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Abstract Novel biologics in MG therapy research is on the rise. This research aimed to investigate the characteristics of registered trials on novel therapies for myasthenia gravis on ClinicalTrials.gov. This cross-sectional study used a descriptive approach to assess the features of the included trials on ClinicalTrials.gov. We found 62 registered trials from 2007 to 2023 on ClinicalTrials.gov. The results showed a yearly rise in the number of registered trials (r = 0.76, p

Abstract Background Annexin (ANN) is calcium (Ca2+)-dependent and phospholipid binding protein family, which is involved in plant growth and development and response to various stresses. However, little known about ANN genes were identified from crape myrtle, an ornamental horticultural plant widely cultivated in the world. Results Here, 9 LiANN genes were identified from Lagerstroemia indica, and their characterizations and functions were investigated in L. indica for the first time. The LiANN genes were divided into 2 subfamilies. The gene structure, chromosomal location, and collinearity relationship were also explored. In addition, the GO annotation analysis of these LiANNs indicated that they are enriched in molecular functions, cellular components, and biological processes. Moreover, transcription factors (TFs) prediction analysis revealed that bHLH, MYB, NAC, and other TFs can interact with the LiANN promoters. Interestingly, the LiANN2/4/6–9 were demonstrated to play critical roles in the branching architecture of crape myrtle. Furthermore, the LiANN2/6/8/9 were differentially expressed under salt treatment, and a series of TFs regulating LiANN2/6/8/9 expression were predicted to play essential roles in salt resistance. Conclusions These results shed light on profile and function of the LiANN gene family, and lay a foundation for further studies of the LiANN genes.

The occurrence of ovarian cancer (OC) is a major factor in women’s mortality rates. Despite progress in medical treatments, like new drugs targeting homologous recombination deficiency, survival rates for OC patients are still not ideal. The tumor microenvironment (TME) includes cancer cells, fibroblasts linked to cancer (CAFs), immune-inflammatory cells, and the substances these cells secrete, along with non-cellular components in the extracellular matrix (ECM). First, the TME mainly plays a role in inhibiting tumor growth and protecting normal cell survival. As tumors progress, the TME gradually becomes a place to promote tumor cell progression. Immune cells in the TME have attracted much attention as targets for immunotherapy. Immune checkpoint inhibitor (ICI) therapy has the potential to regulate the TME, suppressing factors that facilitate tumor advancement, reactivating immune cells, managing tumor growth, and extending the survival of patients with advanced cancer. This review presents an outline of current studies on the distinct cellular elements within the OC TME, detailing their main functions and possible signaling pathways. Additionally, we examine immunotherapy rechallenge in OC, with a specific emphasis on the biological reasons behind resistance to ICIs.

The production management of lactating sows is a crucial aspect of pig farm operations, as their health directly impacts the farm’s production efficiency. The feeding behavior of lactating sows can reflect their health and welfare status, and monitoring this behavior is essential for precise feeding and management. To address the issues of time-consuming and labor-intensive manual inspection of lactating sows’ feeding behavior and the reliance on breeders’ experience, we propose a method based on the improved YOLO (You Only Look Once) v5s algorithm and image segmentation for detecting the feeding behavior of lactating sows. Based on the YOLOv5s algorithm, the SE (Squeeze-and-Excitation) attention module was added to enhance the algorithm’s performance and reduce the probability of incorrect detection. Additionally, the loss function was replaced by WIoU (Weighted Intersection over Union) to accelerate the model’s convergence speed and improve detection accuracy. The improved YOLOv5s-C3SE-WIoU model is designed to recognize pre-feeding postures and feed trough conditions by detecting images of lactating sows. Compared to the original YOLOv5s, the improved model achieves an 8.9% increase in mAP@0.5 and a 4.7% increase in mAP@0.5 to 0.95. This improvement satisfies the requirements for excellent detection performance, making it suitable for deployment in large-scale pig farms. From the model detection results, the trough remnant image within the detection rectangle was extracted. This image was further processed using image processing techniques to achieve trough remnant image segmentation and infer the remnant amount. Based on the detection model and residue inference method, video data of lactating sows’ feeding behavior were processed to derive the relationship between feeding behavior, standing time, and residue amount. Using a standing duration of 2 s and a leftover-feed proportion threshold of 2% achieves the highest accuracy, enabling the identification of abnormal feeding behavior. We analyzed the pre-feeding postures and residual feed amounts of abnormal and normal groups of lactating sows. Our findings indicated that standing time was significantly lower and residual feed amount was higher in the abnormal groups compared to the normal groups. By combining standing time and residual feed amount information, accurate detection of the feeding status of lactating sows can be realized. This approach facilitates the accurate detection of abnormal feeding behaviors of lactating sows in large-scale pig farm environments.

Abstract The power generation of the photovoltaic plant is related to the cleanliness of the photovoltaic modules. The accumulation of natural dust is the main source of pollution, which is affected by human activities and meteorological factors such as temperature, humidity, wind speed, and rainfall concentration in the current region. On the basis of particle swarm optimization (PSO) and the least‐squares support vector machine (LSSVM), the density of dust on photovoltaic modules was estimated. The authors proposed that the inertia weight decreased as a concave function to improve the efficiency of optimization and let the two positive constants change dynamically to improve convergence performance. The dust accumulation prediction model was established considering natural rainfall and the authors obtained the attenuation rate of the photovoltaic power output. Finally, the experiments in Hangzhou showed that the model can predict the density of accumulated dust quickly, which provides a theory for predicting PV power generation and managing the cleaning frequency.

ABSTRACTThe emergence and nosocomial spread of the multidrug-resistant Candida auris pose a severe public health threat. Most C. auris clinical isolates are fluconazole resistant. In this study, we conduct transposon-mediated screens to profile genes whose inactivation causes fluconazole resistance in C. auris. We discover that mutation of genes encoding the Ubr2/Mub1 ubiquitin-ligase complex results in high fluconazole resistance by stabilizing the transcription activator, Rpn4. Global transcriptomic analysis, quantitative PCR, and combinatorial gene deletion reveal that Rpn4 causes fluconazole resistance by upregulating four efflux pump genes, SNQ21, SNQ22, MDR1, and CDR1, increasing efflux activity of the cell. Rpn4 autoactivates its own expression by binding to a PACE element in its promoter, forming a positive autoregulatory loop. Rpn4 also promotes CDR1 expression by binding to a PACE element in the CDR1 promoter. Furthermore, using the published genome sequence data of 304 clinical isolates, we identified a UBR2 A316T mutation in isolates from clades I and III. Although complementation of the ubr2Δ mutant with the UBR2A316T allele resulted in increased susceptibility to fluconazole, the UBR2A316T mutant was still more resistant to fluconazole compared to wild type, suggesting that acquisition of the mutation is sufficient to confer an increase in fluconazole resistance. In conclusion, this study identifies Rpn4 as a critical transcription factor that regulates fluconazole resistance via the Rpn4-efflux pump axis in C. auris.IMPORTANCECandida auris is a recently emerged pathogenic fungus of grave concern globally due to its resistance to conventional antifungals. This study takes a whole-genome approach to explore how C. auris overcomes growth inhibition imposed by the common antifungal drug fluconazole. We focused on gene disruptions caused by a “jumping genetic element” called transposon, leading to fluconazole resistance. We identified mutations in two genes, each encoding a component of the Ubr2/Mub1 ubiquitin-ligase complex, which marks the transcription regulator Rpn4 for degradation. When either protein is absent, stable Rpn4 accumulates in the cell. We found that Rpn4 activates the expression of itself as well as the main drug efflux pump gene CDR1 by binding to a PACE element in the promoter. Furthermore, we identified an amino acid change in Ubr2 in many resistant clinical isolates, contributing to Rpn4 stabilization and increased fluconazole resistance.

Background With the establishment of the cardiac-gut axis concept, increasing evidence has suggested the involvement and important regulatory role of the gut microbiota (GM) and short chain fatty acid (SCFA) in cardiovascular diseases. However, the relationship between GM and atrial fibrillation (AF) is still poorly understood. Objectives The aim of this study was to investigate whether there were differences in GM and SCFA between AF patients and healthy controls. Methods In this study, we enrolled 30 hospitalized patients with AF and 30 matched patients with sinus rhythm (SR). GM species in fecal samples were evaluated through amplicon sequencing targeting the 16Sribosomal RNA gene. The feces SCFAs were describe step by step the quantitative analysis using gas chromatography-mass spectrometry (GC-MS). GM species richness, diversity, differential abundance of individual taxa between AF and SR were analyzed. Results AF patients showed decreased species richness and α-diversity compared to SR patients, but there was no statistical difference. The phylogenetic diversity was significant decreased in AF group. The β-diversity indexes revealed significant differences in GM community structure between the AF group and the SR group. After investigated the individual taxa, AF group showed altered relative abundance in several taxa compared to the SR group. linear discriminant analysis (LDA) effect size (LEfSe) analysis revealed, a significant decrease in Bifidobacterium and a greater abundance of Lactobacillus, Fusobacterium, Haemophilus in AF group compared with the SR group. The abundance of haemophilus was negative correlated with isovaleric acid and isobutyric acid. Conclusions In AF patients, the GM phylogenetic diversity and β-diversity decreased, the relative abundance altered in several taxa and the bacterial community structure changed as well as the SCFA level. GM and SCFA dysbiosis might play a crucial part in the occurrence and development of AF.

Traditional vision methods for solar cell defect detection have problems such as low accuracy and few types of detection, so this paper proposes an optimized YOLOv5 model for more accurate and comprehensive identification of defects in solar cells. The model firstly integrates five data enhancement methods, namely Mosaic, Mixup, hsv transform, scale transform and flip, to expand the existing data set to improve the feature training accuracy and enhance the robustness of the model; secondly, CA attention mechanism is introduced to improve the feature extraction ability of the model; to address the problems of different target defect classification and localization concerns, the detection head in the original model is replaced with a decoupling head, which significantly improve the detection accuracy of the model without affecting the convergence speed of the model. The results show that the optimized model achieves an mAP of 96.1% on the publicly available dichotomous ELPV dataset, and can identify and locate a variety of common defects in the PVEL-AD dataset, while the mAP can reach 87.4%, an improvement of 10.38% compared with the original YOLOv5 model, which enables the model to perform more accurately while ensuring the real-time requirement of solar cell surface defects detection task.

A quasi-continuous-wave (QCW) laser diode (LD) driver is commonly used to drive diode bars and stacks designed specifically for QCW operations in solid-state lasers. Such drivers are optimized to deliver peak current and voltage pulses to LDs while maintaining low average power levels. As a result, they are widely used in laser processing devices and laser instruments. Traditional high-energy QCW LD drivers primarily use capacitors as energy storage components and pulsed constant-current sources with op-amps and power metal-oxide-semiconductor field-effect transistors (MOSFETs) as their core circuits for generating repeated constant-current pulses. The drawback of this type of driver is that the driver’s output voltage needs to be manually adjusted according to the operating voltage of the load before use to maximize driver efficiency while providing a sufficient current. Another drawback is its inability to automatically adjust the output voltage to maintain high efficiency when the load changes during the driver operation. Drastic changes in the load can cause the driver to fail to function properly in extreme cases. Based on the above traditional circuit structure, this study designed a stability compensation circuit and realized a QCW LD driver for driving a GS20 diode stack with a maximum repetition rate of 100 Hz, a constant current of approximately 300 A, a load voltage of approximately 10 V, and a pulse width of approximately 300 μs. In particular, a high-efficiency, load-adaptive driving method was used with the MOSFETs in the critical saturation region (i.e., between the linear and saturated regions), controlling its power loss effectively while achieving maximum output current of the driver. The experiments demonstrated that the driver efficiency could be maintained at more than 80% when the load current varied from 50 to 300 A.

Abstract Background In insects, an interplay between the activities of distinct hormones, such as juvenile hormone (JH) and 20-hydroxyecdysone (20E), regulates the progression through numerous life history hallmarks. As a crucial endocrine factor, JH is mainly synthesized in the corpora allata (CA) to regulate multiple physiological and developmental processes, including molting, metamorphosis, and reproduction. During the last century, significant progress has been achieved in elucidating the JH signal transduction pathway, while less progress has been made in dissecting the regulatory mechanism of JH biosynthesis. Previous work has shown that receptor tyrosine kinase (RTK) signaling regulates hormone biosynthesis in both insects and mammals. Here, we performed a systematic RNA interference (RNAi) screening to identify RTKs involved in regulating JH biosynthesis in the CA of adult Blattella germanica females. Results We found that the epidermal growth factor receptor (Egfr) is required for promoting JH biosynthesis in the CA of adult females. The Egf ligands Vein and Spitz activate Egfr, followed by Ras/Raf/ERK signaling, and finally activation of the downstream transcription factor Pointed (Pnt). Importantly, Pnt induces the transcriptional expression of two key enzyme-encoding genes in the JH biosynthesis pathway: juvenile hormone acid methyltransferase (JHAMT) and methyl farnesoate epoxidase (CYP15A1). Dual-luciferase reporter assay shows that Pnt is able to activate a promoter region of Jhamt. In addition, electrophoretic mobility shift assay confirms that Pnt directly binds to the − 941~ − 886 nt region of the Jhamt promoter. Conclusions This study reveals the detailed molecular mechanism of Egfr signaling in promoting JH biosynthesis in the German cockroach, shedding light on the intricate regulation of JH biosynthesis during insect development.

Abstract Cetirizine hydrochloride (CTZ), an antiallergic drug, is a new‐generation H1 receptor antagonist and a second‐generation H1 antihistamine. We aimed to prepare cetirizine hydrochloride liposomes, based on which cetirizine hydrochloride liposomal (CTZL) in situ gel (ISG) was prepared, to improve the retention time in the eye. CTZL were prepared by the ethanol injection method combined with the ammonium sulfate gradient method. A CTZ liposomal temperature‐sensitive gel was prepared using the cold dissolution method. Large‐eared white rabbits were used in retention and irritation experiments. The liposomes were small single‐chambered liposomes, spherical or sphere‐like, with a vesicle size of 187.03 ± 6.20 nm, an encapsulation efficiency of 70.39 ± 1.13%, and a drug loading capacity of 4.63 ± 0.06%. The gelling temperatures before and after dilution by simulated tear fluid were 26.1 ± 0.2°C and 34.2 ± 0.2°C, the vesicle size was 184.94 ± 7.28 nm, and the liposomes were spherical or sphere‐like in the gel matrix. The in vitro dissolution and release experiments indicate that the gel was released upon dissolution and exhibited a zero‐level release pattern. Preparation into liposomes and liposomal gels prolonged the ocular retention time of the formulation without ocular irritation.

The rapid rise of glacioeustatic change is the most extreme paleoenvironment alteration in the aftermath of Snowball Earth. Although geologists conducted a lot of multi-subdiscipline research on this issue previously, there still exists the potential room for further discussions of the process in detail. For decades, the practice proved that the Fischer plot is a simple and robust tool to illustrate the fluctuations of accommodation patterns v.s. cycle sets or strata depth which could be interpreted as relative sea-level changes. This research simulates the Fischer plot to unravel the sea-level change in the aftermath of Marinoan glaciation by measuring the lower Ediacaran Doushantuo Formation in Shennongjia, South China. The result shows that 131 fifth-order cycles and nine third-order cycles help us propose a completed second-order cycle variation of ice melting-forced sea-level change, i.e., (1) early high-frequency and slow to rapid stepwise rising, and (2) followed by a stable decrease in the latter. In addition, the vertical sedimentary facies of the lower Doushantuo Formation display, in ascending order, (1) intertidal carbonate rock, (2) subtidal clastics with turbidite, and (3) intertidal lagoon fine clastics, indicating the process of the relative waxing and waning of sea-level. Such interpretation of the Fischer plot and the sedimentary facies’ vertical evolution is beneficial for studying the high-frequency sea-level change and paleogeographic reconstruction of post-Marinoan deglaciation.

The core body temperature serves as a pivotal physiological metric indicative of sow health, with rectal thermometry prevailing as a prevalent method for estimating core body temperature within sow farms. Nonetheless, employing contact thermometers for rectal temperature measurement proves to be time-intensive, labor-demanding, and hygienically suboptimal. Addressing the issues of minimal automation and temperature measurement accuracy in sow temperature monitoring, this study introduces an automatic temperature monitoring method for sows, utilizing a segmentation network amalgamating YOLOv5s and DeepLabv3+, complemented by an adaptive genetic algorithm-random forest (AGA-RF) regression algorithm. In developing the sow vulva segmenter, YOLOv5s was synergized with DeepLabv3+, and the CBAM attention mechanism and MobileNetv2 network were incorporated to ensure precise localization and expedited segmentation of the vulva region. Within the temperature prediction module, an optimized regression algorithm derived from the random forest algorithm facilitated the construction of a temperature inversion model, predicated upon environmental parameters and vulva temperature, for the rectal temperature prediction in sows. Testing revealed that vulvar segmentation IoU was 91.50%, while the predicted MSE, MAE, and R2 for rectal temperature were 0.114 °C, 0.191 °C, and 0.845, respectively. The automatic sow temperature monitoring method proposed herein demonstrates substantial reliability and practicality, facilitating an autonomous sow temperature monitoring.

Nutrient recovery and recycling are of great importance in sustainable development. Blackwater (BW) refers to wastewater from toilets, which contains feces, urine, water, and toilet paper from flush toilets. The highly concentrated nutrients of blackwater could be collected through source separation and treated adequately to recover nutrients efficiently and economically. The review intends to give an overview of the characteristics of BW and different techniques to recover nutrients and other valuable products. A number of these technologies are currently under development or being tested at laboratory or pilot scale. The perspective for blackwater nutrient recovery technologies is very positive due to their great potential. For application of source-oriented sanitation infrastructure and systems, there is still a long way to go for development of commercial technologies and valuable products.

In this study, an efficient and accurate staggered-grid finite-difference time-domain method to solve the two-dimensional (2-D) first-order stress–velocity elastic-wave equation is proposed. In the conventional implementation of the staggered-grid finite-difference (SGFD) method, the same SGFD operator is used to approximate the spatial derivatives. However, we propose a numerical method based on the mixed SGFD operators that are more efficient but similar in accuracy when compared with a uniform SGFD operator. We refer to the proposed method as the nonbalanced SGFD numerical scheme that combines the high-order SGFD operators with the second-order SGFD operators. The suitability of the proposed scheme is verified by dispersion analysis. Through SGFD modeling and reverse-time migration examples, we demonstrate that the proposed nonbalanced scheme offers a similar level of accuracy with a lower computational cost compared with the time-consuming conventional SGFD method.

Sow body condition scoring has been confirmed as a vital procedure in sow management. A timely and accurate assessment of the body condition of a sow is conducive to determining nutritional supply, and it takes on critical significance in enhancing sow reproductive performance. Manual sow body condition scoring methods have been extensively employed in large-scale sow farms, which are time-consuming and labor-intensive. To address the above-mentioned problem, a dual neural network-based automatic scoring method was developed in this study for sow body condition. The developed method aims to enhance the ability to capture local features and global information in sow images by combining CNN and transformer networks. Moreover, it introduces a CBAM module to help the network pay more attention to crucial feature channels while suppressing attention to irrelevant channels. To tackle the problem of imbalanced categories and mislabeling of body condition data, the original loss function was substituted with the optimized focal loss function. As indicated by the model test, the sow body condition classification achieved an average precision of 91.06%, the average recall rate was 91.58%, and the average F1 score reached 91.31%. The comprehensive comparative experimental results suggested that the proposed method yielded optimal performance on this dataset. The method developed in this study is capable of achieving automatic scoring of sow body condition, and it shows broad and promising applications.

A Pockels cell driver (PCD) can be viewed as a high-voltage pulse width generator for controlling the bi-refringence effect of electro-optical crystals. The main features of a PCD include a high repetition rate, fast on and off switching, variable pulse duration, and a true square pulse shape. The most commonly used PCD has a narrow pulse width tuning range, typically within a few microseconds. In this paper, we propose a PCD based on a novel pulse width modulation (PWM) signal-generation strategy that can continuously adjust its pulse width with a minimum step size of 10 ns and no restriction on the maximum width. Therefore, it is easily compatible with both “On-type” and “Off-type” applications of the electro-optic crystal quarter-wave voltage. The experimental results show that the rising and falling times of the proposed PCD are approximately 7.3 ns and 7.8 ns, respectively, with a maximum repetition rate of 1 MHz and a maximum voltage of approximately 2.0 kV. Finally, the functionality of the PCD is demonstrated in a home-built slab laser.

The mechanism of how VEGF-C is regulated to promote lymphatic metastasis of oesophageal cancer is unclear. Here the authors show that nicotine prevents the mRNA decay of VEGF-C mRNA and promotes lymphatic metastasis by downregulating deubiquitinase OTUD3 and RNA binding protein ZFP36.

Estrus detection is an essential operation in the breeding of sows, and accurate estrus detection is immensely important to maintain the productivity and reproductive performance of sow. However, traditional sow estrus detection relies on the manually back-pressure test, which is time-consuming and labor-intensive. This study aimed to develop an automatic method to detect estrus. In this study, a model based on the optimized yolov5s algorithm was constructed to detect the four sow postures of standing, sitting, sternum, lateral, and calculated the frequency of posture change in sows. Based on this, we studied the behavior of sows before and after estrus. The method embedded a convolutional block attention module into the backbone network to improve the feature extraction capability of the model. In addition, the object box judgment module was used to avoid interference from other sows in the detection region. Accelerate the optimized model on the TensorRT platform, ensuring that the embedded graphics card can run the model with lower latency. The result shows that the precision of estrus detection is 97.1%, and the accuracy of estrus detection is 94.1%. The processing time of a single image on the embedded graphics card is 74.4 ms, and this method could better meet the estrus detection demand in sow production.

Insect metabolites play vital roles in regulating the physiology, behavior, and numerous adaptations of insects, which has contributed to them becoming the largest class of Animalia. However, systematic metabolomics within the insects is still unclear. The present study performed a widely targeted metabolomics analysis based on the HPLC-MS/MS technology to construct a novel integrated metabolic database presenting comprehensive multimetabolite profiles from nine insect species across three metamorphosis types. A total of 1442 metabolites were identified, including amino acids and their metabolites, organic acids and their derivatives, fatty acids (FAs), glycerophospholipids (GPs), nucleotides and their metabolites, and benzene and its substituted derivatives. Among them, 622 metabolites were used to generate a 0 and 1 matrix based on their presence or absence, and these metabolites were enriched in arachidonic acid metabolism, tyrosine metabolism, phenylalanine metabolism, and insect hormone biosynthesis pathways. Our study revealed that there is a high coincidence between the evolutionary relationships of the species and the hierarchical cluster based on the types of metabolites, while the quantities of the metabolites show a high diversity among species. The metabolome of the nine representative insects provides an important platform for implementing the analysis of insect systemic metabolites and biological events at the metabolic level.

Abstract Background HOMER family scaffolding proteins (HOMER1-3) play critical roles in the development and progression of human disease by regulating the assembly of signal transduction complexes in response to extrinsic stimuli. However, the role of HOMER protein in breast cancer remains unclear. Methods HOMER3 expression was examined by immunohistochemistry in breast cancer patient specimens, and its significance in prognosis was assessed by Kaplan–Meier survival analysis. The effects of HOMER3 in growth factor-induced β-Catenin activation were analyzed by assays such as TOP/FOP flash reporter, tyrosine phosphorylation assay and reciprocal immunoprecipitation (IP) assay. Role of HOMER3 in breast cancer metastasis was determined by cell function assays and mice tumor models. Results Herein, we find that, among the three HOMER proteins, HOMER3 is selectively overexpressed in the most aggressive triple negative breast cancer (TNBC) subtype, and significantly correlates with earlier tumor metastasis and shorter patient survival. Mechanismly, HOMER3 interacts with both c-Src and β-Catenin, thus providing a scaffolding platform to facilitate c-Src-induced β-Catenin tyrosine phosphorylation under growth factor stimulation. HOMER3 promotes β-Catenin nuclear translocation and activation, and this axis is clinically relevant. HOMER3 promotes and is essential for EGF-induced aggressiveness and metastasis of TNBC cells both in vitro and in vivo. Conclusion These findings identify a novel role of HOMER3 in the transduction of growth factor-mediated β-Catenin activation and suggest that HOMER3 might be a targetable vulnerability of TNBC.

Sow farrowing is an important part of pig breeding. The accurate and effective early warning of sow behaviors in farrowing helps breeders determine whether it is necessary to intervene with the farrowing process in a timely manner and is thus essential for increasing the survival rate of piglets and the profits of pig farms. For large pig farms, human resources and costs are important considerations in farrowing supervision. The existing method, which uses cloud computing-based deep learning to supervise sow farrowing, has a high equipment cost and requires uploading all data to a cloud data center, requiring a large network bandwidth. Thus, this paper proposes an approach for the early warning and supervision of farrowing behaviors based on the embedded artificial-intelligence computing platform (NVIDIA Jetson Nano). This lightweight deep learning method allows the rapid processing of sow farrowing video data at edge nodes, reducing the bandwidth requirement and ensuring data security in the network transmission. Experiments indicated that after the model was migrated to the Jetson Nano, its precision of sow postures and newborn piglets detection was 93.5%, with a recall rate of 92.2%, and the detection speed was increased by a factor larger than 8. The early warning of 18 approaching farrowing (5 h) sows were tested. The mean error of warning was 1.02 h.

Neuroradiological methods play important roles in neurology, especially in cerebrovascular diseases. Fluid-attenuated inversion recovery (FLAIR) vascular hyperintensity (FVH) is frequently encountered in patients with acute ischemic stroke and significant intracranial arterial stenosis or occlusion. The mechanisms underlying this phenomenon and the clinical implications of FVH have been a matter of debate. FVH is associated with large-vessel occlusion or severe stenosis, as well as impaired hemodynamics. Possible explanations suggested for its appearance include stationary blood and slow antegrade or retrograde filling of the leptomeningeal collateral circulation. However, the prognostic value of the presence of FVH has been controversial. FVH can also be observed in patients with transient ischemic attack (TIA), which may have different pathomechanisms. Its presence can help clinicians to identify patients who have a higher risk of stroke after TIA. In this review article, we aim to describe the mechanism and influencing factors of FVH, as well as its clinical significance in patients with cerebrovascular disease.

Abstract Background Amnestic mild cognitive impairment (aMCI) is a syndrome characterized by significant forgetfulness that does not meet the criteria of dementia. Individuals with aMCI are at greater risk of progressing to dementia. Current studies suggest that good sleep quality is linked with preserved cognition in the elderly, and sleep complaints are common among the elderly with amnesia. Therefore, improving their sleep may be helpful for maintaining and improving their cognitive capacity. According to the theory of traditional Chinese medicine, Yi-Zhi-An-Shen is an herbal compound which may ameliorate forgetfulness and sleep disorders. As growing evidence indicates that the gut microbiome is associated with major mental symptoms, a hypothesis was proposed that Yi-Zhi-An-Shen granules (YZASG) might work by alternating microbial abundance and diversity. In this study, the investigators intend to assess the efficacy of YZASG on global cognition in the elderly suffering from aMCI and evaluate its safety as well as its potential mechanisms via sleep quality, fecal microbial 16S ribosomal DNA and metagenomics analyses, and serum markers. Methods/design This study is a randomized, double-blind, placebo-controlled clinical trial. A total of 80 patients (aged 60–85 years) will be recruited and allocated randomly to a treatment group and a placebo group in a 1:1 ratio and will then be administered YZASG or isodose placebo three times a day. The intervention course is 16 weeks, with an 18 months follow-up. The primary outcome is the Alzheimer’s Disease Assessment Scale-Cognitive Subscale. Secondary outcome measures are the Mini-Mental State Examination, Montreal Cognitive Assessment, Pittsburgh Sleep Quality Index, serum concentrations of immunological factors and inflammatory cytokines, and fecal microbiota. Fecal microbiota will only be collected at the baseline and endpoint of the intervention. Discussion The results of this trial will be conducive to assessing the safety and effectiveness on cognition of YZASG in intervening aMCI among the elderly and determining if it takes effect via the improvement of sleep quality, regulation of gut microbiota, and concentration of certain serum markers. Trial registration ClinicalTrials.gov, NCT03601000. Registered on 26 July 2018.

Accumulating evidence has shown that long non-coding RNAs (lncRNAs) can be used as biological markers and treatment targets in cancer and play various roles in cancer-related biological processes. However, the lncRNA expression profiles and their roles and action mechanisms in ovarian cancer (OC) are largely unknown. Here, we assessed the lncRNA expression profiles in OC tissues from The Cancer Genome Atlas (TCGA) database, and one upregulated lncRNA, LINC01969, was selected for further study. LINC01969 expression levels in 41 patients were verified using quantitative real-time polymerase chain reaction (qRT-PCR). The in vitro effects of LINC01969 on OC cell migration, invasion, and proliferation were determined by the CCK-8, ethynyl-2-deoxyuridine (EdU), wound healing, and Transwell assays. Epithelial–mesenchymal transition (EMT) was evaluated using qRT-PCR and Western blotting. The molecular mechanisms of LINC01969 in OC were assessed through bioinformatics analysis, RNA-binding protein immunoprecipitation (RIP), dual luciferase reporter gene assays, and a rescue experiment. Finally, in vivo experiments were conducted to evaluate the functions of LINC01969. The results of the current study showed that LINC01969 was dramatically upregulated in OC, and patients with lower LINC01969 expression levels tended to have better overall survival. Further experiments demonstrated that LINC01969 promoted the migration, invasion, and proliferation of OC cells in vitro and sped up tumor growth in vivo. Additionally, LINC01969, which primarily exists in the cytoplasm, boosted LARP1 expression by sponging miR-144-5p and promoted the malignant phenotypes of OC cells. In conclusion, the LINC01969/miR-144-5p/LARP1 axis is a newly identified regulatory signaling pathway involved in OC progression.

Ovarian cancer is the leading cause of gynecologic cancer-related deaths. Emerging research has revealed a close relationship between circular RNAs (circRNAs) and ovarian cancer development, metastasis, and prognosis. The objective of our research was to further explore the relationship between circASH2L and ovarian cancer. Quantitative real-time polymerase chain reaction was used to detect the differential expression of circRNAs between normal ovaries and ovarian cancer tissues. The impact of circASH2L on the proliferation, invasion, and tumorigenicity of ovarian cancer cells was evaluated using gain- and loss-of-function experiments. The molecular mechanisms of circASH2L function were investigated using bioinformatics analysis, RNA fluorescence in situ hybridization, western blots, and dual-luciferase reporter assays. The results showed that circASH2L was remarkably upregulated in ovarian cancer. The invasion and growth of ovarian cancer cells were suppressed by circASH2L knockdown in vitro, and downregulation of circASH2L restrained both angiogenesis and lymphangiogenesis of tumor xenografts in vivo. Furthermore, circASH2L was mostly distributed in the cytoplasm, where it competes with vascular endothelial growth factor A (VEGFA) for binding to miR-665. These findings indicate that circASH2L has an oncogenic function in ovarian cancer. In conclusion, circASH2L plays a critical role in regulating ovarian cancer cell tumorigenesis, angiogenesis, and lymphangiogenesis through the miR-665/VEGFA axis and, therefore, is a possible candidate target for ovarian cancer treatment.

Objective Huang-Lian-Jie-Du-Tang (HLJDT), a traditional Chinese medicine, improves cognitive ability in rat models of Alzheimer’s disease (AD). The objective of this study was to evaluate the protective effects of HLJDT on learning and memory impairment that are caused by Aβ 25–35 . Methods Rats were randomly assigned to the following groups: control (water), Aβ 25–35 , donepezil hydrochloride 1.05 mg/kg, HLJDT 6 g/kg, HLJDT 3 g/kg, and HLJDT 1.5 g/kg and the corresponding drugs were administered for 28 days by oral gavage. HLJDT for the prevention of Aβ 25–35 -induced injury in rats and the underlying mechanisms were assessed. Aβ 25–35 and amyloid precursor protein (APP) levels were measured in the hippocampal specimens. Total superoxide dismutase (T-SOD), glutathione (GSH), and malondialdehyde (MDA) levels in the hippocampus were also measured. The ultrastructure of CA1 hippocampal region was observed using electron microscopy. Results HLJDT treatment ameliorated impaired learning and memory significantly, decreased Aβ 25–35 , and APP levels in the hippocampus, increased T-SOD and GSH activity and decreased the MDA concentration, and alleviated the nuclear and cytoplasmic abnormalities of the hippocampal CA 1 region that were induced by Aβ 25–35 injection. Conclusions HLJDT might decrease hippocampal vulnerability to Aβ 25–35 , suggesting its potential neuroprotective effect in AD.

Electrical stimulation induces significant neovessel formation in vivo. We have shown that electrical stimulation of endothelial cells functions as an important contributor to angiogenesis in monolayer culture. Because angiogenesis occurs in a three-dimensional (3D) environment, in this study we investigated the effects of a direct current (DC) electrical field (EF) on endothelial neovessel formation in 3D culture. There was a significant increase in tube formation when endothelial cells were stimulated with EF for 4 h. The lengths of the tube-like structures were augmented further by the continued EF exposure. The lengths of the tubes also increased dose-dependently in the EF-treated cultures in the field strengths of 50 mV/mm∼200 mV/mm for 6 h. Electrical fields of small physiological magnitude enhanced VEGF expression by endothelial cells in 3D culture. EF treatment also resulted in activation of VEGFR2, Akt, extracellular regulated kinase 1,2 (Erk1/2), as well as the c-Jun NH2-terminal kinase (JNK). The tyrosine kinase inhibitor SU1498 that blocks VEGFR2 activity exhibited a potent inhibition of tube growth, and the Akt inhibitor MK-2206 2HCl, the Erk1/2 inhibitor U0126 and the JNK inhibitor SB203580 significantly reduced EF-stimulated tubulogenesis. These results suggest the importance of the VEGFR2 signaling pathway during EF-induced angiogenesis. The results of this study provide novel evidence that endogenous EFs may promote blood vessel formation of endothelial cells by activating the VEGF receptor signaling pathway.