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Salmonella is a pathogen that comes from different animal-originated foods and poses a significant threat to human health. The present detection methods for Salmonella are time-consuming and labor-intensive and requires skilled workers and specialized instruments. In this study, the conservative invA was selected as the target gene, and a quantitative detection method for Salmonella with wide availability and user-friendliness was established based on CRISPR Cas12a and a personal glucose meter (PGM). The indirect signal transformation from the original target DNA to the final glucose signal was achieved through RAA, CRISPR Cas12a reaction, enzymic reaction, and glucose signal reading by a PGM (accu-chek type from Roche). This PGMs-CRISPR assay showed a detection sensitivity of Salmonella as low as 5 colony-forming units (CFU)/reaction in either pure culture or artificially contaminated food samples and exhibited specificity between Salmonella isolates and non-Salmonella isolates. Furthermore, quantitative detection of Salmonella in spiked milk samples was also achieved within the range from 1 to 1 × 10

Digital maskless lithography is gaining popularity due to its unique ability to quickly fabricate high-resolution parts without the use of physical masks. By implementing controlled grayscaling and exposure control, it has the potential to replace conventional lithography altogether. However, despite the existence of a theoretical foundation for photopolymerization, observing the voxel growth process in situ is a significant challenge. This difficulty can be attributed to several factors, including the microscopic size of the parts, the low refractive index difference between cured and uncured resin, and the rapid rate of photopolymerization once it crosses a certain threshold. As such, there is a pressing need for a system that can address these issues. To tackle these challenges, the paper proposes a modified Schlieren-based observation system that utilizes confocal magnifying optics to create a virtual screen at the camera's focal plane. This system allows for the visualization of the minute changes in refractive indices made visible by the use of Schlieren optics, specifically the deflection of light by the changing density-induced refractive index gradient. The use of focusing optics provides the system with the flexibility needed to position the virtual screen and implement optical magnification. The researchers employed single-shot binary images with different pixel numbers to fabricate voxels and examine the various factors affecting voxel shape, including chemical composition and energy input. The observed results were then compared against simulations based on Beer–Lambert's law, photopolymerization curve, and Gaussian beam propagation theory. The physical experimental results validated the effectiveness of the proposed observation system. The paper also briefly discusses the application of this system in fabricating microlenses and its advantages over theoretical model-based profile predictions.

IntroductionPreeclampsia (PE) differentially impairs female and male fetal endothelial cell function which is associated with the increased risks of adult-onset cardiovascular disorders in children born to mothers with PE. However, the underlying mechanisms are poorly defined. Wehypothesizethat dysregulation of microRNA-29a-3p and 29c-3p (miR-29a/c-3p) in PE disturbs gene expression and cellular responses to cytokines in fetal endothelial cells in a fetal sex-dependent manner.MethodsRT-qPCR analysis of miR-29a/c-3p was performed on female and male unpassaged (P0) human umbilical vein endothelial cells (HUVECs) from normotensive (NT) and PE pregnancies. Bioinformatic analysis of an RNAseq dataset was performed to identify PE-dysregulated miR-29a/c-3p target genes in female and male P0-HUVECs. Gain- and loss-of-function assays were conducted to determine the effects of miR-29a/c-3p on endothelial monolayer integrity and proliferation in response to TGFβ1 and TNFα in NT and PE HUVECs at passage 1.ResultsPE downregulated miR-29a/c-3p in male, but not female P0-HUVECs. PE dysregulated significantly more miR-29a/c-3p target genes in female vs. male P0-HUVECs. Many of these PE-differentially dysregulated miR-29a/c-3p target genes are associated with critical cardiovascular diseases and endothelial functions. We further demonstrated that miR-29a/c-3p knockdown specifically recovered the PE-abolished TGFβ1-induced strengthening of endothelial monolayer integrity in female HUVECs, while miR-29a/c-3p overexpression specifically enhanced the TNFα-promoted cell proliferation in male PE HUVECs.ConclusionsPE differentially dysregulates miR-29a/c-3p and their target genes associated with cardiovascular diseases- and endothelial function in female and male fetal endothelial cells, possibly contributing to the fetal sex-specific endothelial dysfunction observed in PE.

Direct ink writing (DIW) process is a facile additive manufacturing technology to fabricate three-dimensional (3D) objects with various materials. Its versatility has attracted considerable interest in academia and industry in recent years. As such, upsurging endeavors are invested in advancing the ink flow behaviors in order to optimize the process resolution and the printing quality. However, so far, the physical phenomena during the DIW process are not revealed in detail, leaving a research gap between the physical experiments and its underlying theories. Here, we present a comprehensive analytical study of non-Newtonian ink flow behavior during the DIW process. Different syringe-nozzle geometries are modeled for the comparative case studies. By using the computational fluid dynamics (CFD) simulation method, we reveal the shear-thinning property during the ink extrusion process. Besides, we study the viscosity, shear stress, and velocity fields, and analyze the advantages and drawbacks of each syringe-nozzle model. On the basis of these investigations and analyses, we propose an improved syringe-nozzle geometry for stable extrusion and high printing quality. A set of DIW printing experiments and rheological characterizations are carried out to verify the simulation studies. The results developed in this work offer an in-depth understanding of the ink flow behavior in the DIW process, providing valuable guidelines for optimizing the physical DIW configuration toward high-resolution printing and, consequently, improving the performance of DIW-printed objects.

Inkjet printing (IJP) is one of the promising additive manufacturing techniques that yield many innovations in electronic and biomedical products. In IJP, the products are fabricated by depositing droplets on substrates, and the quality of the products is highly affected by the droplet pinch-off behaviors. Therefore, identifying pinch-off behaviors of droplets is critical. However, annotating the pinch-off behaviors is burdensome since a large amount of images of pinch-off behaviors can be collected. Active learning (AL) is a machine learning technique which extracts human knowledge by iteratively acquiring human annotation and updating the classification model for the pinch-off behaviors identification. Consequently, a good classification performance can be achieved with limited labels. However, during the query process, the most informative instances (i.e., images) are varying and most query strategies in AL cannot handle these dynamics since they are handcrafted. Thus, this paper proposes a multiclass reinforced active learning (MCRAL) framework in which a query strategy is trained by reinforcement learning (RL). We designed a unique intrinsic reward signal to improve the classification model performance. Moreover, how to extract the features from images for pinch-off behavior identification is not trivial. Thus, we used a graph convolutional network for droplet image feature extraction. The results show that MCRAL excels AL and can reduce human efforts in pinch-off behavior identification. We further demonstrated that, by linking the process parameters to the predicted droplet pinch-off behaviors, the droplet pinch-off behavior can be adjusted based on MCRAL.

In recent years, topological data analysis (TDA) has become a popular tool for studying 3D point clouds. Persistent homology is one of the most important tools of TDA, as it can extract the topological features hidden in a point cloud. However, the time-consuming computation of persistence diagrams severely limits the application of TDA. In this study, we propose an end-to-end TopologyNet that directly fits the output of the topological representations from the input point cloud data. TopologyNet significantly reduces the computation time of producing topological representations compared with the traditional pipeline, while maintaining a small approximating error in practical instances. For point cloud generation, we use TopologyNet as a topological branch to improve the performance of a point cloud autoencoder. Moreover, the additional topological features are used in a latent generative adversarial network to produce new point clouds.

Achieving a mesoporous structure in superinsulation materials is pivotal for guaranteeing a harmonious relationship between low thermal conductivity, high porosity, and low density. Herein, we report silica-based cryogel and aerogel materials by implementing freeze-drying and ambient-pressure-drying processes respectively. The obtained freeze-dried cryogels yield thermal conductivity of 23 mW m

Thermal management in energy-efficient solar thermal energy conversion and transparent windows requires advanced materials with low thermal conductivity and high transparency, such as transparent silica aerogel materials. However, the large scatter domains in porous silica materials would deteriorate their optical transparency. Herein, we report transparent silica aerogels by controlling hydrolyzation and meanwhile silylation modification to enhance the integrity of the microstructure under ambient pressure drying. The transparent silica aerogel materials show a broad-spectrum transparency of 70% from 400 nm and 800 nm, showing promising applications in transparent windows and solar thermal energy conversion systems. The scalability for transparent windows could be achieved with a composite material by incorporating transparent polymeric materials. The solar receiver coupled with a transparent silica aerogel could reach 122 °C within 12 min at a solar irradiance of 1 Sun, ∼200% higher than that in the ambient atmosphere. The engineered structure of the transparent porous silica backbone provides a pathway for solar thermal systems and transparent window applications.

Global climate changes are affecting organisms and their interactions in terrestrial and aquatic ecosystems, such as the increase in temperature and CO2 concentration. Herbivory interaction is a very important part of nutrient cycle and energy flow in freshwater ecosystem, and climate changes may directly or indirectly affect aquatic plants, aquatic herbivores and their interactions. In this study, we explored the effects of the rising temperature, elevated CO2 concentrations and herbivory by an herbivorous snail (Radix auricularia L.) on a submerged plant (Vallisneria natans L.). Our results showed that herbivory, temperature, and CO2 had specific effects on snail and plant growth, statistically there was only one interaction-a reduction in leaf number. Under different experimental conditions, snail herbivory always has negative effects on biomass accumulation and growth of V. natans. Moreover, the increases in temperature also inhibited its growth. Snail herbivory reduced the content of total carbon and total nitrogen of V. natans in all treatments, while the total phenols content increased. Our findings indicate that the rising temperature, elevated CO2 concentrations and herbivory have interactive effects on the growth and stoichiometry of submerged macrophytes, but further research is needed between aquatic plants and aquatic herbivores to aid prediction the impact of climate change on freshwater ecosystems.

Accurate recognition of facial expressions and emotional gestures is promising to understand the audience's feedback and engagement on the entertainment content. Existing methods are primarily based on various cameras or wearable sensors, which either raise privacy concerns or demand extra devices. To this aim, we propose a novel ubiquitous sensing system based on the commodity microphone array --- SonicFace, which provides an accessible, unobtrusive, contact-free, and privacy-preserving solution to monitor the user's emotional expressions continuously without playing hearable sound. SonicFace utilizes a pair of speaker and microphone array to recognize various fine-grained facial expressions and emotional hand gestures by emitted ultrasound and received echoes. Based on a set of experimental evaluations, the accuracy of recognizing 6 common facial expressions and 4 emotional gestures can reach around 80%. Besides, the extensive system evaluations with distinct configurations and an extended real-life case study have demonstrated the robustness and generalizability of the proposed SonicFace system.

Intra-articular injections containing a corticosteroid are used frequently, and periprosthetic joint infection is a serious complication after total joint arthroplasty. There is debate regarding whether intra-articular corticosteroid injections before arthroplasty increase periprosthetic joint infection after surgery.(1) Does a previous intra-articular corticosteroid injection increase the odds of infection after subsequent hip or knee arthroplasty? (2) Does this risk vary based on how soon before the arthroplasty (such as less than 3 months before surgery) the injection is administered?Using the PubMed, Embase, Cochrane Library, and Web of Science databases from inception to July 2021, we searched for comparative studies in English on patients who received intra-articular corticosteroid injections before arthroplasty and that tracked the frequency of infection after arthroplasty. We extracted data on the risk of infection after subsequent joint arthroplasty. The keywords included "corticosteroid," "steroid," "arthroplasty," "knee replacement," and "hip replacement." Eleven retrospective, comparative studies from four countries were included, of which 10 reported the specific diagnosis criteria and one did not. These articles included data on 173,465 arthroplasties in the hip or knee, as well as of 73,049 injections and 100,416 control patients. The methodologic quality of the included studies was evaluated according to the Newcastle-Ottawa Quality Assessment Scale; the articles' scores ranged from 6 to 7 (the score itself spans 0 to 9, with higher scores representing better study quality). We found no evidence of publication bias based on the Egger test, and tests of heterogeneity generally found heterogeneity, so a random-effects model was used of our meta-analyses. A meta-analysis was performed with Review Manager 5.3 software and Stata version 12.0 software.Overall, there were no differences in the odds of periprosthetic joint infection between the injection group and the control group among patients who received any kind of injection (odds ratio 1.22 [95% CI 0.95 to 1.58]; p = 0.12). However, in a subgroup analysis, there was a higher OR for postoperative PJI in patients with an intra-articular corticosteroid injection in the knee or hip within 3 months (OR 1.39 [95% CI 1.04 to 1.87]; p = 0.03). There were no differences in the infection risk in patients who had injections between 3 and 6 months before arthroplasty (OR 1.19 [95% CI 0.95 to 1.48]; p = 0.13) or between 6 and 12 months before arthroplasty.The current evidence suggests ipsilateral intra-articular corticosteroid injections within 3 months before arthroplasty were associated with an increased risk of periprosthetic joint infection during subsequent joint arthroplasty. We recommend against performing total joint arthroplasty on a patient who has received an intra-articular corticosteroid injection within 3 months. Further high-quality studies on this topic from registries, national databases, or insurance company data are still required to confirm and extend our findings.Level III, therapeutic study.

Lithium-oxygen batteries suffer from the degradation of the catalytic cathode during long-term operation, which limits their practical use. Understanding the direct correlations between the surface morphological evolution of catalytic cathodes at nanoscale and their catalytic activity during cycling has proved challenging. Here, using

Firms typically introduce online promotional channels based on the cooperative format of agency selling or reselling to promote end-of-season products. The selection of the agency selling or reselling format is greatly affected by a firm’s pricing timing between traditional and online promotional channels, particularly in an uncertain market. Within this context, we examine how the pricing timings in an online promotional channel relative to a traditional channel impact a firm’s selection between agency selling and reselling formats in an uncertain market. We find that the promotional pricing timings have no effect on the firm’s price decisions under the agency selling format, whereas they might lead to downward prices under the reselling format—even lower than those under the agency selling format. We show that considering promotional pricing timing in an uncertain market fundamentally changes the general intuition that the firm prefers the agency selling to reselling format due to the double-marginalization effect. Specifically, the reselling format might be more profitable for the firm when it sets traditional-channel promotional price prior to introducing the online promotional channel in an optimistic market (i.e., a market more likely to have high demand) or adopts the opposite promotional pricing timing of channels in a pessimistic market (i.e., a market more likely to have low demand). Our findings complement the emerging online retail literature by underscoring the interacting forces of promotional pricing timing and uncertain demand on a firm’s reselling versus agency selling format choice in promoting end-of-season product online.

Rhus chinensis Mill. (RCM) is the host plant of Galla chinensis, which is valued in traditional medicine. Environmental temperature directly determines the probability of gallnut formation and RCM growth. At present, there is no experiment to systematically analyse the stability of internal reference gene (RG) expression in RCM. In this experiment, leaves that did not form gallnuts were used as the control group, while leaves that formed gallnuts were used as the experimental group. First, we conducted transcriptome experiments on RCM leaves to obtain 45 103 differential genes and functional enrichment annotations between the two groups. On this basis, this experiment established a transcriptional gene change model of leaves in the process of gallnut formation after being bitten by aphids, and RCM reference candidate genes were screened from RNA sequencing (RNA‐seq) data. This study is based on RCM transcriptome data and evaluates the stability of 11 potential reference genes under cold stress (4 °C) and heat stress (34 °C), using three statistical algorithms (geNorm, NormFinder, and BestKeeper). The results show that GAPDH1 + PP2A2/UBQ are stable reference genes under heat stress, while GAPDH1 + ACT are the most stable under cold stress. This study is the first to screen candidate reference genes in RCM and could help guide future molecular studies in this genus., Appropriate and stable reference genes are important for normalization of gene expression. This study is based on Rhus chinensis Mill. transcriptome data and evaluates the stability of 11 potential reference genes under cold stress (4 °C) and heat stress (34 °C), using three statistical algorithms (geNorm, NormFinder, and BestKeeper). This study is the first to screen candidate reference genes in Rhus chinensis Mill. and could help guide future molecular studies in this genus.

Machine learning is widely used in our daily lives. Large amounts of data have been continuously produced and transmitted to the cloud for model training and data processing, which raises a problem: how to preserve the security of the data. Recently, a secure machine learning system named SecureML has been proposed to solve this issue using two-party computation. However, due to the excessive computation expenses of two-party computation, the secure machine learning is about 2× slower than the original machine learning methods. Previous work on secure machine learning mostly focused on novel protocols or improving accuracy, while the performance metric has been ignored. In this article, we propose a GPU-based framework ParSecureML to improve the performance of secure machine learning algorithms based on two-party computation. The main challenges of developing ParSecureML lie in the complex computation patterns, frequent intra-node data transmission between CPU and GPU, and complicated inter-node data dependence. To handle these challenges, we propose a series of novel solutions, including profiling-guided adaptive GPU utilization, fine-grained double pipeline for intra-node CPU-GPU cooperation, and compressed transmission for inter-node communication. Moreover, we integrate architecture specific optimizations, such as Tensor Cores, into ParSecureML. As far as we know, this is the first GPU-based secure machine learning framework. Compared to the state-of-the-art framework, ParSecureML achieves an average of 33.8× speedup. ParSecureML can also be applied to inferences, which achieves 31.7× speedup on average.