Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-type Neighbors Enhanced Global Topology and Pairwise Attribute Learning for Drug-protein Interaction Prediction

MOTIVATION Accurate identification of proteins interacted with drugs helps reduce the time and cost of drug development. Most of previous methods focused on integrating multisource data about drugs and proteins for predicting drug-target interactions (DTIs). There are both similarity connection and interaction connection between two drugs, and these connections reflect their relationships from different perspectives. Similarly, two proteins have various connections from multiple perspectives. However, most of previous methods failed to deeply integrate these connections. In addition, multiple drug-protein heterogeneous networks can be constructed based on multiple kinds of connections. The diverse topological structures of these networks are still not exploited completely. RESULTS We propose a novel model to extract and integrate multi-type neighbor topology information, diverse similarities and interactions related to drugs and proteins. Firstly, multiple drug-protein heterogeneous networks are constructed according to multiple kinds of connections among drugs and those among proteins. The multi-type neighbor node sequences of a drug node (or a protein node) are formed by random walks on each network and they reflect the hidden neighbor topological structure of the node. Secondly, a module based on graph neural network (GNN) is proposed to learn the multi-type neighbor topologies of each node. We propose attention mechanisms at neighbor node level and at neighbor type level to learn more informative neighbor nodes and neighbor types. A network-level attention is also designed to enhance the context dependency among multiple neighbor topologies of a pair of drug and protein nodes. Finally, the attribute embedding of the drug-protein pair is formulated by a proposed embedding strategy, and the embedding covers the similarities and interactions about the pair. A module based on three-dimensional convolutional neural networks (CNN) is constructed to deeply integrate pairwise attributes. Extensive experiments have been performed and the results indicate GCDTI outperforms several state-of-the-art prediction methods. The recall rate estimation over the top-ranked candidates and case studies on 5 drugs further demonstrate GCDTI's ability in discovering potential drug-protein interactions.
Plug-in repetitive control of single-phase grid-connected inverter for AC module applications

This study presents two-stage inverter topology for single-phase grid-connected photovoltaic (PV) applications and its control implementations. The two-stage systems are reliable and work well. Typically, the second stage inverts solar power into AC power, whereas the first stage which is used to increase low PV panel voltage can achieve maximum power point tracking. In this configuration, a boost or a flyback type DC/DC converter topology is usually employed. However, such converters have major drawbacks such as low efficiency and limited voltage gain due to power losses. In the proposed topology, a low-voltage PV panel can be connected to power grid through solar inverter by using high-gain DC/DC converter which has unique features such as galvanic isolation and continuous current for AC module applications. Conventional controller results in poor control performance due to the finite gain at desired frequencies. Hence, a plug-in repetitive controller is proposed to obtain low total harmonic distortions (THDs). The performance of the proposed system is provided for the system which injects the PV panel current in the maximum power point voltage to a grid of 220 V (rms) at a power range of 150-300 W with a unity power factor and a low input current THD.
GEN: Generative Equivariant Networks for Diverse Image-to-Image Translation

Image-to-image (I2I) translation has become a key asset for generative adversarial networks. Convolutional neural networks (CNNs), despite having a significant performance, are not able to capture the spatial relationships among different parts of an object and, thus, do not qualify as the ideal representative model for image translation tasks. As a remedy to this problem, capsule networks have been proposed to represent patterns for a visual object in such a way that preserves hierarchical spatial relationships. The training of capsules is constrained by learning all pairwise relationships between capsules of consecutive layers. This design would be prohibitively expensive both in time and memory. In this article, we present a new framework for capsule networks to provide a full description of the input components at various levels of semantics, which can successfully be applied to the generator-discriminator architectures without incurring computational overhead compared to the CNNs. To successfully apply the proposed capsules in the generative adversarial network, we put forth a novel Gromov–Wasserstein (GW) distance as a differentiable loss function that compares the dissimilarity between two distributions and then guides the learned distribution toward target properties, using optimal transport (OT) discrepancy. The proposed method—which is called generative equivariant network (GEN)—is an alternative architecture for GANs with equivariance capsule layers. The proposed model is evaluated through a comprehensive set of experiments on I2I translation and image generation tasks and compared with several state-of-the-art models. Results indicate that there is a principled connection between generative and capsule models that allows extracting discriminant and invariant information from image data
A prospective case-control validation of procalcitonin as a biomarker diagnosing pacemaker and implantable cardioverter defibrillator pocket infection.

BACKGROUND The diagnosis of device infections, especially pocket infections, is challenging and relies primarily on the clinical presentation. The prospective DIRT (Device associated infections role of new diagnostic tools) study identified procalcitonin (PCT) among 14 biomarkers as the most promising biomarker to aid the diagnosis of pocket infection and identified an optimized cut-off value of 0.05 ng/ml for a localized generator pocket infection. AIMS The present study aims to validate the proposed PCT cut-off value of 0.05 ng/ml for the diagnosis of pocket infection in an independent cohort. METHODS We prospectively enrolled 81 patients with pocket infections and 81 age and renal function matched controls presenting for elective device exchange or lead revision. Patients with concomitant infectious or inflammatory diseases, end-stage renal failure, current active malignancy or receiving immunosuppressive therapy were excluded. RESULTS An elevated PCT over 0.05 ng/ml was found in 68% (n = 55) of pocket infections and 24% (n = 19) of controls, corresponding to a sensitivity of 68% and a specificity of 77% for diagnosing a pocket infection. In ROC analysis, PCT showed an area under the curve of 0.75 (95% confidence interval, 0.68-0.83; P <0.001). Sensitivity remained high with antibiotic pretreatment (65% c.f. 69% without pretreatment) and in cases with minimal inflammatory signs (67% c.f. 70% with extensive inflammation). CONCLUSION Our study validates the cut-off value of 0.05 ng/ml PCT for diagnosis of a pocket infection, even in patients pre-treated with antibiotics or with minimal clinical signs of inflammation.
Adenovirus type 5 SARS-CoV-2 vaccines delivered orally or intranasally reduced disease severity and transmission in a hamster model

Transmission-blocking strategies that slow the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and protect against coronavirus disease 2019 (COVID-19) are needed. We have developed an orally delivered adenovirus type 5–vectored SARS-CoV-2 vaccine candidate that expresses the spike protein. Here, we demonstrated that hamsters vaccinated by the oral or intranasal route had robust and cross-reactive antibody responses. We then induced a postvaccination infection by inoculating vaccinated hamsters with SARS-CoV-2. Orally or intranasally vaccinated hamsters had decreased viral RNA and infectious virus in the nose and lungs and experienced less lung pathology compared to mock-vaccinated hamsters after SARS-CoV-2 challenge. Naïve hamsters exposed in a unidirectional air flow chamber to mucosally vaccinated, SARS-CoV-2–infected hamsters also had lower nasal swab viral RNA and exhibited fewer clinical symptoms than control animals, suggesting that the mucosal route reduced viral transmission. The same platform encoding the SARS-CoV-2 spike and nucleocapsid proteins elicited mucosal cross-reactive SARS-CoV-2–specific IgA responses in a phase 1 clinical trial (NCT04563702). Our data demonstrate that mucosal immunization is a viable strategy to decrease SARS-CoV-2 disease and airborne transmission. Description Oral and intranasal adenovirus 5–vectored SARS-CoV-2 vaccines reduced disease and decreased airborne transmission in a hamster model. Tackling transmission SARS-CoV-2 vaccination is an essential tool to curb the ongoing COVID-19 pandemic. However, current vaccination strategies have not been optimized to elicit immune responses at mucosal sites or to prevent transmission between individuals. Here, Langel et al. tested whether an adenovirus type 5–vectored SARS-CoV-2 vaccine could confer protection in vaccinated hamsters when delivered intranasally or orally. The authors observed that oral or intranasal delivery of the vaccine conferred protection to the vaccinated hamster. Furthermore, it inhibited transmission to unvaccinated, naïve hamsters sharing air with infected index hamsters. Last, the authors report results on clinical trial testing the same vaccine platform, showing elicitation of mucosal antibody responses in vaccinated participants.
Dnmt1a is essential for gene body methylation and the regulation of the zygotic genome in a wasp

Gene body methylation (GBM) is an ancestral mode of DNA methylation whose role in development has been obscured by the more prominent roles of promoter and CpG island methylation. The wasp Nasonia vitripennis has little promoter and CpG island methylation, yet retains strong GBM, making it an excellent model for elucidating the roles of GBM. Here we show that N. vitripennis DNA methyltransferase 1a (Nv-Dnmt1a) knockdown leads to failures in cellularization and gastrulation of the embryo. Both of these disrupted events are hallmarks of the maternal-zygotic transition (MZT) in insects. Analysis of the embryonic transcriptome and methylome revealed strong reduction of GBM and widespread disruption of gene expression during embryogenesis after Nv-Dnmt1a knockdown. Strikingly, there was a strong correlation between loss of GBM and reduced gene expression in thousands of methylated loci, consistent with the hypothesis that GBM directly facilitates high levels of transcription. We propose that lower expression levels of methylated genes due to reduced GBM is the crucial direct effect of Nv-Dnmt1 knockdown. Subsequently, the disruption of methylated genes leads to downstream dysregulation of the MZT, culminating in developmental failure at gastrulation.
“Yes, and…!” Assessing the Impact of Theatre-Based Improvisational Training and a Simulation on Work Group Behavior

“YES, AND. ” ASSESSING THE IMPACT OF THEATRE-BASED IMPROVISATIONAL TRAINING AND A SIMULATION ON WORK GROUP BEHAVIOR by Jillian Rene Anderson Theatre-based improvisational training for executives is becoming a trend with improv-based theatres such as Chicago’s Second City catering their skills to the corporate world. Unfortunately, effectiveness of such training has relied primarily on assumptions and anecdotal testimony, with little supporting empirical data. This study seeks to take the first step toward quantifiably assessing the effectiveness of workplace improvisational training and the use of a supplementary simulation activity. Malcolm Knowles’ assumptions of adult learning guide the research. The Group Behavioral Inventory (GBI), used for assessing impact of organizational interventions, allows for the testing of changes in dimensions of group behavior across time. Results indicate no significant increases in dimensions of group behavior following training and a simulation; however, analysis of trends points to the potential for improv-training to temporarily encourage positive group bonds and reinforce existing group goals. Trends also reveal the value of simulation activities for creating increased self-awareness. “YES, AND. ” ASSESSING THE IMPACT OF THEATRE-BASED IMPROVISATIONAL TRAINING AND A SIMULATION ON WORK GROUP BEHAVIOR
Will the introduction of the national broadband network change the face of preventive medicine

Aging of the Australian population will increase the demand and provision of health services. Older Australians are significant users of healthcare, which is in disproportion to their number.1 A large proportion of health utilisation is devoted to managing chronic diseases,2 many of which are to a certain degree preventable. Some of the diseases are linked to unhealthy lifestyle factors such as cigarette smoking, excessive drinking, lack of physical activity and excess body weight. In some cases, the progress of the chronic diseases may be slowed and serious consequences (i.e. hospitalisations, moving to nursing home) can be avoided or significantly delayed by timely access to care and/or good disease management.3 Thus, preventive measures may ease the burden on the overloaded healthcare system and decrease the health expenditure.
The effects of pre-stressed rods contoured by different bending techniques on posterior instrumentation of L4-L5 lumbar spine segment: A finite element study

Posterior pedicle screw instrumentation (PPSI) is a well-known method in lumbar spine surgery. Understanding how PPSI affects the biomechanics of the lumbar spine is an important issue. In particular, during PPSI operations, surgeons bend rods according to the patients’ spinal curvatures based on their own experiences. As a result, residual stresses develop on the rods due to this bending. Although many finite element-based biomechanical studies have been performed for PPSI, studies comparing the effects of residual stresses arising from rod contouring on the construct stresses are lacking. Thus, this study aimed to investigate the effects of residual stress in PPSI using rods contoured with a French bender and an in-situ bender, as well as comparing the differences in stress increment with straight and contoured rods for different physiological motions. Accordingly, a finite element (FE) model of the L4-L5 lumbar spine segment was developed for PPSI and the effects of residual stresses on rods were investigated by using different bending methods. In the simulations, it was found that rods contoured with a French bender with residual stress resulted in significantly more increased stress in PPSI compared to those contoured with an in-situ bender. The results of this study emphasize that increased stress in PPSI due to the residual stresses for different physiological motions may increase the risk of PPSI failures. Additionally, the finite element modeling approach employed here could be used as a fundamental tool for further investigations of topics such as PPSI fatigue life and failure studies.
The Associations Between Attitudes Toward Interpersonal Affective Touch, Negative Cognitions and Social Anxiety: A Pilot Study

Objective: Affectionate touch promotes psychological well-being likely through inducing cognitive and neurobiological changes, which implies the inverse association of affectionate touch to negative cognitive and psychosocial outcomes. Our aim was to explore relationships between attitudes toward interpersonal touch and social anxiety through fear of negative evaluation and self-critical rumination as mediating variables.Method: Data from 250 participants (69.6% females, n = 174) ranging in age from 18 to 65 years were collected through self-report inventories assessing attitudes toward physical touch from friends and family, nonromantic intimate person and unfamiliar person, fear of negative evaluation, self-critical rumination, and social anxiety. A moderated-mediation analysis was conducted. Results: No direct link was seen between attitudes toward friends and family touch experiences and social anxiety in both genders, but mediation through fear of negative evaluation was significant (p < .05). Attitudes toward nonromantic intimate touch were related to social anxiety only in females and only indirectly through self-critical rumination (p < .05). In both males and females, attitudes toward touch from unfamiliar persons were linked to social anxiety directly (p < .05) but indirect paths through fear of negative evaluation (p < .05) and self-critical rumination were seen only in females (p < .05). Conclusions: Findings indicate that attitudes toward interpersonal affectionate touch may be predictive of social anxiety and the negative cognitions associated with it, extending previous findings on social pain and attesting to the potential clinical utility of touch-based interventions for social anxiety.
Molecular View on the Impact of DHA Molecules on the Physical Properties of a Model Cell Membrane

Docosahexaenoic acid (DHA) is a ω-3 polyunsaturated fatty acid, which can be uptaken by cells and is essential for proper neuronal and retinal function. However, the detailed physical impact of DHA molecules on the plasma membrane is still unclear. Hence, in this work, we carried out μs-scale coarse-grained molecular dynamics (MD) simulations to reveal the interactions between DHA molecules and a model cell membrane. As is known, the cell membrane can segregate into liquid-ordered (Lo) and liquid-disordered (Ld) membrane domains due to the differential interactions between lipids and proteins. In order to capture this feature, we adopted the three-component phase-separated lipid membranes and considered both anionic and neutral DHA molecules in the current work. Our results showed that DHA molecules can spontaneously self-assemble into nanoclusters, fuse with lipid membranes, and localize preferably in Ld membrane domains. During the membrane fusion process, DHA molecules can change the intrinsic transmembrane potential of the lipid membrane, and the effects of anionic DHA molecules are much more significant. Besides, the presence of DHA molecules mainly in the Ld membrane domains could regulate the differences in the lipid chain order, membrane thickness, cholesterol preference, and cholesterol flip-flop basically in a concentration-dependent manner, which further promote the stability of the intraleaflet dynamics and inhibit the interleaflet dynamics (or promote membrane domain registration) of the membrane domains. In short, the impact of DHA molecules on the physical properties of a model cell membrane on the molecular level revealed in our work will provide useful insights for understanding the biological functions of DHA molecules.
IMPACT OF ELECTRICAL NOISE ON THE TORSIONAL RESPONSE OF VFD COMPRESSOR TRAINS

The popularity of VFD motors in compressor trains has increased in recent years. Increased process flexibility is a primary consideration for implementation of VFD systems. However, this comes at a cost of increased mechanical and electrical complexity. Problems rarely experienced with single speed motors have become more likely with VFD's. These include impacts on the torsional behavior leading to component failure and extended downtimes. VFD's can excite the torsional system in several ways. This paper examines the impact of white noise on the torsional response of VFD compressor trains and contrasts it against the response to single frequency harmonic excitation. The characteristics of white noise, noise modeling characteristics for torsional response, and noise generation techniques are examined. Generation of a frequency banded noise signal is presented using a commonly used math modeling code. Two case studies are presented representing VFD compressor trains found in the LNG industry. Both experienced torsional problems related to the VFD and, in one case, led to a coupling failure and release of parts from the train. In the examination of these trains, a single frequency harmonic (SFH) sweep and banded Gaussian white noise (GWN) encompassing the dynamic response envelop of the 1st TNF, are used as inputs to the torsional analysis.
Development and Box–Behnken design optimization of a green extraction method natural deep eutectic solvent‐based for phenolic compounds from barley malt rootlets

In recent years, attention has been turned finding new sources of phenolic compounds, antioxidant molecules, main by‐products from the agri‐food chain like barley malt rootlets (BMRs). Traditionally, phenolic compounds are extracted from food matrices using different procedures, for example, solid–liquid, liquid–liquid, or solid‐phase extraction techniques employing organic solvents. With the advent of green chemistry, attention has been paid to the search for green, nontoxic, inexpensive, and nonflammable solvents and the natural deep eutectic solvents (NADESs) respect these characteristics. The aim of this project was to develop and optimize an environmentally friendly, inexpensive, and rapid extraction method for phenolic compounds from BMRs using natural DESs as extractive solvents. Several natural DESs were tested as extractive solvents and, among them, the best results in terms of total phenolic content were obtained using a choline chloride‐malic acid (1:2 molar ratio)‐based mixture. Box–Behnken experimental design guaranteed the extraction of 9.51 ± 0.83 gallic acid equivalent/g of BMRs, under the following optimal extraction conditions: 1:21 solid‐to‐liquid ratio, 80°C as extraction temperature, 43 min as the time of extraction, and 29% as a percentage of added water in the NADESs. Phenolic acids and flavonoids were detected in the BMRs extract through HPLC‐PDA/MS analysis.
Highly active CAR T cells that bind to a juxtamembrane region of mesothelin and are not blocked by shed mesothelin

Significance Mesothelin (MSLN) is a cell-surface protein that is a popular target for antibody-based therapies. We have identified shed MSLN as a major obstacle to successful antibody therapies and prepared a monoclonal antibody that inhibits shedding and makes very active CAR T cells whose activity is not blocked by shed MSLN and merits further preclinical development.
Optimal Experimental Design for Finding Optimally Located Boreholes in Geothermal Engineering

An obstacle for further commercial utilization of deep geothermal resources is the high cost for deep drilling in regard to the productivity risk of a well. Minimizing the risk by optimizing the location of a well is thus a question of primary importance. For a given geological model of a reservoir, we demonstrate how this problem may be tackled by a mathematical optimization approach called optimal experimental design. We show how this problem can be mathematically derived, numerically formulated, and practically implemented using distributed computing. We discuss an example for a sedimentary geothermal reservoir with multiple lithological units. We show how optimized positions of boreholes can be determined such that uncertainty of estimating the hydraulic permeability of a target rock unit from temperature measurements is minimized.