Miracle-dz/UniFAR-FTUs huggingface dataset:
β-1,2-Glucanase superfamily identified by sequential, functional, and structural analyses

β-1,2-Glucans are natural glucose polymers that play important physiological roles, including as symbiotic or pathogenic factors and in osmoregulation. Phylogenetically new glycoside hydrolase (GH) families have recently been identified from β-1,2-glucanase (SGL) sequences from bacteria (GH144 and GH186) and a fungus (GH162). In this study, we identified four phylogenetically new groups (Groups 1–4), and determined that these families, together with GH144, GH162, and GH189, a family of transglycosylase domains in cyclic β-1,2-glucan synthases, form a superfamily. Biochemical analysis of six proteins in these groups revealed that the proteins in Groups 1–3 showed hydrolytic activity specific to β-1,2-glucan. The kinetic parameters of the enzymes of Groups 1–3 were similar to GH144 and GH162 SGLs, indicating that these enzymes were SGLs. Optical rotation analysis revealed that the SGLs followed an anomer-inverting mechanism. Structural analysis and prediction of the proteins in Groups 1–4, GH144, GH162, and GH189 suggested that Groups 1–3 and GH144 had the same reaction mechanism. Nevertheless, Groups 1–3 were dispersed irregularly in the superfamily. Overall, we determined that Groups 1–3 were new GH families, GHxxx, GHyyy, and GHzzz, respectively, and proposed that this superfamily be called an SGL superfamily because of the phylogenetical, functional, and structural relationships within the superfamily.
Adult neurogenesis through glial transdifferentiation in a CNS injury paradigm

As the global population ages, the prevalence of neurodegenerative disorders is fast increasing. This neurodegeneration as well as other CNS injuries cause permanent disabilities. Thus, generation of new neurons is the rosetta stone in contemporary neuroscience. Glial cells support central nervous system (CNS) homeostasis through evolutionary conserved mechanisms. Upon damage, glial cells activate an immune and inflammatory response to clear the injury site from debris, and proliferate to restore cell number. This glial regenerative response (GRR) is mediated by the neuropil associated glia (NG) in Drosophila, equivalent to vertebrate astrocytes, oligodendrocytes (OL) and oligodendrocyte progenitor cells (OPCs). Here, we examine the contribution of NG lineages and the GRR in response to injury. The results indicate that NG exchanges identities between EG and ALG. Additionally, we found that NG cells undergo transdifferentiation to yield neurons. Moreover, this transdifferentiation increases in injury conditions. Thus, these data demonstrate that glial cells are able to generate new neurons through direct transdifferentiation. The present work makes a fundamental contribution to the CNS regeneration field and describes a new physiological mechanism to generate new neurons.
Interplay of condensation and chromatin binding underlies BRD4 targeting

Nuclear compartments form via biomolecular phase separation, mediated through multivalent properties of biomolecules concentrated within condensates. Certain compartments are associated with specific chromatin regions, including transcriptional initiation condensates, which are composed of transcription factors and transcriptional machinery, and form at acetylated regions including enhancer and promoter loci. While protein self-interactions, especially within low-complexity and intrinsically disordered regions, are known to mediate condensation, the role of substrate-binding interactions in regulating the formation and function of biomolecular condensates is under-explored. Here, utilizing live-cell experiments in parallel with coarse-grained simulations, we investigate how chromatin interaction of the transcription factor BRD4 modulates its condensate formation. We find that both kinetic and thermodynamic properties of BRD4 condensation are affected by chromatin binding: nucleation rate is sensitive to BRD4-chromatin interactions, providing an explanation for the selective formation of BRD4 condensates at acetylated chromatin regions, and thermodynamically, multivalent acetylated chromatin sites provide a platform for BRD4 clustering below the concentration required for off-chromatin condensation. This provides a molecular and physical explanation of the relationship between nuclear condensates and epigenetically modified chromatin that results in their mutual spatiotemporal regulation, suggesting that epigenetic modulation is an important mechanism by which the cell targets transcriptional condensates to specific chromatin loci.
CD81-guided heterologous EVs present heterogeneous interactions with breast cancer cells

Extracellular vesicles (EVs) are cell-secreted particles conceived as natural vehicles for intercellular communication. The intrinsic biocompatibility, stability in biofluids, and heterogeneous molecular cargo of EVs promise advancements in targeted therapy applications. However, predicting cell-targeting spectrum and cargo delivery are fundamental challenges for exploiting EVs or hybrid formulations. In this work, we combined cell-based and biochemical approaches to understand if secreted EVs show predictable EV-cell interactions and consequent cargo delivery. We exploited the tetraspanin CD81 to encode full-length recombinant proteins with a C-terminal GFP reporter encompassing or not Trastuzumab light chains targeting the HER2 receptor. These fusion proteins participated in vesicular trafficking dynamics and accumulated on secreted EVs when transiently over-expressed in HEK293T cells. Despite the presence of GFP, secreted EV populations retained a HER2 receptor-binding capacity and were used in EV-cell interaction assays. In time-frames where the global GFP spot distribution did not change between HER2-positive (SK-BR-3) or –negative (MDA-MB-231) breast cancer cell lines, the HER2 manipulation in isogenic cells remarkably affected the tropism of heterologous EVs. In this line, secreted doxorubicin-EVs, which showed improved efficacy compared to the free drug, had a reduced cell-killing activity on SK-BR-3 with a knocked-out HER2 receptor. Interestingly, the fusion protein-corresponding transcripts also present as full-length mRNAs in recombinant EVs could reach orthotopic breast tumors in JIMT-1-xenografted mice, as detected by ddPCR in tissue biopsies, improving our sensitivity in detecting bioavailable cargoes. These data show multiple mechanisms underlying EV-cell interactions and prioritize the profiling of surfaceomes for better comprehension of cell engagement and design new generations of EV-based nanovehicles.
Single-nucleus RNA sequencing reveals cellular and molecular dynamics of white and brown adipose tissue in a mouse model of type-2 diabetes

Excessive adipose tissue expansion is often linked with type-2 diabetes. Despite recent efforts mapping adipose tissue changes in obesity using single-cell omics, an understanding of cellular and gene expression changes in a model of type 2 diabetes, and the transcriptional circuitry controlling it, is still lacking. Here, we use single-nucleus RNA sequencing to analyse the remodelling of gonadal white and interscapular brown adipose tissue from female and male mice with or without diabetes. Analysis of 51,877 nuclei revealed altered phenotypes in every cell population in type 2 diabetes. This included an immunoregulatory response, and changes in extracellular matrix organisation, energy generation, and hormone stimuli. Key transcription factors were inferred as cell-specific and non-specific nodes controlling diabetes-linked phenotypes. Finally, female-to-male population heterogeneity and gene expression differences were observed. Here we provide a resource detailing how adipose tissue remodelling, and the molecular mechanisms governing it, may contribute to cardiometabolic disease.
TPPB modulates PKC activity to attenuate neuroinflammation and ameliorate experimental multiple sclerosis

Protein kinase C (PKC) plays a key role in modulating the activities of the innate immune cells of the central nervous system (CNS). A delicate balance between pro-inflammatory and regenerative activities by microglia and CNS-associated macrophages is necessary for the proper functioning of the CNS. Thus, a maladaptive activation of these CNS innate immune cells results in neurodegeneration and demyelination associated with various neurologic disorders, such as multiple sclerosis (MS) and Alzheimer’s disease. Prior studies have demonstrated that modulation of PKC activity by bryostatin-1 (bryo-1) and its analogs (bryologs) attenuates the pro-inflammatory processes by microglia/CNS macrophages and alleviates the neurologic symptoms in experimental autoimmune encephalomyelitis (EAE), an MS animal model. Here, we demonstrate that (2S,5S)-(E,E)-8-(5-(4-(trifluoromethyl)phenyl)-2,4-pentadienoylamino)benzolactam (TPPB), a structurally distinct PKC modulator, has a similar effect to bryo-1 on CNS innate immune cells both in vitro and in vivo, attenuating neuroinflammation and resulting in CNS regeneration and repair. This study identifies a new structural class of PKC modulators, which can therapeutically target CNS innate immunity as a strategy to treat neuroinflammatory and neurodegenerative disorders.
31. MIGRATION OF Ci TO C8 VOLATILE ORGANIC COMPOUNDS IN SEDIMENTS FROM THE DEEP SEA DRILLING PROJECT, LEG 75, HOLE 530A

The distribution of C, to C% hydrocarbons in sediment samples from DSDP Leg 75, Hole 53OA, indicates that significant amounts of methane and ethane have migrated from organic-rich to organic-lean shales in close proximity. Most compounds larger than ethane are not migrating out of black shales, where they occur in high concentrations. These results lead to a general model for assessing migration. In addition, three shale types are identified on the basis of organic carbon and pyrolysis products and patterns.
In situ and remotely sensed horizontal winds and temperature intercomparisons obtained using integrated sounding systems during TOGA COARE

The Coupled Ocean-Atmosphere Response Experiment (COARE) of the Tropical Ocean and Global Atmosphere (TOGA) program has generated a uniquely large data set of colocated wind profiler and radiosonde sounding observations. During the Intensive Observing Period (IOP), Nov. '92 through Feb. '93, there were over 2000 radiosondes launched from within tens of meters of wind profilers at six sites. This initial study shows good agreement between the wind and temperature measurements made by the wind profilers and those made from the radiosondes. However, the intercomparison also identified a number of shortcomings in the radiosonde and profiler measurements. Some of these errors have been corrected, while the cause of others remains unidentified and a topic for future investigation.
Estimation of Weather Noise in Coupled Ocean–Atmosphere Systems Using Initialized Simulations

AbstractThis study presents a new method to estimate atmospheric weather noise from coupled models, which is based on initialized simulations with a CGCM. In this method, the weather noise is estimated by removing the signal part, as determined from the coupled ensemble mean simulations. The weather noise estimated from coupled models is compared with that estimated from uncoupled AGCM simulations. The model used in this study is CFSv2. The initialized simulations start from each April during 1982–2009 paired with four members and extend for 6 months. To make a clear comparison between weather noise in coupled and uncoupled simulations, a set of uncoupled AGCM (the atmospheric component of CFSv2) simulations are conducted, which are forced by the daily mean SSTs from the above initialized CGCM simulations. The comparison indicates that, over the Asia–Pacific monsoon region where the local air–sea coupling is important, the noise variances are generally reduced as a result of air–sea coupling, as are the t.
Project-Based Learning in the curricular unit ICT in Professional Contexts - perceptions of Sociocultural Animation students

This article reflects on the teaching of Information and Communication Technologies in Professional Contexts with Sociocultural Animation students. This curricular unit (CU) aimed to develop digital citizenship and stimulate students' personal and professional growth through active and projectbased learning strategies. The objectives included analysing software, integrating technology into the profession, planning interventions, using software and online tools, creating multimedia presentations, organizing digital portfolios, and understanding distance learning platforms. The CU was lectured by three professors and the study presented in this article involved 26 students that were enrolled in the 2nd semester of 2022/2023. Student-centred teaching strategies, such as Project-Based Learning, were adopted to prioritize learning and hands-on, real- world experiences of project planning and management. The activities focused on situated learning and service to the community, allowing students to implement their projects with target audiences identified by them. The results of a questionnaire applied at the end of the semester indicated positive perceptions in relation to the three areas in which it focused, and which relate to learning, motivation, and performance. In conclusion, the project-based learning strategy in higher education has been shown to have a favourable impact on students' digital skills and others that are transferable to their professions, including project management, communication, collaboration, autonomy, and self-regulation. The study suggests the potential benefits of projectbased learning can be applicable to other areas and recommends expanding research to explore this approach more comprehensively.
Reflections on a technology curricular unit in initial teacher training: the students’ perspective

This paper aims at presenting the results of a study focused on a Curricular Unit of the Elementary Education degree course at a Higher Education School, where active methodologies and the use of ICT are the core of the unit. The authors' goal was to understand whether the objectives of the curricular unit were attained. Thus, the students were asked to reflect on the development of the unit and their reflections were analysed, using a qualitative methodology. The results point to the students' acceptance of the methodologies and tools used, valuing the content covered and its importance in their academic path.
Performance Evaluation of Denial of Service Attack Detection in Cloud Computing Environments

One of the most widely used technologies today, both by developers and end users, is cloud networking. Despite the widespread use of cloud networks, security in the cloud continues to be a crucial research problem and a hotly debated subject. One or more attackers use several compromised nodes to flood a specified target during a denial of service (DoS) assault in the cloud, which renders services unavailable. It is possible to discover the attack characteristics or frequent trends of such denial of service attacks using classification algorithms. In order to identify the Denial of Service attacks, feature selection and classification utilizing deep learning approaches have been applied in this study. This study proposes a novel method for identifying DoS attacks that makes use of the expertise of an authority on the domain. In addition, deep learning algorithm such as Gated Recurrent Units is proposed in this research for Detecting DoS Attacks. In this algorithms, the final classification is carried out and validated on NSL-KDD dataset. The suggested approach is tested on a cloud-based experimental setup, and found that it performed better at detecting DoS attacks than the current security classification methods.
Development of an Instrumented Glove for the Characterization of Human Wrist Tremor

It is common for human beings to present some diseases and disorders as they age, due to neuromusculoskeletal disorders. One of the problems that can appear is the human tremor. There are numerous strategies for tremor attenuation. Among the most common methods, the use of medications, local surgical procedures, electrical stimulation and the use of active orthoses stand out. In this context, robotic rehabilitation is of interest to science more and more. Among the methods for inhibiting tremor, active orthoses are the most efficient and non-invasive means. With that in mind, and also in terms of their quality of life, studies on orthoses to suppress tremor were carried out. Due to the complexity of the device, the present study aims to develop and evaluate an instrumented glove, properly constructed to characterize human wrist tremor in patients affected with such dysfunction. To this end, the basic operating principle of the active orthosis is presented, seeking to highlight more specifically the instrumented glove with its motion and muscle actuation sensors.
An Empirical Model of Soft Bellows Actuator

Soft actuators are used for automation in the food industry and medical applications due to their compliance and flexibility. However, modeling such actuators has been a challenging task owing to its softness and continuous nature. In this study, we focus on soft bellows actuator and propose a simple empirical model for estimating its output force. The model includes the parameters of geometry and material, which can be used to facilitate the actuator design and control. To validate the proposed empirical model, we first conducted finite element (FE) simulations of the bellows actuator with different design parameters and then performed experiments on actual bellows actuator which was fabricated using a 3D printer and TPU material. Both simulation and experimental results show that the proposed empirical model can accurately estimate the output force of soft bellows actuator. The model is expected to effectively facilitate the design and control of bellows actuator.
Facial Expression Recognition Algorithm Based on Swin Transformer

Expressions are an important non-verbal behavior for humans to convey their emotional information, reflecting their inner activities. As attention in Transformers has excellent feature representation capabilities, it is catching more interests in computer vision field. Swin Transformer is a successful implementation of transformer in computer vision field. This paper proposes a Swin Transformer-based emotion recognition algorithm called Swin Emotion. The algorithm utilizes Swin Transformer as the backbone network and fuses the varying-sized feature vectors extracted from multiple stages, taking into account both the detailed features of the image and its macroscopic characteristics while preserving the integrity of the modeling process. The multi-scale feature fusion network simultaneously uses both low-level and high-level features of images, thereby improving the model's perception ability for objects of different scales and its capture ability of detail and contextual information. Experimental results show that the model demonstrates better understanding of emotions and achieves outstanding performance on all tasks. With an accuracy of up to 99.38% in peak expressions on the CK+ dataset, Swin Emotion holds broad application prospects in the field of emotion recognition.
Security and Privacy Preservation Method Based on Data Disturbance for Collaborative Edge Computing for Social-Internet-of-Things (S-IoT)

Socia1 Internet of Things (SIoT) is new paradigm that integrate human social with physical Internet of Things (IoT) systems, social IoT is ray of hope in providing ubiquitous connectivity among users. The collaborative edge computing for SIoT is significant because it ensures human social features and connections among IoT devices and users. But it is formidable to perform CEC for social IoT due to user privacy, data security and network heterogeneity and so on. The problem of computing and storage in IoT devices is solved by Collaborative edge computing (CEC) with deep learning (DL). To prevent privacy breach and security threats at edge network and edge devices in SIoT system. This research work discusses the data protection method based on data disturbance approach. To ensure correctness of model adversarial training viewpoint is introduced. The proposed method is capable of predicting contextual filtering words in adversarial text examples, and adaptively determine word replacement order. The proposed method BESAW, a BERT Based Simulated Annealing Word algorithm is used. BESAW compare with five existing methods includes TextFooler, BAE, BERT-Attack, PWWS, and PSO in experimental analysis.
Determinants of Youth Financial Inclusion in MENA Countries: Account Holding versus Fintech Use

Why youths in Middle East and North Africa (MENA) countries lack financial inclusion before and during the pandemic and what are the determinants of their financial inclusion? We design three pooled households’ samples including youths aged 15-34 from Egypt, Jordan and Tunisia for 2014, 2017 and 2021. Two probit regressions address financial inclusion regarding account holding at banks or other financial institutions and digital services (fintech) they provide. We highlight five main results. Before the pandemic (i) the financial inclusion of young entrepreneurs is affected by their (female) gender, (middle) income, (low) education level and country policy. During the pandemic, (ii) women became more financially included; (iii) there was no age gap for fintech; and (iv) despite the fact that digital services have improved, they remain unsuitable for poorly educated youth. (v) Gender has no effect on the financial inclusion of young employees before and during the pandemic.
STEM Career Aspirations Among Portuguese Secondary School Students

The main objective of this study was to investigate the Science, Technology, Engineering and Mathematics (STEM) career interests of secondary school students in Portugal. Data were collected from a sample of 190 twelfth grade students, consisting of 106 females and 84 males, using the STEM Career Interest Survey. The results showed that interest in careers in engineering tended to be lower than interest in mathematics, science, and technology among secondary school students. The study also found a gender gap in students' interest in science, engineering, and technology careers. Female students were less interested in engineering and technology-related careers than their male counterparts, but more interested in science-related careers. These findings can inform education policy makers, curriculum developers, teachers, and researchers about the importance of STEM education in nurturing and cultivating students' interest in STEM fields.