Ion transport based structural description for in situ synthesized SBA-15 nanochannels in a sub-micropipette.

Construction of nanoporous arrays can greatly facilitate their development in the fields of sensing, energy conversion, and nanofluidic devices. It is important to characterize the structure and understand the ion transport behaviour of a nanoporous array, especially those prepared by in situ synthesis, which are difficult to be characterized by conventional methods. Herein, an inorganic and non-crystalline mesoporous silica SBA-15 is selected as a template, where a combination (GP-SBA-15) of a sub-micropipette and SBA-15 is constructed by in situ synthesis, and the multichannel array structure of GP-SBA-15 is illustrated by its ion transport properties from current-voltage responses. Experiments of linear scan voltammetry and chronoamperometry show a rapid accumulation and slow redistribution of ions in the surface-charged nanochannels, and the high/low currents originate from the accumulation/depletion of ions in the channels. The finite element simulation is introduced to calculate the effects of surface charge and pore size on ion rectification and ion concentration distribution. In addition, the short straight channels and long bending channels present in GP-SBA-15 are demonstrated by the voltage-independent resistance pulse signals in the translocation of BSA. This study shows that electrochemical means effectively provide insight into ion transport, achieve structural description and reveal the sensing potential of GP-SBA-15.

How much can AI see in early pregnancy: A multi-center study of fetus head characterization in week 10-14 in ultrasound using deep learning.

PURPOSE: To investigate if artificial intelligence can identify fetus intracranial structures in pregnancy week 11-14; to provide an automated method of standard and non-standard sagittal view classification in obstetric ultrasound examination METHOD AND MATERIALS: We proposed a newly designed scheme based on deep learning (DL) - Fetus Framework to identify nine fetus intracranial structures: thalami, midbrain, palate, 4th ventricle, cisterna magna, nuchal translucency (NT), nasal tip, nasal skin, and nasal bone. Fetus Framework was trained and tested on a dataset of 1528 2D sagittal-view ultrasound images from 1519 females collected from Shenzhen People's Hospital. Results from Fetus Framework were further used for standard/non-standard (S-NS) plane classification, a key step for NT measurement and Down Syndrome assessment. S-NS classification was also tested with 156 images from the Longhua branch of Shenzhen People's Hospital. Sensitivity, specificity, and area under the curve (AUC) were evaluated for comparison among Fetus Framework, three classic DL models, and human experts with 1-, 3- and 5-year ultrasound training. Furthermore, 4 physicians with more than 5 years of experience conducted a reader study of diagnosing fetal malformation on a dataset of 316 standard images confirmed by the Fetus framework and another dataset of 316 standard images selected by physicians. Accuracy, sensitivity, specificity, precision, and F1-Score of physicians' diagnosis on both sets are compared. RESULTS: Nine intracranial structures identified by Fetus Framework in validation are all consistent with that of senior radiologists. For S-NS sagittal view identification, Fetus Framework achieved an AUC of 0.996 (95%CI: 0.987, 1.000) in internal test, at par with classic DL models. In external test, FF reaches an AUC of 0.974 (95%CI: 0.952, 0.995), while ResNet-50 arrives at AUC∼0.883, 95% CI 0.828-0.939, Xception AUC∼0.890, 95% CI 0.834-0.946, and DenseNet-121 AUC∼0.894, 95% CI 0.839-0.949. For the internal test set, the sensitivity and specificity of the proposed framework are (0.905, 1), while the first-, third-, and fifth-year clinicians are (0.619, 0.986), (0.690, 0.958), and (0.798, 0.986), respectively. For the external test set, the sensitivity and specificity of FF is (0.989, 0.797), and first-, third-, and fifth-year clinicians are (0.533, 0.875), (0.609, 0.844), and (0.663, 0.781), respectively.On the fetal malformation classification task, all physicians achieved higher accuracy and F1-Score on Fetus selected standard images with statistical significance (p < 0.01). CONCLUSION: We proposed a new deep learning-based Fetus Framework for identifying key fetus intracranial structures. The framework was tested on data from two different medical centers. The results show consistency and improvement from classic models and human experts in standard and non-standard sagittal view classification during pregnancy week 11-13+6. CLINICAL RELEVANCE/APPLICATION: With further refinement in larger population, the proposed model can improve the efficiency and accuracy of early pregnancy test using ultrasound examination.

Studies on the Morphology Effect on Catalytic Ability of a Single MnO2 Catalyst Particle with a Solid Nanopipette.

Investigating the catalytic ability of an individual catalyst particle helps to understand heterogeneity and can provide new insights into the synthesis of high-efficiency catalysts. Solid-state nanopores have become a promising tool for detecting single molecules/particles due to their high temporal and spatial resolution. Here, we report a nanopore-based strategy for the evaluation and comparison of a single MnO2 catalyst particle with different morphologies by monitoring the generated O2 bubbles from the catalytic decomposition of H2O2. The finite element simulation was introduced to account for the flow velocity and bubble-induced current variation in the nanopore. In particular, the differences in catalytic ability of spherical and cubic MnO2 have been studied by calculating the production rate and volume of O2. It demonstrates that the shape of a single MnO2 catalyst particle has a significant effect on its catalytic activity indeed.

A Fourier Transform-Induced Data Process for Label-Free Selective Nanopore Analysis under Sinusoidal Voltage Excitations.

Nanopore analysis based on a resistive-pulse technique is an attractive tool for single-molecule detection in different fields, but it suffers a great drawback in selectivity. A common solution to this challenge is to add extra sensing aptamers and labels to analytes by improving the sensitivity of their pulses for distinguishing. Compared to the labeling methods, we alternatively develop and demonstrate a novel data process for label-free nanopore analysis that enables the conversion of resistive current signals to more specific frequency domain phase angle features with the contribution from both sinusoidal voltage excitation and Fourier transform. In particular, we find that the transmural capacitance induced by nanoparticle translocations under a sinusoidal voltage plays an important role in this process, making phase angle features more pronounced. In practical applications, the method is successfully applied to directly distinguish the translocation events through a nanopipette by their unique phase angles for similarly sized SiO2, Ag, and Au nanoparticles and soft living organisms of HeLa and LoVo and even in a more complicated case of a SiO2, Ag, and Au nanoparticle mixture.

Experimental and finite element method studies for femtomolar cobalt ion detection using a DHI modified nanochannel.

In this work, a sensing nanochannel based on a N-[3-(triethoxysilyl)propyl]-4,5-dihydroimidazole (DHI) modified nanopipette was prepared and characterized for the ultrasensitive detection of cobalt ions (Co2+) in aqueous solutions. By both experimental and theoretical studies, the detection conditions (chelation balance time, pH of the electrolyte, nanopipette diameter, potentials for ionic current) and parameters (rectification value, resistance and ionic current) have been fully optimized, and the proposed Co2+ sensor shows a significantly wide detection range from 20 fM to 0.2 mM, with an ultra-low detection limit down to 0.94 fM.

Boronic acid-functionalized molybdenum disulfide quantum dots for the ultrasensitive analysis of dopamine based on synergistic quenching effects from IFE and aggregation.

Herein, a novel fluorescent material, boronic acid-functionalized molybdenum disulfide quantum dots (B-MoS2 QDs) produced by an amidation reaction between 3-aminobenzeneboronic acid and previously prepared molybdenum disulfide quantum dots (MoS2 QDs), was prepared to fabricate a rapid and sensitive platform for the quantitative analysis of dopamine. This material exhibits strong fluorescence, excellent salt tolerance and light fastness. In particular, the quantum yield of this material is about 21.1 times that of its fundamental material, MoS2 QDs. Notably, owing to an interesting synergistic effect between the inner filter effect and the aggregation quenching effect, this material was successfully applied for the determination of dopamine in the linear range 0.25-35 µmol L-1 with the detection limit of 0.087 µmol L-1; moreover, B-MoS2 QDs manifested better selectivity in the presence of multiple interferences due to their inert surface. As expected, this proposed material shows satisfactory performance in human serum; thus, the present study exploits a new avenue for the application of functionalized MoS2 QDs in fluorescence sensing.

Moisture-Absorption and Water Dynamics in the Powder of Egg Albumen Peptide, Met-Pro-Asp-Ala-His-Leu.

Moisture absorbed into the powder of Met-Pro-Asp-Ala-His-Leu (MPDAHL)-a novel egg albumen antioxidant peptide-profoundly affects its properties. In this study, we elucidated water dynamics in MPDAHL using DVS, DSC, and low-field 1 H NMR. Based on the DVS data, we found that MPDAHL sorption kinetics obey a parallel exponential model. DSC results indicated that both water and heating could change the microstructure of MPDAHL. The T2 parameters of NMR reflected the different phases of moisture absorption revealed that there were 4 categories of water with different states or mobility in the MPDAHL during the moisture absorption process. The fastest fraction T2b mainly dominated the hygroscopicity of MPDAHL and the absorbed water significantly changed the proton distribution and structure of MPDAHL. Thus, this study shows that DVS, DSC, and low-field 1 H NMR are effective methods for monitoring water mobility and distribution in synthetic peptides. It can be used to improve the quality assurance of functional peptides.

Water Dynamics in Egg White Peptide, Asp-His-Thr-Lys-Glu, Powder Monitored by Dynamic Vapor Sorption and LF-NMR.

Water absorbed into the bulk amorphous structure of peptides can have profound effects on their properties. Here, we elucidated water dynamics in Asp-His-Thr-Lys-Glu (DHTKE), an antioxidant peptide derived from egg white ovalbumin, using water dynamic vapor sorption (DVS) and low-field nuclear magnetic resonance (LF-NMR). The DVS results indicated that parallel exponential kinetics model fitted well to the data of sorption kinetics behavior of DHTKE. Four different proton fractions with different mobilities were identified based on the degree of interaction between peptide and water. The water could significantly change the proton distribution and structure of the sample. The different phases of moisture absorption were reflected in the T2 parameters. In addition, the combined water content was dominant in the hygroscopicity of DHTKE. This study provides an effective real-time monitoring method for water mobility and distribution in synthetic peptides, and this method may have applications in promoting peptide quality assurance.

Analysis of DPPH inhibition and structure change of corn peptides treated by pulsed electric field technology.

In this study, the effects on antioxidant activity and structure change of corn peptides (CPS) with 10 to 30 kDa molecular weight (MW) treated by pulsed electric field (PEF) technology were investigated. 2, 2-diphenyl-1-picrylhydrazyl (DPPH) inhibition was used to evaluate the antioxidant activity of CPS. Response surface methodology (RSM) was used to investigate the effects of PEF treatment parameters on antioxidant activity of CPS. The optimal conditions were as follows: concentration of CPS 10 mg mL(-1), electric field intensity 15 kV cm(-1), and pulse frequency 2,000 Hz. Under the optimized conditions, the DPPH inhibition of CPS increased 32.1 %, compared to the sample untreated. And mid-infrared spectroscopy (MIR) was used for analyzing the structure change of CPS. The results showed that PEF technology could obviously increase the DPPH inhibition of CPS under the optimized conditions (P < 0.05).