RESUMEN
AlGaN-based solar-blind ultraviolet avalanche detectors have huge potentials in the fields of corona discharge monitoring, biological imaging, etc. Here, we study the impact of the heterojunction polarization-related effects on the AlGaN-based solar-blind ultraviolet avalanche detectors. Our work confirms that the polarization heterojunction is beneficial to reducing avalanche bias and lifting avalanche gain by improving the electric field in the depletion region, while the polarization-induced fixed charges will lead to a redistribution of the electrons, in turn shielding the charges and weakening the electric field enhancement effect. This shielding effect will need external bias to eliminate, and that is why the polarization heterojunction cannot work at relatively low bias but has an enhancement effect at high bias. Controlling the doping level between the hetero-interface can affect the shielding effect. An unintentionally doped polarization heterojunction can effectively reduce the shielding effect, thus reducing the avalanche bias. The conclusions also hold true for the negative polarization regime. We believe our findings can provide some useful insights for the design of the AlGaN-based solar-blind ultraviolet detectors.
RESUMEN
Acute myeloid leukemia (AML) is a rare and heterogeneous disease. Over the past few decades, patient prognosis has improved with continuous improvements in treatment, but outcomes for some patients with primary drug resistance or relapse after treatment remain poor. Additional therapies to improve outcomes for these patients are urgently needed. FYB1 expression differs substantially between AML tissues and normal tissues. High FYB1 expression is correlated with poorer overall survival (OS), indicating that FYB1 may regulate AML progression. Therefore, understanding the effect of FYB1 on AML could improve the success rate of therapeutic approaches and prognosis for patients with AML. In this study, through analysis of large databases and both in vivo and in vitro experiments, we assessed the expression and role of FYB1 in AML and the relationship of FYB with patient prognosis. Downstream targets of the FYB1 gene were analyzed by RNA-seq. Database mining and in vitro experiments were used to further clarify the effect of the downstream target gelsolin-like actin-capping protein (CAPG) on AML cells and its relationship with patient prognosis. FYB1 expression was significantly higher in AML tissue and corresponded with a poor prognosis. FYB1 knockdown inhibited AML cell proliferation, promoted cell apoptosis, reduced cell adhesion capability and significantly reduced the tumor formation rate in mice. In addition, FYB1 knockdown induced a notable decrease in CAPG expression. The suppression of CAPG significantly inhibited cell proliferation and increased cell apoptosis. The conclusions of this study underscore the pivotal role of the FYB1/CAPG axis in promoting AML. We propose that the FYB1/CAPG axis could serve as a new thread in the development of therapeutic strategies for AML.
RESUMEN
A simple and efficient transition-metal/photocatalyst-free visible-light-driven one-pot three-component reaction between thianthrenium salts, carbon disulfide and amines under an air atmosphere for the preparation of biologically relevant S-aryl dithiocarbamates is developed. This methodology is robust and scalable, and exhibits a broad substrate scope and excellent functional group tolerance. Of note, a wide range of primary aliphatic amines bearing different groups are suitable for this strategy. The synthetic utility was further demonstrated by a two-step one-pot multi-component reaction and photo-flow decagram-scale synthesis. Preliminary mechanistic studies suggest that the association of the dithiocarbamate anion with thianthrenium salts formed an electron donor-acceptor complex, which upon excitation with visible light produced an aryl radical via single-electron transfer.
RESUMEN
Large-scale benchmark datasets are crucial in advancing research within the computer science communities. They enable the development of more sophisticated AI models and serve as "golden" benchmarks for evaluating their performance. Thus, ensuring the quality of these datasets is of utmost importance for academic research and the progress of AI systems. For the emerging vision-language tasks, some datasets have been created and frequently used, such as Flickr30k, COCO, and NoCaps, which typically contain a large number of images paired with their ground-truth textual descriptions. In this paper, an automatic method is proposed to assess the quality of large-scale benchmark datasets designed for vision-language tasks. In particular, a new cross-modal matching model is developed, which is capable of automatically scoring the textual descriptions of visual images. Subsequently, this model is employed to evaluate the quality of vision-language datasets by automatically assigning a score to each 'ground-truth' description for every image picture. With a good agreement between manual and automated scoring results on the datasets, our findings reveal significant disparities in the quality of the ground-truth descriptions included in the benchmark datasets. Even more surprising, it is evident that a small portion of the descriptions are unsuitable for serving as reliable ground-truth references. These discoveries emphasize the need for careful utilization of these publicly accessible benchmark databases.
Asunto(s)
Benchmarking , Bases de Datos FactualesRESUMEN
With the fast development of artificial intelligence (AI), Internet of things (IOT), etc, there is an urgent need for the technology that can efficiently recognize, store and process a staggering amount of information. The AlScN material has unique advantages including immense remnant polarization, superior temperature stability and good lattice-match to other III-nitrides, making it easy to integrate with the existing advanced III-nitrides material and device technologies. However, due to the large band-gap, strong coercive field, and low photo-generated carrier generation and separation efficiency, it is difficult for AlScN itself to accumulate enough photo-generated carriers at the surface/interface to induce polarization inversion, limiting its application in in-memory sensing and computing. In this work, an electro-optic duplex memristor on a GaN/AlScN hetero-structure based Schottky diode has been realized. This two-terminal memristor shows good electrical and opto-electrical nonvolatility and reconfigurability. For both electrical and opto-electrical modes, the current on/off ratio can reach the magnitude of 104, and the resistance states can be effectively reset, written and long-termly stored. Based on this device, the "IMP" truth table and the logic "False" can be successfully reproduced, indicating the huge potential of the device in the field of in-memory sensing and computing.
RESUMEN
BACKGROUND: Inflammatory markers, including the product of neutrophil count, platelet count, and monocyte count divided by lymphocyte count (PIV) and the platelet-to-white blood cell ratio (PWR), have not been previously reported as prognostic factors in nasopharyngeal carcinoma (NPC) patients. In order to predict overall survival (OS) in NPC patients, our goal was to create and internally evaluate a nomogram based on inflammatory markers (PIV, PWR). METHODS: A retrospective study was done on patients who received an NPC diagnosis between January 2015 and December 2018. After identifying independent prognostic indicators linked to OS using Cox proportional hazards regression analysis, we created a nomogram with the factors we had chosen. RESULTS: A total of 630 NPC patients in all were split into training (n = 441) and validation sets (n = 189) after being enrolled in a population-based study in 2015-2018 and monitored for a median of 5.9 years. In the training set, the age, PIV, and PWR, selected as independent predictors for OS via multivariate Cox's regression model, were chosen to develop a nomogram. Both training and validation cohorts had C-indices of 0.850 (95% confidence interval [CI]: 0.768-0.849) and 0.851 (95% CI: 0.765-0.877). Furthermore, compared with traditional TNM staging, our nomogram demonstrated greater accuracy in predicting patient outcomes. The risk stratification model derived from our prediction model may facilitate personalized treatment strategies for NPC patients. CONCLUSION: Our findings confirmed the prognostic significance of the PWR and PIV in NPC. High PIV levels (>363.47) and low PWR (≤36.42) values are associated with worse OS in NPC patients.
Asunto(s)
Neoplasias Nasofaríngeas , Nomogramas , Humanos , Carcinoma Nasofaríngeo/patología , Estudios Retrospectivos , PronósticoRESUMEN
BACKGROUND AND PURPOSE: Inhibitors of voltage-gated sodium channels (NaVs) are important anti-epileptic drugs, but the contribution of specific channel isoforms is unknown since available inhibitors are non-selective. We aimed to create novel, isoform selective inhibitors of Nav channels as a means of informing the development of improved antiseizure drugs. EXPERIMENTAL APPROACH: We created a series of compounds with diverse selectivity profiles enabling block of NaV1.6 alone or together with NaV1.2. These novel NaV inhibitors were evaluated for their ability to inhibit electrically evoked seizures in mice with a heterozygous gain-of-function mutation (N1768D/+) in Scn8a (encoding NaV1.6) and in wild-type mice. KEY RESULTS: Pharmacologic inhibition of NaV1.6 in Scn8aN1768D/+ mice prevented seizures evoked by a 6-Hz shock. Inhibitors were also effective in a direct current maximal electroshock seizure assay in wild-type mice. NaV1.6 inhibition correlated with efficacy in both models, even without inhibition of other CNS NaV isoforms. CONCLUSIONS AND IMPLICATIONS: Our data suggest NaV1.6 inhibition is a driver of efficacy for NaV inhibitor anti-seizure medicines. Sparing the NaV1.1 channels of inhibitory interneurons did not compromise efficacy. Selective NaV1.6 inhibitors may provide targeted therapies for human Scn8a developmental and epileptic encephalopathies and improved treatments for idiopathic epilepsies.
RESUMEN
Introduction: COVID-19 continues to spread worldwide, with an increasing number of individuals experiencing reinfection after recovering from their primary infection. However, the nature and progression of this infection remain poorly understood. We aimed to investigate the immune response, severity and outcomes of Omicron BA.5 reinfection among individuals previously infected with different SARS-CoV-2 variants. Methods: We enrolled 432 COVID-19 cases who had experienced prior infection with the ancestral SARS-CoV-2 virus, Delta variant or Omicron BA.2 variant between January 2020 and May 2022 in Guangzhou, China. All cases underwent follow-up from March to April, 2023 through telephone questionnaires and clinical visits. Nasal lavage fluid and peripheral blood were collected to assess anti-RBD IgA, anti-RBD IgG and virus-specific IFN-γ secreting T cells. Results: Our study shows that 73.1%, 56.7% and 12.5% of individuals with a prior infection of the ancestral virus, Delta or Omicron BA.2 variant experienced reinfection with the BA.5 variant, respectively. Fever, cough and sore throat were the most common symptoms of BA.5 reinfection, with most improving within one week and none progressing to a critical condition. Compared with individuals without reinfection, reinfected patients with a prior Delta infection exhibited elevated levels of nasal anti-RBD IgA, serum anti-RBD IgG and IFN-γ secreting T cells, whereas there was no noticeable change in reinfected individuals with a prior BA.2 infection. Conclusion: These results suggest that BA.5 reinfection is common but severe outcomes are relatively rare. Reinfection with a novel SARS-CoV-2 variant different from the prior infection may induce a more robust immune protection, which should be taken into account during vaccine development.