Miracle-dz/UniFAR-FTUs huggingface dataset:
Acute 4,4'-Methylene Diphenyl Diisocyanate Exposure-Mediated Downregulation of miR-206-3p and miR-381-3p Activates Inducible Nitric Oxide Synthase Transcription by Targeting Calcineurin/NFAT Signaling in Macrophages.

Exposure to 4,4'-methylene diphenyl diisocyanate (MDI) in the occupational setting may lead to development of occupational asthma (OA), and the underlying molecular mechanisms of MDI-induced disease pathogenesis remain an active area of research. Using a nose-only mouse inhalation model, we find that circulating microRNA (miR)-206-3p and miR-381-3p are downregulated after MDI exposure; however, cellular miR-206-3p and miR-381-3p responses after MDI aerosol exposure and their pathophysiological roles in MDI-OA are unknown. We hypothesize that miR-206-3p and miR-381-3p-regulated mechanisms cause increased expression of the inducible nitric oxide synthase (iNOS) after MDI aerosol exposure. We examined cellular miR-206-3p and miR-381-3p, calcineurins, nuclear factors of activated T-cells (NFATs) and iNOS levels from both nose-only exposed murine bronchoalveolar lavage cells (BALCs) and differentiated THP-1 macrophages treated with MDI-glutathione (GSH) conjugates. Both in vivo murine MDI aerosol exposure and in vitro MDI-GSH exposures in THP-1 macrophages results in downregulation of endogenous miR-206-3p and miR-381-3p and upregulation of PPP3CA and iNOS expression. Transfection of THP-1 macrophages with miR-inhibitor-206-3p and miR-inhibitor-381-3p resulted in the upregulation of PPP3CA and iNOS. Using RNA-induced silencing complex immunoprecipitation (RISC-IP) and translational reporter assays, we verified that PPP3CA, but not iNOS, is directly targeted by both miR-206-3p and miR-381-3p. Downregulation of miR-206-3p and miR-381-3p following by MDI exposure induces Calcineurin/NFAT signaling-mediated iNOS transcription in macrophages and BALCs.
Novel investigational therapeutics for generalized anxiety disorder (GAD)

ABSTRACT Introduction: Generalized anxiety disorder (GAD) is a common and disabling psychiatric condition that affects 3% of the population and exacts significant costs to society if untreated. There are numerous treatment options available, but all have side effects, and none are reliably effective; hence, there is a significant need for new medications. Areas covered: The authors reviewed clinical Phase II and III studies listed on the clinicaltrials.gov and clinicaltrialsregister.eu websites, 2007-present. Additional information was gathered from the study sponsor websites and Pubmed. The categories of mechanisms investigated include: modulators of GABAergic or glutamatergic activity; modulators of monoaminergic systems including serotonin, norepinephrine, and dopamine; and modulators of neuropeptide corticotropin release factor. Expert opinion: There are few investigational drugs in the later stages of clinical development. Challenges include high placebo response rates, enrollment of symptomatic volunteers with minimal depressive and anxiety comorbidity, and the lack of a unifying pathophysiological model. Drug developers should consider implementing trial designs such as sequential parallel comparison design to enhance signal detection. Inclusion of depressive comorbidity may also enhance signal detection by reducing placebo-responsivity. More studies examining glutamate-mediated neuroplasticity in GAD are needed.
Pediatric asthma severity scores distinguish suitable inpatient level of care for children admitted for status asthmaticus

Abstract Objective: To determine if the Pediatric Asthma Severity Score (PASS) can distinguish “late-rescues” (transfer to the pediatric intensive care unit [PICU] within 24-hours of general pediatric floor admission), “PICU readmissions” (readmission within 24-h after transfer to a lower inpatient level of care), and unplanned 30-day hospital readmission in children admitted with status asthmaticus. Methods: We performed a single center, retrospective cohort study in 328 children admitted for asthma exacerbation aged 5–18 years from May 2015 to October 2017. We sought to determine if PASS values preceding admission from the emergency department or transfer to the general pediatric unit will be greater in children with late rescues and PICU readmissions and if a cutoff PASS values exist to discriminate these events prior to intrafacility transfer. Results: Nine (5%) late-rescues and 5 (3%) PICU readmissions accounted for 14/328 (4%) composite outcomes. PASS values were greater in children with these events (8 [IQR:5–8] vs. 5 [IQR:3–6], p < .01). Logistic regression of PASS on composite outcome yielded an odds ratio of 1.4 (1.1–1.8, p < .01) and ROC curve of PASS on a composite outcome yielded an AUC of 0.74 (0.61–0.87) with a threshold of ≥ 9. Nine (3%) children experienced unplanned 30-day hospital readmissions but PASS preceding hospital discharge was neither discriminative nor associated with hospital readmission. Conclusions: PASS values ≥ 9 identify children at increased risk for late-rescue and PICU readmission. Applied with traditionally criteria for selection of inpatient level of care, PASS may assist providers in reducing acute inpatient disposition errors.
Math problem-solving and cognition among emerging bilingual children at risk and not at risk for math difficulties

ABSTRACT Cognitive processes that underlie individual differences in mathematical problem-solution accuracy in elementary emerging bilingual children (English Learners) at risk and not at risk for math problem-solving difficulties (MD) were examined. A battery of tests was administered in both English and Spanish that assessed problem-solving, achievement, and cognitive processing in children in first (N = 155/MD N = 23), second (N = 129/MD N = 44) and third grades (N = 110/MD N = 39). The results were that (a) the executive component of working memory (WM) predicted MD status independent of measures of fluid intelligence, reading, calculation, knowledge of algorithms, processing speed, short-term memory, and inhibition, (b) low performance on Spanish measures of numeracy and executive component of WM were major predictors of the odds of being classified as MD and (c) bilingual proficiency primarily moderated English rather than Spanish measures of cognition. The results support the notion that the executive system of WM is an important predictor of emerging bilingual children’s math problem-solving difficulties.
Biomarker expression analysis in different age groups revealed age was a risk factor for breast cancer

The relationship between age and breast cancer is ambiguous. Here, we analyzed the differential expression pattern of long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) in different age groups to provide an effective association between age and breast cancer risk at the molecular level. We integrated the microarray information from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data sets. The patients were divided into young ( < 50 years) and old ( ≥ 50 years) age groups and evaluated by differential gene expression, weighted gene correlation network analysis (WGCNA), functional enrichment analyses, and coexpression analysis. To determine their potential clinical significance, univariate Cox regression analysis and survival assessment were conducted. We identified two lncRNAs (AL139280.1 and AP000851.1) and three mRNAs (MT1M, HBB, and TFPI2) as the risk markers, and Gene set enrichment analysis (GSEA) focusing on a single gene revealed that "pyrimidine metabolism," "cell cycle," and "P53 signaling pathway" were coenriched. These data demonstrated that age may be a risk factor for breast carcinogenesis and prognosis and provide an in‐depth molecular characterization based on the expression patterns of lncRNAs and mRNAs.
Tensor-Based Rule-Space Management System in SDN

This paper presents a tensor-based rule-space management (TERM) system for improving the available capacity of switches in software defined networking (SDN). Limited storage capacity of switches is a key challenge in SDN as the switches use ternary content addressable memories having very low capacity. Low rule storage capacity eventually leads to the high number of Packet-In messages and control plane overloading. The challenge is to design a dynamic scheme to store a large number of heterogeneous flow-rules in SDN switches and reduce the number of Packet-In messages. To address this problem, we apply the concept of tensor decomposition in order to aggregate flow-rules. In addition, we employ a rule caching mechanism for better throughput. Simulation results show the efficiency of TERM in terms of reduction in the number of Packet-In messages. TERM reduces the Packet-In message count by ${{57.78\%}}$ than the flow aggregation approach proposed in the existing literature.
Terrestrosin D from Tribulus terrestris attenuates bleomycin-induced inflammation and suppresses fibrotic changes in the lungs of mice

Abstract Context: Terrestrosin D (TED), from Tribulus terrestris L. (Zygophyllaceae), exhibits anti-tumour and anti-inflammatory activities. However, its effects on bleomycin (BLM)-induced pulmonary inflammation and the subsequent fibrotic changes remain unclear. Objective: To examine the anti-inflammatory and anti-fibrotic effects of TED against BLM in murine pulmonary tissues. Materials and methods: Male SPF mice received saline (control), TED (10 mg/kg), BLM (2.5 mg/kg), or BLM (2.5 mg/kg) + TED (10 mg/kg) group. BLM was administered as a single intranasal inoculation, and TED was intraperitoneally administered once daily. After 2 and 6 weeks of treatment, cell number and differentiation (Giemsa staining) and TNF-α, IL-6, IL-8, TGF-β1, and PDGF-AB levels (ELISA) were determined in the bronchoalveolar lavage fluid (BALF). Hydroxyproline (Hyp) content in the left pulmonary tissue was also determined (ELISA). The right pulmonary tissue was H&E-stained and assessed for the severity of pulmonary fibrosis using the Ashcroft scoring method. Compared with the BLM group, TED decreased inflammatory cell infiltration; number of macrophages (p < 0.05), neutrophils (p < 0.05), lymphocytes (p < 0.05); percentage of macrophages in the monocyte-macrophage system (p < 0.05), and levels of TNF-α (p < 0.01), IL-6 (p < 0.01), IL-8 (p < 0.05), TGF-β1 (p < 0.05), and PDGF-AB (p < 0.05) in the BALF. TED also reduced Hyp content (p < 0.05) in the pulmonary tissue and attenuated the BLM-induced deterioration in lung histopathology. Discussion and conclusions: TED can inhibit BLM-induced inflammation and fibrosis in the lungs of mice, which may be related to reduced inflammatory and fibrotic markers. These results could be further tested in humans through clinical studies.
Cationic copolymer-chaperoned short-armed 10–23 DNAzymes

Abstract The cationic copolymer poly(L-lysine)-graft-dextran (PLL-g-Dex) has nucleic acid chaperone-like activity. The copolymer facilitates both DNA hybridization and strand exchange reactions. For these reasons, DNA-based enzyme (DNAzyme) activity is enhanced in the presence of copolymer. In this study, we evaluated activities of DNAzymes with substrate-binding arms (S-arms) of various lengths. The copolymer promoted DNAzyme reactivity and turnover efficacy, and, depending on S-arm length, maximally accelerated the reaction rate by 250-fold compared to the rate in the absence of copolymer. The copolymer permitted up to six nucleotides truncation of the S-arms having initial length of 10 and 11 nucleotides without loss of catalytic efficiency, enable tuning of the optimal temperature ranging from 30 to 55 °C. The approach might be useful for the development of DNAzyme systems targeting short or highly structured RNAs as well for improvement of DNAzyme-based nanomachines and biosensors.
Evaluation of the effectiveness of relaxation in lowering the level of anxiety in young adults - a pilot study.

OBJECTIVES Anxiety is a negative emotion that acts as a mediator between stress stimuli and emotional (physiological) reaction patterns. The myofascial system is particularly sensitive to stress. The aim of this study was to determine which of the 2 popular methods used to reduce psychophysical tension, i.e., soft tissue manipulation and Jacobson's progressive relaxation, is more effective. MATERIAL AND METHODS This study was conducted at Gdansk University of Physical Education and Sports in the sports psychology laboratory and the manual therapy room. After performing specialist consultations and interviews to exclude potential participants with contraindications to any of the interventions, the final sample included 90 people who were randomly assigned to 1 of 2 treatment groups. In group I, soft tissue techniques were applied, including the techniques of post-isometric muscle relaxation, elements of myofascial relaxation of tissues, and elastic tissue deformation using the Swedish massage limited to the cervicothoracic complex. In group II, Jacobson's progressive relaxation was performed. The training consisted of tightening and relaxing specific muscle groups. The experiment was conducted under an ambulatory condition, consisting of a single physiotherapeutic session (group I) or a single progressive relaxation session using the Jacobson method (group II). The level of anxiety was assessed twice, i.e., immediately before and after the therapy. RESULTS According to a repeated-measures ANOVA, each therapeutic impact was effective in reducing the level of perceived anxiety. Furthermore, the level of perceived anxiety in group I decreased significantly more than that in group II. CONCLUSIONS In conclusion, both the soft tissue manipulation and Jacobson's progressive relaxation techniques were efficient methods of minimizing the negative effects of stress.
Current insights in veterinarians’ psychological wellbeing

ABSTRACT This article outlines some of the key prevalence studies regarding the psychological health of veterinarians, and highlights the reasons for distress, with factors such as workload, financial issues, long working hours, challenging interactions, unexpected outcomes, euthanasia and fear of complaints or making mistakes being commonly cited. During the last decade, many ways to improve veterinarians’ wellbeing have been suggested, including both individual and organisational strategies. However, what appears to be lacking is a body of intervention research to test the effectiveness of these strategies. This article outlines some of the types of psychological distress which have been reported in veterinarians, and emphasises key issues such as the impact of practitioners’ help-seeking behaviour and moral and ethical dilemmas. Some wellbeing interventions from overseas studies are highlighted, with a focus on strategies that can be adopted by organisations as well as individuals. The review includes several recommendations to improve the psychological wellbeing of veterinarians such as using multi-disciplinary clinician wellbeing models to structure interventions, the possibilities of mindful self-compassion practices, and the regular use of peer support and reflective groups. It concludes that implementation and robust evaluation of wellbeing initiatives in the New Zealand veterinary population are urgently needed.
Tumor Cell Identification in Ki-67 Images on Deep Learning

The proportion of cells staining for the nuclear antigen Ki-67 is an important predictive indicator for assessment of tumor cell proliferation and growth in routine pathological investigation. Instead of traditional scoring methods based on the experience of a trained laboratory scientist, deep learning approach can be automatically used to analyze the expression of Ki-67 as well. Deep learning based on convolutional neural networks (CNN) for image classification and single shot multibox detector (SSD) for object detection are used to investigate the expression of Ki-67 for assessment of biopsies from patients with breast cancer in this study. The results focus on estimating the probability heatmap of tumor cells using CNN with accuracy of 98% and detecting the tumor cells using SSD with accuracy of 90%. This deep learning framework will provide an objective basis for the malignant degree of breast tumors and be beneficial to the pathologists for fast and efficiently Ki-67 scoring.
Availability-Aware Secure Application Offloading for Mobile Edge Computing

Mobile edge computing (MEC) literally pushes cloud computing to the life radius of end users. The state-of-the-art mobile edge applications (MEApps) are posing rigorous latency requirements to service providers, as well as the need of security and high availability. However, vulnerabilities exist for both cloud and MEC environments. In this dissertation, our goal is to create a secure MEC environment for hosting MEApps with high availability, and to encourage resource sharing by both users for their Customer-premises equipment (CPE) and service providers (SPs) for their MEC hosts. While there is a number of challenges to achieve the goal, we present four parts of work to address these challenges. We first investigate the security issues in offloading applications and analyze vulnerabilities by modules of an application. A model called EdgePlace is formulated as a stochastic programming problem with a heuristic algorithm to leverage affinity and anti-affinity host placement rules for higher availability and lower cost. We then present IoT-B&B, an architecture featuring resource sharing of physical CPE nodes, with the goal to leverage unused resources at the network edge and to share them with users across the network edge. At last, we propose EdgeChain, a model for making fair MEApps placement decisions for multiple SPs and a heuristic placement algorithm for MEApps across different SPs. The algorithm is intended to run by multiple service providers for consensus and the placement decisions can be recorded onto a blockchain for the fairness of the results.
The Use of Technology for Vocabulary Instruction in EFL Classrooms: Support and Challenges

Technology is believed and proven to provide support for teaching and learning in the classroom. Nevertheless, it also turns out into problems when the teachers are not ready for its use. This study aims to investigate the support technology offers to EFL teachers in their teaching practice and figure out some challenges they face when using technology for teaching vocabulary. By using semi-structured interview and classroom observation, this multiple case study revealed that technology supported the EFL teachers through several ways, such as the use of digital dictionaries, internet, and Powerpoint presentation as teaching media. In addition, some challenges which appeared when the teachers attempted to use technology in the classroom
On the Impact of the Customer Base on the Added Value through System-Oriented Service Delivery in Industrial Maintenance

Today, during service delivery, providers allocate their delivery resources such that their own delivery-dependent costs are minimal. However, during service delivery, costs arise not only for the provider, but for the customer, too. In industrial maintenance, for example, those costs arise—depending on service delivery—due to longer equipment unavailability. The concept of system-oriented service delivery aims at minimizing the total (customer and provider) delivery-dependent costs within the service system and promises a Pareto improvement over today’s practice. Hence, added value is created. However, so far, we have no understanding of the magnitude of and factors favoring high added value through system-oriented service delivery. Consequently, this work aims at ﬁlling this gap and widening knowledge on the added value through system-oriented service delivery. We present a simulation study to elaborate on the added value in dependency of the customer base constellation in an industrial maintenance illustrative scenario.
A multi-scale feature fusion target detection algorithm

For existing Faster R-CNN and single shot multibox detector (SSD) target detection algorithms, they all have the problem of low object detection accuracy under small target conditions. This paper proposes a general and effective target detection algorithm and the detection accuracy has greatly improved for smaller targets. The algorithm is divided into two parts. In the first part, in the feature extraction process, the feature map extracted by the basic feature extraction network is deconvoluted and merged with the previous layer feature map to generate Multi-scale feature maps with rich semantics and high resolution. Using proposed multi-scale feature maps to generate proposals. The second part uses the generated proposals to be sent to the Faster R-CNN network for classification and detection. Experiments show that using this algorithm for target detection can not only improve the recall of proposals, but also improve the accuracy of target detection, especially for small targets. The algorithm provides a new idea for small target detection.
Energy Efficiency of Multiple Antenna Cellular Networks Considering a Realistic Power Consumption Model

We analyze the area energy efficiency (AEE) of a cellular network employing spatial multiplexing (SM), maximal ratio transmission and transmit antenna selection (TAS) schemes. Moreover, we consider a realistic power consumption model for small base stations (BSs), which includes the power consumed by the backhaul as well as different interference attenuation levels. Our goal is to maximize the AEE by deploying the optimal number of BSs given some requirements, such as demanded network capacity, amount of interference and employed MIMO scheme. Results show that TAS performs better in terms of AEE when the interference is not fully canceled and for no interference cancellation when the demand for system capacity is lower, while SM becomes more energy efficient when the demanded capacity is higher. Additionally, when the capacity demand and the area to be covered are fixed, we show that although achieving the highest AEE, TAS also demands more small BSs than SM. The system performance in terms of AEE is shown to be strongly dependent on the amount of interference, which in turn depends on the employed interference-mitigation scheme and on the power consumption model.
Characterizing Causes for Query Answers in Databases via Database Repairs and their Computation through Repair Programs

A correspondence between database tuples as causes for query answers in databases and tuple-based repairs of inconsistent databases with respect to denial constraints has already been established. In this work, answer-set programs that specify repairs of databases are used as a basis for solving computational and reasoning problems about causes. Here, causes are also introduced at the attribute level by appealing to a both null-based and attribute-based repair semantics. The corresponding repair programs are presented, and they are used as a basis for computation and reasoning about attribute-level causes. They are extended to deal with the case of causality under integrity constraints. Several examples with the DLV system are shown.