.

In situ sulfur-doped graphitic carbon nitride nanosheets with enhanced electrogenerated chemiluminescence used for sensitive and selective sensing of l-cysteine.

In this study, in situ sulfur-doped carbon nitride nanosheets (S-g-C3N4 NSs) are used as the signal readout for the sensitive and selective sensing of l-cysteine (l-Cys) in human serum samples based on the competitive coordination chemistry of Cu2+ between l-Cys and S-g-C3N4 NSs. S-g-C3N4 NSs are prepared by using trithiocyanuric acid as a precursor for the first time, which exhibits stronger electrogenerated chemiluminescence (ECL) intensity compared with pristine graphitic carbon nitride nanosheets (g-C3N4 NSs). The ECL signals of the S-g-C3N4 NSs can be quenched by Cu2+ and the subsequent presence of l-Cys can recover the ECL signals of the S-g-C3N4 NSs. These changes are ascribed to the higher coordination ability between Cu2+ and l-Cys than that between Cu2+ and the S-g-C3N4 NSs. On the basis of this, the concentration of l-Cys can be quantitatively determined. Under optimized conditions, the ECL intensity recovery shows a linear relationship with the l-Cys concentration range from 30 nM to 0.2 mM with a lower detection limit of 5 nM (S/N = 3). The proposed method is highly sensitive and selective and is thus particularly useful for fast and simple clinical diagnosis of diseases, such as Alzheimer's disease and cardiovascular disease.

Nitrogen-doped carbon dots-V2O5 nanobelts sensing platform for sensitive detection of ascorbic acid and alkaline phosphatase activity.

In this work, the as-prepared V2O5 nanobelts can sensitively quench the fluorescence of nitrogen-doped carbon dots (N-CDs) based on the inner filter effect (IFE). In the presence of ascorbic acid (AA), the fluorescence of N-CDs can recover through the redox reaction between V2O5 nanobelts and AA. Meanwhile, in the presence of both alkaline phosphatase (ALP) and ascorbyl-2-phosphate (AAP), the fluorescence of N-CDs can also restore since AAP can be hydrolyzed into AA by ALP. Under optimum conditions, the linear range for AA is from 0.01 to 2.5 µM with a detection limit of 3 nM and that for ALP is from 0.1 to 30 U/L with a detection limit of 0.04 U/L (S/N = 3). Particularly, the proposed probe could be successfully used to detect AA and ALP in human serum samples. Furthermore, N-CDs can be applied in fluorescence imaging of Human breast cancer cells with satisfactory results.

For the optical detection of anthrax biomarker using a luminescent rare earth-organic framework modified by rhodamine molecules: Synthesis, characterization and two sensing channels.

This work was devoted to the synthesis and performance report of an optical sensing platform for dipicolinate (DPA), which was known as a biomarker for Bacillus anthracis spores. This DPA optical sensing platform (denoted as EuBTC@RB) was composed of luminescent rare earth MOF and rhodamine-derived sensing probe. Its structure was discussed and confirmed by means of XRD, IR, TGA, absorption, emission and excitation spectra. EuBTC@RB showed two sensing channels for DPA, including colorimetric sensing and ratiometric fluorescent sensing. Linear response was found for both sensing channels, with LOD value of 3.4 µM. Its sensing mechanism was discussed and confirmed as the combination of an emission turn off effect caused by energy transfer process (EuBTC → DPA pyridine) and an emission turn on effect of rhodamine molecules triggered by DPA-released protons. EuBTC@RB showed its advantage over traditional DPA optical sensing systems due to its dual sensing skills and the possibility of naked eye detection.