Miracle-dz/UniFAR-FTUs huggingface dataset:
Endotoxin Tolerance in Abdominal Aortic Aneurysm Macrophages, In Vitro: A Case–Control Study

Macrophages are implicated in the pathogenesis of abdominal aortic aneurysm (AAA). This study examined the environmentally conditioned responses of AAA macrophages to inflammatory stimuli. Plasma- and blood-derived monocytes were separated from the whole blood of patients with AAA (30–45 mm diameter; n = 33) and sex-matched control participants (n = 44). Increased concentrations of pro-inflammatory and pro-oxidant biomarkers were detected in the plasma of AAA patients, consistent with systemic inflammation and oxidative stress. However, in monocyte-derived macrophages, a suppressed cytokine response was observed in AAA compared to the control following stimulation with lipopolysaccharide (LPS) (tumor necrosis factor alpha (TNF-α) 26.9 ± 3.3 vs. 15.5 ± 3.2 ng/mL, p < 0.05; IL-6 3.2 ± 0.6 vs. 1.4 ± 0.3 ng/mL, p < 0.01). LPS-stimulated production of 8-isoprostane, a biomarker of oxidative stress, was also markedly lower in AAA compared to control participants. These findings are consistent with developed tolerance in human AAA macrophages. As Toll-like receptor 4 (TLR4) has been implicated in tolerance, macrophages were examined for changes in TLR4 expression and distribution. Although TLR4 mRNA and protein expression were unaltered in AAA, cytosolic internalization of receptors and lipid rafts was found. These findings suggest the inflamed, pro-oxidant AAA microenvironment favors macrophages with an endotoxin-tolerant-like phenotype characterized by a diminished capacity to produce pro-inflammatory mediators that enhance the immune response.
Consistent Video Style Transfer via Relaxation and Regularization

In recent years, neural style transfer has attracted more and more attention, especially for image style transfer. However, temporally consistent style transfer for videos is still a challenging problem. Existing methods, either relying on a significant amount of video data with optical flows or using single-frame regularizers, fail to handle strong motions or complex variations, therefore have limited performance on real videos. In this article, we address the problem by jointly considering the intrinsic properties of stylization and temporal consistency. We first identify the cause of the conflict between style transfer and temporal consistency, and propose to reconcile this contradiction by relaxing the objective function, so as to make the stylization loss term more robust to motions. Through relaxation, style transfer is more robust to inter-frame variation without degrading the subjective effect. Then, we provide a novel formulation and understanding of temporal consistency. Based on the formulation, we analyze the drawbacks of existing training strategies and derive a new regularization. We show by experiments that the proposed regularization can better balance the spatial and temporal performance. Based on relaxation and regularization, we design a zero-shot video style transfer framework. Moreover, for better feature migration, we introduce a new module to dynamically adjust inter-channel distributions. Quantitative and qualitative results demonstrate the superiority of our method over state-of-the-art style transfer methods. Our project is publicly available at: https://daooshee.github. io/ReReVST/.
Applications of Genome-Wide Screening and Systems Biology Approaches in Drug Repositioning

Simple Summary Drug repurposing is an accelerated route for drug development and a promising approach for finding medications for orphan and common diseases. Here, we compiled databases that comprise both computationally- or experimentally-derived data, and categorized them based on quiddity and origin of data, further focusing on those that present high throughput omic data or drug screens. These databases were then contextualized with genome-wide screening methods such as CRISPR/Cas9 and RNA interference, as well as state of art systems biology approaches that enable systematic characterizations of multi-omic data to find new indications for approved drugs or those that reached the latest phases of clinical trials. Abstract Modern drug discovery through de novo drug discovery entails high financial costs, low success rates, and lengthy trial periods. Drug repositioning presents a suitable approach for overcoming these issues by re-evaluating biological targets and modes of action of approved drugs. Coupling high-throughput technologies with genome-wide essentiality screens, network analysis, genome-scale metabolic modeling, and machine learning techniques enables the proposal of new drug–target signatures and uncovers unanticipated modes of action for available drugs. Here, we discuss the current issues associated with drug repositioning in light of curated high-throughput multi-omic databases, genome-wide screening technologies, and their application in systems biology/medicine approaches.
Risk Assessment Using Risk Scores in Patients with Acute Coronary Syndrome

Risk scores are widely used in patients with acute coronary syndrome (ACS) prior to treatment decision-making at different points in time. At initial hospital presentation, risk scores are used to assess the risk for developing major adverse cardiac events (MACE) and can guide clinicians in either discharging the patients at low risk or swiftly admitting and treating the patients at high risk for MACE. During hospital admission, risk assessment is performed to estimate mortality, residual ischemic and bleeding risk to guide further in-hospital management (e.g., timing of coronary angiography) and post-discharge management (e.g., duration of dual antiplatelet therapy). In the months and years following ACS, long term risk can also be assessed to evaluate current treatment strategies (e.g., intensify or reduce pharmaceutical treatment options). As multiple risk scores have been developed over the last decades, this review summarizes the most relevant risk scores used in ACS patients.
Transcirculation Silk Vista Baby-assisted coiling in half-T configuration for the treatment of posterior communicating artery aneurysms associated with a fetal posterior circulation: An alternative flow diversion strategy

Flow diverter devices have become a routine first-line option for treatment of an increasing population of intracranial aneurysms at many neurovascular centers. Despite the promising results of flow diverter stents on anterior circulation, incomplete occlusion on the presence of fetal posterior circulation has been described on several reports. Here we describe a novel technical alternative to conventional flow diversion approach for this specific subgroup of aneurysms using the low-profile flow diverter, Silk Vista Baby. The device was selectively placed into the fetal type posterior cerebral artery in half-T configuration for the treatment of a posterior communicating aneurysm using a transcirculation approach through the anterior communicating artery. This represents a useful and effective technique and should be considered when encountering the above-described situation.
Biological batch normalisation: How intrinsic plasticity improves learning in deep neural networks

In this work, we present a local intrinsic rule that we developed, dubbed IP, inspired by the Infomax rule. Like Infomax, this rule works by controlling the gain and bias of a neuron to regulate its rate of fire. We discuss the biological plausibility of the IP rule and compare it to batch normalisation. We demonstrate that the IP rule improves learning in deep networks, and provides networks with considerable robustness to increases in synaptic learning rates. We also sample the error gradients during learning and show that the IP rule substantially increases the size of the gradients over the course of learning. This suggests that the IP rule solves the vanishing gradient problem. Supplementary analysis is provided to derive the equilibrium solutions that the neuronal gain and bias converge to using our IP rule. An analysis demonstrates that the IP rule results in neuronal information potential similar to that of Infomax, when tested on a fixed input distribution. We also show that batch normalisation also improves information potential, suggesting that this may be a cause for the efficacy of batch normalisation—an open problem at the time of this writing.
Disturbance-Aware Neuro-Optimal System Control Using Generative Adversarial Control Networks

Disturbance, which is generally unknown to the controller, is unavoidable in real-world systems and it may affect the expected system state and output. Existing control methods, like robust model predictive control, can produce robust solutions to maintain the system stability. However, these robust methods trade the solution optimality for stability. In this article, a method called generative adversarial control networks (GACNs) is proposed to train a controller via demonstrations of the optimal controller. By formulating the optimal control problem in the presence of disturbance, the controller trained by GACNs obtains neuro-optimal solutions without knowing the future disturbance and determines the objective function explicitly. A joint loss, composed of the adversarial loss and the least square loss, is designed to be used in the training of the generator. Experimental results on simulated systems with disturbance show that GACNs outperform other compared control methods.
Physical activity and gestational weight gain predict physiological and perceptual responses to exercise during pregnancy

Exercise is known to improve the health of the pregnant woman and her child. Studies that have evaluated physiological parameters during prenatal exercise have conflicting results. Better understanding of these physiological responses can modify exercise prescriptions, safety, and monitoring strategies. We examined the association between age, prepregnancy body mass index (BMI), gestational weight gain (GWG), and physical activity (PA) levels, factors that may influence a change in physiological (HR, VO2 responses) and perceptual (RPE) responses to acute exercise throughout pregnancy.
Systematic review of trauma system regionalization and implementation on outcomes in traumatic brain injury patients

ABSTRACT Background The number of trauma systems has increased dramatically within the United States over the past 40 years. The implementation of these systems has contributed to a decrease in mortality and improved outcomes in patients with trauma. Several studies have evaluated the effect of implementation of these systems on outcomes, but few studies examine the effects of such systems specifically on traumatic brain injury (TBI). Methods A systematic review of the literature was conducted according the guidelines for the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) to determine the effects of trauma system implementation and regionalization on mortality and other outcome measures in adult TBI. We sought to include both experimental and observational studies within the United States. Results From 1983 to 2015, nine studies were identified that adhered to the predefined inclusion and exclusion criteria representing six different geographic areas within the United States. All studies utilized a retrospective pre-post implementation methodology. A variety of mortality outcome measures were identified in the literature. Six of the nine studies demonstrated some benefit on various mortality metrics. Conclusion The existing literature on the effects of trauma system implementation or regionalization on outcomes in TBI is sparse but overall seems to convey an improvement in mortality.
In vitro production of entomopathogenic nematodes in different artificial media

Different plant and animal protein media were evaluated in vitro for production of 3 indigenous isolates of Steinernema carpocapsae, 2 isolates of S. bicornutum and one of Heterorhabditis indica. The flasks containing specific media with foam chips were inoculated with different isolates of Steinernema spp. , incubated at 24±1°C for 25 days. Of the 9 artificial media evaluated for mass multiplication of Steinernema spp. , 4 viz., Wout's medium, modified egg yolk, soyflour + cholesterol and modified dog biscuit, yielded highest number of IJs of 2 isolates of S. carpocapsae, one isolate of S. bicornutum (PDBC EN 2.1) and one of H. indica (PDBC EN6.71). Maximum yield of IJs of S. carpocapsae (PDBC EN 6.11 and 6.61) was observed on modified dog biscuit, while S. bicornutum (PDBC EN 2.1) recorded maximum yield of IJs on modified egg yolk medium. H. indica (PDBC EN 6.71) recorded maximum yield of IJs on Wout's medium. The isolates of S. bicornutum (PDBC EN 3.1 and 3.2) did not multiply on any of the 9 media tried suggesting further improvement of the tested media.
Social Support and Well-Being of Chinese Special Education Teachers—An Emotional Labor Perspective

Due to their high expectations, teachers often hide their real emotions and play a role that conforms to public expectations of educational work. Special education teachers face a group of students with physical and mental disabilities who have high heterogeneity and require individualized services every day. Using social support theory, this study discusses special education teachers’ emotional labor and well-being. A total of 439 special education teachers in China participated in this study. We collected data at two different time-points and verified the research hypotheses with hierarchical regression and structural equation modeling analysis. The research findings show the mediating role of emotional labor in social support and well-being. It is, therefore, suggested that schools should pay more attention to special education teachers’ mental health and provide them with regular guidance and support.
Risk Factors of Overweight and Obesity Related to Diet and Disordered Eating Attitudes in Adolescent Girls with Clinical Features of Polycystic Ovary Syndrome

Background: We aimed to find the difference between girls with clinical features of Polycystic ovary syndrome (PCOS), divided into two groups: Overweight/obesity (Ov/Ob) and normal weight (N), related to diet, disordered eating attitudes (DEA), metabolic and hormonal differences, and to identify the risk factors of being overweight or obese. Methods: Seventy-eight adolescents with PCOS, aged 14–18 years, were divided into Ov/Ob and N groups. Patients underwent blood tests for determination of follicle-stimulating hormone (FSH), luteinizing hormone (LH), total testosterone, DHEA-S, estradiol, of sex hormone-binding globulin (SHBG), fasting glucose, insulin, Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), and lipid profile. Nutrition was evaluated using a 3-day food record. To examine the level of DEA, the Eating Attitudes Test-26 (EAT-26) was used. We defined an EAT-26 score ≥20 as positive for DEA. Logistic regression was carried out to identify the independent predictors of being overweight and obese. Results: An increase of 10 g in plant protein intake decreased the probability of being overweight and of obesity (OR = 0.54; p = 0.036). EAT-26 score ≥20 was correlated with a 7-fold (OR = 6.88; p = 0.02) increased odds of being overweight or of obesity. Conclusion: Being overweight and obesity in adolescents with PCOS may be associated with DEA and the type and amount of protein intake.
Bio-Guided Fractionation Driven by In Vitro α-Amylase Inhibition Assays of Essential Oils Bearing Specialized Metabolites with Potential Hypoglycemic Activity

Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by unpaired blood glycaemia maintenance. T2DM can be treated by inhibiting carbohydrate hydrolyzing enzymes (α-amylases and α-glucosidases) to decrease postprandial hyperglycemia. Acarbose and voglibose are inhibitors used in clinical practice. However, these drugs are associated with unpleasant gastrointestinal side effects. This study explores new α-amylase inhibitors deriving from plant volatile specialized metabolites. Sixty-two essential oils (EOs) from different plant species and botanical families were subjected to α-amylase in vitro enzymatic assay and chemically characterized using gas chromatography coupled to mass spectrometry. Several EOs were found to be potential α-amylase inhibitors, and Eucalyptus radiata, Laurus nobilis, and Myristica fragrans EOs displayed inhibitory capacities comparable to that of the positive control (i.e., acarbose). A bio-guided fractionation approach was adopted to isolate and identify the active fractions/compounds of Eucalyptus radiata and Myristica fragrans EOs. The bio-guided fractionation revealed that EOs α-amylase inhibitory activity is often the result of antagonist, additive, or synergistic interactions among their bioactive constituents and led to the identification of 1,8-cineole, 4-terpineol, α-terpineol, α-pinene, and β-pinene as bioactive compounds, also confirmed when they were tested singularly. These results demonstrate that EO oils are a promising source of potential α-amylase inhibitors.
Immunomagnetic Capture and Multiplexed Surface Marker Detection of Circulating Tumor Cells with Magnetic Multicolor Surface Enhanced Raman Scattering Nanotags.

Circulating tumor cells (CTCs) have substantial clinical implications in cancer diagnostics and monitoring. Although significant progress has been made in developing technologies for CTC detection and counting, the ability to quantitatively detect multiple surface protein markers on individual tumor cells remains very limited. In this work, we report a multiplexed method that uses magnetic multicolor surface enhanced Raman scattering (SERS) nanotags in conjunction with a chip-based immunomagnetic separation to quantitatively and simultaneously detect four surface protein markers on individual tumor cells in whole blood. Four-color SERS nanotags were prepared using magnetic-optical iron oxide-gold core-shell nanoparticles with different Raman reporters to recognize four different cancer markers with respective antibodies. A microfluidic device was fabricated to magnetically capture the nanoparticle-bound tumor cells and to perform on-line negative staining and single cell optical detection. The level of each targeted protein was obtained by signal deconvolution of the mixed SERS signals from individual tumor cells with classic least square regression. The method was tested with spiked tumor cells in human whole blood with three different breast cancer cell lines and compared with the results with purified cancer cells suspended in phosphate buffer solution. The method, with either spiked cancer cells in blood or purified cancer cells, showed a strong correlation with purified cancer cells by enzyme-linked immunosorbent assay (ELISA), suggesting the potential of our method for reliable detection of multiple surface markers on CTCs. Combining immunomagnetic enrichment with high specificity, multiplexed targeting for capture of CTC subpopulations, multicolor SERS detection with high sensitivity and specificity, microfluidics for handling rare cells and magnetic-plasmonic nanoparticles for dual enrichment and detection, our method provides an integrated yet simple and efficient platform that has the potential to more sensitively detect and monitor cancer metastasis.
Learning Perceptual Aesthetics of 3-D Shapes From Multiple Views

The quantification of 3-D shape aesthetics has so far focused on specific shape features and manually defined criteria such as the curvature and the rule of thirds. In this article, we built a model of 3-D shape aesthetics directly from human aesthetics preference data and show it to be well aligned with human perception of aesthetics. To build this model, we first crowdsource a large number of human aesthetics preferences by showing shapes in pairs in an online study and then use the same to build a 3-D shape multiview-based deep neural network architecture to allow us to learn a measure of 3-D shape aesthetics. In comparison to previous approaches, we do not use any predefined notions of aesthetics to build our model. Our algorithmically computed measure of shape aesthetics is beneficial to a range of applications in graphics such as search, visualization, and scene composition.
The Effects of Flavonoids in Cardiovascular Diseases

Flavonoids are metabolites of plants and fungus. Flavonoid research has been paid special attention to in recent times after the observation of their beneficial effects on the cardiovascular system. These favorable effects are exerted by flavonoids mainly due to their antioxidant properties, which result from the ability to decrease the oxidation of low-density lipoproteins, thus improving the lipid profiles. The other positive effect exerted on the cardiovascular system is the ability of flavonoids to produce vasodilation and regulate the apoptotic processes in the endothelium. Researchers suggested that these effects, including their anti-inflammatory function, are consequences of flavonoids’ potent antioxidant properties, but recent studies have shown multiple signaling pathways linked to them, thus suggesting that there are more mechanisms involved in the beneficial effect of the flavonoids on the human body. This review aims to present the latest data on the classification of these substances, their main mechanisms of action in the human body, and the beneficial effects on the physiological and pathological status of the cardiovascular system.
Practice Patterns and Outcomes of Online Hemodiafiltration: A Real-World Evidence Study in a Russian Dialysis Network

Background: Evidence suggests that online hemodiafiltration (OL-HDF) is associated with improved survival. Whether the dose-response relationship between convective volume and mortality may be confounded by selection bias or descends from practice patterns is not clear. We sought to evaluate the role of patients’ characteristics and practice patterns on OL-HDF dose and mortality in a large private dialysis network in the Republic of Russia. Methods: In this multicenter, historical cohort study, we included adult incident patients on OL-HDF with at least 90 days of survival on renal replacement therapy in centers belonging to the Russian Federation Fresenius Medical Care network (January 1, 2011, to December 31, 2016). We evaluated predictors and outcomes (survival) of substitution volume target achievement (Qsub > 21 L/session). Results: Among 1,081 enrolled patients, the average Qsub was 22.9 (±3.2) L/session; the mean ultrafiltration volume was 1.6 (±0.8) L/session. The mean age was 55.8 ± 13.2; 42% were woman. Most common comorbidities were congestive heart failure (39.7%) and peripheral vascular disease (21.7%). The average hemoglobin was 9.3 ± 1.3. The case-mix adjusted center effect accounted for 20% of variance in Qsub. The top 10 most important variables associated with higher Qsub were effective Qb, serum protein, Charlson’s comorbidity index, hemoglobin, year of dialysis initiation (proxy of high Qsub treatment policy in the clinic network), predialysis heart rate, serum bicarbonate, serum phosphate, age, serum sodium, and dry body weight. In addition, we found that the association of Qb with Qsub is moderated by year of enrollment, intradialytic weight gain, and coronary artery disease, whereas higher hemoglobin concentration moderated the relationship between treatment time and Qsub. Finally, Qsub between 21 and 25 L/session was associated with longer 5-year survival. Conclusions: Both center-dependent clinical practice standards and patient clinical conditions substantially contributed to the risk of low Qsub. We confirmed previous evidence indicating better survival among patients with Qsub ≥ 21 L/session.