Doping Engineering To Modulate Surface Plasmon Resonance and Enzyme-like Activities for Enhancing Photoacoustic Imaging-Guided Targeted Cancer Therapy in the Second Near-Infrared Window.

Biological imaging-guided targeted tumor therapy has been a soughtafter goal in the field of cancer diagnosis and treatment. To this end, we proposed a strategy to modulate surface plasmon resonance and endow WO3-x nanoparticles (NPs) with enzyme-like catalytic properties by doping Fe2+ in the structure of the NPs. Doping of the Fe2+ introduced oxygen vacancies into the structure of the NPs, inducing a red shift of the maximum absorption wavelength into the near-infrared II (NIR-II) region and enhancing the photoacoustic (PA) and photothermal properties of the NPs for more effective imaging-guided cancer therapy. Under NIR-II laser irradiation, the Fe-WO3-x NPs produced very strong NIR-II PA and photothermal effects, which significantly enhanced the PA imaging and photothermal treatment effects. On the other hand, Fe2+ in Fe-WO3-x could undergo Fenton reactions with H2O2 in the tumor tissue to generate ·OH for chemodynamic therapy. In addition, Fe-WO3-x can also catalyze the above reactions to produce more reactive oxygen species (ROS) and induce the oxidation of NADH to interfere with intracellular adenosine triphosphate (ATP) synthesis, thereby further improving the efficiency of cancer therapy. Specific imaging of tumor tissue and targeted synergistic therapy was achieved after ligation of a MUC1 aptamer to the surface of the Fe-WO3-x NPs by the complexing of -COOH in MUC1 with tungsten ions on the surface of the NPs. These results demonstrated that Fe-WO3-x NPs could be a promising diagnosis and therapeutic agent for cancer. Such a study opens up new avenues into the rational design of nanodiagnosis and treatment agents for NIR-II PA imaging and cancer therapy.

A study on the high power microwave effects of PIN diode limiter based on deep learning algorithm.

PIN diodes, due to their simple structure and variable resistance characteristics under high-frequency high-power excitation, are often used in radar front-end as limiters to filter high power microwaves (HPM) to prevent its power from entering the internal circuit and causing damage. This paper carries out theoretical derivation and research on the HPM effects of PIN diodes, and then uses an optimized neural network algorithm to replace traditional physical modeling to calculate and predict two types of HPM limiting indicators of PIN diode limiters. We proposes a neural network model for each of the following two prediction scenarios: in the scenario of time-junction temperature curves under different HPM irradiation, the weighted mean squared error (MSE) between the predicted values from the test dataset and the simulated values is below 0.004. While in predicting PIN limiter's power limitation threshold, insertion loss, and maximum isolation under different HPM irradiation, the MSE of the test set prediction values and simulation values are all less than 0.03. The method proposed in this research, which applies an optimized neural network algorithm to replace traditional physical modeling algorithms for studying the high-power microwave effects of PIN diode limiters, significantly improves the computational and simulation speed, reduces the calculation cost, and provides a new method for studying the high-power microwave effects of PIN diode limiters.

Prediction of electrical properties of GAAFET based on integrated learning model.

As device feature sizes continue to decrease and fin field effect transistors reach their physical limits, gate all around field effect transistors (GAAFETs) have emerged with larger gate control areas and stackable characteristics for better suppression of second-order effects such as short-channel effects due to their gate encircling characteristics. Traditional methods for studying the electrical characteristics of devices are mostly based on the technology computer-aided design. Still, it is not conducive to developing new devices due to its time-consuming and inefficient drawbacks. Deep learning (DL) and machine learning (ML) have been well-used in recent years in many fields. In this paper, we propose an integrated learning model that integrates the advantages of DL and ML to solve many problems in traditional methods. This integrated learning model predicts the direct current characteristics, capacitance characteristics, and electrical parameters of GAAFET better than those predicted by DL or ML methods alone, with a linear regression factor (R2) greater than 0.99 and very small root mean square error. The proposed integrated learning model achieves fast and accurate prediction of GAAFET electrical characteristics, which provides a new idea for device and circuit simulation and characteristics prediction in microelectronics.

Rational design of a near-infrared dual-emission fluorescent probe for ratiometric imaging of glutathione in cells.

Sensors for which the output signal is an intensity change for a single-emission peak are easily disturbed by many factors, such as the stability of the instrument, intensity of the excitation light, and biological background. However, for ratiometric fluorescence sensors, the output signal is a change in the intensity ratio of two or more emission peaks. The fluorescence intensity of these emission peaks is similarly affected by external factors; thus, these sensors have the ability to self-correct, which can greatly improve the accuracy and reliability of the detection results. To accurately image glutathione (GSH) in cells, gold nanoclusters (AuNCs) with intrinsic double emission at wavelengths of 606 nm and 794 nm were synthesized from chloroauric acid. With the emission peak at 606 nm as the recognition signal and the emission peak at 794 nm as the reference signal, a near-infrared dual-emission ratio fluorescence sensing platform was constructed to accurately detect changes in the GSH concentration in cells. In vitro and in vivo analyses showed that the ratiometric fluorescent probe specifically detects GSH and enables ultrasensitive imaging, providing a new platform for the accurate detection of active small molecules.

Enhancing intracellular mRNA precise imaging-guided photothermal therapy with a nucleic acid-based polydopamine nanoprobe.

Despite significant advancements in cancer research, real-time monitoring and effective treatment of cancer through non-invasive techniques remain a challenge. Herein, a novel polydopamine (PDA) nucleic acid nanoprobe has been developed for imaging signal amplification of intracellular mRNA and precise photothermal therapy guidance in cancer cells. The PDA nucleic acid nanoprobe (PDA@DNA) is constructed by assembling an aptamer hairpin (H1) labeled with the Cy5 fluorophore and another nucleic acid recognition hairpin (H2) onto PDA nanoparticles (PDA NPs), which have exceptionally high fluorescence quenching ability and excellent photothermal conversion properties. The nanoprobe could facilitate cellular uptake of DNA molecules and their protection from nuclease degradation. Upon recognition and binding to the intracellular mRNA target, a catalytic hairpin assembly (CHA) reaction occurs. The stem of H1 unfolds upon binding, allowing the exposed H1 to hybridize with H2, forming a flat and sturdy DNA double-stranded structure that detaches from the surface of PDA NPs. At the same time, the target mRNA is displaced and engages in a new cyclic reaction, resulting in the recovery and significant amplification of Cy5 fluorescence. Using thymidine kinase1 (TK1) mRNA as a model mRNA, this nanoprobe enables the analysis of TK1 mRNA with a detection limit of 9.34 pM, which is at least two orders of magnitude lower than that of a non-amplifying imaging nucleic acid probe. Moreover, with its outstanding performance for in vitro detection, this nanoprobe excels in precisely imaging tumor cells. Through live-cell TK1 mRNA imaging, it can accurately distinguish between tumor cells and normal cells. Furthermore, when exposed to 808-nm laser irradiation, the nanoprobe fully harnesses exceptional photothermal conversion properties of PDA NPs. This results in a localized temperature increase within tumor cells, which ultimately triggers apoptosis in these tumor cells. The integration of PDA@DNA presents innovative prospects for tumor diagnosis and image-guided tumor therapy, offering the potential for high-precision diagnosis and treatment of tumors.

A Silver-Induced Absorption Red-Shifted Dual-Targeted Nanodiagnosis-Treatment Agent for NIR-II Photoacoustic Imaging-Guided Photothermal and ROS Simultaneously Enhanced Immune Checkpoint Blockade Antitumor Therapy.

Tumor metastasis remains a leading factor in the failure of cancer treatments and patient mortality. To address this, a silver-induced absorption red-shifted core-shell nano-particle is developed, and surface-modified with triphenylphosphonium bromide (TPP) and hyaluronic acid (HA) to obtain a novel nanodiagnosis-treatment agent (Ag@CuS-TPP@HA). This diagnosis-treatment agent can dual-targets cancer cells and mitochondria, and exhibits maximal light absorption at 1064 nm, thereby enhancing nesr-infrared II (NIR-II) photoacoustic (PA) signal and photothermal effects under 1064 nm laser irradiation. Additionally, the silver in Ag@CuS-TPP@HA can catalyze the Fenton-like reactions with H2 O2 in the tumor tissue, yielding reactive oxygen species (ROS). The ROS production, coupled with enhanced photothermal effects, instigates immunogenic cell death (ICD), leading to a substantial release of tumor-associated antigens (TAAs) and damage-associated molecular patterns, which have improved the tumor immune suppression microenvironment and boosting immune checkpoint blockade therapy, thus stimulating a systemic antitumor immune response. Hence, Ag@CuS-TPP@HA, as a cancer diagnostic-treatment agent, not only accomplishes targeted the NIR-II PA imaging of tumor tissue and addresses the challenge of accurate diagnosis of deep cancer tissue in vivo, but it also leverages ROS/photothermal therapy to enhance immune checkpoint blockade, thereby eliminating primary tumors and effectively inhibiting distant tumor growth.

Dual Coupled Long-Range Hybrid Surface Plasmon Polariton Waveguide for Sub-Wavelength Confinement.

In this paper, a long-range hybrid waveguide for subwavelength confinement based on double SPP coupling is proposed. The hybrid waveguide consists of a metal-based cylindrical hybrid waveguide and a silver nanowire. There are two coupling regions in the waveguide structure that enhance mode coupling. Strong mode coupling enables the waveguide to exhibit both a small effective mode area (0.01) and an extremely long transmission length (700 µm). The figure of merit (FOM) of the waveguide can be as high as 4000. In addition, the cross-sectional area of the waveguide is only 500 nm × 500 nm, allowing optical operation in the subwavelength range, which helps enhance the miniaturization of optoelectronic devices. The excellent characteristics of the hybrid waveguide make it have potential applications in photoelectric integrated systems.

The causal relationship between gut microbiota and bone mineral density: a Mendelian randomization study.

Background: The gut microbiota has emerged as an intriguing and potentially influential factor in regulating bone health. However, the causal effect of the gut microbiota on bone mineral density (BMD) appears to differ throughout various life stages. Methods: We conducted a Mendelian randomization (MR) analysis to investigate the potential causal relationship between gut microbiota and BMD in five distinct age groups: 0-15, 15-30, 30-45, 45-60, and 60 years and older. The analysis employed three different methods, namely MR-Egger, weighted median, and Inverse-variance weighting, to ensure the robustness of our findings, a series of sensitivity analyses were also conducted, such as horizontal pleiotropy tests, heterogeneity tests, and leave-one-out sensitivity tests. Results: In the age group of 0-15 years, Eubacterium_fissicatena_group and Eubacterium_hallii_group were identified as risk factors for BMD. During the 15-30 age group, Phascolarctobacterium, Roseburia, and Ruminococcaceae_UCG_003 were found to be protective factors for BMD. In the 30-45 age group, Lachnospira genus demonstrated a protective effect on BMD, while Barnesiella and Lactococcus were identified as risk factors for BMD. Moving on to the 45-60 age group, Eubacterium_ventriosum_group, Lachnospiraceae_UCG_004, and Subdoligranulum were observed to be protective factors for BMD, while Eubacterium_coprostanoligenes_group, Fusicatenibacter, and Lactococcus were associated with an increased risk of BMD. In individuals aged 60 years and older, Fusicatenibacter and Ruminococcaceae_UCG_002 were also noted as risk factors for BMD. Conversely, Eubacterium_ruminantium_group, Ruminococcus_gauvreauii_group, Alistipes, and Coprococcus_3 were found to be protective factors for BMD, whereas Barnesiella and Sellimonas were identified as risk factors for BMD. Conclusion: A robust causal relationship between gut microbiota and bone mineral density (BMD) exists throughout all stages of life, with Firmicutes phylum being the primary group associated with BMD across age groups. Gut microbiota linked with BMD primarily belong to the Firmicutes phylum across age groups. The diversity of gut microbiota phyla associated with BMD depicts relatively stable patterns during the ages of 0-45 years. However, for individuals aged 45 years and above, there is an observed increase in the number of gut microbiota species linked with BMD, and by the age of 60 years, a trend toward an increase in the Bacteroidetes phylum categories is proposed.

Fabrication of Ag-CaCO3 Nanocomposites for SERS Detection of Forchlorfenuron.

In this study, Ag-CaCO3 nanocomposites were synthesized using silver nitrate as the precursor solution based on calcium carbonate nanoparticles (CaCO3 NPs). The synthesis involved the reaction of calcium lignosulphonate and sodium bicarbonate. The properties of Ag-CaCO3 nanocomposites were studied by various technologies, including an ultraviolet-visible spectrophotometer, a transmission electron microscope, and a Raman spectrometer. The results showed that Ag-CaCO3 nanocomposites exhibited a maximum UV absorption peak at 430 nm, the surface-enhanced Raman spectroscopy (SERS) activity of Ag-CaCO3 nanocomposites was evaluated using mercaptobenzoic acid (MBA) as the marker molecule, resulting in an enhancement factor of 6.5 × 104. Additionally, Ag-CaCO3 nanocomposites were utilized for the detection of forchlorfenuron. The results demonstrated a linear relationship in the concentration range of 0.01 mg/mL to 2 mg/mL, described by the equation y = 290.02x + 1598.8. The correlation coefficient was calculated to be 0.9772, and the limit of detection (LOD) was determined to be 0.001 mg/mL. These findings highlight the relatively high SERS activity of Ag-CaCO3 nanocomposites, making them suitable for analyzing pesticide residues and detecting toxic and harmful molecules, thereby contributing to environmental protection.

Research on electronic synaptic simulation of HfO2-based memristor by embedding Al2O3.

The potential of neuromorphic computing in synaptic simulation has led to a renewed interest in memristor. However, the demand for multilevel resistive switching with high reliability and low power consumption is still a great resistance in this application. In this work, the electronic synaptic plasticity and simulated bipolar switching behavior of Pt/Al2O3(2 nm)/HfO2(10 nm)/Al2O3(2 nm)/Ti tri-layer memristor is investigated. The effect of Al2O3layer embedded at the top electrode and the bottom electrode on the resistive performance of the memristor was studied. It is found that both of them can effectively improve the reliability of the device (104cycles), the resistive window (>103), the tunable synaptic linearity and reduce of the operating voltage. RRAM with Al2O3embedded at the top electrode have higher uniformity and LTP linearity, while those with Al2O3embedded at the bottom electrode significantly reduce the operating current (∼10µA) and improve LTD linearity. Electron transport mechanisms were compared between single-layer HfO2and tri-layer Al2O3/HfO2/Al2O3samples under DC scanning. The results showed that the thin Al2O3layer at the top electrode led to Fowler Northeim tunneling in the low-resistance state, while the thin Al2O3layer at the bottom electrode led to Schottky emission in the high-resistance state. The Al2O3/HfO2/Al2O3memristors were successfully used to achieve synaptic properties, including enhancement, inhibition, and spike time-dependent plasticity, demonstrating an important role in high-performance neuromorphic computing applications.

NIR-II photoacoustic imaging-guided synergistic cancer therapy with a tumor-targeting copper selenide-iron manganese layered double hydroxide nanocomplex.

A novel biodegradable layered double hydroxide-copper selenide nanocomplex was prepared by anchoring copper selenide on manganese iron layered double hydroxide nanosheets. This nanocomplex can specifically release CuSe, Mn2+ and Fe3+ in the tumor microenvironment, which implements NIR-II photoacoustic imaging-guided synergistic cancer therapy under 1064 nm laser irradiation.

mRNA-activated DNAzyme nanoprobe for tumor cell precise imaging and gene therapy.

A novel Au-nucleic acid nanoprobe, catalyzed by mRNA, has been developed for live cell imaging and precise treatment of tumor cells. This nanoprobe exhibits the remarkable ability to differentiate between tumor cells and normal cells through live cell mRNA imaging, while selectively inducing apoptosis in tumor cells.

H2O2 Self-Supply and Glutathione Depletion Engineering Nanoassemblies for NIR-II Photoacoustic Imaging of Tumor Tissues and Photothermal-Enhanced Gas Starvation-Primed Chemodynamic Therapy.

The development of tumor microenvironment (TME)-activated nanoassemblies which can produce a photoacoustic (PA) signal and enhance the H2O2 level is critical to achieve accurate diagnosis and highly efficient chemodynamic therapy (CDT). In this study, we developed nanoassemblies consisting of oxygen vacancy titanium dioxide (TiO2-x) surface-constructed copper, sulfur-doped mesoporous organosilica and glucose oxidase (TiO2-x@Cu,S-MONs@GOx, hereafter TMG). We found that highly abundant glutathione (GSH) in the TME nanoassemblies can reduce tetrasulfide bonds and Cu2+ to sulfur ions and Cu+ in the TMG nanoassemblies, respectively, causing the breakage of the tetrasulfide bond and the mesoporous structure collapse, releasing Cu+ ions and TiO2-x nanoparticles, and producing hydrogen sulfide gas, thereby achieving synergistic multimodal tumor treatment through TME-activated NIR-II PA imaging and photothermal-enhanced gas starvation-primed CDT. Therefore, the TMG nanoassemblies form a smart nanoplatform that can serve as an excellent tumor diagnosis-treatment agent by playing an important role in imaging-guided precision diagnosis of cancer and efficient targeting treatment.

A False Trigger-Strengthened and Area-Saving Power-Rail Clamp Circuit with High ESD Performance.

A power clamp circuit, which has good immunity to false trigger under fast power-on conditions with a 20 ns rising edge, is proposed in this paper. The proposed circuit has a separate detection component and an on-time control component which enable it to distinguish between electrostatic discharge (ESD) events and fast power-on events. As opposed to other on-time control techniques, instead of large resistors or capacitors, which can cause a large occupation of the layout area, we use a capacitive voltage-biased p-channel MOSFET in the on-time control part of the proposed circuit. The capacitive voltage-biased p-channel MOSFET is in the saturation region after the ESD event is detected, which can serve as a large equivalent resistance (~106 Ω) in the structure. The proposed power clamp circuit offers several advantages compared to the traditional circuit, such as having at least 70% area savings in the trigger circuit area (30% area savings in the whole circuit area), supporting a power supply ramp time as fast as 20 ns, dissipating the ESD energy more cleanly with little residual charge, and recovering faster from false triggers. The rail clamp circuit also offers robust performance in an industry-standard PVT (process, voltage, and temperature) space and has been verified by the simulation results. Showing good performance of human body model (HBM) endurance and high immunity to false trigger, the proposed power clamp circuit has great potential for application in ESD protection.

Global research trends and hotspots analysis of hallux valgus: A bibliometric analysis from 2004 to 2021.

Background: Hallux valgus (HV) is a common foot and ankle surgery disease. The correction of HV deformity relies on a highly challenging surgical treatment. Thus, widely adopted evidence-based clinical guidelines are still needed to guide the selection of the most appropriate interventions. Recently, the study of HV has been growing and scholars are increasingly paying particular attention to this area. However, bibliometric literature remains lacking. Therefore, this study aims to reveal the hotspots and future research trends in HV via bibliometric analysis to fill this knowledge gap. Methods: Literature related to HV from 2004 to 2021 was retrieved from the Science Citation Index Expanded (SCI-expanded) of the Web of Science Core Collection (WoSCC). Quantitative and qualitative analyses of scientific data are performed using software such as CiteSpace, R-bibliometrix, and VOSviewer. Results: A total of 1,904 records were identified for analysis. The United States had the most number of published articles and total citations. Thus, the United States has made an essential contribution to the field of HV. Meanwhile, La Trobe University in Australia was the most productive institution. Menz HB and Foot & Ankle International were the most influential authors and the most popular journals among researchers, respectively. In addition, "older people," "chevron osteotomy," "Lapidus," and "hallux rigidus" have always been the hotspots of attention. Changes and developments in the surgery of HV have gained researchers' interest. Future research trends are more focused on "radiographic measurement," "recurrence," "outcome," "rotation," "pronation," and "minimally invasive surgery." Thus, focusing on these subject directions can facilitate academic progress and provide the possibility of better treatments for HV. Conclusion: This study summarizes the hotspots and trends in the field of HV from 2004 to 2021, which will provide researchers with an updated view of essential information and somehow guide future research.

Prediction of Single-Event Effects in FDSOI Devices Based on Deep Learning.

Single-event effects (SEE) are an important index of radiation resistance for fully depleted silicon on insulator (FDSOI) devices. The research into traditional FDSOI devices is based on simulation software, which is time consuming, requires a large amount of calculation, and has complex operations. In this paper, a prediction method for the SEE of FDSOI devices based on deep learning is proposed. The characterization parameters of SEE can be obtained quickly and accurately by inputting different particle incident conditions. The goodness of fit of the network curve for predicting drain transient current pulses can reach 0.996, and the accuracy of predicting the peak value of drain transient current and total collected charge can reach 94.00% and 96.95%, respectively. Compared with TCAD Sentaurus software, the simulation speed is increased by 5.10 × 102 and 1.38 × 103 times, respectively. This method can significantly reduce the computational cost, improve the simulation speed, and provide a new feasible method for the study of the single-event effect in FDSOI devices.

Study on the Simulation of Biosensors Based on Stacked Source Trench Gate TFET.

In order to detect biomolecules, a biosensor based on a dielectric-modulated stacked source trench gate tunnel field effect transistor (DM-SSTGTFET) is proposed. The stacked source structure can simultaneously make the on-state current higher and the off-state current lower. The trench gate structure will increase the tunneling area and tunneling probability. Technology computer-aided design (TCAD) is used for the sensitivity study of the proposed structured biosensor. The results show that the current sensitivity of the DM-SSTGTFET biosensor can be as high as 108, the threshold voltage sensitivity can reach 0.46 V and the subthreshold swing sensitivity can reach 0.8. As a result of its high sensitivity and low power consumption, the proposed biosensor has highly promising prospects.

A Novel Fluorescent Aptamer Sensor with DNAzyme Signal Amplification for the Detection of CEA in Blood.

Carcinoembryonic antigen (CEA) is a tumor-specific biomarker; however, its low levels in the early stages of cancer make it difficult to detect. To address the need for analysis of ultra-low-level substances, we designed and synthesized a fluorescent aptamer sensor with DNAzyme signal amplification and used it for the detection of CEA in blood. In the presence of the target protein, the aptamer sequence in the recognition probe binds to the target protein and opens the hairpin structure, hybridizes with the primer and triggers a polymerization reaction in the presence of polymerase to generate double-stranded DNA with two restriction endonuclease Nb.BbvCl cleavage sites. At the same time, the target protein is displaced and continues to bind to another recognition probe, triggering a new round of polymerization reaction, forming a cyclic signal amplification triggered by the target. The experimental results show that the blood detection with CEA has a high sensitivity and a wide detection range. The detection range: 10 fg/mL~10 ng/mL, with a detection limit of 5.2 fg/mL. In addition, the sensor can be used for the analysis of complex biological samples such as blood.

GaN JBS Diode Device Performance Prediction Method Based on Neural Network.

GaN JBS diodes exhibit excellent performance in power electronics. However, device performance is affected by multiple parameters of the P+ region, and the traditional TCAD simulation method is complex and time-consuming. In this study, we used a neural network machine learning method to predict the performance of a GaN JBS diode. First, 3018 groups of sample data composed of device structure and performance parameters were obtained using TCAD tools. The data were then input into the established neural network for training, which could quickly predict the device performance. The final prediction results show that the mean relative errors of the on-state resistance and reverse breakdown voltage are 0.048 and 0.028, respectively. The predicted value has an excellent fitting effect. This method can quickly design GaN JBS diodes with target performance and accelerate research on GaN JBS diode performance prediction.

An autocatalytically-activatable hydrogen peroxide photoacoustic sensor for in situ visualization precise diagnosis and drug intervention tracing in diabetes syndrome.

In situ visualization for the diagnosis of diabetic syndrome and visual monitoring the response to drug treatment is a challenge. Herein, we designed and prepared an autocatalytically-activatable hydrogen peroxide photoacoustic (PA) sensor. We first prepared the FeMoOx nanoparticle with catalase activity, then combined it to 2,2'-azino-bis(3-ethylbenzothi-azoline-6-sulfonic acid) (ABTS) and distearoylphos-phoethanola-mine-polyethylene-glycol (DSPE-PEG) to construct a autocatalytically-activatable PA sensor (FeMoOx@ABTS@DSPE-PEG). In its presence, ABTS can be converted into oxidized ABTS·+ by H2O2. ABTS·+ exhibits strong light absorption in the near-infrared region, and can serve as an ideal contrast agent for PA imaging. H2O2 as a biomarker of oxidative stress response is closely related to the occurrence and development of diabetes mellitus and its complications. Therefore, FeMoOx@ABTS@DSPE-PEG was used as a PA sensor of H2O2 for visual monitoring of the progression of diabetes-induced liver injury and metformin-mediated treatment of diabetes. The autocatalytically-activatable PA sensor developed in this study provides a promising platform for in situ visual diagnosis of diabetes and its syndrome and monitoring the response to therapy.