The chemical and optical stability evaluation of injectable restorative materials under wet challenge.

OBJECTIVES: To investigate and compare the chemical and optical stability of four restorative composite materials: two injectable resins, one flowable resin and one compomer. METHODS: Two injectable nano-filled composite resins: G-aenial Universal (GU) and Beautifil Injectable XSL (BI), a flowable composite resin: Filtek Supreme Flowable (FS) and a compomer: Dyract Flow (DF), in A2 shade were tested and compared. Water sorption and solubility were conducted according to ISO4049:2019 standard; ICP-OES and F-ion selective electrode were used to test the elemental release; Degree of conversion (DC) was obtained by using FTIR; water contact angle was obtained by static sessile drop method, and a spectrophotometer was used for optical properties (ΔE⁎, ΔL⁎ and TP). SPSS 28.0 was used for statistical analysis and the significant level was pre-set as α = 0.05. RESULTS: GU performed the best in water sorption and solubility, FS had the lowest elemental release, the best colour stability, and the highest DCIM and DC24-h. DF, the compomer had the lowest, and GU and BI, the injectable composites had the largest water contact angle, respectively. Correlations were found between water sorption and water solubility. CONCLUSIONS: The four composite restorative materials showed different chemical and optical behaviours. Overall, composite resins performed better than compomer, while additional laboratory and in vivo tests are necessary to obtain a more comprehensive comparison between injectable and flowable composite resins. Wsp and Wsl are influenced by many common factors, and the values are highly positively related. CLINICAL SIGNIFICANCE: A comprehensive understanding of materials is crucial before selecting materials for clinical practice. Composite resins rather than compomers are recommended because of their exceptional properties, which make them eligible for a wide range of clinical applications and an elongated lifespan.

The mechanical, wear, antibacterial properties and biocompatibility of injectable restorative materials under wet challenge.

OBJECTIVES: To evaluate the mechanical, wear, antibacterial properties, and biocompatibility of injectable composite materials. METHODS: Two injectable composite resins (GU and BI), one flowable composite resin (FS), and one flowable compomer (DF), in A2 shade, were tested. Mechanical properties were tested via three-point bending test immediately after preparation and after 1-day, 7-day, 14-day, and 30-day water storage. Under water-PMMA slurry immersion, specimens were subjected to a 3-body wear test (10,000 cycles) against stainless steel balls, while the roughness, wear depth, and volume loss were recorded. After 1-day and 3-day MC3T3-E1 cell culture, cell viability was evaluated with CCK-8 test kits, while the cell morphology was observed under CLSM and SEM. Antibacterial properties on S. mutans were assessed via CFU counting, CLSM, and SEM observation. SPSS 26.0 was used for statistical analysis (α = 0.05). RESULTS: The mechanical properties were material-dependent and sensitive to water storage. Flexural strength ranked GU > FS > BI > DF at all testing levels. Three nanocomposites had better wear properties than DF. No significant difference on 1-day cell viability was found, but DF showed significantly lower cell proliferation than nanocomposites on 3-day assessment. GU and FS had more favourable cell adhesion and morphology. CFU counting revealed no significant difference, while FS presented a slightly thicker biofilm and BI showed relatively lower bacteria density. CONCLUSIONS: Injectable nanocomposites outperformed the compomer regarding mechanical properties, wear resistance, and biocompatibility. The tested materials presented comparable antibacterial behaviours. Flowable resin-based composites' performances are affected by multiple factors, and their compositions can be attributed. CLINICAL SIGNIFICANCE: A profound understanding of the mechanical, wear, and biological properties of the restorative material is imperative for the clinical success of dental restorations. The current study demonstrated superior properties of highly filled injectable composite resins, which imply their wider indications and better long-term clinical performances.

Heterogeneous nucleation induced A. pernyi/B. mori silk fibroin coatings on AZ31 biometals with enhanced corrosion resistance, adhesion and biocompatibility.

Silk fibroin coatings on biomedical magnesium alloys have garnered significant attention due to their enhanced corrosion resistance and biocompatibility. However, the utilization of wild A. pernyi silk fibroin, known for its RGD sequence that facilitates tissue regeneration, presents a challenge for corrosion-resistant coatings on magnesium alloys due to its weak adhesion and high dissolution rate. In this study, we employed hexafluoroisopropanol as a solvent to blend A. pernyi silk fibroin with B. mori silk fibroin. The resulting blended fibroin coating at a 3:7 mass ratio exhibited a heterogeneous nucleation effect, enhancing ß-sheet content (32.3 %) and crystallinity (28.6 %). This improved ß-sheet promoted the "labyrinth effect" with an Icorr of 2.15 × 10-6 A cm-2, resulting in significantly improved corrosion resistance, which is two orders of magnitude lower than that of pure magnesium alloy. Meanwhile, the increased content of exposed serine in zigzag ß-sheet contributes to a higher adhesion strength. Cell cytotoxicity evaluation confirmed the enhanced cell adhesion and bioactivity. This work provides a facile approach for wild A. pernyi silk fibroin coatings on magnesium alloys with enhanced corrosion resistance, adhesion and biocompatibility.

A Modulation Method for Tunnel Magnetoresistance Current Sensors Noise Suppression.

To mitigate the impact of low-frequency noise from the tunnel magnetoresistance (TMR) current sensor and ambient stray magnetic fields on weak current detection accuracy, we propose a high-resolution modulation-demodulation test method. This method modulates and demodulates the measurement signal, shifting low-frequency noise to the high-frequency band for effective filtering, thereby isolating the target signal from the noise. In this study, we developed a Simulink model for the TMR current sensor modulation-demodulation test method. Practical time-domain and frequency-domain tests of the developed high-resolution modulation-demodulation method revealed that the TMR current sensor exhibits a nonlinearity as low as 0.045%, an enhanced signal-to-noise ratio (SNR) of 77 dB, and a heightened resolution of 100 nA. The findings indicate that this modulation-demodulation test method effectively reduces the impact of low-frequency noise on TMR current sensors and can be extended to other types of resistive devices.

Synthesis of bioactive evodiamine and rutaecarpine analogues under ball milling conditions.

Mechanochemical reactions achieved by processes such as milling and grinding are promising alternatives to traditional solution-based chemistry. This approach not only eliminates the need for large amounts of solvents, thereby reducing waste generation, but also finds applications in chemical and materials synthesis. The focus of this study is on the synthesis of quinazolinone derivatives by ball milling, in particular evodiamine and rutaecarpine analogues. These compounds are of interest due to their diverse bioactivities, including potential anticancer properties. The study examines the reactions carried out under ball milling conditions, emphasizing their efficiency in terms of shorter reaction times and reduced environmental impact compared to conventional methods. The ball milling reaction of evodiamine and rutaecarpine analogues resulted in yields of 63-78% and 22-61%, respectively. In addition, these compounds were tested for their cytotoxic activity, and evodiamine exhibited an IC50 of 0.75 ± 0.04 µg mL-1 against the Ca9-22 cell line. At its core, this research represents a new means to synthesise these compounds, providing a more environmentally friendly and sustainable alternative to traditional approaches.

The neddylation inhibitor MLN4924 inhibits proliferation and triggers apoptosis of oral cancer cells but not for normal cells.

Increased neddylation benefits the survival of several types of cancer cells. The inhibition of neddylation has the potential to exert anticancer effects but is rarely assessed in oral cancer cells. This study aimed to investigate the antiproliferation potential of a neddylation inhibitor MLN4924 (pevonedistat) for oral cancer cells. MLN4924 inhibited the cell viability of oral cancer cells more than that of normal oral cells (HGF-1) with 100% viability, that is, IC50 values of oral cancer cells (CAL 27, OC-2, and Ca9-22) are 1.8, 1.4, and 1.9 µM. MLN4924 caused apoptotic changes such as the subG1 accumulation, activation of annexin V, pancaspase, and caspases 3/8/9 of oral cancer cells at a greater rate than in normal oral cells. MLN4924 induced greater oxidative stress in oral cancer cells compared to normal cells by upregulating reactive oxygen species and mitochondrial superoxide and depleting the mitochondrial membrane potential and glutathione. In oral cancer cells, preferential inductions also occurred for DNA damage (γH2AX and 8-oxo-2'-deoxyguanosine). Therefore, this investigation demonstrates that MLN4924 is a potential anti-oral-cancer agent showing preferential inhibition of apoptosis and promotion of DNA damage with fewer cytotoxic effects on normal cells.

Highly flexible anisotropic magnetoresistance sensor for wearable electronics.

The emerging market of wearable devices for tracking and positioning requires the development of highly flexible magnetic sensors. Due to the stable magnetoresistance ratio and simple fabrication process, sensors based on the anisotropic magnetoresistance (AMR) effect have been proposed as promising candidates. However, the stability of AMR sensors under different bending situations has rarely been investigated. In this work, we proposed a flexible AMR magnetic sensor deposited on an ultra-thin Kapton substrate, which exhibits excellent anti-fatigue behavior at different bending curvatures ranging from 1/3 to 1/10 mm-1. Experimental results show that the sensitivity of our proposed flexible AMR sensor remains as high as 0.25 Oe-1 after being bent 500 times, showing promising potential for application in wearable electronic devices.

Ginger-Derived 3HDT Exerts Antiproliferative Effects on Breast Cancer Cells by Apoptosis and DNA Damage.

Ginger-derived compounds are abundant sources of anticancer natural products. However, the anticancer effects of (E)-3-hydroxy-1-(4'-hydroxy-3',5'-dimethoxyphenyl)-tetradecan-6-en-5-one (3HDT) have not been examined. This study aims to assess the antiproliferation ability of 3HDT on triple-negative breast cancer (TNBC) cells. 3HDT showed dose-responsive antiproliferation for TNBC cells (HCC1937 and Hs578T). Moreover, 3HDT exerted higher antiproliferation and apoptosis on TNBC cells than on normal cells (H184B5F5/M10). By examining reactive oxygen species, mitochondrial membrane potential, and glutathione, we found that 3HDT provided higher inductions for oxidative stress in TNBC cells compared with normal cells. Antiproliferation, oxidative stress, antioxidant signaling, and apoptosis were recovered by N-acetylcysteine, indicating that 3HDT preferentially induced oxidative-stress-mediated antiproliferation in TNBC cells but not in normal cells. Moreover, by examining γH2A histone family member X (γH2AX) and 8-hydroxy-2-deoxyguanosine, we found that 3HDT provided higher inductions for DNA damage, which was also reverted by N-acetylcysteine. In conclusion, 3HDT is an effective anticancer drug with preferential antiproliferation, oxidative stress, apoptosis, and DNA damage effects on TNBC cells.

Morphology and mechanical performance of dental crown designed by 3D-DCGAN.

OBJECTIVES: This study utilised an Artificial Intelligence (AI) method, namely 3D-Deep Convolutional Generative Adversarial Network (3D-DCGAN), which is one of the true 3D machine learning methods, as an automatic algorithm to design a dental crown. METHODS: Six hundred sets of digital casts containing mandibular second premolars and their adjacent and antagonist teeth obtained from healthy personnel were machine-learned using 3D-DCGAN. Additional 12 sets of data were used as the test dataset, whereas the natural second premolars in the test dataset were compared with the designs in (1) 3D-DCGAN, (2) CEREC Biogeneric, and (3) CAD for morphological parameters of 3D similarity, cusp angle, occlusal contact point number and area, and in silico fatigue simulations with finite element (FE) using lithium disilicate material. RESULTS: The 3D-DCGAN design and natural teeth had the lowest discrepancy in morphology compared with the other groups (root mean square value = 0.3611). The Biogeneric design showed a significantly (p < 0.05) higher cusp angle (67.11°) than that of the 3D-DCGAN design (49.43°) and natural tooth (54.05°). No significant difference was observed in the number and area of occlusal contact points among the four groups. FE analysis showed that the 3D-DCGAN design had the best match to the natural tooth regarding the stress distribution in the crown. The 3D-DCGAN design was subjected to 26.73 MPa and the natural tooth was subjected to 23.97 MPa stress at the central fossa area under physiological occlusal force (300 N); the two groups showed similar fatigue lifetimes (F-N curve) under simulated cyclic loading of 100-400 N. Designs with Biogeneric or technician would yield respectively higher or lower fatigue lifetime than natural teeth. SIGNIFICANCE: This study demonstrated that 3D-DCGAN could be utilised to design personalised dental crowns with high accuracy that can mimic both the morphology and biomechanics of natural teeth.

A Bibliometric Mapping Study of the Literature on Oral Health-related Quality of Life.

BACKGROUND: Oral health is an indispensable component of overall health, and oral health status significantly influences people's physical, mental, and social well-being. Oral health-related quality of life (OHRQoL), an important and widely used dental patient-reported outcome (dPRO), is attracting more and more researchers' attention and interest. This study aimed to analyze and map the existing scientific literature regarding OHRQoL through a bibliometric approach, including a summary of the characteristics of OHRQoL-related publications, the identification of prolific entities, high-frequency keywords analysis, and research trend analysis via periodic high-impact keywords. METHODS: A literature search was conducted in the Web of Science Core Collection to collect OHRQoL-related original research and review articles. After examination and deduplication, the following bibliometric information was extracted from each article: title, abstract, keywords, authors, affiliations, geographic origin (countries/regions), year of publication, journal name, and references. Various scientometric mapping tools including Microsoft Office spreadsheet, VOSviewer, Biblioshiny R-package software, and Scimago Graphica were used to analyze basic bibliometric parameters, leading producers, high-impact keywords, and research trends. RESULTS: A total of 3324 OHRQoL-related articles (3119 original research articles and 205 review papers) were collected, which received 65,704 citations. A total of 9950 authors from 2429 organizations contributed to this body of research. Prolific authors from Europe, USA, Brazil, New Zealand, China, and Canada were identified, and they also centered collaboration clusters in the co-author network. Community Dentistry and Oral Epidemiology was the most prolific journal. Twenty-one keywords with more than 200 occurrences, and 23 keywords with more than 150 occurrences, were identified for publications of 1994-2021 and 2012-2021, respectively. Keyword analysis revealed hot topics such as instrument development and validation, studies targeting children and adolescents, as well as clinical studies in operative dentistry, implantology, orthodontics, and community dentistry. Oral Health Impact Profile is the most commonly used instrument in OHRQoL-related research. CONCLUSIONS: OHRQoL is an impactful topic in dental health care as it is not only useful in dental research and patient-centered clinical outcome measures but also provides valuable guidance in dental public health administration and policy making. OHRQoL-related research presents a dynamic landscape and is expected to continue presenting high productivity and broad application in the future.

Which dentine analogue material can replace human dentine for crown fatigue test?

OBJECTIVE: To seek dentine analogue materials in combined experimental, analytical, and numerical approaches on the mechanical properties and fatigue behaviours that could replace human dentine in a crown fatigue laboratory test. METHODS: A woven glass fibre-filled epoxy (NEMA grade G10; G10) and a glass fibre-reinforced polyamide-nylon (30% glass fibre reinforced polyamide-nylon 6,6; RPN) were investigated and compared with human dentine (HD). Flexural strength and elastic modulus (n = 10) were tested on beam-shaped specimens via three-point bending, while indentation hardness (n = 3) was tested after fracture. Abutment substrates of G10, RPN and HD were prepared and resin-bonded with monolithic lithium disilicate crowns (n = 10), then subjected to wet cyclic loading in a step-stress manner (500 N initial load, 100 N step size, 100,000 cycles per step, 20 Hz frequency). Data were statistically analysed using Kruskal-Wallis one-way ANOVA followed by post-hoc comparisons (α = 0.05). Survival probability estimation was performed by Mantel-Cox Log-Rank test with 95% confidence intervals. The fatigue failure load (FFL) and the number of cycles until failure (NCF) were evaluated with Weibull statistics. Finite Element Models of the fatigue test were established for stress distribution analysis and lifetime prediction. Fractographic observations were qualitatively analysed. RESULTS: The flexural strength of HD (164.27 ± 14.24 MPa), G10 (116.48 ± 5.93 MPa), and RPN (86.73 ± 3.56 MPa) were significantly different (p < 0.001), while no significant difference was observed in their flexural moduli (p = 0.377) and the indentation hardness between HD and RPN (p = 0.749). The wet cyclic fatigue test revealed comparable mean FFL and NCF of G10 and RPN to HD (p = 0.237 and 0.294, respectively) and similar survival probabilities for the three groups (p = 0.055). However, RPN promotes higher stability and lower deviation of fatigue test results than G10 in Weibull analysis and FEA. SIGNIFICANCE: Even though dentine analogue materials might exhibit similar elastic properties and fatigue performance to human dentine, different reliabilities of fatigue on crown-dentine analogues were shown. RPN seems to be a better substrate that could provide higher reliability and predictability of laboratory study results.

Antioral Cancer Effects by the Nitrated [6,6,6]Tricycles Compound (SK1) In Vitro.

A novel nitrated [6,6,6]tricycles-derived compound containing nitro, methoxy, and ispropyloxy groups, namely SK1, was developed in our previous report. However, the anticancer effects of SK1 were not assessed. Moreover, SK1 contains two nitro groups (NO2) and one nitrogen-oxygen (N-O) bond exhibiting the potential for oxidative stress generation, but this was not examined. The present study aimed to evaluate the antiproliferation effects and oxidative stress and its associated responses between oral cancer and normal cells. Based on the MTS assay, SK1 demonstrated more antiproliferation ability in oral cancer cells than normal cells, reversed by N-acetylcysteine. This suggests that SK1 causes antiproliferation effects preferentially in an oxidative stress-dependent manner. The oxidative stress-associated responses were further validated, showing higher ROS/MitoSOX burst, MMP, and GSH depletion in oral cancer cells than in normal cells. Meanwhile, SK1 caused oxidative stress-causing apoptosis, such as caspases 3/8/9, and DNA damages, such as γH2AX and 8-OHdG, to a greater extent in oral cancer cells than in normal cells. Siilar to cell viability, these oxidative stress responses were partially diminished by NAC, indicating that SK1 promoted oxidative stress-dependent responses. In conclusion, SK1 exerts oxidative stress, apoptosis, and DNA damage to a greater extent to oral cancer cells than in normal cells.

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.

Corrosion Resistance of the GO/ZIF-8 Hybrid Loading Benzotriazole as a Multifunctional Composite Filler-Modified MgAlY Layered Double Hydroxide Coating.

A composite coating with good load-carrying and controlled release capabilities for the corrosion inhibitor benzotriazole (BTA) was prepared while providing active and passive corrosion protection for magnesium alloy systems. In this paper, the organic corrosion inhibitor BTA was loaded into the ZIF-8/GO hybrid (GZB), and then, the GZB composite was coated with hexadecyltrimethoxysilane (HDTMS). Then, the GZB composites carried by HDTMS were made to adhere a ternary MgAlY layered double hydroxide (LDH) coating based on microarc oxidation (MAO) coating by electrophoresis (Si-MgAlY LDH coating). The successful loading of BTA by GZB composites was verified by X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). Meanwhile, the Si-MgAlY LDH coating was characterized by X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy. The potentiodynamic polarization curves show that the corrosion current density of the Si-MgAlY LDH coating reaches (2.08 ± 0.49) × 10-9 A/cm2, which means that the Si-MgAlY LDH coating greatly improves the corrosion resistance of magnesium alloy AZ31. The Si-MgAlY LDH coating can also achieve self-healing function in harsh environments, which is attributed to the synergistic effect of passive and active protection. The composite coating is of great significance to expand the potential applications of magnesium alloys.

The Effect of Fine-Grained Control of Workflow on Informal Learning: The Mediating Effect of Teacher Burnout.

Workflow fine control is an important research tool for the mediating effect of teacher burnout. Based on the fine control theory of workflow, this paper constructs a mediating effect model of teacher burnout in primary and secondary school teachers from the perspective of informal learning. The model designs a measurement scale based on the results of fine control, and the scale is revised through informal learning pretests to form the logical frame analysis loop of this paper. The scale uses Likert 5-point scoring, from 1.5 to represent never, rarely, occasionally, often, and always, which solves the difficulty of quantitative analysis of teacher burnout data. During the simulation process, SPSS 20.0 and AMOS 7.0 were used to conduct empirical analysis, exploratory factor analysis and confirmatory factor analysis on the survey data, and the measurement scales were tested. The empirical analysis results show that this paper uses cluster sampling and random sampling to carry out a questionnaire survey on 1022 primary and secondary school teachers. The measurement scale includes 19 items. Through exploratory factor analysis and confirmatory factor analysis, the control method is determined. In two dimensions, the revised control style questionnaire has a reliability of 0.951, and items with factor loadings less than 0.5 are eliminated, which effectively improves the control performance of informal learning.

Compute-in-Memory for Numerical Computations.

In recent years, compute-in-memory (CIM) has been extensively studied to improve the energy efficiency of computing by reducing data movement. At present, CIM is frequently used in data-intensive computing. Data-intensive computing applications, such as all kinds of neural networks (NNs) in machine learning (ML), are regarded as 'soft' computing tasks. The 'soft' computing tasks are computations that can tolerate low computing precision with little accuracy degradation. However, 'hard' tasks aimed at numerical computations require high-precision computing and are also accompanied by energy efficiency problems. Numerical computations exist in lots of applications, including partial differential equations (PDEs) and large-scale matrix multiplication. Therefore, it is necessary to study CIM for numerical computations. This article reviews the recent developments of CIM for numerical computations. The different kinds of numerical methods solving partial differential equations and the transformation of matrixes are deduced in detail. This paper also discusses the iterative computation of a large-scale matrix, which tremendously affects the efficiency of numerical computations. The working procedure of the ReRAM-based partial differential equation solver is emphatically introduced. Moreover, other PDEs solvers, and other research about CIM for numerical computations, are also summarized. Finally, prospects and the future of CIM for numerical computations with high accuracy are discussed.

Morphology and fracture behavior of lithium disilicate dental crowns designed by human and knowledge-based AI.

This study aimed to compare the occlusal morphology and fracture behavior of lithium disilicate ceramic dental crowns on 12 human participants' premolar #45 designed by a knowledge-based AI (CEREC, biogeneric individual function, BI) and different human personnel (experienced technician, TD, and trained dental students, AD) using CAD software. Digital datasets of crown design were best-fit aligned with the original teeth to evaluate profile and volume discrepancies of the occlusal morphology, and difference in the functional cuspal angle. Milled and sintered lithium disilicate crowns were resin-luted to 3D-printed dental casts and were subjected to axial load-to-fracture test. The fracture loads and failure modes were recorded and examined. Repeated measures ANOVA with LSD post-hoc test, Kruskal-Wallis test, Pearson's correlation coefficient, paired t-test, and chi-square exact test were used for statistical analyses (α = 0.05). BI-generated crowns showed the highest occlusal profile discrepancy (0.3677 ± 0.0388 mm), whereas human-CAD designed crowns showed higher conformity to the original teeth (0.3254 ± 0.0515 mm for TD, 0.3571 ± 0.0820 for AD; z-difference method; p < 0.001). Cusp angle values were significantly different in all groups except BI and TD (54.76 ± 3.81° for the original teeth, 70.84 ± 4.31° for BI, 67.45 ± 5.30° for TD, and 62.30 ± 7.92° for AD; p < 0.001). Although all three groups of crown designs could achieve clinically acceptable fracture resistance (1556.09 ± 525.68 N for BI, 1486.00 ± 520.08 N for TD, 1425.77 ± 433.34 for AD; p = 0.505) such that no significant difference in fracture strength was found, most crowns presented catastrophic bulk fracture that was not clinically restorable because of the substrate fracture. Group BI had a significantly higher percentage of restorable substrate damage than TD (p = 0.014) and AD (p < 0.001). In conclusion, in designing lithium disilicate dental crown, CAD design with human may be better than knowledge-based AI.

Novel Step Floating Islands VDMOS with Low Specific on-Resistance by TCAD Simulation.

A novel VDMOS with Step Floating Islands VDMOS (S-FLI VDMOS) is proposed for the first time in this letter, in order to optimize the breakdown voltage (BV) and the specific on-resistance (Ron,sp). The innovative terminal technology of Breakdown Point Transfer (BPT) is applied to S-FLI VDMOS, which transfers the breakdown point from the high electric field region to the low electric field region, and the S-FLI VDMOS structure uses multiple layers of charge compensation blocks to generate multiple electric field peaks in the drift region in order to optimize the electric field distribution. In the TCAD simulation, the BV of the proposed S-FLI VDMOS is improved to 326 V, which is higher than that of 281 V for the conventional Si VDMOS with the same drift region length of 15 µm, and the Ron,sp is reduced from 21.54 mΩ·cm2 for the conventional Si VDMOS to 7.77 mΩ·cm2 for the S-FLI VDMOS. Compared with the conventional Si VDMOS, the current density of the effective current conduction path is increased when the forward bias is applied to the proposed device.

Adverse events of different PD-1 inhibitors in lung cancer patients: a real-world study.

Background: Programmed death-1 (PD-1) inhibitors have been approved and are currently widely used to treat lung cancer patients. However, comparative data on the adverse events (AEs) associated with different PD-1 inhibitors are very limited. Methods: Patients with histologically confirmed lung cancer who had been treated with at least 1 dose of PD-1 inhibitors between January 2017 and December 2019 at a tertiary cancer hospital were included in the study. Data on treatment-related AEs (tr-AEs) were collected from their electronic medical records. Results: A total of 227 lung cancer patients treated with nivolumab (n=83), pembrolizumab (n=65), camrelizumab (n=27), sintilimab (n=31), and toripalimab (n=21) were included. In relation to nivolumab, pembrolizumab, camrelizumab, sintilimab, and toripalimab, the incidence rates of all-grade tr-AEs were 37.34%, 24.62%, 62.96%, 29.03% and 9.52%, respectively (P=0.01), and the incidence rates of grade 3-4 tr-AEs were 2.41%, 3.08%, 22.22%, 3.23% and 0%, respectively (P=0.05). The most common all-grade tr-AEs were capillary hemangioma (22.22%) and abnormal liver function (22.22%) for camrelizumab, pneumonitis for nivolumab (12.05%), pembrolizumab (6.15%) and nausea/vomiting (12.9%) for sintilimab, and pneumonitis (4.76%), rash/pruritus (4.76%) and shingles (4.76%) for toripalimab. Sex, age, PD-1 inhibitors, histology type and PD-1 cycles were significantly associated with tr-AEs. Conclusions: There were significant differences in the incidence and most common tr-AEs among the different PD-1 inhibitors. Different monitoring priorities should be given to different PD-1 inhibitors during treatment cycles.

Decrease in ambient volatile organic compounds during the COVID-19 lockdown period in the Pearl River Delta region, south China.

During the COVID-19 lockdown, ambient ozone levels are widely reported to show much smaller decreases or even dramatical increases under substantially reduced precursor NOx levels, yet changes in ambient precursor volatile organic compounds (VOCs) have been scarcely reported during the COVID-19 lockdown, which is an opportunity to examine the impacts of dramatically changing anthropogenic emissions on ambient VOC levels in megacities where ozone formation is largely VOC-limited. In this study, ambient VOCs were monitored online at an urban site in Guangzhou in the Pearl River Delta region before, during, and after the COVID-19 lockdown. The average total mixing ratios of VOCs became 19.1% lower during the lockdown than before, and those of alkanes, alkenes and aromatics decreased by 19.0%, 24.8% and 38.2%, respectively. The levels of light alkanes (C < 6) decreased by only 13.0%, while those of higher alkanes (C ≥ 6) decreased by 67.8% during the lockdown. Disappeared peak VOC levels in morning rush hours and the drop in toluene to benzene ratios during the lockdown suggested significant reductions in vehicle exhaust and industrial solvent emissions. Source apportioning by positive matrix factorization model revealed that reductions in industrial emissions, diesel exhaust (on-road diesel vehicles and off-road diesel engines) and gasoline-related emissions could account for 48.9%, 42.2% and 8.8%, respectively, of the decreased VOC levels during the lockdown. Moreover, the reduction in industrial emissions could explain 56.0% and 70.0% of the reductions in ambient levels of reactive alkenes and aromatics, respectively. An average increase in O3-1 h by 17% and a decrease in the daily maximum 8-h average ozone by 11% under an average decrease in NOx by 57.0% and a decrease in VOCs by 19.1% during the lockdown demonstrated that controlling emissions of precursors VOCs and NOx to prevent ambient O3 pollution in megacities such as Guangzhou remains a highly challenging task.