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Biomarcadores , Hiperuricemia , Análisis de la Aleatorización Mendeliana , Ácido Úrico , Trombosis de la Vena , Humanos , Ácido Úrico/sangre , Trombosis de la Vena/sangre , Trombosis de la Vena/genética , Trombosis de la Vena/diagnóstico , Trombosis de la Vena/epidemiología , Factores de Riesgo , Biomarcadores/sangre , Hiperuricemia/sangre , Hiperuricemia/diagnóstico , Hiperuricemia/genética , Hiperuricemia/epidemiología , Predisposición Genética a la Enfermedad , Medición de Riesgo , Fenotipo , Polimorfismo de Nucleótido Simple , Europa (Continente)/epidemiologíaRESUMEN
The elasticity of soft tissues has been widely considered a characteristic property for differentiation of healthy and lesions and, therefore, motivated the development of several elasticity imaging modalities, for example, ultrasound elastography, magnetic resonance elastography, and optical coherence elastography to directly measure the tissue elasticity. This paper proposes an alternative approach of modeling the elasticity for prior knowledge-based extraction of tissue elastic characteristic features for machine learning (ML) lesion classification using computed tomography (CT) imaging modality. The model describes a dynamic non-rigid (or elastic) soft tissue deformation in differential manifold to mimic the tissues' elasticity under wave fluctuation in vivo. Based on the model, a local deformation invariant is formulated using the 1st and 2nd order derivatives of the lesion volumetric CT image and used to generate elastic feature map of the lesion volume. From the feature map, tissue elastic features are extracted and fed to ML to perform lesion classification. Two pathologically proven image datasets of colon polyps and lung nodules were used to test the modeling strategy. The outcomes reached the score of area under the curve of receiver operating characteristics of 94.2% for the polyps and 87.4% for the nodules, resulting in an average gain of 5 to 20% over several existing state-of-the-art image feature-based lesion classification methods. The gain demonstrates the importance of extracting tissue characteristic features for lesion classification, instead of extracting image features, which can include various image artifacts and may vary for different protocols in image acquisition and different imaging modalities.
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BACKGROUND: Porcine deltacoronavirus (PDCoV) is a swine enteropathogenic coronavirus that affects young pigs, causing vomiting, acute diarrhea, dehydration, and even death. There is growing evidence that PDCoV can undergo cross-species as well as zoonotic transmissions. Due to the frequent outbreaks of this deadly virus, early detection is essential for effective prevention and control. Therefore, developing a more convenient and reliable method for PDCoV detection is the need of the hour. RESULTS: This study utilized a high-affinity monoclonal antibody as the capture antibody and a horseradish peroxidase labeled polyclonal antibody as the detection antibody to develop an enzyme-linked immunosorbent assay (DAS-ELSA) for PDCoV detection.Both antibodies target the PDCoV nucleocapsid (N) protein. The findings of this study revealed that DAS-ELISA was highly specific to PDCoV and did not cross-react with other viruses to cause swine diarrhea. The limit of detection of the virus titer using this method was 103 TCID50/mL of PDCoV particles. The results of a parallel analysis of 239 known pig samples revealed a coincidence rate of 97.07% (κ = 0.922) using DAS-ELISA and reverse transcriptase PCR (RT-PCR). The DAS-ELISA was used to measure the one-step growth curve of PDCoV in LLC-PK cells and the tissue distribution of PDCoV in infected piglets. The study found that the DAS-ELISA was comparable in accuracy to the TCID50 method while measuring the one-step growth curve. Furthermore, the tissue distribution measured by DAS-ELISA was also consistent with the qRT-PCR method. CONCLUSION: The developed DAS-ELISA method can be conveniently used for the early clinical detection of PDCoV infection in pigs, and it may also serve as an alternative method for laboratory testing of PDCoV.
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Deltacoronavirus , Ensayo de Inmunoadsorción Enzimática , Enfermedades de los Porcinos , Animales , Ensayo de Inmunoadsorción Enzimática/veterinaria , Ensayo de Inmunoadsorción Enzimática/métodos , Porcinos , Enfermedades de los Porcinos/virología , Enfermedades de los Porcinos/diagnóstico , Enfermedades de los Porcinos/inmunología , Deltacoronavirus/aislamiento & purificación , Infecciones por Coronavirus/veterinaria , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/virología , Infecciones por Coronavirus/inmunología , Anticuerpos Monoclonales/inmunología , Sensibilidad y Especificidad , Antígenos Virales/análisis , Antígenos Virales/inmunología , Anticuerpos Antivirales/sangreRESUMEN
Pancreatic cancer (PC) is heterogeneous cancer having a high death rate and poor prognosis. The perioperative variables, such as anesthetics, may affect the cancer progression. Ciprofol is an intravenous anesthetic widely used recently. We aimed to explore the influence of ciprofol on PC and investigate its possible pathway. The proliferation, migration and invasion roles and apoptosis of ciprofol in human PC cells were examined using methylthiazolyldiphenyl-tetrazolium bromide, trans well and flow cytometery analysis. Then the putative targeted genes were examined using RNA-sequencing (RNA-seq) analysis. When differentially expressed genes (DEGs) were found, a protein-protein interaction network and pathway analyses were made. Moreover, MMP1 gene expression was confirmed in PC cells using quantitative real-time PCR. PANC-1 cells of PC were significantly suppressed with ciprofol in a dose-dependent and time-dependent way, and 20µg/mL ciprofol significantly suppressed tumor cell aggressiveness. Additionally, the RNA-seq analysis demonstrated that ciprofol controls the expression of 929 DEGs. 5 of 20 hub genes with increased connection were selected. Survival analysis demonstrated that MMP1 may be involved in the carcinogenesis and establishment of PC, reflecting the possible roles associated with ciprofol. Moreover, one target miRNA (hsa-miR-330-5p) of MMP1 was identified.
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Movimiento Celular , Proliferación Celular , Metaloproteinasa 1 de la Matriz , Invasividad Neoplásica , Neoplasias Pancreáticas , Humanos , Neoplasias Pancreáticas/patología , Neoplasias Pancreáticas/genética , Neoplasias Pancreáticas/tratamiento farmacológico , Neoplasias Pancreáticas/metabolismo , Proliferación Celular/efectos de los fármacos , Movimiento Celular/efectos de los fármacos , Línea Celular Tumoral , Metaloproteinasa 1 de la Matriz/genética , Metaloproteinasa 1 de la Matriz/metabolismo , Regulación Neoplásica de la Expresión Génica/efectos de los fármacos , Apoptosis/efectos de los fármacos , Mapas de Interacción de ProteínasRESUMEN
Biomedical texts provide important data for investigating drug-drug interactions (DDIs) in the field of pharmacovigilance. Although researchers have attempted to investigate DDIs from biomedical texts and predict unknown DDIs, the lack of accurate manual annotations significantly hinders the performance of machine learning algorithms. In this study, a new DDI prediction framework, Subgraph Enhance model, was developed for DDI (SubGE-DDI) to improve the performance of machine learning algorithms. This model uses drug pairs knowledge subgraph information to achieve large-scale plain text prediction without many annotations. This model treats DDI prediction as a multi-class classification problem and predicts the specific DDI type for each drug pair (e.g. Mechanism, Effect, Advise, Interact and Negative). The drug pairs knowledge subgraph was derived from a huge drug knowledge graph containing various public datasets, such as DrugBank, TwoSIDES, OffSIDES, DrugCentral, EntrezeGene, SMPDB (The Small Molecule Pathway Database), CTD (The Comparative Toxicogenomics Database) and SIDER. The SubGE-DDI was evaluated from the public dataset (SemEval-2013 Task 9 dataset) and then compared with other state-of-the-art baselines. SubGE-DDI achieves 83.91% micro F1 score and 84.75% macro F1 score in the test dataset, outperforming the other state-of-the-art baselines. These findings show that the proposed drug pairs knowledge subgraph-assisted model can effectively improve the prediction performance of DDIs from biomedical texts.
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Algoritmos , Biología Computacional , Interacciones Farmacológicas , Aprendizaje Automático , Biología Computacional/métodos , Humanos , Farmacovigilancia , Bases de Datos Factuales , Minería de Datos/métodosRESUMEN
Introduction: Pancreatic cancer (PC) is a malignancy with poor prognosis. This investigation aimed to determine the relevant genes that affect the prognosis of PC and investigate their relationship with immune infiltration. Methods: : First, we acquired PC single-cell chip data from the GEO database to scrutinize dissimilarities in immune cell infiltration and differential genes between cancerous and adjacent tissues. Subsequently, we combined clinical data from TCGA to identify genes relevant to PC prognosis. Employing Cox and Lasso regression analyses, we constructed a multifactorial Cox prognostic model, which we subsequently confirmed. The prognostic gene expression in PC was authenticated using RT-PCR. Moreover, we employed the TIMER online database to examine the relationship between the expression of prognostic genes and T and B cell infiltration. Additionally, the expression of GPRC5A and its correlation with B cells infiltration and patient prognosis were ascertained in tissue chips using multiple immune fluorescence staining. Results: The single-cell analysis unveiled dissimilarities in B-cell infiltration between cancerous and neighboring tissues. We developed a prognostic model utilizing three genes, indicating that patients with high-risk scores experienced a more unfavorable prognosis. Immune infiltration analysis revealed a significant correlation among YWHAZ, GPRC5A, and B cell immune infiltration. In tissue samples, GPRC5A exhibited substantial overexpression and a robust association with an adverse prognosis, demonstrating a positive correlation with B cell infiltration. Conclusion: GPRC5A is an independent risk factor in PC and correlated with B cell immune infiltration in PC. These outcomes indicated that GPRC5A is a viable target for treating PC.
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BACKGROUND: Menopause hormone therapy (MHT), as an effective method to alleviate the menopause-related symptoms of women, its benefits, risks, and potential influencing factors for the cardiovascular system of postmenopausal women are not very clear. OBJECTIVES: To evaluate cardiovascular benefits and risks of MHT in postmenopausal women, and analyze the underlying factors that affect both. SEARCH STRATEGY: The EMBASE, MEDLINE, and CENTRAL databases were searched from 1975 to July 2022. SELECTION CRITERIA: Randomized Clinical Trials (RCTs) that met pre-specified inclusion criteria were included. DATA COLLECTION AND ANALYSIS: Two reviewers extracted data independently. A meta-analysis of random effects was used to analyze data. MAIN RESULTS: This systematic review identified 33 RCTs using MHT involving 44,639 postmenopausal women with a mean age of 60.3 (range 48 to 72 years). There was no significant difference between MHT and placebo (or no treatment) in all-cause death (RR = 0.96, 95%CI 0.85 to 1.09, I2 = 14%) and cardiovascular events (RR = 0.97, 95%CI 0.82 to 1.14, I2 = 38%) in the overall population of postmenopausal women. However, MHT would increase the risk of stroke (RR = 1.23, 95%CI 1.08 to 1.41,I2 = 0%) and venous thromboembolism (RR = 1.86, 95%CI 1.39 to 2.50, I2 = 24%). Compared with placebo, MHT could improve flow-mediated arterial dilation (FMD) (SMD = 1.46, 95%CI 0.86 to 2.07, I2 = 90%), but it did not improve nitroglycerin-mediated arterial dilation (NMD) (SMD = 0.27, 95%CI - 0.08 to 0.62, I2 = 76%). Compared with women started MHT more than 10 years after menopause, women started MHT within 10 years after menopause had lower frequency of all-cause death (P = 0.02) and cardiovascular events (P = 0.002), and more significant improvement in FMD (P = 0.0003). Compared to mono-estrogen therapy, the combination therapy of estrogen and progesterone would not alter the outcomes of endpoint event. (all-cause death P = 0.52, cardiovascular events P = 0.90, stroke P = 0.85, venous thromboembolism P = 0.33, FMD P = 0.46, NMD P = 0.27). CONCLUSIONS: MHT improves flow-mediated arterial dilation (FMD) but fails to lower the risk of all-cause death and cardiovascular events, and increases the risk of stroke and venous thrombosis in postmenopausal women. Early acceptance of MHT not only reduces the risk of all-cause death and cardiovascular events but also further improves FMD, although the risk of stroke and venous thrombosis is not reduced. There is no difference in the outcome of cardiovascular system endpoints between mono-estrogen therapy and combination therapy of estrogen and progesterone.
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Accidente Cerebrovascular , Tromboembolia Venosa , Trombosis de la Vena , Femenino , Humanos , Persona de Mediana Edad , Anciano , Posmenopausia , Progesterona , Arterias , Estrógenos , Terapia de Reemplazo de Hormonas , Medición de RiesgoRESUMEN
BACKGROUND: The association between anti-vascular endothelial growth factor (VEGF) drugs and ocular adverse events (AEs) has been reported, but large real-world studies of their association with systemic AEs are still lacking. METHODS: A disproportionality analysis of reports from the FDA Adverse Event Reporting System from January 2004 to September 2021 was conducted to detect the significant ADR signals with anti-VEGF drugs (including aflibercept, bevacizumab, brolucizumab, pegaptanib, and ranibizumab). RESULTS: A total of 2980 reported cases with 7125 drug-AEs were included. Five drugs were all associated with eye disorders, and pegaptanib and ranibizumab were also associated with cardiac disorders. For ranibizumab, pegaptanib, bevacizumab and aflibercept, the proportions of cardiac AEs were 8.57%, 5.62%, 3.43% and 3.20%, respectively, and the proportions of central nervous AEs were 8.81%, 7.41, 5.86% and 5.68%, respectively. In multiple comparisons, ranibizumab was significantly higher than bevacizumab and aflibercept in the proportion of cardiac AEs (P < 0.001), and ranibizumab was significantly higher than aflibercept in central nervous AEs (P < 0.001). CONCLUSIONS: Our findings support the associations between anti-VEGF drugs and ocular AEs, cardiac AEs, and central nervous AEs. After intravitreal injection, attention should not only be paid to ocular symptoms, but also to systemic symptoms.
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Inhibidores de la Angiogénesis , Ranibizumab , Humanos , Ranibizumab/efectos adversos , Bevacizumab/efectos adversos , Inhibidores de la Angiogénesis/efectos adversos , Factor A de Crecimiento Endotelial Vascular , Receptores de Factores de Crecimiento Endotelial Vascular , Inyecciones Intravítreas , Proteínas Recombinantes de Fusión/efectos adversosRESUMEN
The long non-coding RNA MIR4435-2HG has been confirmed to play a crucial regulatory role in various types of tumors. As a novel type of non-coding RNA, MIR4435-2HG plays a key role in regulating the expression of tumor-related genes, interfering with cellular signaling pathways, and affecting tumor immune evasion. Its unique structure allows it to regulate the expression of various tumor-related genes through different pathways, participating in the regulation of tumor signaling pathways, such as regulating the expression of oncogenes and tumor suppressor genes, influencing the biological behaviors of proliferation, metastasis, and apoptosis in tumors. Numerous studies have found a high expression of MIR4435-2HG in various tumor tissues, closely related to the clinical pathological characteristics of tumors, such as staging, lymph node metastasis and prognosis. Some studies have discovered that MIR4435-2HG can regulate the sensitivity of tumor cells to chemotherapy drugs, affecting tumor cell drug resistance. This provides new insights into overcoming tumor drug resistance by regulating MIR4435-2HG. Therefore, studying its molecular mechanisms, expression regulation, and its relationship with the clinical features of tumors is of great significance for revealing the mechanisms of tumor occurrence and developing new therapeutic targets.
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In children after cardiac surgery, alterations in cognitive ability and behavior are increasingly common, but whether postoperative cognitive dysfunction (POCD) occurs in children undergoing noncardiac surgery is not known. The present study was performed to investigate the incidence rate and potential risk factors of early neurocognitive dysfunction in children after noncardiac surgery. Two hundred patients aged between 4 and 14 years old underwent elective noncardiac surgery and 100 healthy age-matched controls were enrolled in this prospective observational study. Wechsler Preschool and Primary Scale of Intelligence or Wechsler Intelligence Scale for Children-Revised were conducted 1 day before and 3 days after surgery. POCD was calculated and diagnosed as a combined Z score. Any factors that differed between POCD and non-POCD group (p < 0.10) were tested together by multivariate logistic regression analysis against the cognitive outcome of patients, to find out the independent risk factors of POCD. The general incidence of POCD was 15.6%. The univariate analysis revealed that POCD was associated with general anesthesia, surgical and anesthesia duration, early postoperative fever (EPF), and surgical history. However, only the history of surgery (p = 0.029), anesthesia duration (p = 0.010), and EPF (p < 0.001) were demonstrated to be independent risk factors for POCD. The occurrence rate of early POCD after noncardiac surgery in children is 15.6%. Children who had surgical history, longer anesthesia duration, or EPF are more prone to develop POCD.
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In this study, a high-precision rotation angle measurement method based on polarization self-mixing interference (SMI) is proposed. The higher signal-to-noise ratio SMI signal can be obtained by the differential processing of two polarized SMI signals with opposite phases. In order to reduce the influence of the speckle effect, the envelope signal is used to normalize the SMI signal. The fringe subdivision method is used to improve the accuracy of the rotation angle measurement. The experimental results show that the error of the rotation angle measurement is within ±0.5%, and the measurement range can reach up to 20°.
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Having a hypoxic microenvironment is a common and salient feature of most solid tumors. Hypoxia has a profound effect on the biological behavior and malignant phenotype of cancer cells, mediates the effects of cancer chemotherapy, radiotherapy, and immunotherapy through complex mechanisms, and is closely associated with poor prognosis in various cancer patients. Accumulating studies have demonstrated that through normalization of the tumor vasculature, nanoparticle carriers and biocarriers can effectively increase the oxygen concentration in the tumor microenvironment, improve drug delivery and the efficacy of radiotherapy. They also increase infiltration of innate and adaptive anti-tumor immune cells to enhance the efficacy of immunotherapy. Furthermore, drugs targeting key genes associated with hypoxia, including hypoxia tracers, hypoxia-activated prodrugs, and drugs targeting hypoxia-inducible factors and downstream targets, can be used for visualization and quantitative analysis of tumor hypoxia and antitumor activity. However, the relationship between hypoxia and cancer is an area of research that requires further exploration. Here, we investigated the potential factors in the development of hypoxia in cancer, changes in signaling pathways that occur in cancer cells to adapt to hypoxic environments, the mechanisms of hypoxia-induced cancer immune tolerance, chemotherapeutic tolerance, and enhanced radiation tolerance, as well as the insights and applications of hypoxia in cancer therapy.
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Neoplasias , Humanos , Hipoxia de la Célula/genética , Neoplasias/terapia , Neoplasias/tratamiento farmacológico , Hipoxia/genética , Inmunoterapia , Tolerancia a Radiación , Microambiente Tumoral/genéticaRESUMEN
Camera calibration is a key problem for 3D reconstruction in computer vision. Existing calibration methods, such as traditional, active, and self-calibration, all need to solve the internal and external parameters of the imaging system to clarify the image-object mapping relationship. The artificial neural network, which is based on connectionist architecture, provides a novel idea for the calibration of nonlinear mapping vision systems. It can learn the image-object mapping relationship from some sample points without considering too many uncertain factors in the middle. This paper discusses the learning ability. A binocular stereo-vision mapping model is used as the learning model to explore the ability of image-object mapping for artificial neural networks. This paper constructs sample libraries by pixel and world coordinates of checkerboard corners, builds the artificial neural network, and, through the training samples and test samples prediction, verifies the learning performance of the network. Furthermore, by the laser scanning binocular vision device constructed in the authors' laboratory and trained-well network, the 3D point cloud reconstruction of a physical target is performed. The experimental results show that the artificial neural network can learn the image-object mapping relationship well and more effectively avoid the impact of lens distortion and achieve more accurate nonlinear mapping at the edge of the image. When the X and Y coordinates are in the range of 100 mm and the Z coordinates are in the range of a 1000 mm, the absolute error rarely exceeds 2.5 mm, and the relative error is in the level of 10-3; for 1000 mm distance measurement, the standard deviation does not exceed 1.5 mm. Network parameter selection experiments show that, for image-object mapping, a three-layer network and increasing the number of hidden layer's nodes can improve the training time more significantly.
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Regulatory T cells (Tregs) are found to participate in the pathogenesis of cerebral ischemic stroke. Exosomes derived from Tregs (Treg-Exos) were found to mediate the mechanism of Tregs' roles under various physiological and pathological conditions. But the roles of Treg-Exos in cerebral ischemic stroke are still unclear. Here, we explored the protective effects of Treg-Exos against microglial injury in response to oxygen-glucose deprivation/reperfusion (OGD/R) exposure. The results showed that Tregs-Exos relieved OGD/R-caused increases in LDH release and caspase-3 activity in BV-2 cells. The decreased cell viability and increased percentage of TUNEL-positive cells in OGD/R-exposed BV-2 cells were attenuated by Tregs-Exos treatment. Tregs-Exos also suppressed OGD/R-induced increase in production of tumor necrosis factor (TNF)-α, interleukin (IL)-1ß, and IL-6 in BV-2 microglia. Furthermore, Tregs-Exos induced the expression levels of phosphorylated phosphatidylinositol-3-kinase (p-PI3K) and phosphorylated protein kinase B (p-Akt) in BV-2 microglia under the challenge of OGD/R. Inhibition of the PI3K/Akt signaling by LY294002 partly reversed the effects of Tregs-Exos on cell apoptosis and inflammation in OGD/R-exposed BV-2 microglia. These results indicated that Tregs-Exos exerted protective effects against the OGD/R-caused injury of BV-2 microglia by activating the PI3K/Akt signaling.
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Porcine deltacoronavirus (PDCoV) and porcine epidemic diarrhoea virus (PEDV) are the main porcine enteric coronaviruses that cause severe diarrhoea in piglets, posing huge threat to the swine industry. Our previous study verified that the co-infection of PDCoV and PEDV is common in natural swine infections and obviously enhances the disease severity in piglets. However, the effects of co-infection of PDCoV and PEDV on intestinal microbial community are unknown. In current study, the microbial composition and diversity in the colon of piglets were analyzed. Our results showed that both of PDCoV and PEDV were mainly distributed in the small intestines and caused severe damage of ileum but not colon in the co-inoculated piglets. Furthermore, we observed that PDCoV and PEDV co-infection alters the gut microbiota composition at the phylum, family and genus levels. The abundance of Mitsuokella and Collinsella at genus level were significantly increased in PDCoV-PEDV co-infection piglets. Spearman's correlation analysis further suggested that there existed strong positive correlation between Mitsuokella and TNF-α, IL-6 and IL-8 secretion, these two factors may together aggravating the small intestine pathological lesions. These results proved there existed obvious correlation between the disease severity caused by PDCoV-PEDV co-infection and intestinal microbial community.
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Coinfección , Infecciones por Coronavirus , Microbioma Gastrointestinal , Virus de la Diarrea Epidémica Porcina , Enfermedades de los Porcinos , Animales , Porcinos , Coinfección/veterinariaRESUMEN
Antibody-dependent enhancement (ADE) is an event in preexisting sub-, or non-neutralizing antibodies increasing the viral replication in its target cells. ADE is one crucial factor that intensifies porcine reproductive and respiratory syndrome virus (PRRSV) infection and results in PRRSV-persistent infection. Nevertheless, the exact mechanisms of PRRSV-ADE infection are poorly understood. In the current research, the results of the ADE assay showed that porcine immunoglobulin G (IgG) specific for the PRRSV significantly enhanced PRRSV proliferation in porcine alveolar macrophages (PAMs), suggesting that the ADE activity of PRRSV infection existed in pig anti-PRRSV IgG. The results of the RNA interference assay showed that knockdown of the Fc gamma receptor I (FcγRI) or FcγRIII gene significantly suppressed the ADE activity of PRRSV infection in PAMs, suggesting that FcγRI and FcγRIII were responsible for mediating PRRSV-ADE infection. In addition, the results of the antibody blocking assay showed that specific blocking of the Sn1, 2, 3, 4, 5, or 6 extracellular domain of the sialoadhesin (Sn) protein or selective blockade of the scavenger receptor cysteine-rich (SRCR) 5 domain of the CD163 molecule significantly repressed the ADE activity of PRRSV infection in PAMs, suggesting that Sn and CD163 were involved in FcγR-mediated PRRSV-ADE infection. The Sn1-6 domains of porcine Sn protein and the SRCR 5 domain of porcine CD163 molecule might play central roles in the ADE of PRRSV infection. In summary, our studies indicated that activating FcγRs (FcγRI and FcγRIII) and viral receptors (Sn and CD163) were required for ADE of PRRSV infection. Our findings provided a new insight into PRRSV infection that could be enhanced by FcγRs and PRRSV receptors-mediated PRRSV-antibody immune complexes (ICs), which would deepen our understanding of the mechanisms of PRRSV-persistent infection via the ADE pathway.
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Time-space four-dimensional motion target localization is a fundamental and challenging task in the field of intelligent driving, and an important part of achieving the upgrade in existing target localization technologies. In order to solve the problem of the lack of localization of moving targets in a spatio-temporal four-dimensional environment in the existing spatio-temporal data model, this paper proposes an optical imaging model in the four-dimensional time-space system and a mathematical model of the object-image point mapping relationship in the four-dimensional time-space system based on the central perspective projection model, combined with the one-dimensional "time" and three-dimensional "space". After adding the temporal dimension, the imaging system parameters are extended. In order to solve the nonlinear mapping problem of complex systems, this paper proposes to construct a time-space four-dimensional object-image mapping relationship model based on a BP artificial neural network and demonstrates the feasibility of the joint time-space four-dimensional imaging model theory. In addition, indoor time-space four-dimensional localization prediction experiments verify the performance of the model in this paper. The maximum relative error rates of the predicted motion depth values, time values, and velocity values of this localization method compared with the real values do not exceed 0.23%, 2.03%, and 1.51%, respectively.
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Algoritmos , Imagenología Tridimensional , Imagenología Tridimensional/métodos , Movimiento (Física) , Redes Neurales de la ComputaciónRESUMEN
Porcine deltacoronavirus (PDCoV) is a novel coronavirus that causes diarrhea in suckling piglets and has the potential for cross-species transmission, posing a threat to animal and human health. However, the susceptibility profile of different species of mice to PDCoV infection and its evolutionary characteristics are still unclear. In the current study, we found that BALB/c and Kunming mice are susceptible to PDCoV. Our results showed that there were obvious lesions in intestinal and lung tissues from the infected mice. PDCoV RNAs were detected in the lung, kidney, and intestinal tissues from the infected mice of both strains, and there existed wider tissue tropism in the PDCoV-infected BALB/c mice. The RNA and protein levels of aminopeptidase N from mice were relatively high in the kidney and intestinal tissues and obviously increased after PDCoV infection. The viral-specific IgG and neutralizing antibodies against PDCoV were detected in the serum of infected mice. An interesting finding was that two key amino acid mutations, D138H and Q641K, in the S protein were identified in the PDCoV-infected mice. The essential roles of these two mutations for PDCoV-adaptive evolution were confirmed by cryo-electron microscope structure model analysis. The evolutionary characteristics of PDCoV among Deltacoronaviruses (δ-CoVs) were further analyzed. δ-CoVs from multiple mammals are closely related based on the phylogenetic analysis. The codon usage analysis demonstrated that similar codon usage patterns were used by most of the mammalian δ-CoVs at the global codon, synonymous codon, and amino acid usage levels. These results may provide more insights into the evolution, host ranges, and cross-species potential of PDCoV.
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COVID-19 , Enfermedades de los Porcinos , Aminoácidos , Animales , Anticuerpos Neutralizantes , Antígenos CD13/genética , Antígenos CD13/metabolismo , Deltacoronavirus , Humanos , Inmunoglobulina G , Mamíferos/metabolismo , Ratones , Filogenia , ARN , PorcinosRESUMEN
BACKGROUND: It is challenging to predict the outcome of the pregnancy when fetal heart activity is detected in early pregnancy. However, an accurate prediction is of importance for obstetricians as it helps to provide appropriate consultancy and determine the frequency of ultrasound examinations. The purpose of this study was to investigate the role of the convolutional neural network (CNN) in the prediction of spontaneous miscarriage risk through the analysis of early ultrasound gestational sac images. METHODS: A total of 2196 ultrasound images from 1098 women with early singleton pregnancies of gestational age between 6 and 8 weeks were used for training a CNN for the prediction of the miscarriage in the retrospective study. The patients who had positive fetal cardiac activity on their first ultrasound but then experienced a miscarriage were enrolled. The control group was randomly selected in the same database from the fetuses confirmed to be normal during follow-up. Diagnostic performance of the algorithm was validated and tested in two separate test sets of 136 patients with 272 images, respectively. Performance in prediction of the miscarriage was compared between the CNN and the manual measurement of ultrasound characteristics in the prospective study. RESULTS: The accuracy of the predictive model was 80.32% and 78.1% in the retrospective and prospective study, respectively. The area under the receiver operating characteristic curve (AUC) for classification was 0.857 (95% confidence interval [CI], 0.793-0.922) in the retrospective study and 0.885 (95%CI, 0.846-0.925) in the prospective study, respectively. Correspondingly, the predictive power of the CNN was higher compared with manual ultrasound characteristics, for which the AUCs of the crown-rump length combined with fetal heart rate was 0.687 (95%CI, 0.587-0.775). CONCLUSIONS: The CNN model showed high accuracy for predicting miscarriage through the analysis of early pregnancy ultrasound images and achieved better performance than that of manual measurement.
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Aborto Espontáneo , Saco Gestacional , Aborto Espontáneo/diagnóstico por imagen , Estudios de Cohortes , Femenino , Saco Gestacional/diagnóstico por imagen , Humanos , Lactante , Redes Neurales de la Computación , Embarazo , Primer Trimestre del Embarazo , Estudios Prospectivos , Estudios Retrospectivos , Ultrasonografía Prenatal/métodosRESUMEN
Pancreatic cancer is one of the most common malignant tumors in the digestive system with a poor prognosis. Accordingly, better understanding of the molecular mechanisms and innovative therapies are warranted to improve the prognosis of this patient population. In addition to playing a crucial role in coagulation, platelets reportedly contribute to the growth, invasion and metastasis of various tumors, including pancreatic cancer. This narrative review brings together currently available evidence on the impact of platelets on pancreatic cancer, including the platelet-related molecular mechanisms of cancer promotion, pancreatic cancer fibrosis, immune evasion, drug resistance mechanisms, thrombosis, targeted platelet therapy, combined radiotherapy and chemotherapy treatment, platelet combined with nanotechnology treatment and potential applications of pancreatic cancer organoids. A refined understanding of the role of platelets in pancreatic cancer provides the foothold for identifying new therapeutic targets.