Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual Activity BLEG-1 from Bacillus lehensis G1 Revealed Structural Resemblance to B3 Metallo-β-Lactamase and Glyoxalase II: An Insight into Its Enzyme Promiscuity and Evolutionary Divergence

Metallo-β-lactamases (MBLs) are class B β-lactamases from the metallo-hydrolase-like MBL-fold superfamily which act on a broad range of β-lactam antibiotics. A previous study on BLEG-1 (formerly called Bleg1_2437), a hypothetical protein from Bacillus lehensis G1, revealed sequence similarity and activity to B3 subclass MBLs, despite its evolutionary divergence from these enzymes. Its relatedness to glyoxalase II (GLXII) raises the possibility of its enzymatic promiscuity and unique structural features compared to other MBLs and GLXIIs. This present study highlights that BLEG-1 possessed both MBL and GLXII activities with similar catalytic efficiencies. Its crystal structure revealed highly similar active site configuration to YcbL and GloB GLXIIs from Salmonella enterica, and L1 B3 MBL from Stenotrophomonas maltophilia. However, different from GLXIIs, BLEG-1 has an insertion of an active-site loop, forming a binding cavity similar to B3 MBL at the N-terminal region. We propose that BLEG-1 could possibly have evolved from GLXII and adopted MBL activity through this insertion.
Effect of Water Extract of Mangosteen Pericarp on Donepezil Pharmacokinetics in Mice

The pharmacokinetic (PK) change in a drug by co-administered herbal products can alter the efficacy and toxicity. In the circumstances that herb–drug combinations have been increasingly attempted to alleviate Alzheimer’s disease (AD), the PK evaluation of herb–drug interaction (HDI) is necessary. The change in systemic exposure as well as target tissue distribution of the drug have been issued in HDIs. Recently, the memory-enhancing effects of water extract of mangosteen pericarp (WMP) has been reported, suggesting a potential for the combination of WMP and donepezil (DNP) for AD treatment. Thus, it was evaluated how WMP affects the PK change of donepezil, including systemic exposure and tissue distribution in mice after simultaneous oral administration of DNP with WMP. Firstly, co-treatment of WMP and donepezil showed a stronger inhibitory effect (by 23.0%) on the neurotoxicity induced by Aβ(25–35) in SH-SY5Y neuroblastoma cells than donepezil alone, suggesting that the combination of WMP and donepezil may be more effective in moderating neurotoxicity than donepezil alone. In PK interaction, WMP increased donepezil concentration in the brain at 4 h (by 63.6%) after administration without affecting systemic exposure of donepezil. Taken together, our results suggest that WMP might be used in combination with DNP as a therapy for AD.
Local delivery of mRNA-encoding cytokines promotes antitumor immunity and tumor eradication across multiple preclinical tumor models

Description Local immunotherapy with an mRNA mixture encoding four cytokines mobilizes a systemic antitumor response and promotes tumor eradication. Encoding antitumor immunity Cytokine-based treatments for cancer have been hindered by both off-target toxicity and difficulty in achieving local delivery. To address these challenges, Hotz et al. developed a saline-formulated mixture of four mRNAs delivered by intratumoral injection. The mRNAs encoded interleukin-12 (IL-12) single chain, interferon-α, granulocyte-macrophage colony-stimulating factor, and IL-15 sushi. The combination led to robust antitumor immune responses and tumor regression in multiple mouse models, including models with more than one tumor. Together, these data support further development of cytokine-encoding mRNAs as a treatment for cancer. Local immunotherapy ideally stimulates immune responses against tumors while avoiding toxicities associated with systemic administration. Current strategies for tumor-targeted, gene-based delivery, however, are limited by adverse effects such as off-targeting or antivector immunity. We investigated the intratumoral administration of saline-formulated messenger (m)RNA encoding four cytokines that were identified as mediators of tumor regression across different tumor models: interleukin-12 (IL-12) single chain, interferon-α (IFN-α), granulocyte-macrophage colony-stimulating factor, and IL-15 sushi. Effective antitumor activity of these cytokines relied on multiple immune cell populations and was accompanied by intratumoral IFN-γ induction, systemic antigen-specific T cell expansion, increased granzyme B+ T cell infiltration, and formation of immune memory. Antitumor activity extended beyond the treated lesions and inhibited growth of distant tumors and disseminated tumors. Combining the mRNAs with immunomodulatory antibodies enhanced antitumor responses in both injected and uninjected tumors, thus improving survival and tumor regression. Consequently, clinical testing of this cytokine-encoding mRNA mixture is now underway.
Estimating SOC and SOH of lithium battery based on nano material

Abstract Nano-carbon materials are widely used and studied in a new generation of energy storage systems. Lithium batteries are widely used in transportation, power networks, and mobile devices. This paper mainly studies the estimation methods of SOC and SOH of lithium batteries based on nano materials. The SOC state equation and output equation of the lithium battery are established by the ampere integration method, and the parameters in the system are observed to achieve the purpose of observing the charging state of the lithium battery online. Using the internal resistance and SOC of the cell model as state parameters, the nonlinear transfer of equal and covariance is handled. The working voltage was modified using the lithium battery model, and different control methods were implemented for different SOC situations. According to the experimental data, the voltage estimation error is less than 2.1%, which can meet the actual use requirements. It was found that there are different types of lithium-ion batteries, and the model obtained by training samples of lithium-ion batteries reduces the prediction accuracy when predicting other lithium-ion batteries.
CROSS-RACIAL AND INTERSECTIONAL ALLYSHIP EFFORTS AMONG FACULTY IN A PSYCHOLOGY DOCTORAL PROGRAM

The current study examined events by which four faculty members who teach in the same psychology doctoral program engaged each other in an allyship development process primarily related to race over the course of two years. The purpose of the study is to provide a model for allyship among faculty members in a psychology doctoral program. The study utilized critical incident techniques (CIT) and thematic analysis to identify and examine the formative experiences that became catalysts for intrapersonal, interpersonal, and structural changes resulting from these allyship processes. Textual evidence to identify critical incidents included e-mails, social media posts, text messages, and personal conversations from each coauthor about the process of these internal and external shifts. Recommendations for the implications of this allyship development process, as well as potential applications for other psychology doctoral programs, are discussed.
Nanoparticles in the diagnosis and treatment of coronary artery diseases under sports rehabilitation intervention

Abstract The emergence of nanotechnology provides a new method for the development and application of nanomaterials in the medical field. Nanoparticles could promote the expression of vascular endothelial growth factor (VEGF), dilate the coronary artery, improve the cardiac mechanism and reduce the recurrence rate of angina pectoris. Nanoparticles have the advantages of large specific surface area, high surface reactivity, high catalytic efficiency and strong adsorption capacity, which provide a new method for biomedical research. This paper mainly studies the application of nanoparticles in the diagnosis and treatment of coronary artery disease under the intervention of exercise rehabilitation. Then the prepared nanoparticles were added into the medium for co culture. The effect of nanoparticles on coronary cells was observed. It was found that the detection of zinc in the extracellular medium and in the cell increased with the increase of the concentration of ZnO NPs, and the differences were statistically significant (F = 13012.34, P < 0.001; F = 7033.54, P < 0.001). The results showed that the nanoparticles could promote the expression of vascular endothelial growth factor (VEGF), dilate the coronary artery, improve the cardiac mechanism and reduce the recurrence rate of angina pectoris.
Effects of an e-reader intervention on literacy, numeracy and non-verbal reasoning among adolescent girls in Zambia: evidence from a randomised controlled trial

ABSTRACT This paper presents results from a three-arm randomized controlled trial in Zambia with a sample of nearly 1200 adolescent girls enrolled in Grade 7. Selected primary schools (N=36) were randomly assigned within each of three districts to one of three arms: 1) e-readers, which girls could take home, provided within a safe space group platform plus community engagement activities; 2) safe space groups plus community engagement activities; and 3) control. The intent-to-treat estimates indicate that girls in the e-reader arm scored significantly better on two basic literacy assessments as well as non-verbal reasoning compared with girls in the control arm.
Análise de forragens por espectroscopia no infravermelho próximo, espectroscopia de emissão óptica em plasma induzido por laser e fusão de dados

Most of the reference methods for determining nutritive value and nutritional status of forage crops require specific reagents, demand several sample treatments, are timeconsuming and expensive. Herein, methods using near-infrared spectroscopy (NIRS) and laser-induced breakdown spectroscopy (LIBS) are proposed as alternatives for analysis of forages from the Brachiaria genus. This work was divided into two parts. In the first part, a portable near-infrared spectrometer is compared to a benchtop one with regards to analytical performance for determination of crude fiber (CF), neutral detergent fiber (NDF), acid detergent fiber (ADF), in vitro dry matter digestibility (IVDMD), crude protein (CP), and lignin (LG). Despite some minor differences between models for IVDMD, ADF and CP, both instruments were suitable for determining Brachiaria nutritive value properties. In the second part of the work, determination of microand macronutrients present in Brachiaria was performed by LIBS, NIRS and NIRS+LIBS data fusion. Results showed that models obtained with data fusion had better or equivalent predictive ability in comparison with models built with only NIRS or LIBS data.
Effects of Aging on the Neural Mechanisms Underlying the Recollection of Memories Encoded by Social Interactions With Persons in the Same and Different Age Groups

Memories related to ingroup members are remembered more accurately than those related to outgroup members. However, little is known about the age-dependent differences in neural mechanisms underlying the retrieval of memories shared with ingroup or outgroup members that are categorized by age-group membership. The present functional magnetic resonance imaging (fMRI) study investigated this issue. Healthy young and older adults participated in a 2-day experiment. On the first day outside fMRI, participants were presented with words by unfamiliar persons in movie clips and exchanged each word with persons belonging to the same age group (SAG) or different age group (DAG). On the second day during fMRI, participants were randomly presented with learned and new words one by one, and they judged whether each word had been encoded with either SAG or DAG members or neither. fMRI results demonstrated that an age-dependent decrease in successful retrieval activation of memories presented by DAG was identified in the anterior temporal lobe (ATL) and hippocampus, whereas with memories presented by SAG, an age-dependent decrease in activation was not found in any regions. In addition, an age-dependent decrease in functional connectivity was significant between the hippocampus/ATL and posterior superior temporal sulcus (pSTS) during the successful retrieval of memories encoded with the DAG people. The “other”-related mechanisms including the hippocampus, ATL, and pSTS with memories learned with the outgroup members could decrease in older adults, whereas with memories learned with the ingroup members, the “self”-related mechanisms could be relatively preserved in older adults.
Systemic Pharmacological Smoothened Inhibition Reduces Lung T-Cell Infiltration and Ameliorates Th2 Inflammation in a Mouse Model of Allergic Airway Disease

Allergic asthma is a common inflammatory airway disease in which Th2 immune response and inflammation are thought to be triggered by inhalation of environmental allergens. Many studies using mouse models and human tissues and genome-wide association have indicated that Sonic Hedgehog (Shh) and the Hedgehog (Hh) signaling pathway are involved in allergic asthma and that Shh is upregulated in the lung on disease induction. We used a papain-induced mouse model of allergic airway inflammation to investigate the impact of systemic pharmacological inhibition of the Hh signal transduction molecule smoothened on allergic airway disease induction and severity. Smoothened-inhibitor treatment reduced the induction of Shh, IL-4, and IL-13 in the lung and decreased serum IgE, as well as the expression of Smo, Il4, Il13, and the mucin gene Muc5ac in lung tissue. Smoothened inhibitor treatment reduced cellular infiltration of eosinophils, mast cells, basophils, and CD4+ T-cells to the lung, and eosinophils and CD4+ T-cells in the bronchoalveolar lavage. In the mediastinal lymph nodes, smoothened inhibitor treatment reduced the number of CD4+ T-cells, and the cell surface expression of Th2 markers ST2 and IL-4rα and expression of Th2 cytokines. Thus, overall pharmacological smoothened inhibition attenuated T-cell infiltration to the lung and Th2 function and reduced disease severity and inflammation in the airway.
Oridonin Prolongs the Survival of Mouse Cardiac Allografts by Attenuating the NF-κB/NLRP3 Pathway

Background Oridonin (Ori), the main bioactive ingredient of the natural anti-inflammatory herb Rabdosia rubescens, could be a covalent inhibitor of the NLRP3 inflammasome. Solid organ transplantation provides a life-saving optional therapy for patients with end-stage organ dysfunction. The long-term survival of solid organ transplantation remains restricted because of the possibility of rejection and the toxicity, infection, cardiovascular disease, and malignancy related to immunosuppressive (IS) drugs. However, the pathogenic mechanisms involved remain unclear. The ideal IS drugs to prevent allograft rejection have not been identified. Here, we investigated whether Ori could prolong the in vivo survival of completely mismatched cardiac allografts. Methods The cardiac transplantation models were conducted among three groups of mice from C57BL/6NCrSlc (B6/N) or C3H/HeNSlc (C3H) to C3H: the syngeneic and the allogeneic group, whose recipients were treated with vehicle of Ori, and the Ori treatment group, in which the recipients were transplanted hearts from MHC-I mismatched donors and treated with different dosages of Ori from post-operative day (POD) 0 to 7. Then, we investigated the effect of Ori on bone marrow-derived dendritic cell (BMDC) and allogeneic mixed lymphocyte reaction in vitro. Results Ori with 3, 10, and 15 mg/kg Ori could prolong the survival (MST = 22.8, 49.2, and 65.3 days, respectively). We found that infiltrating CD8+ T cells and macrophages were decreased, and regulatory T cells (Tregs) were expanded in allografts on POD7. The mRNA level of IL-1β and IFN-γ of allografts was downregulated. Mechanistically, Ori-treated BMDCs suppressed T-cell proliferation and IFN-γ+CD4+ T-cell differentiation, along with the expansion of Tregs and IL-10+CD4+ T cells. Ori inhibited NOD, LRR-, and pyrin domain-containing protein 3 (NLRP3) expression; attenuated NF-κB and IκBα phosphorylation in LPS-activated BMDCs; downregulated NLRP3, Caspase-1, IL-1β, IL-18, and IFN-γ; and upregulated IL-10 expression. Conclusions Our findings highlight the potential of Ori as a novel and natural IS agent to improve transplant tolerance. Ori could exert IS activity through decreasing IL-1β and IL-18 production and Th1 differentiation and proliferation and expanding Tregs via inhibiting the NF-κB/NLRP3 signaling pathway.
An Efficient Feature Fusion of Graph Convolutional Networks and Its Application for Real-Time Traffic Control Gestures Recognition

Recently, skeleton-based gesture and action recognition have emerged thanks to the progress in human pose estimation. Gesture representation using skeletal data is robust since skeletal data are invariant to the individual’s appearance. Among different approaches proposed for skeleton-based action/gesture recognition, Graph Convolutional Network (GCN) and its variations have obtained great attention thanks to its ability to capture the graph essence of the skeletal data. In this paper, we aim to design an efficient scheme using relative joints of skeleton sequences adapted in a GCN framework. Both spatial features (i.e., joint positions) and temporal ones (i.e., the velocity of joints) are combined to form the input of Attention-enhanced Adaptive GCN (AAGCN). The proposed framework deals with limitations of the original AAGCN when it works on challenging datasets with incomplete and noisy skeletal data. Extensive experiments are carried out on three datasets CMDFALL, MICA-Action3D, NTU-RGBD. Experimental results show that the proposed method achieves superior performance compared with existing methods. Moreover, to illustrate the application of the proposed method in real-time traffic control gesture recognition for autonomous vehicles, we have evaluated the proposed method on the TCG dataset. The obtained results show that the proposed method offers real-time computation capability and good recognition results. These results suggest a promising solution to deploy a real-time and robust recognition technique for gesture-based traffic control in autonomous vehicles.
A Comparison of Several Approaches for Image Recognition used in Food Recommendation System

In food recommendation systems, users can use mobile devices to capture images of the dishes they eat. The types of dishes in images will be automatically recognized and input to the recommendation system to suggest other dishes which the users likely to enjoy. Food image recognition is therefore an essential part of the food recommendation system. This used to be a hard problem in computer vision as many foods are very similar in color and texture. Thanks to the development of artificial intelligent and especially deep learning techniques, it is much easier to build a program to recognize the type of foods in the image. This paper examines several approaches, from traditional machine learning to state-of-the-art deep learning techniques for food image recognition to provide a comparison of the performance of these techniques. To this end, a new dataset of Vietnamese cuisine including 12,017 photos of 15 dishes has been built to test algorithms. Traditional machine learning techniques including Histogram of Gradient (HOG) and Scale-Invariant Feature Transform (SIFT) and state-of-the-art deep learning models including VGG16, MobileNet, ANN, Resnet18, Resnet50, Densenet121 have been used for extracting features in the food images. Logistic Regression (SF) and SoftMax (SM) classification have been used for classification using the extracted features. Based on the comparison results provided in this paper, one can choose appropriate techniques for image recognition to build a good food recommendation system.
30VNFoods: A Dataset for Vietnamese Foods Recognition

This paper introduces a large dataset of 25136 images of 30 popular Vietnamese foods. Several machine learning and deep learning image classification techniques have been applied to test the dataset and the results were compared and report. A decent accuracy of 77.54% and a high top 5-accuracy of 96.07% were achieved. The dataset and the performance comparison of state-of-the-art algorithm tested on the dataset will be useful for ones to develop new food image classification algorithms.
Trajectory Tracking of a Quadcopter with an Attached Payload Mass under External Disturbances

Unmanned Aerial Vehicles (UAVs) present the ability to carry different onboard systems, such as sensors, cameras, measurement tools. Especially under unexpected scenarios, such as the pandemic, the need for a cheap, fast and feasible solution makes the quadcopter a promising opportunity to overcome these challenges. Also, depending on the required mission, quadcopters ensures not only follow the desired trajectory but also guarantee the stability of their components. A robust controller is required to maintain the quadcopter in its initial path even under external disturbances as well as not inferring the quality of the measurement responses. In this context, the present article introduces the performance analysis of three controllers designed for a quadcopter carrying a payload under external disturbances. The results show that the second-order Sliding Mode Controller (SO-SMC) exhibits a more robust response against external disturbances and trajectory adherence in comparison to the First-Order SMC (FO-SMC) and Proportional Integral Derivative (PID).
Relation Between GCD Constraint and Full-Length Row-Multiplier QC-LDPC Codes With Girth Eight

The greatest-common-divisor (GCD) method is a general framework employing a set of simple inequalities (called GCD constraint) to guarantee girth eight for a class of <inline-formula> <tex-math notation="LaTeX">$(J,L)$ </tex-math></inline-formula> quasi-cyclic (QC) low-density parity-check (LDPC) codes. However, an important problem, i.e., whether the GCD constraint is necessary for this class of codes to have girth eight, remains open. In this letter, the question is answered affirmatively, following which a novel algorithm aiming to find the shortest codes with girth eight in such a class is proposed. Besides, a close connection is established between the GCD method and the base expansion method, which are both applicable for any <inline-formula> <tex-math notation="LaTeX">$J$ </tex-math></inline-formula> and any <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula>.