Activity

To overcome resulting conceptual and methodological challenges, we highlight the need for a contextualized mindfulness framework whereby acceptance enables the process of engaging with life’s challenges rather than avoiding them.Direct oral anticoagulants are widely used to treat and prevent thromboembolic disorders. With rising clinical application, monitoring concentrations of direct oral anticoagulants are necessary in certain clinical conditions. A rapid and sensitive ultra-performance liquid chromatography-tandem mass spectrometry method was developed for the simultaneous determination of dabigatran etexilate, dabigatran, rivaroxaban, edoxaban, and apixaban, in human plasma. Protein precipitation with methanol was performed for sample preparation. The direct oral anticoagulants and internal standards were separated under gradient conditions using a C18 column, at an analytical run time of 8 min. The mobile phase was composed of 0.1% (v/v) formic acid in water (solvent A) and 0.1% (v/v) formic acid in acetonitrile (solvent B) at a flow rate of 0.3 mL/min. Mass detection was performed in multiple reaction monitoring using positive ionization mode. The method was validated over a range of 1.0-500 ng/mL for dabigatran etexilate, 0.1-500 ng/mL for dabigatran, and 0.5-500 ng/mL for edoxaban, rivaroxaban, and apixaban. The method detection limits of five analytes were in the range of 0.05-0.5 ng/mL. The lower limits of quantification of five analytes ranged from 0.1 to 1 ng/mL. The linearity (r2 values) was higher than 0.997. The accuracy of the low, medium, and high quality control samples were between 85.9 and 114%, and intra- and inter-day precision were below 9.47%. This validated method was successfully used to determine the plasma concentrations of rivaroxaban in 32 patients, and of dabigatran etexilate and dabigatran in 1 patient.

Excessive activation of maternal systemic inflammation is one of the underlying causes of pathology during the disease course of preeclampsia (PE). The triggering receptor expressed on myeloid cells-1 (TREM-1) participates in the development and persistence of inflammation. We hypothesized that dysregulated TREM-1 may be involved in the pathogenesis of PE by promoting the secretion of trophoblastic pro-inflammatory cytokines that augment inflammation.

The localization of TREM-1 in placenta and the extravillous trophoblast cell line (TEV-1) was determined by immunohistochemical staining. The expression level of TREM-1 and pro-inflammatory cytokines in placentas were compared between normal pregnancies and PE. We used lipopolysaccharide (LPS) to simulate trophoblastic inflammation. TEV-1cells were transfected with TREM-1 plasmid and si-TREM-1 respectively, and then were incubated with LPS. The expression levels of pro-inflammatory cytokines and key molecules featured in nuclear transcription factor-kappaB (atory effects in the pathogenesis of PE.KRAS is mutated in approximately 25% of Non-small Cell Lung Cancer (NSCLC) patients and first specific inhibitors showed promising responses that may be improved by concurrent interference with downstream signaling pathways. Cell lines exhibiting KRAS mutations show specific sensitivities to modulators affecting glucose utilization, signal transduction and cell survival. Novel SOS1-directed inhibitors with a broader anticancer coverage such as BAY-293 and BI-3406 inhibit KRAS through the hindrance of SOS1-KRAS interactions. The aim of this study was to check the putative synergy of BAY-293 with modulators having revealed specific vulnerabilities of KRAS-mutated cell lines. The present investigation tested the cytotoxicity of BAY-293 combinations against a series of Osimertinib-resistant primary NSCLC cell lines using MTT tests and calculation of combination indices according to the Chou-Talalay method. The results show that BAY-293 synergizes with modulators of glucose metabolism, inhibitors of cellular proliferation, several chemotherapeutics and a range of diverse modulators, thus corroborating the chemosensitivities of cells expressing mutated KRAS. In conclusion, BAY-293 exerts cytotoxicity with a wide range of drugs against Osimertinib-resistant primary NSCLC cell lines. The administration of pan-KRAS inhibitors alone may be limited in vivo by toxicity to normal tissues but made feasible by its use as part of suitable drug combinations. This study shows that BAY-293 combinations are active against NSCLC cells not further amenable to mutated EGFR-directed targeted therapy and results likewise hold relevance for pancreatic and colon cancer.

Bomb blast injuries exerts a shearing force on the air-tissue interfaces, causing devastating ocular injury from the blast wave. Improvised explosive devices (IEDs) are usually placed at different heights from the ground to induce more severe injury through ground blast reinforcement (GBR). However, there is still a lack of knowledge of the role of GBR and IED height from the ground on ocular biomechanics, and how they can affect the intraocular pressure (IOP) in the eye. This study aimed to estimate the IOP due to frontal IED explosion at different heights from the ground using a fluid-structure interaction model with and without GBR effects.

A 2kg IED was placed within 5m of the victim at 5 different heights from the ground, including 0, 0.42, 0.85, 1.27, and 1.70m. Two different blast formulations were used to simulate the IED explosion (a) spherical airburst, with no amplification of the initial shock wave due to interaction with the ground-surface, and (b) hemispherical surface-burst, where the initi of GBR in ocular blast simulations.

When the role of GBR was ignored, the results showed similar patterns and magnitudes of stresses and deformations in the skull and eye regardless of the height of the IED from the ground, which was not the case when GBR was considered. The findings of this study suggest the critical role of GBR in ocular blast simulations.

The accurate prediction of blood glucose (BG) level is still a challenge for diabetes management. This is due to various factors such as diet, personal physiological characteristics, stress, and activities influence changes in BG level. To develop an accurate BG level predictive model, we propose a personalized model based on a convolutional neural network (CNN) with a fine-tuning strategy.

We utilized continuous glucose monitoring (CGM) datasets from 1052 professional CGM sessions and split them into three groups according to type 1, type 2, and gestational diabetes mellitus (T1DM, T2DM, and GDM, respectively). During the preprocessing, only CGM data points were utilized, and future BG levels of four different prediction horizons (PHs, 15, 30, 45, and 60min) were used as output. In training, we trained a general CNN and a multi-output random forest regressor using a hold-out method for each group. Next, we developed two personalized models (1) by fine-tuning the general CNN on partial sample points of earibute to the development of an accurate personalized model and the analysis for its predictions.

We demonstrated the efficacy of the fine-tuning method in a large number of CGM datasets and analyzed the four predictive patterns. this website Therefore, we believe that the proposed method will significantly contribute to the development of an accurate personalized model and the analysis for its predictions.

Fundus fluorescein angiography (FFA) technique is widely used in the examination of retinal diseases. In analysis of FFA sequential images, accurate vessel segmentation is a prerequisite for quantification of vascular morphology. Current vessel segmentation methods concentrate mainly on color fundus images and they are limited in processing FFA sequential images with varying background and vessels.

We proposed a multi-path cascaded U-net (MCU-net) architecture for vessel segmentation in FFA sequential images, which is capable of integrating vessel features from different image modes to improve segmentation accuracy. Firstly, two modes of synthetic FFA images that enhance details of small vessels and large vessels are prepared, and are then used together with the raw FFA image as inputs of the MCU-net. By fusion of vessel features from the three modes of FFA images, a vascular probability map is generated as output of MCU-net.

The proposed MCU-net was trained and tested on the public Duke dataset and our own dataset for FFA sequential images as well as on the DRIVE dataset for color fundus images. Results show that MCU-net outperforms current state-of-the-art methods in terms of F1-score, sensitivity and accuracy, and is able of reserving details such as thin vessels and vascular connections. It also shows good robustness in processing FFA images captured at different perfusion stages.

The proposed method can segment vessels from FFA sequential images with high accuracy and shows good robustness to FFA images in different perfusion stages. This method has potential applications in quantitative analysis of vascular morphology in FFA sequential images.

The proposed method can segment vessels from FFA sequential images with high accuracy and shows good robustness to FFA images in different perfusion stages. This method has potential applications in quantitative analysis of vascular morphology in FFA sequential images.Histopathologists make diagnostic decisions that are thought to be based on pattern recognition, likely informed by cue-based associations formed in memory, a process known as cue utilisation. Typically, the cases presented to the histopathologist have already been classified as ‘abnormal’ by clinical examination and/or other diagnostic tests. This results in a high disease prevalence, the potential for ‘abnormality priming’, and a response bias leading to false positives on normal cases. This study investigated whether higher cue utilisation is associated with a reduction in positive response bias in the diagnostic decisions of histopathologists. Data were collected from eighty-two histopathologists who completed a series of demographic and experience-related questions and the histopathology edition of the Expert Intensive Skills Evaluation 2.0 (EXPERTise 2.0) to establish behavioural indicators of context-related cue utilisation. They also completed a separate, diagnostic task comprising breast histopathology images where the frequency of abnormality was manipulated to create a high disease prevalence context for diagnostic decisions relating to normal tissue. Participants were assigned to higher or lower cue utilisation groups based on their performance on EXPERTise 2.0. When the effects of experience were controlled, higher cue utilisation was specifically associated with a greater accuracy classifying normal images, recording a lower positive response bias. This study suggests that cue utilisation may play a protective role against response biases in histopathology settings.Head Mounted Display (HMD) based Augmented Reality (AR) is being increasingly used in manufacturing and maintenance. However, limited research has been done to understand user interaction with AR interfaces, which may lead to poor usability, risk of occupational hazards, and low acceptance of AR systems. This paper uses a theoretically-driven approach to interaction design to investigate the impact of different AR modalities in terms of information mode (i.e. video vs. 3D animation) and interaction modality (i.e. hand-gesture vs. voice command) on user performance, workload, eye gaze behaviours, and usability during a maintenance assembly task. The results show that different information modes have distinct impacts compared to paper-based maintenance, in particular, 3D animation led to a 14% improvement over the video instructions in task completion time. Moreover, insights from eye gaze behaviours such as number of fixations and transition between Areas of Interest (AOIs) revealed the differences in attention switching and task comprehension difficulty with the choice of AR modalities.