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.

Analysis of coupling effect between TID and SET in SOI Tri-Gate nanowire field-effect transistors.

This study investigates the response of nanowire field-effect transistors (NWFETs) to total ionizing dose (TID), single-event transient (SET), and their coupling effects in junctionless (JL), inversion (IM), and junctionless accumulation (AC) modes. The degradation of the three modes under irradiation and the effect of device bias configuration on the electrical properties of NWFETs are analyzed, and the different effects of SET on the three modes are compared. On this basis, the influence of TID on SET current generation and the charge collection mechanism are studied, and the changes in peak current, pulse width, and collected charge of transient current under different TIDs are compared. The results show that JL mode has the worst resistance to TID and SET coupling effects, followed by IM and AC modes.

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.

Skin microbiome and causal relationships in three dermatological diseases: Evidence from Mendelian randomization and Bayesian weighting.

BACKGROUND: Atopic dermatitis (AD), psoriasis (PSO), rosacea, and other related immune skin diseases are affected by multiple complex factors such as genetic and microbial components. This research investigates the causal relationships between specific skin microbiota and these diseases by using Mendelian randomization (MR), and Bayesian weighted Mendelian randomization (BWMR). METHODS: We utilized genome-wide association study (GWAS) data to analyze the associations between various skin bacteria and three dermatological diseases. Single nucleotide polymorphisms (SNPs) served as instrumental variables (IVs) in MR methods, including inverse variance weighted (IVW), and MR Egger. BWMR was employed to validate results and address pleiotropy. RESULTS: The IVW analysis identified significant associations between specific skin microbiota and dermatological diseases. ASV006_Dry, ASV076_Dry, and Haemophilus_Dry were significantly positively associated with AD, whereas Kocuria_Dry was negatively associated. In PSO, ASV005_Dry was negatively associated, whereas ASV004_Dry, Rothia_Dry, and Streptococcus_Moist showed positive associations. For rosacea, ASV023_Dry was significantly positively associated, while ASV016_Moist, Finegoldia_Dry, and Rhodobacteraceae_Moist were significantly negatively associated. These results were corroborated by BWMR analysis. CONCLUSION: Bacterial species such as Finegoldia, Rothia, and Streptococcus play crucial roles in the pathogenesis of AD, PSO, and rosacea. Understanding these microbial interactions can aid in developing targeted treatments and preventive strategies, enhancing patient outcomes and quality of life.

Correction: Systemic Delivery of MicroRNA-101 Potently Inhibits Hepatocellular Carcinoma In Vivo by Repressing Multiple Targets.

[This corrects the article DOI: 10.1371/journal.pgen.1004873.].

Explore the feasibility of using spot-scanning proton arc therapy for a synchrotron accelerator-based proton therapy system - A simulation study.

OBJECTIVE: The aim of this study was to evaluate the feasibility and plan quality of spot-scanning proton arc therapy (SPArc) using a synchrotron-accelerator-based proton therapy system compared to intensity-modulated proton therapy (IMPT). APPROACH: Five representative disease sites, including head and neck, lung, liver, brain chordoma, and prostate cancers, were retrospectively selected. Both IMPT and SPArc plans are generated with the HITACHI ProBEAT PBS system's minimum MU constraints and physics beam model. The SPArc plans are generated with 2.5° sampling frequency. The static delivery time was simulated based on the previously published synchrotron delivery sequence model, and the dynamic delivery time was simulated using a proton arc gantry mechanical model integrated with the synchrotron delivery sequence. Both dosimetric plan quality and delivery efficiency are evaluated. MAIN RESULTS: A superior plan quality is reached compared with the IMPT plans generated for the same disease site. However, a relatively prolonged static and dynamic delivery time post new challenge, as static time increased by 49.22% and dynamic time 59.10% on average. SIGNIFICANCE: This study presents the first simulation results of delivering the SPArc plans using a synchrotron-accelerated proton therapy system. The result shows its feasibility and limitations, which could guide future development.

Walnut peptide relieves hypertension and associated kidney and heart injury by regulating the renin-angiotensin-aldosterone system and intestinal microbiota.

BACKGROUND: Hypertension is a chronic disease with high morbidity and mortality. Previously, we screened a walnut meal peptide FDWLR (PEP) with significant angiotensin-converting enzyme inhibitory activity. The present study further investigated the anti-hypertensive effects of PEP in vivo using spontaneously hypertensive rats. RESULTS: The results indicated that PEP reduced blood pressure and the indices in the renin-angiotensin-aldosterone system (RAAS) including angiotensin-converting enzyme (ACE) (decreased by 15.36%), angiotensin II (Ang II) (decreased by 31.56%), angiotensinogen (AGT) (decreased by 58.84%) and aldosterone (ALD) (decreased by 18.27%), whereas NO levels increased by 54.96%. The pathological analysis showed that PEP relieved cardiac and renal damage. PEP also alleviated oxidative stress, inflammation and fibrosis in the heart and kidney. Mechanistically, PEP mitigated cardiac and renal damage by simultaneously regulating ACE-Ang II-AT1R and the ACE2-Ang (1-7)-MAS axis. Additionally, PEP increased the levels of short chain fatty acids by 224.16% and improved gut microbiota by increasing the abundance of Prevotella, Phascolarctobacterium, Clostridium_sensu_stricto and Bifidobacterium, at the same time as decreasing Bacteroides and Alistipes abundances. CONCLUSION: This study indicated that PEP prevented hypertension and associated heart and kidney damage by modulating the RAAS system and gut microbiota, which is valuable in guiding future development and optimal utilization of walnut meal. © 2024 Society of Chemical Industry.

A high performance trench gate tunneling field effect transistor based on quasi-broken gap energy band alignment heterojunction.

In this letter, a tunneling field effect transistor based on quasi-broken gap energy band alignment (QB-TFET) is proposed and investigated by simulation method. To offering high on-state current, InGaAs/GaAsSb heterojunction with quasi-broken gap energy band alignment is applied to QB-TFET to improve the band-to-band tunneling rate. Trench gate structure and InGaAs pocket layer are applied to further increase the tunneling efficiency. To suppress the leakage current caused by the off-state tunneling path from source to drain, an intrinsic InGaAs spacer is inserted between n+ InGaAs drain and p+ GaAsSb source. In order to further improve the control ability of gate voltage on channel, TiO2is used as the gate dielectric of the proposed QB-TFET. Moreover, the effect ofxandyfraction of InxGa1-xAs and GaAsySb1-yon quasi-broken gap tunneling junction are studied in this work. The electrical characteristic change of QB-TFET with differentxandyfraction is analyzed. The proposed QB-TFET is compared with other works and shows an obvious advantage on performance. As a result, a large on-state current (Ion) of 921µAµm-1can be obtained. Moreover, steep average subthreshold swing (SSavg) of 4.9 mV/dec can be achieved whenIon = 1µAµm-1.

Prediction of electrical properties of FDSOI devices based on deep learning.

Fully depleted Silicon on insulator technology (FDSOI) is proposed to solve the various non-ideal effects when the process size of integrated circuits is reduced to 45 nm. The research of traditional FDSOI devices is mostly based on simulation software, which requires a lot of calculation and takes a long time. In this paper, a deep learning (DL) based electrical characteristic prediction method for FDSOI devices is proposed. DL algorithm is used to train the simulation data and establish the relationship between the physical parameters and electrical characteristics of the device. The network structure used in the experiment has high prediction accuracy. The mean square error of electrical parameters and transfer characteristic curve is only 4.34 × 10-4and 2.44 × 10-3respectively. This method can quickly and accurately predict the electrical characteristics of FDSOI devices without microelectronic expertise. In addition, this method can be extended to study the effects of various physical variables on device performance, which provides a new research method for the field of microelectronics.

Single event effects prediction of MOSFET device using deep learning.

Single event effect (SEE) is an important problem in the reliability research of integrated circuits. The study of SEE of traditional MOSFET devices is mainly based on simulation software, which is characterized by slow simulation speed, large computation and time-consuming. In this paper, a SEE research method based on deep learning is proposed. The method relies on 28 nm MOSFET. The complete drain transient current pulse, transient current peak value and total collected charge can be obtained in a short time by inputting relevant parameters that affect the SEE. The accuracy of the network for predicting transient current peak and total collected charge is 96.95% and 97.53% respectively, and the mean goodness of fit of the network for predicting the drain transient current pulse curve is 0.985. Compared with TCAD Sentaurus software, the simulation speed is increased by 5.89 × 103and 1.50 × 103times respectively. This method has good prediction effect and provides a new possibility for the study of SEE.

MR-based synthetic CT image for intensity-modulated proton treatment planning of nasopharyngeal carcinoma patients.

PURPOSE: To develop an advanced deep convolutional neural network (DCNN) architecture to generate synthetic CT (SCT) images from MR images for intensity-modulated proton therapy (IMPT) treatment planning of nasopharyngeal cancer (NPC) patients. METHODS: T1-weighted MR images and paired CT (PCT) images were obtained from 206 NPC patients. For each patient, deformable image registration was performed between MR and PCT images to create an MR-CT image pair. Thirty pairs were randomly chosen as the independent test set and the remaining 176 pairs (14 for validation and 162 for training) were used to build two conditional generative adversarial networks (GANs): 1) GAN3D: using a 3D U-net enhanced with residual connections and attentional mechanism as the generator and 2) GAN2D: using a 2D U-net as the generator. For each test patient, SCT images were generated using the generators with the MR images as input and were compared with respect to the corresponding PCT image. A clinical IMPT plan was created and optimized on the PCT image. The dose was recalculated on the SCT images and compared with the one calculated on the PCT image. RESULTS: The mean absolute errors (MAEs) between the PCT and SCT, within the body, were (64.89 ± 5.31) HU and (64.31 ± 4.61) HU for the GAN2D and GAN3D. Within the high-density bone (HU > 600), the GAN3D achieved a smaller MAE compared with the GAN2D (p < 0.001). Within the body, the absolute point dose deviation was reduced from (0.58 ± 1.61) Gy for the GAN2D to (0.47 ± 0.94) Gy for the GAN3D. The (3 mm/3%) gamma passing rates were above 97.32% for all SCT images. CONCLUSIONS: The SCT images generated using GANs achieved clinical acceptable dosimetric accuracy for IMPT of NPC patients. Using advanced DCNN architecture design, such as residual connections and attention mechanism, SCT image quality was further improved and resulted in a small dosimetric improvement.

Synthesis and Spectral Characteristics Investigation of the 2D-2D vdWs Heterostructure Materials.

Due to the attractive optical and electrical properties, van der Waals (vdWs) heterostructures constructed from the different two-dimensional materials have received widespread attention. Here, MoS2/h-BN, MoS2/graphene, WS2/h-BN, and WS2/graphene vdWs heterostructures are successfully prepared by the CVD and wet transfer methods. The distribution, Raman and photoluminescence (PL) spectra of the above prepared heterostructure samples can be respectively observed and tested by optical microscopy and Raman spectrometry, which can be used to study their growth mechanisms and optical properties. Meanwhile, the uniformity and composition distribution of heterostructure films can also be analyzed by the Raman and PL spectra. The internal mechanism of Raman and PL spectral changes can be explained by comparing and analyzing the PL and Raman spectra of the junction and non-junction regions between 2D-2D vdWs heterostructure materials, and the effect of laser power on the optical properties of heterostructure materials can also be analyzed. These heterostructure materials exhibit novel and unique optical characteristics at the stacking or junction, which can provide a reliable experimental basis for the preparation of suitable TMDs heterostructure materials with excellent performance.

Effects of subchronic exposure of mercuric chloride on intestinal histology and microbiota in the cecum of chicken.

This study aimed to investigate the influences of mercuric chloride (HgCl2, 250 ppm, drink water) on the growth performance, cecal morphology and microbiota of chickens (n = 60) after 30, 60, and 90 days of exposure. A control group of sixty chickens received water free of HgCl2. Our results suggested that mercury exposure reduced the body weight and changed the cecal morphology of chickens after the 90-day treatment. Furthermore, sequence analysis of 16 S rRNA gene revealed that the diversity and composition of cecal microbiota in chickens differed between the control and exposure group. At the phylum level, Proteobacteria and Tenericutes phyla both significantly increased in mercury exposure groups on day 30 while only Tenericutes phyla significantly increased on day 60. At the genus level, we observed that the change in microbial populations are most dramatic on day 30. Besides, compared with the control group, the genus Prevotellaceae_UCG-001 significantly increased in exposure group on day 30 but showed no significant difference on day 60, whereas there was a significant decrease on day 90. PICRUSt analysis revealed potential metabolic changes, such as Bacterial invasion of epithelial cells and Metabolism of xenobiotics, associated with mercury exposure in chickens. Taken together, the data show that subchronic exposure to mercury not only affected the growth and development but also caused the dysbiosis of gut microbiota, which may further induced metabolic disorders in chickens.

The Large-Scale Preparation and Optical Properties of MoS2/WS2 Vertical Hetero-Junction.

A variety of hetero-junctions can be constructed to form the basic structural units in the different optoelectronic devices, such as the photo-detectors, solar cells, sensors and light-emitting diodes. In our research, the large-area high-quality MoS2/WS2 vertical hetero-junction are prepared by the two-step atmospheric pressure chemical vapor deposition (APCVD) methods and the dry transfer method, and the corresponding optimal reaction conditions of MoS2/WS2 vertical hetero-junction are obtained. The morphology, composition and optical properties of MoS2/WS2 vertical hetero-junction are systematically characterized by the optical microscopy, Raman spectroscopy, photoluminescence spectroscopy, atomic force microscopy and the field emission scanning electron microscopy. Compared to the mechanical transfer method, the MoS2/WS2 vertical hetero-junction sample obtained by the APCVD and dry transfer methods have lower impurity content, cleaner interfaces and tighter interlayer coupling. Besides, the strong interlayer coupling and effective interlayer charge transfer of MoS2/WS2 vertical hetero-junction are also further studied. The photoluminescence intensity of MoS2/WS2 vertical hetero-junction is significantly reduced compared to the single MoS2 or WS2 material. In general, this research can help to achieve the large-scale preparation of various Van der Waals hetero-junctions, which can lay the foundation for the new application of optoelectronic devices.

Chemotherapeutic drugs stimulate the release and recycling of extracellular vesicles to assist cancer cells in developing an urgent chemoresistance.

BACKGROUND: Chemotherapy is a widely used treatment for cancer. However, the development of acquired multidrug resistance (MDR) is a serious issue. Emerging evidence has shown that the extracellular vesicles (EVs) mediate MDR, but the underlying mechanism remains unclear, especially the effects of chemotherapeutic agents on this process. METHODS: Extracellular vesicles isolation was performed by differential centrifugation. The recipient cells that acquired ATP-binding cassette sub-family B member 1 (ABCB1) proteins were sorted out from co-cultures according to a stringent multi-parameter gating strategy by fluorescence-activated cell sorting (FACS). The transfer rate of ABCB1 was measured by flow cytometry. The xenograft tumor models in mice were established to evaluate the transfer of ABCB1 in vivo. Gene expression was detected by real-time PCR and Western blotting. RESULTS: Herein, we show that a transient exposure to chemotherapeutic agents can strikingly increase Rab8B-mediated release of extracellular vesicles (EVs) containing ABCB1 from drug-resistant cells, and accelerate these EVs to circulate back onto plasma membrane of sensitive tumor cells via the down-regulation of Rab5. Therefore, intercellular ABCB1 transfer is significantly enhanced; sensitive recipient cells acquire a rapid but unsustainable resistance to evade the cytotoxicity of chemotherapeutic agents. More fascinatingly, in the xenograft tumor models, chemotherapeutical drugs also locally or distantly increase the transfer of ABCB1 molecules. Furthermore, some Non-small-cell lung carcinoma (NSCLC) patients who are undergoing primary chemotherapy have a rapid increase of ABCB1 protein in their monocytes, and this is obviously associated with poor chemotherapeutic efficacy. CONCLUSIONS: Chemotherapeutic agents stimulate the secretion and recycling of ABCB1-enriched EVs through the dysregulation of Rab8B and Rab5, leading to a significant increase of ABCB1 intercellular transfer, thus assisting sensitive cancer cells to develop an urgent resistant phenotype. Our findings provide a new molecular mechanism of how chemotherapeutic drugs assist sensitive cancer cells in acquiring an urgent resistance.

Systemic delivery of microRNA-101 potently inhibits hepatocellular carcinoma in vivo by repressing multiple targets.

Targeted therapy based on adjustment of microRNA (miRNA)s activity takes great promise due to the ability of these small RNAs to modulate cellular behavior. However, the efficacy of miR-101 replacement therapy to hepatocellular carcinoma (HCC) remains unclear. In the current study, we first observed that plasma levels of miR-101 were significantly lower in distant metastatic HCC patients than in HCCs without distant metastasis, and down-regulation of plasma miR-101 predicted a worse disease-free survival (DFS, P<0.05). In an animal model of HCC, we demonstrated that systemic delivery of lentivirus-mediated miR-101 abrogated HCC growth in the liver, intrahepatic metastasis and distant metastasis to the lung and to the mediastinum, resulting in a dramatic suppression of HCC development and metastasis in mice without toxicity and extending life expectancy. Furthermore, enforced overexpression of miR-101 in HCC cells not only decreased EZH2, COX2 and STMN1, but also directly down-regulated a novel target ROCK2, inhibited Rho/Rac GTPase activation, and blocked HCC cells epithelial-mesenchymal transition (EMT) and angiogenesis, inducing a strong abrogation of HCC tumorigenesis and aggressiveness both in vitro and in vivo. These results provide proof-of-concept support for systemic delivery of lentivirus-mediated miR-101 as a powerful anti-HCC therapeutic modality by repressing multiple molecular targets.

A feasibility study of intrafractional tumor motion estimation based on 4D-CBCT using diaphragm as surrogate.

PURPOSE: To investigate the intrafractional stability of the motion relationship between the diaphragm and tumor, as well as the feasibility of using diaphragm motion to estimate lung tumor motion. METHODS: Eighty-five paired (pre and posttreatment) daily 4D-CBCT images were obtained from 20 lung cancer patients who underwent SBRT. Bony registration was performed between the pre- and post-CBCT images to exclude patient body movement. The end-exhalation phase image of the pre-CBCT image was selected as the reference image. Tumor positions were obtained for each phase image using contour-based translational alignments. Diaphragm positions were obtained by translational alignment of its apex position. A linear intrafraction model was constructed using regression analysis performed between the diaphragm and tumor positions manifested on the pretreatment 4D-CBCT images. By applying this model to posttreatment 4D-CBCT images, the tumor positions were estimated from posttreatment 4D-CBCT diaphragm positions and compared with measured values. A receiver operating characteristic (ROC) test was performed to determine a suitable indicator for predicting the estimate accuracy of the linear model. RESULTS: Using the linear model, per-phase position, mean position, and excursion estimation errors were 1.12 ± 0.99 mm, 0.97 ± 0.88 mm, and 0.79 ± 0.67 mm, respectively. Intrafractional per-phase tumor position estimation error, mean position error, and excursion error were within 3 mm 95%, 96%, and 99% of the time, respectively. The residual sum of squares (RSS) determined from pretreatment images achieved the largest prediction power for the tumor position estimation error (discrepancy < 3 mm) with an Area Under ROC Curve (AUC) of 0.92 (P < 0.05). CONCLUSION: Utilizing the relationship between diaphragm and tumor positions on the pretreatment 4D-CBCT image, intrafractional tumor positions were estimated from intrafractional diaphragm positions. The estimation accuracy can be predicted using the RSS obtained from the pretreatment 4D-CBCT image.

CD133+ liver cancer stem cells resist interferon-gamma-induced autophagy.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most fatal malignancies worldwide, and CD133 is a popular cancer stem cell (CSC) marker for HCC. CD133(+) CSCs have been reported to resist conventional chemo- and radiotherapy, but little is known about their response to immune surveillance. Interferon-gamma (IFN-γ) is one of key cytokines that the immune system produce to eradicate cancer cells, so we investigated the function of IFN-γ on CD133+ HCC CSCs in this study. METHODS: The response of CD133(+) cells to IFN-γ was performed with functional assays (cell proliferation assay and tumor formation in nude mice), flow cytometry, immunofluorescence staining and RNA interference. RESULTS: We found that IFN-γ inhibited the proliferation of cell lines with low percentage of CD133(+) cells (wild-type human cells, BEL7402, QGY7701) but it did not affect the proliferation of cell lines with high percentage of CD133(+) cells (wild-type human cells, Huh7, PLC8024) in vivo and in vitro (nude mice). Flow cytometry analysis demonstrated that the percentage of CD133+ cells increased after IFN-γ treatment of low CD133(+) cell lines. Furthermore, IFN-γ induced the autophagy of low CD133(+) cell lines to decrease proliferation. CONCLUSION: CD133(+) HCC CSCs resisted IFN-γ-induced autophagy, which might also be a mechanism through which CSCs resist immune eradication.