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Ground Penetrating Radar (GPR) image detection currently faces challenges such as low accuracy, false detections, and missed detections. To overcome these challenges, we propose a novel model referred to as GDS-YOLOv8n for detecting common underground targets in GPR images. The model incorporates the DRRB (Dilated Residual Reparam Block) feature extraction module to achieve enhanced multiscale feature extraction, with certain C2f modules in the YOLOv8n architecture being effectively replaced. In addition, the space-to-depth Conv downsampling module is used to replace the Conv modules corresponding to feature maps with a resolution of 320×320 pixels and less. This replacement assists in mitigating information loss during the downsampling of GPR images, particularly for images with limited resolution and small targets. Furthermore, the detection performance is enhanced using an auxiliary training module, ensuring performance improvement without increasing inference complexity. The introduction of the Inner-SIoU loss function refines bounding box predictions by imposing new constraints tailored to GPR image characteristics. Experimental results on real-world GPR datasets demonstrate the effectiveness of the GDS-YOLOv8n model. For six classes of common underground targets, including metal pipes, PVC pipes, and cables, the model achieves a precision of 97.1%, recall of 96.2%, and mean average precision at 50% IoU (mAP50) of 96.9%. These results indicate improvements of 4.0%, 6.1%, and 4.1%, respectively, compared to corresponding values of the YOLOv8n model, with notable improvements observed when detecting PVC pipes and cables. Compared with those of models such as YOLOv5n, YOLOv7-tiny, and SSD (Single Shot multibox Detector), our model’s mAP50 is improved by 7.20%, 5.70%, and 14.48%, respectively. Finally, the application of our model on a NVIDIA Jetson Orin NX embedded system results in an increase in the detection speed from 22 to 40.6 FPS after optimization via TensorRT and FP16 quantization, meeting the demands for the real-time detection of underground targets in mobile scenarios.

Abstract Background Defects in PPP1R12A can lead to genitourinary and/or brain malformation syndrome (GUBS). GUBS is primarily characterized by neurological or genitourinary system abnormalities, but a few reported cases are associated with neonatal seizures. Here, we report a case of a female newborn with neonatal seizures caused by a novel variant in PPP1R12A, aiming to enhance the clinical and variant data of genetic factors related to epilepsy in early life. Methods Whole-exome and Sanger sequencing were used for familial variant assessment, and bioinformatics was employed to annotate the variant. A structural model of the mutant protein was simulated using molecular dynamics (MD), and the free binding energy between PPP1R12A and PPP1CB was analyzed. A mutant plasmid was constructed, and mutant protein expression was analyzed using western blotting (WB), and the interaction between the mutant and PPP1CB proteins using co-immunoprecipitation (Co-IP) experiments. Results The patient experienced tonic-clonic seizures on the second day after birth. Genetic testing revealed a heterozygous variant in PPP1R12A, NM_002480.3:c.2533 C > T (p.Arg845Ter). Both parents had the wild-type gene. MD suggested that loss of the C-terminal structure in the mutant protein altered its structural stability and increased the binding energy with PPP1CB, indicating unstable protein–protein interactions. On WB, a low-molecular-weight band was observed, indicating that the protein was truncated. Co-IP indicated that the mutant protein no longer interacted with PPP1CB, indicating an effect on the structural stability of the myosin phase complex. Conclusion The PPP1R12A c.2533 C > T variant may explain the neonatal seizures in the present case. The findings of this study expand the spectrum of PPP1R12A variants and highlight the potential significance of truncated proteins in the pathogenesis of GUBS.

This study aimed to optimize the extraction and purification processes for selenium-enriched Morchella esculenta (L.) Pers. (also known as Morchella) polysaccharides (Se-MPS) and to evaluate their anti-tumor activities and mechanisms. The extraction process was optimized using single-factor and response surface methodology. The crude polysaccharides were purified through column chromatography and their chemical composition was analyzed. The anti-tumor activity of Se-MPS was evaluated using HepG2 cells through a series of assays, including CCK-8, colony formation, scratching, and Transwell assays. The potential anti-tumor mechanisms of Se-MPS were assessed using RT-qPCR, Western blot, and immunofluorescence methods. Experimental results from single-factor and response surface methodology revealed that the optimal extraction conditions for selenium-enriched Morchella crude polysaccharides were: An extraction time of 2.5 h, a liquid-to-material ratio of 45:1 (mL/g), and an extraction temperature of 82 ℃, yielding a crude polysaccharides yield of 7.95%. After purification, the total sugar content of Se-MPS reached 95.86%, with a selenium concentration of 76.07±0.32 mg/g. Furthermore, Se-MPS significantly reduced colony formation efficiency, cell migration rate, and the number of invasive cells in HepG2 cells (P

Abstract Wine is renowned for its rich content of polyphenols, including resveratrol (Res), known for their health promoting properties. Steamed clam with wine, a popular Mediterranean delicacy that highlights the role of wine as a key ingredient. However, despite these benefits, resveratrol’s low bioavailability poses challenges. Could the process of steaming together with clam alter the digestive fate of resveratrol from wine? This study explores the potential of proteoglycan-based nanoparticles from freshwater clam (CFNPs) as a delivery vehicle for enhancing the stability and bioavailability of resveratrol, compared with wine and free Res’ solution, aiming to elucidate mechanisms facilitating Res’ absorption. The results demonstrated that CFNPs can effectively encapsulate Res with an efficiency over 70%, leading to a uniform particle size of 70.5±0.1 nm (PDI

Objective: To optimize the extraction process of tea polysaccharides from Liubao brick tea and to further investigate the immunomodulatory effects and the possible regulatory mechanisms. Methods: A single-factor experiment was used to investigate the effects of extraction temperature, material-liquid ratio, and ethanol concentration on the yield of tea polysaccharides, based on which the extraction process was optimized by combining with response surface methodology. By measuring the phagocytosis and nitric oxide (NO) release of Liubao brick tea polysaccharides on RAW264.7 cells, detecting the expression of genes and proteins related to nuclear factor-κB (NF-κB) and AMP-dependent protein kinase (AMPK) signaling pathway, in vitro immunomodulatory activity of the purified tea polysaccharides was evaluated. Results: The optimal extraction process for the polysaccharides from Liubao brick tea were as follows: 91.11 ℃ of the extraction temperature, 1:15.45 of the solid-liquid ratio, and 82.84% of the ethanol concentration. In vitro immunomodulatory activity assay showed that Liubao brick tea polysaccharides significantly enhanced phagocytosis and NO release of RAW264.7 cells, significantly activated NF-κB and AMPK signaling pathway, and significantly up-regulated the mRNA expression levels of inducible nitric oxide synthase (iNOS), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and interleukin-1β (IL-1β) to exert immunomodulatory effects. Conclusion: By optimizing the extraction temperature, material-liquid ratio and ethanol concentration, the yield of Liubao brick tea polysaccharide could be effectively improved, and it could play an immunomodulatory role by activating the NF-кB/AMPK pathway. The results provide a research basis for the in-depth investigation and application of the Liubao brick polysaccharide.

Abstract Background Modern perioperative guidelines encourage drinking oral carbohydrates 2 h before management. Nevertheless, research on the safety of preoperative carbohydrate drinks, particularly in extremely elderly patients is lacking. We aimed to evaluate the safety of carbohydrate drinks 2 h before surgery in extremely elderly patients (≥ 80 years) using gastric ultrasonography. Methods We conducted a randomized prospective comparative study of 70 patients aged over 80 years who were scheduled for total knee arthroplasty, hip fracture or humerus fracture surgery. These patients were randomly assigned to the carbohydrate group (n = 35), which fasted from midnight, except for drinking 355 mL of a carbohydrate-containing fluid 2 h before surgery, or the fasting group (n = 35), which fasted from midnight and drank no fluid before surgery. The primary outcome of the study was the cross-sectional area (CSA) of the gastric antrum in the right lateral decubitus position (RLDP) before surgery. The secondary outcomes included CSA in the supine position, intraoperative blood glucose levels and their variability coefficients, Perlas grade, and the visual analog scale of subjective feelings. Results The CSA in the RLDP and supine positions revealed no differences between the carbohydrate and fasting groups at 0 h preoperatively (P > 0.05). In the qualitative assessment, preoperative 0-h Perlas grading did not differ significantly between the groups (P > 0.05). From 2 h before surgery to transfer out of the post-anesthesia care unit, the average blood glucose level of patients in the carbohydrate group was significantly higher than that in the fasting group (P

The unearthed artifacts from the ruins of the Weiyang Palace in the Han Dynasty’s Chang’an City include a large number of bone stick relics. The front and back of each bone stick form a pair, with similar appearances within each pair, indicating a matching relationship. However, the close resemblance in shape and complex texture features of the bone sticks make traditional image matching methods inefficient and less accurate. To address these challenges, this paper proposes a ConvNeXt-based Siamese network for bone stick image matching, utilizing feature similarity metrics. The method introduces a polarized self-attention module to enhance the model’s focus on the edges and texture features of the bone sticks, thereby improving the feature extraction capability of the ConvNeXt network. The utilization of DIS-Net for background normalization reduces noise interference, enhancing the precision of model matching. The adaptive adjustment of the learning rate using the cosine annealing algorithm accelerates network convergence. Additionally, transfer learning and contrastive learning methods are employed to pre-train the network, expediting convergence and improving matching accuracy. Experimental results demonstrate that compared to Siamese network algorithms with backbone networks such as VGG16, ResNet50, and MobileNet, the proposed method achieves an accuracy of 88.46% and 80% at Rank-10. This indicates a higher matching accuracy, providing an effective solution for automated bone stick matching.

Accurate classification of moss species is essential for progress in ecology and biology. However, traditional methods for classifying moss require significant expertise, and current deep learning techniques struggle due to limited dataset diversity and poor performance in multi-class classification tasks. To overcome these challenges, we proposed the Swin Routiformer, a new algorithm for moss image classification that enhances the Swin Transformer with bi-level routing attention. Addressing the issue of limited data, we constructed a dataset with images of 110 different moss types. Additionally, we propose the Crop-Similar data augmentation algorithm, specifically designed for moss images, to reduce background noise interference and prevent information loss due to feature scaling. Adopting the Swin Transformer model with its multi-level hierarchical architecture for visual feature extraction, we introduce the Swin Routiformer Block, which enhances the network’s feature interaction capabilities, reduces computational complexity, and improves classification accuracy and image processing speed for moss species. Our experimental results show that the Swin Routiformer achieves a top-1 accuracy of 82.19% and an f1-score of 82.79% on the test set, outperforming most mainstream models by 4.53% and 1.81% respectively compared to the baseline Swin Transformer model. These findings establish the Swin Routiformer as a valuable tool for the precise identification of moss species, offering significant contributions to the related fields.

Conventional multiple input multiple output (MIMO) detection algorithms face challenges related to computational complexity and limited performance when handling high-dimensional inputs and complex channel conditions. In order to enhance signal recovery accuracy in atmospheric turbulence channels for faster-than-Nyquist (FTN) optical wireless communication (OWC) systems, a deep learning (DL) based MIMO detector is proposed. By leveraging a deep neural network (DNN), it becomes possible to learn nonlinear mappings within MIMO systems, resulting in improved detection performance while reducing computational overheads. Simulation results validate that our proposed DNN detector achieves comparable performance to the maximum likelihood (ML) method, while reducing complexity by 40%.

To mitigate inter-symbol interference (ISI) caused by Faster-than-Nyquist (FTN) technology in a multiple input multiple output (MIMO) optical wireless communication (OWC) system, we propose an ISI cancellation algorithm that combines multi-head self-attention (MHSA), a one-dimensional convolutional neural network (1D CNN), and bi-directional long short-term memory (Bi-LSTM). This hybrid network extracts data features using 1D CNN and captures sequential information with Bi-LSTM, while incorporating MHSA to comprehensively reduce ISI. We analyze the impact of antenna numbers, acceleration factors, wavelength, and turbulence intensity on the system’s bit error rate (BER) performance. Additionally, we compare the waveform graphs and amplitude–frequency characteristics of FTN signals before and after processing, specifically comparing sampled values of four-pulse-amplitude modulation (4PAM) signals with those obtained after ISI cancellation. The simulation results demonstrate that within the Mazo limit for selecting acceleration factors, our proposal achieves a 7 dB improvement in BER compared to the conventional systems without deep learning (DL)-based ISI cancellation algorithms. Furthermore, compared to systems employing a point-by-point elimination adaptive pre-equalization algorithm, our proposal exhibits comparable BER performance to orthogonal transmission systems while reducing computational complexity by 31.15%.

Virus-induced genomic remodeling and altered gene expression contribute significantly to cancer development. Some oncogenic viruses such as Human papillomavirus (HPV) specifically trigger certain cancers by integrating into the host’s DNA, disrupting gene regulation linked to cell growth and migration. The effect can be through direct integration of viral genomes into the host genome or through indirect modulation of host cell pathways/proteins by viral proteins. Viral proteins also disrupt key cellular processes like apoptosis and DNA repair by interacting with host molecules, affecting signaling pathways. These disruptions lead to mutation accumulation and tumorigenesis. This review focuses on recent studies exploring virus-mediated genomic structure, altered gene expression, and epigenetic modifications in tumorigenesis.

BackgroundWe explored clinical characteristics and risk factors for mortality in patients with mental disorders combined with severe pneumonia and developed predictive models.MethodsWe retrospectively analyzed the data of 161 patients with mental disorders combined with severe pneumonia in the intensive care unit (ICU) of a psychiatric hospital from May 2020 to February 2023, and divided them into two groups according to whether they died or not, and analyzed their basic characteristics, laboratory results and treatments, etc. We analyzed the risk factors of patients' deaths using logistics regression, established a prediction model, and drew a dynamic nomogram based on the results of the regression analysis. Based on the results of regression analysis, a prediction model was established and a dynamic nomogram was drawn.ResultsThe non-survivor group and the survivor group of patients with mental disorders combined with severe pneumonia were statistically different in terms of age, type of primary mental illness, whether or not they were intubated, whether or not they had been bedridden for a long period in the past, and the Montreal Cognitive Assessment (MoCA) scale, procalcitonin (PCT), albumin (ALB), hemoglobin (Hb), etc. Logistics regression analysis revealed the following: MoCA scale (OR = 0.932, 95% CI:0.872–0.997), age (OR = 1.077, 95%CI:1.029–1.128), PCT (OR = 1.078, 95% CI:10.006–10.155), ALB (OR = 0.971, 95%CI:0.893–1.056), Hb (OR = 0.971, 95% CI: 0.942–0.986) were statistically significant. The ROC curve showed that the model predicted patient death with an area under the curve (AUC) of 0.827 with a sensitivity of 73.4% and a specificity of 80.4%.ConclusionLow MoCA score, age, PCT, and low Hb are independent risk factors for death in patients with mental disorders with severe pneumonia, and the prediction model constructed using these factors showed good predictive efficacy.

The omega-3 fatty acid desaturase enzyme gene FAD3 is responsible for converting linoleic acid to linolenic acid in plant fatty acid synthesis. Despite limited knowledge of its role in cotton growth, our study focused on GhFAD3-4, a gene within the FAD3 family, which was found to promote fiber elongation and cell wall thickness in cotton. GhFAD3-4 was predominantly expressed in elongating fibers, and its suppression led to shorter fibers with reduced cell wall thickness and phosphoinositide (PI) and inositol triphosphate (IP3) levels. Transcriptome analysis of GhFAD3-4 knock-out mutants revealed significant impacts on genes involved in the phosphoinositol signaling pathway. Experimental evidence demonstrated that GhFAD3-4 positively regulated the expression of the GhBoGH3B and GhPIS genes, influencing cotton fiber development through the inositol signaling pathway. The application of PI and IP6 externally increased fiber length in GhFAD3-4 knock-out plants, while inhibiting PI led to a reduced fiber length in GhFAD3-4 overexpressing plants. These findings suggest that GhFAD3-4 plays a crucial role in enhancing fiber development by promoting PI and IP3 biosynthesis, offering the potential for breeding cotton varieties with superior fiber quality.

The classification of land cover types is an important task for monitoring land use. Moreover, with the continuous application of high resolution remote sensing images, the time and space span is becoming larger, which greatly increases the difficulty of classification of target types. And there are few results that can effectively deal with deep land category information. Furthermore, the extraction and fusion of deep features still need to be improved. In this article, a multiangle attention fusion network is proposed for the classification of land cover types. The network uses a 50-layer residual network as a feature extraction network, and an adaptive special-shaped window attention module is added to the deep layer of the network to extract deep semantic information, building the connection between global information. In addition, the multiangle interactive attention fusion module is used to fuse feature maps at different levels, and an interactive attention mechanism is established at different angles. Finally, a new decoder module is proposed for the decoder to adjust the fused feature map again. Through experiments on three datasets, the results show that the method proposed in this article is more accurate than the previous network for the segmentation results of different categories. It can realize the accurate division of land types in remote sensing images, and has good generalization ability.

A large number of bone stick cultural relics have been unearthed in Weiyang Palace of Han Period Chang’an City, Xi’an City, Shaanxi Province, China. Utilizing deep learning-based image classification methods can improve the efficiency of categorizing bone stick fracture locations and colors. However, due to factors such as variations in surface texture features and different degrees of wear on the bone sticks, the classification accuracy of the model is low. To address this issue, this paper proposes a bone stick image classification method using the YOLOv5s-ViT cascade model. The method incorporates the C3CA attention module to enhance the model’s recognition of fracture areas, reduce interference from the image background, and improve the effectiveness of the Vision Transformer self-attention mechanism. Furthermore, Increase the learning rate by comparing the training data of the test to improve the training efficiency of the model. Lastly, the Batch Normalization layer is introduced to normalize the output of the encoder, suppress model training divergence, and enhance generalization ability. The experimental results show that the average recognition accuracy of the bone stick fracture region features of this paper reaches 97.6%, the average recall rate reaches 93.3%, which is 2.1% and 6.0% higher than the YOLOv5s model, respectively, and the average classification accuracy reaches 88.7%, which is 7.9% higher than the Vision Transformer model, and can effectively improve the classification accuracy of bone stick images.

A large number of bone stick fragments were unearthed at the Weiyang Palace, and the manual stitching method is inefficient and time-consuming, therefore Image Stitching Method of Bone Stick Fragment Based on Similarity Freeman code Matching is proposed by this paper to improve bone stick stitching efficiency. The Freeman code is used to represent the contour of the true color RGB image of bone stick fragments, and the direction change dense feature of the bone stick fragment fracture is fused with the Freeman code difference to represent the change direction feature to locate the fracture boundary. At the same time, the integer basic operation is used to replace the complex calculus calculation to improve the efficiency of the algorithm; The longest common subsequence algorithm is used to perform local similarity rough matching on Freeman code of the contour at the fragment fracture, and then the angle and distance error threshold is set according to the prior knowledge of manual stitching to reduce the matching error; Finally, according to the matching results, the complete bone stick contour binary image is drawn. Compared with other algorithms, the contour Cosine similarity accuracy of the bone stick image stitched by this algorithm is improved by 21.68%, which can be accurate to 97.80%; the Editing distance similarity accuracy is improved by 14.29%, which can be accurate to 91.87%;the Peak signal-to-noise ratio is improved by 83%, which can be accurate to 31.13%;the Structural Similarity is improved by 29%, which can be accurate to 0.87; the Figure of merit is improved by 39%, which can be accurate to 0.85. The experiment results show that the algorithm proposed in this paper can effectively assist the stitching work of bone stick cultural relics.

Abstract Purpose This study aims to analyze the clinical application value of shear wave elastography (SWE) technique for early diagnosis of diabetic peripheral neuropathy (DPN). Methods Diabetic patients hospitalized in the Department of Endocrinology of the First Affiliated Hospital of Anhui Medical University from August 2021 to February 2022 were enrolled as DPN group (n=38) and non-DPN group (n=35) based on the neurophysiological examination results. 30 healthy subjects were recruited as the control group during the same period. Ultrasound examination of the tibial nerve and related laboratory tests were examined and collected for the total 103 study subjects. Statistical analysis of the collected data, and the receiver operating characteristic(ROC) curve for determination of the optimal cut-off values of mean stiffness of tibial nerve to detect DPN, with determination of area under curve (AUC), specificity, sensitivity, and Youden index.P value 0.05). The difference of serological indicators between DPN and non-DPN groups was also not found (P>0.05), whereas longer duration of diabetes was observed in DPN group as compared to non-DPN group. As to the ultra-sound relevant parameters, the cross-sectional area and elastic modulus of the tibial nerve in both lower extremities among these three groups were not significantly different (Oneway ANOVA analysis) although the differences were indeed observed if we compared DPN group exclusively with non-DPN group, or compared non-DPN group with healthy group, or compared DPN group with healthy group (t test). Additionally, the mean elasticity (Emean) cut-off value for the diagnosis of DPN was preferably taken as 67.55 kPa. Conclusion SWE has unique advantages in early detection and diagnosis of DPN, which deserve further research.

Abstract Background To investigate the association between low-carbohydrate-diet (LCD) score and cognitive performance based on a nationally representative sample aged ≥ 60 years from National Health and Nutrition Examination Survey (NHANES) database. Methods This cross-sectional study included 2,537 eligible older adults from the NHANES database 2011–2014. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) word learning subtest, Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST) were used to assess the cognitive performance. All participants were categorized into the low and normal cognitive performance groups. The univariate and multivariate logistic regression analyses were utilized to evaluate the association of LCD score with cognitive performance. Stratified analyses based on age, body mass index (BMI), gender, marital status, education level was conducted. Results After adjusting age, education level, marital status, household income, history of diabetes, history of hypertension, history of congestive heart failure, history of coronary heart disease, history of heart disease, history of stroke, magnesium and the using of psychotropic medication, LCD score was correlated with the CERAD word learning subtest. The associations between LCD score and AFT, DSST were not statistically significant. Moreover, LCD score was also related to cognitive performance among individuals who were aged

Abstract Background Heat stress is a major abiotic stress affecting the growth and development of plants, including crop species. Plants have evolved various adaptive strategies to help them survive heat stress, including maintaining membrane stability, encoding heat shock proteins (HSPs) and ROS-scavenging enzymes, and inducing molecular chaperone signaling. Brassinosteroids (BRs) are phytohormones that regulate various aspects of plant development, which have been implicated also in plant responses to heat stress, and resistance to heat in Arabidopsis thaliana is enhanced by adding exogenous BR. Brassinazole resistant 1 (BZR1), a transcription factor and positive regulator of BR signal, controls plant growth and development by directly regulating downstream target genes. However, the molecular mechanism at the basis of BR-mediated heat stress response is poorly understood. Here, we report the identification of a new factor critical for BR-regulated heat stress tolerance. Results We identified ERF49 in a genetic screen for proteins required for BR-regulated gene expression. We found that ERF49 is the direct target gene of BZR1 and that overexpressing ERF49 enhanced sensitivity of transgenic plants to heat stress. The transcription levels of heat shock factor HSFA2, heat stress-inducible gene DREB2A, and three heat shock protein (HSP) were significantly reduced under heat stress in ERF49-overexpressed transgenic plants. Transcriptional activity analysis in protoplast revealed that BZR1 inhibits ERF49 expression by binding to the promoter of ERF49. Our genetic analysis showed that dominant gain-of-function brassinazole resistant 1-1D mutant (bzr1-1D) exhibited lower sensitivity to heat stress compared with wild-type. Expressing ERF49-SRDX (a dominant repressor reporter of ERF49) in bzr1-1D significantly decreased the sensitivity of ERF49-SRDX/bzr1-1D transgenic plants to heat stress compared to bzr1-1D. Conclusions Our data provide clear evidence that BR increases thermotolerance of plants by repressing the expression of ERF49 through BZR1, and this process is dependent on the expression of downstream heat stress-inducible genes. Taken together, our work reveals a novel molecular mechanism mediating plant response to high temperature stress.

The rejoining of bone sticks holds significant importance in studying the historical and cultural aspects of the Han Dynasty. Currently, the rejoining work of bone inscriptions heavily relies on manual efforts by experts, demanding a considerable amount of time and energy. This paper introduces a multi-scale feature fusion Siamese network guided by edge contour (MFS-GC) model. Constructing a Siamese network framework, it first uses a residual network to extract features of bone sticks, which is followed by computing the L2 distance for similarity measurement. During the extraction of feature vectors using the residual network, the BN layer tends to lose contour detail information, resulting in less conspicuous feature extraction, especially along fractured edges. To address this issue, the Spatially Adaptive DEnormalization (SPADE) model is employed to guide the normalization of contour images of bone sticks. This ensures that the network can learn multi-scale boundary contour features at each layer. Finally, the extracted multi-scale fused features undergo similarity measurement for local matching of bone stick fragment images. Additionally, a Conjugable Bone Stick Dataset (CBSD) is constructed. In the experimental validation phase, the MFS-GC algorithm is compared with classical similarity calculation methods in terms of precision, recall, and miss detection rate. The experiments demonstrate that the MFS-GC algorithm achieves an average accuracy of 95.5% in the Top-15 on the CBSD. The findings of this research can contribute to solving the rejoining issues of bone sticks.

Depression is a major neuropsychiatric disease that considerably impacts individuals’ psychosocial function and life quality. Neurotrophic factors are now connected to the pathogenesis of depression, while the definitive neurotrophic basis remains elusive. Besides, phytotherapy is alternative to conventional antidepressants that may minimize undesirable adverse reactions. Thus, further research into the interaction between neurotrophic factors and depression and phytochemicals that repair neurotrophic factors deficit is highly required. This review highlighted the implication of neurotrophic factors in depression, with a focus on the brain-derived neurotrophic factor (BDNF), glial cell line-derived neurotrophic factor (GDNF), vascular endothelial growth factor (VEGF), and nerve growth factor (NGF), and detailed the antidepressant activities of various phytochemicals targeting neurotrophic factors. Additionally, we presented future opportunities for novel diagnostic and therapeutic strategies for depression and provided solutions to challenges in this area to accelerate the clinical translation of neurotrophic factors for the treatment of depression.

Abstract How to maintain the physicochemical stability of oil emulsion has been one of the major challenges in food industry. Previously we reported the demulsification effects of catalase in the fish oil emulsion. In comparison, the influences of other two metal ion-containing oxidoreductases, horseradish peroxidase (HRP) and copper/zinc superoxide dismutase (SOD), on the emulsion’s stability were investigated. Submicron fish oil-in-water emulsion stabilized by polysorbate 80 was prepared by high-speed homogenization. Its physical stability was evaluated by visual and microscopic observation, turbidity and light scattering measurements, while chemical stability by the hydroperoxide content and lipid peroxidation. HRP demulsified the emulsion in a concentration-responsive manner after 3–7 days’ incubation, resulting in a decreased turbidity and significant delamination. The enlargement of oil-polysorbate droplets and protein precipitates were confirmed by size distribution and TEM observation. HRP initially elevated the emulsion’s hydroperoxide then decreased it while raising TBARS levels during 7-Day incubation. In contrary, SOD stabilized the emulsion physically and chemically. The demulsification was correspondingly attributed to the oxidation catalyzing activity of the peroxidase and the electrostatic and hydrophobic interaction between lipids and proteins. This study adds new insight to the influences of the two oxidoreductases on the stability, lipids and peroxides of food emulsions, proposes an exciting subject of elucidating the underlying mechanism.

In view of the high computational complexity in spatial pulse position modulation systems when using maximum likelihood detection algorithm, a step-by-step classification detection algorithm based on K-means clustering was proposed according to the characteristics of signal matrix with spatial pulse position modulation.The signal vector detection algorithm was utilized to detect the index of light source in the training samples.The on K-means clustering algorithm was utilized to acquire the mapping rule between centroid of samples and modulated symbol by offline training.Subsequently, online detection of modulated symbols was achieved based on the mapping rule, and then the index of light sources was detected by exhaustive search.In addition, Monte Carlo method was used to investigate the effects of key parameters such as the number of clusters and initialization times on the system bit error rate (BER) performance.Simulation results demonstrate that the proposed algorithm can achieve an approximate BER performance as the maximum likelihood algorithm on the basis of greatly reducing the computational complexity.Compared with the linear decoding algorithms, the proposed algorithm is also applicable to scenarios where the number of detectors is less than the number of light sources.

Objectives We investigated the effect and mechanism of miR-21-3p on the biological behavior of keratinocyte HaCaT cells. Methods HaCaT cells were transfected with miR-21-3p mimics and miR-21-3p inhibitor, respectively. Cell proliferation was detected by CCK-8, and apoptosis and cell cycle were analyzed by flow cytometry. The expression changes of Bax and Bcl-2 were measured with immunohistochemistry. The mRNA expressions of IL-17A and STAT3 were detected by real-time fluorescence quantitative PCR. Cytokeratin 17 protein was detected by Western blot. The relationship between miR-21-3p and STAT3 was verified by dual luciferase reporter gene assay. Results The miR-21-3p mimics significantly promoted the proliferation and cell cycle progression of HaCaT cells. However, miR-21-3p mimics significantly inhibited cell apoptosis, decreased Bax expression and increased Bcl-2 expression. Additionally, miR-21-3p mimics significantly increased the expressions of Cytokeratin 17 protein, IL-17A mRNA and STAT3 mRNA. Of note, the miR-21-3p inhibitor exhibited contrary effects to miR-21-3p mimics. Furthermore, STAT3 was a direct target of miR-21-3p . Conclusion miR-21-3p may promote the abnormal proliferation and inhibit apoptosis of HaCaT cells, possibly through regulating JAK/STAT pathway and the expression of Cytokeratin 17.

The ergodic channel capacity of wireless optical multiple-input multiple-output (MIMO) system with pulse position modulation (PPM) is investigated. The combined effects of atmospheric turbulence, atmospheric attenuation, pointing error and channel spatial correlation are taken into consideration. The expression of ergodic channel capacity is derived, and is further performed by Wilkinson approximation method for simplicity. The simulation results indicated that the strong spatial correlation has the greatest influence on the ergodic channel capacity, followed by pointing errors and atmospheric turbulence. Moreover, the ergodic channel capacity growth brought by space diversity only performs well under independent and weakly correlated channels. Properly increasing the size and spacing of the receiving apertures is an effective means of effectively increasing the ergodic channel capacity.

Mucormycosis is a conditionally pathogenic fungal disease with high morbidity that mainly affects patients with decreased immunity. Diagnosis relies on the histopathological examination of microorganisms with the typical structure of mucormycetes in tissues and subsequent confirmation via culture. Early detection of causative microorganisms is critical to rapidly administer appropriately targeted antibiotics. Metagenomic next-generation sequencing (mNGS) is an innovative and sensitive technique used to identify pathogenic strains. Here we used mNGS to timely diagnose an infection with Lichtheimia ramosa and Mucor irregularis in two patients with hematologic malignancies; the infections manifested as nasal and cutaneous infections and developed after chemotherapy and small molecule targeted therapy. Following treatment with amphotericin B cholesteryl sulfate complex, the symptoms were reduced significantly, and both patients obtained successful outcomes. Additionally, we searched and summarized the current medical literature on the successful diagnosis of mucormycosis using mNGS. These cases indicated that mNGS, a novel culture-independent method, is capable of rapid, sensitive, and accurate identification of pathogens. mNGS may be a complementary method for the early identification of mucormycosis, allowing for appropriate and timely antibiotic administration and thus improving patient outcomes.

Hexokinase (HXK) is involved in hexose phosphorylation, sugar sensing, and signal transduction, all of which regulate plant growth and adaptation to stresses. Gossypium hirsutum L. is one of the most important fiber crops in the world, however, little is known about the HXKs gene family in G. hirsutum L. We identified 17 GhHXKs from the allotetraploid G. hirsutum L. genome (AADD). G. raimondii (DD) and G. arboreum (AA) are the diploid progenitors of G. hirsutum L. and contributed equally to the At_genome and Dt_genome GhHXKs genes. The chromosomal locations and exon-intron structures of GhHXK genes among cotton species are conservative. Phylogenetic analysis grouped the HXK proteins into four and three groups based on whether they were monocotyledons and dicotyledons, respectively. Duplication event analysis demonstrated that HXKs in G. hirsutum L. primarily originated from segmental duplication, which prior to diploid hybridization. Experiments of qRT-PCR, transcriptome and promoter cis-elements demonstrated that GhHXKs’ promoters have auxin and GA responsive elements that are highly expressed in the fiber initiation and elongation stages, while the promoters contain ABA-, MeJA-, and SA-responsive elements that are highly expressed during the synthesis of the secondary cell wall. We performed a comprehensive analysis of the GhHXK gene family is a vital fiber crop, which lays the foundation for future studies assessing its role in fiber development.

Daily foods contain a great number of self-assembled nanoparticles (NPs) which were incidentally produced during food processing. These food incidental NPs can directly access the human gastrointestinal tract in high frequency and large quantities. Limited reports were focused on whether and how these food incidental NPs affected the gastrointestinal tissues and gut microbiota. In the present study, bone soup and its NPs both significantly ameliorated colitis symptoms in dextran sulfate sodium (DSS)-induced mice and inhibited the release of pro-inflammatory cytokines. They also restored intestinal microbiota dysbiosis by improving the diversity and richness of intestinal microbiota and regulating community composition, such as a remarkable increase in Muribaculaceae, Alistipes, and Alloprevotella, and a decrease in Helicobacter. Moreover, the correlation analysis showed that pro-inflammatory cytokines were negatively correlated with Muribaculaceae, Alloprevotella, and Alistipes, but positively correlated with Helicobacter. These findings suggest that the food incidental NPs can influence human health through regulating the inflammation of the gastrointestinal tissues and the gut microbiota.

Damaged edges of bone tag images contain external factors such as impurities and damage, which affect the stitching process and lead to repair errors. Therefore, this paper proposes a stitching method based on image edge position feature matching. The objective is to improve the accuracy of image stitching by matching feature points based on the position of the image edge pixel so as to solve the accurate stitching of broken edge contour. In the first step of this method, the image containing the broken edge is preprocessed by edge detection, and the location of the broken edge pixel is proposed. Secondly, the feature descriptors were calculated to extract the shape and texture information of the feature points on the fracture edge. Finally, the feature points are optimized by minimum correction and image mosaic is carried out. In terms of image stitching, pre-registration is performed by finding the feature descriptors that are most similar to the edge of the optimum fracture surface profile. The matching operator is added to the overlapping region to obtain the corrected image, and the panoramic image mosaic of the image fracture surface is performed. The experimental results show that feature descriptor matching can ensure the integrity of the fracture, improve the matching accuracy, optimize the uneven deformation of the fracture, ensure the quality of image stitching, and reduce the degree of image distortion.

Objective: To investigate the immunological mechanism of bone marrow–derived mesenchymal stem cells (BM-MSCs) in inflammatory bowel disease (IBD).Methods: Mice with 2,4,6-trinitrobenzene sulfonic acid (TNBS)–induced colitis were intraperitoneally injected with phosphate-buffered saline, BM-MSCs, BM-MSCs with tumor necrosis factor–induced protein 6 (Tnfaip6) knockdown mediated by RNA interference recombinant adenovirus, and BM-MSCs–infected with control adenovirus or recombinant mouse Tnfaip6. The disease activity index, weight loss, and histological scores were recorded. Serum levels of Tnfaip6 and pro- and anti-inflammatory cytokines, including interleukin (IL)-21, tumor necrosis factor-alpha (TNF-α), IL-10 were measured by enzyme-linked immunosorbent assay. The relative expression levels of these cytokines, B-cell lymphoma 6 (BCL-6) and fork-like transcription factor p3 (Foxp3) in the colon were determined by real-time quantitative PCR (RT-qPCR). BCL-6 and Foxp3 are the master regulators of follicular helper T cells (Tfh) and follicular regulatory T cells (Tfr), respectively. The infiltration of Tfh and Tfr in mesenteric lymph nodes (MLNs) and spleens was analyzed by flow cytometry.Results: Compared to the normal control group, the expression levels of BCL-6 and IL-21 in the colon, Tfh infiltration, and ratios of Tfh/Tfr in the MLNs and spleen, and the serum concentrations of IL-21 and TNF-α increased significantly in the colitis model group (p < 0.05). Intraperitoneal injection of BM-MSCs or Tnfaip6 ameliorated weight loss and clinical and histological severity of colitis, downregulated the expression of BCL-6, IL-21, and TNF-α, upregulated the expression of Foxp3, IL-10, and Tnfaip6 (p < 0.05), increased Tfr and reduced the infiltration of Tfh in the MLNs and spleen, and downregulated the Tfh/Tfr ratio (p < 0.05). On the other hand, BM-MSCs lost the therapeutic effect and immune regulatory functions on Tfh and Tfr after Tnfaip6 knockdown.Conclusion: Tfh increase in the inflamed colon, Tfh decrease and Tfr increase during the colitis remission phase, and the imbalance of the Tfh/Tfr ratio is closely related to the progression of IBD. Tnfaip6 secreted by BM-MSCs alleviates IBD by inhibiting Tfh differentiation, promoting Tfr differentiation, and improving the imbalance of Tfh/Tfr in mice.

Bone sticks are composed of thin slices of animal bones created by ancient people, which mainly served the functions of fixing books, writing scripts, and divination. The bone stick script is an essential material for studying the history of Chinese Western Han script. Using a neural network for text recognition can quickly interpret ancient text, while extracting deeper semantic information, neural networks will also lose superficial image details. After multi-layer convolution and pooling of bone sticks, the continuous loss of superficial details affects classification accuracy. At the same time, the unbalanced distribution of bone stick quantity leads to a low recognition rate with small samples of bone sticks. Aiming to solve the above problems, a bone stick recognition method based on multi-scale features and focal loss function is proposed. Firstly, based on the residual network ResNet, the output features of the first layer and four Conv_x layers are pooled globally to reduce the feature dimension of each channel, and the channel splicing method is used to add different depths of base information to the original high-level features, which improves the detail feature extraction ability of the model. Secondly, in view of the unbalanced distribution of the bone stick data, the original cross-entropy loss function is replaced by the focus loss function, which increases the penalty for classification errors and improves the recognition rate of classes with few training samples. Experimental results show that the recognition accuracy of the proposed method on the bone stick data set is up to 90.5%.

In order to improve the accuracy of signal recovery after transmitting over atmospheric turbulence channel, a deep-learning-based signal detection method is proposed for a faster-than-Nyquist (FTN) hybrid modulated optical wireless communication (OWC) system. It takes advantage of the long short-term memory (LSTM) network in the recurrent neural network (RNN) to alleviate the interdependence problem of adjacent symbols. Moreover, an LSTM attention decoder is constructed by employing the attention mechanism, which can alleviate the shortcomings in conventional LSTM. The simulation results show that the bit error rate (BER) performance of the proposed LSTM attention neural network is 1 dB better than that of the back propagation (BP) neural network and outperforms by 2.5 dB when compared with the maximum likelihood sequence estimation (MLSE) detection method.

Safety concerns arose on the interaction between nanoparticles in food and intestinal tract. Food components could spontaneously assemble into a large number of nanoparticles during food processing. These nanoparticles may possess physiological effects differed from those of constituent components, are worth paying attention to, but are barely investigated yet, especially on their interaction with intestinal tract. Porcine bone soup is rich in nanoparticles, which can directly interact with oral macrophages disclosed by our previous study. In this study, the effects of bone soup nanoparticles on intestinal barrier function were subsequently evaluated on Caco-2 cell monolayers. The results revealed the nanoparticles did not develop but restore intestinal barrier dysfunction compared with engineered nanoparticles, indicated by barrier integrity, sodium fluorescein permeability, tight junctions and adherent junctions related proteins. These results showed the potential of bone soup nanoparticles on improving intestinal disorders, which resonated with traditional knowledge on the efficacies of bone soup.

Depression is an inflammation-associated disease that results in major depression as inflammation increases and progresses. Ginsenoside Rg1 (Rg1), the major bioactive ingredient derived from ginseng, possesses remarkable anti-depressant and anti-inflammatory effects. Our previous studies showed that the pathogenesis of depression was concomitant with the acceleration of connexin43 (Cx43) ubiquitin degradation, while Rg1 could upregulate Cx43 expression to attenuate depression. However, whether the ubiquitination of Cx43 is the specific correlation between depression and inflammation, and how Rg1 ameliorates neuroinflammation to attenuate depression, are still under investigation. In in vivo experiments, Rg1 treatment significantly ameliorated depression-like behaviors in rats subjected to chronic unpredictable stress (CUS). Moreover, these CUS rats treated with Rg1 exhibited attenuated neuroinflammation, together with the suppression of Cx43 ubiquitination. In in vitro experiments, Rg1 reduced the secretion of inflammatory cytokines and the ubiquitination of Cx43 in lipopolysaccharide-induced glial cells. Furthermore, treatment with ubiquitin-proteasome inhibitor MG132 suppressing the ubiquitination of Cx43 ameliorated lipopolysaccharide-induced neuroinflammation. The results suggest that Rg1 attenuates depression-like behavioral performances in CUS-exposed rats; and the main mechanism of the antidepressant-like effects of Rg1 appears to involve protection against neuroinflammation via suppression of Cx43 ubiquitination. In conclusion, Rg1 could ameliorate neuroinflammation via suppression of Cx43 ubiquitination to attenuate depression, which represents the perspective of an innovative therapy of Rg1 in the treatment of inflammation-associated depression.

Food nanoparticles have recently been identified to be engulfed by oral macrophages conducting antioxidant effects. It suggests an important but long overlooked food-body interaction and prompts the importance of the correlated methodology development. As oral macrophages are restricted in numbers, peritoneal macrophages can provide an alternative for its easy availability and its role in the gastrointestinal entry of food particles. To test the feasibility, the interaction between murine peritoneal macrophages and colloidal particles from porcine bone soup was investigated. The particles were isolated with size-exclusive chromatography and could be internalized by peritoneal macrophages. Similar to oral macrophages, the engulfment did not influence the normal cells, but prevented them from peroxyl radical induced membrane hyperpolarization, mitochondria malfunction and phagocytosis suppression. These results elucidate that food colloidal particles can directly interact with peritoneal macrophages, and that peritoneal macrophages can be a substitute to oral macrophages in studying food nanoparticle-macrophage interaction.

Aspergillus flavus and Aflatoxins in grain crops give rise to a serious threat to food security and cause huge economic losses. In particular, aflatoxin B1 has been identified as a Class I carcinogen to humans by the International Agency for Research on Cancer (IARC). Compared with conventional methods, Surface-Enhanced Raman Scattering (SERS) has paved the way for the detection of Aspergillus flavus and Aflatoxins in grain crops as it is a rapid, nondestructive, and sensitive analytical method. In this work, the rapid detection of Aspergillus flavus and quantification of Aflatoxin B1 in grain crops were performed by using a portable Raman spectrometer combined with colloidal Au nanoparticles (AuNPs). With the increase of the concentration of Aspergillus flavus spore suspension in the range of 102–108 CFU/mL, the better the combination of Aspergillus flavus spores and AuNPs, the better the enhancement effect of AuNPs solution on the Aspergillus flavus. A series of different concentrations of aflatoxin B1 methanol solution combined with AuNPs were determined based on SERS and their spectra were similar to that of solid powder. Moreover, the characteristic peak increased gradually with the increase of concentration in the range of 0.0005–0.01 mg/L and the determination limit was 0.0005 mg/L, which was verified by HPLC in ppM concentration. This rapid detection method can greatly shorten the detection time from several hours or even tens of hours to a few minutes, which can help to take effective measures to avoid causing large economic losses.

Chronic stress is an essential factor leading to depression. However, there exist individual differences in people exposed to the same stressful stimuli. Some people display negative psychology and behavior, while others are normal. Given the importance of individual difference, finding differentially expressed proteins in stress-resistant and stress-susceptible groups has great significance for the study of pathogenesis and treatment of depression. In this study, stress-susceptible rats and stress-resilient rats were first distinguished by sucrose preference test. These stress-susceptible rats also displayed depression-like behaviors in forced swimming test and open field test. Then, we employed label-free quantitative proteomics to analyze proteins in the ventral hippocampus. There were 4,848 proteins totally identified. Based on statistical analysis, we found 276 differentially expressed proteins. Bioinformatics analysis revealed that the biological processes of these differential proteins were related to mitochondrion organization, protein localization, coenzyme metabolic process, cerebral cortex tangential migration, vesicle-mediated transport, and so on. The KEGG pathways were mainly involved in metabolic pathways, axon guidance, autophagy, and tight junction. Furthermore, we ultimately found 20 stress-susceptible proteins and two stress-resilient proteins. These stress-related proteins could not only be potential biomarkers for depression diagnosis but also contribute to finding new therapeutic targets and providing personalized medicine.

The Chinese herb couple Fuzi and Ganjiang (FG) has been a classic combination of traditional Chinese medicine that is commonly used clinically in China for nearly 2000 years. Traditional Chinese medicine suggests that FG can treat various ailments, including heart failure, fatigue, gastrointestinal upset, and depression. Neuroinflammation is one of the main pathogenesis of many neurodegenerative diseases in which microglia cells play a critical role in the occurrence and development of neuroinflammation. FG has been clinically proven to have an efficient therapeutic effect on depression and other neurological disorders, but its mechanism remains unknown. Cancer-related fatigue (CRF) is a serious threat to the quality of life of cancer patients and is characterized by both physical and psychological fatigue. Recent studies have found that neuroinflammation is a key inducement leading to the occurrence and development of CRF. Traditional Chinese medicine theory believes that extreme fatigue and depressive symptoms of CRF are related to Yang deficiency, and the application of Yang tonic drugs such as Fuzi and Ganjiang can relieve CRF symptoms, but the underlying mechanisms remain unknown. In order to define whether FG can inhibit CRF depression-like behavior by suppressing neuroinflammation, we conducted a series of experimental studies in vitro and in vivo. According to the UPLC-Q-TOF/MSE results, we speculated that there were 49 compounds in the FG extraction, among which 30 compounds were derived from Fuzi and 19 compounds were derived from Ganjiang. Our research data showed that FG can effectively reduce the production of pro-inflammatory mediators IL-6, TNF-α, ROS, NO, and PGE2 and suppress the expression of iNOS and COX2, which were related to the inhibition of NF-κB/activation of Nrf2/HO-1 signaling pathways. In addition, our research results revealed that FG can improve the depression-like behavior performance of CRF model mice in the tail suspension test, open field test, elevated plus maze test, and forced swimming test, which were associated with the inhibition of the expression of inflammatory mediators iNOS and COX2 in the prefrontal cortex and hippocampus of CRF model mice. Those research results suggested that FG has a satisfactory effect on depression-like behavior of CRF, which was related to the inhibition of neuroinflammation.

Delayed fluorescence (DF) materials have shown great potential in time‐resolved luminescence imaging (TRLI), due to the relatively elongated emission lifetimes. However, the sensitivity of DF to environmental quenching leads to a challenge to realize TRLI directly using pure thermally‐activated DF (TADF) molecules. Herein, two TADF molecules, namely CzPOTCF and tBCzPOTCF, are designed and synthesized, featuring a diphenylphosphine oxide (DPPO) group substituted at the ortho‐position of the carbazole group. Compared with DPPO‐free CzTCF, the steric hindrance of DPPO groups enlarges dihedral angles between TCF and the carbazole groups in CzPOTCF and tBCzPOTCF; meanwhile, PO provides other channels for forming intermolecular hydrogen bonds. The optimized intermolecular interactions facilitate the dimer formation of CzPOTCF and tBCzPOTCF, which simultaneously enhance aggregation‐induced DF and mitigate disordered packing‐induced quenching. As a consequence, CzPOTCF and tBCzPOTCF show the enhanced aggregation‐induced DF with largely increased lifetimes. Without any additional assistance, the long‐lived fluorescence of CzPOTCF and tBCzPOTCF is successfully observed for cell TRLI, with 1–1.7 μs elongated average lifetimes of 6.69 and 7.41 μs, respectively.

Accurate regulation of cell cycle is important for normal tissue development and homeostasis. RCC2 (Regulator of Chromosome Condensation 2) play a role as chromosomal passenger complex (CPC) implicated in all cell cycle phases. RCC2 was initially identified as Ran guanine exchange factor (GEF) for small G proteins. Therefore, RCC2 plays a key role in oncogenesis of most cancers. RCC2 is implicated in Colorectal Cancer (CRC), Lung Adenocarcinoma (LUAD), breast cancer, and ovarian cancer. Expression level of RCC2 protein determines regulation of tumor cell proliferation, invasion, metastasis, and radio-chemotherapeutic resistance. In this review, we explored proteins that interact with RCC2 to modulate tumor development and cancer therapeutic resistance by regulation of cell cycle process through various signaling pathways.

In recent years, rapid urbanization in China has led to land transformation and unequal social and economic development among rural collective land in different regions. Although there has been considerable research on land development in China, there is a lack of studies on the socioeconomic impacts of unequal collective land development on rural elders. This research investigates collective land support, family support, and social support among the elderly in three types of villages—urban, suburban, and remote—in China’s Pearl River Delta. The findings show that land support retains an important factor for supporting the rural elderly, while family support is in steep decline, and social elderly support offers low coverage. However, land support differs greatly with location, and only urban villages in central locations with high land values are found to provide adequate land support for the rural elderly. The key influential factor of land income has shifted from land quantity to land location, and there now appears to be a need to adjust relevant land, fiscal, and taxation policies for collective land in different locations.

The performance of wireless optical MIMO system with multiple pulse position modulation (MPPM) over correlated fading channel is investigated. The combined effects of atmospheric attenuation, atmospheric turbulence, and pointing error are taken into consideration. The bit error rate (BER) and the ergodic channel capacity are analyzed by utilizing the Poisson counting model and the exponential correlation model. Moreover, their approximate expressions are derived. The simulation results demonstrate that the pointing error is the most prominent influence factor over weak correlated channel. The performance degradation caused by a high channel correlation coefficient is more than that of pointing error in strong correlated channel. Therefore, the use of pointing, acquisition, and tracking (PAT) system and reasonable arrangement of the number and spacing of antennas at the transceiver are the keys to improve system performance.

Abstract In order to solve the geometric offset caused by replacing the filter during imaging of multichannel spectral image data, a multichannel spectral image registration method based on SURF feature merged with maximum submatrix is proposed. Firstly, the feature of multichannel spectral image is extracted by SURF. Then, a perspective transformation is performed to obtain a preliminary registration image. For the problem of invalid areas with zero pixel values appearing at the boundary of the image after registration, the largest submatrix is used to detect the maximum inscribed rectangle of the image to remove the invalid boundary region, and maximize the reserved effective region information. Experimented was processed with multichannel imaging data of murals. Experimental results agree with the theoretic analysis and verified that the proposed registration method is better adapted to image scale and brightness changing. At the same time, it can avoid the influence of invalid regions generated by other registration methods on subsequent spectral reconstruction and color restoration which has better performance.

It has been revealed that numerous nanoparticles are formed during the boiling preparation of traditional Chinese medical decoctions and culinary soups. They may possess physiological effects different from those of constituent components and are worth paying attention to but are barely noticed and investigated as of yet. In this study, six groups of nanoparticles, whose size ranged from 57 to 300 nm, were successfully isolated from the decoction of Isatis indigotica Fort. root, according to their particle size by the means of size-exclusive chromatography. All of the obtained nanoparticles have a high content of polysaccharides, which distinguishes them from the disclosed BLG protein nanoparticles. They also have high similarities in other compositions, surface charge, and stimuli responses. However, four out of these six nanoparticles (F2, F3, F4, and F5) exhibited significant antiviral activity against influenza virus H1N1, and their antiviral activities and cytotoxicity towards MDCK cells varied with their sizes. It suggested that the antiviral efficacy of BLG decoction could also be from its nanoparticles besides its well-known antiviral phytochemicals. It also implied that the biological effects of these polysaccharide nanoparticles, including cytotoxicity and antiviral activity, may be correlative with the physicochemical properties, especially the particle size.

Transcranial ultrasound stimulation (TUS; f < 1 MHz) is a promising approach to non-invasive brain stimulation. Transcranial magneto-acoustic stimulation (TMAS) is a technique of neuromodulation for regulating neuroelectric-activity utilizing a magnetic–acoustic coupling electric field generated by low-intensity ultrasound and magnetic fields. However, both techniques use the physical means of low-intensity ultrasound and can induce the response of the motor cortex. Therefore, it is necessary to distinguish the difference between the two techniques in the regulation of neural activity. This study is the first to quantify the amplitude and response latency of motor cortical electromyography (EMG) in mice induced by TMAS and TUS. The amplitude of EMG (2.73 ± 0.32 mV) induced by TMAS was significantly greater than that induced by TUS (2.22 ± 0.33 mV), and the EMG response latency induced by TMAS (101.25 ± 88.4 ms) was significantly lower than that induced by TUS (181.25 ± 158.4 ms). This shows that TMAS can shorten the response time of nerve activity and enhance the neuromodulation effect of TUS on the motor cortex. This provides a theoretical basis for revealing the physiological mechanisms of TMAS and the treatment of neuropsychiatric diseases using it.

Sand-dust weather conditions are considered the primary challenge to free-space optical (FSO) communications. It may cause severe attenuation that is malignant to FSO link performance. This study investigates the impact of sand-dust particles on a laser signal using the radiation propagation method and the small-angle approximation method. Numerical simulation shows that in sand-dust weather conditions, the multiple scattering effect is dominant and results in signal pulse delay and pulse broadening. Furthermore, the signal attenuation follows a negative exponential distribution to the laser wavelength. Superior performance can be achieved by employing a longer wavelength laser to reduce pulse delay and mutual interference.

Immunomagnetic beads (IMBs) for cell sorting are universally used in medical and biological fields. At present, the IMBs on the market are ferrite coated with a silicon shell. Based on a new type of magnetic material, the graphene coated iron nitride magnetic particle (G@FeN-MP), which we previously reported, we prepared a novel IMB, a graphene oxide coated iron nitride immune magnetic bead (GO@FeN-IMBs), and explored its feasibility for cell sorting. First, the surface of the G@FeN-MP was oxidized to produce oxygen-containing groups as carboxyl, etc. by the optimized Hummers’ method, followed by a homogenization procedure to make the particles uniform in size and dispersive. The carboxy groups generated were then condensed and coupled with anti-CD3 antibodies by the carbodiimide method to produce an anti-CD3-GO@FeN-IMB after the coupling efficacy was proved by bovine serum albumin (BSA) and labeled antibodies. Finally, the anti-CD3-GO@FeN-IMBs were incubated with a cell mixture containing human T cells. With the aid of a magnetic stand, the T cells were successfully isolated from the cell mixture. The isolated T cells turned out to be intact and could proliferate with the activation of the IMBs. The results show that the G@FeN-MP can be modified for IMB preparation, and the anti-CD3-GO@FeN-IMBs we prepared can potentially separate T cells.