Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effector Function of Allergens

Allergens are antigens that generate an IgE response (sensitization) in susceptible individuals. The allergenicity of an allergen can be thought of in terms of its ability to sensitize as well as its ability to cross-link IgE/IgE receptor complexes on mast cells and basophils leading to release of preformed and newly formed mediators (effector activity). The identity of the allergens responsible for sensitization may be different from those that elicit an allergic response. Effector activity is determined by (1) the amount of specific IgE (sIgE) and in some circumstances the ratio of sIgE to total IgE, (2) the number of high affinity receptors for IgE (FcεR1) on the cell surface, (3) the affinity of binding of sIgE for its epitope and, in a polyclonal response, the collective avidity, (4) the number and spatial relationships of IgE binding epitopes on the allergen and (5) the presence of IgG that can bind to allergen and either block binding of sIgE and/or activate low affinity IgG receptors that activate intracellular inhibitory pathways. This review will discuss these important immunologic and physical properties that contribute to the effector activity of allergens.
Dimensionality Reduction and Louvain Agglomerative Hierarchical Clustering for Cluster-Specified Frequent Biomarker Discovery in Single-Cell Sequencing Data

The major interest domains of single-cell RNA sequential analysis are identification of existing and novel types of cells, depiction of cells, cell fate prediction, classification of several types of tumor, and investigation of heterogeneity in different cells. Single-cell clustering plays an important role to solve the aforementioned questions of interest. Cluster identification in high dimensional single-cell sequencing data faces some challenges due to its nature. Dimensionality reduction models can solve the problem. Here, we introduce a potential cluster specified frequent biomarkers discovery framework using dimensionality reduction and hierarchical agglomerative clustering Louvain for single-cell RNA sequencing data analysis. First, we pre-filtered the features with fewer number of cells and the cells with fewer number of features. Then we created a Seurat object to store data and analysis together and used quality control metrics to discard low quality or dying cells. Afterwards we applied global-scaling normalization method “LogNormalize” for data normalization. Next, we computed cell-to-cell highly variable features from our dataset. Then, we applied a linear transformation and linear dimensionality reduction technique, Principal Component Analysis (PCA) to project high dimensional data to an optimal low-dimensional space. After identifying fifty “significant”principal components (PCs) based on strong enrichment of low p-value features, we implemented a graph-based clustering algorithm Louvain for the cell clustering of 10 top significant PCs. We applied our model to a single-cell RNA sequential dataset for a rare intestinal cell type in mice (NCBI accession ID:GSE62270, 23,630 features and 1872 samples (cells)). We obtained 10 cell clusters with a maximum modularity of 0.885 1. After detecting the cell clusters, we found 3871 cluster-specific biomarkers using an expression feature extraction statistical tool for single-cell sequencing data, Model-based Analysis of Single-cell Transcriptomics (MAST) with a log 2 FC threshold of 0.25 and a minimum feature detection of 25%. From these cluster-specific biomarkers, we found 1892 most frequent markers, i.e., overlapping biomarkers. We performed degree hub gene network analysis using Cytoscape and reported the five highest degree genes (Rps4x, Rps18, Rpl13a, Rps12 and Rpl18a). Subsequently, we performed KEGG pathway and Gene Ontology enrichment analysis of cluster markers using David 6.8 software tool. In summary, our proposed framework that integrated dimensionality reduction and agglomerative hierarchical clustering provides a robust approach to efficiently discover cluster-specific frequent biomarkers, i.e., overlapping biomarkers from single-cell RNA sequencing data.
Scaling Up Patient-Centered Psychological Treatments for Perinatal Depression in the Wake of a Global Pandemic

There is a call to action to reduce the public health burden of perinatal depression worldwide. The COVID-19 pandemic has further highlighted significant gaps in perinatal mental health care, especially among women who identify as Black, Indigenous, People of Color (BIPOC). While psychotherapeutic (cognitive, behavioral and interpersonal) interventions are endorsed for perinatal mood disorders, barriers to access and uptake contribute to inequitable access to treatment at the population level. To effectively address these barriers and increase the scalability of psychotherapy among perinatal women, we suggest four pragmatic questions to be answered from a patient-centered lens; namely, “who,” “what,” “how,” and “when. ” Promising avenues include task-sharing among mental health non-specialists, an emphasis on culturally sensitive care, web-based delivery of psychotherapy with some caveats, and a lifespan approach to perinatal mental health. Innovative research efforts are seeking to validate these approaches in diverse contexts across North America and the UK, lending optimism toward scalable and long-term solutions for equitable perinatal mental health care.
The “Connectivome Theory”: A New Model to Understand Autism Spectrum Disorders

The classical approach to autism spectrum disorders (ASD) is often limited to considering their neuro-functional aspects. However, recent scientific literature has shown that ASDs also affect many body systems and apparatuses such as the immune system, the sensory-motor system, and the gut-brain axis. The connective tissue, a common thread linking all these structures, may have a pathogenetic role in the multisystem involvement of ASD. Depending on its different anatomical sites, the connective tissue performs functions of connection and support; furthermore, it acts as a barrier between the external and internal environments, regulating the interchange between the two and performing immunological surveillance. The connective tissue shares a close relationship with the central nervous system, the musculoskeletal system and the immune system. Alterations in brain connectivity are common to various developmental disorders, including ASD, and for this reason here we put forward the hypothesis that alterations in the physiological activity of microglia could be implicated in the pathogenesis of ASD. Also, muscle hypotonia is likely to clinically correlate with an altered sensoriality and, in fact, discomfort or early muscle fatigue are often reported in ASDs. Furthermore, patients with ASD often suffer from intestinal dysfunctions, malabsorption and leaky gut syndrome, all phenomena that may be linked to reduced intestinal connectivity. In addition, at the cutaneous and subcutaneous levels, ASDs show a greater predisposition to inflammatory events due to the lack of adequate release of anti-inflammatory mediators. Alveolar-capillary dysfunctions have also been observed in ASD, most frequently interstitial inflammations, immune-mediated forms of allergic asthma, and bronchial hyper-reactivity. Therefore, in autism, altered connectivity can result in phenomena of altered sensitivity to environmental stimuli. The following interpretative model, that we define as the “connectivome theory,” considers the alterations in connective elements of common mesodermal origin located in the various organs and apparatuses and entails the evaluation and interpretation of ASDs through also highlighting somatic elements. We believe that this broader approach could be helpful for a more accurate analysis, as it is able to enrich clinical evaluation and define more multidisciplinary and personalized interventions.
New Insights in Early Detection of Anticancer Drug-Related Cardiotoxicity Using Perfusion and Metabolic Imaging

Cardio-oncology requires a good knowledge of the cardiotoxicity of anticancer drugs, their mechanisms, and their diagnosis for better management. Anthracyclines, anti-vascular endothelial growth factor (VEGF), alkylating agents, antimetabolites, anti-human epidermal growth factor receptor (HER), and receptor tyrosine kinase inhibitors (RTKi) are therapeutics whose cardiotoxicity involves several mechanisms at the cellular and subcellular levels. Current guidelines for anticancer drugs cardiotoxicity are essentially based on monitoring left ventricle ejection fraction (LVEF). However, knowledge of microvascular and metabolic dysfunction allows for better imaging assessment before overt LVEF impairment. Early detection of anticancer drug-related cardiotoxicity would therefore advance the prevention and patient care. In this review, we provide a comprehensive overview of the cardiotoxic effects of anticancer drugs and describe myocardial perfusion, metabolic, and mitochondrial function imaging approaches to detect them before over LVEF impairment.
An Exploratory Study of Physiological Linkage Among Strangers

The present study explores physiological linkage (i.e., any form of statistical interdependence between the physiological signals of interacting partners; PL) using data from 65 same-sex, same ethnicity stranger dyads. Participants completed a knot-tying task with either a cooperative or competitive framing while either talking or remaining silent. Autonomic nervous system activity was measured continuously by electrocardiograph for both individuals during the interaction. Using a recently developed R statistical package (i.e., rties), we modeled different oscillatory patterns of coordination between partner's interbeat interval (i.e., the time between consecutive heart beats) over the course of the task. Three patterns of PL emerged, characterized by differences in frequency of oscillation, phase, and damping or amplification. To address gaps in the literature, we explored (a) PL patterns as predictors of affiliation and (b) the interaction between individual differences and experimental condition as predictors of PL patterns. In contrast to prior analyses using this dataset for PL operationalized as covariation, the present analyses showed that oscillatory PL patterns did not predict affiliation, but the interaction of individual differences and condition differentially predicted PL patterns. This study represents a next step toward understanding the roles of individual differences, context, and PL among strangers.
Theoretical and Therapeutic Implications of the Spasticity-Plus Syndrome Model in Multiple Sclerosis

In patients with multiple sclerosis (MS), a typical pattern of muscle tone alteration, known as spasticity, is frequently observed in combination with other signs or symptoms such as spasms, cramps, pain, bladder dysfunction, sleep disturbances, fatigue, and tremor. Recently, the concept of spasticity-plus syndrome (SPS) has been proposed to take into account the frequent coexistence of all these complaints in patients with MS and a common pathophysiological basis for this putative new clinical entity has been proposed. Muscle tone, sleep, bladder function, and the pain pathway are controlled by cannabinoid CB1 (CB1R) and CB2 receptors (CB2R) that are particularly enriched in the brainstem. Axons with smaller diameters are particularly susceptible to conduction block and the irritative, ephaptic, consequences of demyelination and their involvement in the demyelination process caused by MS in the brainstem might underlie the various clinical manifestations of SPS. The adoption of SPS in clinical practice could be useful to improve symptomatic treatments in a significant proportion of patients with MS, possibly limiting the adverse events produced by polypharmacotherapy.
Genetically Determined Circulating Levels of Cytokines and the Risk of Rheumatoid Arthritis

Background: Accumulation of inflammatory leukocytes in articular tissues is the hallmark feature of rheumatoid arthritis (RA). Increasing evidence from observational studies has suggested that several cytokines may be involved in the development of RA. However, traditional observational studies are susceptible to bias from confounding and reverse causation; therefore, the potential causal relationships of individual cytokines with the risk of RA remain elusive. Objective: In this study, we evaluated whether genetically determined circulating levels of cytokines were associated with the risk of RA by performing Mendelian randomization (MR). Methods: We identified single nucleotide polymorphisms (SNPs) associated with circulating levels of cytokines and growth factors from a genome-wide association study (GWAS) including 8,293 participants of Finnish ancestry as instrumental variables (IVs). The association estimates of these IVs with the risk of RA were obtained from a GWAS meta-analysis including 14,361 RA cases and 43,923 controls of European ancestry. We conducted a series of MR analyses to assess the relationship between genetically determined circulating cytokines and the risk of RA, including the random-effects inverse variance-weighted, weighted-median, MR-Egger regression, and MR pleiotropy residual sum and outlier tests. For potential cytokine-RA associations supported by MR evidence, sensitivity analyses were further performed using restricted IV sets of SNPs with colocalization evidence and that excluding pleiotropic SNPs. Results: In the primary MR analysis, there was a suggestive inverse association between genetically determined circulating level of macrophage inflammatory protein-1β (MIP-1b) and the risk of RA [odds ratio (OR): 0.95, 95% confidence interval (CI) = 0.92-0.99, p = 0.016]. The effect estimates were similar in alternative MR analyses. Among SNPs used as IVs for MIP-1b, we found 92 SNPs without documented pleiotropy and three SNPs with evidence of colocalization. The association of MIP-1b with RA from sensitivity analyses using these two sets of restricted IVs remained stable. Conclusion: Our study suggests that genetically determined elevated circulating level of MIP-1b may be associated with a lower risk of RA. Further studies are warranted to determine how MIP-1b and related pathways may contribute to the development of RA.
Do Dolls Resemble Their Makers?

Many often say that people resemble their pets or that the faces of manga characters and Buddha statues resemble those of their artists. Previous studies demonstrated that participants could match dogs with their owners, suggesting that pets resemble their owners. Other studies also demonstrated that people can match personal belongings, including inanimate objects, to their owners. However, it is unknown whether people tend to make objects that resemble themselves. In this study, we examined whether people tend to make objects that resemble themselves with dolls made of cloth as stimuli. The results demonstrated that people tend to project themselves into dolls, even in the case of amateur college students. The mere exposure effect or the algorithm “self seeks like” may be at play in not only people’s selection of pets but also their making of objects.
Long-Term Cultures of Spinal Cord Interneurons

Spinal cord interneurons (SpINs) are highly diverse population of neurons that play a significant role in circuit reorganization and spontaneous recovery after spinal cord injury. Regeneration of SpIN axons across rodent spinal injuries has been demonstrated after modification of the environment and neurotrophin treatment, but development of methods to enhance the intrinsic regenerative ability of SpINs is needed. There is a lack of described in vitro models of spinal cord neurons in which to develop new regeneration treatments. For this reason, we developed a new model of mouse primary spinal cord neuronal culture in which to analyze maturation, morphology, physiology, connectivity and regeneration of identified interneurons. Isolated from E14 mice, the neurons mature over 15 days in vitro, demonstrated by expression of maturity markers, electrophysiological patch-clamp recordings, and formation of synapses. The neurons express markers of SpINs, including Tlx3, Lmx1b, Lbx1, Chx10, and Pax2. The neurons demonstrate distinct morphologies and some form perineuronal nets in long-term cultivation. Live neurons in various maturation stages were axotomized, using a 900 nm multiphoton laser and their fate was observed overnight. The percentage of axons that regenerated declined with neuronal maturity. This model of SpINs will be a valuable tool in future regenerative, developmental, and functional studies alongside existing models using cortical or hippocampal neurons.
Estimating the Collocation of Separated-Waste Containers in Demonstration Communities for Solid Waste Separation in Beijing

A method for estimating the collocation of separated-waste containers was proposed based on the conventional way of calculating waste containers.The method involved two procedures:to determine the theoretical demand of separated-waste containers;and to modify the theoretical demand of waste containers in terms of their configuration and the structure of various communities.The method was applied in Beijing to estimate the demand of separated-waste containers in six typical communities(schools,residential area,office buildings,shopping centers,government offices,and hotels) at different separation rates.The result shows that for residents area,the configuration is recyclables:kitchen waste:others= 1:1:1 in all the separation rates;for schools,office buildings,shopping centers and government offices,when the separation rate is lower than 50%,the configuration is recyclables:kitchen waste:others= 1:0:1,and when the rate is higher than 50%,the proportion is 2:1:1;for hotels,the proportion changed greatly.The collocation number increases with the separation rate in schools,office buildings,shopping centers and government offices,while the changes in residents area and hotels are small.
City of Cape Town Solar Water Heater Bylaw: Barriers to Implementation

This paper builds on the rich literature on implementation that has developed since the topic started to attract scholarly attention in the early 1970s. The richness of this literature relies on its large repertoire of findings, perspectives and policy ideas. From this resource we extracted four ideas, which have guided this study.1. We adhere to the ‘relaxed’ definition of implementation suggested by Ferman (1990) as that which happens between policy expectations and policy result. In line with this interpretation we define our study - of how a municipal government declared its expectation that a new city bylaw would be adopted, which never happened - as a case of a failed policy implementation.2. Policy implementation can be perceived as a ‘negotiated order’ (Bardach, 1977), necessitating a focus on the political processes, through which such orders are established, maintained and changed (O’Toole and Montjoy, 1984). 3. Implementation usually implies the involvement of different organisational units, and requires an exploration of inter-organisational relations and inter-institutional linkages (O’Toole and Montjoy, 1984) as well as a focus on the organisational cultures (Barrett, 2004). 4. Policy implementation may be viewed as problem-solving, necessitating a focus on organisational learning processes. This requires exploring how learning takes place – or is inhibited – within and across organisational units (Schofield, 2001; 2004).
An energy-efficient reconfigurable asymmetric modular cryptographic operation unit for RSA and ECC

RSA and ellipse curve cryptography (ECC) algorithms are widely used in authentication, data security, and access control. In this paper, we analyze the basic operation of the ECC and RSA algorithms and optimize their modular multiplication and modular inversion algorithms. We then propose a reconfigurable modular operation architecture, with a mix-memory unit and double multiply-accumulate structures, to realize our unified, asymmetric cryptosystem structure in an operational unit. Synthesized with 55-nm CMOS process, our design runs at 588 MHz and requires only 437 801 µm2 of hardware resources. Our proposed design takes 21.92 and 23.36 mW for 2048-bit RSA modular multiplication and modular inversion respectively, as well as 16.16 and 15.88 mW to complete 512-bit ECC dual-field modular multiplication and modular inversion respectively. It is more energy-efficient and flexible than existing single algorithm units. Compared with existing multiple algorithm units, our proposed method shows better performance. The operation unit is embedded in a 64-bit RISC-V processor, realizing key generation, encryption and decryption, and digital signature functions of both RSA and ECC. Our proposed design takes 0.224 and 0.153 ms for 256-bit ECC point multiplication in G(p) and G(2m) respectively, as well as 0.96 ms to complete 1024-bit RSA exponentiation, meeting the demand for high energy efficiency.
Sensitivity and Efficiency of the Frequency Shift Coefficient Based on the Damage Identification Algorithm: Modeling Uncertainty on Natural Frequencies

Health surveillance in industries is an important prospect to ensure safety and prevent sudden collapses. Vibration Based Structure Health Monitoring (VBSHM) is being used continuously for structures and machine diagnostics in industry. Changes in natural frequencies are frequently used as an input parameter for VBSHM. In this paper, the frequency shift coefficient (FSC) is used for the assessment of various numerical damaged cases. An FSC-based algorithm is employed in order to estimate the positions and severity of damages using only the natural frequencies of healthy and unknown (damaged) structures. The study focuses on cantilever beams. By considering the minimization of FSC, damage positions and severity are obtained. Artificially damaged cases are assessed by changes in its positions, the number of damages and the size of damages along with the various parts of the cantilever beam. The study is further investigated by considering the effect of uncertainty on natural frequencies (0.1%, 0.2% and 0.3%) in damaged cases, and the algorithm is used to estimate the position and severity of the damage. The outcomes and efficiency of the proposed FSC based method are evaluated in order to locate and quantify damages. The efficiency of the algorithm is demonstrated by locating and quantifying double damages in a real cantilever steel beam using vibration measurements.
Introduction au domaine de recherche : Processus de fragmentation et arbres branchants Markoviens

2 Fragmentations de partitions échangeables 2 2.1 Partitions échangeables . 2 2.1. 1 Boîtes de peinture . 3 2.2 Fragmentations échangeables homogènes . 4 2.2.1 Définitions . 4 2.2.2 Construction par un processus ponctuel . 5 2.2. 3 Représentation Poissonnienne des fragmentations . 5 2.2. 4 Arbres de fragmentation . 7
A comparative study of student experiences of ubiquitous learning via mobile devices and learner management systems at a South African university

Notwithstanding the strides technology has made vis-a-vis communication and socialising (Boyed & Ellison, 2007). WhatsApp social networking, together with the Blackboard learning management system (known as e-thutho) was used to create a ubiquitous space where students could connect with others and collaborate academically. Students created virtual platforms on both WhatsApp and Blackboard. A comparison was made using students’ experience to deduce a popular ubiquitous learning platform for the participants. 98 out of 183 questionnaires were returned. The results indicated that most students prefer the ubiquitous learning supported by WhatsApp social networking compared to learner management systems. Free access, edutainment and multitasking are among the aspects that made WhatsApp a popular platform. Keywords : Blackboard, Learner management systems, WhatsApp, Ubiquitous