Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploration of the GARDskin applicability domain: Indirectly acting haptens, hydrophobic substances and UVCBs.

Hazard assessments of skin sensitizers are increasingly being performed using new approach methodologies (NAMs), with several in chemico, in vitro and most recently also defined approaches (DAs) being accepted for regulatory use. However, keeping track of potential limitations of each method in order to define applicability domains remains a crucial component to ensure adequate predictivity as well as facilitating the appropriate selection of method(s) for each hazard assessment task. The objective of this report is to share test results generated with the GARD™skin assay on chemicals that have traditionally been considered as difficult to test in some of the conventional in vitro and in chemico OECD Test Guidelines for skin sensitization. Such compounds may include, for example, indirectly acting haptens, hydrophobic substances, and substances of unknown variable composition or biological substances (UVCBs). Based on the results of this study, the sensitivity for prediction of skin sensitizing hazard of indirectly acting haptens was 92.4% and 87.5%, when compared with LLNA (n=25) and human data (n=8), respectively. Similarly, the sensitivity for prediction of skin sensitizing hazard of hydrophobic substances was 85.1% and 100%, when compared with LLNA (n=24) and human data (n=9), respectively. Lastly, a case study involving assessment of a set of hydrophobic UVCBs (n=7) resulted in a sensitivity of 100, as compared to available reference data. Thus, it was concluded that these data provide support for the inclusion of such chemistries in the GARD™skin applicability domain, without an increased risk of false negative classifications.
Effect of Strain and Stiffness on Matrix Remodelling Genes

Cells embedded within tissues respond to mechanical, chemical and biological signals. However, the detail of how mechanical forces are transmitted to cells is poorly understood at present and represents a key missing link in Tissue Engineering. As cells attach to the fibrils in fibroblast-seeded 3D collagen scaffolds they generate contractile forces to levels, which depend on cell type, attachment, density, growth factors and matrix stiffness. The aim of this study was to use external applied strain to increase matrix stiffness in collagen constructs. Embedded resident cells (from three different sites) were then subjected to specific mechanical loading regimes in scaffolds of increasing stiffness and matrix remodelling genes quantified as markers of mechanoregulatory cellular response. Mechanical responses of cells were also quantified as contraction profiles over time. Our findings indicated that collagen got stiffer with application of high strains and visco-elastic properties resulted in minimal transfer of applied loads as recorded by movement of indwelling markers. The mechanical and molecular responses of three different cell lineages: human dermal (HDF), neonatal foreskin fibroblasts (HNFF) and human bone marrow stem (hBMSC) cells seeded in constructs of increased stiffness was tested. Results indicated that in HNFFs contraction was predominantly attachment-dependent while in HDFs it was predominantly stiffness-dependent. hBMSCs showed differential response to serum levels. Molecular responses in progressively stiffer constructs investigated were MMP-2, MMP-3, MMP-9, TIMP- 2,COL-l,COL-3 and IGF-1. Different cell types expressed specific variations in gene regulation. The effect of specific mechanical loading (slow and fast ramp) regimes on regulation of matrix remodelling genes also showed a lineage dependent response. The major impact of this project has been the identification of a strong co-relation between substrate stiffness, mechanical loading and regulation of key ECM turnover genes. This knowledge is crucial to successful tissue engineering outcomes. The differential lineage dependent response is a key finding and will have to be tailored depending on cell source and specific outcomes desired. regimes on regulation of matrix remodelling genes also showed a lineage dependent response. The major impact of this project has been the identification of a strong co-relation between substrate stiffness, mechanical loading and regulation of key ECM turnover genes. This knowledge is crucial to successful tissue engineering outcomes. The differential lineage dependent response is a key finding and will have to be tailored depending on cell source and specific outcomes desired.
Remote Respiratory and Cardiac Motion Patterns Separation With 4D Imaging Radars

Radar-based noncontact physiological signals monitoring is meaningful for daily health monitoring, post-disaster rescue, and public security. This paper focuses on the theoretical and experimental study of noncontact respiratory and cardiac motion signals separation by remote sensing using a four-dimensional (4D) imaging radar. To adaptively separate respiratory and cardiac motion patterns, we propose a variational mode separation (VMS) algorithm. VMS is established on optimizing a variational problem to separate different modes. It minimizes the energy overlap of the heartbeat and respiration signals as well as their harmonics with an equality constraint. Both simulation and real scene data results show that the proposed VMS algorithm is suitable for separating the weaker cardiac motion pattern from the strong respiratory motion pattern, restraining the influence of respiration harmonics on the heartbeat component. Furthermore, we have implemented continuous remote monitoring of respiratory rate (RR) and heart rate (HR) by employing the proposed method in a real scene. The results validate the consistency with the reference respiration belt and electrocardiogram (ECG). The root mean square errors (RMSEs) of RR and HR for the remote measurement are 0.13 breaths per minute (brpm) and 1.7 beats per minute (bpm), respectively.
Development of a strategic framework for information technology implementation in Libyan airports

This study aims to establish the key factors that will encourage the Libyan government, through the Libyan Civil Aviation Authority, to expand their activities to upgrade Libyan airports’ technology in general and its IT departments in particular. A number of objectives were formulated in order to achieve this aim and two case study organisations were chosen to represent Libyan airports as a whole. Modern day IT implementation poses numerous difficulties which, when surmounted, brings a lot of benefits and can help speed up processes as well as prevent or mitigate the effects of risks. However, organisations feel overwhelmed by the complexity of IT management and they sometimes fail to assess the costs of associated risks. Therefore, they are usually reluctant to invest in IT solutions that may be untested or unsuitable to their environments. As a result, IT implementation system processes can be misaligned. This thesis examines the benefits of IT strategic alignment in IT implementation to promote the use of IT and to realise the value thereof. This research has identified the alignment of IT and the current barriers to the special needs of this area. Application of IT in the aviation industry in general, and in airports in particular, should recognise and deal with some of the factors, both expected and the unexpected, to implement a successful programme for IT. Therefore, this research proposes methods and conceptual models based on modern IT frameworks that will help IT implementation in organisations to align IT initiatives with the objectives of IT systems. The researcher used qualitative, quantitative and modelling techniques during the various stages of the research. IT facilitates inter-airport relations and the transfer of responsibility through the coordination of IT implementation systems in all airport departments by aligning IT initiatives with implementation units and IT organisations that work with government committees. The implementation of standardised and advanced IT systems will cause management organisations to appreciate high level standards in IT initiatives for the benefit of their management, staff and their customers (passengers).
Local Learning Enabled Iterative Linear Quadratic Regulator for Constrained Trajectory Planning

Trajectory planning is one of the indispensable and critical components in robotics and autonomous systems. As an efficient indirect method to deal with the nonlinear system dynamics in trajectory planning tasks over the unconstrained state and control space, the iterative linear quadratic regulator (iLQR) has demonstrated noteworthy outcomes. In this article, a local-learning-enabled constrained iLQR algorithm is herein presented for trajectory planning based on hybrid dynamic optimization and machine learning. Rather importantly, this algorithm attains the key advantage of circumventing the requirement of system identification, and the trajectory planning task is achieved with a simultaneous refinement of the optimal policy and the neural network system in an iterative framework. The neural network can be designed to represent the local system model with a simple architecture, and thus it leads to a sample-efficient training pipeline. In addition, in this learning paradigm, the constraints of the general form that are typically encountered in trajectory planning tasks are preserved. Several illustrative examples on trajectory planning are scheduled as part of the test itinerary to demonstrate the effectiveness and significance of this work.
The long non-coding RNA T cell leukemia homeobox 1 neighbor enhances signal transducer and activator of transcription 5A phosphorylation to promote colon cancer cell invasion, migration, and metastasis

ABSTRACT Colon cancer is among the most prevalent gastrointestinal tumor types. The long noncoding RNA (lncRNA) T cell leukemia homeobox 1 neighbor (TLX1NB) is up-regulated in colorectal cancer (CRC). However, the functional role of this lncRNA in colon cancer remains unknown. In our study, we investigated the clinical significance of TLX1NB in colon cancer through bioinformatics analysis and explored its role in migration, invasion and metastasis of colon cancer cell with a series of experiments. Firstly, TLX1NB was up-regulated in colon cancer tissues and increased TLX1NB expression was significantly associated with advanced N stages. In wound healing assays and transwell assays, TLX1NB overexpression promoted HCT116 cell migration and invasion while TLX1NB knockdown inhibited SW620 cell migration and invasion. In vivo, TLX1NB knockdown suppressed pulmonary metastasis of SW620 cell and vimentin expression but increased E-cadherin expression. Then, TLX1NB overexpression enhanced signal transducer and activator of transcription 5A (STAT5A) phosphorylation and TLX1NB knockdown suppressed STAT5A phosphorylation. Moreover, the inhibition of STAT5A phosphorylation reversed TLX1NB overexpression-associated increase in HCT116 cell migratory and invasive activity. In conclusion, TLX1NB enhances STAT5A phosphorylation to promote colon cancer cell invasion, migration, and metastasis. Graphical abstract
Rare case of leptomeningeal small lymphocytic lymphoma with TP53 mutation detected by deep next-generation sequencing

Abstract Involvement of the central nervous system (CNS) is an exceedingly rare presentation of chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL), with no consensus on the optimal therapy. Here we describe a 71-year-old man with a skull-base leptomeningeal mass consistent with SLL on biopsy. Malignant cells were observed in the cerebrospinal fluid (CSF), but not in the peripheral blood, bone marrow, or other extramedullary sites. Molecular analysis of the patient’s disease by next generation sequencing (NGS) detected no pathogenic mutations in 111 genes, with the exception of two low allele frequency variants identified during deep NGS analysis of TP53. The patient was treated with six cycles of high-dose methotrexate and systemic/intrathecal rituximab followed by venetoclax monotherapy, with complete resolution of CSF disease and radiographic decrease in size of the skull base lesion.
Research and design innovations for mobile user experience

Research and Design Innovations for Mobile User Experience offers innovative design solutions for mobile human-computer interfaces, addressing both challenges and opportunities in the field to pragmatically improve the accessibility of mobile technologies. Through cutting-edge empirical studies and investigative cases, this reference book will enable designers, developers, managers, and experts of mobile computer interfaces with the most up-to-date tools and techniques for providing their users with an outstanding mobile experience.
Impact of dietary Lactobacillus supplementation on intramuscular fat deposition and meat quality of Sunit sheep.

To investigate the impacts of dietary Lactobacillus supplementation on meat quality such as edible quality and nutritional value of Sunit sheep, a 90-day feeding experiment (Lactobacillus dietary group, R group; non-Lactobacillus dietary group, C group) using twelve 3-month-old Sunit sheep was conducted. The deposition of intramuscular fat (IMF) was increased (p < .05) while the share force and cooking loss were decreased (p < .05) in the R group compared with the C group. The proportions of seven kinds of fatty acids (FAs) have changed significantly (p < .05), especially with higher functional FAs and lower trans-FA in the R group. Metabonomics analysis showed that the metabolites and pathway-related lipid syntheses, such as carnitine cycle, tricarboxylic acid cycle, and glycerophosphocholine metabolic pathway, have significantly changed in the R group. The Lactobacillus dietary supplements impacted the variation of IMF deposition and FAs composition by altering the lipid metabolism pathways of Sunit sheep and then changed the edible quality and nutritional value. PRACTICAL APPLICATIONS: It is well known that the intramuscular fat (IMF) and fatty acids composition in livestock is positively correlated with various aspects of meat quality such as edible quality and nutritional value, which are related to consumer preference. The present study analyzed the effects of Lactobacillus supplement on the intramuscular fat deposition and meat quality of Sunit sheep, which resulted in the increase of IMF, and the differences of fatty acids composition, especially the functional fatty acids. It was explored the mechanism of Lactobacillus affect the variation of lipid metabolism pathways and key metabolites in sheep, which suggested that altering the feeding regimen could improve the meat quality of agri-animals.
On-line Coupling of Aptamer Affinity Solid-Phase Extraction and Immobilized Enzyme Microreactor Capillary Electrophoresis-Mass Spectrometry for the Sensitive Targeted Bottom-Up Analysis of Protein Biomarkers

In this paper, we present a fully integrated valve-free method for the sensitive targeted bottom-up analysis of proteins through on-line aptamer affinity solid-phase extraction and immobilized enzyme microreactor capillary electrophoresis-mass spectrometry (AA-SPE-IMER-CE-MS). The method was developed analyzing α-synuclein (α-syn), which is a protein biomarker related to different neurodegenerative disorders, including Parkinson’s disease. Under optimized conditions, on-line purification and preconcentration of α-syn, enzymatic digestion, electrophoretic separation, and identification of the tryptic peptides by mass spectrometry was achieved in less than 35 min. The limit of detection was 0.02 μg mL–1 of digested protein (66.7% of coverage, i.e., 8 out of 12 expected tryptic peptides were detected). This value was 125 and 10 times lower than for independent on-line digestion by IMER-CE-MS (2.5 μg mL–1) and on-line preconcentration by AA-SPE-CE-MS (0.2 μg mL–1). The repeatability of AA-SPE-IMER-CE-MS was adequate (at 0.5 μg mL–1,% RSD ranged from 3.7 to 16.9% for peak areas and 3.5 to 7.7% for migration times of the tryptic peptides), and the modified capillary could be reused up to 10 analyses with optimum performance, similarly to IMER-CE-MS. The method was subsequently applied to the analysis of endogenous α-syn from red blood cell lysates. Ten α-syn tryptic peptides were detected (83.3% of coverage), enabling the characterization and localization of post-translational modifications of blood α-syn (i.e., N-terminal acetylation).
Can Feelings “Feel” Wrong? Similarities Between Counter-Normative Emotion Reports and Perceptual Errors

In popular belief, emotions are regarded as deeply subjective and thus as lacking truth value. Is this reflected at the behavioral or brain level? This work compared counter-normative emotion reports with perceptual-decision errors. Participants (university students; N = 29, 16, 40, and 60 in Experiments 1–4, respectively) were given trials comprising two tasks and were asked to (a) report their pleasant or unpleasant feelings in response to emotion-invoking pictures (emotion report) and (b) indicate the gender of faces (perceptual decision). Focusing on classical error markers, we found that the results of both tasks indicated (a) post-error slowing, (b) speed/accuracy trade-offs, (c) a heavier right tail of the reaction time distribution for errors or counter-normative responses relative to correct or normative responses, and (d) inconclusive evidence for error-related negativity in electroencephalograms. These results suggest that at both the behavioral and the brain levels, the experience of reporting counter-normative emotions is remarkably similar to that accompanying perceptual-decision errors.
Changes in Electroencephalography Alpha Associated With Childhood Neglect and Adolescent Alcohol Use

The present pilot study is interested in the relationship between childhood neglect, brain function, and alcohol use in adolescence. The goal is to guide future prevention and intervention efforts related to alcohol use following childhood neglect. This pilot study comprised 53 adolescents (12-14 years at baseline) recruited from the Department of Social Services (DSS). Self- and DSS-reported neglect, electroencephalography (EEG) alpha power, and alcohol use behaviors were measured over 1 year. Higher DSS neglect severity in year 1 was related to lower self-efficacy to alcohol use temptation in year 2. Lower EEG alpha power in the parietal region in year 1 was linked to lower self-efficacy to the temptation of alcohol use in year 2. This pilot project has value for using tools, such as EEG, in child maltreatment and alcohol use studies, including with underrepresented adolescents, to better understand brain-related mechanisms in home-based research.
Race/Ethnicity and Reference Equations for Spirometry

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FMGNN: A Method to Predict Compound-Protein Interaction With Pharmacophore Features and Physicochemical Properties of Amino Acids

Identifying interactions between compounds and proteins is an essential task in drug discovery. To recommend compounds as new drug candidates, applying the computational approaches has a lower cost than conducting the wet-lab experiments. Machine learning-based methods, especially deep learning-based methods, have advantages in learning complex feature interactions between compounds and proteins. However, deep learning models will over-generalize and lead to the problem of predicting less relevant compound-protein pairs when the compound-protein feature interactions are high-dimensional sparse. This problem can be overcome by learning both low-order and high-order feature interactions. In this paper, we propose a novel hybrid model with Factorization Machines and Graph Neural Network called FMGNN to extract the low-order and high-order features, respectively. Then, we design a compound-protein interactions (CPIs) prediction method with pharmacophore features of compound and physicochemical properties of amino acids. The pharmacophore features can ensure that the prediction results much more fit the expectation of biological experiment and the physicochemical properties of amino acids are loaded into the embedding layer to improve the convergence speed and accuracy of protein feature learning. The experimental results on several datasets, especially on an imbalanced large-scale dataset, showed that our proposed method outperforms other existing methods for CPI prediction. The western blot experiment results on wogonin and its candidate target proteins also showed that our proposed method is effective and accurate for finding target proteins. The computer program of implementing the model FMGNN is available at https://github.com/tcygxu2021/FMGNN.