17 research outputs found

    Magnetic resonance imaging of the supra-cervical fetal membrane detects an increased risk of prelabor rupture of membranes

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    OBJECTIVE: In 10% of term deliveries and 40% of preterm deliveries, the fetal membrane (FM) ruptures before labor. However, the ability to predict these cases of premature rupture of membranes (PROM) and preterm premature rupture of membranes (PPROM) is very limited. In this paper, our objective was to determine whether a prediction method based on T2 weighted magnetic resonance imaging (MRI) of the supra-cervical FM could predict PROM and PPROM. METHODS: This prospective cohort study enrolled 77 women between the 28th and 37th weeks of gestation. Two indicators of fetal membrane defects, including prolapsed depth \u3e5 mm and signal abnormalities, are investigated for our prediction. Fisher\u27s exact test was used to determine whether prolapsed depth \u3e5 mm and/or signal abnormalities were associated with PROM and PPROM. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated for prolapsed depth \u3e5 mm, signal abnormalities, and the combination of prolapsed depth \u3e5 mm and signal abnormalities. RESULT: Among 12 women with PROM (5 preterm and 7 term, prior to labor onset), 9 had membrane prolapse \u3e5 mm and 5 had FM signal abnormalities. Among 65 women with rupture of membranes at term, 2 had membrane prolapse \u3e5 mm and 1 had signal abnormalities. By Fisher\u27s exact test both indicators, membrane prolapse \u3e5 mm and signal abnormalities, were associated with PROM (P\u3c0.001, P\u3c0.001) and PPROM (P=0.001, P\u3c0.001). Additionally, membrane prolapse \u3e5 mm, signal abnormalities, and the combination of the two indicators all demonstrated high specificity for predicting PROM (96.9%, 98.5%, and 100%, respectively) and PPROM (90.3%, 97.2%, and 100%, respectively). CONCLUSION: MRI can distinguish the supra-cervical fetal membran

    In vivo assessment of supra-cervical fetal membrane by MRI 3D CISS: A preliminary study

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    In approximately 8% of term births and 33% of pre-term births, the fetal membrane (FM) ruptures before delivery

    Screening and characterization of the scFv for chimeric antigen receptor T cells targeting CEA-positive carcinoma

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    IntroductionChimeric antigen receptor T (CAR-T) cell therapy presents a promising treatment option for various cancers, including solid tumors. Carcinoembryonic antigen (CEA) is an attractive target due to its high expression in many tumors, particularly gastrointestinal cancers, while limited expression in normal adult tissues. In our previous clinical study, we reported a 70% disease control rate with no severe side effects using a humanized CEA-targeting CAR-T cell. However, the selection of the appropriate single-chain variable fragment (scFv) significantly affects the therapeutic efficacy of CAR-T cells by defining their specific behavior towards the target antigen. Therefore, this study aimed to identify the optimal scFv and investigate its biological functions to further optimize the therapeutic potential of CAR-T cells targeting CEA-positive carcinoma.MethodsWe screened four reported humanized or fully human anti-CEA antibodies (M5A, hMN-14, BW431/26, and C2-45), and inserted them into a 3rd-generation CAR structure. We purified the scFvs and measured the affinity. We monitored CAR-T cell phenotype and scFv binding stability to CEA antigen through flow cytometry. We performed repeated CEA antigen stimulation assays to compare the proliferation potential and response of the four CAR-T cells, then further evaluated the anti-tumor efficacy of CAR-T cells ex vivo and in vivo.ResultsM5A and hMN-14 CARs displayed higher affinity and more stable CEA binding ability than BW431/26 and C2-45 CARs. During CAR-T cell production culture, hMN-14 CAR-T cells exhibit a larger proportion of memory-like T cells, while M5A CAR-T cells showed a more differentiated phenotype, suggesting a greater tonic signal of M5A scFv. M5A, hMN-14, and BW431/26 CAR-T cells exhibited effective tumor cell lysis and IFN-γ release when cocultured with CEA-positive tumor cells in vitro, correlating with the abundance of CEA expression in target cells. While C2-45 resulted in almost no tumor lysis or IFN-γ release. In a repeat CEA antigen stimulation assay, M5A showed the best cell proliferation and cytokine secretion levels. In a mouse xenograft model, M5A CAR-T cells displayed better antitumor efficacy without preconditioning.DiscussionOur findings suggest that scFvs derived from different antibodies have distinctive characteristics, and stable expression and appropriate affinity are critical for robust antitumor efficacy. This study highlights the importance of selecting an optimal scFv in CAR-T cell design for effective CEA-targeted therapy. The identified optimal scFv, M5A, could be potentially applied in future clinical trials of CAR-T cell therapy targeting CEA-positive carcinoma

    Design Method and Finite Element Analysis of a New Prefabricated Steel Special-shaped Lattice Column

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    A new steel special-shaped lattice column (SSLC) was proposed, which can be used in prefabricated steel structure residence. The finite element models of four SSLC with different cross-section (L-shaped, T1-shaped, T2-shaped and X-shaped) were established under cyclic loading by using ABAQUS, in which the strength, lateral resist capacity and hysteretic behavior were analyzed. The results indicate that SSLC has adequate strength, stiffness and safety redundancy. Among the four SSLC, the SSLC with X-shaped has the best structural performance and seismic behavior

    Characterization of the Relationship of CDKL5 with MeCP2 and Dnmt1 in PrimaryRat Cortical Neurons

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    ABSTRACT Cyclin-dependent kinase-like 5 (CDKL5) is a protein kinase that is homologous to mitogen-activated protein kinases (MAPKs) and cyclin-dependent kinases (CDKs). Mutations in the CDKL5 gene cause X-linked infantile spasms and phenotypes that overlap with that of Rett syndrome, which is a neurodevelopmental disorder caused primarily by mutations in the methyl CpG binding protein 2 gene (MECP2). Previous studies in transfected cell lines showed that CDKL5 interacts with MeCP2 and DNA (cytosine-5)-methyltransferase 1 (Dnmt1). However, little is known about the relationships of CDKL5 with interacting proteins in primary neuronal cultures. In this study, we investigated the expression patterns of CDKL5, MeCP2 and Dnmt1, and their interaction in cultured rat cortical neurons. Using real-time PCR analysis, we found that CDKL5, MeCP2 and Dnmt1 have similar expression patterns at the mRNA level. In contrast, the expression patterns of those proteins at the protein level are different and could be inversely correlated, as shown by western blotting. Using co-immunoprecipitation, we further demonstrated that CDKL5 interacts with MeCP2 and Dnmt1 in primary rat cortical neurons. These data suggest that a functional link exists among CDKL5, MeCP2 and Dnmt1 during neuronal development and may provide further insight into the pathogenesis of Rett syndrome

    Functional Characterization of 9-/13-LOXs in Rice and Silencing Their Expressions to Improve Grain Qualities

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    Lipoxygenases (LOXs) are involved in oxidative rancidity and render rice unsuitable for human consumption. Here, RNA interference- (RNAi-) induced gene expression inhibition was used to analyze the functions of the bran/seed-specific LOXs in rice. r9-LOX1 and L-2 (9-LOX category) were the candidate genes expressing a bran/seed-specific LOX, while RCI-1 was (13-LOX category) a plastid-specific LOX. Real-time PCR showed that three LOXs were cultivar/tissue specific expression on a certain level. r9-LOX1 and L-2 were generally much higher in active bran/seed than in stabilized bran, mature seed, and regenerated plant. RCI-1 was barely expressed in seed. In transgenic lines, r9-LOX1, as well as L-2, expression was dramatically downregulated, compared to the nontransgenic controls. SPME/GC-MS analysis of r9-LOX1 RNAi transgenic lines showed 74.33% decrease in nonanal content (formed during oxidation of linoleic acid by lipoxygenase), but 388.24% increase in acetic acid and 184.84% hexanal (direct products of 13-LOX). These results indicate that r9-LOX1 positively regulates the amount of nonanal but negatively regulates acetic acid and hexanal. The negative regulation may be due to a mechanism of negative feedback between LOX family members. The information will help comprehensively understand the function of the bran/seed-specific LOXs, r9-LOX1, and improve the storage quality in the future

    Anti-occlusion multi-object surveillance based on improved deep learning approach and multi-feature enhancement for unmanned smart grid safety

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    Unattended substations are the basis of intelligent substations, which require remote surveillance and control. Limited by the number of visual sensors, remote manual monitoring is incomplete and inefficient. Onsite workers and intruders are easily hidden by the smart grid facility, which affects the safety surveillance of personnel and equipment. The traditional kernelized correlation filter (KCF) method has a poor ability to adapt to the practical environment. This paper presents an anti-occlusion framework on the basis of imaging techniques to solve the problem of optimized surveillance. The novelty is further strengthened by its more practical Deep Learning model and tracking methods. Firstly, a multi-feature fusion model of the HOG feature and color feature is proposed to enhance target characteristics as the target is severely blocked. Secondly, a target classifier training and fast detection method based on improved CNN is introduced. Lastly, to overcome the drawbacks of the KCF tracking algorithm, such as its inability to scale adaptive and blind updates, a new adaptive learning rate strategy is proposed for occlusion tracking. The effects on the OTB-2013 dataset demonstrate that the improved technique has better accuracy and robustness when compared to KCF methods

    Multi-objective tracking for smart substation onsite surveillance based on YOLO Approach and AKCF

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    The onsite surveillance plays an important role in the smart substation since the smart substation is unattended. All the sites and operation staff should be supervised throughout the process since a series of risks exist on the working sites. KCF (Kernel Correlation Filter) is an effective method to track a moving object for safety surveillance. However, the occlusion and shape changes worsen the performance of KCF, especially on the occasion of multi-objective detection. This paper proposes a comprehensive method for improving the precision and robustness of detection. Firstly, all the moving objects are detected by the YOLO method. In the tracking part, an AKCF (Augmented Kernel Correlation Filter) is proposed for the heavily occluded object, and the Kalman Filter (KF) serves as a supplementary output. Moreover, in the target association section, based on priority matching and rematching based on motion estimation, a two-stage target association method is proposed. Test outcomes indicate that the proposed algorithm is accurate and robust for tracking workers’ trajectories and conducting surveillance
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