Miracle-dz/UniFAR-FTUs huggingface dataset:
SM22α cell specific HIF stabilization mitigates hyperoxia-induced neonatal lung injury.

In premature infants the incidence of chronic lung disease of infancy, or bronchopulmonary dysplasia (BPD), remains high. Histologically BPD is characterized by larger and fewer alveoli. Hypoxia-inducible factors (HIF) play a role in alveolarization, but cell specific effects of HIF expression in neonatal lung injury remain unknown. Thus, we sought to determine whether HIF stabilization in SM22α expressing cells mitigates hyperoxia-induced neonatal lung injury. We crossed SM22α-promotor-driven Cre recombinase mice with prolyl hydroxylase (PHD) PHD1flox/flox and PHD2flox/flox mice. Neonatal mice were randomized to 21% O2 (normoxia) or 80% O2 (hyperoxia) exposure for 14 days, with longer term studies (hyperoxia recovery) performed on mice recovered in normoxia for 10 weeks. SM22α-specific HIF stabilization mitigated hyperoxia-induced lung injury and preserved microvessel density compared to control mice. In SM22α-PHD1/2-/- mice, pulmonary artery endothelial cells (PAEC) were more proliferative and pulmonary arteries expressed more collagen IV compared to control mice. Angiopoietin-2 (Ang2) mRNA expression in pulmonary artery smooth muscle cells (PASMC) was greater in SM22α-PHD1/2-/- compared to control mice. Co-culture of PEC with PASMC isolated from SM22α-PHD1/2-/- mice increased angiogenesis compared to PEC co-cultured with control PASMC. Cell-specific deletion of PHD 1 and 2 selectively increases HIF-1α expression in SM22α expressing cells and protects neonatal lung development despite prolonged hyperoxia exposure. HIF stabilization in SM22α expressing cells preserved endothelial cell proliferation, microvascular density, increased angiopoetin-2 expression, and lung structure, suggesting a role for cell-specific HIF-1α stabilization to prevent neonatal lung injury.
The satisfaction is mine: revenge seeking following extrinsic reward

ABSTRACT The extrinsic reward should impede revenge-seeking if revenge is solely driven by the desire to feel gratified. Study 1 (N = 114) showed that satisfaction from receiving monetary compensation decreased thinking about getting back at the provocateur. However, Study 2 (N = 213) found that insulted participants aggressed against their partners despite fulfillment from receiving the unexpected monetary reward. This evidence indicates that gratification is insufficient to impede revenge following provocation, suggesting that avengers want to feel pleasure when retaliating and want to balance the scales by sending offenders a message.
Fake news, real risks: How online discussion and sources of fact‐check influence public risk perceptions toward nuclear energy

This study seeks to understand how online discussion, fact‐checking, and sources of fact‐checks will influence individuals’ risk perceptions toward nuclear energy when they are exposed to fake news. Using a 2 × 3 experimental design, 320 participants were randomly assigned to one of the six experimental conditions. Results showed an interaction effect between online discussion and exposure to fact‐checking, in which online discussion lowered individuals’ risk perception toward nuclear energy when a fact‐check was unavailable. Of those who participated in the online discussion, those who viewed a fact‐check posted by traditional media have higher risk perception as compared to those who viewed a fact‐check posted by a fact‐check organization. Our findings indicate that different fact‐checking sources can have differential effects on public risk perceptions, depending on whether online discussion is involved. To curb the spread of fake news, different fact‐checking strategies will need to be deployed depending on the situation.
Circulating metabolites associated with incident myocardial infarction and stroke: A prospective cohort study of 90 438 participants

The relevance between circulating metabolites and vascular events remains controversial and comprehensive studies are lacking. We sought to investigate the prospective associations of plasma metabolomics with risks of incident stroke, ischemic stroke (IS), hemorrhagic stroke (HS), and myocardial infarction (MI). Within the UK Biobank cohort, 249 circulating metabolites were measured in 90 438 participants without baseline vascular diseases. Cox proportional hazards regressions were applied to estimate adjusted hazard ratios (HRs) for per 1 standard deviation increment in metabolites. The least absolute shrinkage and selection operator algorithm was used for selecting metabolite subsets. During a median of 9.0 years of follow‐up, we documented 833 incident stroke and 1256 MI cases. Lipid constituents, comprising cholesterol, cholesteryl esters, free cholesterol, phospholipids, and total lipids, in very low‐ (VLDL), intermediate‐ (IDL), and low‐density lipoprotein (LDL) particles were positively associated with MI risk (HR = 1.12 to 1.36; 95% CI = 1.06 to 1.44), while in high‐density lipoprotein (HDL) particles showed inverse associations (HR = 0.68 to 0.81; 95% CI = 0.63 to 0.87). Similar association pattern with MI was also observed for VLDL, IDL, LDL, and HDL particles themselves. In contrast, triglycerides within all lipoproteins, including most HDL particles, were positively associated with MI risk (HR = 1.14 to 1.28; 95% CI = 1.08 to 1.35) and, to a slightly lesser extent, with stroke and IS. Unsaturation of fatty acids and albumin were inversely associated with risks of stroke, IS, and MI. In contrast, the linear association for HS is absent. When combining multiple metabolites, the metabolite risk score captured a drastically elevated risk of all vascular events, about twice that of any single metabolite. Taken together, circulating metabolites showed remarkably widespread associations with incident MI, but substantially weakened associations with risks of stroke and its subtypes. Exhaustive metabolomics profiling may shed light on vascular risk prediction and, in turn, guide pertinent strategies of intervention and treatment.
Parallel Implementation of Model Predictive Control for Multilevel Cascaded H-Bridge STATCOM With Linear Complexity

The algorithm complexity of model predictive control (MPC) for cascaded H-bridge (CHB) static synchronous compensators (STATCOMs) was optimized to a polynomial level in previous studies. However, implementing MPC with conventional approaches still suffers from long execution time, where a low cost digital signal processor (DSP) is used to execute optimization algorithms and a small-sized field-programmable gate array (FPGA) is used to extend gate signals and sampling functions. This paper presents a parallel implementation approach to reduce the execution time of MPC, where the FPGA is configured to be used for accelerating the high-complexity sorting tasks. By running the DSP and FPGA in parallel, the algorithm execution time is only determined by the DSP, and the resource consumption is only determined by the FPGA. To minimize the resource consumption and requirement in FPGA, a parallel comparison-based sorter with multiple comparison and accumulators is proposed. The proposed implementation method can reduce the time and space complexity of the MPC from the polynomial level to a linear level without additional hardware cost, which means the MPC for medium-voltage CHB STATCOMs (e.g., 20 stages) can be implemented online with existing control platforms. Experimental results for various CHB STATCOMs are presented to validate the proposed configuration and algorithm.
Evaluation of a new low-cost particle sensor as an internet-of-things device for outdoor air quality monitoring

ABSTRACT Many low-cost particle sensors are available for routine air quality monitoring of PM2.5, but there are concerns about the accuracy and precision of the reported data, particularly in humid conditions. The objectives of this study are to evaluate the Sensirion SPS30 particulate matter (PM) sensor against regulatory methods for measurement of real-time particulate matter concentrations and to evaluate the effectiveness of the Intelligent AirTM sensor pack for remote deployment and monitoring. To achieve this, we co-located the Intelligent AirTM sensor pack, developed at Clemson University and built around the Sensirion SPS30, to collect data from July 29, 2019, to December 12, 2019, at a regulatory site in Columbia, South Carolina. When compared to the Federal Equivalent Methods, the SPS30 showed an average bias adjusted R2 = 0.75, mean bias error of −1.59, and a root mean square error of 2.10 for 24-hour average trimmed measurements over 93 days, and R2 = 0.57, mean bias error of −1.61, and a root mean square error of 3.029, for 1-hr average trimmed measurements over 2300 hours when the central 99% of data was retained with a data completeness of 75% or greater. The Intelligent AirTM sensor pack is designed to promote long-term deployment and includes a solar panel and battery backup, protection from the elements, and the ability to upload data via a cellular network. Overall, we conclude that the SPS30 PM sensor and the Intelligent AirTM sensor pack have the potential for greatly increasing the spatial density of particulate matter measurements, but more work is needed to understand and calibrate sensor measurements. Implications: This work adds to the growing body of research that indicates that low-cost sensors of particulate matter (PM) for air quality monitoring has a promising future, and yet much work is left to be done. This work shows that the level of data processing and filtering effects how the low-cost sensors compare to existing federal reference and equivalence methods: more data filtering at low PM levels worsens the data comparison, while longer time averaging improves the measurement comparisons. Improvements must be made to how we handle, calibrate, and correct PM data from low-cost sensors before the data can be reliably used for air quality monitoring and attainment.
Decapod eggs membranes: powerful barriers or regulatory structures?

Osmoregulatory abilities and mechanisms of adults and larvae of decapod crustaceans have been extensively investigated. However, how embryos carried by their mothers can deal with changing or extreme salinities is less understood. The egg membranes are believed to isolate embryos from a challenging environment, although osmoregulatory ability has been demonstrated in early developing embryos (naupliar stage) of two crabs. To establish whether embryos are isolated by their membranes and/or are able to osmoregulate, we measured the survival and volume change over 48 h of oocytes and embryos in different stages of three carideans (Betaeus lilianae, Palaemon macrodactylus and P. argentinus) and the brachyuran Neohelice granulata, subjected to different salinities. In addition, we recorded osmolality changes in homogenates of the same stages in P. argentinus and N. granulata after 2 h of exposure and mapped the presence of putative sites of ions exchange in the membrane of all species. High mortality, when existed, was associated to low salinity and their variation with the stage of development depended on the species. All species precipitated silver salts in or under the egg envelope, with a different pattern between carideans and brachyuran. Changes in osmolality and egg volume after hypo/hyper osmotic salinity challenges indicate that eggs are not fully isolated by their membranes, and that some osmoregulatory mechanisms are in play to maintain developmental homeostasis. We suggest that egg membranes can participate in osmoregulation by selectively transporting ions to an intramembrane space, with differences between carideans and brachyurans.
Advances in Hybrid Vesicular Based Drug Delivery Systems: Improved Biocompatibility, Targeting, Therapeutic Efficacy and Pharmacokinetics of Anticancer Drugs.

Anticancer drugs and diagnostics can be transported in nanoscale vesicles that provide a flexible platform. A hybrid nanoparticle, a nano assembly made up of many types of nanostructures, has the greatest potential to perform these two activities simultaneously. Nanomedicine has shown the promise of vesicular carriers based on lipo-polymersomes, lipid peptides, and metallic hybrid nano-vesicle systems. However, there are significant limitations that hinder the clinical implementation of these systems at the commercial scale such as productivity is low, energy consumption is high, setup is expensive, process durations are long, and the current cancer therapies described in this article. Combinatorial hybrid systems can be used to reduce the above limitations. A greater therapeutic index and improved clinical results are possible with hybrid nanovesicular systems, which integrate the benefits of many carriers into a single structure. Due to their unique properties, cell-based drug delivery systems have shown tremendous benefits in the treatment of cancer. Nanoparticles (NPs) can benefit significantly from the properties of erythrocytes and platelets, which are part of the circulatory cells and circulate for a long time. Due to their unique physicochemical properties, nanomaterials play an essential role in cell-based drug delivery. Combining the advantages of different nanomaterials and cell types gives the resulting delivery systems a wide range of desirable properties. NPs are next-generation core-shell nanostructures that combine a lipid shell with a polymer core. The fabrication of lipid-polymer hybrid nanoparticles has recently undergone a fundamental shift, moving from a two-step to a one-step technique based on joint self-assembly of polymers and lipids. Oncologists are particularly interested in this method as a combinatorial drug delivery platform because of its two-in-one structure. This article addresses various preparative methods for the preparation of hybrid nano-vesicular systems. It also discusses the cellular mechanism of hybrid nano-vesicular systems and describes the thorough knowledge of various hybrid vesicular systems.
Robust real-time driver drowsiness detection based on image processing and feature extraction methods

Recently, the human lifestyle has strongly been affected by the novel technological equipment. The applications of Artificial Intelligence are widely being utilised to improve the performance and quality of the modern life. One of the important applications of these techniques is to seek to improve public safety, including the safety of driving. The statistics indicate that the mortality of car accidents yearly constitutes a significant proportion of the overall deaths. A number of strategies have been studied to materialise driver drowsiness detection systems. One of the best strategies relies on image processing and computer vision methods. In this paper, a novel real-time method for driver drowsiness detection is presented. This method uses Haar wavelet-based features for face detection. The eye state determination has been performed using PCA feature extraction along with an SVM classifier. The proposed method has been implemented and tested on a real-time ARM based embedded system, with a camera installed in front of the driver. Results show that the presented intelligent system has a high detection accuracy, compared to the methods presented thus far, on the standard datasets such as BioID and RS-DMV.
Stacked Topological Preserving Dynamic Brain Networks Representation and Classification

In recent years, numerous studies have adopted rs-fMRI to construct dynamic functional connectivity networks (DFCNs) and applied them to the diagnosis of brain diseases, such as epilepsy and schizophrenia. Compared with the static brain networks, the DFCNs have a natural advantage in reflecting the process of brain activity due to the time information contained in it. However, most of the current methods for constructing DFCNs fail to aggregate the brain topology structure and temporal variation of the functional architecture associated with brain regions, and often ignore the inherent multi-dimensional feature representation of DFCNs for classification. In order to address these issues, we propose a novel DFCNs construction and representation method and apply it to brain disease diagnosis. Specifically, we fuse the blood oxygen level dependent (BOLD) signal and interactions between brain regions to distinguish the brain topology within each time domain and across different time domains, by embedding block structure in the adjacency matrix. After that, a sparse tensor decomposition method with sparse local structure preserving regularization is developed to extract DFCNs features from a multi-dimensional perspective. Finally, the kernel discriminant analysis is employed to provide the decision result. We validate the proposed method on epilepsy and schizophrenia identification tasks, respectively. The experimental results show that the proposed method outperforms several state-of-the-art methods in the diagnosis of brain diseases.
Changes in the continuous leaping performance of Finnish adolescents between 1979 and 2020

ABSTRACT The aims of this secular trend design study were: 1) to investigate whether the continuous leaping performance of Finnish adolescents (mean age 14.99 ± .61 years) changed between 6 data sets collected between 1979 and 2020, and 2) to analyse if variation in leaping performance increased from 1979 to 2020. The data for this secular trend study of 6 cohorts were collected in 1979 (n = 599), 1995 (n = 498), 1998 (n = 796), 2003 (n = 2383), 2010 (n = 1383), and 2020 (n = 719). All cohorts performed the 5-leaps test, following the same protocol. Between-cohort differences in scores were analysed using a General Linear Contrast Model. Between-cohort differences in variance were tested using Chi-square-based between-group tests. Sex, age, and BMI were used as covariates in the secular trend analyses. Continuous leaping performance demonstrated a decreasing trend in both girls and boys. Specifically, girls’ scores were stable between 1979 and 1995, decreased from 1995 to 2010 and remained stable thereafter. Boys leaping performance improved from 1979 to 1995, was stable until 2003, and had declined by 2020. Within-group variation in continuous leaping was greater in girls and boys during the first decades of the 21st century than previously.
Refractory HypertensionNovelty and Significance

Refractory hypertension is an extreme phenotype of treatment failure defined as uncontrolled blood pressure in spite of ≥5 classes of antihypertensive agents, including chlorthalidone and a mineralocorticoid receptor antagonist. A prospective evaluation of possible mechanisms of refractory hypertension has not been done. The goal of this study was to test for evidence of heightened sympathetic tone as indicated by 24-hour urinary normetanephrine levels, clinic and ambulatory heart rate (HR), HR variability, arterial stiffness as indexed by pulse wave velocity, and systemic vascular resistance compared with patients with controlled resistant hypertension. Forty-four consecutive patients, 15 with refractory and 29 with controlled resistant hypertension, were evaluated prospectively. Refractory hypertensive patients were younger (48±13.3 versus 56.5±14.1 years; P =0.038) and more likely women (80.0 versus 51.9%; P =0.047) compared with patients with controlled resistant hypertension. They also had higher urinary normetanephrine levels (464.4±250.2 versus 309.8±147.6 µg per 24 hours; P =0.03), higher clinic HR (77.8±7.7 versus 68.8±7.6 bpm; P =0.001) and 24-hour ambulatory HR (77.8±7.7 versus 68.8±7.6; P =0.0018), higher pulse wave velocity (11.8±2.2 versus 9.4±1.5 m/s; P =0.009), reduced HR variability (4.48 versus 6.11; P =0.03), and higher systemic vascular resistance (3795±1753 versus 2382±349 dyne·s·cm5·m2; P =0.008). These findings are consistent with heightened sympathetic tone being a major contributor to antihypertensive treatment failure and highlight the need for effective sympatholytic therapies in patients with refractory hypertension. # Novelty and Significance {#article-title-44}
Caring touch in intensive care nursing: a qualitative study

ABSTRACT Background Historically, caring touch was integrated in targeted nursing acts as shoulder massage, calming patients or to check vital parameters by touching the patient`s skin. However, this phenomenon in intensive care nursing still lacks convincing descriptions. Caring touch is an important part of being an intensive care nurse and confirming the patient`s dignity. To touch the patient`s skin is a common nursing act, but not much spoken of. Caring touch on the patient`s chin, holding hands or giving a hug has earlier been called e.g., non-procedural touch. Purpose Explore the meaning of caring touch as it appeared for Norwegian intensive care nurses. Methods Secondary analysis of data from qualitative, individual semi-structured interviews. Eight experienced intensive care nurses at public Norwegian non-university hospitals. Registered by the Norwegian Center for Research data NSD December 2014. ID 41164. Findings Data analysis revealed one main-theme: The speaking body, with four sub-themes 1) Eyes and facial expressions, 2) Patients emotional expressions, 3) Closeness and distance, 4) ICU nurses’ emotional responses. Conclusion Caring touch is a silent way of showing culturally competent care and establish or continue nurse-patient relationships in intensive care units. Caring touch contributes to heighten ethical dimensions of dignity in intensive care nursing.
The contribution of object identity and configuration to scene representation in convolutional neural networks

Scene perception involves extracting the identities of the objects comprising a scene in conjunction with their configuration (the spatial layout of the objects in the scene). How object identity and configuration information is weighted during scene processing and how this weighting evolves over the course of scene processing however, is not fully understood. Recent developments in convolutional neural networks (CNNs) have demonstrated their aptitude at scene processing tasks and identified correlations between processing in CNNs and in the human brain. Here we examined four CNN architectures (Alexnet, Resnet18, Resnet50, Densenet161) and their sensitivity to changes in object and configuration information over the course of scene processing. Despite differences among the four CNN architectures, across all CNNs, we observed a common pattern in the CNN’s response to object identity and configuration changes. Each CNN demonstrated greater sensitivity to configuration changes in early stages of processing and stronger sensitivity to object identity changes in later stages. This pattern persists regardless of the spatial structure present in the image background, the accuracy of the CNN in classifying the scene, and even the task used to train the CNN. Importantly, CNNs’ sensitivity to a configuration change is not the same as their sensitivity to any type of position change, such as that induced by a uniform translation of the objects without a configuration change. These results provide one of the first documentations of how object identity and configuration information are weighted in CNNs during scene processing.