Nanoparticles targeting OPN loaded with BY1 inhibits vascular restenosis by inducing FTH1-dependent ferroptosis in vascular smooth muscle cells.

Vascular restenosis following angioplasty continues to pose a significant challenge. The heterocyclic trioxirane compound [1, 3, 5-tris((oxiran-2-yl)methyl)-1, 3, 5-triazinane-2, 4, 6-trione (TGIC)], known for its anticancer activity, was utilized as the parent ring to conjugate with a non-steroidal anti-inflammatory drug, resulting in the creation of the spliced conjugated compound BY1. We found that BY1 induced ferroptosis in VSMCs as well as in neointima hyperplasia. Furthermore, ferroptosis inducers amplified BY1-induced cell death, while inhibitors mitigated it, indicating the contribution of ferroptosis to BY1-induced cell death. Additionally, we established that ferritin heavy chain1 (FTH1) played a pivotal role in BY1-induced ferroptosis, as evidenced by the fact that FTH1 overexpression abrogated BY1-induced ferroptosis, while FTH1 knockdown exacerbated it. Further study found that BY1 induced ferroptosis by enhancing the NCOA4-FTH1 interaction and increasing the amount of intracellular ferrous. We compared the effectiveness of various administration routes for BY1, including BY1-coated balloons, hydrogel-based BY1 delivery, and nanoparticles targeting OPN loaded with BY1 (TOP@MPDA@BY1) for targeting proliferated VSMCs, for prevention and treatment of the restenosis. Our results indicated that TOP@MPDA@BY1 was the most effective among the three administration routes, positioning BY1 as a highly promising candidate for the development of drug-eluting stents or treatments for restenosis.

Developing Cardiac Digital Twins at Scale: Insights from Personalised Myocardial Conduction Velocity.

Large-cohort studies using cardiovascular imaging and diagnostic datasets have assessed cardiac anatomy, function, and outcomes, but typically do not reveal underlying biological mechanisms. Cardiac digital twins (CDTs) provide personalized physics- and physiology-constrained in-silico representations, enabling inference of multi-scale properties tied to these mechanisms. We constructed 3464 anatomically-accurate CDTs using cardiac magnetic resonance images from UK biobank and personalised their myocardial conduction velocities (CVs) from electrocardiograms (ECG), through an automated framework. We found well-known sex-specific differences in QRS duration were fully explained by myocardial anatomy, as CV remained consistent across sexes. Conversely, significant associations of CV with ageing and increased BMI suggest myocardial tissue remodelling. Novel associations were observed with left ventricular ejection fraction and mental-health phenotypes, through a phenome-wide association study, and CV was also linked with adverse clinical outcomes. Our study highlights the utility of population-based CDTs in assessing intersubject variability and uncovering strong links with mental health.

MRI Radiomics-Based Machine Learning Models for Ki67 Expression and Gleason Grade Group Prediction in Prostate Cancer.

PURPOSE: The Ki67 index and the Gleason grade group (GGG) are vital prognostic indicators of prostate cancer (PCa). This study investigated the value of biparametric magnetic resonance imaging (bpMRI) radiomics feature-based machine learning (ML) models in predicting the Ki67 index and GGG of PCa. METHODS: A total of 122 patients with pathologically proven PCa who had undergone preoperative MRI were retrospectively included. Radiomics features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) maps. Then, recursive feature elimination (RFE) was applied to remove redundant features. ML models for predicting Ki67 expression and GGG were constructed based on bpMRI and different algorithms, including logistic regression (LR), support vector machine (SVM), random forest (RF), and K-nearest neighbor (KNN). The performances of different models were evaluated with receiver operating characteristic (ROC) analysis. In addition, a joint analysis of Ki67 expression and GGG was performed by assessing their Spearman correlation and calculating the diagnostic accuracy for both indices. RESULTS: The ML model based on LR and ADC + T2 (LR_ADC + T2, AUC = 0.8882) performed best in predicting Ki67 expression, and ADC_wavelet-LHH_firstorder_Maximum had the highest feature weighting. The SVM_DWI + T2 (AUC = 0.9248) performed best in predicting GGG, and DWI_wavelet HLL_glcm_SumAverage had the highest feature weighting. The Ki67 and GGG exhibited a weak positive correlation (r = 0.382, p < 0.001), and LR_ADC + DWI had the highest diagnostic accuracy in predicting both (0.6230). CONCLUSION: The proposed ML models are suitable for predicting both Ki67 expression and GGG in PCa. This algorithm could be used to identify indolent or invasive PCa with a noninvasive, repeatable, and accurate diagnostic method.

Additional coils mitigate elevated defibrillation threshold in right-sided implantable cardioverter defibrillator generator placement: a simulation study.

AIMS: The standard implantable cardioverter defibrillator (ICD) generator (can) is placed in the left pectoral area; however, in certain circumstances, right-sided cans may be required which may increase defibrillation threshold (DFT) due to suboptimal shock vectors. We aim to quantitatively assess whether the potential increase in DFT of right-sided can configurations may be mitigated by alternate positioning of the right ventricular (RV) shocking coil or adding coils in the superior vena cava (SVC) and coronary sinus (CS). METHODS AND RESULTS: A cohort of CT-derived torso models was used to assess DFT of ICD configurations with right-sided cans and alternate positioning of RV shock coils. Efficacy changes with additional coils in the SVC and CS were evaluated. A right-sided can with an apical RV shock coil significantly increased DFT compared to a left-sided can [19.5 (16.4, 27.1) J vs. 13.3 (11.7, 19.9) J, P < 0.001]. Septal positioning of the RV coil led to a further DFT increase when using a right-sided can [26.7 (18.1, 36.1) J vs. 19.5 (16.4, 27.1) J, P < 0.001], but not a left-sided can [12.1 (8.1, 17.6) J vs. 13.3 (11.7, 19.9) J, P = 0.099). Defibrillation threshold of a right-sided can with apical or septal coil was reduced the most by adding both SVC and CS coils [19.5 (16.4, 27.1) J vs. 6.6 (3.9, 9.9) J, P < 0.001, and 26.7 (18.1, 36.1) J vs. 12.1 (5.7, 13.5) J, P < 0.001]. CONCLUSION: Right-sided, compared to left-sided, can positioning results in a 50% increase in DFT. For right-sided cans, apical shock coil positioning produces a lower DFT than septal positions. Elevated right-sided can DFTs may be mitigated by utilizing additional coils in SVC and CS.

Non-invasive localization of post-infarct ventricular tachycardia exit sites to guide ablation planning: a computational deep learning platform utilizing the 12-lead electrocardiogram and intracardiac electrograms from implanted devices.

AIMS: Existing strategies that identify post-infarct ventricular tachycardia (VT) ablation target either employ invasive electrophysiological (EP) mapping or non-invasive modalities utilizing the electrocardiogram (ECG). Their success relies on localizing sites critical to the maintenance of the clinical arrhythmia, not always recorded on the 12-lead ECG. Targeting the clinical VT by utilizing electrograms (EGM) recordings stored in implanted devices may aid ablation planning, enhancing safety and speed and potentially reducing the need of VT induction. In this context, we aim to develop a non-invasive computational-deep learning (DL) platform to localize VT exit sites from surface ECGs and implanted device intracardiac EGMs. METHODS AND RESULTS: A library of ECGs and EGMs from simulated paced beats and representative post-infarct VTs was generated across five torso models. Traces were used to train DL algorithms to localize VT sites of earliest systolic activation; first tested on simulated data and then on a clinically induced VT to show applicability of our platform in clinical settings. Localization performance was estimated via localization errors (LEs) against known VT exit sites from simulations or clinical ablation targets. Surface ECGs successfully localized post-infarct VTs from simulated data with mean LE = 9.61 ± 2.61 mm across torsos. VT localization was successfully achieved from implanted device intracardiac EGMs with mean LE = 13.10 ± 2.36 mm. Finally, the clinically induced VT localization was in agreement with the clinical ablation volume. CONCLUSION: The proposed framework may be utilized for direct localization of post-infarct VTs from surface ECGs and/or implanted device EGMs, or in conjunction with efficient, patient-specific modelling, enhancing safety and speed of ablation planning.

Optimization of anti-tachycardia pacing efficacy through scar-specific delivery and minimization of re-initiation: a virtual study on a cohort of infarcted porcine hearts.

AIMS: Anti-tachycardia pacing (ATP) is a reliable electrotherapy to painlessly terminate ventricular tachycardia (VT). However, ATP is often ineffective, particularly for fast VTs. The efficacy may be enhanced by optimized delivery closer to the re-entrant circuit driving the VT. This study aims to compare ATP efficacy for different delivery locations with respect to the re-entrant circuit, and further optimize ATP by minimizing failure through re-initiation. METHODS AND RESULTS: Seventy-three sustained VTs were induced in a cohort of seven infarcted porcine ventricular computational models, largely dominated by a single re-entrant pathway. The efficacy of burst ATP delivered from three locations proximal to the re-entrant circuit (septum) and three distal locations (lateral/posterior left ventricle) was compared. Re-initiation episodes were used to develop an algorithm utilizing correlations between successive sensed electrogram morphologies to automatically truncate ATP pulse delivery. Anti-tachycardia pacing was more efficacious at terminating slow compared with fast VTs (65 vs. 46%, P = 0.000039). A separate analysis of slow VTs showed that the efficacy was significantly higher when delivered from distal compared with proximal locations (distal 72%, proximal 59%), being reversed for fast VTs (distal 41%, proximal 51%). Application of our early termination detection algorithm (ETDA) accurately detected VT termination in 79% of re-initiated cases, improving the overall efficacy for proximal delivery with delivery inside the critical isthmus (CI) itself being overall most effective. CONCLUSION: Anti-tachycardia pacing delivery proximal to the re-entrant circuit is more effective at terminating fast VTs, but less so slow VTs, due to frequent re-initiation. Attenuating re-initiation, through ETDA, increases the efficacy of delivery within the CI for all VTs.

Podoplanin neutralization reduces thrombo-inflammation in experimental ischemic stroke by inhibiting interferon/caspase-1/GSDMD in microglia.

Background: Cerebral ischemia/reperfusion (I/R) injury involves the interaction between thrombosis and inflammatory pathways. The aim of this study was to explore the therapeutic effect of podoplanin neutralizing antibody (α-PDPN, clone 8.1.1) on I/R-induced thrombo-inflammation in a mouse model of ischemic stroke. Methods: Male C57BL/6 mice (weight: 22-25 g, aged 6-8 weeks, n=114) were subjected to transient middle cerebral artery occlusion (MCAO) and administered intracerebroventricular injection of α-PDPN (29 µg). Stroke outcomes and microvascular thromboses were examined by immunohistochemistry (IHC) and western blot analysis. In vitro, microglia BV2 cells were pre-treated with α-PDPN and then subjected to oxygen-glucose deprivation/reoxygenation (OGD/R) insult. The microglia culture medium (MCM) was co-cultured with vascular endothelial b.End3 cells. The MCM-induced bEnd.3 cells dysfunction were examined by western blot assays and IHC. Results: Blocking PDPN decreased the infarct size and ameliorated neurological deficit after MCAO without enhancing the risk of intracerebral hemorrhage. In addition, α-PDPN treatment significantly alleviated thrombus formation in the cerebral microvasculature. Furthermore, treatment with α-PDPN attenuated I/R-induced caspase-1 and gasdermin D expression in vivo and in vitro. The MCM containing α-PDPN reduced the expressions of von Willebrand factor and intercellular cell adhesion molecule-1 in bEnd.3 cells. Moreover, RNA sequencing analysis showed that α-PDPN decreased interferon signaling pathways in BV2 cells. Conclusions: Blocking PDPN can alleviate thrombo-inflammation in acute ischemic stroke by inhibiting caspase-1 expression in microglia, and indirectly reduce endothelial cell dysfunction. These data indicated the beneficial effects of blocking podoplanin during stroke in mice.

Regio-selective synthesis and activity research on 7-icaritin norcantharidin conjugates.

Due to complexity of tumor diseases and resistance of targeted drug, targeted drug usually cannot meet the needs of cancer treatment. Therefore, the conjugate constructed by two anticancer agents maybe a better solution for the tumor diseases. As natural anticancer agents, icaritin and norcantharidin are selected for the construction of conjugate. In the condition of EDCI/DMAP, icaritin is reacted with norcantharidin esters to give the desired 7-esters selectively in a moderate yield. MTT method was used to test the cytotoxicity and intensity on Hep G2 and MCF-7 in vitro. Some of the compounds (4a, 4i and 4j) show a better inhibition against Hep G2 and MCF-7 cell lines in vitro, and are deserved to be a potential drug candidate to develop in vivo.

Effect of Scalp Nerve Block Combined with Intercostal Nerve Block on the Quality of Recovery in Patients with Parkinson's Disease after Deep Brain Stimulation: Protocol for a Randomized Controlled Trial.

BACKGROUND: Parkinson's disease (PD) patients who receive deep brain stimulation (DBS) have a higher risk of postoperative pain, which will affect their postoperative quality of recovery (QoR). Scalp nerve block (SNB) and intercostal nerve block (ICNB) can alleviate postoperative pain, yet their effect on postoperative QoR in PD patients has proven to be unclear. Therefore, we have aimed to explore the effect of SNB paired with ICNB on postoperative QoR. METHODS: To explore the effect, we have designed a randomized controlled trial in which 88 patients with PD will be randomly assigned to either an SNB group or control group, receiving either SNB combined with ICNB or without before surgery. The primary outcome will be a 15-item QoR score at 24 h after surgery. The secondary outcomes will include: 15-item QoR scores at 72 h and 1 month after surgery; the numeric rating scale pain scores before discharge from the postanesthesia care unit (PACU) at 24 h, 72 h, and 1 month after surgery; rescue analgesics; nausea and vomiting 24 h after operation and remifentanil consumption during operation; emergence agitation; the duration of anesthesia and surgery; time to respiratory recovery, time to response, and time to extubation; the PACU length of stay; as well as adverse events. Proposed protocol and conclusion: Our findings will provide a novel method for the management of recovery and acute pain after DBS in PD patients. This research was registered at clinicaltrials.gov NCT05353764 on 19 April 2022.

Transcriptome sequencing analysis revealed the molecular mechanism of podoplanin neutralization inhibiting ischemia/reperfusion-induced microglial activation.

Background: Anti-podoplanin antibody (α-PDPN, clone 8.1.1) reduces microglia-mediated inflammation and decreases cerebral infarct volume in mice with stroke. However, the molecular mechanism by which this occurs is unknown. This study sought to systematically analyze the molecular mechanism of α-PDPN treatment on ischemia/reperfusion (I/R)-injured microglia. Methods: Microglia BV2 cells were pre-cultured with α-PDPN and then exposed to oxygen-glucose deprivation and reoxygenation (OGD-R) insult. The differentially expressed genes (DEGs) underwent a transcriptome sequencing technology analysis, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Quantitative real-time polymerase chain reaction (PCR) was performed to confirm the transcriptional expression of some DEGs. Results: The results showed that α-PDPN downregulated 338 genes and upregulated 340 genes in the BV2 cells. The GO items of the downregulated DEGs mainly involved biological processes, such as the response to the interferon (IFN), lipopolysaccharide-mediated signaling pathway, and the regulation of cell chemotaxis and migration. The upregulated molecular function mainly involved glucocorticoid-receptor binding. Further, the KEGG pathway analysis indicated that the enriched categories for the upregulated DEGs mainly involved the adenosine triphosphate (ATP) binding cassette transporters. However, the interleukin-17 signaling pathway, IFN signaling pathway, tumor necrosis factor signaling pathway, transforming growth factor beta (TGF-ꞵ) signaling pathway, nucleotide-binding and oligomerization domain (NOD)-like receptor signaling pathway, cytokine-cytokine receptor interaction, and chemokine signaling pathway were downregulated by the α-PDPN treatment. Conclusions: Numerous inflammation-related signaling pathways were regulated by the α-PDPN treatment in the OGD-R injured BV2 cells. This study provided further insights into the protective mechanism of α-PDPN treatment in ischemic stroke.

Radiomics-Based Machine Learning Models for Predicting P504s/P63 Immunohistochemical Expression: A Noninvasive Diagnostic Tool for Prostate Cancer.

Objective: To develop and validate a noninvasive radiomic-based machine learning (ML) model to identify P504s/P63 status and further achieve the diagnosis of prostate cancer (PCa). Methods: A retrospective dataset of patients with preoperative prostate MRI examination and P504s/P63 pathological immunohistochemical results between June 2016 and February 2021 was conducted. As indicated by P504s/P63 expression, the patients were divided into label 0 (atypical prostatic hyperplasia), label 1 (benign prostatic hyperplasia, BPH) and label 2 (PCa) groups. This study employed T2WI, DWI and ADC sequences to assess prostate diseases and manually segmented regions of interest (ROIs) with Artificial Intelligence Kit software for radiomics feature acquisition. Feature dimensionality reduction and selection were performed by using a mutual information algorithm. Based on screened features, P504s/P63 prediction models were established by random forest (RF), gradient boosting decision tree (GBDT), logistic regression (LR), adaptive boosting (AdaBoost) and k-nearest neighbor (KNN) algorithms. The performance was evaluated by the area under the ROC curve (AUC) and accuracy. Results: A total of 315 patients were enrolled. Among the 851 radiomic features, the 32 top features were derived from T2WI, in which the gray-level run length matrix (GLRLM) and gray-level cooccurrence matrix (GLCM) features accounted for the largest proportion. Among the five models, the RF algorithm performed best in general evaluations (microaverage AUC=0.920, macroaverage AUC=0.870) and provided the most accurate result in further sublabel prediction (the accuracies of label 0, 1, and 2 were 0.831, 0.831, and 0.932, respectively). In comparative sequence analyses, T2WI was the best single-sequence candidate (microaverage AUC=0.94 and macroaverage AUC=0.78). The merged datasets of T2WI, DWI, and ADC yielded optimal AUCs (microaverage AUC=0.930 and macroaverage AUC=0.900). Conclusions: The radiomic-based RF classifier has the potential to be used to evaluate the presurgical P504s/P63 status and further diagnose PCa noninvasively and accurately.

One-step algorithm for fast-track localization and multi-category classification of histological subtypes in lung cancer.

BACKGROUNDS: Accumulated evidence has proven that computer-derived features from computed tomography (CT) through radiomics and deep learning technologies can identify extensive characteristics of pulmonary malignancies, such as nodules detection and malignant lesion discrimination. However, there are few studies on whether CT images can reflect histological subtypes of lung cancer through computer-derived features. METHODS: Contrast-enhanced CT images prior treatment from 417 patients diagnosed with small cell lung cancer (SCLC), lung adenocarcinoma (ADC), or lung squamous cell carcinoma (SCC) were collected. ITK-SNAP software was used by trained radiologists for the manual delineation of tumor volume. Patients of each category (SCLC, ADC, SCC) were then randomly split into training datasets and test datasets in an approximately ratio of 8:2. After image pre-processing and augmentation, 25,042 CT images from the training datasets were used to train our self-developed deep learning model for fast-tracking tumor lesions and classifying corresponding histological subtypes simultaneously. The performance of the network was evaluated by accuracy, F1-score and weighted F1-average using 1,921 testing images based on parameters generated during training. RESULTS: The prediction accuracy of SCLC, ADC, and SCC were 0.83, 0.75 and 0.67, respectively. The weighted F1-average was 0.75. ADC obtained the best F1-score of 0.78, which was outperformed SCLC (0.77) and SCC (0.66). The corresponding AUC values of SCLC, ADC, and SCC were 0.87, 0.84, and 0.76, respectively. Only 0.24 s were required to simultaneously achieve functions of tumor localization and histological classification on a thoracic CT image slice. The heat map visualization illustrated the extracted tumor features to classify subtypes of lung cancer by the proposed model. CONCLUSIONS: The newly developed multi-task algorithm provides a CNN-based DL approach in lung cancer for automatically fast-tracking tumor lesions and classifying corresponding histological subtypes in one-step.

Interleukin-35 exhibits protective effects in a rat model of hypoxic-ischemic encephalopathy through the inhibition of microglia-mediated inflammation.

Background: Hypoxic-ischemic encephalopathy (HIE) brain damage is related to inflammatory responses and oxidative stress. Interleukin (IL)-35 is an antioxidant and anti-inflammatory cytokine. Thus, the effect of IL-35 treatment on neonatal rats with hypoxic-ischemic brain injury was investigated. Methods: A total of 96 7-day-old Sprague Dawley rats were randomly divided into three groups: sham group, HIE group, and IL-35 group. After left common carotid occlusion and 2.5 h hypoxia (HI injury), IL-35 (20 µg/g) was intraperitoneally (i.p.) administered to the pups. In vitro, BV2 cells were treated with or without IL-35 6 h before oxygen-glucose deprivation (OGD) insult and the microglia culture medium (MCM) was co-cultured with b.End3 cerebral vascular endothelial cells. Microglial polarization and activation were assessed by real-time quantitative polymerase chain reaction (RT-qPCR), Western blot, and enzyme-linked immunosorbent assay (ELISA). Endothelial cell dysfunction was measured by cell counting kit-8 and Western blot assays. Results: Administration of IL-35 alleviated neurological deficiencies, decreased brain edema, ameliorated cerebral infarction, and limited M1 microglial polarization in HI-injured pups. Meanwhile, IL-35 decreased pro-inflammatory cytokines, tumor necrosis factor-α, IL-1ß, and reactive oxygen species generation in OGD-induced bEnd.3 cells. Furthermore, IL-35 treatment could reverse the vascular endothelial cell injury induced by microglial polarization. Finally, IL-35 markedly suppressed the activation of hypoxia-inducible factor-1α (HIF-1α) and the nuclear factor-κB (NF-κB) signaling pathway in vivo and in vitro. Conclusions: IL-35 relieved hypoxic-ischemic-induced brain injury and inhibited the inflammatory response by suppressing microglial polarization and activation. These results suggest that IL-35 might have potential applications for the treatment of HIE.

An in-silico assessment of efficacy of two novel intra-cardiac electrode configurations versus traditional anti-tachycardia pacing therapy for terminating sustained ventricular tachycardia.

The implanted cardioverter defibrillator (ICD) is an effective direct therapy for the treatment of cardiac arrhythmias, including ventricular tachycardia (VT). Anti-tachycardia pacing (ATP) is often applied by the ICD as the first mode of therapy, but is often found to be ineffective, particularly for fast VTs. In such cases, strong, painful and damaging backup defibrillation shocks are applied by the device. Here, we propose two novel electrode configurations: "bipolar" and "transmural" which both combine the concept of targeted shock delivery with the advantage of reduced energy required for VT termination. We perform an in silico study to evaluate the efficacy of VT termination by applying one single (low-energy) monophasic shock from each novel configuration, comparing with conventional ATP therapy. Both bipolar and transmural configurations are able to achieve a higher efficacy (93% and 85%) than ATP (45%), with energy delivered similar to and two orders of magnitudes smaller than conventional ICD defibrillation shocks, respectively. Specifically, the transmural configuration (which applies the shock vector directly across the scar substrate sustaining the VT) is most efficient, requiring typically less than 1 J shock energy to achieve a high efficacy. The efficacy of both bipolar and transmural configurations are higher when applied to slow VTs (100% and 97%) compared to fast VTs (57% and 29%). Both novel electrode configurations introduced are able to improve electrotherapy efficacy while reducing the overall number of required therapies and need for strong backup shocks.

Computational fluid dynamics of the right atrium: Assessment of modelling criteria for the evaluation of dialysis catheters.

Central venous catheters are widely used in haemodialysis therapy, having to respect design requirements for appropriate performance. These are placed within the right atrium (RA); however, there is no prior computational study assessing different catheter designs while mimicking their native environment. Here, a computational fluid dynamics model of the RA, based on realistic geometry and transient physiological boundary conditions, was developed and validated. Symmetric, split and step catheter designs were virtually placed in the RA and their performance was evaluated by: assessing their interaction with the RA haemodynamic environment through prediction of flow vorticity and wall shear stress (WSS) magnitudes (1); and quantifying recirculation and tip shear stress (2). Haemodynamic predictions from our RA model showed good agreement with the literature. Catheter placement in the RA increased average vorticity, which could indicate alterations of normal blood flow, and altered WSS magnitudes and distribution, which could indicate changes in tissue mechanical properties. All designs had recirculation and elevated shear stress values, which can induce platelet activation and subsequently thrombosis. The symmetric design, however, had the lowest associated values (best performance), while step design catheters working in reverse mode were associated with worsened performance. Different tip placements also impacted on catheter performance. Our findings suggest that using a realistically anatomical RA model to study catheter performance and interaction with the haemodynamic environment is crucial, and that care needs to be given to correct tip placement within the RA for improved recirculation percentages and diminished shear stress values.

Impact of side-hole geometry on the performance of hemodialysis catheter tips: A computational fluid dynamics assessment.

Hemodialysis catheters are used to support blood filtration, yet there are multiple fundamentally different approaches to catheter tip design with no clear optimal solution. Side-holes have been shown to increase flow rates and decrease recirculation but have been associated with clotting/increased infection rates. This study investigates the impact of changing the shape, size and number of side-holes on a simple symmetric tip catheter by evaluating the velocity, shear stress and shear rate of inflowing blood. A platelet model is used to examine the residence time and shear history of inflowing platelets. The results show that side-holes improve the theoretical performance of the catheters, reducing the maximum velocity and shear stress occurring at the tip compared to non-side-hole catheters. Increasing the side-hole area improved performance up to a point, past which not all inflow through the hole was captured, and instead a small fraction slowly 'washed-out' through the remainder of the tip resulting in greater residence times and increasing the likelihood of platelet adhesion. An oval shaped hole presents a lower chance of external fibrin formation compared to a circular hole, although this would also be influenced by the catheter material surface topology which is dependent on the manufacturing process. Overall, whilst side-holes may be associated with increased clotting and infection, this can be reduced when side-hole geometry is correctly implemented though; a sufficient area for body diameter (minimising residence time) and utilising angle-cut, oval shaped holes (reducing shear stress and chances of fibrin formation partially occluding holes).

Finite element modelling of discontinuous action potential propagation in larval zebrafish and human cardiac tissue.

Recently the larval zebrafish has emerged as a model organism which is used to assist in the studies of human cardiac electrophysiology. Although they share many similar electrophysiological characteristics, it has been found that the conduction velocity (CV) of action potential (AP) propagation in larval zebrafish heart is up to two orders of magnitude smaller than in the adult mammalian heart. To address this difference, we have developed three dimensional discrete models of larval zebrafish ventricular fibres (LZVF) in order to simulate AP propagation, taking into account the cellular nature of the tissues and intercellular conduction via gap junctions. Since our ultimate goal is to simulate a whole larval zebrafish heart, we have used the phenomenological Fitzhugh Nagumo (FHN) equations to describe transmembrane currents, and manually adjusted the FHN parameters, to fit published AP shapes for larval zebrafish ventricular cells. This has the benefit of reduced computational load compared to approaches based on biophysical ion current models. We have created models for 48 and 72 h post fertilisation LZVF tissue using published AP and cell size data for zebrafish embryos and used mammalian values for passive electrical parameters. Using the gap junction resistivity per myocyte as an adjustable parameter, we were able to obtain CVs in both of our LZVF models which agree with experimental observations. In order to validate our approach, we have applied it to a human ventricular fibre (HVF) model similar in structure and parameters to other models of the mammalian heart, but adjusting the FHN parameters to fit published AP shapes for human ventricular cells. We find good agreement with the human models. The gap junction resistivities used in the LZVF models are significantly higher than in the HVF case and are consistent with a lower density of gap junctions connecting cells.

Associative attention networks for temporal relation extraction from electronic health records.

Temporal relations are crucial in constructing a timeline over the course of clinical care, which can help medical practitioners and researchers track the progression of diseases, treatments and adverse reactions over time. Due to the rapid adoption of Electronic Health Records (EHRs) and high cost of manual curation, using Natural Language Processing (NLP) to extract temporal relations automatically has become a promising approach. Typically temporal relation extraction is formulated as a classification problem for the instances of entity pairs, which relies on the information hidden in context. However, EHRs contain an overwhelming amount of entities and a large number of entity pairs gathering in the same context, making it difficult to distinguish instances and identify relevant contextual information for a specific entity pair. All these pose significant challenges towards temporal relation extraction while existing methods rarely pay attention to. In this work, we propose the associative attention networks to address these issues. Each instance is first carved into three segments according to the entity pair to obtain the differentiated representation initially. Then we devise the associative attention mechanism for a further distinction by emphasizing the relevant information, and meanwhile, for the reconstruction of association among segments as the final representation of the whole instance. In addition, position weights are utilized to enhance the performance. We validate the merit of our method on the widely used THYME corpus and achieve an average F1-score of 64.3% over three runs, which outperforms the state-of-the-art by 1.5%.

Contextual label sensitive gated network for biomedical event trigger extraction.

Biomedical events play a key role in improving biomedical research. Event trigger identification, extracting the words describing the event types, is a crucial and prerequisite step in the pipeline process of biomedical event extraction. There exist two main problems in previous methods: (1) The association among contextual trigger labels which can provide significant clues is ignored. (2)The weight between word embeddings and contextual features needs to be adjusted dynamically according to the trigger candidate. In this paper, we propose a novel contextual label sensitive gated network for biomedical event trigger extraction to solve the above two problems, which can mix the two parts dynamically and capture the contextual label clues automatically. Furthermore, we also introduce the dependency-based word embeddings to represent dependency-based semantic information as well as attention mechanism to get more focused representations. Experimental results show that our approach advances state-of-the-arts and achieves the best F1-score on the commonly used Multi-Level Event Extraction (MLEE) corpus.

Age influences the olfactory profiles of the migratory oriental armyworm mythimna separate at the molecular level.

BACKGROUND: The oriental armyworm Mythimna separata (Walk) is a serious migratory pest; however, studies on its olfactory response and its underlying molecular mechanism are limited. To gain insights to the olfactory mechanism of migration, olfactory genes were identified using antennal transcriptome analysis. The olfactory response and the expression of olfactory genes for 1-day and 5-day-old moths were respectively investigated by EAG and RT-qPCR analyses. RESULTS: Putative 126 olfactory genes were identified in M. separata, which included 43 ORs, 13 GRs, 16 IRs, 37 OBPs, 14 CSPs, and 3 SNMPs. RPKM values of IR75d and 10 ORs were larger than co-receptors IR25a and ORco, and the RPKM value of PR2 was larger than that of other ORs. Expression of GR1 (sweet receptor) was higher than that of other GRs. Several sex pheromones activated evident EAG responses where the responses of 5-day-old male moths to the sex pheromones were significantly greater than those of female and 1-day old male moths. In accordance with the EAG response, 11 pheromone genes, including 6 PRs and 5 PBPs were identified in M. separate, and the expression levels of 7 pheromone genes in 5-day-old moths were significantly higher than those of females and 1-day-old moths. PR2 and PBP2 might be used in identifying Z11-16: Ald, which is the main sex pheromone component of M. separata. EAG responses to 16 plant volatiles and the expression levels of 43 olfactory genes in 1-day-old moths were significantly greater than that observed in the 5-day-old moths. Heptanal, Z6-nonenal, and benzaldehyde might be very important floral volatiles for host searching and recognized by several olfactory genes with high expression. Some plant volatiles might be important to male moths because the EAG response to 16 plant volatiles and the expression of 43 olfactory genes were significantly larger in males than in females. CONCLUSIONS: The findings of the present study show the effect of adult age on olfactory responses and expression profile of olfactory genes in the migratory pest M. separate.