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Abstract Vertical cavity surface emitting lasers (VCSELs) have emerged as a versatile and promising platform for developing advanced integrated photonic devices and systems due to their low power consumption, high modulation bandwidth, small footprint, excellent scalability, and compatibility with monolithic integration. By combining these unique capabilities of VCSELs with the functionalities offered by micro/nano optical structures (e.g. metasurfaces), it enables various versatile energy-efficient integrated photonic devices and systems with compact size, enhanced performance, and improved reliability and functionality. This review provides a comprehensive overview of the state-of-the-art versatile integrated photonic devices/systems based on VCSELs, including photonic neural networks, vortex beam emitters, holographic devices, beam deflectors, atomic sensors, and biosensors. By leveraging the capabilities of VCSELs, these integrated photonic devices/systems open up new opportunities in various fields, including artificial intelligence, large-capacity optical communication, imaging, biosensing, and so on. Through this comprehensive review, we aim to provide a detailed understanding of the pivotal role played by VCSELs in integrated photonics and highlight their significance in advancing the field towards efficient, compact, and versatile photonic solutions.

Recent advances in scaffold-free three-dimensional (3D) culture methods have significantly enhanced the potential of stem cell-based therapies in regenerative medicine. This cutting-edge technology circumvents the use of exogenous biomaterial and prevents its associated complications. The 3D culture system preserves crucial intercellular interactions and extracellular matrix support, closely mimicking natural biological niches. Therefore, stem cells cultured in 3D formats exhibit distinct characteristics, showcasing their capabilities in promoting angiogenesis and immunomodulation. This review aims to elucidate foundational technologies and recent breakthroughs in 3D scaffold-free stem cell engineering, offering comprehensive guidance for researchers to advance this technology across various clinical applications. We first introduce the various sources of stem cells and provide a comparative analysis of two-dimensional (2D) and 3D culture systems. Given the advantages of 3D culture systems, we delve into the specific fabrication and harvesting techniques for cell sheets and spheroids. Furthermore, we explore their applications in pre-clinical studies, particularly in large animal models and clinical trials. We also discuss multidisciplinary strategies to overcome existing limitations such as insufficient efficacy, hostile microenvironments, and the need for scalability and standardization of stem cell-based products.

The thermal error of machine tool has always been an important reason affecting the accuracy of machine tool. In modern methods to reduce thermal error, thermal error compensation method and thermal error isolation method are two methods with high operability. Thermal error compensation method emphasizes predicting deformation in advance and then compensating in advance. Thermal error isolation method emphasizes the reduction of numerical value in thermal error propagation path. In this paper, the machine tool swing head is taken as the research object, and the above two methods are innovatively combined; Build an experimental platform and a simulation model to ensure the accuracy of the experiment through mutual verification; The POA-LSTM prediction model is established to predict the expansion of the swing head shell structure caused by thermal load accumulation, and compared with the LSTM prediction model. The results show that the prediction accuracy of the POA-LSTM prediction model in Z direction and X direction is 98.89 % and 98.38 %, respectively, which is higher than that of LSTM's 89.33 % and 89.47 %. The experiment for shell structure optimization is designed to reduce the thermal expansion of the pendulum and improve the machining accuracy. As a result, the thermal expansion inhibition effect on the whole pendulum is 26.14 %, and the thermal expansion inhibition effects on the X-direction, Y-direction and Z-direction are 34.93 %, 33.35 % and 30.24 % respectively.

Abstract Background Teeth identification has a pivotal role in the dental curriculum and provides one of the important foundations of clinical practice. Accurately identifying teeth is a vital aspect of dental education and clinical practice, but can be challenging due to the anatomical similarities between categories. In this study, we aim to explore the possibility of using a deep learning model to classify isolated tooth by a set of photographs. Methods A collection of 5,100 photographs from 850 isolated human tooth specimens were assembled to serve as the dataset for this study. Each tooth was carefully labeled during the data collection phase through direct observation. We developed a deep learning model that incorporates the state-of-the-art feature extractor and attention mechanism to classify each tooth based on a set of 6 photographs captured from multiple angles. To increase the validity of model evaluation, a voting-based strategy was applied to refine the test set to generate a more reliable label, and the model was evaluated under different types of classification granularities. Results This deep learning model achieved top-3 accuracies of over 90% in all classification types, with an average AUC of 0.95. The Cohen’s Kappa demonstrated good agreement between model prediction and the test set. Conclusions This deep learning model can achieve performance comparable to that of human experts and has the potential to become a valuable tool for dental education and various applications in accurately identifying isolated tooth.

Public environmental concern (PEC) serves as a prominent representative of informal environmental regulation, which in turn propels the high-quality economic development. It’s important to understand how enterprise digital transformation (EDT) and PEC are connected, as this connection plays a crucial role in driving strong economic growth—it can be seen as a key pathway to achieving high-quality economic development. This research examines the influence and mechanism of PEC on EDT through the analysis of data obtained from publicly traded companies in Shanghai and Shenzhen, China along with city-level PEC data covering the period from 2010 to 2021. In addition, a heterogeneity analysis was performed to examine the variations among cities, industries, and enterprises, and we obtained a total of three conclusions as follows. (1) The results of our study reveal a statistically significant positive association, indicating that an increase in PEC has a substantial impact on the development of EDT. This association remains robust even after a series of robustness tests. (2) Mechanistic analyses further support our finding. PEC encourages companies to investments in research and development (R&D), attract skilled personnel, and commit to environmental responsibilities, thus promoting EDT. (3) From the municipal viewpoint, the influence of PEC on EDT is more significant in cities with advanced digital infrastructure, greater governmental subsidies, and those located in the central and western regions. From an industrial viewpoint, the effect of PEC on EDT is more pronounced in manufacturing firms and heavily polluting industries. At the enterprise level, the beneficial impact of PEC on EDT is more evident in companies with a stronger emphasis on environmental investment, in non-state-owned enterprises, and in those with higher levels of pollution. In conclusion, this research sheds light on the significant role of PEC in driving EDT and, consequently, economic growth. The research will offer valuable insights for policymakers and stakeholders aiming to align economic progress with environmental awareness.

Given the serious neurological complications and deaths associated with enterovirus 71 (EV71) infection, there is an urgent need to develop effective antivirals against this viral infection. In this study, we demonstrated that two Cathelicidin-derived peptides, LL-18 and FF-18 were more potent against EV71 infection than the parent peptide LL-37, which is the mature and processed form of Cathelicidin. These peptides could directly bind to the EV71 virus particles, but not to coxsackievirus, indicative of their high specificity. The binding of peptides with the virus surface occupied the viral canyon region in a way that could block virus-receptor interactions and inhibit viral uncoating. In addition, these peptide analogues could also relieve the deleterious effect of EV71 infection in vivo. Therefore, Cathelicidin-derived peptides might be excellent candidates for further development of antivirals to treat EV71 infection.

The miniature heat sink is an essential component in integrated circuit packaging, playing a vital role in ensuring the stable and reliable performance of integrated circuits. In this paper, we establish a simulation model of the heat transfer performance of a miniature heat sink with a square columnar array microstructure and study the effect of the dimensional parameters of the miniature heat sink on the heat transfer performance. Then, the mathematical equations between the heat source temperature and the dimensional parameters of the miniature heat sink are obtained based on the response surface method, and the dimensional parameters are optimized. Finally, wire electrical discharge machining (WEDM) was used to prepare miniature heat sinks and to test the heat transfer performance. The experimental results show that both the simulation model and the mathematical equations have high accuracy, and the heat source temperature of the miniature heat sink with column width, column distance, and column height of 364 μm, 331 μm, and 1500 μm, respectively, can be reduced to 101.8 °C, which is 93.5 °C lower than the heat source temperature of 195.3 °C without heat sink, and the temperature reduction reaches 47.9%. The miniature heat sink has a simple manufacturing process, low manufacturing cost, small overall size, and good heat transfer performance, which has a broad application prospect in the field of integrated circuit packaging.

Recent advances in scaffold-free three-dimensional (3D) culture methods have significantly enhanced the potential of stem cell-based therapies in regenerative medicine. This cutting-edge technology circumvents the use of exogenous biomaterial and prevents its associated complications. The 3D culture system preserves crucial intercellular interactions and extracellular matrix support, closely mimicking natural biological niches. Therefore, stem cells cultured in 3D formats exhibit distinct characteristics, showcasing their capabilities in promoting angiogenesis and immunomodulation. This review aims to elucidate foundational technologies and recent breakthroughs in 3D scaffold-free stem cell engineering, offering comprehensive guidance for researchers to advance this technology across various clinical applications. We first introduce the various sources of stem cells and provide a comparative analysis of two-dimensional (2D) and 3D culture systems. Given the advantages of 3D culture systems, we delve into the specific fabrication and harvesting techniques for cell sheets and spheroids. Furthermore, we explore their applications in pre-clinical studies, particularly in large animal models and clinical trials. We also discuss multidisciplinary strategies to overcome existing limitations such as insufficient efficacy, hostile microenvironments, and the need for scalability and standardization of stem cell-based products. [ABSTRACT FROM AUTHOR]

In the context of precision diagnosis for various subtypes of melanoma, identifying biomarkers with clinical translational potential from a molecular standpoint is crucial for a more comprehensive characterization of the disease. Mucin 18 (MUC18) is highly expressed in both tumor cells and tumor vasculature in major melanoma subtypes and is restricted to normal tissues. A noninvasive imaging approach for MUC18 in melanoma utilizing an immune positron emission tomography (PET) radionuclide‐conjugated drug (RDC) with an 89Zr‐labeled humanized anti‐MUC18 monoclonal antibody (mAb) was developed. A375, Sk‐Mel‐28, HMVII, and A549 cells and tumor model mice were conducted. Immuno‐PET was employed to assess the specificity and targeting of three distinct melanoma cell line‐derived xenografts (CDXs) and patient‐derived tumor xenografts (PDXs) in immunodeficient mice. The developed RDC, named 89Zr‐IP150, demonstrated robust in vitro stability and high binding affinity, ensuring reliable and specific PET imaging of small, medium, and large subcutaneous tumors in human melanoma mouse xenotransplantation models. Notably, for the first time, the clinical translational potential of 89Zr‐IP150 was successfully validated using PDX models. These findings present a noninvasive, real‐time method for the early screening of MUC18 (+) melanoma patients and are important for studying the early‐stage biological distribution of MUC18‐targeted antibody‐drug conjugates. [ABSTRACT FROM AUTHOR]