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With the rapid development of technologies, the third generation semiconductor is being studied, as it is leading to the significant change in industry like the manufacture of PC, mobile devices, lighting etc. Till now, due to its irreplaceable physical characteristics, third generation semiconductor is applied to lots of fields. This paper analyzes the application of third generation semiconductor, namely, GaN and SiC. Their characteristics including advantages as well as disadvantages will be discussed through reviewing the result of relevant researches. Meanwhile, comparison between the third generation semiconductors and the second as well as the first generation semiconductors is made in this paper. Through the comparison of physical characteristics, recent marketing, production and limitations, the advantages and disadvantages of each semiconductor is analyzed and the suggestion of how to avoid the disadvantage through application is proposed. At last, the future development is predicted. According to the analysis result of this paper, silicon poses more merits. Silicon is not only cheaper but also performs better making it a preference of GaAs, and GaN in the domain of IC. The second generation semiconductor, GaAs, is widely used in the circuits and photoelectric integration. Furthermore, the third semiconductor material GaN is a promising material for power switching and communication and has the great possibility to play a crucial role in market.

Central nervous system (CNS) diseases are some of the most difficult to treat because the blood-brain barrier (BBB) almost entirely limits the passage of many therapeutic drugs into the CNS. Gene therapy based on the adeno-associated virus (AAV) vector has the potential to overcome this problem. For example, an AAV serotype AAV9 has been widely studied for its ability to cross the BBB to transduce astrocytes, but its efficiency is limited. The emergence of AAV directed evolution technology provides a solution, and the variants derived from AAV9 directed evolution have been shown to have significantly higher crossing efficiency than AAV9. However, the mechanisms by which AAV crosses the BBB are still unclear. In this review, we focus on recent advances in crossing the blood-brain barrier with AAV vectors. We first review the AAV serotypes that can be applied to treating CNS diseases. Recent progress in possible AAV crossing the BBB and transduction mechanisms are then summarized. Finally, the methods to improve the AAV transduction efficiency are discussed.

Digital rural construction is a key strategic direction to promote China’s rural revitalization and alleviate global climate problems. In order to put forward feasible suggestions for the subsequent development and ensure the smooth development of digital village construction, how to reflect the development level of the digital village through scientific and reasonable comprehensive evaluation has become an urgent problem to be solved. This paper establishes a comprehensive evaluation index system through the Delphi method and principal component analysis method, then assigns weights to the evaluation indicators based on the improved CRITIC-G1 method, and then grades the development level of digital villages according to the extension matter element method. Finally, taking Jiangxi Province in China as an example, the overall development level of digital villages in Jiangxi Province is evaluated from the provincial level according to the proposed method. And put forward the corresponding countermeasures and suggestions. Results: Firstly, the development level of digital villages in Jiangxi Province is good, and there is a trend of excellent development level. Secondly, from different aspects of digital rural development, the digitalization of infrastructure, services, economy, and green production in Jiangxi Province is at a good level, and the digitalization of life has reached an excellent level. Thirdly, from the perspective of development trends, the digitization of infrastructure has a progressive trend towards an excellent level of development, while the digitization of services, economy and green production has signs of development regression. According to the analysis results, the relevant countermeasures and suggestions are put forward from four aspects: talent, capital, governance system and development planning. Other regions can evaluate the development level of the digital village according to the evaluation model proposed in this paper so as to analyze the existing problems and put forward targeted solutions to promote the construction of the digital village.

Most acute strokes are ischemic, and subsequent neuroinflammation promotes further damage leading to cell death but also plays a beneficial role by promoting cellular repair. Neutrophils are forerunners to brain lesions after ischemic stroke and exert elaborate functions. While neutrophil extracellular traps (NETs) possess a fundamental antimicrobial function within the innate immune system under physiological circumstances, increasing evidence indicates that NETosis, the release process of NETs, occurs in the pathogenic process of stroke. In this review, we focus on the processes of NET formation and clearance, the temporal and spatial alterations of neutrophils and NETs after ischemic damage, and how NETs are involved in several stroke-related phenomena. Generally, NET formation and release processes depend on the generation of reactive oxygen species (ROS) and the activation of nuclear peptidylarginine deiminase-4 (PAD4). The acid–base environment, oxygen concentration, and iron ions around the infarct may also impact NET formation. DNase 1 has been identified as the primary degrader of NETs in serum, while reactive microglia are expected to inhibit the formation of NETs around ischemic lesions by phagocytosis of neutrophils. The neutrophils and NETs are present in the perivascular space ipsilateral to the infarct arising after ischemic damage, peaking between 1 and 3 days postischemia, but their location in the brain parenchyma remains controversial. After the ischemic injury, NETs are involved in the destruction of neurological function primarily by disrupting the blood–brain barrier and promoting thrombosis. The potential effects of NETs on various ischemic nerve cells need to be further investigated, especially in the chronic ischemic phase.

Blockchain is considered a breakthrough technology in the construction industry, with the potential to improve the trust environment and workflow of construction stakeholders. Although recent research offers hints regarding possible contributing elements to blockchain adoption in the construction industry, no specific study has addressed this topic. This knowledge gap hinders the adoption and promotion of blockchain in construction organizations. This study aimed to identify the determinants of blockchain adoption in the construction industry and verify the influence of the combination of various factors on adoption intention. Based on the technology–organization–environment framework, a conceptual model of blockchain adoption in the construction industry was constructed. Data were collected through the distribution of questionnaires, and 244 professionals in the construction field participated in this study. To evaluate the model hypotheses, we used a two-stage partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) combination. The PLS-SEM revealed that factors such as compatibility, top management support, relative advantage, regulatory support, cost, competitive pressure, organizational readiness, and firm size significantly influence blockchain adoption. The fsQCA indicated that six causal conditions achieve high adoption intention. This is one of the first empirical studies on blockchain adoption in the construction industry, which can aid organizations, policymakers, and project participants in making informed decisions regarding the adoption of blockchain.

Colorectal cancer (CRC) is commonly associated with aberrant transcription regulation, but characteristics of the dysregulated transcription factors in CRC pathogenesis remain to be elucidated. In the present study, core-binding factor β (CBFβ) is found to be significantly upregulated in human CRC tissues and correlates with poor survival rate of CRC patients. Mechanistically, CBFβ is found to promote CRC cell proliferation, migration, invasion, and inhibit cell apoptosis in a RUNX2-dependent way. Transcriptome studies reveal that CBFβ and RUNX2 form a transcriptional complex that activates gene expression of OPN, FAM129A, and UPP1. Furthermore, CBFβ significantly promotes CRC tumor growth and live metastasis in a mouse xenograft model and a mouse liver metastasis model. In addition, tumor-suppressive miR-143/145 are found to inhibit CBFβ expression by specifically targeting its 3′-UTR region. Consistently, an inverse correlation between miR-143/miR-145 and CBFβ expression levels is present in CRC patients. Taken together, this study uncovers a novel regulatory role of CBFβ-RUNX2 complex in the transcriptional activation of OPN, FAM129A, and UPP1 during CRC development, and may provide important insights into CRC pathogenesis.

The dynamic immune response to various diseases and therapies has been considered a promising indicator of disease status and therapeutic effectiveness. For instance, the human peripheral blood mononuclear cell (PBMC), as a major player in the immune system, is an important index to indicate a patient’s immune function. Therefore, establishing a simple yet sensitive tool that can frequently assess the immune system during the course of disease and treatment is of great importance. This study introduced an integrated system that includes an electrochemical impedance spectroscope (EIS)-based biosensor in a digital microfluidic (DMF) device, to quantify the PBMC abundance with minimally trained hands. Moreover, we exploited the unique droplet manipulation feature of the DMF platform and conducted a dynamic cell capture assay, which enhanced the detection signal by 2.4-fold. This integrated system was able to detect as few as 104 PBMCs per mL, presenting suitable sensitivity to quantify PBMCs. This integrated system is easy-to-operate and sensitive, and therefore holds great potential as a powerful tool to profile immune-mediated therapeutic responses in a timely manner, which can be further evolved as a point-of-care diagnostic device to conduct near-patient tests from blood samples.

Parasitic nematodes infect one quarter of the world’s population and impact all humans through widespread infection of crops and livestock. Resistance to current anthelmintics has prompted the search for new drugs. Traditional screens that rely on parasitic worms are costly and labour intensive and target-based approaches have failed to yield novel anthelmintics. Here, we present our screen of 67,012 compounds to identify those that kill the non-parasitic nematode Caenorhabditis elegans . We then rescreen our hits in two parasitic nematode species and two vertebrate models (HEK293 cells and zebrafish), and identify 30 structurally distinct anthelmintic lead molecules. Genetic screens of 19 million C. elegans mutants reveal those nematicides for which the generation of resistance is and is not likely. We identify the target of one lead with nematode specificity and nanomolar potency as complex II of the electron transport chain. This work establishes C. elegans as an effective and cost-efficient model system for anthelmintic discovery. Screening for new anthelmintic compounds that are active against parasitic nematodes is costly and labour intensive. Here, the authors use the non-parasitic nematode Caenorhabditis elegans to identify 30 anthelmintic lead compounds in an effective and cost-efficient manner.

Background In China many respiratory pathogens stayed low activities amid the COVID-19 pandemic due to strict measures and controls. We here aimed to study the epidemiological and clinical characteristics of pediatric inpatients with Mycoplasma pneumoniae pneumonia (MPP) after the mandatory COVID-19 restrictions were lifted, in comparison to those before the COVID-19 pandemic. Methods We here included 4,296 pediatric patients with MPP, hospitalized by two medical centers in Jiangsu Province, China, from January 2015 to March 2024. Patients were divided into the pre-COVID ( n  = 1,662) and post-COVID ( n  = 2,634) groups. Their baseline characteristics, laboratory test results and radiological patterns were separately assessed and compared between the two groups to determine the substantial changes in the disease profile of MPP after the COVID-19 pandemic. Results Epidemiological results suggested a higher annual incidence of MPP after the COVID-19 pandemic when the outbreak reached a peak in October, two months delayed in seasonality compared to that in the pre-COVID era. For pediatric patients with MPP, there was no difference in their median ages, gender ratios, and severe case percentages between the two groups, where most patients were younger than 14 years old. With significance, the post-COVID group had more occurrences of cough and expectoration and higher incidences of influenza A/B virus (IAV/IBV) co-infection than the pre-COVID group. Many hematological parameters and radiological features between the two groups displayed alteration, but comparatively there demonstrated no worsened severity in hospitalized children with MPP after COVID-19 pandemic. Concurrently, the post-COVID group was administered with fewer antibiotics but more corticosteroids for effective treatment than the pre-COVID group. Conclusion Through the COVID-19 pandemic, the epidemiological and clinical characteristics of pediatric patients with MPP differed, but there was no evident change in the disease severity. After the COVID-19 pandemic, the increased incidence of IAV/IBV co-infection may contribute to the differences in clinical symptoms and hematological profiles, while the adding usage of corticosteroids might treat more effectively.

Modern high-resolution microscopes are commonly used to study specimens that have dense and aperiodic spatial structure. Extracting meaningful information from images obtained from such microscopes remains a formidable challenge. Fourier analysis is commonly used to analyze the structure of such images. However, the Fourier transform fundamentally suffers from severe phase noise when applied to aperiodic images. Here, we report the development of an algorithm based on nonconvex optimization that directly uncovers the fundamental motifs present in a real-space image. Apart from being quantitatively superior to traditional Fourier analysis, we show that this algorithm also uncovers phase sensitive information about the underlying motif structure. We demonstrate its usefulness by studying scanning tunneling microscopy images of a Co-doped iron arsenide superconductor and prove that the application of the algorithm allows for the complete recovery of quasiparticle interference in this material. Aperiodic structure imaging suffers limitations when utilizing Fourier analysis. The authors report an algorithm that quantitatively overcomes these limitations based on nonconvex optimization, demonstrated by studying aperiodic structures via the phase sensitive interference in STM images.