Miracle-dz/UniFAR-FTUs huggingface dataset:
Approaches to Improve Macromolecule and Nanoparticle Accumulation in the Tumor Microenvironment by the Enhanced Permeability and Retention Effect

Passive targeting is the foremost mechanism by which nanocarriers and drug-bearing macromolecules deliver their payload selectively to solid tumors. An important driver of passive targeting is the enhanced permeability and retention (EPR) effect, which is the cornerstone of most carrier-based tumor-targeted drug delivery efforts. Despite the huge number of publications showcasing successes in preclinical animal models, translation to the clinic has been poor, with only a few nano-based drugs currently being used for the treatment of cancers. Several barriers and factors have been adduced for the low delivery efficiency to solid tumors and poor clinical translation, including the characteristics of the nanocarriers and macromolecules, vascular and physiological barriers, the heterogeneity of tumor blood supply which affects the homogenous distribution of nanocarriers within tumors, and the transport and penetration depth of macromolecules and nanoparticles in the tumor matrix. To address the challenges associated with poor tumor targeting and therapeutic efficacy in humans, the identified barriers that affect the efficiency of the enhanced permeability and retention (EPR) effect for macromolecular therapeutics and nanoparticle delivery systems need to be overcome. In this review, approaches to facilitate improved EPR delivery outcomes and the clinical translation of novel macromolecular therapeutics and nanoparticle drug delivery systems are discussed.
Plasma Exosomal S1PR5 and CARNS1 as Potential Non-invasive Screening Biomarkers of Coronary Heart Disease

Background Early diagnosis and treatment significantly improve the prognosis of coronary heart disease (CHD), but no convenient screening tools are available. This study aims to find potential non-invasive screening biomarkers of coronary heart disease. Method We performed microarray analysis to investigate the mRNA expression levels in Small extracellular vesicles (sEVs) and screen significantly differentially expressed mRNAs in CHD patients vs. non-CHD patients. We then performed quantitative real-time polymerase chain reaction (qRT-PCR) to validate the microarray results, and we calculated the correlations between expression levels and clinicopathological data. Microarray analysis identified 72 downregulated mRNAs and 31 upregulated mRNAs in CHD patients relative to non-CHD patients. Results From the study, we found that upregulated sphingosine-1-phosphate receptor 5 (S1PR5) and downregulated carnosine synthase 1 (CARNS1) had the most significant differences between the patient group and the control group. S1PR5 expression was correlated with diabetes, heart rate, triglycerides, total cholesterol, low-density lipoprotein cholesterol, apolipoprotein B, and fasting blood glucose (P < 0.05). CARNS1 level was correlated with uric acid (UA) (P < 0.05). Overexpressed S1PR5 and downregulated CARNS1 were independent risk factors for CHD. The area under the receiver operating characteristic curve (AUC) of S1PR5 was 0.838 for diagnosing CHD; the AUC of CARNS1 was 0.883 for non-CHD; and the AUC of S1PR5 plus CARNS1 was 0.921 for CHD. Conclusions Microarray analysis showed that upregulated S1PR5 and downregulated CARNS1 in sEVs have the potential to become non-invasive biomarkers for CHD screening.
Stress-adaptive meander track for stretchable electronics

Stretchable metallic interconnects are commonly designed using a meander-shaped metal track with a uniform width. This article reports on a ‘stress-adaptive’ metal track design which varies in width to accommodate the produced torque in the metal track during stretching. The stress-adaptive design is inspired by computational and experimental studies of two conventional meander-shape metal tracks identifying a common failure mode; specifically, the propagation of torque leading to twist and mechanical fatigue. The understanding gained led to the stress-adaptive design. The stress-adaptive structure is compared with horseshoe- and U-shaped references and shows improvements in the stress distribution, levels of twist, maximum level of elongation (>320%), and required stretch and release cycles (>6000 at 150% elongation) to cause failure in a long term cycling test.
Speech Kinematics and Coordination Measured With an MEG-Compatible Speech Tracking System

Articulography and functional neuroimaging are two major tools for studying the neurobiology of speech production. Until recently, however, it has generally not been possible to use both in the same experimental setup because of technical incompatibilities between the two methodologies. Here we describe results from a novel articulography system dubbed Magneto-articulography for the Assessment of Speech Kinematics (MASK), which we used to derive kinematic profiles of oro-facial movements during speech. MASK was used to characterize speech kinematics in two healthy adults, and the results were compared to measurements from a separate participant with a conventional Electromagnetic Articulography (EMA) system. Analyses targeted the gestural landmarks of reiterated utterances /ipa/, /api/ and /pataka/. The results demonstrate that MASK reliably characterizes key kinematic and movement coordination parameters of speech motor control. Since these parameters are intrinsically registered in time with concurrent magnetoencephalographic (MEG) measurements of neuromotor brain activity, this methodology paves the way for innovative cross-disciplinary studies of the neuromotor control of human speech production, speech development, and speech motor disorders.
Renewable Energy Cooperatives as a Stimulating Factor in Household Energy Savings

Little is known about how renewable energy cooperatives (REScoops) try to influence energy conservation among households and the resulting impact. In this article the main research question is: What is the predictive value of renewable energy cooperatives on intention to save energy, engagement in energy-saving actions, and self-reported energy conservation by households? A survey was conducted to answer this question. Data analysis involved multivariate and binary logistic regression on data from two cooperatives: Ecopower (Belgium; N = 1000) and Enercoop (France; N = 8290). Results show that in addition to psychological and socio-demographic variables, REScoop items modestly contribute to the explained variation in engagement in energy-saving actions and reported energy conservation. At Enercoop 18.2% of the respondents indicated that their cooperative contributed to household energy savings; for Ecopower this figure was 36.9%. Moreover, at Enercoop, 38.7% of the respondents reported consuming less energy since obtaining cooperative membership; at Ecopower this was 64.7%. The article concludes with suggestions for future research.
Managing Reputation in Collaborative Social Computing Applications

Reputation is a fundamental concept for making decisions about service providers. However, managing reputation in peer-to-peer distributed applications is not easy due to the lack of a central server that can compute this property from user opinions. Moreover, users have to marry this information with their individual trust in the service provider, which may be based on their past experiences, the opinions of their direct contacts, or both. This paper develops a reputation management system embedded in the Digital Avatars framework for collaborative social computing applications, using subjective logic. We show how the reputation of a given service provider can be calculated using the users’ opinions about it, and how this reputation can be explicitly represented, managed and combined with the trust that individual service requesters may have in them, in order to make better informed decisions.
Intronic Polyadenylation in Acquired Cancer Drug Resistance Circumvented by Utilizing CRISPR/Cas9 with Homology-Directed Repair: The Tale of Human DNA Topoisomerase IIα

Simple Summary DNA topoisomerase IIα (170 kDa, TOP2α/170) resolves nucleic acid topological entanglements by generating transient double-strand DNA breaks. TOP2α inhibitors/poisons stabilize TOP2α-DNA covalent complexes resulting in persistent DNA damage and are frequently utilized to treat a variety of cancers. Acquired resistance to these chemotherapeutic agents is often associated with decreased TOP2α/170 expression levels. Studies have demonstrated that a reduction in TOP2α/170 results from a type of alternative polyadenylation designated intronic polyadenylation (IPA). As a consequence of IPA, variant TOP2α mRNA transcripts have been characterized that have resulted in the translation of C-terminal truncated TOP2α isoforms with altered biological activities. In this paper, an example is discussed where circumvention of acquired TOP2α-mediated drug resistance was achieved by utilizing CRISPR/Cas9 specific gene editing of an exon/intron boundary through homology directed repair (HDR) to reduce TOP2α IPA. These results illustrate the therapeutic potential of CRISPR/Cas9/HDR to impact drug resistance associated with aberrant IPA. Abstract Intronic polyadenylation (IPA) plays a critical role in malignant transformation, development, progression, and cancer chemoresistance by contributing to transcriptome/proteome alterations. DNA topoisomerase IIα (170 kDa, TOP2α/170) is an established clinical target for anticancer agents whose efficacy is compromised by drug resistance often associated with a reduction of nuclear TOP2α/170 levels. In leukemia cell lines with acquired resistance to TOP2α-targeted drugs and reduced TOP2α/170 expression, variant TOP2α mRNA transcripts have been reported due to IPA that resulted in the translation of C-terminal truncated isoforms with altered nuclear-cytoplasmic distribution or heterodimerization with wild-type TOP2α/170. This review provides an overview of the various mechanisms regulating pre-mRNA processing and alternative polyadenylation, as well as the utilization of CRISPR/Cas9 specific gene editing through homology directed repair (HDR) to decrease IPA when splice sites are intrinsically weak or potentially mutated. The specific case of TOP2α exon 19/intron 19 splice site editing is discussed in etoposide-resistant human leukemia K562 cells as a tractable strategy to circumvent acquired TOP2α-mediated drug resistance. This example supports the importance of aberrant IPA in acquired drug resistance to TOP2α-targeted drugs. In addition, these results demonstrate the therapeutic potential of CRISPR/Cas9/HDR to impact drug resistance associated with aberrant splicing/polyadenylation.
How has the COVID-19 pandemic affected our rheumatology patients using biological/targeted DMARDs?

INTRODUCTION We aimed to investigate the effects of the coronavirus disease 2019 (COVID-19) pandemic on the course and treatment of patients with inflammatory rheumatic musculoskeletal disease (iRMD) using biologic or targeted synthetic disease modifying and rheumatic drugs (b/tsDMARDs). METHODOLOGY The study was carried out in two stages: in the first stage we investigated the delay of b/tsDMARD treatment in the first 3 months of the pandemic; in the second stage, we investigated all patients who decided to continue treatment after interruption in the 12-month period. RESULTS A total of 521 patients were included in the study. The iRMD diagnosis was listed as spondyloarthritis (SpA) (54.3%), rheumatoid arthritis (RA) (25.7%), psoriatic arthritis (PsA) (8.4%), vasculitis (6.1%), and others (5.4%). Concurrent use of hydroxychloroquine (hazard ratio [HR] = 1.49), iv bDMARD use (HR = 1.34), and a history of discontinuation of drug in the first 3 months of the pandemic (HR = 1.19) were determined as factors that reduced 12-month drug retention rates. The use of glucocorticoid (HR = 3.81) and having a diagnosis of interstitial lung disease/chronic obstructive lung disease (HR = 4.96) were found to increase the risk of being infected by SARS coronavirus 2 (SARS-CoV-2). CONCLUSIONS It was shown that approximately 1/5 of iRMD patients using b/tsDMARDs delayed their treatment due to the fear of COVID-19 in the first three months of the pandemic process. However, with good communication with the patients, b/tsDMARD treatment was restarted and the 12-month drug retention status was quite high.
Joint Beamforming Design for IRS Aided Multiuser MIMO With Imperfect CSI

This paper investigates the joint beamforming design for the intelligent reflecting surface (IRS) aided multi-antenna multiuser (MU) multiple-input multiple-output (MIMO) downlink transmissions under imperfect channel state information (CSI), where the IRS can only take discrete PSs (PSs) at each element and the weighted sum rate (WSR) is adopted as the performance metric. By deriving the covariance matrix of the interference and noise at the users under the statistical channel estimation errors (CEEs) model, the joint WSR maximization problem is reformulated as an equivalent weighted minimum mean square error minimization problem and decoupled into two subproblems which are solved alternatively. In particular, two algorithms based on the majorization-minimization and gradient descent methods are proposed to obtain the optimal beamforming matrix at the IRS. Simulation results validate the accuracy of the proposed robust design and reveal that in case of imperfect CSI, the IRS can still achieve a significant improvement in WSR even with 2-bits PSs at the IRS. Moreover, it is also found that increasing the number of reflecting elements may not always be beneficial and that the optimal location of the IRS may be closer to the base station in the presence of CEEs.
Endophytic Fungi from Marine Macroalgae in Nova Scotia

Abstract - Marine macroalgae are a polyphyletic group of photosynthetic eukaryotes and play critical roles in oxygen production, as primary producers, and in providing physical habitat structure. They harbor diverse microbial communities, including mutualistic, commensalistic, and parasitic fungi. These fungi may be obligately or facultatively marine and symbiotic. In this investigation, we isolated endophytic algicolous fungi from marine macroalgae collected from 5 intertidal sites in Nova Scotia. Fungi were cultured from surface-sterilized algal tissue and identified using ITS rDNA barcoding. From 21 marine macroalgal species collected, 11 algal species harbored endophytic fungi. We identified 23 endophytic algicolous fungi from the Bay of Fundy and Atlantic coasts of Nova Scotia. Marine endophytes are a promising new resource for bioactive compounds.
Crowding-Out Effects of Laws, Policies and Incentives on Compliant Behaviour

Laws, policies, and incentives provide people with extrinsic reasons to engage in desired behaviours. But by doing so, they may attenuate or displace people’s intrinsic reasons for complying. In this chapter, I review theorising and empirical evidence on such crowding-out effects . I outline perspectives from psychology and economics on how laws, policies, and incentives may undermine people’s intrinsic motivation. Moreover, I describe how such insights have been applied to explain why laws, policies, and incentives may fail to increase compliance—or may even undermine it. The chapter will then review the empirical evidence on these processes in environmental, organisational, and other legal settings. Although it is plausible that laws, policies, and incentives will affect intrinsic motivation to comply, I conclude that empirical evidence of these processes is still modest. I conclude by outlining some important directions for future research, and some (tentative) recommendations for policy.
Differences in Upper-Body Peak Force and Rate of Force Development in Male Intermediate, Advanced, and Elite Sport Climbers

The aim of this study was to investigate the difference in climbing-specific strength and rate of force development (RFD) between intermediate, advanced, and elite male sport climbers. Seventy-eight male climbers were recruited and divided into groups based on the International Rock Climbing Research Association (IRCRA) numerical (1–32) grading system (intermediate (10–17) group (IG; n = 28)), advanced (18–23) group (AG; n = 30) and elite (24–27) group (EG; n = 20). Peak force (Fpeak) and average force (Favg) were measured while performing an isometric pull-up on a 23 mm thick campus rung. RFD was calculated from the onset of force to maximal peak force. The elite group performed better in all test parameters than the advanced (Fpeak: 39.7%, ES = 1.40, p < 0.001; Favg: 45.6%, ES = 4.60, p < 0.001; RFD: 74.9%, ES = 1.42, p = 0.001) and intermediate group (Fpeak: 95.7%, ES = 2.54, p < 0.001, Favg: 131.1%, ES = 5.84, p < 0.001, RFD: 154.4%, ES = 2.21, p = 0.001). Moreover, the advanced group demonstrated greater Fpeak (40.1%, ES = 1.24, p < 0.001), Favg (59.1%, ES = 1.57, p < 0.001) and RFD (45.5%, ES = 1.42, p = 0.046), than the intermediate group. Finally, climbing performance displayed strong correlations with Fpeak (r = 0.73, p < 0.001) and Favg (r = 0.77, p < 0.001), and a moderate correlation with RFD (r = 0.64, p < 0.001). In conclusion, maximal force and RFD in a climbing specific test are greater among climbers on higher performance levels. Independent of climbing level there is a moderate-to-strong association between maximal and rapid force production and climbing performance.
Application of Machine Learning Algorithms for Asthma Management with mHealth: A Clinical Review

Background Asthma is a variable long-term condition. Currently, there is no cure for asthma and the focus is, therefore, on long-term management. Mobile health (mHealth) is promising for chronic disease management but to be able to realize its potential, it needs to go beyond simply monitoring. mHealth therefore needs to leverage machine learning to provide tailored feedback with personalized algorithms. There is a need to understand the extent of machine learning that has been leveraged in the context of mHealth for asthma management. This review aims to fill this gap. Methods We searched PubMed for peer-reviewed studies that applied machine learning to data derived from mHealth for asthma management in the last five years. We selected studies that included some human data other than routinely collected in primary care and used at least one machine learning algorithm. Results Out of 90 studies, we identified 22 relevant studies that were then further reviewed. Broadly, existing research efforts can be categorized into three types: 1) technology development, 2) attack prediction, 3) patient clustering. Using data from a variety of devices (smartphones, smartwatches, peak flow meters, electronic noses, smart inhalers, and pulse oximeters), most applications used supervised learning algorithms (logistic regression, decision trees, and related algorithms) while a few used unsupervised learning algorithms. The vast majority used traditional machine learning techniques, but a few studies investigated the use of deep learning algorithms. Discussion In the past five years, many studies have successfully applied machine learning to asthma mHealth data. However, most have been developed on small datasets with internal validation at best. Small sample sizes and lack of external validation limit the generalizability of these studies. Future research should collect data that are more representative of the wider asthma population and focus on validating the derived algorithms and technologies in a real-world setting.
Study of FBG-based optical sensors for thermal measurements in aerospace applications

Optical fibers have revolutionized several technological sectors in recent decades, above all that of communication, and have also found many applications in the medical, lighting engineering, and infrastructural fields. In the aerospace field, many studies investigated the adoption of fiber optics considering the planned transition from fly-by-wire to fly-by-light flight controls. A significant feature of optical fiber is its ability to be used not only as a transmission medium but also as a basis for fiber-embedded sensors; one of the most prominent types is based on Bragg gratings (FBGs). FBGs can replace several traditional sensors, providing measures of temperature, vibrations, and mechanical deformation. Optical sensors provide many advantages over traditional, electrical-based sensors, including EMI insensitivity, ease of multiplexing on a single line, resilience to harsh environments, very compact sizes and global weight saving. Furthermore, punctual knowledge of the temperature field is essential to perform the thermal compensation of the optical sensors used for strain measurements. In this work, the authors analyzed the performance of thermal sensors based on FBGs to verify their stability, accuracy, and sensitivity to operating conditions. Two different methods of FBGs surface application have been considered (gluing with pre-tensioning vs. non-tensioned bonding). The results were then compared to those acquired using typical temperature sensors to determine the relationship between the observed temperature and the Bragg wavelength variation (i.e. the proportionality coefficient Kt). The effects on the proportionality coefficient Kt, arising from fiber pre-tensioning and thermal expansion of the structural support, were then evaluated by comparing the results obtained with the two bonding approaches.
Informing Users: Effects of Notification Properties and User Characteristics on Sharing Attitudes

Abstract Information sharing on social networks is ubiquitous, intuitive, and occasionally accidental. However, people may be unaware of the potential negative consequences of disclosures, such as reputational damages. Yet, people use social networks to disclose information about themselves or others, advised only by their own experiences and the context-invariant informed consent mechanism. In two online experiments (N = 515 and N = 765), we investigated how to aid informed sharing decisions and associate them with the potential outcomes via notifications. Based on the measurements of sharing attitudes, our results showed that the effectiveness of informing the users via notifications may depend on the timing, content, and layout of the notifications, as well as on the users’ curiosity and rational cognitive style, motivating information processing. Furthermore, positive emotions may result in disregard of important information. We discuss the implications for user privacy and self-presentation. We provide recommendations on privacy-supporting system design and suggest directions for further research.
Considerations to Optimize Strength and Muscle Mass Gains Through Flywheel Resistance Devices: A Narrative Review

ABSTRACT Flywheel (FW) resistance training is a valid and time-efficient method to improve force production and muscular hypertrophy. However, no definitive consensus exists regarding FW parameters for optimizing chronic training responses. Therefore, this review aims to examine the FW training literature and provide evidence-based conclusions and practical applications for practitioners. This review reports that FW resistance training is a valid strategy to improve force, power, and hypertrophy responses; however, differences with traditional training programs have not been clearly established. It is not possible to state that FW training is superior to traditional resistance training methodologies. Moreover, the differences between populations and sex should be studied in further depth to establish robust conclusions. Finally, this review reports variables (duration, volume, and intensity) that should be adopted to improve force, power, and hypertrophy responses—even though future research is needed to establish the appropriate training dose for specific populations.